Real Time Streamflow Forecasting and Reservoir Operation System for Krishna and Bhima River Basins in Maharashtra (RTSF & ROS) Inception Report

Transcription

1 Government of Maharashtra Water Resources Department Hydrology Project II IBRD Loan No: 4749-IN Real Time Streamflow Forecasting and Reservoir Operation System for Krishna and Bhima River Basins in Maharashtra (RTSF & ROS) Inception Report December 2011 DHI (India) Water & Environment Pvt. Ltd.

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3 Real Time Streamflow Forecasting and Reservoir Operation System for Krishna and Bhima River Basins in Maharashtra (RTSF & ROS) Inception Report December 2011 DHI (India) Water & Environment Pvt Ltd 3 rd Floor, NSIC Bhawan, Okhla Industrial Estate New Delhi India Tel: Fax: gnp@dhigroup.com Client Client s representative Chief Engineer, Planning & Hydrology Superintending Engineer Project Real Time Streamflow Forecasting and Reservoir Operation System for Krishna and Bhima River Basins in Maharashtra (RTSF & ROS) Authors Guna Paudyal Finn Hansen Dhananjay Pandit Project No Date: December 2011 Approved by Hans G. Enggrob 01 Inception report (based on comments from Client & other stakeholders) GNP HGE Revision Description By Checked Approved Date Key words Real Time, Streamflow, Flood, Forecasting, Reservoir Operation, Forecast Models, Hydrology, Hydraulics, River Basin, Capacity Building Classification Open Internal Proprietary Distribution Client: DHI: PDF file No of copies 15

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5 Krishna & Bhima River Basins RTSF&ROS List of Acronyms and Abbreviations BSD CWC DA DAS DEM DSS FMO GIS GMRBA GMS GoI GoM GPRS GSM HD HIS HP-II IBRD IMD KRBA MERI MKRBA MODIS MoWR NIH NCMRWF NRSA NWP QA QAP QC QPF RMC ROS RR Basin Simulation Division Central Water Commission Data Assimilation Data Acquisition System Digital Elevation Model Decision Support System Flood meteorological Office (of IMD) Geographic Information System Godavari Marathwada River Basin Agency Geostationary Meteorological Satellite Government of India Government of Maharashtra General Packet Radio Service Global System for Mobile Communications Hydrodynamic Hydrological Information system Hydrology Project Phase II International Bank for Reconstruction and Development Indian Meteorological Department Konkan River Basin Agency Maharashtra Engineering Research Institute Maharashtra Krishna River Basin Agency Moderate Resolution Imaging Spectro-radiometer Ministry of Water Resources National Institute of Hydrology, Roorkee National Centre for Medium Range Weather Forecasting National Remote Sensing Organisation Numerical Weather Prediction Quality Assurance Quality Assurance Plan Quality Control Quantitative Precipitation Forecast Regional Meteorological Centre (of IMD) Reservoir Operation System Rainfall-Runoff Inception Report i

6 RTSF&ROS Krishna & Bhima River Basins RS RTDAS RTDSS RTSF SAR SRTM TKRBA VRBA WALMI WB WRD Remote Sensing Real Time Data Acquisition System Real Time Decision Support System Real Time Streamflow Forecasting Synthetic Aperture Radar Shuttle Radar Topography Mission Tapi Khandesh River Basin Agency Vidarbha River Basin Agency Water and Land Management Institute World Bank Water Resources Department ii Inception Report

7 Krishna & Bhima River Basins RTSF&ROS Table of Contents List of Acronyms and Abbreviations... i EXECUTIVE SUMMARY...VI 1 INTRODUCTION Background Krishna and Bhima River Basins Krishna River Basin Bhima River Basin Flood Prone Area PROJECT OBJECTIVES, OUTPUTS & ACTIVITIES Objectives Outputs Activities / Tasks PROGRESS OF INCEPTION PHASE ACTIVITIES Summary of Progress made during the Inception phase Description of Progress Task 1.1 Review current forecasting & reservoir operation Task 1.2 Identify the needs of WRD and stakeholders Task 1.3 Identify and assess sources of weather forecasts and flow forecasting and reservoir operation tools Task-1.4 Review available data and, the RTDAS network and identify critical gaps and recommend strategies to fill these Task-1.5 Define options and scenarios for optimal multiple reservoir operation Task 1.6 Review institutional capacity of WRD, and recommend improvements for human resource development, and facilities for effective functioning METHODOLOGY AND APPROACH Knowledge Base and Management System Design and Development of the Knowledge Base Design and Development of the Knowledge Base Management System Streamflow and Forecasting Models Role of Mathematical Models Flow Forecasting Development of Simulation Models Boundary Conditions Integration with Real-time Data Inception Report iii

8 RTSF&ROS Krishna & Bhima River Basins 4.3 Reservoir Operation Guidance System Implementation of Existing Operation Rules Optimisation of Existing Operation Rules Operational Guidance System Communication and Information Management System Communication Strategy and protocols Web Portal The Alert Module CAPACITY BUILDING Introduction Water Resources Department (WRD) Planning & Hydrology The Basin Simulation Division (BSD) Training Needs assessment Institutional Development Plan Proposed Setup and Functions of BSD Operational Control Room Capacity Building and Training Plan during the Project On-the-job training Training Courses Workshops International technical training cum study visits International Study Tour PROJECT IMPLEMENTATION PLAN Activity Schedule Project Management Project Organisation Quality Assurance Quality Management at DHI Quality Assurance Plan Requirements from WRD Data Collection and Processing RTDAS iv Inception Report

9 Krishna & Bhima River Basins RTSF&ROS Coordination with other stakeholders Dissemination of River Flow and Flood Forecasts Establish Operational Control Room and RT Data Centre Workshops and Training Engagement of BSD staff with the Consultant Project Monitoring REFERENCES..93 APPENDIX A.1: REVIEW OF PAST FLOODS...95 APPENDIX A.2: TYPICAL FLOOD INFORMATION FORM THE FLOOD CONTROL CELL, WRD PUNE.97 APPENDIX A.3: KOYANA RESERVOIR OPERATION SYSTEM 105 APPENDIX A.4: GENERAL DESCRIPTION OF RESERVOIR OPERATION..109 APPENDIX B: INCEPTION WORKSHOP 117 APPENDIX C: LIST OF DAMS 123 APPENDIX D: LIST OF MEETINGS AND CONSULTATIONS.125 APPENDIX E: DATABASE DOCUMENTATION.128 Inception Report v

10 RTSF&ROS Krishna & Bhima River Basins EXECUTIVE SUMMARY The Project Consultancy services for the implementation of streamflow forecasting and reservoir operations for Krishna and Bhima River Basins in Maharashtra commenced with the opening of the project office in Pune on the auspicious day of Ganesh Chaturthi on 17 th August DHI (India) Water and Environment are the Consultants assigned by the Water Resources Department of Government of Maharasthra, India. The assignment is scheduled to be completed in 18 months with an extended technical support period of two years. The Inception Report presents the progress made during the first three months planned as Inception Phase in which all the activities under Task 1 as stipulated in the contract have been carried out. Based on review and needs assessment, a capacity building program has been developed. The capacity building is an integrated approach comprising on-the-job training, formal training, international technical training and study visits and international study tour. The Draft Inception Report was submitted on November 11, 2011 for review and comments by WRD and other stakeholders. Useful suggestions and comments were received from WRD and from other stakeholders. This final version incorporates the comments and suggestions. As part of stakeholder consultation, an Inception Workshop was organised on December 7, 2011 to further consolidate the needs assessment process. The Workshop was well attended and was very participatory in nature. The Proceedings of the Workshop are reported separately. However key recommendations are presented in Appendix B, which are considered in this final version of the Inception Report. The Report also presents an updated approach and methodology, which includes knowledge base and knowledge management, the modelling system, the forecasting system and the reservoir operation guidance. Three types of simulation models are being developed for the two basins: Rainfall-Runoff Model (NAM), River basin water resources management model (MIKEBASIN), and hydrodynamic model (MIKE11). The simulation models are the basic engines of real time streamflow forecasting, flood forecasting and reservoir operation in the basins. vi Inception Report

11 Krishna & Bhima River Basins RTSF&ROS The project implementation plan is prepared in line with the milestones specified in the TOR and the provisions in the Contract. A few critical paths have been identified, which are related to the availability of data in time. These are availability of historical data of the basins, survey of new cross sections in the Krishna and Bhima rivers and their tributaries, and the completion of the Real Time Data Acquisition System (RTDAS). Inception Report vii

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13 Krishna & Bhima River Basins RTSF&ROS 1 INTRODUCTION 1.1 Background The geographical area of Maharashtra state is 308,000 Km 2. Major river basins in the state are the Krishna river with its major tributary as Bhima, Godavari, Tapi and the West flowing rivers of Konkan strip (Figure 1.1). Maharashtra receives rainfall from both south-west and north-east monsoon. The state has very highly variable rainfall ranging from 6000 mm in upper catchments to 400 mm in shadow areas of lower catchments. Majority of rainfall mainly occurs in a four months period between June to September with the number of rainy days varying between 40 to 100. The state experiences flash floods particularly in Western Ghats including Krishna and Upper Bhima basins. For instance, Sangli, Satara and Kolhapur districts in Krishna Basin and Pune and Solapur districts in Bhima basin experienced severe flood several times during recent decade. Figure 1-1 River Basins of Maharashtra The Water Resources Department (WRD) of Government of Maharashtra (GoM) is entrusted with the surface water resources planning, development and management. A large number of major, medium and minor water resources development projects (reservoirs and weirs) have been constructed in Maharashtra. Though, the reservoirs in Maharashtra are not specifically provided with flood cushion, they have moderated flood peaks to considerable extent by proper reservoir operations. The reservoirs are multipurpose including hydropower, irrigation, domestic and industrial uses and are operated with rigid schedules as single entities based on the historical hydro-meteorological data and experience gained. These methods are often not adequate for establishing optimal operational decisions, especially where integrated operation of multiple reservoirs for flood management is contemplated. In addition, manual data observation and transmission results in a considerable time lag, between data observed in field and its communication to decision making level which sometime leaves little time, for flood forecasts. The Ministry of Water Resources (MoWR), Government of India (GoI) has initiated Hydrology Project Phase II (HP-II), which is a follow-on to the concluded Hydrology Project-I (HP-I: ). During HP-I, the Hydrological Information Inception Report 1

14 RTSF&ROS Krishna & Bhima River Basins System (HIS) was developed for the entire state of Maharashtra and the data is monitored manually 1-2 times a day. Under HP-II project, real time decision support system inflow forecasting in Bhakra Beas system and Decision Support System (DSS) for water resources planning and management are being developed. The Upper Bhima basin has been selected as a pilot basin for latter one i.e. DSS (planning). In addition, Government of Maharashtra has proposed to upgrade the existing HIS with real time data acquisition system (RTDAS) for Krishna and Bhima basins. Simultaneously, it is proposed to develop a real time streamflow forecasting (RTSF) and reservoir operation system (ROS) in Krishna and Bhima river basins to manage the floods and operate reservoirs optimally for multiple uses. It is envisaged that the system would facilitate reservoir operators to act on time and prepare stakeholders for the floods. The forecast of river flow and mapping of flood zone will help in taking the decisions such as evacuation of the likely affecting areas well in advance. In addition, the reservoir operation system would facilitate the optimization of the storages for ensuring flood cushion and improving agricultural productivity. 1.2 Krishna and Bhima River Basins The Krishna River Basin, of which Bhīma is a major tributary, covers an area of 258,000 sq.km (nearly 8% of India) in three large states Karnataka, Maharashtra, Andhra Pradesh. Maharashtra covers 69,967 km 2 of Bhima & Krishna basin area (Figure 1.2). As Bhima joins Krishna in Karnataka, these two rivers basins are generally treated as separate basins. This part is one of the fastest, economically growing regions and hence there is an ever growing competition for water among different sectors viz. agriculture, industries and domestic users. There are 46 reservoirs in Bhima & Krishna out of which 30 are Major Projects and 16 are Medium Projects Krishna River Basin The river Krishna which is one of the major rivers of Maharashtra covering an area of 21,114 km 2 in Maharashtra is 282 km long. Krishna originates from Mahabaleshwar in Satara district and flows through Satara, Sangli and Kolhapur Districts. It mainly flows from north to south. Three of its main tributaries namely, Koyna, Warna, Panchaganga flow from west to east and the fourth main tributary Yerala flows from east to west. There are 19 reservoirs in Krishna basin, out of which 10 are major projects viz. Dhom, Kanher, Urmodi, Tarali, Koyna, Warna, Radhanagari, Dudhganga, Tembhu Barrage and Satpewadi Barrage. The 9 medium projects are Dhom Balkawadi, Mahu, Uttarmand, Morna(Gureghar), Wang, Kadvi, Kasari, Kumbhi and Dhamni. Figure 1.3 shows locations of reservoirs in the Krishna Basin. 2 Inception Report

15 Krishna & Bhima River Basins RTSF&ROS Figure 1-2 The Krishna and Bhima River Basins in Maharashtra Figure 1-3 Locations of Reservoirs in the Krishna & Bhima River Basins Inception Report 3

16 RTSF&ROS Krishna & Bhima River Basins Bhima River Basin The Bhima River rises from Bhimashankar near Karjat on the western side of the Western Ghats known as Sahyadri hill ranges at an altitude of about 945 m above the sea level. The Bhima River flows in the southeast direction for 745 km covering the states of Maharashtra and Karnataka. The Bhima River drains an area of 48,853 km2 in Maharashtra. The length of Bhima in Maharashtra is 451 km and it joins Krishna on the Karnataka Andhra Pradesh boundary near Kudlu in Raichur District. In the course of the journey it meets many small rivers. The major tributaries of this river around Pune are Kundali, Ghod, Bhama, Indrayani, Mula, Mutha and Pawana. The Indrayani, Mula, Mutha and Pawana flow through Pune and Pimpri Chinchwad city. The major tributaries of Bhima in Solapur are Chandani, Kamini, Moshi, Bori, Sina, Man, Bhogwati and Nira. The Bhima meets the Nira River in Narsinghpur in Malshiras taluka in Solapur district. The last 298 km of its course is in Karnataka where it merges with the Krishna River. The banks of the Bhima River are densely populated and form a fertile agricultural land. The river also causes floods due to heavy rainfall it receives during the monsoon. Bhima basin has 27 reservoirs out of which 20 are major projects and 7 are medium projects. The major projects are Pimpalgaon Joga, Manikdoh, Yedgaon, Wadaj, Dimbe, Chaskaman, Bhama Askheda, Pawana, Mulshi, Temghar, Warasgaon, Panshet, Khadakwasla, Ghod, Ujjani, Sina-Kolegaon, Gunjawani, Bhatghar, Vir and Nira Deoghar. The medium projects are Chilewadi, Kalmodi, Andhra, Wadiwale, Kasar Sai, Sina (Nimgaon) and Nazare. Figure 1.3 shows the locations of reservoirs in the Bhima Basin Flood Prone Area Some areas of the Krishna and Bhima basins suffer from floods. Figure 1.4 shows reaches of Krishna and Bhima and their tributaries which are flooded. The years 2005 and 2006 observed heavy floods in the basins. Due to heavy rains in the catchment of Krishna, Warna and, Panchganga rivers created flood havocs in Sangli, Satara and Kolhapur districts in July Sangli city is one of the most flood prone areas in the Krishna basin. Pandharpur city on Bhima basin is another flood prone area. Some areas in Pune city gets flooded from the Mutha and Mula rivers. 4 Inception Report

17 Krishna & Bhima River Basins RTSF&ROS Figure 1-4 Flood Prone Reaches (in red) in Krishna and Bhima Basins Inception Report 5

18 RTSF&ROS Krishna & Bhima River Basins 2 PROJECT OBJECTIVES, OUTPUTS & ACTIVITIES 2.1 Objectives The objective of this consultancy is to equip the Water Resources Department of Government of Maharashtra with a web-based real time streamflow monitoring and forecasting system and reservoir operation system for flood management in the Krishna and Bhima basins in Maharashtra. The system will be used to optimize releases from reservoirs for multiple uses throughout the year, in addition to providing a system to better manage floods. This will build upon the existing hydrological information system (HIS) and eventually on a real time data acquisition system (RTDAS) telemetry network that is being developed in parallel. 2.2 Outputs The principal outputs in relation to the forecasting and operation guidance system will be: (1) A hydrological Knowledge Base comprising: Historical data from the existing Hydrologic Information System Historical and real time satellite images Real time weather forecasts Real Time Data Acquisition System Knowledge Management System for ease of access, display and maintenance of the knowledge base (2) A Forecasting System for reservoir, river and flood plain levels and flows efficiently utilising weather forecasts, real time satellite data and the RTDAS (3) A Guidance System for integrated optimal reservoir operations for flood and water resources management year round (4) A web based interactive Communication System allowing access to the Knowledge Base, and the Forecasting and Guidance Systems for WRD offices and stakeholders: View historical, real time and forecast data and information in a range of formats GIS maps, graphs, schematics, reports, etc Disseminate the forecasts and reservoir operation guidance in a range of formats tailored to the needs of the users, and over various media including the web and mobile GPRS 6 Inception Report

19 Krishna & Bhima River Basins RTSF&ROS (5) A comprehensive Capacity Building programme for WRD comprising formal training courses, on-the-job training, workshops, study tours and hotline support 2.3 Activities / Tasks The following main tasks are envisaged to be carried out. Each task has associated sub-tasks. Task 1 Main task Review Current Forecasting and Operational Capabilities Sub-tasks / activities (1.1)Review current forecasting, reservoir operation, warning dissemination and emergency response capabilities in the Krishna and Bhima Basins (1.2)Identify the needs of WRD and stakeholders for effective water resources and flood management in Krishna and Bhima Basins (1.3)Identify and assess sources of weather forecasts, and flow forecasting and reservoir operation tools (1.4)Review available hydro-climatological data and data management systems, the RTDAS network, real time satellite data, and identify critical gaps and recommend strategies to fill these (1.5)Define options and scenarios for optimal multiple reservoir operation (1.6)Review institutional capacity of WRD, and recommend improvements for human resource development, and facilities for effective functioning Task 2 Knowledge Base Development (2.1) Functional specifications for the WRD Krishna- Bhima knowledge base (2.2) Design and develop database management system (2.3) Develop knowledge base (2.4) Develop knowledge management system Task 3 Real-Time Streamflow / Flood Forecasting Model (3.1)Based on the modelling framework set out in Task 1, the modelling system will be established and calibrated against historical and current data (3.2)Through analysis of the model results, critical reaches will be identified for forecasts, as well as the need for additional real time monitoring (3.3)The modelling system will be integrated with weather Inception Report 7

20 RTSF&ROS Krishna & Bhima River Basins forecasts, real time satellite data, and the RTDAS (3.4)Data assimilation will be applied to ensure the maximum information is extracted from the real time data to ensure the best possible forecasts (3.5)Prepare flood mapping, for critical historical events, and for flood forecasts Task 4 Reservoir Operational Guidance System Task 5 Communication and Information Management Systems Task 6 Capacity Building and (4.1)Extend the simulation models with optimisation for water resources and flood management (4.2)Establish the operational guidance system for multiple multi-purpose reservoir operation (5.1)Develop the Communication Strategy and Protocol supporting information channels and dissemination (5.2)Design and prepare specifications for the Operational Control Room, and support procurement arrangements (5.3)Develop the Web Portal to provide access and disseminate information from the Knowledge Base and the RTSF-ROS (6.1)Engage WRD staff in the development of the Streamflow and Reservoir Operation Guidance System (6.2)Preparation of an overall training programme for WRD staff, comprising training at Indian institutes, and formal courses given by DHI s specialists (6.3)Facilitation of Workshops organised by WRD (6.4)Organisation of international study tours for senior managers of WRD (6.5)Preparation of operational user and reference manuals, online context dependent help, documented demonstration cases, training materials (6.6)Technical support, with further training courses and hotline support (6.7)Preparation of a strategy for long term sustainability and enhancement of the developed system 8 Inception Report

21 Krishna & Bhima River Basins RTSF&ROS 3 PROGRESS OF INCEPTION PHASE ACTIVITIES 3.1 Summary of Progress made during the Inception phase The Tor stipulates the tasks shown in Table 3.1 to be carried out during the three months Inception Phase (17 August 16 November). A summary of progress made against the tasks is also presented below. Table 3.1 Summary of tasks and progress made during the Inception Phase Task No. Stipulated Tasks 1.1 Review current forecasting, reservoir operation, warning dissemination and emergency response capabilities in the Krishna and Bhima Basins completed Progress 1.2 Identify the needs of WRD and stakeholders for effective water resources and flood management in Krishna and Bhima Basins 1.3 Identify and assess sources of weather forecasts, and flow forecasting and reservoir operation tools 1.4 Review available hydro-climatological data and data management systems, the RTDAS network, real time satellite data, and identify critical gaps and recommend strategies to fill these 1.5 Define options and scenarios for optimal multiple reservoir operation 1.6 Review institutional capacity of WRD, and recommend improvements for human resource development, and facilities for effective functioning completed completed completed. Some of the possible scenarios defined, but the actual scenarios and strategies will be defined during testing and implementation of the system with feedback from stakeholders. completed. 3.2 Description of Progress Task 1.1 Review current forecasting & reservoir operation A review of the current forecasting, reservoir operation and warning dissemination and emergency response has been carried. Most of the review was reported in Monthly Progress Reoprt-1 (September 2011). Inception Report 9

22 RTSF&ROS Krishna & Bhima River Basins The review is presented in five sections. Supplementary details are provided in Appendix A.1 to A Review of Past Floods, forecasting system and Studies The Government of Maharashtra Water Resources Department constituted a Technical Committee on January 4, 2007 to study the 2005 and 2006 floods of Maharashtra and to recommend measures of efficient reservoir operation and flood forecasting. The report of the technical committee is an extensive one encompassing review of floods, causes, review of hydrological data and reservoir operation systems. On the forecasting systems, the Technical Committee commented that the gauge-gauge Correlation method of flood forecasting was inadequate. The Technical Committee identified a need of establishing mathematical models for the river basins in order to provide effective tools for emergency flood management, integrated reservoir operations, use of basin simulation models and real time flood forecasting. On July19, 2011 floods submerged about 30 cars near Bund Garden in Pune due to sudden releases from the Khadakwasala Dam. This was reported in INDIATV (20 July 2011). Floods were also reported in Kolhapur during the same week. 10 Inception Report

23 Krishna & Bhima River Basins RTSF&ROS Notable floods in the recent past were also observed in 1995 and It is reported that about 35 villages in the district of Satara are affected by floods every year from Koyna river. The extent of flooding could be so severe that these villages remain cut off from the rest of the area for about a week. In Solapur district, major flood events were reported during 16-17, August During this event the discharge at Daund was 3.45 lakh cusecs with a flood level of m. The corresponding release from Ujjani dam was 2.45 lakh cusecs. The discharge at Narsingpur was 2.68 lakh cusecs and at Pandharpur the discharge was 2.94 lakh cusecs with a flood level of m. During July, 1994, the discharge at Daund was 2.54 lakh cusecs at a flood level of m, while the release from Ujjani dam was 2.17 lakh cusecs. In the same period the discharge at Narsingpur was 2.38 lakh cusecs and at Pandharpur it was 3.09 lakh cusecs at a flood level of m. Another major event occurred at Daund during August, 1997, with a discharge of 2.75 lakh cusecs (flood level 507.8m). The release from Ujjani dam was 2.75 lakh cusecs. In the same period, the discharge at Narsingpur was 2.70 lakh cusecs at a level of m and at Pandharpur the discharge was lakh cusecs at the water level of m. The most recent flood events occurred during 3-5 August 2005 and 8-10 August 2006, in which the discharge at Daund was 2.43 lakh cusecs (water level 507.5m) & 2.54 lakh cusecs (water level m), respectively. The corresponding releases from Ujjani dam were 2.25 and 2.75 lakh cusecs. The discharges at Narsingpur were 2.56 lakh cusecs (water level m) & 3.19 lakh cusecs (water level m). At Pandharpur the discharges were 3.33 lakh cusecs (water level m) & 3.24 lakh cusecs (water level m), respectively during the two events. These discharge values need to be validated and appropriate corrections will be applied based on last 5 years data at Pandharpur river GD station. Figure 3-1 Records of Flood events downstream of Ujjani Dam (Source: Ujjani Control Room) Inception Report 11

24 RTSF&ROS Krishna & Bhima River Basins 2. Review of Activities of the Flood Control Cell, WRD Pune The consultant together with the Executive Engineer, Basin Simulation Division visited the Flood Control Cell of Water Resources Department in Sinchan Bhawan to review the present set up of flood monitoring and forecasting. For Bhima and Krishna basins, the Krishna Basin Flood Control Cell is established, which collects the reservoir levels, rainfall and spillway discharge for each of the reservoirs twice a day (0700 hrs and 1700 hrs) in normal circumstances and hourly in flood like situation. The data is received by any available means viz. Cell Phones, Wireless, Land Line etc. The Flood Control Cell is under the Executive Engineer, Khadakwasla Irrigation Division. During monsoon (from June to October) three Section Engineers along with four wireless operators manage the cell 24X7 in three shifts. During non-monsoon periods, the wireless operators collect the data. In the control room, the staff from the Police Department are also deployed round the clock to communicate the flood situation to respective police commands in the districts. The collected data is entered into computers and every day at 0800 hrs. Reports are generated and send to the Chief Engineer, Water Resources Pune. The Chief Engineer (SP), Water Resources, Pune and the Superintendenting Engineer, Pune Irrigation Circle. The copy is also sent by Fax to Mantranlaya (Ministry of Water Resources) in Mumbai Flood Unit, Minister of Water Resources, Divisional Commissioner, Pune, SE (CADA), Solapur and Baramati Hostel (Members of Parliament: On demand). All the information on spillway discharges are given to the Police Department. The updated data is also published daily on the website ( In case of high releases from dams, the information is provided to concerned corporations/municipal authorizes as well as to the Police for evacuation from low lying areas. The Format of reporting as per the website is given in Appendix A Reservoir Operation During the monsoon period, reservoir operation usually consists of release of water for various uses, considering actual demands and storages available. The release schedules are routinely prepared by the concerned authorities. Since the day to day routine procedure is known to the officials it requires less attention in general for release programmers in fair season. Flood forecasting operations and reservoir operation are physically carried out during rainy season. It is generally seen that during the remaining period (normal period), allied and supporting activities related to reservoir operation/flood forecasting do not get proper attention. 12 Inception Report

25 Krishna & Bhima River Basins RTSF&ROS Maharashtra State Water Policy (July 2003) states that (para 8.0 Flood control and management) an adequate flood cushion shall be provided in water storage projects wherever feasible to facilitate better flood management. The flood control space is provided in the reservoir for storing flood water temporarily in order to reduce peak discharge and to minimize flooding on downstream locations. The official website of WRD ( published daily dam storages during 1 st June to 15 th October and weekly in the remaining period. Khadakwasla, Panshet, Warasgaon & Temghar Reservoirs A review of the current inflow forecasting and reservoir operation has been made based on a visit to the Khadakwasla, Panshet and Warasgaon reservoir system (Figures 3-2 and 3-3). Figure 3-2 The Khadakwasla reservoir system Figure 3-3 An Schematic diagram of the Khadakwasla reservoir operation system Inception Report 13

26 RTSF&ROS Krishna & Bhima River Basins The visit to these dams on 15 th Oct, 2011 and discussions with the Engineers managing these dams revealed that the inflow forecasting mainly done with water balance method based on the information rainfall data in catchment area, change in reservoir level, elevation-area-capacity curve, discharge through spillway and canal/power outlet. Figure 3-4 A Manual data entry system The reservoir operators use the approved reservoir schedules for each dam. During rainy season, when the reservoir levels are increasing and rainfall in the catchment also continues, the in-charge of reservoir decides when and how much to release the water from reservoir with the help of guide curves and experience. The information on reservoir releases is sent to Krishna Flood Control Cell in Pune, which compiles data from all the reservoir releases and issues the warnings/reports. Based on the travel time to the flood prone areas in Pune, around 2 hours of lead time is given before releasing the water from reservoir. The reservoir operators opined that the operation of the combined reservoir system would result into an efficient water flood management if information on catchment rainfall, upstream inflows and downstream flood impacts are available in real time. Koyna Reservoir The operation schedule for Koyna reservoir was reviewed based on earlier reports and on the Technical Committee Report of July A site visit and discussion with Koyna reservoir authorities is planned in the near future. Presently the field officers are estimating the inflows into Koyna reservoir by past experience and established rules based on historical events, like an inch of rain at Mahabaleshwar will result in an inflow of so many cusecs into the Koyna reservoir after six hours. The reservoir operation schedule for Koyna reservoir is described in Appendix A.3. is of Figure 3-5 Koyna Reservoir and other projects 14 Inception Report

27 Krishna & Bhima River Basins RTSF&ROS All the reservoir operation systems in Maharashtra are guided by the Dam Safety Manual (Appendix A.4). Ujjani Reservoir A team of consultants consisting of the Team Leader, Deputy Team Leader and two international modelling experts visited the Ujjani Dam on November 20, 2011 to review the reservoir operation system. Detailed discussions were held with the Engineer in-charge of reservoir operation and other staff at site. The Ujajani Dam office keeps a good record of operation and monitors the reservoir water level in real time. Ujjani Reservoir is one of the most important reservoirs in Bhima basin in Maharashtra. The reserboir is named as Yeshwant Sagar and has the submergence area of 290 km 2. The gross storage capacity of the reservoir is 3320 MCM, out of which MCM is live storage and MCM is dead storage. Ujjani project has 2,05,277 ha of command area, out of which, left bank canal irrigates 1,33,332 ha and the right bank irrigates 71,945 ha. The project also has 34,883 ha of area irrigated under lift irrigation schemes. There are 41 radial gates with discharge capacity of 15,717 cumecs. The power generation capacity is 12 MW. The digital water level recorder indicates the level and storage in the reservoir. In addition, the digital water recorders are installed at canal head indicating the level and discharge in the canal. Inception Report 15

28 RTSF&ROS Krishna & Bhima River Basins The information of all 22 reservoirs (including Ujjani) in Bhima basin on live storage, releases from reservoirs through spillway and power outlets, rainfall, and cumulative rainfall are collected daily in the prescribed format by available communication mechanism like telephone, cell phones, SMS, wireless, fax etc. In the flood like situation, this information is collected on hourly basis. The inflow into the reservoir is calculated from the releases from Ghod, Khadakwasla, Chaskaman, Bhma-Askhed, Andhra, Wadiwale, Pawana, Mulshi and Visapur. At Ujjani, the decision to how much and when to release the water depends on current level in Ujjani, discharges from u/s and rainfall. An estimate of travel time from upstream to downstream at the dam site is also used to decide on when to operate the gates. The releases from Ujjani and Gunjavane, Bhatghar, Nira-Deodhar and Vir are used for flood warnings at Pandharpur. In case of emergency, the flood warnings are send to office of Collector, Disaster management Cell, Police, Municipalities etc. Many flood events in Solapur district, as described in Section 3.2.1, have been associated with releases from the Ujjani Dam. The officials responsible for operation use their experience and judgement. The officials expressed a strong need to have a real time information system and a reservoir operation guide to deal with emergencies as well as to improve the management of the water resources system. They also expressed their desire to be involved in discussions related to development of reservoir operation strategies during the implementation of the RTSF & ROS project. 4. Flood forecasting by CWC and IMD The flood forecasting work of entire Krishna basin is being carried out by Central water Commission (CWC) from its Lower Krishna Division, Hyderabad. However, Kurundwad in Kolhapur district on river Krishna is the station in Maharashtra where forecasts are being issued by CWC. CWC uses the correlation method for flood forecasting. Karad is the upstream base station on river Krishna for flood forecasting at Kurundwad. The contribution of tributary Warna is taken at Samdoli station. Gauge and Discharge correlation diagrams have been developed with due travel time based on historical data. In addition the Rainfall and Quantitative Precipitation Forecast (QPF) for the intermediate catchment is also used to update the forecast. A forecast of 24 hour lead time is calculated and issued to user agencies through telephone/wireless or special messenger. 16 Inception Report

29 Krishna & Bhima River Basins RTSF&ROS Rainfall warnings and QPF for the Krishna basin is provided by the Flood Meteorological Office (FMO) of Indian Meteorological Department (IMD), Hyderabad or IMD has set up ten Flood Meteorological Offices (FMO) located over flood prone areas of the country. FMOs provide necessary meteorological support to the Central Flood Forecasting Divisions of Central Water Commission. These FMOs function under the technical control of Hydromet Division, IMD, Delhi while their administrative control rests with the Regional Meteorological Centers (RMC). During the flood season, FMOs issue daily hydro-meteorological bulletins to Flood Forecasting Divisions of CWC on operational basis. It contains the following items: i. Quantitative Precipitation Forecast(QPF) in different ranges which are 1 10 mm, 11 25mm, 26 50mm, mm and > 100mm. ii. Prevailing synoptic weather situation in the region iii. Basin wise areal rainfall. iv. Station wise significant rainfall during past 24 hours( > 50mm). v. Heavy rainfall warning in the next 48 hours, if any. 5. Warning dissemination and emergency management The State of Maharashtra has developed a well functioning disaster management system with a coordinated administrative system from the state level through divisions, districts and down to village levels ( Flood warning dissemination and emergency management systems are part of the overall disaster preparedness and management system being practiced by the districts and other authorities. District Collector, Pune A review meeting was held on November 8, 2011 with Resident Deputy Collector, Shri Anil Pawar, who also holds charge of District Disaster Management Officer for Pune district. The meeting was also attended by Shri Ganesh Sonune, UDRR Project, UNDP, Pune Municipal Corporation. It was observed that a well functioning control room is established at the district collector s office in Pune. The control rooms monitors all disasters, especially floods during the monsoon season and disseminates information to all concerned in an efficient way. Based on the Disaster Management Act of 2005 and Standard Operating Procedures SOP), each district has prepared a District Disaster Management Plan. Flood prone areas up to village level are identified based on past disasters and well trained human resources are mobilised for preparedness as well as for emergency management. A resource inventory (equipment, human, etc.) is prepared and updated for each village. For example, out of 14 talukas of Pune district 3 talukas are identified as flood vulnerable which include 89 villages. Disaster Management Cells (DMC) at local levels are well prepared to tackle any emergency situation including floods. In the flood prone villages, the DMC has trained at least ten local volunteers, and have a computerised inventory of all the necessary equipment, machinery, boats, Life jackets etc. It has also included the names and contacts of Government officials, Members of village/municipality Disaster Management Committee and Groups, rescue team members like swimmers, health workers, Inception Report 17

30 RTSF&ROS Krishna & Bhima River Basins anganwadi workers etc. The Pune District Disaster management System is illustrated Figure 3.6. Figure 3-6 Pune District Disaster Management System Similar disaster management systems are developed for all the districts under Revenues Division of Pune. The related information is available in ; ; ; The Standard Operating Procedure (SOP) Booklet is available in Marathi and is in circulation to all concerned. The village level/ Municipality level Disaster Management Plan is updated every year. Figure 3.7 shows some of the disaster management related documents including SOP, Disaster Management Act 2005 and Disaster Management Plan. 18 Inception Report

31 Krishna & Bhima River Basins RTSF&ROS Figure 3-7 Disaster Management related documents The Disaster Management Plan prepared for Village/Municipality level has two parts. Part-1 contains information on 1. Information about Village / Municipality 2. Hazardous, Vulnerable and Risk Areas in the Village / Municipality and Map showing Disaster Prone area 3. Response and Improvement Plan 4. Early Warning and Preparedness Plan 5. Mitigation, Relief and rehabilitation Plan Part-2 of the Plan includes 1. Telephone numbers of Government Officials (State/District/Taluk/Control Room) 2. List of Members of Disaster Management Committee, Groups, Swimmers etc. 3. Mitigation Measures for Hazardous, Vulnerable and Risk Areas 4. List of Emergency and Important Services 5. List of NGOs, Addresses, Telephone Numbers, Specialization 6. Inventory of available resources and equipment. It was learnt that some major flood prone rivers are marked with blue lines (for 25 year flood) and red lines (for 100 year floods) by WRD. The current flood information received from WRD, however, is inadequate in terms of timing and magnitude of floods related to geographic areas. The disaster management officers expressed their need to have a more meaningful flood forecast with early warning message on when and where a certain level/depth of flood will occur. The lead time of such warning could be between a couple of hours for urban areas and a few days for rural areas. A longer (3-10 days) warning will always be useful in flood preparedness, but they realise that accuracy of such warnings is limited due to fast responding catchments in the Krishna and Bhima river basins. The officers met expressed their desire to cooperate with WRD in utilising the flood forecasts and warnings to be prepared by the RTSF&ROS project. District Collector, Sangli A meeting-cum-workshop was organised at the Office of the District Collector, Sangli on November 23, 2011 in which Additional Collector, Shri D.S. Patil and Resident Deputy Collector, Shri Uttam Patil gave their valuable suggestions from disaster management Inception Report 19

32 RTSF&ROS Krishna & Bhima River Basins point of view. Executive Engineer, BSD, Pune presented the overview of RTSF & ROS project. Officers from various line departments attended the meeting. Resident Deputy Collector informed that they presently receive hourly update from WRD during flood like situation at Sangli where Krishna and Warna rivers meet. During the floods similar to those of 2005 and 2006, the Sangli town always getting affected, with standing water in many areas. Apart from tackling flood situation, the district administrators also expressed that the RTSF & ROS project should provide information related to water resources planning and management in drought prone areas like Atpadi and Kavathe Mahankal tahsils of the district. The District Disaster Management Cell is also established here like Pune and functioning under the Resident District Collector as Disaster Management Officer Task 1.2 Identify the needs of WRD and stakeholders The integrated and multi-sectorial approach to water resources planning, development and management on sustainable basis is very important due to various stakeholders involved. In addition to WRD and its various circles and divisions, the list of stakeholders is as follows. 1. Reservoir Managers / Operators 2. District Administrations / Disaster Management Officials 3. Flood affected people 4. Municipal Corporations (Domestic and Industrial Supply) 5. Farmers / Water User Associations 6. Electricity Boards. 7. Public Works Department (PWD) 8. Agricultural Department 9. Health Department 10. Maharashtra Jeevan Pradhikaran Reservoir Managers / Operators All dams in Maharashtra State are planned for the conservation purposes for utilization of the stored water for irrigation, industrial use, water supply and /or power generation. Provision of specific flood absorption storage is not considered in any of the reservoirs up till now. They are not planned as flood control reservoirs. Dams can moderate the floods through a proper reservoir operation aided by reliable flood forecasting system. Reservoir operation has to be regulated in such a way that all the floods impinging upon the reservoir can be safely routed without involving any risk to the structure itself or any damage to the property downstream. Both these requirements will have to be given due weightage in reservoir operation. The RTSF & ROS, hence will become quite useful for the Reservoir Authorities. During the visit to the Khadakwasla reservoir system the officials responsible for operating were interviewed to assess their needs. Although the reservoir operation rules and procedures are well documented, the operators have expressed difficulty in taking decisions at times high inflows generated due to sudden and heavy rainfall 20 Inception Report

33 Krishna & Bhima River Basins RTSF&ROS in the catchment. They expressed that operation of the reservoirs would be much more effective if an inflow forecast is available in time. It was noted that, in case of the Khadakwasla reservoir the travel time of upstream flood is only about two hours. They also expressed that the reservoir operation should also consider downstream flood situation when large releases have to be made in short time. A reliable inflow forecast would also be useful in effectively using the emergency spillways during very high floods. Flood Control Cell For Bhima and Krishna basins, the Krishna Basin Flood Control Cell is established, which collects the reservoir levels, rainfall, spillway discharge for each of the reservoirs twice a day (0700 Hrs and 1700 Hrs) in normal circumstances and hourly in flood like situation. The data is received by any available means viz. Cell Phones, Wireless, Land Line etc. Flood control cell is under the Executive Engineer, Khadakwasala Irrigation Division, Pune and during monsoon (from June to October) is operational 24X7 in three shifts. Everyday, at 0800 Hrs Report is generated and send to The Chief Engineer, Water Resources Pune; The Chief Engineer (SP), Water Resources, Pune; Divisional Commissioner, Pune and the District Administration. The Disaster Management Cell under District Collector with the help of other departments is prepared for emergency response. But as on today, there is time delay in information dissemination which is mainly manual. Once the RTSF & ROS is operational, the information dissemination will be real time and District Administration will be prepared to tackle the situation with a longer lead time. Disaster Management Offices Stakeholders in this category include all district administration offices, which have a special disaster management cell headed by district disaster management officer. All talukas and villages have also established such cells. Every flood prone village has a number of trained disaster preparedness persons. Flood Affected People The flood affected people are the most important stakeholders of any flood forecasting system. For a successful flood disaster preparedness, the people have to receive and understand flood warning messages in time and in clearly understandable forms. An extensive field visit was made around the Pune city to identify areas and people affected from floods and to assess how a flood forecasting system will help in disaster preparedness. Visits to the Pune Municipal Corporation (PMC) Building area (Figure 3.8) revealed that the Mutha river floods its bank submerging parked vehicles. Therefore a short (1-2 hours) flood warning would save vehicles from flooding. Inception Report 21

34 RTSF&ROS Krishna & Bhima River Basins Figure 3-8 Flood Prone area near PMC Building Another area prone to floods is around the Bund Garden, where rivers Mula and Mutha meet (Figure 3-9). The gauging station would be a suitable flood forecast location. Discussion with some city dwellers revealed that they would be able to save movable property if a flood warning can be received about two hours in advance. This seems to be feasible as the travel time of flood wave from Khadakwasla reservoir to Bund Garden is about 2 hours. 22 Inception Report

35 Krishna & Bhima River Basins RTSF&ROS Figure 3-9 Flood Prone Area near Bund Garden As mentioned in Section (page 19-20), similar flood affected conditions were reported by district administrators and other stakeholders in Sangli. Municipal Corporations (Domestic and Industrial Supply) The reservoirs in the Bhima and Krishna Basin provide water to the various users throughout the year, mainly within the agricultural, domestic, and industrial sector. Restrictions in the water allocation may be required from time to time depending on availability and user priority. While the water storage is known, the inflow to the reservoirs depends on the weather and climatic conditions in the coming days/weeks/months. The Municipal corporations at Pune, PCMC, Kolhapur, Sangli, Satara and other urban and rural areas are dependent on the supply from the reservoirs. Hence the less storage in the reservoirs at the end of monsoon season means less availability of water to these corporations. Along with District Administration, corporations and municipalities also have their disaster management cells, and requires timely and accurate information, which can be generated and disseminated from RTSF &ROS. Maharashtra Jeevan Pradhikaran The Maharashtra Jeevan Pradhikaran (earlier known as Maharashtra Water Supply and Sewerage Board) was constituted for rapid development and proper regulation of Water Supply and Sewerage service in the State of Maharashtra. As most of the water supply schemes will be dependent on supply from reservoirs or rivers, the information on water availability in the reservoirs as well as flows in the rivers will be very useful for water supply planning. In case of flood like situations, the timely Inception Report 23

36 RTSF&ROS Krishna & Bhima River Basins information from RTSF & ROS can be very useful in using the alternate sources of water adhering to safety norms. Farmers / Water User Associations To overcome the cumbersome procedure to get water, unreliability of water supply, inequity in water distribution, limitation on area under sugarcane, frequent conflicts and water logging problems, the Water User Associations (WUAs) have been functional in many irrigation areas in command areas. The WUA signs an agreement with the irrigation department to receive water on volumetric basis. They are expected to maintain and repair the minor and also was responsible for water distribution. As they are one of the main stakeholders to receive the water from reservoirs, the information on reservoir operation schedule as well as availability of water in the reservoirs can help them make better crop planning. Agricultural Department Agricultural Department considers farmer as the focal point and the whole department is organized in such a fashion that a single mechanism is working to facilitate the farmer for adoption of advanced technology and sustainable use of available resources. Thus the department advises farmers and water user associations on crop practices and irrigation methods, in normal circumstances as well as during drought and flooding. The information generated from the RTSF & ROS will also equip the department with information required to deal with abnormal conditions. Public Works Department (PWD) PWD takes care of development and maintenance of road network in the state as well as various construction activities for public use. The road network includes bridges and culverts and therefore, it is very essential for the PWD to have the latest status of river levels so that the safe transit of people is managed. Based on the information in advance, the traffic can also be diverted to safer routes. Electricity Boards The real time forecasts for reservoir releases also mean the running the hydropower plants, whenever possible with its optimum capacities. The timely information in this aspect can also help the electricity boards to manage additional power supply in their grid or even trade additional power. Health Department Health department is a very important department in disaster management. In the eventuality of floods, the department has to take care of different measures including short term and long term medical services. The prior information on flood thus will help the department in assessing the gravity of the situation and get the requisite resources at right time and at right place. Regular interaction with the officials of the Basin Simulation Division has been made to ascertain their needs. The tasks and activities planned to be carried out in the project are in line with their needs. 24 Inception Report

37 Krishna & Bhima River Basins RTSF&ROS Further consultation with stakeholders was carried out during the Inception Workshop, which was recognised as a forum for all stakeholders to participate interactively with each other as well as with the Consultants. The discussion and recommendations provided further insight into to assess stakeholders needs (Appendix B) Task 1.3 Identify and assess sources of weather forecasts and flow forecasting and reservoir operation tools Detailed description pertaining to this task is presented in Monthly Progress Report -2 (October 2011). Also Chapter for (4) of this Inception Report presents in detail the various tools (models) to be developed and applied in this project. Sources of Weather Forecasts Weather forecast is the key requirement for inflow forecast as well as for flood forecast. Out of the many weather parameters, only rainfall forecasts over the Krishna and Bhima river basins is sufficient for the purpose of the present assignment. The potential sources of rainfall forecast are: IMD Short Term Forecasts: IMD short term forecasts are prepared from synoptic maps, and made at district level up to five days ahead (Figure 3-10). The forecasts and a range of background information are available on the web site ( A range of ground based and remotely sensed sources is used, including mathematical models. Reliability of the forecasts will be checked before using the forecasts. Figure 3-10 IMD's 5-day District Wise Forecast IMD s Flood Meteorological Office (FMO) in Hyderabad may also provide Quantitative Precipitation Forecast (QPF) for the Krishna and Bhima basins on demand by Water Resources Department of Maharashtra. FMOs provide necessary meteorological support to the Central Flood Forecasting Divisions of Central water Commission (CWC). These FMOs function under the technical control of Hydromet Division, IMD, Delhi while their administrative control rests with RMCs (Regional Meteorological Centre). During the Flood season, FMOs issue daily Hydro-meteorological bulletins to Flood Forecasting Divisions of CWC on operational basis. It contains the following items:- i. Quantitative Precipitation Forecast(QPF) in different range which are 1 10 mm, 11 25mm, 26 50mm, mm and > 100mm. Inception Report 25

38 RTSF&ROS Krishna & Bhima River Basins ii. Prevailing synoptic weather situation in the region. iii. Basin wise areal rainfall. iv. Station wise significant rainfall during past 24 hours( > 50mm). v. Heavy rainfall warning in the next 48 hours, if any. Figure 3-11 IMD Catchment areas for Krishna & Bhima River basins During flood alert period, FMOs work round the clock and modifies QPF if required. The FMO, Hyderabad is assigned with the estimation of Meteorological information for the Krishna basin. IMD provides QPF for each ¼ th of a grid of the catchment. QPF for Bhima and Krishna catchments in Maharashtra, defined as sub catchments Upper Bhima (K5) and Upper Krishna (K1) as grid point rainfall up to 72hrs in advance (Figure 3-11). The proposed Doppler Radars at Ratangiri and Aurangabad in near future will enhance the resolution and accordingly data input provision will be made in the system. The contact office is: IMD, Flood Meterology Office, RS/RW Building, Airport Colony, Hyderabad (Andhra Pradesh) Land Line no , Fax no , - fmohyderabad@vsnl.net or fmohyderabad@gmail.com National Centre for Medium Range Weather Forecasting: The National Centre for Medium Range Weather Forecasting (NCMRWF is the premier institution in India to provide weather forecasts through deterministic methods. A mesoscale model (MM5 developed by Penn State University and the 26 Inception Report

39 Krishna & Bhima River Basins RTSF&ROS National Centre for Atmospheric Research, USA) is executed in real time for forecasting mesoscale systems, e.g. western disturbances, severe thunderstorms, tropical cyclones and heavy rainfall episodes. The model is run on triple nested domains at 90, 30 and 10km resolutions using initial conditions from a Global Model (Figure 3-12). MM5 coverage is only available at the regional 30km scale (11). Although this will have limited use in quantitative rainfall forecast, it will provide a basis for judgment of future events over the catchments. Quantitative rainfall forecasting can considerably increase the flood warning time, though the accuracy declines rapidly with lead time. The MM5 forecasts, while too coarse to be of real use for real time inflow forecasts, can nonetheless be assimilated for the operators to gain experience with the system. The technology for quantitative precipitation forecasting is developing rapidly, and new versions with greater accuracy can be incorporated as and when they become available. The project will consult NCMRWF in obtaining further information and in utilising their expert services. Figure 3-12 Domains of MM5 Meteorological Models European Centre for Medium-Range Weather Forecasts (ECMWF) Quantitative precipitation estimates from the European Centre for Medium-Range Weather Forecasts (ECMWF) modelling system may be used for areas where rainfall data are not available or where the number of rainfall stations is inadequate. ECMWF is one of the leading global modelling centres, producing high quality analyses and forecasts at various time scales. ECMWF produces weather and climate forecasts useful for medium range (1-10 day) and seasonal/long range rainfall prediction. The predictions are, however, of Inception Report 27

40 RTSF&ROS Krishna & Bhima River Basins probabilistic nature as a large sets of ensemble values are produced and analysed. The forecast system incorporates probabilistic meteorological and climate forecasts and satellite data. The ECMWF weather variables are surface fields of wind, humidity, and precipitation. The weather forecasts are provided as 51 ensemble members for each variable and for each forecast lead-time. The model resolution is at approximately 50 x 50 km grid from 0 to 10 days, with the forecasts horizon also extending to 15 days. All forecast fields are interpolated to the same 1/2 x 1/2 grid. The shorter-term hydrological forecasts uses the a 51-member ECMWF Ensemble Prediction System initialized twice each day. For the seasonal forecasts the 1-6 month predictions of the 41-member ECMWF Ensemble System coupled ocean-atmosphere climate model. The model is initialized each month and run for seven months. Both models provide the distributions of precipitation that are used to force the hydrological models. The ECMWF precipitation forecasts require statistical adjustment. This is accomplished using NASA and NOAA satellite and rain gauge estimates of rainfall data and a quantile-to-quantile (q-to-q) bias correction at each grid point in the basins. The q-to-q statistical corrections minimize systematic error in the forecasts of model precipitation; random error in the precipitation forecast is less important because of the large ensemble size used and the integrating effect of the largecatchment basin on the stream flow. To generate statistically accurate forecasts, the many uncertainties present in the analysis process must be accounted for in some manner. After these corrections have been applied, the probabilistic forecasts are produced. Tropical Rainfall Measuring Mission (TRMM) The tropical rainfall measuring mission of the National Aeronautics and Space Administration (NASA) produces merged 3-hourly rainfall rates incorporating space borne radar, microwave data and infrared imagery. The data are then processed at the United States Geological Survey s Earth Resources Observation and Science centre to convert them to daily accumulations and for converting to GIS-ready images. The NASA-TRMM product (version 3B42) covers the tropics between 50 N and 50 S, with grid cells of spatial resolution 0.25 by The NASA TRMM daily rainfall products are available from 1998 to the present. The processed rainfall data are made available within 12 h after the remote sensing data collection. The NASA TRMM 3B42 products are reported to be superior to other satellite data in regions with limited in situ gauges. The TRMM 3B42 satellite estimate is a merged product comprising calibrated IR rainfall and microwaverainfall. These satellite estimates are again calibrated by precipitation radar of TRMM and gauges over land. The final product of TRMM 3B42 is a gridded data available 3-hourly for extended tropical regions of the globe. Even though TRMM is a polar-orbiting satellite, the merging of IR and microwave-rain from many other satellites compensate for the deficiency to produce rainfall. Although the TRMM data will be useful in data assimilation and model applications in hind cast, their use in real time flow forecasting is limited. Flow Forecasting Tools 28 Inception Report

41 Krishna & Bhima River Basins RTSF&ROS A detailed review and requirements of the tools is presented in Chapter 4. Flow forecasting will be a based on a coupled rainfall-runoff and hydrodynamic model being developed based on DHI s MIKE 11 modelling package. The Rainfall- Runoff component is based on the NAM module while calculation and forecasting of flood water and reservoir levels are being managed by MIKE 11 s hydrodynamic module. Rainfall-Runoff modelling As a component of the DSS-Planning Project a number of NAM models have been established in the Upper Bhima catchment. A similar schematisation and calibration approach as applied in that project is initially being developed in the Krishna and Bhima RTSF & ROS. After dividing the river basins into a number of catchments and sub-catchments these sub-models are calibrated applying historical rainfall and discharge observations. In delineating the catchments following factors are considered: topography, rainfall variation, sub-basin outlets, watershed atlas produced by Soil & Land Use Survey of India ( and the Maharashtra Water & Irrigation Commission Report (1999). Further details are provided in Chapter 4. After calibration the NAM model shall be configured to a full utilisation of all available real time data including ROS data and weather forecasts to simulate and update the catchment runoff. River Basin Simulation Modelling The MIKEBASIN river basin water resources modelling system is being developed for water assessment and water allocation. Details are provided in Chapter 4. Hydrodynamic modelling The development of the MIKE 11 hydrodynamic model has also been initiated. Based on available river and reservoir shape files and satellite images the river network is being digitized. River cross-sections, reservoir operation rules and updated Stage-Area-Volume relations, catchment drainage pattern and data assimilation for real-time updating will subsequently be developed. Following the set up and calibration the short term flow forecasting model will be imported into the Flood Watch Online DSS tool. Flood Watch Online is a DSS platform, which is used to assist in the daily forecasting procedure. Flood Watch Online runs in automated or in manual controlled mode. After importing real-time data output facilities will be developed and customised to meet the need of WRD. Reservoir Operation Tools The requirement for reservoir operation is a comprehensive description of multipurpose multiple reservoir management. The Reservoirs may be on parallel and sequential rivers, purposes may be domestic and industrial water supply, irrigation, hydropower or flood control. A list of major and medium dams in the Krishna and Bhima river basins with their purposes are given in Appendix C. Existing operation rules will be incorporated into the MIKE 11 model in parallel with DSS tools allowing the responsible officer to base his forecast on these or on user defined policies, on predicted inflows combined with multiple objective functions and constraints. Outputs and dissemination Inception Report 29

42 RTSF&ROS Krishna & Bhima River Basins The scope of the Krishna-Bhima basin management system is to support reservoir operation through rapid access to data and guidance in the application of operation rules. The outputs of the RTSF-ROS will be modelling results analysing a number of possible future scenarios that may be the consequence of observed and predicted climatic input and options for system operations. This will provide a readily comprehensible decision background for efficient reservoir management. The information displayed will be real time observations and forecasted river and reservoir stages and will include: GIS maps showing weather forecasts and rainfall intensity maps Time series (tables and/or graphs) of river flows, reservoir, river and flood plain levels, irrigation and water supply and hydropower generated The primary output will be the most important data required for daily operations, e.g. the latest measurement of reservoir levels and discharges at selected locations. Additional information displayed can relate to a particular sub-basin, data category, and other groupings Task-1.4 Review available data and, the RTDAS network and identify critical gaps and recommend strategies to fill these A detailed review and analysis made on the various components of the data network is presented in Monthly progress Report-2 (October 2011). A detailed documentation on data availability and requirement is presented in Appendix D. Hydro-climatological data Network Figure 3-14 shows the Krishna and Bhima river basin map with existing hydroclimatological stations and proposed real time stations under the RTDAS project. Rainfall Rainfall is the only source of water in the Krishna and Bhima river basins. The quality of inflow and flow forecasts depends on the density and timeliness of rainfall data. Hence measurement and collection of rainfall data from stations representative of all catchments is a prerequisite to any analysis and forecasting. The total number of rainfall stations reporting in real time is shown in Table 3.1. This seems to be adequate with a density of one rainfall station covering about 333 km 2. Figure 3-13 shows only rainfall stations overlaid on the proposed rainfallrunoff model (NAM) catchments. The total number of NAM Catchments in the two basins as delineated presently is 93. The number of proposed real time stations indicates that each catchment will have one to four rainfall stations depending on the size. Although, there is no limit to how many rainfall stations can provide adequate data in hilly catchments, the proposed coverage seems to be adequate from the rainfall-runoff modelling point of view. 30 Inception Report

43 Krishna & Bhima River Basins RTSF&ROS Figure 3-13 Rainfall stations with basin catchment delineation Figure 3-14 Hydro-Met Network in Krishna and Bhima River Basins Figure 3-15 proposed real time Water level Stations Table 3.1 Summary of rainfall data network (to be upgraded to real time reporting stations). River Basin Area (km 2 ) Category I (nos.) Category II (Existing and new) nos. Krishna 21, (existing 52, new 15) Bhima 48, (existing 39, new 43) Category (FCS) III 16 (7 existing, 9 new) 26 (10 existing, 16 new) Total 69, Total no. of rainfall stations Inception Report 31

44 RTSF&ROS Krishna & Bhima River Basins During the review and analysis of adequacy of rainfall network, comparison was also made with WMO and Indian standards. There are a variety of standard recommendations on the density of rain gauges. According to Raghunath (2006), the recommended density is given below: Area Plains 520 km 2 Elevated regions km 2 Hilly regions with very heavy rain Rain gauge density (area per rain gauge) 130 km 2 Raghunath (2006) also states that in India an average density of 500 km 2 is acceptable. One governing factor is also the cost of establishing and maintaining the rain gauges. WMO recommendations on the density of rain gauges are given below: (WMO, 1996) Regions Ideal density (area per rain gauge) Acceptable density (area per rain gauge) Flat km ,000 km 2 Mountainous km ,000 km 2 The density of proposed RT rain gauges in the Krishna-Bhima basins is given below: Basin Area (km 2 ) Number of Rain gauges Krishna 21, km 2 Bhima 48, km 2 Total 69, km 2 Density (area per rain gauge) The average density of 333 km 2 per rain gauge appears to be adequate. Separating the hilly and flat catchments, the average density is: Hilly Area average density: 100 km 2 per rain gauge Flat Area average density: 716 km 2 per rain gauge. It is noted that the flat areas in the lower part of Bhima basin are dry with low rainfall. Hence these catchments have a rain gauge density 716 km 2 per rain gauge as against the 100 km 2 per rain gauge in hilly areas. In summary, it can be concluded that the proposed network is adequate. 32 Inception Report

45 Krishna & Bhima River Basins RTSF&ROS River water level & discharge stations Automated River Water Level (stage) and River Discharge stations fall under Category IV of the proposed RTDAS project. Figure 3-15 shows the proposed real time river water level and discharge stations. The new stations or existing stations proposed to be upgraded, will measure river stage and report in real time to the data centre at Pune. A total of 14 river water level stations (with 3 new) will report in real time in the Krishna basin. In the Bhima basin 20 water level stations (with 6 new) will report in real time. It is found that the proposed river water level network for real time reporting is adequate for the modelling purpose including flood forecast. It is suggested to include two downstream river gauging stations (namely at Bubnal or Kurundwad in Krishna and Develkavthe in Bhima. These two stations will serve as the downstream boundaries for the hydrodynamic models, and therefore, it is very useful to obtain real time data from them. Reservoir Water Levels: Automated Reservoir Water Level and Outflow Discharge Stations fall under Category V. This category data collection stations that will measure reservoir water elevation and transmit this data to data centre at Pune. A total of 46 automatic reservoir water level stations (19 in Krishna and 27 in Bhima basin) is proposed to be installed under the RTDAS project (Figure 3-16). Reservoir Release data (from gate opening) Under category VI, automated measurements of gate opening (spillway, irrigation and power outlet) will be established to provide reservoir release data in real time on experimental basis. The measured gate opening will be used along with water elevation to determine accurate discharge past the gates. The reservoirs namely Koyna and Radhanagari will be provided with spillway gate sensors and the reservoirs namely Ujjani, Dhom and Kanher will be provided with irrigation and/or power outlet sensors. Khadakwasla, Vir and Warna reservoirs will be provided with both spillway gate sensors and outlet sensors. A total of 59 gate openings (37 spillway gates, 19 irrigation outlets gates and 3 power outlet gates) is proposed to be established for real time transmission on experimental basis. Presently, the data of spillway gate, irrigation and / or power outlet operations is generally available in the form of telephone, mobile, Figure 3-16 Proposed real time Reservoir Water level Stations wireless or radio messages from dam operations staff. The reservoir data collection station/network will support manually entered gate operation information and transmit this data to data centre at Inception Report 33

46 RTSF&ROS Krishna & Bhima River Basins Pune. In some situations, the outflows are also measured directly in off-take canals downstream of the dam. River Cross Sections River Cross sections including flood plain levels are the key topographical information required for hydraulic modelling of a river system on which the flood forecasting system will be built. Also the reservoir operation system will be based on the hydraulic model (MIKE11) of the whole River and reservoir system. Hence an updated river-floodplain cross section is required for all the rivers under the model domain. A total of 101 river cross section data have been made available by WRD, out of which 17 cross sections are from CWC, 41 from G-D stations and 43 are from WRD s river survey of lower reaches of Krishna river. WRD is planning to carry out a river survey programme to collect about 2,000 river cross sections in the river reaches shown in Figure WRD has been advised to use same reference Bench mark and to extend the river cross section surveys to flood plains so that the levels can be used for flood mapping in the absence of adequate topo maps. If the proposed survey data will be available (on time), the coverage of cross section is adequate for the purpose of modelling and flood forecasting. Figure 3-17 River reaches showing the proposed cross section survey Satellite Images Taking into account the large area coverage of the river basins, conventional methods to collect this information proves to be costly, time-consuming & 34 Inception Report

47 Krishna & Bhima River Basins RTSF&ROS cumbersome. Hence remote sensing becomes to be an effective tool in river basins where timely information of the dynamic changes has to be taken into consideration. This technique provides us synoptic, repetitive, multi-spectral coverage of large areas and data is quantifiable. Indian Remote Sensing Satellite (IRS) data from LISS-II, LISS-III, LISS-IV, PAN, AWiFS & WiFS sensors are extensively used for generating spatial databases. Satellite data will be very useful in identifying irrigation areas including crop coverage, flood affected areas and other land use. For this project it is recommended to use IRS Resourcesat LISS-III and AWiFS data sets. These data sets can be procured from NRSC Data Centre, National Remote Sensing Centre, Hyderabad. Specific requirements will be worked out as the modelling work progresses. Figure 3-18 Satellite Map of Krishna-Bhima Basin (RESOURCESAT IRS-P6 AWiFS data) Topographic Maps The Survey of India (SOI) 1:50,000 scale maps coverage is shown in Figure 3-19 and also in table. These topo maps have limited use as their vertical accuracy not be useful for flood mapping. It is also expected that irrigation command area maps may provide contour of acceptable accuracy. Inception Report 35

48 RTSF&ROS Krishna & Bhima River Basins Figure 3-19 Index map of topo sheets of SOI These maps and information will be used in conjunction with floodplain to be obtained during the proposed river cross section survey. 47 E 11, 12, 15, F 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, G 9, 10, 11, 12, 13, 14, 15, H 9, 13, 14, 15, I 3, 4, 8, 12, 15, J 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, K 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, L 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, M 4 47 N 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14, 15, O 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, P 1, 5, 9 48 I 1, 5 56 B 4, 8 56 C 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, Task-1.5 Define options and scenarios for optimal multiple reservoir operation A variety of scenarios will be defined while developing an optimal reservoir operation guide. There are two main types of scenarios: General and Specific. General scenarios are applicable to all reservoirs in the basin. For example, the system behaviour (present and future stages and related releases) may be analysed for a set of climatic conditions either based on historical data or based on forecasts. A set of pre-defined simulated scenarios of rainfall, inflows, downstream floods, release for each water use will be stored in the system for use during the real time scenario management. Another method of testing an input scenario is using statistical methods. For example, what will be the flooding if the forecast rainfall varies by ±20%? Long term scenarios include hydrological impacts of climate change and land use changes in catchment. Both short and long term forecasts will be used to analyse what if scenarios. Short term forecasting is carried out when rainfall is dominating the catchment runoff, and will guide operations in flood 36 Inception Report

49 Krishna & Bhima River Basins RTSF&ROS situations, and day to day operations. Long term forecasting will be applied to predict seasonal flows dependent on long term climate predictions. The latter made as stochastic predictions based on historical records and correlations have a higher degree of uncertainty, though nonetheless useful for long term reservoir management. The river basin and hydrodynamic models will be run with key scenarios to simulate the performance of the system on selected historical flood and drought events, with a full description of the system input and outputs. Another set of scenarios are implemented by changing the simulated releases from reservoirs either directly or through changing the operation strategy. Basic predefined scenarios will be determined which could include varying the predicted rainfall by say ±20%, varying reservoir releases, shifting the balance of releases among the reservoirs, shifting the relative importance of flooding, irrigation and hydropower. With the assistance of a scenario manager, users may also define their own scenarios, including recalling previous events. For example, what will be the level of satisfaction of crop water demand if a reservoir release is changed from the long-term operation rule established to a new rule based on short term forecasts? Another example could be what happens to irrigation releases if the flood control buffer in reservoirs varies by ±20%? The other category of scenarios belongs to specific operation scenario of a particular reservoir system. These specific scenarios will be studied and tested in consultation with the reservoir operators and other decision makers/stakeholders during actual implementation of the reservoir operation guide. A Video conferencing facility is therefore, useful at the operational control room. The simulation models may be combined with optimisation routines to iterate automatically through various operation scenarios to identify the ones best fulfilling a set of predefined objectives, for example minimal downstream flooding, maximum timely water supplies and hydropower generation. Often short term objectives compromise long term objectives, thus short term analysis has to be combined with long term analysis to reach a combined optimum. The DSS Planning Project has reported a case study of testing a specific scenario in the Upper Bhima Basin. The reservoirs in the Upper Bhima Basin provide water to the various users throughout the year, mainly within the agricultural, domestic, and industrial sector. Restrictions in the water allocation may be required from time to time depending on availability and user priority. While the water storage is known, the inflow to the reservoirs depends on the climatic conditions in the coming months. It is likely that the inflow in the near future will resemble the inflow of earlier years. In order to provide a solid basis for planning, long time series of inflow to each reservoir in Upper Bhima have been generated using the observed data and hydrological modelling. It is now possible to test the performance of the reservoirs over the coming months for different water allocation plans and the likely range of inflow. An example is shown below for Pawna reservoir. Starting from the current reservoir level, which has been set quite low in this example, and using planned releases to the various users, the reservoir level for the next 12 months has been calculated for each of the available 39 years of daily inflow (Figure 3-20). Inception Report 37

50 RTSF&ROS Krishna & Bhima River Basins Figure 3-20 Ensemble of 39 simulations of Pawna reservoir level variation as a function of inflow. These results are automatically further processed in the DSS into three curves, representing different percentiles to indicate the likelihood of water level exceedence, as shown below (Figure 3-21). Figure 3-21 The Likely Variation of Pawna Reservoir in the Future The curves represent: - A dry year with low inflow and a late start of the next monsoon. This is shown as the blue curve below. It is a pessimistic, but realistic, prediction, corresponding to a 1-in- 10 year low, as the likelihood of getting higher water levels is 90% 38 Inception Report

51 Krishna & Bhima River Basins RTSF&ROS - An average year with a 50% likelihood is shown as the red curve - A wet year with relatively high inflow and an early start of next monsoon. These or higher levels have a 10% probability of occurring. The user can in this way easily obtain information of the likely performance of a reservoir for proposed water allocations. If the analysis shows an unacceptable risk of failure, the user can modify the planned amount of water allocation and re-run the analysis. These analyses may be made at any time of year and repeated regularly to ensure that the reservoir operations are on track. During the development and implementation of reservoir operation guidelines, the existing strategies will be reviewed and analysed. WRD has been requested to provide detailed information and data of all the reservoirs in the basin including the operational rule curves. The simulation models being developed integrate all the reservoirs in the two basins. Therefore, it will be possible to look into the combined operation of the reservoirs in which impacts of water releases from upstream dams will be reflected in the downstream reservoirs Task 1.6 Review institutional capacity of WRD, and recommend improvements for human resource development, and facilities for effective functioning The detailed description pertaining to this task is presented in Chapter 5 of this report. Inception Report 39

52 RTSF&ROS Krishna & Bhima River Basins 4 METHODOLOGY AND APPROACH 4.1 Knowledge Base and Management System The Knowledge Base and its Management System will be based on DHI s DSS architecture which is presently being applied in the DSS-Planning Project (NIH/World Bank) and for the RTDSS Project with Bhakra Beas Management Board (BBMB/World Bank). DSS Platform combines the MIKE modelling system via the Scenario Manager, and it incorporates a general purpose simulation-optimisation framework to provide an optimal solution to multiple often competing objective functions. In addition, it incorporates a comprehensive Knowledge Management System, a number of communication protocols, and a Web Portal with a user defined Alert System The Knowledge Base Management System within the DSS Platform provides an existing proven structure with generic interfaces to external data allowing ready import and export of data. Data access bridges ensure availability from various sources such as HIS, weather forecasts, remote sensed data, RTDAS, etc. The GIS interface conforms to the Open GIS Consortium, allowing linkage with, for example, Google Maps for display and spatial queries Design and Development of the Knowledge Base The Krishna-Bhima RTSF & ROS Knowledge base will basically adopt the overall architecture and design from the DDS-Planning Project. The Metadata document established during the Inception Phase and presented in Appendix E, together with the Modelling Concept, presented in Section 4.2, is setting out the need for further developments and configuration. During the project implementation phase additional requirements might be revealed, but it is anticipated that the Knowledge will comprise the following data: Geographic Data Infrastructure, built environments, demarcation, demographics, Land use and vegetation, soils and surface geology, WRD offices and locations for emergency services such as police and hospitals Historical and Real-time Hydro-meteorological Time Series Climate, Rainfall, Evaporation, discharge, river, reservoir and ground water level, water quality, spatial cropping patterns, crop water requirements, hydropower demands, satellite data and weather forecasts Other Topography and Hydrography Data Topography (DEM), water bodies (lakes, reservoirs, rivers, canals), hydraulic structures (dams, barrages, abstractions), location and characteristics of gauging stations, embankment alignments and heights 40 Inception Report

53 Krishna & Bhima River Basins RTSF&ROS The major difference between the DSS-Planning Knowledge Base and the database developed under the present RTSF & ROS project is the presence of Real-time hydro-meteorological data, such as weather forecasts from Numerical Weather Prediction models, on-line real time remote sensed data, and data from the Real Time Data Acquisition System. These data shall be automated imported, quality controlled and appended to existing observations. The Knowledge Base architectural structure is shown below in Figure 4-1. Inputs GIS Maps Time Series Satellite Data Analysis Catchment Delineation Flooded Areas Terrain Slope and Aspect Knowledge Base Management Quality Control Backup and Restore Monitor Performance Upgrade and Expand Outputs (pre and user defined) Documents and Tables Maps and Images Web Pages Figure 4-1: Knowledge Base Structure Design and Development of the Knowledge Base Management System As for the Knowledge Base itself, the Management System shall be based on the developments carried out under the DSS-Planning Project. The front end to the Knowledge Management System will provide a graphical user interface with explorer and data views, and tools for defining and targeting data queries in explorer and data views in user defined formats (see for example Figure 4-2). In consultation with WRD, the Consultant will establish a set of pre-defined reports (eg MS Excel report templates that can easily be tailored and modified). These will enable flood managers, operators and other users to view the information and data in the Knowledge Base in a convenient presentation format. The reports will include maps with selected GIS features, satellite images, spatial displays and charts of hydrologic data, tabular summaries of data, and documents. The pre-defined reports will be oriented towards the different sectors, e.g. hydrology, surface water, ground water, irrigation, power generation, environment, demographics, etc. This will also include generation of daily crop water requirement of major crops based on the real time data of climate stations for the basin at key locations. Inception Report 41

54 RTSF&ROS Krishna & Bhima River Basins Figure 4-2: Example of a Knowledge Base Management System Front End The knowledge management system can be accessed remotely over the Intra/Internet controlled by User IDs and passwords by WRD offices, other organisations and the general public, and in the field by PDAs (Personal Data Assistant). Access privileges will be determined in consultation with WRD. In addition to the Windows interface shown above in Figure 4-2, a web interface will be developed. This will allow remote access and facilitating communication with stakeholders and with the general public. The web-interface will be based on DHI s Dashboard Manager providing a number of tools for composing web pages, enhancing Internet access and the web portal. Additional information regarding this development are provided in Section 4.4: Communication and Information Management System 4.2 Streamflow and Forecasting Models Role of Mathematical Models Mathematical models are used to predict future developments of the water resources situation in the river basins on the basis of updated real time information (short-term forecasting) or analyses of historical data and developments (long-term forecasting). The models will be used to simulate the hydrologic cycle and supplement the real time information from the RTDAS with estimates of the state variables such as catchment runoff, reservoir inflow, levels and releases and downstream flood conditions. In addition, the models will be 42 Inception Report

55 Krishna & Bhima River Basins RTSF&ROS used to analyse effects of various reservoir operation strategies and to optimise these rules. Types of Models Many types of computer models have been applied for forecasting and management of hydrologic and hydraulic phenomena. Such models may be categorised as empirical models and conceptual/physically based models. Empirical models are sometimes termed black box models because they concentrate on producing the correct output from a given input without considering the processes that generate the output. This group includes various types of correlation and regression analyses, ARMA (Autoregressive Moving Average) and ARIMA (Autoregressive Integrated Moving Average) models, neural networks, generic algorithms, etc. The empirical type of model uses more or less advanced analyses of local historical data to generate algorithms that result in the correct output. The models are easy to establish and often quite effective. However, they are based on local historical data and cannot account for changes in the system that may arise after the period on which they have been trained. Since, they are based on local historical data they are also not necessarily able to cope well with events out of the data ranges used to develop them. Such events could be extreme floods larger than those in the time series used in the development of the model. Conceptual and physically based models are built on a description of the physical system they represent. The degree of detail of the physical system represented in the models varies. The conceptual model has the simplest system description and may also include certain empirical elements. Conceptual models are normally fast and robust while physically based models include a more detailed process description and are, for this reason, often more computationally demanding. Both conceptual and physically based models need to be calibrated on historical data from the area to give good results. During the calibration process, model parameters are adjusted to fit the generated output as well as possible to reality. The physical descriptions in the models are not changed during calibration. This type of model benefits from a process description and understanding developed on the basis of a large number of catchments and situations. They have a better chance of simulating correctly extreme events not present in the calibration data. Owing to their physical description, impacts of changes in the physical system such as new infrastructure can be simulated. Empirical models can only account for such changes after a certain period of time, maybe several years. The consultant has vast experience establishing modelling system of the conceptual physically based type, and has successfully applied flow forecasting and reservoir operation DSSs around the world. They are superior to empirical models, are transparent and allow tracing the analytical process, adding to the user s trust in their results. The proposed selection of models are therefore based on a conceptual and physically based suite of models. Inception Report 43

56 RTSF&ROS Krishna & Bhima River Basins The RTDAS and the model results will feed into multi or single criteria decision tools which may be used directly by WRD or feed back into the models when they are run in optimisation mode to suggest optimal or non-dominant solutions. The detailed and tailor made design of such tools will be specified in close cooperation with WRD. Based on experience with similar systems, the types of conceptual and physical models that will be included in the RTSF & ROS will be: A meteorological forecast model external to the system - results from the models will be used by the RTSF & ROS A rainfall-runoff model for simulation of the transformation of rainfall into evaporation, baseflow and superficial flow contributions to the rivers and reservoir inflow A river model with hydraulic and storage routing for routing of flow peaks though the system and for simulation of releases and storage in reservoirs A water resources allocation model to evaluate the impacts of the reservoir strategy for downstream users and recipients and for the power production Flow Forecasting Flow forecasting involves the use of hydrological and hydraulic models to transform measured and predicted rainfall in a catchment to a forecast time series of flows and water levels in a river system. They are typically used to provide warnings to residents at risk during times of flood, but can also be applied to predict inflows to reservoirs to optimise operations and hydropower production. Required features are: (1) Hydrological Rainfall-Runoff module (RR) which routes rain water to the rivers. The hydrological module utilises real time rainfall data as well as quantitative precipitation forecasts to generate runoff hydrographs to the future forecast horizon. (2) Hydrodynamic module (HD), which routes forecast inflows from the RR module through the rivers, canals and reservoirs included in the model. This may additionally include the dynamic operation of gates or other moveable structures. Fully dynamic routing is essential where rapid changes in flows or water levels occur, e.g. for short term simulation in power canals or for flood operations of structures. Where this is not required, e.g. for long term forecasting, simpler routing models can be used. (3) Structure operation (gate or hydropower discharge) module (SO), which incorporates the defined rules for operating the reservoir, which may change dynamically during a model simulation. 44 Inception Report

57 Krishna & Bhima River Basins RTSF&ROS (4) Data assimilation module (DA), which applies real time corrections to the simulated water levels and discharges based on available measurements, and makes a prediction of the necessary corrections to the forecasting horizon. Real time data assimilation is an essential prerequisite for an accurate flow forecasting system. The technology is described further in the following section. (5) A decision support system (DSS) to coordinate the exchange of data between the telemetry system and the model, and to provide operators with a user friendly interface to the underlying models. The core of modern inflow and flood forecasting systems is thus a hydrological and hydraulic model that applies to the current state of the river basin. The frequency of short term forecasts will vary over the year and according to the alarm level. The frequency may be daily during the low flow season and during filling of the reservoirs. During the period with high reservoir levels and high rainfall the frequency increase to four times a day or even more. The frequency can increase automatically when certain alarms in the systems are triggered. Flood peaks have to be calibrated at least on an hourly resolution. For important historical floods, the preceding rainfall events as well as flood water levels and flows should be on an hourly basis. This also applies to other highly dynamic events in the river such as flooding due to burst of upstream blockages or waves generated by flushing upstream reservoirs. All available data for the largest floods on records will be studied and a decision made on how many of these floods to include in the model calibration. Short Term Forecasting In situations where rainfall is dominating flow conditions, due to the response time of the catchment, the models can predict the runoff and the reservoir inflows around one or two day ahead on the basis of the climatic input observed up to the time of forecast (Figure 4-3). If reliable precipitation and temperature forecasts can be made, this period can be extended by some days. Where the runoff is dominated by M I K E 1 1 M O D E L L I N G baseflow or originates mainly from reservoir releases the runoff can be predicted with precision for a longer time horizon on the basis of real time information. F O R E C A S T S Figure 4-3: Short term forecasting The short term forecasts may assist in decisions regarding short term hydro power production strategies, day to day operations in general and operation in flood situations in particular. G r o u n d D a t a S a t e l lit t e D a t a R A I N F A L L F O R E C A S T S Inception Report 45

58 RTSF&ROS Krishna & Bhima River Basins Long Term Forecasts Long term forecasts, used to predict the seasonal or annual inflows, depend on long term climate predictions. Thus having a higher degree of uncertainty. Often the climate predictions are made as stochastic predictions based on the historical records (extended time series prediction), possibly combined with long term meteorological predictions. This requires running simulation periods of many historical years for each forecast, as illustrated in Figure 4-4. Often simpler flow routing models are used in such cases. Real-time data Historical Data Sutron stations Extended Stream flow Prediction -Real Time Data Probabilistic forecast Time of forecast. Figure 4-4: Long term forecasting Data Assimilation No simulation model is perfect, implying that the variables and output of the model will not completely match reality. For simulations into the future such as forecasts, the real situation is not known beyond the time of forecast. However, it has been found to be crucial for the accuracy of the forecasts that the stage variables (river flows, reservoir volumes, etc.) in the model match the real conditions in the basin at the same time, and that inaccuracies occurring in the model are analysed and properly adjusted for the remainder of the forecast simulation. The process of automating this procedure is termed data assimilation (or model updating). It uses real time information from the basin up to the time of forecast. The impact on forecasted flow series is illustrated in Figure 4-5. Proper Data Assimilation is crucial for the accuracy of flow forecasts. State variables in the model are adjusted to the real time conditions in the basin and the errors analysed to produce the best estimate of the future. The process is described in further detail in Section 4.2.2: Data Assimilation. 46 Inception Report

59 Krishna & Bhima River Basins RTSF&ROS Figure 4-5: Data Assimilation Concept Structure Operation Control structures may be used whenever the flow through a structure is to be regulated by the operation of a movable gate forming part of the structure. The structure may be described as an underflow structure, an overflow structure, a radial gate or a sluice gate. They can also be used to control the flow directly without taking the moveable gate into consideration. In this case it can simulate turbines and pump. What If Scenarios Both short and long term forecasts may be used to analyse what if scenarios, and hence to predict impacts of certain regulations at the focus reservoirs as well as at other reservoirs in the system. This is carried out by altering internal or external model boundary conditions. Examples of such analyses are flood operation scenarios, analyses of peak production strategies for upstream power plants or flood consequences caused by extreme rainfall intensities during the forecast period. Optimisation The models may be combined with optimisation routines to iterate automatically through various operation strategies to identify the ones best fulfilling a set of prescribed objectives. This is useful for determining optimal reservoir operation strategies with short or long horizons from the coming days, to the next season and to the coming years. The result of this model of operation could be optimised releases during the coming dry season on a monthly or weekly basis. Since such optimisations are typically computationally demanding, they may be carried out with simplified models capable of running with time steps longer than the detailed models normally used for short term inflow forecasting. Flood Mapping The hydrodynamic model will output water levels and discharges throughout the system of reservoirs, rivers and flood plains. By matching the water levels with a Digital Elevation Model (DEM), flooded areas, depths and durations are mapped. Inception Report 47

60 RTSF&ROS Krishna & Bhima River Basins Flood events can be displayed as animations of the flooded area from the onset to the recession of the flood. The Consultant will apply this mapping in GIS to study historical flood events, and to map current and forecast situations in real time. The flood maps will overlay basic infrastructure, human settlements and roads and railways (to assess safe evacuation routes), etc Development of Simulation Models Rainfall-Runoff The rainfall-runoff module simulates the rainfall-runoff processes occurring at the scale of a catchment and will be of the lumped conceptual type. The runoff hydrographs can either be applied independently or used to represent one or more contributing catchments that generate lateral inflows to the river network. In this manner it is possible to treat a single catchment or a large river basin containing numerous catchments and a complex network of rivers and channels within the same modelling framework. The rainfall-runoff module simulates the rainfall-runoff process by continuously accounting for the water content in three different and mutually interrelated storages that represent different physical elements of the catchment. These storages are: Surface storage Lower or root zone storage Ground water storage The meteorological input data to the model are precipitation and potential evaporation. On this basis, the model produces time series of catchment runoff and information about other elements of the land phase of the hydrological cycle, such as soil moisture content and groundwater recharge. The resulting catchment runoff is split conceptually into overland flow, interflow and baseflow components. The baseflow depends on the difference between the ground water level and the level of the outflow point in the linear reservoir. The latter is normally constant, but may be given a seasonal variation to represent the baseflow conditions of catchments draining to large rivers, which have a seasonal variation independent of the local hydrological conditions. The rainfall-runoff model (NAM) catchments for both the Krishna and Bhima basins have been delineated as shown in Figure 4-6. In delineating the 93 catchments the following factors have been considered: topography, rainfall variation, sub-basin outlets, watershed atlas produced by Soil & Land Use Survey of India ( and the Maharashtra Water & Irrigation Commission Report (1999). The present delineation of catchments is in agreement with the 48 Inception Report

61 Krishna & Bhima River Basins RTSF&ROS sub-basin map available in the above report. The All India Soil and Land Use Survey (AISLUS) Organization (Now known as Soil and Land Use Survey of India) of the Department of Agriculture and Cooperatives has published a national level watershed atlas on 1: 1 million scale using the base map from irrigation atlas of India in the year In this atlas, the entire river systems of the country have been divided into 6 Water Resources Regions, which have been further divided into 35 basins and 112 catchments. These catchments have been further divided into 500 sub-catchments and 3237 watersheds. The atlas consists of 17 sheets on 1:1 million scales along with a compendium of watersheds giving details of other related information such as area within the basin, sharing states and stream names etc. This atlas is being extensively used for various purposes by all the State and Central Government agencies, including WRD and GSDA of Government of Maharashtra. Further refinement in the delineation may need to be carried out in course of model calibration and when more information becomes available. Figure 4-6: Rainfall-Runoff Model (NAM) Catchment Delineation An important asset for the rainfall-runoff model is a proven built-in autocalibration routine, which significantly reduces the work load for model establishment and calibration. A sample result of rainfall-runoff model calibration from the DSS-Planning Project for one catchment in Upper Bhima is shown in Figure 4-7. Inception Report 49

62 RTSF&ROS Krishna & Bhima River Basins Figure 4-7: Calibration of Upper Bhima Catchment with discharge at Chaskaman River Hydraulics Short-time Forecasting The module will analyse and predict the flows and water levels in rivers and canals in response to defined inflows, downstream water levels and gate operations. The model will therefore be of the physically based finite difference type. The core hydrodynamic component provides a robust and stable numerical solution to the Saint-Venant equations of mass and momentum conservation in a one dimensional network. The solution is equally applicable to open channels or closed (pressurised) systems such as tunnels. Dynamic structure operations (e.g. gates, pumps, turbines) have to be incorporated, allowing the operation to be defined based on other model variables in the system (flows, levels) or time functions on defined priorities. The module has to cater for a wide range of hydraulic structures including: Weirs Culverts Pumps Reservoir operation Bridges Dynamically controllable gates Dam or embankment breaches The modules require reservoir modelling capabilities, and to accommodate multipurpose reservoirs and multiple reservoir systems. While the water resources module focuses on the allocation and use of water resources (see section??), the hydraulic aspects of structure operations are addressed by the hydrodynamic river module. 50 Inception Report

63 Krishna & Bhima River Basins RTSF&ROS The entire reaches of the Bhima and the Krishna River and their major tributaries are being developed for irrigation, hydropower and flood control, with projects running virtually head to tail in some of the catchments. The module must therefore be capable of simulating the complex operation of the control structures with full hydrodynamics of the complex flow patterns, compounded by reflections and interference patterns in the reservoirs. The development of the MIKE 11 hydrodynamic model has also been initiated. Based on available river and reservoir shape files and satellite images the river network is being digitized. An example of this is shown in Figure 4-8. After the overall schematisation nodes (junctions and bifurcations) will be detailed, reservoirs schematised, structures inserted and calibrated and crosssections (new and existing) applied. Figure 4-8: MIKE 11 River schematisation Inception Report 51

64 RTSF&ROS Krishna & Bhima River Basins Water Resources Allocation Long-time Forecasting The water resources allocation model is required for long term simulations and for water resource allocation issues. The model should be simple and intuitive, yet provide in-depth insight for planning and management. While the hydrodynamic module is applied to systems where advanced hydrodynamic routing of inflow hydrographs is important, for example to analyse the hydrodynamic impact of fast gate operation as a function of hydraulic conditions (water levels, flow velocities, or concentrations) at any location in the system or to predict impacts of highly dynamic flooding events, the water resources model simulates the long term seasonal variation in flow pattern and their management for various purposes. A model of the conceptual type is preferred for this purpose due to its flexibility in calculation time steps and faster computations. The MIKEBASIN river basin water resources modelling system is being developed for water assessment and water allocation (Figure 4-9). Figure 4-9 MIKEBASIN Model Schematic for the Krishna and Bhima Basins The long term management of the water resources is based on rules for the allocation of water throughout the basins to various priorities: water supply, irrigation, hydropower, the environment, and intra and interbasin diversions. The allocations can vary according to the level of stress in the system. The modelling systems have to be equipped with GIS based graphical user interfaces that offer a unique and flexible environment to establish and maintain an overview of the real time or predicted water resources situation in larger management areas. Not only do these opportunities serve reservoir operators and 52 Inception Report

65 Krishna & Bhima River Basins RTSF&ROS decision makers in the development of short and long term operation strategies, they also serve as excellent means of communication of complex technical matters to non-specialists such as political decision makers and stakeholder groups. The module should have built in routines for hydropower simulation, for optimization and the derivation of reservoir operation rules. Crop Water demand Crop water demands can vary significantly from year to year. In the Krishna- Bhima Basin, it is understood that cropping patterns and farmer behaviour are relatively stable, crop water coefficients are well established, and the main factors affecting the crop water requirement are rainfall and soil moisture. The cropping pattern and water requirement for each reservoir command will be determined using satellite images and project database. The timing of releases from the reservoir will be advised based on crop water demand schedule. During drought years the critical water demand will be considered. A biophysical approach is proposed to compute crop water demand (FAO56 CropWat) for major crops, where actual and forecast soil and soil moisture conditions, crop types and growth stages, and climatic data are used to compute evapotranspiration and hence forecast water requirements. Ground water abstraction and recharge can also be incorporated. Reservoir simulation and Structure Operation Except a few reservoirs with minor or no effect on the flow conditions within the two river basins, the operation of the Bhima and the Krishna reservoirs will be schematised in the short-time hydrodynamic as well as in long-term water allocation forecasting models. Elevation-Volume-Area (EVA) relations together with relevant geometrical information are being obtained as listed below: Stage-Volume and Stage-Surface Area relations All existing reservoir bathymetric surveys Type of Dam (Arch, Buttress, Gravity, Embankment) Spillway information (no s, crest levels, widths) Gate information (no s, crest levels, widths, type (underflow, overflow, radial) The geometrical information shall be incorporated into the respective mathematical models together with structure operation strategies, reservoir operation rules, irrigation demands, expected leakage, etc. To the extent possible the structure flow and corresponding energy loss will be calibrated, either based on observed data or on design criteria. A typical example is the Khadakwasla dam (Figure 4-10), which shows irrigation outlet (front) and flood spillway (most distant) is shown. Inception Report 53

66 RTSF&ROS Krishna & Bhima River Basins Figure 4-10: Khadakwasla Dam Data Assimilation - Model Stage Updating State updating or data assimilation (DA) refers to methods that take into account real time measurements such as water level or discharge in preparing a forecast, and then adjusting the model through a feedback process to match the observations (see Figure 4-11). Updating is adopted for real time forecasting to improve the initial state of the system prior to the time of forecast. In addition, updating is applied to model correction in the forecast period to account for any inadequacy in the model or in the input data. 54 Inception Report

67 Krishna & Bhima River Basins RTSF&ROS Figure 4-11: State Updating with Data Assimilation Updating the forecasts on observed runoff or water levels provides a practical method of reducing the sensitivity of the flow forecasting model to uncertainties in rainfall data, as well as taking advantage of the persistence in hydrologic flows to reduce prediction errors. Applying data assimilation techniques in flow modelling significantly enhances model accuracy. Both real time and forecast data are required to run a real time forecast. Real time and near real time information is used to assimilate the conditions in the model to the conditions in the basin, while forecast data are used as model input from the time of forecast into the future. Flood Mapping The hydrodynamic model will output water levels and discharges throughout the system of reservoirs, rivers and flood plains. In addition the hydrodynamic model is able to simulate and present (in hindcast as well as in forecast mode) overbank river flow and inundation. The flood mapping is an integrated component in the MIKE 11 hydrodynamic model. Based on applied river cross-sections, reservoir storage capacities and available terrain data (a DEM) these 2-dimensional flood maps will be generated on the fly, either as maximum flood inundation maps or as time series in two horizontal dimensions. I.e. inundation maps are available immediately after finalising the forecast simulation. Inundation maps can be published either in a GIS environment or in Google Earth (GE). Below in Figure 4.12 an example of flood inundation maps from upstream, respectively downstream Bhakra Dam are presented. Inception Report 55

68 RTSF&ROS Krishna & Bhima River Basins Figure 4-12: Flood Inundation Maps from the BBMB DSS project The Consultant will apply this mapping in GIS to study historical flood events, and to map current and forecast situations in real time. The flood maps will overlay basic infrastructure, location of WRD offices and emergency services, roads and railways (to assess safe evacuation routes), etc. Catchment and Flood Plain Topography To generate flood inundation maps a reliable DEM must be established for the flood prone areas Generally for accurate flood plain mapping, a vertical accuracy better than ±0.5m is required, though useful indicative flood maps can be prepared from less accurate data. The absolute accuracy of remote sensed DEMs (the SRTM 90m and ASTER 30m DEM) will not be better than say ±5m, though the relative accuracy from one grid to the next will be higher. The Consultant has discussed this issue with WRD in connection with the review of the river survey campaign. It was agreed that, in all the flood prone areas, the 56 Inception Report

69 Krishna & Bhima River Basins RTSF&ROS river transects should be extended into the floodplains up to levels above highest possible flood level These transects, together with available satellite images, shall then form the basis for developing the Digital Terrain Models (DTM) Boundary Conditions Meteorological data Meteorological data are used as input to the hydrological rainfall runoff model. Historical data are required for model calibration and for long term simulations while real time information is required for short term forecast simulations The following data types are required by the models: Precipitation Potential evapotranspiration or meteorological parameters allowing this estimation Historical meteorological data are available from the ground observation network while real time information on these data types will be collected through the DAS. Data from Meteorological Models and Satellite Data Collection and processing of these data are discussed in Chapter 3. Presently the Krishna and Bhima catchments within the State of Maharashtra are not covered by any meteorological radar thus radar observed rainfall cannot be applied in the forecasting models. The Consultant is aware of the availability of Satellite-based Rainfall Data from the Tropical Rainfall Measuring Mission (i.e. TRMM) available from the NASA s website ( Historical data are available in 3-hour time step format and the possibility of sourcing and applying real-time data is being investigated. As Numerical Weather Prediction on an operational basis has been carried out by the India Meteorological Department (IMD) for more than 20 years these data shall form the basis of the short-term QFP. But with a possibility of manual adjustment prior to submission of the forecast simulations. The forecast products of NWP are available on the website of IMD. These forecasts are updated at regular intervals Integration with Real-time Data Following the setup and calibration of the NAM hydrological Rainfall-Runoff and the MIKE 11 HD hydrodynamic river flow models, these shall be imported into and configured in DHI s Flood Watch Online DSS tool. Flood Watch Online is a user friendly platform, which is used to assist in the daily forecasting procedure. Flood Watch Online can run in automated mode or it can work in manual controlled mode. Flood Watch Online operates on a MIKE 11 Inception Report 57

70 RTSF&ROS Krishna & Bhima River Basins model, which will include the most important rivers and tributaries, subcatchments and all important reservoirs. Flood Watch Online Includes: Online status of forecast simulation including display of last forecast time Provision to load historical model simulation from archive. Fast access to data at all forecast locations through a mapping interface Time series data of forecasts and observations available in graphical and tabular view with graphical zooming facilities (Figure 4-13). Figure 4-13: Flood Watch On-line On-line, but user restricted Configuration Editor (Figure 4-14). Direct access to the forecasting model via the MIKE11 Editor button. Provision to View the Log file from the MIKE11 simulation Direct access to the MIKE11 Result Viewer via the Result Viewer button. Via this viewer it is possible to carry out detailed examination of simulation results before a publication is executed. Provision for opening MIKE FLOOD WATCH in a GIS environment. Provision to run and test alternative scenarios with user defined rainfall (Figure 4-15) and/or reservoir operation strategies (Figure 4-16). 58 Inception Report

71 Krishna & Bhima River Basins RTSF&ROS Figure 4-14: Configuration of Flood Watch Online Figure 4-15: Example of QPF adjustment Figure 4-16: Example of Reservoir Operation Strategy Inception Report 59

72 RTSF&ROS Krishna & Bhima River Basins 4.3 Reservoir Operation Guidance System Implementation of Existing Operation Rules Step one in developing the Reservoir Operation Guidance System must be an implementation of existing strategies in both the long- and the short term forecasting models. Both MIKE BASIN, which shall form the modelling component in the long-term forecasts and MIKE 11 HD, applied in the short-term forecasts, have extensively developed Structure Operation Modules. The BSD has started collection of Operation Rule curves and other documents from the 46 major reservoirs located within the project area, which will be handed over to Consultants. About 19 major reservoirs will have been given the highest priority with respect to schematisation and model implementation but shall be succeeded by collection of similar information from the minor reservoirs too. In addition to the operation rules, reservoir capacities as stage-volume and stagearea relations and structural information (dam types, spillways, gate dimensions, etc.) are being collected and processed Optimisation of Existing Operation Rules Short term optimisation of operations in succeeding hours and days will be based on the outputs from the MIKE 11 hydrodynamic model, whereas long term optimisation over succeeding weeks and months shall be based on the outputs from the MIKE Basin water resources model. In order to optimise the model simulations with respect to water resources and flood management, a set of objective functions and constraints will be defined in consultation with WRD. The optimisation process will iterate automatically through a large number of simulations representing various strategies to identify those best fulfilling the prescribed objectives. Rule Curve Optimisation The Rule Curve optimisation will be based on historical data and will be developed applying the MIKE 11 AUTOCAL module. Dependencies among variables and weights assigned to the different objectives shall be defined in close corporation with WRD. The AUTOCAL optimisation procedure consists of the optimisation of a single objective function, being a weighted aggregate of the different objective functions defined. By performing several optimisation runs with different sets of weights, the entire Pareto surface can be explored (Figure 4-17). Eventually, the decisionmaker can express his/her choice to select a preferred optimum from the Pareto solutions. It is also possible to include a multi-objective optimization, if the decision makers (or reservoir operators) are capable of setting objective functions in terms of water release targets, economic benefits or losses from flood damages. 60 Inception Report

73 Krishna & Bhima River Basins RTSF&ROS However, rigorous multi-objective optimization may only be carried out off-line and results stored for comparison during actual operation. Figure 4-17: Rule Curve Optimisation Based on this optimisation, the goodness of possible updating of the individual rule curves will be discussed among stakeholders of WRD during the actual implementation. A set of demonstration cases will be established, presented to users and documented. For demonstration at the Interim Workshop, and presentation in the Interim Report, two cases will cover selected monsoon and dry periods. Based on these experiences, the updated rules curves will be suggested, if required Operational Guidance System The entire system including the knowledge base, forecasting models, optimisation and scenarios, will be encapsulated within an Operational Guidance System. During the Inception Phase the needs of WRD as well as civil authorities with regard to media and formats for flood forecasting and dissemination have been discussed. A pilot system will be presented at the Interim Report and demonstrated during the Interim Workshop proposed to be organised in the first half of April Communication and Information Management System The Knowledge Base Development (Section 4.1) will provide WRD with an invaluable data bank of information for multiple decision situations. Combined with the analytical capabilities of the RTSF system, the Reservoir Operation optimisations delivered through the ROS this system and simulation results from short- and long-term forecasting will provide WRD with a strong decision support capability. A password protected user login system will grant access according to categories of users, from WRD managers to the general public as defined below: Inception Report 61

74 RTSF&ROS Krishna & Bhima River Basins Administrator - a profile that provides access to all parts of the system Configurator - a profile that provides access to the all parts of the system except those aimed at making administrative and once-in-a-lifetime settings. Typically, this profile is assigned to staff setting up the system Forecaster - a profile that provides access to all features required to work with the forecast related parts of the system. Typically, this profile is assigned to staff working with the system on a daily basis to produce forecasts Viewer - a profile that facilitates viewing of observed and forecasted data. Typically, this profile is assigned to managerial staff interested in examining data and results Communication Strategy and protocols The Communication and Information Management System will be based on the DSS Platform incorporating the Knowledge Management System and the Web Portal, disseminating data from the Knowledge Base, the RTSF and ROS analytical modules and from the short- and long-time Forecasting modules. The layout of the Communication and Information Management System is shown below in Figure 4-18: Communication and Information Management System and detailed in the following sections. 62 Inception Report

75 Reservoir Operational Guidance System Krishna & Bhima River Basins RTSF&ROS In the office On the move Web Portal Secure Password login Access levels In the field Alerts Knowledge System Management System Metadata & Atlas Knowledge Base Real Time Data Discussion Forum RTSF Flood Forecasting Water Resources Scenarios, Demo Cases ROS Optimisation Climatic Conditions Reservoir and River Levels Flood Plain Inundation Gate Operations Water Supply Allocation Figure 4-18: Communication and Information Management System Web Portal The Web Portal will be the gateway to the Knowledge Base and to the RTSF and ROS inclusive forecasts from the short- and long-time forecasting modules. The Consultant will develop the Web Portal using the Dashboard Manager, which is an integrated part of the Consultant s DSS Platform and provides a point-andclick interface for developing web pages on top of the DSS data and modelling capabilities. The web portal will be configured to display all relevant data from the Knowledge Base and the RTSF and ROS, including: Historical and real-time hydro-meteorological time series. Forecasts (river and reservoir stages and river flow) from the forecasting models Observed and forecasted reservoir inflow and proposed releases Gate operation strategies incl. real-time gate positions Flood Inundation maps. Inception Report 63

76 RTSF&ROS Krishna & Bhima River Basins The information will be available by clicking on GIS maps and basin schematics. Examples of customised web interfaces are given in Figure 4-19 and Figure 4-19: Customised Web Interface Figure 4-20: Example of DHI s Dashboard Manager driven web application with GIS and time series visualisation 64 Inception Report

77 Krishna & Bhima River Basins RTSF&ROS From the web-portal users will be able to: navigate among different views through a menu system select different stations within the basin and display e.g. RTDAS records and forecasts, including fact boxes for selected items Report output from the latest executed stream-flow and reservoir operation forecast model output, displayed as time series, tables and GIS maps showing inundated areas The Alert Module Alerting is a means of information dissemination, pushing information to specific staff and organisations for their immediate action. The DSS Platform logs all messages issued by processes such as real-time data import, simulation processes, publication processes and task execution processes and the Alert Module makes it possible to respond to any state in the system. The Consultant will in corporation with WRD define relevant alarms, each to be triggered to raise the alarm and the associated system response. Examples of states that users can respond to are: Upward or downward real-time data thresholds Upward or downward thresholds of selected simulation time series results Premature termination of tasks, simulations and publications Inception Report 65

78 RTSF & ROS Krishna and Bhima River Basins 5 CAPACITY BUILDING 5.1 Introduction The goal of Capacity building is to ensure that by the end of the project WRD has a self sustaining team operating and maintaining the Real Time Streamflow Forecast and Reservoir Operation System (RTSF&ROS), with a strong internal structure, and links to external organisations with whom WRD can share experience, impart to and draw on external knowledge. As a process of needs analysis, a review of the existing organisations and institutional arrangement is made in the following sections. 5.2 Water Resources Department (WRD) Water Resources Department, formerly known as Irrigation Department of Government of Maharashtra has a glorious history of Irrigation over last 150 years. The Water Resources Department (WRD) is entrusted with the surface water resources planning, development and management. A large number of major, medium and minor water resources development projects have been constructed in Maharashtra. The State Water resources Department tackles Irrigation projects which irrigate area more than 250 ha. In order to speed up the completion of irrigation projects, WRD has formed 5 Irrigation Development Corporations viz. Maharashtra Krishna Development Corporation (MKVDC), Vidarbha Irrigation Development Corporation (VIDC), Konkan Irrigation Development Corporation (KIDC), Godavari Marathwada Irrigation Development Corporation (GMIDC) and Tapi Irrigation Development Corporation (TIDC). The office of Director General at Nashik is responsible for Design, Training, Planning & Hydrology, Research and Survey. Under this office the Maharashtra Engineering Research Institute (MERI), Nashik conducts research in Civil Engineering and allied fields. The Water and Land Management Institute (WALMI) at Aurangabad is headed by Director General, which conducts the research and training in Water Management Planning & Hydrology The Office of Chief Engineer, Planning & Hydrology is located at Nashik and was established during Hydrology Project Phase-I. The Organisational set up of units of WRD involved in RTSF & ROS project is shown in Figure 5.1. Hydrology Project has developed and implemented a Hydrological Information System (HIS) through improvement and strengthening the infrastructure of Hydro-meteorological stations, training extensively the personnel involved and computerization of the data for meaningful analysis and dissemination to the users. The use of SWDES and HYMOS software in data entry and processing has resulted in giving out quality data. Figure 5.2 depicts a structure of HIS. Development of hydrological database is supporting major aspects of State and Central level Water Policy particularly in: Water Allocation, Water Planning, Water Management and Water Quality Monitoring. The Hydrology Project has five data processing centres and 26 sub-divisional data processing centres with the main State Data Processing Centre and the State Data Storage Centre at Nashik. 66 Inception Report

79 (Related to RTSF & ROS Project) Krishna & Bhima River Basins RTSF & ROS Inception Report 67

80 RTSF & ROS Krishna and Bhima River Basins Based on the database created under the Hydrology Project phase I (HP-I), Government of Maharashtra has authorized Hydrology Project organization to assess the yield for any project to be taken up and certify the water availability. The project can be sanctioned by any organization only if water availability is certified by this organization. One Water Planning Division has been assigned the work on yield computation of proposed schemes. Figure 5-1 Structure of the Hydrologic Information System (HIS) of HP-I The Basin Simulation Division (BSD) The Basin Simulation Division (BSD) at Pune was established in April, 2008 after recommendations of the Vadnere Committee for Real Time Streamflow and Flood Forecasting. The reservoirs in Maharashtra though not developed specifically as flood control reservoirs, they have moderated flood peaks to considerable extents by adopting proper reservoir operations. The reservoirs are multipurpose including hydropower, irrigation, domestic and industrial uses and are operated with rigid schedules as single entities based on the historical hydro-meteorological data and experience gained. These methods are often not adequate for establishing optimal operational decisions, especially where integrated operation of multiple reservoirs for flood management is contemplated. In addition, manual data observation and transmission results in a considerable time lag. The time taken between data observed in field and its communication to decision making level provides little time for flood forecasts. Therefore, under the Chief Engineer, Planning & Hydrology, the Basin Simulation Division has been established at Pune, which is 68 Inception Report

81 Krishna & Bhima River Basins RTSF & ROS engaged in upgrading the existing HIS with real time data acquisition system (RTDAS) for Krishna and Bhima basins and for the development and implementation of Real Time Streamflow Forecasting and Reservoir Operation System. The present Organizational set-up of Basin Simulation Division is given in Figure 5.3. Figure 5-2 Organogram of the Basin Simulation Division, Pune BSD is headed by an Executive Engineer supported by administrative staff. At present there are four Assistant Engineers (Grade I) and six Assistant Engineers (Grade-II). The six Assistant Engineers (Grade-II) are also assigned to subdivisions in Shirur, Kohlapur, Sangli, Stara, Solapur and Pune. Table 5.1 presents the list of BSD Officers. The organisational aspects of the RTSF& ROS are of paramount importance for the sustainability of the established systems. It is important to foster an environment through training and participation in which WRD staff take ownership of the system. To sustain this it is critical to establish simple and well thought work processes ensuring optimal use of the capabilities of the modelling systems. The BSD is, therefore, considered as the key division of WRD in implementing the project and develop into a sustainable organisation in operating, maintaining and updating the modelling systems developed under the RTSF& ROS project. Therefore, the training needs assessment and institutional development plan is focussed at BSD. Inception Report 69

82 RTSF & ROS Krishna and Bhima River Basins Table 5.1 List of Officers of BSD, Pune Sl. No Name Designation Educational Qualification 1 Dnyandeo A Executive M Tech. Bagade Engineer (Hydraulics & Water Resources Engineering) 2 Girish V Nagarkar 3 Shivali D Pardeshi 4 Deepgauri A Joshi Assistant Engineer Gr-I Assistant Engineer Gr-I Assistant Engineer Gr-I M.E.(Construction & Management) Responsibility / experience In-charge of Basin Simulation Division, Pune. Network Investigation for RTDSS Maharashtra, ICB tendering for procurement of consultancy, Goods and related services. Responsible for execution of RTDSS work(krishna and Bhima Basin) In-charge of Hydro-meteorological Data processing division Nashik. Data dissemination activities. Data collection, Validation, and management of Hydrometeorological network of Ratnagiri District, Investigation of Irrigation project Construction of LIS, canal works, survey works, rehabilitation works in Satara district. Hydrology Project, Network Investigation for RTDSS Maharashtra, ICB tendering for procurement of Goods and related services. Responsible for execution of RTDSS work (Bhima Basin) B.E.(Civil) Responsible for execution of RTDSS work (Krishna Basin) Canal works Design of civil structures B.E.(Civil) Responsible for execution of RTDSS work (Krishna Basin) 5 Mayur M Mahajan Assistant Engineer Gr-I B.E.(Civil) Responsible for execution of RTDSS work (Bhima Basin) Water supply works 6 Yojana B Patil Assistant Engineer Gr-II B.E.(Civil) Network Investigation for RTDSS Maharashtra, ICB tendering for procurement of consultancy, Responsible for execution of RTDSS work (Krishna Basin) Water quality validation, Hydro-meteorological Data validation 7 Rahul B Mali Assistant Engineer B.E.(Civil) Responsible for execution of RTDSS work (Krishna Basin) 70 Inception Report

83 Krishna & Bhima River Basins RTSF & ROS Sl. No Name Designation Educational Responsibility / experience Qualification Gr-II Irrigation Project Investigation 8 Sanjay G Bhakt 9 Sushma D Meshram Assistant Engineer Gr-II Assistant Engineer Gr-II B.E.(Civil) Responsible for execution of RTDSS work (Bhima Basin) Irrigation Project Investigation in Krishna Basin. Hydro-meteorological data processing B.E.(Civil) Network Investigation for RTDSS Maharashtra, ICB tendering for procurement of Goods and related services, Responsible for execution of RTDSS work (Bhima Basin) Hydro-meteorological Data validation 10 Asish S Jadhav B.E.(Civil) HP Pune Sub-division Hydro-meteorological data 11 C S Desai B.E.(Civil) HP Kolhapur Sub-division Hydro-meteorological data Inception Report 71

84 RTSF & ROS Krishna and Bhima River Basins Training Needs assessment The training needs assessment of the officers at BSD is based on the educational background, professional experience and the requirements of the RTSF&ROS project during the development stage as well as during actual operation. If as proposed, the officers are fully engaged with the consultant s experts during the development period, then they are expected to be capable of operating the system. However, since this is the first time the officers will be taking a new responsibility, they will need technical back up support from DHI for certain period after the system is installed. This has been taken care of in the project by planning a technical support period (including helpdesk support at DHI) for a period of 2 years after instalment of the system. Table 5.2 shows a training needs assessment related to the tasks of the project. Table 5.2 Training Needs Assessment Project Task Training Need in Subjects General level of present staff of BSD Task 1: Review Current Forecasting and Operational Capabilities Task 2 Knowledge Base Development Task 3 Real-Time Streamflow / Flood Forecasting Model Task 4 Reservoir Operational Guidance System Task 5 Communication and Information Management Systems None Data processing, verification, database systems, working with GIS and Remote sensing data Hydrology, hydraulics, GIS, hydrological modelling, hydrodynamic modelling including flood forecast (NAM, MIKE11, MIKEBASIN). DSS, river basin modelling (MIKEBASIN) reservoir operation modelling. Internet technologies, web design and update adequate Basic Mostly basic, a new staff with expertise in meteorology and forecasting will be required. Basic Basic, a new staff with ICT expertise will be required at BSD 5.3 Institutional Development Plan Proposed Setup and Functions of BSD The Basin Simulation Division will be responsible to maintain all the data and models developed in the present project. Regular updating of the models including timely validation as new data becomes available will also be the responsibility of 72 Inception Report

85 Krishna & Bhima River Basins RTSF & ROS BSD. The operational control room will be central operations room for BSD. Therefore, BSD will perform the following functions: Operation and maintenance of the Data Acquisition System (Responsibility of HPD, Pune) Management of the central Database Meteorological analysis and forecast Hydrologic and hydraulic analyses of the basin Update of the hydrologic and hydrodynamic models Operation and maintenance of real time forecasting systems (inflow and flood) Operation and maintenance of the reservoir operation guidance system Communication and information dissemination These functions should be performed by the assistant engineering staff with one executive engineer as the manager of BSD. The engineering staff will take turns to manage the operational control room. Additional staff might be required to man the operational control room round the clock during critical situations. In addition to the existing assistant engineers, it is recommended to employ two more staff at BSD: 1) Meteorologist, 2) ICT Expert. The proposed meteorologist should have a postgraduate degree in meteorology/climatology with expertise in rainfall forecasting and satellite data applications in meteorology. The ICT expert should have a graduate degree in computer science/engineering with expertise in information communication, web design and updates. It is proposed to organise BSD into the following sub-divisions/sections. Also shown in Figure 5.4 is the proposed Organogram. No. Sub-div/Section Functions Responsible Officer 1 Operational Control Room 2 Meteorological forecast Operation of the forecast and reservoir operation guidance system. Management of meteorological data, Analysis of meteorological conditions of the basins, Compilation of rainfall forecasts. 3 Database Acquisition of hydro-met, river, reservoir, GIS and satellite data and database maintenance Assistant Engineer (Gr-I) Meteorologist Assistant Engineer (Gr-I) Other staff Assistant Eng. (Gr-II), Meteorologist, ICT Expert, Office Assistant 2 Assistant Engineers (Gr-II) Inception Report 73

86 RTSF & ROS Krishna and Bhima River Basins 4 Modelling Maintain and update of all models including DSS and reservoir operation system 5 Information Management Communication of forecasts, reservoir operation guidance system, dissemination of flood forecasts, web page management and updates. Assistant Engineer (Gr-I) ICT expert 4 Assistant Engineer (Gr- II) Figure 5-3 Proposed Organogram of BSD Operational Control Room The Operational Control Room will be located at the 2nd floor of Sinchan Bhawan, Pune together with the RTDAS Data Centre. Out of a total floor area of 1,000 sft, the operation control room will occupy about 400 sft. The control room will be linked to the BSD at the 4th floor with LAN. Both the BSD and the Control Room will have dedicated broadband internet connectivity. The communication between BSD and the Control Room should preferably be via intranet in addition to the general purpose internet for links with all stakeholders. It is expected that all important reservoir operation offices and related decision making offices in Pune, Nashik, Mumbai and other districts have broadband Internet connectivity so that 74 Inception Report

87 Krishna & Bhima River Basins RTSF & ROS communications to and from the control room is efficient and transparent. It is expected that the Operational Control Room and hence the staff will be active beyond the monsoon season. Water resources monitoring will be required for droughts as well as for optimal management of the river basins. Figures 5.5 and 5.6 show a schematic layout of the Control Room with tentative dimensions. Figure 5-4 Plan of the Operational Control Room Figure D View of the Operational Control Room Inception Report 75

88 RTSF & ROS Krishna and Bhima River Basins WRD will develop the physical infrastructure including uninterrupted power supply, air-conditioning, window and door curtains/blinds and broadband internet connection. The RTSF&ROS Consultant will provide the following equipment and furniture: Two (2) high performance Servers with UPS: 1 data server, 1 web server Two (2) high performance PCs with UPS One (1) high resolution wall mounted LCD display One (1) high resolution web camera with Skype based video conferencing facility One (1) printer with table One (1) semi-circular/oval desk suitable for such a control room Four (4) revolving chairs for operators and staff One (1) conference table and eight revolving chairs The data server will be linked to the computer in which processed real time data from the RTDAS Data Centre are stored. It is also expected that BSD will have a similar servers and PCs for back up and mirroring databases and modelling systems Capacity Building and Training Plan during the Project An integrated capacity building and technology transfer is being adopted during the project period. The main components of the integrated capacity building are: formal training on theoretical concepts and practical modelling tools, on-the-job training, Workshops, International technical and study tours, technical and hotline support during a period of 2 years after installation of the RTSF&RO system On-the-job training In addition to the proposed formal training activities, all BSD officers and the executive engineer will be engaged in the activities of the consultants. In order to facilitate learning by doing The consultant s office is provided with adequate space for BSD officers to work together with the consultant s experts. It is proposed that the BSD officers are assigned with primary responsibilities of working together with Consultant s experts in the following field. However, these staff will also learn other areas during training and also during on-the-job training. Data management including GIS & Remote Sensing data: 2 officers Rainfall Runoff Modelling: 2 officers Hydrodynamic (river) Modelling: 2 officers Inflow Forecasting and Reservoir Operation: 2 officers Flood forecasting: 2 officers 76 Inception Report

89 Krishna & Bhima River Basins RTSF & ROS Training Courses The proposed training courses cover both theoretical concepts of hydrology and hydraulics, data management, remote sensing and GIS tools, modelling tools and reservoir operation guidance system. A training programme is presented in Table 5.3. It is also proposed that BSD officers attend some of the training courses offered by the National Water Academy (NDA) based in Pune. In order to enhance relevancy, the consultant staff will also deliver some of the training courses in coordination with NWA. The officers of BSD will also be encouraged to attend relevant courses in other institutions in India on GIS, remote sensing, water resources management, disaster management, ICT, Computer applications, web design, database management etc. Inception Report 77

90 RTSF & ROS Krishna and Bhima River Basins Table 5.3 Proposed Training Programme No Duration / date 1 4 days 2 1 day Sept Oct week Jan week 5-9 Dec days Dec days Jan days Jan 2012 Topic / contents Introduction to Remote sensing & GIS and application to water resources Introduction to modelling Decision Support System (DSS) Flood Forecast technology including inflow forecast Hydraulics: Open Channels, Control Structures Hydrology: Concepts of rainfall runoff, met forecasts, rainfall runoff modelling using NAM Hydrodynamic Modelling using MIKE11, structure operation, flood forecasting Venue Trainers Participants BSD RTSF&ROS Consultant s Project office, Pune NWA, Khadakwasla, Pune NWA Khadakwasla, Pune RTSF&ROS Consultant s Project office, Pune RTSF&ROS Consultant s Project office, Pune RTSF&ROS Consultant s Project office, Consultant staff (Dr. Pandit) Consultant staff (Guna Paudyal, Finn Hansen) Experts of DSS (planning) Project NWA Faculty Consultant staff (Guna Paudyal) Consultant staff Consultant staff (Finn Hansen) Executive Engineer, and 8 officers of BSD (9 persons) Executive Engineer, and 8 officers of BSD (9 persons) Executive Engineer, and 2 officers of BSD (3 persons) 4 officers of BSD (this course was missed), will consider future events. 8 officers of BSD Executive Engineer, and 8 officers of BSD (9 persons) Executive Engineer, and 8 officers of BSD (9 persons) 78 Inception Report

91 Krishna & Bhima River Basins RTSF & ROS No Duration / date 7 3 days Feb week March days March days June week Nov-Dec days Feb Jan 2014 Topic / contents GIS & remote sensing: Use of GIS spatial data, sources of data, image processing Flood Disaster Management Hydrodynamic modelling, flood mapping Development of real time DSS, RTSF and ROS system Application of RTDSS in real time stream flow forecasting and reservoir operation Operation of the RTSF&RO system, maintenance, troubleshooting ( as & when required during the technical support period) four training courses to be planned in consultation with WRD. Venue Trainers Participants RTSF&ROS Consultant s Project office NWA Khadakwasla, Pune RTSF&ROS Consultant s Project office RTSF&ROS Consultant s Project office BSD, Pune Consultant staff (Dr. Pandit) NWA Faculty, Consultant s experts Consultant staff (Finn Hansen) Consultant staff Consultant staff 8 officers of BSD 4 officers of BSD BSD officers and officers from other stakeholders (CE offices) Executive Engineer & 8 officers of BSD (9 persons), other stakeholders Executive Engineer & 8 officers of BSD (9 persons), other stakeholders BSD Pune DHI All officers, several courses. Inception Report 79

92 RTSF & ROS Krishna & Bhima River Basins Workshops Workshops are important forums for consultation as well as capacity building of stakeholders. In this project a series of workshops will be conducted. Three workshops, namely, Inception, Interim and Final will be organised as general workshop with a large number of stakeholders. Two workshops will be of more technical nature in which only WRD officials and selected and most relevant stakeholders will be invited. As stipulated in the contract, the Workshop will be arranged by client and will be facilitated by resource experts from consultant Figure 5-6 Schedule of Workshops (showing the timing in month in blue) Sl. No. Table 5.4 Plan of Workshops 1 Inception Workshop 2 Interim Workshop 3 Workshop on Knowledge base & data manageme nt 4 Workshop on flow and flood forecasting Workshop Date Activities 7 December 2011 First week of April 2012 Mid-June 2012 Mid- September Presentation of Inception Report, stakeholder consultation, further needs assessment, feedback on approach & methodology and on capacity building plan. Presentation of Interim Report, feedback on the modelling systems developed. Demonstration of the knowledge base and knowledge management system, review of the RT DAS and plan to incorporate the real time data into the forecasting and reservoir operation systems. Demonstration of the modelling system, comments & discussion on the system, including the forecasting formats and flood mapping, suggestions to incorporate into the final version of the forecasting system. 5 Workshop on Reservoir Operation Guidance and communication / Last week of November 2012 Demonstration of the Reservoir Operation Guidance system, comments and discussion on the system, suggestions for incorporation into the final version of the Reservoir Operational Guidance System. The communication and information 80 Inception Report

93 Krishna & Bhima River Basins web portal RTSF & ROS management system including web portal will also be demonstrated in this workshop. 6 Final Workshop 1 st week Feb 2013 Presentation of Final Report, feedback/comments/suggestions in the Final Report, evaluation of project achievement, finalisation of technical support for the next two years of system operation. the project deliverables International technical training cum study visits It is proposed to conduct two technical study visits to two batches of technical officers with six participants in each batch. Each of the technical training cum visit will be of 2 weeks duration. It is also proposed that each group may be led by an Executive Engineer. The tentative programme of the two week training cum study visit is given below. The first batch of technical officers will go on the visit during 5 to 18 February 2012 and the second batch during 11 to 24 March Week 1: Training at DHI Denmark The technical officers will receive training from DHI experts on real time stream flow forecasting, reservoir operation, flood mapping and flood forecasting, and on modelling and web based water resources information management. They will be presented with examples of real time forecasting systems from all over the world based on DHI s work. Various experts of DHI will be available for interactive sessions with the participants. Week 2: Technical visit to Austria and Slovenia The first part of the technical visit will be conducted near Vienna, Austria where the participants will visit the International Forecasting Centre in Graz. An automated river forecasting system is working in three different basins in Styria, namely the Mur, Raab and Enns rivers. The forecasting system is based on MIKE11, similar to the system proposed to be implemented in the Krishna and Bhima river basins. A field visit will be conducted in two basins (Mur and Raab) to study the real time data acquisition systems. The second part of the technical visit will be conducted in Slovenia. The participants will be taken to the meteorological Office and the Forecasting Centre in Ljubljana, Slovenia. A Mike11 based real time forecasting system is operation for two river basins, namely Sava and Soca. Field visits will be organised in these river basins to observed the telemetric network. The telemetry systems in these basins are being upgraded since 2010 to utilise the latest technology available in the market. The timing of the above technical training cum visits will be finalised in consultation with WRD. However, it is recommended that the visits be conducted between January and May 2012 so that the technical staff of WRD get an early exposure while the modelling work is being carried out in the RTSF&ROS Project. Inception Report 81

94 RTSF & ROS Krishna & Bhima River Basins International Study Tour It is proposed to organise a study tour for eight senior officials of WRD to observe real time forecasting and reservoir operation systems. The study tour will be of 1 week duration including travel days. Two alternate locations are being considered at this stage. Further discussion with WRD is required to finalise the timing, venue and budget for the study tour. The study tour is proposed to be conducted during 12 to 18 February USA: to observe and interact with officials and experts in California where several water resources system use real time data for optimal operation of reservoirs, examples are: Black Canyon Irrigation District, Napa Valley in San Francisco; Blackfoot Reservoir command area, a fully automated systems for water release pattern. In terms of real-time flood forecasting systems, most US Army Corps of Engineers and US Bureau of Reclamation Reservoirs in the Pacific Northwest and California have such systems 2. South Africa: to observe real time reservoir and river operations in the Orange-Fish Sundays River Basin. The Orange-Fish-Sundays River System in the Eastern Cape consists of an extensive system of canals, tunnels, rivers, dams, and diversion weirs. Water is transferred from the Orange River to the Great Fish River through a tunnel 83 km long. The main purpose of this transfer is to satisfy irrigation demands. Due to a general water shortage as well as problems arising from highly saline return flows, it became necessary to make a real time model that could assist the operators in deriving release hydrographs from the dams and diversion weirs. These hydrographs will ensure that the irrigators receive the right quantity and quality of water when required using a minimum amount of water. The hydrographs will also ensure that the reservoir water levels are kept within required limits during normal operation and that excess water during flooding is diverted to reservoirs with any storage capacity left. Finally the hydrographs also ensures a minimum downstream flow. A comprehensive real time operational (including optimization) water management system is implemented in this basin to enable operators to optimize release hydrographs throughout the system. 82 Inception Report

95 Krishna & Bhima River Basins RTSF & ROS 6 PROJECT IMPLEMENTATION PLAN 6.1 Activity Schedule A summary of the schedule of project s main tasks as stipulated in the contract is shown in Figure 6-1. In order to complete the main tasks, each task is further divided into sub-tasks or activities, the schedule of which is given in Figure 6-2. Figure 6-3 presents the schedule of reports and deliverables. The schedules presented in figures 6-1 through 6-3 are as stipulated in the contract and at this stage, there is no reason to modify them. However, there are a few critical paths in the schedules, which are related to the availability of data in time: 1. Availability of historical data (for model development & calibration) 2. Availability of river cross section data from the proposed new river survey programme of WRD (for the development of the MIKE11 flood forecasting models) 3. Availability of real time data on time from the RTDAS contract. In order to develop the real time inflow forecasting, reservoir operation system and flood forecasting, the proposed telemetry data must be received at the data centre latest from the beginning of the monsoon season of Figure 6-1 Overall Schedule of Project Tasks Inception Report 83