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United States Department of Agriculture

Agricultural Research Service

Related Topics

Research Project: Improving Computational Modeling in Support of Better Erosion and Sediment Movement Control in Agricultural Watersheds

Location: Watershed Physical Processes Research

2012 Annual Report

1a. Objectives (from AD-416):
Objective 1: Improve the capability, accuracy and efficiency of the computational modeling technology and methodology to better predict the free surface flows associated with physical processes, e.g. complex flows over irregular and varying topography resulting from storms, levee breaching and dam failure. (2.2) Objective 2: Integrate the improved free surface flow models with the erosion and sediment transport models to quantify and predict ephemeral gully development, dam and levee breaching, and sediment relocation and control during dam removal or failure. (2.1, 2.2, 2.4) Objective 3: Develop and upgrade models to better predict the movement and dispersion of agricultural contaminants and their interactions with the sediment and bed materials in surface water systems. (2.2) Objective 4: Integrate and improve decision support systems for watershed management that are reliable, computationally efficient, readily usable, and transferable. (2.3, 2.4)

1b. Approach (from AD-416):
In order to better assess and better predict soil erosion and sediment movement in the stream system of agricultural watershed, existing technology must be upgraded to assess and improve predictions for more realistic conditions in particular those that are encountered during extreme events that threatens life, property, and agricultural production areas. The objectives of this project relate to The Action Plan of the National Program NP211, Problem Area 2 concerning prediction and quantification of in-stream erosion and sedimentation processes. Specifically, the first objective addresses the need for improving the capability, accuracy, and efficiency of the computational modeling technology of free surface flows in stream systems of watersheds that must reflect more realistic and complex physical realizations, conditions and processes (2.2). The second objective relates to erosion and sediment movement during rapidly varying flows such as in gully development (2.1), dam failure and removal (2.1, 2.2), embankment erosion and channel migration (2.4). The third one relates to the transport and physical dispersion of sediment attached, dissolved, and exchanged between the sediment and water phase in open water bodies of the agricultural environment (2.2). The fourth objective concerns the development of decision support systems for better water management purposes such as for watershed protection, flood prevention, and environmental protection (2.3 and 2.4).

3. Progress Report:
Objective III: Develop and upgrade models to better predict the movement and dispersion of agriculture contaminants and their interaction with the sediment and material in surface water system. FY 12: Modify the National Center for Computational Hydroscience and Engineering's (NCCHE) water quality model for simulating the transport of contaminated sediment and the response of aquatic ecosystems after dam removal and failure. An aquatic ecology/ecotoxicology model has been incorporated into the one-dimensional modeling package CCHE1D for simulating hydrodynamic, sediment transport, contaminant transport, water quality, aquatic ecosystem, and ecotoxicology in channel networks. The model calculates water temperature, dissolved oxygen, biological oxygen demand, nitrogen, and phosphorus, and considers a basic food web structure consisting of four trophic levels: phytoplankton, zooplankton, forage fish, and predatory fish. It simulates the bioaccumulation of toxic chemicals in organisms and takes into account the effects of toxicity on the growth, grazing, and gamete mortality of the organisms. The model has been tested by simulating the water quality, aquatic ecosystem, poluychlorinated biphenyl (PCB) transport and bioaccumulation in the Upper Hudson River, New York, showing promising results. An updated numerical scheme for chemical transport were developed and implemented for CCHE2D pollutant transport module. The updated module and schemes were tested and verified using several analytical solutions. Combined with sediment transport model, the chemical module was applied to study scenarios of contaminant sediment transport of this field case. The flow, pollutants and contaminated sediment were from assumed failures of tailing dams of mines. The study was to assess the potential impacts on the drinking water quality in downstream reservoirs in case radioactively contaminated sediments and pollutants were discharged following the tailing dam failure. Simulations of unsteady flow and non-uniform suspended sediment and contaminant transport were conducted for two-year periods representing the wettest and driest hydrologic conditions for the area. The process of chemical adsorption-desorption on multiple suspended sediment particles was considered. The study focused on simulating the spatial and temporal variation of contaminant concentrations and residence time of contaminants in the polluted reservoirs. A dam removal related sediment transport and morphologic change case has been simulated using CCHE2D model and experimental data from literature. The processes of propagation of the erosion in the reservoir and deposition in the downstream channel reach were simulated very well. Preparation of simulating sediment transport and bed change using CCHE2D due to the Marmot Dam removal on Sandy River is underway. Measured field data with flow sediment transport were collected; computational mesh for the reservoir has been generated; flow and sediment transport simulation results will be reported in next period. During the 2011 spring floods in Mississippi River, the water surface elevations surpassed historic record level elevations and the situation was quite serious. Any breach of the levees along the Mississippi River would have caused considerable damage. USDA-ARS Crop Genetics Research in Stoneville, MS, asked NCCHE to perform 10 day simulations of the consequences of a levee breach at Mounds Landing near Greenville, MS. NCCHE used the newly developed DSS-WISE software with the solver CCHE2D-FLOOD to calculate the flood in a few hours and provided the ArcGIS compatible raster files of maximum flow depths, flood arrival times, flow velocities and discharges in x and y directions. These results were used in emergency management planning for the Crop Genetics Research Center. Objective IV: Integrate relevant NCCHE models in hydrology, hydraulics, soil erosion, sedimentation and water quality and provide training, technical support and maintenance of the integrated USDA-NCCHE models that are developed. FY 12: Porting CCHE1D Graphic User Interface and sediment transport models include RUSLE2, AnnAGNPS, CONCEPTS, CCHE1D, and CCHE2D with a common internet-based geographic information system (GIS) interface and database management system (Product 2.2.1); Develop a multi-objective and multi-constraint optimization module to identify the best compromised decision (Product 2.2.2). The newly developed ArcGIS based graphic user interface for one-dimensional hydro-dynamical model CCHE1D has been tested for robustness using the Goodwin Creek watershed hydrologic data. The functions of TOPAZ module: delineation of watershed boundary, sub-watersheds and stream network based on the critical source area and the minimum source channel length are all found to be working well. The model was run for the simulation of 10 storm events in Goodwin Creek watershed and the results were found to be satisfactory. Watershed model results are often used as input for CCHE1D. A utility module has been developed to read the output files from Soil and Water Assessment Tool (SWAT) watershed model and convert them into CCHE1D readable files for watershed type boundary conditions. The updated CCHE1D is ready and testing of these types of boundary conditions are undergoing using Goodwin Creek and Amana watershed data. We have newly developed flow control elements into CCHE1D in order to implement reservoirs and dams for operations of release flows through these in-stream structures. This newly developed capability enables CCHE1D to model flows in a large scale watershed with multiple reservoirs and dams. By means of adjoint sensitivity approach, an optimal control procedure has been developed and implemented in CCHE1D to control river flows in multiple reservoirs and downstream river reaches. Preliminary results have showed that this newly developed control approach is effective, and has a great potential to facilitate design, operation, and management of multiple in-stream structures such as reservoirs and dams in rivers and watershed. The research aims to develop a simulation-based optimization model to find the optimal solutions for flood prevention and erosion control in river and watershed by means of variational data assimilation and adjoint sensitivity approach. CCHE1D serves as a simulation model to compute flows, sediment transport, and morphological changes in rivers. An inverse model (i.e. an adjoint model) of CCHE1D has been developed to obtain sensitivity of water surface variations and morphological changes. The adjoint model was established for the flows and morphodynamic processes which CCHE1D are solving. A Limited-Memory Quasi-Newton (LMQN) optimization procedure with bound constraints for control variables is adopted to search for the optimal solutions of the nonlinear control problems on flows and morphology. By integrating with CCHE1D with its geographic information system (GIS) features, the optimization model is general so that it can solve the control problems on flooding/inundation and erosion in river and watershed. This integrated simulation-based optimization system has been tested to find the optimal control schedules for single and multiple control structures (e.g. floodgates) to satisfy the specific criteria for management of flood water and sediments in rivers and watershed. Specially, this model was successfully applied to find the best sediment release schedule in dam removal. It also has been applied to control morphological changes in alluvial rivers with various installations of control structures. The test results shows that this optimization is effective to find optimal locations and to determine optimal control actions of control structures (e.g. floodgates, dams, etc.) for the purpose of planning river flooding, managing sedimentation of fluvial rivers, etc. To reduce tedious work in model parameter calibration, an automatic calibration technique has been developed for calibrating CCHE1D and CCHE2D hydrodynamic models by using data-assimilation and optimization theories. The adjoint sensitivity analysis has been adopted to obtain a set of adjoint equations for the CCHE1D hydrodynamic model and to identify the roughness coefficients in channel network over watershed. The sensitivity-equation method was adopted to derive the sensitivity equations of the 2D shallow water equations in CCHE2D and to determine the roughness coefficients in the model. We have successfully validated a parameter identification code to identify Manning’s roughness coefficients in CCHE1D and CCHE2D which are spatially distributed along river reaches. During this period (2011-2012), the integrated simulation-optimization models (CCHE1D, 2D, and inverse models) are being updated to the new FORTRAN compiler (i.e. the Intel FORTRAN). The coupling between CCHE1D and SWAT using a file interface is being verified and validated. At the moment verification and validation tests are being carried out using the data from Amana watershed. This work is being performed in collaboration with researchers at the University of Iowa, who are providing the data. Additional verification is also being performed using the data from Goodwin Creek. NCCHE is using this opportunity to complete all missing data and thoroughly analyze the rainfall data for more than 30 rain gages. The corrected data will be used for validation purposes.

4. Accomplishments

Last Modified: 06/27/2017
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