SEDIMENT TRANSPORT IN A SHALLOW COASTAL ESTUARY DURING THE WINTER SEASON1

ABSTRACT: This project analyzes suspended sediment flux through the upper Barataria basin in Louisiana during the winter season defined from November through April. The Barataria is a shallow coastal estuary located in southeastern Louisiana. The controls exerted by environmental parameters (such as wind or atmospheric pressure) in wetlands‐shallow bay ecosystems on transport of water and sediment were examined. Water samples were taken at a bayou (which serve as the inlet for flow to the estuary) on a regular basis. These samples were analyzed for total suspended solids and volatile suspended solids. Velocity, depth, temperature, salinity, conductivity, and meteorological measurements were all recorded at the time of each sampling. A multi‐parameter field probe was employed to continually monitor turbidity, water level, conductivity, and temperature during frontal events. These data were used in a regression analysis to examine the factors that drive carbon flux in the region. Investigations have determined that synoptic climate and prevailing weather conditions explain much of the variations in water levels, flow circulation patterns, salinity, and suspended sediment. Relatively small amounts of sediment appear to leave the estuary during normal tidal activity, but winter storm fronts result in significant fluxes of sediment in both up‐basin and down‐basin directions.     

Estimating Forest Ecosystem Evapotranspiration at Multiple Temporal Scales With a Dimension Analysis Approach1

Abstract:  It is critical that evapotranspiration (ET) be quantified accurately so that scientists can evaluate the effects of land management and global change on water availability, streamflow, nutrient and sediment loading, and ecosystem productivity in watersheds. The objective of this study was to derive a new semi‐empirical ET modeled using a dimension analysis method that could be used to estimate forest ET effectively at multiple temporal scales. The model developed describes ET as a function of water availability for evaporation and transpiration, potential ET demand, air humidity, and land surface characteristics. The model was tested with long‐term hydrometeorological data from five research sites with distinct forest hydrology in the United States and China. Averaged simulation error for daily ET was within 0.5 mm/day. The annual ET at each of the five study sites were within 7% of measured values. Results suggest that the model can accurately capture the temporal dynamics of ET in forest ecosystems at daily, monthly, and annual scales. The model is climate‐driven and is sensitive to topography and vegetation characteristics and thus has potential to be used to examine the compounding hydrologic responses to land cover and climate changes at multiple temporal scales.     

Development of a SWAT Patch for Better Estimation of Sediment Yield in Steep Sloping Watersheds1

Abstract: The watershed scale Soil and Water Assessment Tool (SWAT) model divides watersheds into smaller subwatersheds for simulation of rainfall‐runoff and sediment loading at the field level and routing through stream networks. Typically, the SWAT model first needs to be calibrated and validated for accurate estimation through adjustment of sensitive input parameters (i.e., Curve Number values, USLE P, slope and slope‐length, and so on). However, in some instances, SWAT‐simulated results are greatly affected by the watershed delineation and Digital Elevation Models (DEM) cell size. In this study, the SWAT ArcView GIS Patch II was developed for steep sloping watersheds, and its performance was evaluated for various threshold values and DEM cell size scenarios when delineating subwatersheds using the SWAT model. The SWAT ArcView GIS Patch II was developed using the ArcView GIS Avenue program and Spatial Analyst libraries. The SWAT ArcView GIS Patch II improves upon the SWAT ArcView GIS Patch I because it reflects the topographic factor in calculating the field slope‐length of Hydrologic Response Units in the SWAT model. The simulated sediment value for 321 subwatersheds (watershed delineation threshold value of 25 ha) is greater than that for 43 subwatersheds (watershed delineation threshold value of 200 ha) by 201% without applying the SWAT ArcView GIS Patch II. However, when the SWAT ArcView GIS Patch II was applied, the difference in simulated sediment yield decreases for the same scenario (i.e., difference in simulated sediment with 321 subwatersheds and 43 subwatersheds) was 12%. The simulated sediment value for DEM cell size of 50 m is greater than that for DEM cell size of 10 m by 19.8% without the SWAT ArcView GIS Patch II. However, the difference becomes smaller (3.4% difference) between 50 and 10 m with the SWAT ArcView GIS Patch II for the DEM scenarios. As shown in this study, the SWAT ArcView GIS Patch II can reduce differences in simulated sediment values for various watershed delineation and DEM cell size scenarios. Without the SWAT ArcView GIS Patch II, variations in the SWAT‐simulated results using various watershed delineation and DEM cell size scenarios could be greater than those from input parameter calibration. Thus, the results obtained in this study show that the SWAT ArcView GIS Patch II should be used when simulating hydrology and sediment yield for steep sloping watersheds (especially if average slope of the subwatershed is >25%) for more accurate simulation of hydrology and sediment using the SWAT model. The SWAT ArcView GIS Patch II is available at http://www.EnvSys.co.kr/~swat for free download.     

Entrainment mortality of Ichthyoplankton: Detectability and precision of estimates

The ability to detect and to develop a precise and accurate estimate of the entrainment mortality fraction is an important step in projecting power plant impacts on future fish population levels. Recent work indicates that these mortailities may be considerably less than 100% for some fish species in the early life stages. Point estimates of the entrainment mortality fraction have been developed based on probabilistic arguments, but the precision of these estimates has not been studied beyond the simple statistical test of the null hypothesis that no entrainment mortaility exists.The ability to detect entrainment mortality is explored as a function of the sample sizes (numbers of organisms collected) at the intake and discharge sampling stations of a power plant and of the proportion of organisms found alive in the intake samples (intake survival). Minimum detectable entrainment mortality, confidence interval width, and type II error (probability of accepting the null hypothesis of no entrainment mortality when there is mortality) are considered. Increasing sample size and/or decreasing sampling mortality will decrease the minimum detectable entrainment mortality, confidence interval width, and type II error for a given level of type I error.The results of this study are considered in the context of designing useful monitoring programs for determining the entrainment mortality fraction. Preliminary estimates of intake survival and the entrainment mortality fraction can be used to obtain estimates of the sample size needed for a specified level of confidence interval width or type II error. Final estimates of the intake survival and the entrainment mortality fraction can be used to determine the minimum detectable entrainment mortality and the type II error.     

Applications of Explicitly Incorporated/Post‐Processing Measurement Uncertainty in Watershed Modeling

In the field of watershed modeling, the impact of measurement uncertainty (MU) on calibration results indicates the potential issue of inaccurate model predictions. It is important to note that MU refers to the uncertainty in measured data such as flow and nutrient values that are used to evaluate model outputs. The calculation of error statistics assuming measured data are deterministic may not be appropriate as has been frequently stated in literature. Although MU can affect model calibration results, it is rarely incorporated in modeling practice. MU can be incorporated in two schemes: explicitly incorporated (MU‐EI) during model calibration and post‐processed (MU‐PP) after calibration is completed. In this study, both schemes are implemented in a case study of the Arroyo Colorado Watershed, Texas. Unexpectedly, no substantial differences were observed between each scheme for flow predictions. Although MU did not cause dramatic differences in most sediment and NH₄‐N predictions, error statistics were affected in cases with MU greater than 50%, especially for sediment and NH₄‐N. Therefore, it is concluded that MU may not exert a significant impact on model predictions until certain threshold is reached. This study demonstrates that high levels of uncertainty in measured calibration/validation data significantly affect parameter estimation, especially in the auto‐calibration process.     

Using SWAT to Model Streamflow in Two River Basins With Ground and Satellite Precipitation Data1

Abstract: Both ground rain gauge and remotely sensed precipitation (Next Generation Weather Radar – NEXRAD Stage III) data have been used to support spatially distributed hydrological modeling. This study is unique in that it utilizes and compares the performance of National Weather Service (NWS) rain gauge, NEXRAD Stage III, and Tropical Rainfall Measurement Mission (TRMM) 3B42 (Version 6) data for the hydrological modeling of the Middle Nueces River Watershed in South Texas and Middle Rio Grande Watershed in South Texas and northern Mexico. The hydrologic model chosen for this study is the Soil and Water Assessment Tool (SWAT), which is a comprehensive, physical‐based tool that models watershed hydrology and water quality within stream reaches. Minor adjustments to selected model parameters were applied to make parameter values more realistic based on results from previous studies. In both watersheds, NEXRAD Stage III data yields results with low mass balance error between simulated and actual streamflow (±13%) and high monthly Nash‐Sutcliffe efficiency coefficients (NS > 0.60) for both calibration (July 1, 2003 to December 31, 2006) and validation (2007) periods. In the Middle Rio Grande Watershed NEXRAD Stage III data also yield robust daily results (time averaged over a three‐day period) with NS values of (0.60‐0.88). TRMM 3B42 data generate simulations for the Middle Rio Grande Watershed of variable qualtiy (MBE = +13 to ?16%; NS = 0.38‐0.94; RMSE = 0.07‐0.65), but greatly overestimates streamflow during the calibration period in the Middle Nueces Watershed. During the calibration period use of NWS rain gauge data does not generate acceptable simulations in both watersheds. Significantly, our study is the first to successfully demonstrate the utility of satellite‐estimated precipitation (TRMM 3B42) in supporting hydrologic modeling with SWAT; thereby, potentially extending the realm (between 50°N and 50°S) where remotely sensed precipitation data can support hydrologic modeling outside of regions that have modern, ground‐based radar networks (i.e., much of the third world).     

Fine‐Sediment Loadings to Lake Tahoe1

Abstract: Over the past 35 years, a trend of decreasing water clarity has been documented in Lake Tahoe, attributable in part to the delivery of fine‐grained sediments emanating from upland and channel sources. The overall objective of the research reported here was to determine the amount of fine sediment delivered to Lake Tahoe from each of the 63 contributing watersheds. The research described in this report used combinations of field‐based observations of channel and bank stability with measured and simulated data on fine‐sediment loadings to estimate fine‐sediment loadings from unmonitored basins throughout the Lake Tahoe Basin. Loadings were expressed in the conventional format of mass per unit time but also in the number of particles finer than 20 μm, the latter for future use in a lake‐clarity model. The greatest contributors of fine sediment happened to be those with measured data, not requiring extrapolation. In descending order, they are as follows: Upper Truckee River [1,010 tonnes per year (T/year)], Blackwood Creek (846 T/year), Trout Creek (462 T/year), and Ward Creek (412 T/year). Summing estimated values from the contributing watersheds provided an average, annual estimate of fine‐sediment (<0.063 mm) loadings to the lake of 5,206 T/year. A total of 7.79E + 19 particles in the 5‐20 μm fraction were calculated to enter Lake Tahoe in an average year with the Upper Truckee River accounting for almost 25% of the total. Contributions from Blackwood, Ward, Trout, and Third creeks account for another 23% of these very fine particles. Thus, these five streams making up about 40% of the basin area, account for almost 50% of all fine‐sediment loadings to the lake. Contribution of fine sediment from streambank erosion were estimated by developing empirical relations between measured or simulated bank‐erosion rates with a field‐based measure of the extent of bank instability along given streams. An average, annual fine‐sediment loading from streambank erosion of 1,305 T/year was calculated. This represents about 25% of the average, annual fine‐sediment load delivered to the lake from all sources. The two largest contributors, the Upper Truckee River (639 T/year) and Blackwood Creek (431 T/year), account for slightly more than 80% of all fines emanating from streambanks, representing about 20% of the fine sediment delivered to Lake Tahoe from all sources. Extrapolations of fine‐sediment loadings to the unmonitored watersheds are based on documented empirical relations, yet contain a significant amount of uncertainty. Except for those values derived directly from measured data, reported results should be considered as estimates.     

WATER QUALITY MODEL OUTPUT UNCERTAINTY AS AFFECTED BY SPATIAL RESOLUTION OF INPUT DATA1

ABSTRACT: Resolution of the input GIS data used to parameterize distributed‐parameter hydrologic/water quality models may affect uncertainty in model outputs and impact the subsequent application of model results in watershed management. In this study we evaluated the impact of varying spatial resolutions of DEM, land use, and soil data (30 × 30 m, 100 × 100 m, 150 × 150 m, 200 × 200 m, 300 × 300 m, 500 × 500 m, and 1,000 × 1,000 m) on the uncertainty of SWAT predicted flow, sediment, NO₃‐N, and TP transport. Inputs included measured hydrologic, meteorological, and watershed characteristics as well as water quality data from the Moores Creek watershed in Washington County, Arkansas. The SWAT model output was most affected by input DEM data resolution. A coarser DEM data resolution resulted in decreased representation of watershed area and slope and increased slope length. Distribution of pasture, forest, and urban areas within the watershed was significantly affected at coarser resolution of land use and resulted in significant uncertainty in predicted sediment, NO₃‐N, and TP output. Soils data resolution had no significant effect on flow and NO₃‐N predictions; however, sediment was overpredicted by 26 percent, and TP was underpredicted by 26 percent at 1,000 m resolution. This may be due to change in relative distribution of various hydrologic soils groups (HSGs) in the watershed. Minimum resolution for input GIS data to achieve less than 10 percent model output error depended upon the output variable of interest. For flow, sediment, NO₃‐N, and TP predictions, minimum DEM data resolution should range from 30 to 300 m, whereas minimum land use and soils data resolution should range from 300 to 500 m.     

TESTS OF THE CREAMS MODEL ON AGRICULTURAL FIELDS IN VERMONT1

ABSTRACT: The computer model, CREAMS, has been developed for field-sized agricultural areas to aid in best management practices evaluation and planning. A test of CREAMS was performed by comparing monthly observed and simulated values for runoff, sediment, and phosphorus exports from two agricultural fields in Vermont to determine the applicability of the model in cold climates. Water quality samples were collected from field runoff and analyzed for both total suspended solids and total phosphorus. Generally, exports were overestimated during low flow months and underestimated during high flow months. Significant r²values (p <0.05), ranging from 0.78 to 0.90, between simulated and observed data were found for all comparisons except for sediment export from one field. Comparisons of the slopes of the regressions between observed and simulated values and the ideal slope of one using t-tests revealed significant differences between simulated and observed monthly runoff, sediment, and phosphorus exports. It is postulated that this lack of adequate prediction could be attributed to the use of average monthly, instead of daily, temperature and solar radiation in calculations of evapotranspiration and snowmelt, and the use of static parameter values for parameters that vary seasonally.     

AFTER THE 1993 FLOOD: A WATER AND SURFICIAL BED SEDIMENT QUALITY SCENARIO ON THE ILLINOIS AND UPPER MISSISSIPPI RWERS1

ABSTRACT: Effects of the 1993 flood on river water and sediment quality were investigated using historical data and data collected from the Illinois River and Upper Mississippi River in a post‐flood period. Overall the post‐flood results showed systematic reductions and individual changes in the water and sediment constituents. The reductions in sediment metals and nutrients were most obvious at the Keokuk and Lock and Dam 26 stations. By analyzing and comparing the physical changes to the changes in water and sediment constituents at each station, it was found that physical processes such as sediment entrainment and, more importantly, the removal of fine sediment to be the main causes for the reduced concentrations in sediment constituents. On the other hand, sediment redistribution and associated secondary contamination could have caused the emergence of several water and sediment constituents that were undetected before the flood.     

Estimation of Suspended‐Sediment Concentration From Total Suspended Solids and Turbidity Data for Kentucky, 1978‐19951

Williamson, Tanja N. and Charles G. Crawford, 2011. Estimation of Suspended‐Sediment Concentration From Total Suspended Solids and Turbidity Data for Kentucky, 1978‐1995. Journal of the American Water Resources Association (JAWRA) 47(4):739‐749. DOI: 10.1111/j.1752‐1688.2011.00538.x Abstract: Suspended sediment is a constituent of water quality that is monitored because of concerns about accelerated erosion, nonpoint contamination of water resources, and degradation of aquatic environments. In order to quantify the relationship among different sediment parameters for Kentucky streams, long‐term records were obtained from the National Water Information System of the U.S. Geological Survey. Suspended‐sediment concentration (SSC), the parameter traditionally measured and reported by the U.S. Geological Survey, was statistically compared to turbidity and total suspended solids (TSS), two parameters that are considered surrogate data. A linear regression of log‐transformed observations was used to estimate SSC from TSS; 72% of TSS observations were less than coincident SSC observations; however, the estimated SSC values were almost as likely to be overestimated as underestimated. The SSC‐turbidity relationship also used log‐transformed observations, but required a nonlinear, breakpoint regression that separated turbidity observations ≤6 nephelometric turbidity units. The slope for these low turbidity values was not significantly different than zero, indicating that low turbidity observations provide no real information about SSC; in the case of the Kentucky sediment record, this accounts for 30% of the turbidity observations.     

Physically Based,Hydrologic Model Results Based on Three Precipitation Products1

Abstract: The main objective of the study is to examine the accuracy of and differences among simulated streamflows driven by rainfall estimates from a network of 22 rain gauges spread over a 2,170 km² watershed, NEXRAD Stage III radar data, and Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite data. The Gridded Surface Subsurface Hydrologic Analysis (GSSHA), a physically based, distributed parameter, grid‐structured, hydrologic model, was used to simulate the June‐2002 flooding event in the Upper Guadalupe River watershed in south central Texas. There were significant differences between the rainfall fields estimated by the three types of measurement technologies. These differences resulted in even larger differences in the simulated hydrologic response of the watershed. In general, simulations driven by radar rainfall yielded better results than those driven by satellite or rain‐gauge estimates. This study also presents an overview of effects of land cover changes on runoff and stream discharge. The results demonstrate that, for major rainfall events similar to the 2002 event, the effect of urbanization on the watershed in the past two decades would not have made any significant effect on the hydrologic response. The effect of urbanization on the hydrologic response increases as the size of the rainfall event decreases.     

GIS‐BASED WATER QUALITY MODELING IN THE SANDUSKY WATERSHED,OHIO, USA1

ABSTRACT: This study focused on the Sandusky Watershed (SW) in Ohio, located within the Great Lakes Basin, with emphasis on two of its subwatersheds, namely Honey Creek (HC) and Rock Creek (RC). The goal was to assess the capabilities of the Soil and Water Assessment Tool (SWAT) to simulate suspended sediment (SS), phosphorus (P) and nitrogen (N) yield in the SW that contribute major sediment and nutrient loads into Lake Erie. The model was calibrated using water flow and water quality parameters for water years 1998 to 1999 and validated model simulations covering the period of water years 2000 to 2001 for monthly conditions. The validation of SS showed correlation coefficients of 0.29 (SW), 0.75 (HC) and 0.69 (RC). Correlation coefficients for P were 0.68 (SW), 0.78 (HC) and 0.37 (RC); for N0₂‐N 0.84 (HC) and 0.38 (RC); for N0₃‐N 0.27 (HC) and 0.76 (RC); for NH₃‐N 0.57 (SW), 0.49 (HC), and 0.13 (RC). In addition, mean errors, root mean square errors, Nash‐Sutcliffe coefficients, and graphs were used to compare simulated to measured data. Simulation success was variable with poor and good simulations, but in most cases, simulated water quality values followed the trend of measured data except for extreme (or intense) rainfall/runoff events. Reviews of 17 applications indicated that the SWAT is suitable for long term continuous simulations but not for storm events. A spatially distributed modeling approach generated maps showing the spatial distribution of SS, P, and N for each simulation element across the Sandusky Watershed.     

Carbon and nitrogen losses by surface runoff following changes in vegetation

Rainfall simulation experiments were conducted on annual grassland and coastal sage scrub hillslopes to determine the quantities of C and N removed by surface runoff in sediment and solution. Undisturbed coastal sage scrub soils have very high infiltration capacities (> 140 mm h(-1)), preventing the generation of surface runoff. Trampling disturbance to the sage scrub plots dramatically reduced infiltration capacities, increasing the potential for surface runoff and associated nutrient loss. Infiltration capacities in the grassland plots (30-50 mm h(-1)) were lower than in the sage scrub plots. Loss rates of dissolved C and N in surface runoff from grasslands were 0.5 and 0.025 mg m(-2) s(-1) respectively, with organic N accounting for more than 50% of the dissolved N. Total dissolved losses with simulated rainfall were higher than losses in simulations with just surface runoff, demonstrating the importance of raindrop impact in transferring solutes into the flow. Experimental data were incorporated into a numerical model of runoff and sediment transport to estimate hillslope-scale sediment-bound nutrient losses from grasslands. According to the model results, sediment-bound nutrient losses are sensitive to the density of vegetation cover and rainfall intensity. The model estimates annual losses in surface runoff of 0.2 and 0.02 g m(-2) for sediment-hound C and N, respectively. The results of this study suggest that conversion of coastal sage scrub to annual grasslands increases hillslope nutrient losses and may affect stream water quality in the region.     

HYSTAR Sediment Model: Distributed Two‐Dimensional Simulation of Watershed Erosion and Sediment Transport Using Time‐Area Routing

An erosion and sediment transport component incorporated in the HYdrology Simulation using Time‐ARea method (HYSTAR) upland watershed model provides grid‐based prediction of erosion, transport and deposition of sediment in a dynamic, continuous, and fully distributed framework. The model represents the spatiotemporally varied flow in sediment transport simulation by coupling the time‐area routing method and sediment transport capacity approach within a grid‐based spatial data model. This avoids the common, and simplistic, approach of using the Universal Soil Loss Equation (USLE) to estimate erosion rates with a delivery ratio to relate gross soil erosion to sediment yield of a watershed, while enabling us to simulate two‐dimensional sediment transport processes without the complexity of numerical solution of the partial differential governing equations. In using the time‐area method for routing sediment, the model offers a novel alternative to watershed‐scale sediment transport simulation that provides detailed spatial representation. In predicting four‐year sediment hydrographs of a watershed in Virginia, the model provided good performance with R² of 0.82 and 0.78 and relative error of ?35% and 11% using the Yalin and Yang's sediment transport capacity equations, respectively. Prediction of spatiotemporal variation in sediment transport processes was evaluated using maps of sediment transport rates, concentrations, and erosion and deposition mass, which compare well with expected behavior of flow hydraulics and sediment transport processes.     

MODELING DEVELOPED COASTAL WATERSHEDS WITH THE AGRICULTURAL NON-POINT SOURCE MODEL1

ABSTRACT: Many coastal states are facing increasing urban growth along their coast lines. The growth has caused urban non-point source nitrogen runoff to be a major contributor to coastal and estuarine enrichment. Water resource managers are responsible for evaluating the impacts from point and non-point sources in developed watersheds and developing strategies to manage future growth. Non-point source models provide an effective approach to these management challenges. The Agricultural Non-Point Source Model (AGNPS) permits the incorporation of important spatial information (soils, landuse, topography, hydrology) in simulating surface hydrology and nitrogen non-point source runoff. The AGNPS model was adapted for developed coastal watersheds by deriving urban coefficients that reflect urban landuse classes and the amount of impervious surface area. Popperdam Creek watershed was used for model parameter development and model calibration. Four additional watersheds were simulated to validate the model. The model predictions of the peak flow and total nitrogen concentrations were close to the field measurements for the five sub-basins simulated. Measured peak flow varied by 30 fold among the sub-basins. The average simulated peak flow was within 14 percent of the average measured peak flow. Measured total nitrogen loads varied over an order of magnitude among the sub-basins yet error between the measured and simulated loads for a given sub-basin averaged 5 percent. The AGNPS model provided better estimates of nitrogen loads than widely used regression methods. The spatial distribution of important watershed characteristics influenced the impacts of urban landuse and projecting future residential expansion on runoff, sediment and nitrogen yields. The AGNPS model provides a useful tool to incorporate these characteristics, evaluate their importance, and evaluate fieldscale to watershed-scale urban impacts.     

Coupling PCSWMM and WASP to Evaluate Green Stormwater Infrastructure Impacts to Storm Sediment Loads in an Urban Watershed

We coupled rainfall–runoff and instream water quality models to evaluate total suspended solids (TSS) in Wissahickon Creek, a mid‐sized urban stream near Philadelphia, Pennsylvania. Using stormwater runoff and instream field data, we calibrated the model at a subdaily scale and focused on storm responses. We demonstrate that treating event mean concentrations as a calibration parameter rather than a fixed input can substantially improve model performance. Urban stormwater TSS concentrations vary widely in time and space and are difficult to represent simply. Suspended and deposited sediment pose independent stressors to stream biota and model results suggest that both currently impair stream health in Wissahickon Creek. Retrofitting existing detention basins to prioritize infiltration reduced instream TSS loads by 20%, suggesting that infiltration mitigates sediment more effectively than detention. Infiltrating stormwater from 30% of the watershed reduced instream TSS loads by 47% and cut the frequency of TSS exceeding 100 mg/L by half. Settled loads and the frequency of high TSS values were reduced by a smaller fraction than suspended loads and duration at high TSS values. A widely distributed network of infiltration‐focused projects is an effective stormwater management strategy to mitigate sediment stress. Coupling rainfall–runoff and water quality models is an important way to integrate watershed‐wide impacts and evaluate how management directly affects urban stream health.     

Automatic Calibration of Hydrologic Models With Multi‐Objective Evolutionary Algorithm and Pareto Optimization1

Abstract: In optimization problems with at least two conflicting objectives, a set of solutions rather than a unique one exists because of the trade‐offs between these objectives. A Pareto optimal solution set is achieved when a solution cannot be improved upon without degrading at least one of its objective criteria. This study investigated the application of multi‐objective evolutionary algorithm (MOEA) and Pareto ordering optimization in the automatic calibration of the Soil and Water Assessment Tool (SWAT), a process‐based, semi‐distributed, and continuous hydrologic model. The nondominated sorting genetic algorithm II (NSGA‐II), a fast and recent MOEA, and SWAT were called in FORTRAN from a parallel genetic algorithm library (PGAPACK) to determine the Pareto optimal set. A total of 139 parameter values were simultaneously and explicitly optimized in the calibration. The calibrated SWAT model simulated well the daily streamflow of the Calapooia watershed for a 3‐year period. The daily Nash‐Sutcliffe coefficients were 0.86 at calibration and 0.81 at validation. Automatic multi‐objective calibration of a complex watershed model was successfully implemented using Pareto ordering and MOEA. Future studies include simultaneous automatic calibration of water quality and quantity parameters and the application of Pareto optimization in decision and policy‐making problems related to conflicting objectives of economics and environmental quality.     

AN ILLUSTRATION OF MODEL STRUCTURE IDENTIFICATION1

ABSTRACT: The purpose of this article is to discuss the importance of uncertainty analysis in water quality modeling, with an emphasis on the identification of the correct model specification. A wetland phosphorus retention model is used as an example to illustrate the procedure of using a filtering technique for model structure identification. Model structure identification is typically done through model parameter estimation. However, due to many sources of error in both model parameterization and observed variables and data, error-in-variable is often a problem. Therefore, it is not appropriate to use the least squares method for parameter estimation. Two alternative methods for parameter estimation are presented. The first method is the maximum likelihood estimator, which assumes independence of the observed response variable values. In anticipating the possible violation of the independence assumption, a second method, which coupled a maximum likelihood estimator and Kalman filter model, was presented. Furthermore, a Monte Carlo simulation algorithm is presented as a preliminary method for judging whether the model structure is appropriate or not.     

Measuring Suspended‐Sediment Concentration and Turbidity in the Middle Mississippi and Lower Missouri Rivers Using Landsat Data

The Middle Mississippi River (MMR) and lower Missouri River (MOR) provide critical navigation waterways, ecological habitat, and flood conveyance. They are also directly linked to processes affecting geomorphic and ecological conditions in the lower MR and Delta. For this study, a method was developed to measure suspended‐sediment concentration (SSC) and turbidity along the MMR and the lower MOR using Landsat imagery. Data from nine United States Geological Survey water‐quality monitoring stations were used to create a model‐development dataset and a model‐validation dataset. Concurrent gaging data were identified for available Landsat images to generate the datasets. Surface‐reflectance filters were developed to eliminate images with cirrus cloud coverage or vessel traffic. Using the filtered model‐development dataset, unique reflectance‐SSC and reflectance‐turbidity models were developed for three Landsat sensors: Landsat 8 Operational Land Imager, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 4–5 Thematic Mapper. Coefficient of determination values for the models ranged from 0.72 to 0.88 for the model‐development dataset. The model‐validation dataset was used to evaluate the performance of the models and had coefficient of determination values ranging from 0.62 to 0.79.