Empirical Model: Two Basic Types of Models. Why Use Watershed Modeling? Overview of Models for Estimating Pollutant Loads & Reductions

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1 m 3 /s A p r-9 3 Valley Mills (BO1) Monthly Average daily streamflow E =.66 %E = M = 14.4 P = 12.7 O c t-9 3 A p r-9 4 O c t-9 4 A p r-9 5 Teas Watershed Planning Short Course Wednesday, Jan 14, 29 Larry Hauck hauck@tiaer.tarleton.edu O c t-9 5 Month measured A p r-9 6 predicted O c t-9 6 A p r-9 7 O c t Overview of Models for Estimating Pollutant Loads & Reductions (Handbook Chapter ) Upper Oyster Creek - Lower portion (8/9/24) Mainstem A Humorous View or a Reality Check? Watershed Monitoring and Modeling is the Art and Science of Collecting data in systems we cannot adequately sample Using methods developed by committees of technically unqualified participants For organisms and pollutants we know very little about In order to form concepts about processes we do not fully understand That we represent as mathematical abstractions that we cannot precisely analyze To determine their responses to indeterminate stresses we cannot accurately predict now let alone in the future All in such a way that society at large is given no reason to suspect the etent of our ignorance. DO (mgo2/l) Avg(P) DO (mgo2/l) Avg(O) DO (mgo2/l) Min(P) Min(O) DO (mgo2/l) Ma(O) Presentation II 1 DO (mgo2/l) Ma(P) DO (mgo2/l) DO sat(p) Adapted from a slide by Dr. Thom Hardy, Utah State Univ. Why Use Watershed Modeling? Models provide another approach, besides monitoring data and eport coefficients, for estimating loads, providing source load estimates, and evaluating various management alternatives. What Are Models? Mathematical models are analytical abstractions of the real world and as such represent an approimation of the real system. In the contet of watershed planning, mathematical models are computer based, simplified representations of landscape and water quality processes that govern the fate and transport of one or more pollutants. Presentation II 3 Presentation II 4 Two Basic Types of Models Empirical Model Mechanistic Model Empirical Model: A model where the structure is determined by the observed relationship among eperimental data. These models can be used to develop relationships for forecasting and describing trends. These relationships and trends are not necessarily mechanistically relevant. Source: EPA website, glossary of frequently used modeling terms. Presentation II 5 Presentation II 6 1

2 An Eample of an Empirical Model: Investigating the relationship of inflowing nutrients in a lake to algal biomass production (eutrophication). Most early (circa 197) lake eutrophication models based on statistical relationships between mass loading of nutrients and average algal biomass (e.g., Vollenweider models with numerous adaptations by others) Applied to PL-566 reservoirs in North Bosque River Watershed Presentation II 7 Annual mean summer chlorophyll-a concentration as a function of predicted total-p for years from PL-566 reservoirs. N=25 Presentation II 8 Mechanistic Model: A model that has a structure that eplicitly represents an understanding of biological, chemical, and/or physical processes. These models attempt to quantify phenomena by their underlying casual mechanisms. Source: EPA website, glossary of frequently used modeling terms and our Handbook Presentation II 9 Presentation II 1 Two Common Mechanistic Models Used in Watershed Modeling in Teas: Types of Mechanistic Models HSPF Hydrologic Simulation Program -FORTAN SWAT Soil & Water Assessment Tool Both models are comprehensive watershed loading, hydrologic, water quality models. Both models are intensive in use of resources and skills to operate the models. More on these a little later. Presentation II 11 Steady State Model Dynamic Model Presentation II 12 2

3 Steady-State Models: A mathematical model of fate and transport of waterborne constituents using constant input parameters to predict constant values of receiving water quality concentrations (typically under low-flow conditions) Source: Our Handbook An Eample: QUAL2K QUAL2K is a stream water quality model. It is one-dimensional* and operates under steady-state flow. All water quality variables are simulated on a diurnal (24-hour) time scale, including dissolved oygen. *fully-mied in the vertical and lateral directions Presentation II 13 Presentation II 14 Portion of Oyster Creek Dissolved Oygen (DO) Results for Verification Period 2 Upper Oyster Creek - Lower Reach - May 24 Verification Case (5/7/24) Mainstem Dynamic Models: A mathematical model of fate and transport of waterborne constituents formulated to describe the physical behavior of a system and its temporal variability DO (mgo2/l) Avg(P) DO (mgo2/l) Avg(O) DO (mgo2/l) Min(P) DO (mgo2/l) Ma(P) DO (mgo2/l) Min(O) DO (mgo2/l) Ma(O) DO sat(p) Presentation II 15 Presentation II 16 SWAT Prediction for a Subbasin of North Bosque River (Streamflow) SC2 Monthly Average daily streamflow SWAT Prediction for a Subbasin of North Bosque River (Total Phosphorus) SC2 Monthly Total TP.6 1,6.5.4 E =.3 %E = M =.11 P =.8 1,4 1,2 1, E = -8.7 %E = 199 M = 88 P = 263 m 3 /s.3.2 kgs Jan-95 Jun-95 Nov-95 Apr-96 Sep-96 Feb-97 Jul-97 Dec-97 month measured predicted Presentation II 17 Jan-95 Jun-95 Nov-95 Apr-96 Sep-96 Feb-97 Jul-97 Dec-97 month measured predicted Presentation II 18 3

4 HSPF & SWAT Two Dynamic Watershed Models: Both supported by EPA BASINS (Better Assessment Science Integrating Point & Nonpoint Sources) Include processes of: Rainfall/runoff Erosion & sediment transport Pollutant loading Stream transport Management practices Presentation II 19 Model efficiency (E) for measured and predicted daily (d) and monthly (m) flow, total suspended solids (TSS), and nutrient loadings during (a) calibrations and (b) verification, at the outlet of the UNBRW. Presentation II 2 HSPF & SWAT General Impressions by Presenter Both models are complete watershed and water quality models with several state variables (runoff, streamflow, bacteria, nutrients, dissolved oygen, toics). HSPF has an edge in predicting hydrology SWAT more user friendly SWAT more powerful in representing agricultural practices HSPF more powerful in urban environment HSPF has an edge with instream fate and transport processes Presentation II 21 EPIC & APEX Two Dynamic Field-Scale Models: Field-scale: application focused at the subbasin or smaller level; often on a single land use EPIC Environmental Policy Integrated Climate APEX Agricultural Prediction Policy/Environmental extender Developer: Dr. Jimmy Williams, BREC Presentation II 22 Field plot and rain gauge locations within the Goose Branch microwatershed. Presentation II 23 APEX Application: Measured versus predicted storm runoff volume for a) all values and b) for values less than 5 cubic meters per hectare. Presentation II 24 4

5 APEX Application Comparison of measured and predicted storm loads of total nitrogen. APEX predicted soil etractable P levels (-15 cm) for Coastal bermudagrass field. Presentation II 25 Presentation II 26 Load Duration Curves Not a model Method of data organization and presentation that assists in understanding and refining water quality assessments (data requirements: streamflow and pollutant data) Applicable to stream systems Eplained in previous session. Presentation II 27 E. coli (cfu/day) 1.E+15 1.E+14 1.E+13 1.E+12 1.E+11 1.E+1 1.E+9 1.E+8 75th 75 percentile percentile geo. mean geo. mean % 1% 2% 3% 4% 5% 6% 7% 8% 9% 1% Percent of days loading eceeded Allowable Load Geometric Mean (CFU / Day) Allowable Load Single Sample (CFU / Day) Measured Load Geomean 75th Percentile Presentation II 28 What Questions Can Models Assist in Answering? Will management actions achieve desired goals? Which sources are the main contributors to pollutant load? What are the loads associated with individual sources? Which combination of management actions will most effectively meet identified goals? When does impairment occur? Will the loading or impairment get worse under future conditions? How can future growth be managed? Eamples of questions models can answer from North Bosque River (SWAT) Upper Oyster Creek (QUAL2K) Presentation II 29 Presentation II 3 5

6 Land Use and Soluble-P Sources North Bosque River at Clifton BMPs Imposed on Selected Scenarios PO 4 -P Source Contribution Wood/Range 22% Urban 6% Crop 5% Pasture 8% WWTP 1% Dairy Waste Appl. 49% Crop 9% Pasture 14% Dairy Waste Appl. 4% Land Uses Urban 2% Wood/Range 71% Presentation II 31 Scenario WWTP Flow WWTP P Limit Dairy Dairy Manure Feed App. Rate P Diet No Dairy Manure Haul off No Eisting Median Btw N&P Rate Baseline 22 Median N rate Yes No Scenario A mg/l P rate Yes No Scenario B 22 1 mg/l P rate Yes No Scenario C 22 1 mg/l P rate Yes Yes Presentation II 32 Eceedence Probability for the North Bosque River at Valley Mills Soluble Phosphorus Concentration (ppb) Preliminary Target Probability of Eceedence Baseline Eisting Scenario A Scenario B Scenario C Upper Oyster Creek - Lower Reach Presentation II 33 Presentation II 34 Dissolved Oygen, mg/l Lower Reach Summer Critical High Temperature - Upper Oyster Cr. (Preliminary Results) Dam 3 Present Permit Limits Criteria BOD=5 mg/l, NH3=2 mg/l, DO=6 mg/l Stafford Run Steep Bank Cr. Hwy 6 Comple Watershed Modeling Systems: Reservoirs Tidal & Estuarine Systems Location, km 5 Presentation II 35 Presentation II 36 6

7 Integrated Modeling Approach for Watershed and Reservoir The Soil and Water Assessment Tool (SWAT) applied to the Bosque River Watershed to predict In-stream PO 4 -P concentrations Used to assess various P Control Strategies Integrated Modeling Approach CE-QUAL-W2, a two- dimensional, laterally averaged, hydrodynamic and water quality model developed by U.S. Army Corps of Engineers, Waterways Eperiment Station, Vicksburg, MS applied to Lake Waco to predict in-lake PO 4 -P concentrations and algal response Used to assess various P Control Strategies Presentation II 37 Presentation II 38 CE-QUAL-W2 Segmentation of Lake Waco Lake Waco-Bosque River Watershed Presentation II 39 Presentation II 4 Eceedence Probability for Lake Waco CE-QUAL-W2 Calibration Presentation II 41 Soluble Phosphorus Concentration (ppb) Target Range Probability of Eceedence Preliminary Target Baseline Eisting Scenario A Scenario B Scenario C Presentation II 42 7

8 Tidal Streams & Estuaries Link watershed model to appropriate hydrodynamic and water quality models Watershed: HSPF, SWAT, etc. Water Quality: for eample, Water Quality Analysis Simulation Program (WASP) Hydrodynamic model: for eample, DYNHYD, RMA2 Complete H / WQ models: for eample, Environmental Fluid Dynamics Computer Code (EFDC) Presentation II 43 Four Considerations That Assist in Defining Your Model Application 1. Relevance: Is the approach appropriate to your situation? 2. Credibility: Has the model been shown to give valid results? 3. Usability: Is the model easy to learn and use? (If not, is the epertise available to apply a sophisticated model?) Are data available to support the model? 4. Utility: Is the model able to predict the water quality changes based on anticipated management changes? Presentation II 44 Available Models & Model Capabilities See our Handbook, pages 8-18 through 8-27 EPA Compendium of Tools for Watershed Assessment and TMDL Development. EPA841-B-97-6 EPA s Council on Regulatory Environmental Modeling ( Presentation II 45 Source: Handbook, page 8-26 Presentation II 46 Oh, No! No Model Does Close to What Is Needed Try load duration curve approach or Modify and adapt an eisting model An Eample: Modifying APEX to Better Accommodate Situations in Forestry Work by Drs. Jimmy Williams, BREC & Ali Saleh, TIAER Presentation II 47 Presentation II 48 8

9 Modifications of APEX for forestry conditions. Simulated and measured sediment losses for (a) SHR and (b) CON treatments during (average of three replications). Presentation II 49 Presentation II 5 An Eample Model Selection & Application North Bosque River Watershed Presentation II 51 Land Use Lake Waco Watershed Presentation II 52 North Bosque River Watershed with SWAT subbasin delineation Measured X-sectional Areas X-sectional areas measured at over 1 sites along the North Bosque and its tributaries. Elevation (ft) BO95 Cross-Section Tagline (ft) Presentation II 53 Presentation II 54 9

10 Model Validation The validation process consists of model calibration and verification. Calibration - model parameters are adjusted within allowable limits until model output for a given time period matches measured output within some predetermined measure of model performance. Verification - refers to running the calibrated model (i.e., holding adjustment parameters constant) during a different time period and comparing model output to measured values. Note: Definitions & terms vary from those in Handbook. Model Validation Calibration and verification increases confidence that the model will accurately simulate watershed conditions for different management scenarios. This process gives confidence that the model output during management scenarios will reasonably reflect what the true measured values would be. Presentation II 55 Presentation II 56 Calibration and Verification Periods Time Site SF2 NF9 NF2 NF5 SF75 BO2 MB4 BO4 IC2 AL4 SC2 GC1 SP2 BO7 (Hico) BO9 (Clifton) NC6 BO1 (VM) Measures of Model Performance Nash-Suttcliffe goodness of fit (E) % error (% E) Calibration Verification Presentation II 57 Presentation II 58 Measures of Model Performance Percent Error ( + %E ) Very Good Good Satisfactory Unsatisfactory Moriasi et al. (27) Sediment < > 55 P, N < > 7 m 3 /s Apr-93 Calibration of Total Streamflow Hico Monthly (BO7) Average daily streamflow E =.86 %E = -8.5 M = 3.45 P = 3.16 Sep-93 Feb-94 Jul-94 Dec-94 May-95 Oct-95 Month Mar-96 Aug-96 Jan-97 Jun-97 Nov-97 measured predicted Presentation II 59 Presentation II 6 1

11 Calibration: Average daily loads BO7 average daily load Verification Period (flow) Valley Mills (BO1) Monthly Average daily streamflow kgs OrgN OrgP NO3 MinP TP TN BO7 sim BO7 meas m 3 /s E =.7 %E = 11.9 M = 6.1 P = 6.8 Jan-98 Jul-98 Jan-99 Jul-99 Month measured predicted Presentation II 61 Presentation II 62 Verification: Average daily loads Scenarios Evaluated kgs BO7 average daily load OrgN OrgP NO3 MinP TP TN BO7 sim BO7 meas Scen A B C D E F G Filter strip P WWTP 1 mg/l X R New lagoon A 5% manure C NRCS T New PL-566 I Microgy remed. C HWAF remed. E 75% manure S WWTP.5 mg/l Red. graze Presentation II 63 Presentation II 64 PO4 concentration (ppb) 199s and Future Baseline and Scenario A and G Annual daily-average PO 4 conc. and annual PO 4 loadings At Valley Mills (PRELIMINARY RESULTS SUBJECT TO CHANGE) Eceedance Probability full-permitted baseline future A 199s baseline future G PO4 load (kg) 2, 18, 16, 14, 12, 1, 8, 6, 4, 2, Eceedance Probability full-permitted baseline future A 199s baseline future G Land Uses of North Bosque River Watershed with dairy waste application fields Presentation II 65 Presentation II 66 11

12 Questions? Presentation II 67 12