Mengqi Xiong is a Master of Science student in the Department of Civil Engineering at North Dakota State University. She holds a B.S. degree in Water and Wastewater Engineering from Beijing University of Civil Engineering and Architecture, China, obtained in 2012. Her current research focuses on estimating sediment, nitrogen, and phosphorus loads into Lake Ashtabula, North Dakota, using the Soil and Water Assessment Tool (SWAT) model.
Application of Soil and Water Assessment Tool (SWAT) Model for Estimating Nutrient Loads to Lake Ashtabula, ND, under Different Climate Scenarios
Fellow: Mengqi Xiong
Advisor: G. Padmanabhan, Professor, Department of Civil Engineering, North Dakota State University
Co-Advisor: Zhulu Lin, Assistant Professor, Department of Agriculture and Biosystems Engineering, North Dakota State University
Degree Progress: M.S. in Civil Engineering, expected graduation in Spring2014.
Surface water quality impairment resulting from point and non-point sources pollution is of concern for watershed and water resource management. Therefore, Section 303(d) of the Clean Water Act and the U.S. Environmental Protection Agency’s (USEPA) Water Quality Planning and Management Regulations require states to identify and list the impaired and threatened surface waters within their boundaries, to prioritize them, and to develop Total Maximum Daily Loads (TMDLs) for the pollutants of concern. The 2012 Section 303(d) TMDL list for North Dakota has targeted 45 water bodies for completion by the end of 2014. Lake Ashtabula is listed as impaired due to excess nutrients and eutrophication (http://iaspub.epa.gov/tmdl_waters10/attains_impaired_waters.impaired_waters_list?p_state=ND&p_cycle=2012). Lake Ashtabula is a large impoundment on the main stem of the Sheyenne River. It is a U.S. Army Corps of Engineers multipurpose reservoir built for flood protection, recreation and irrigation.
Watershed modeling is an integral part of the TMDL development process of estimating nutrient loads from point and non-point sources to the receiving waters. Of all the suitable models for TMDL development, SWAT has been extensively applied for TMDL development and ArcSWAT provides a user-friendly GIS interface for developing site-specific SWAT models. SWAT is a semi-distributed watershed model and requires spatially explicit topographical, land use, soils, and meteorological data (such as precipitation, air temperature, and evapotranspiration, etc.) as model inputs. SWAT has also been applied to assess the impact of potential climate variability and change on nutrient loads to surface waters.
Our study will develop a SWAT model for the Lake Ashtabula watershed that drains the upper Sheyenne River basin (SRB) and a portion of the middle SRB for nutrient TMDL development purpose. The SWAT model will also be used to investigate the impact of the Devils Lake diversion on the water quality in Lake Ashtabula under different climate scenarios.
The objectives of the study are:
This study can be divided into three stages: database development, model development, and evaluation of results. The database development for model setup and calibration has been done. The input data: include topographic, soil, land use, management, and weather data. The calibration data include daily streamflow observations and bi-weekly measurements of concentrations of water quality parameters. The model development is ongoing. We are currently using ArcSWAT, the GIS interface of SWAT, to setup the SWAT model for Lake Ashtabula watershed. A careful examination of the watershed is required to separate the non-contributing drainage area. The curve number is one of the most sensitive parameters and therefore will also need careful evaluation.
Expected Outcomes and Significance:
A fully calibrated and operational SWAT model will be developed for the Lake Ashtabula watershed to estimate nutrient loads to Lake Ashtabula for TMDL development. The SWAT model will also be coupled with a reservoir water quality model to study nutrient transport processes on upland and in surface water bodies. The SWAT model will also be used to investigate the impact of the Devils Lake diversion on the water quality in Lake Ashtabula under different climate scenarios. This proposed project will benefit watershed model development for TMDL purposes and surface water quality management in North Dakota.
Advisor: G. Padmanabhan, Ph.D.
Co-Advisor: Zhulu Lin, Ph.D.