A METHOD FOR COMPARING BATHYMETRIC SURVEY DATA TO DETERMINE CHANGES IN SEDIMENT ELEVATION
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1 page 3 A METHOD FOR COMPARING BATHYMETRIC SURVEY DATA TO DETERMINE CHANGES IN SEDIMENT ELEVATION J Herzog, Floyd Snider, Seattle, USA and A S Bradshaw, Department of Ocean Engineering, University of Rhode Island, USA Abstract For waterway maintenance, infrastructure development, environmental and habitat restoration projects, scientists and engineers frequently need to determine the changes in marine or river bottom surfaces that have occurred over time. Changes in sediment surface elevation for any given area may be estimated by several methods, including the comparison of bathymetric survey data that have been collected over a number of years. Comparison of survey datasets, however, requires consideration of the uncertainties inherent in the survey technology used, the level of survey precision (which is determined by the objective of the survey) and the method utilised to compare the data. Thorough consideration of these uncertainties informs which survey differences indicate real physical changes in bathymetry versus apparent variations stemming from the survey and comparison methodologies. This paper describes a standardised approach for comparing bathymetric survey datasets to allow appropriate interpretation of the comparison results. For this study, field data were used to evaluate both the inherent uncertainties of the individual surveys and the uncertainties introduced as part of the comparison process to determine the overall uncertainty of a given survey comparison. The bathymetric surveys used in this study were collected in the Passaic River, New Jersey. Introduction Scientists and engineers often need to analyse elevation changes in the sediment surfaces of rivers, lakes and marine waters for a variety of reasons. Evaluating trends in the increase or decrease in sediment elevation can help determine whether a river system, for example, is a depositional or erosional environment. In addition, changes in sediment elevation may also be used to estimate the net volume of sediment deposited or eroded. Correct interpretation of sediment elevation changes that occur over time and the behaviour of the subsurface environment is critical information for waterway maintenance, infrastructure development and restoration of sediment and habitat. One method to determine changes in sediment elevation over time is to compare data from historical bathymetric surveys. Historical survey records are often available because routine bathymetric surveys are generally conducted by federal and local governments as well as private parties for navigational, maintenance and development purposes. When comparing survey data, one must consider whether the differences between the recorded elevations from two surveys indicate real changes or if these differences reflect apparent changes resulting from the manner in which the two surveys were conducted or compared. The impact of real versus apparent changes can only be accounted for by quantifying the uncertainty in the comparison of two surveys so that the apparent changes can be eliminated from the interpretation of the comparison results. In the comparison of two bathymetric survey datasets, there is always some degree of uncertainty resulting from the method used to compare the survey datasets, the precision 1 of the survey data collection process and the data processing techniques (where digitisation of historical data is used). Contributing factors to uncertainty include: precision of survey vessel position measurements (location control) depth measurement precision, including: resolution, equipment characteristics, calibration, datum, survey stability, the effects of vessel velocity and echo sounding sensitivity to sediment materials data processing, including: data linking, tidal corrections, sound speed corrections and vessel draft corrections data quality control data presentation, including: drawing construction and sounding data density data comparison and interpolation, including manual interpolation and the use of computer-generated surface models. Also, for the comparison of datasets spanning a number of years, it is likely that each dataset was generated with different equipment and methods, adding another degree of uncertainty. Correct comparison of bathymetric datasets must consider the inherent uncertainty in the comparison and also the uncertainty introduced because of the changes in technology or methods. Therefore, a standardised procedure that considers the above contributors to uncertainty, quantifying them into an expected overall uncertainty 2, must be used to compare survey datasets in order to draw appropriate and scientifically defensible conclusions about net changes in bathymetry. Previous Work to Quantify Bathymetric Data Comparison Uncertainty Several previous investigations comparing bathymetric data were completed by Hicks and Hume (1997 [1]), Gibbs and Gelfenbaum (1999 [2]), Byrnes et al (2002 [3]), Johnston (2003 [4]) and Van Der Wal and Pye (2003 [5]). Each of these investigations recognised that uncertainties resulting from the comparison of bathymetric data are a function of the variables discussed above, but were not intended to evaluate the overall uncertainty when comparing bathymetric data. Rather, these previous investigations relied on either published tolerances for uncertainty such as those presented in survey manuals, or data from non-overlapping or non-repeat surveys to establish uncertainty limits for data comparisons. Thus, the results of these previous investigations are insufficient to understanding and quantifying the overall uncertainty resulting from comparing two bathymetric surveys.
2 page 4 Positioning Echo Linking of Survey system sounding Tide gauge Navigation position & methodology equipment equipment equipment equipment depth data Trimble Odom Coastal OSI 1990s 7400 Echotrac Leasing Maretrack II Automated Kinematic Model DF Microtide GPS 3200 MK II IMC Hydro-1 Raytheon Coastal OSI 1989 Range Model Leasing Maretrack II Automated Azimuth DE-719 Microtide IMC Hydro-1 Raytheon Coastal OSI 1986 Range Model Leasing Maretrack II Manual Azimuth DE-719 Microtide Table 1: Summary of bathymetric survey equipment Figure 1: Lower Passaic River This paper specifically addresses the uncertainties associated with bathymetric data comparison. The results of an empirical field study are used to quantify the overall uncertainty in comparing hydrographic data from specific surveys conducted in the Passaic River, New Jersey (Figure 1). The overall uncertainty for the survey methods used in the study was established at the 95 percent confidence level, consistent with US Army Corps of Engineers (USACE) guidance [6]. A standardised comparison procedure is also presented that applies these overall uncertainties to the calculation of net differences between the two surveys compared. The comparison method presented supports the appropriate interpretation of the data and is applicable to other survey data; however, the overall uncertainty estimates presented in this paper are specific to the survey methods evaluated for this study. Background Since the last major dredging event in 1949, the New York District of the USACE performed periodic bathymetric surveys of sections of the Passaic River. As part of this study, an extensive review of available documentation from the historical Passaic River surveys was completed to obtain information on the actual survey methodologies used and other relevant information that could be utilised to evaluate the uncertainties of a given survey. Insufficient documentation was available on the historical surveys conducted prior to 1986 to fully evaluate the data collection and processing techniques. Therefore, only two historical surveys performed by the USACE in 1986 and in 1989 were considered for this study. The bathymetric survey method used for these surveys (explained below and in Table 1) is no longer used by the USACE, as methods have been updated with advances in technology. The 1986 and 1989 survey methods used by the USACE are collectively referred to in this study as 1980s methods. These 1980s survey methods were selected for this study because there was sufficient available documentation of the actual surveys and the procedures used to allow for the survey methodology to be recreated in the field. For surveys conducted prior to 1986, adequate documentation about the surveys, and methodologies to recreate the survey methodologies, was not available. Consistent with the methods of the time, the 1980s bathymetric survey methods employed data collection transects oriented perpendicular to the shoreline. Positions were measured using a hand-operated, optical range-azimuth positioning system, depth data were acquired using an analogue echosounder and the associated water level measurements were recorded by hand from a tide staff. Since 1989, there have been five bathymetric surveys of the Passaic River that provide full overlap with the 1986 and 1989 surveys, and are, therefore, reasonable to use for comparison. One of these surveys was completed in 1995 as part of a Remedial Investigation/Feasibility Study (RI/FS) conducted under the direction and oversight of the US Environmental Protection Agency (USEPA). These well-documented surveys, conducted in 1995, 1996, 1997, 1999 and 2001, all utilised the same methodology, which included a differential global positioning system and digital echosounder with digital water level monitors that provided electronic records of water level fluctuations during the survey. As for the 1980s methods, these surveys were also performed along transects oriented perpendicular to the shoreline; however, the system used to complete these more recent surveys utilised more reliable and precise survey equipment and methodology than the 1980s methods. The survey methods used for the 1995, 1996, 1997, 1999 and 2001 surveys are referred to in this study as 1990s methods. Method to Determine Overall Uncertainty The methodology to determine the overall uncertainty for comparing bathymetric survey data presented in this section is based on the analysis of data from repeat surveys performed within a limited area of the Passaic River. The assumption for determining the overall uncertainty for a given bathymetric survey method is that repeating surveys along the same transects within a short time frame during which changes in sediment elevation should not occur will result in no calculable difference in elevation between the individual surveys. Therefore, any sediment elevation differences resulting from comparing the individual surveys of a repeat dataset may be attributable to the uncertainties introduced during data collection, processing and analysis. The empirical study utilised data from the repeat bathymetric surveys performed with the 1980s and 1990s survey methods as a means to quantify the overall uncertainty associated with each bathymetric survey method. The methodology for quantifying the overall uncertainty for comparing bathymetric survey datasets is discussed below. Repeat Surveys This study utilised two repeat surveys conducted in a limited area of the Passaic River in 1996 and The repeat survey area was selected because the river bottom topography is relatively simple in comparison to other parts of the lower Passaic River, thus providing a less complex comparison surface. The repeat survey in 1996 was conducted using the 1990s survey methodology. At this same location in 2001, an additional repeat survey was performed using the 1980s survey methods. 3 The bathymetric survey equipment used in each of these repeat surveys is summarised in Table 1. Each repeat survey was comprised of three individual surveys performed along the same five tracklines oriented perpendicular to the shoreline. For example, the sounding locations from the individual runs for the 2001 repeat survey conducted using the 1980s methodology are shown on Figure 2. The individual surveys comprising a repeat survey set were completed within a relatively short time frame (less than 4 days) during normal flow conditions in which no major sediment elevation change should have occurred. To ensure that each bathymetric survey was truly independent, the survey equipment was broken down, set up, recalibrated and the survey crew rotated between each survey. No. 118 October 2005 THE HYDROGRAPHIC JOURNAL
3 page 5 Figure 2: 1980s method repeat survey sounding data Figure 3: Bias and variability for an example elevation difference distribution Data resulting from each of the repeat surveys were collected and processed in accordance with standard procedures specific to the 1980s and 1990s methods, as derived from USACE guidance manuals [6]. Because the 1986 repeat survey methodology utilised a paper record, scaling and digitisation were required to create an electronic dataset. In the 1989 repeat survey, a digitiser was used to convert the analogue signal to a digital signal that was automatically linked to the position data. The data collected from the 1990s repeat survey were collected digitally and required no further manipulation before processing. Repeat Survey Data Comparison To compare the bathymetric survey data for each repeat survey set, a computer-generated triangulated irregular network (TIN) model of the sediment surface was created for each survey from the sounding data. AutoCAD Release 14 [7] was used to create the TIN surface model for each survey with a standard automated algorithm that interpolated linearly between the three nearest sounding data points. Each TIN sediment surface model was visually verified to identify and remove any outlying data points. Outlying data constituted only those points that plotted onshore or within the boundary of an in-water structure such as a bridge abutment. A subtraction grid 4 was applied to each TIN sediment surface model and was used to calculate sediment elevation differences between each bathymetric survey within the repeat survey set. The AutoCAD programme was used to calculate the elevation difference between the two TIN surfaces at each subtraction location. After the preliminary difference data were calculated, the individual survey data and the TIN surface models were visually reviewed to identify any outlying data points, which were removed from the dataset. Only a nominal number of points were identified and removed; typically, these points were co-located with in-water structures. The subtraction grid differences calculated between the TIN surface models of a repeat survey dataset were analysed statistically to determine the overall uncertainty for each survey method. After the difference data were reviewed for quality, histograms of the elevation differences obtained from the subtraction of the TIN surface models were generated and evaluated. Standardised statistical tests were used to test the normality of the data distributions. The bathymetric survey elevation differences were determined to be non-normal distributions at the 95 percent confidence level. Therefore, a non-parametric approach was used to calculate the overall bathymetric survey method uncertainty [8]. The comparison of the TIN surface models from any two repeat bathymetric surveys should result in a difference value of zero. Graphically, this expected result would plot as a line directly on the ordinate at a value of zero; however, the results of the comparison of the TIN surface models show non-zero values with the average of the values offset from zero, as shown on Figure 3. The overall uncertainty of a particular bathymetric survey method is the result of both random variability and systematic bias in the calculated repeat survey difference data. Variability is the range of results about a median value and bias is the difference or offset between the true value and the average measured value. The variability and bias are illustrated in Figure 3. While true elevations of the sediment surface are unknown, the average differences between repeated measurements are expected to be zero over short time frames and under average environmental conditions. Given this relationship, the overall method uncertainty (U m ) was calculated using the following equation:
4 page 6 U m = + (V + B) (1) where: V = Average variability among the repeat survey set comparisons B = Maximum bias for the repeat survey set comparisons Survey method Overall uncertainty 1990s Table 2: Summary of overall survey method uncertainty The overall method uncertainty calculated by this equation includes the uncertainties associated with bottom surface irregularity, survey measurement precision, data processing, sounding data spacing, data interpolation, data comparison and random errors. The variability was determined for the 95 percent confidence level of the calculated differences, consistent with the criteria specified in the Engineering and Design Manual for Hydrographic Surveying [6]. Equation 1 was used to calculate the overall uncertainty of the 1980s and 1990s survey methods and the results are presented in Table 2. The values in Table 2 indicate that there is significantly less overall uncertainty in the 1990s method, which is attributable to the higher precision of the instrumentation used in this method. The overall uncertainty when comparing the actual Passaic River bathymetric survey datasets collected by the 1980s or 1990s methods consists of the uncertainties for each survey method as shown in Figure 4. The overall Figure 4: Components of overall comparison uncertainty uncertainty of the comparison (U c ) was estimated using the following equation: U c =(+U m1 ) + (+U m2 ) (2) where: U m1 = Overall uncertainty of the first survey in the comparison set U m2 = Overall uncertainty of the second survey in the comparison set The overall uncertainty for comparison of bathymetric survey data collected using the 1980s and 1990s methods was calculated using Equation 2 and the results are presented in Table 3. When comparing two different surveys to determine the changes in sediment elevation that have occurred during the time between the two surveys, elevation differences within the range listed in Table 3 are considered indeterminate because they fall within the range of the overall uncertainty. As a result, elevation differences that are less than or equal to this magnitude cannot be used to draw conclusions regarding changes in sediment elevation. Comparison results outside of the range of the overall uncertainty values can be used to reasonably interpret changes in sediment elevation during the time between surveys. Survey data comparison Overall uncertainty 1990s vs. 1990s s vs vs vs Table 3: Overall uncertainties from bathymetric survey data comparison Application of Overall Uncertainty to Passaic River Bathymetric Data Using the comparison methodology and overall uncertainty values presented in Table 3, three bathymetric comparisons were made using four Passaic River bathymetric datasets: 1996 vs This comparison was completed to evaluate river bottom elevation changes over a relatively short time frame (1.6 years). In addition, the US Geological Survey (USGS) records from this time frame show moderate peaks in Passaic River flow with a peak flow event occurring within one month prior to the 1996 survey. Therefore, comparison of these surveys should provide an estimate of changes in the net elevation during a relatively short time frame with a significant peak river flow event occurring just prior to the concluding survey vs This comparison was completed to evaluate river bottom elevation changes over an intermediate time frame (approximately 2.2 years) vs This comparison was completed to evaluate changes in river bottom elevation over the longest 1990s survey method time frame available (approximately 6.5 years). Each of the comparisons was made with bathymetric data comprising five reaches of the lower Passaic River including Point No Point, Harrison, Newark, Kearny and Arlington as shown in Figure 1. Since these comparisons include only datasets acquired using 1990s survey methods, an overall uncertainty of ±0.12 metre (Table 3) was applied to the calculated differences. Differences that fall within this range of overall uncertainty are indeterminate. Positive values greater than metre indicate an increase in the bottom elevation over time (i.e. deposition). Negative values less than metre indicate a decrease in the bottom elevation over time (i.e. erosion). Discussion of Bathymetric Data Comparison Results The results of the bathymetric comparisons are shown as histograms indicating frequency of occurrence versus elevation difference in Figures 5, 6 and 7, representing comparisons between 1996 vs. 1995, 1997 vs and 2001 vs. 1995, respectively. Results of the comparisons No. 118 October 2005 THE HYDROGRAPHIC JOURNAL
5 page 7 Figure 5: Elevation difference frequency, 1996 vs Figure 6: Elevation difference frequency, 1997 vs Figure 7: Elevation difference frequency, 2001 vs Comparison Time between surveys Percentage of total elevation differences (years) Indeterminate a Deposition b Erosion c 1996 vs vs vs Table 4: Summary of Statistics from Bathymetric Comparisons are also presented in Tables 4 and 5. Table 4 summarises the percentage of the total elevation differences for all three comparisons that are either indeterminate, show deposition, or show erosion. Table 5 summarises the magnitude of the elevation differences calculated outside the range of overall uncertainty for both positive (sediment deposition) and negative (sediment erosion) elevation differences. The range, average and the 99th percentile for the given comparison differences are shown. The upper and lower 1 percent (as indicated by the 99th percentile) was used to delineate the greatest positive and negative elevation differences for the evaluation of potential causes. In addition to representing the greatest magnitude of change for a given comparison, the upper and lower 1 percent of the calculated differences provided a manageable number of data points to evaluate. Similar results were found in the comparisons of the surveys performed less than 3 years apart (i.e vs and 1997 vs. 1995). As shown in Table 4, about 55 percent of the data from these comparisons are indeterminate. About 34 to 37 percent of the data show deposition ranging from to metres, with average elevation differences ranging from to Deposition was greater in frequency and in magnitude compared to erosion. Approximately 8 to 12 percent of the data show erosion ranging from to metres, with an average ranging from to metre. The amount of indeterminate data is approximately 20 percent less in the bathymetric comparison spanning 6.5 years (i.e vs. 1995). In this comparison, the data indicating deposition are also approximately 20 percent greater, while the percentage indicating erosion remains relatively unchanged from the other comparisons. Similar to the results of the other two comparisons, the percentage indicating deposition is significantly greater than the percentage indicating erosion. Table 5 also demonstrates that the elevation differences for a very small percentage of the data (less than 1 percent of the total data points, as indicated by the 99th percentile) are significantly greater than the average values. To examine the potential causes of these changes, the areas in which these greater differences occurred were evaluated on a site map of the river. The higher positive differences Notes: a. Elevation difference between and m. b. Elevation difference greater than m. c. Elevation difference less than m.
6 page 8 Positive elevation differences Negative elevation differences 99th 99th Comparison Range Average Percentile Range Average Percentile 1996 vs to to vs to to vs to to Table 5: Summary of elevation differences outside the range of uncertainty Note: All values are relative to the range of uncertainty of m were located at four locations within the river: in the middle of the channel in the Kearny Reach and Newark Reach, inside the river bend of the Newark Reach and at the upriver end of the Point No Point Reach (Figure 8). Consistent with the long-term net depositional environment of the lower Passaic River, the higher positive differences occurred at locations that are known areas of relatively low water velocities, encouraging increased deposition. The greatest negative differences occurred at two distinct locations within the river: in the Point No Point Reach just south of the bend near a vessel berthing dock and adjacent to columns that support a railway bridge at the lower portion of the Harrison Reach (Figure 8). While inconsistent with the net depositional environment of the lower Passaic River, the higher negative difference locations correspond to areas where turbulence from vessel propeller wash or high water velocities from constriction of the river by the bridge supports may induce erosive forces in localised areas. The calculated differences from these three comparisons of Passaic River bathymetric survey data are consistent with the expected morphological processes for the river system. Conclusions Relative changes in sediment surface elevation for any given area can be estimated by comparing bathymetric survey data using the standardised methodology presented in this paper. This methodology takes into consideration the uncertainties inherent in the differences in the survey technology, level of survey precision and the process used to compare the data. The methodology and uncertainty factors presented for the comparison of bathymetric survey data are empirically based and repeatable. The use of the overall uncertainty ranges determined for bathymetric survey data collected by the 1980s and 1990s methods is essential to make valid interpretations of elevation differences between surveys. In comparing two different surveys, elevation differences of a predictable magnitude should be expected solely due to the level of precision of each survey and the method used for comparing surveys. Elevation differences that are smaller than, or equal to, these uncertainty factors cannot be used to draw conclusions quantifying sediment elevation changes. The results of comparisons of recent Passaic River bathymetry using the methods and uncertainties derived by this study show that the calculated elevation differences outside the range of overall uncertainty are consistent with the expected naturallyoccurring river processes or are caused by location-specific anthropogenic influences. Figure 8: Location of greatest positive and negative elevation differences No. 118 October 2005 THE HYDROGRAPHIC JOURNAL
7 page 9 biographies Dr John Herzog is a Principal at Floyd Snider, an environmental engineering firm in Seattle, Washington, USA. Dr Herzog is an accomplished geologist and oceanographer with more than 12 years experience using hydrographic information in his work comprising remedial design, strategy development and environmental management. Aaron Bradshaw is a doctoral candidate in Ocean Engineering at the University of Rhode Island in Narragansett, Rhode Island, USA. Mr Bradshaw is an ocean engineer with almost 9 years experience studying marine geomechanics, applying his knowledge to sediment remediation projects requiring accurate slope stability assessments. FOOTNOTES: 1 Survey precision is the ability to replicate a given measurement (i.e. to get the same result for the same survey point) regardless of accuracy or the true value for that point. Two measurements comprise an individual bathymetric survey data point: the location where the depth measurement is taken and the distance to the bottom (which is converted to elevation). 2 The term overall uncertainty has been adopted in this paper to refer to the uncertainty associated with both the individual survey methods (Um) and the uncertainty in comparing data from two individual surveys (Uc). 3 Because of the minor differences in the equipment and procedures used for the 1986 and 1989 surveys, a repeat survey was completed for each of these 1980s survey methods. 4 A subtraction grid is an array of evenly spaced points arranged within the limits of the TIN surface model boundaries. ACKNOWLEDGMENTS The authors would like to acknowledge Ocean Surveys, Inc. for conducting the field studies in support of this project. Additionally, Tierra Solutions, Inc. is recognised for funding this project. REFERENCES Hicks, D M and Hume, T M (1994). Determining Sand Volumes and Bathymetric Change on and Ebb-Tidal Delta. Journal of Coastal Research, 13(2), Gibbs, A E and Gelfenbaum, G. (1999). Bathymetric Change Off the Washington- Oregon Coast. Coastal Sediments 99 Proceedings of the 4th International Conference on Coastal Engineering and Coastal Sediment Processes. American Society of Civil Engineers. Long Island, New York, June Byrnes, M R, Baker, J L and Li, F (2002). Quantifying potential measurement errors associated with bathymetric change analysis. ERDC/CHL CHETN-IV-50, US Army Corps of Engineers Research and Development Center, Vicksburg, Mississippi. Johnston, S (2003). Uncertainty in Bathymetric Surveys. ERDC/CHL CHETN-IV- 59, US Army Corps of Engineers Research and Development Center, Vicksburg, Mississippi. March Van Der Wal, D and Pye, K (2003). The use of historical bathymetric charts in a GIS to assess morphological change in estuaries. The Geographical Journal 169(1): USACE - US Army Corps of Engineers (2002). Engineering and Design Manual for Hydrographic Surveying. EM , 1 January AutoCAD Release 14, Autodesk, San Rafael, California. Daniel, W W (1978). Applied Nonparametric Statistics. Houghton Mifflin Company, Boston. swathe services Providing swathe bathymetry services to professional survey companies Swathe Services specialise in providing turn key solutions to worldwide shallow water swathe bathymetry projects. We offer the latest GeoSwath Plus systems including all peripheral equipment with highly experienced survey operators. If you are considering placing a bid on any future swathe contracts but do not have experienced staff or the resources to purchase the equipment, then we can help from the initial stages to producing the final products. For further information and a full list of equipment and personnel availability, please contact us on: Telephone: +44 (0) enquiries@swathe-services.com
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