1. NMDESS: A Decision Support System for Nutrient Management E. O. Mutlu 1, I. Chaubey 1, M. Matlock 1, R. Morgan 1, B. Haggard 1, D. E. Storm 2 Ecological Engineering Group 1 Biological & Agricultural Engineering Department - University of Arkansas, Fayetteville, AR 2 Biosystem & Agricultural Engineering Department-Oklahoma State University, Stillwater, OK Structure of NMDESS NMDESS is a knowledge-based computer system which integrates data, information, physical simulation models and economic analysis for solving specific watershed problems. The NMDESS has three components: data entry, a graphical user interface (GUI), and a GIS (Arc-IMS) (Figure 3). 020 Introduction Lake Eucha water quality is being degraded from excess algal growth, resulting in odor and taste problems in this critical drinking water supply. This excess growth is the result of an overabundance of nutrients in the lake, assumed to be primarily phosphorus from either point sources, such as City of Decatur municipal wastewater treatment plant, or from non point sources from pastures (Storm et al., 2001). Storm et al. (2001) attributed the majority of the phosphorus loading to non point sources such as pastures that received surface application of poultry litter. Phosphorus from the soil and land applied litter is transport during runoff to the stream and eventually to the lake. The eutrophication of the lake threatens the primary drinking water supplies of the cities of Tulsa, OK and Jay, OK. A decision support system (DSS) is an interactive computer based system that intends to help managers make decisions (Power, 1998). The overall goal of this study is to develop, implement and evaluate a nutrient management decision and education support system (NMDESS). The NMDESS will integrate a GIS ecosystem model with a stakeholder driven risk based nutrient management decision process, using bio-indicators and water quality data. ArkansasOklahoma 4010 Scenario 360 Scenario 360 is GIS based decision support software for planners and resource managers. It is an ArcMap extension that adds interactive analysis tools and a decision-making framework to ArcGIS (Communityviz, 2004), Scenario 360 helps view, analyze and understand potential alternatives and impacts via visual exploration and the construction and analysis of alternative scenarios (Communityviz, 2004), This software allows illustrating and discussing future scenarios in watershed and visualizing results in real time, Table 1 shows example watershed management scenarios, analyzed by SWAT, that will be used in Scenario 360, Figure 5 shows output display of litter application for current, scenario#1 (25 % increase in litter application) and scenario#2 (50 % increase in litter application). Figure 5 : Land management scenarios analysis result using scenario 360 model Figure 3 : Schematic of NMDESS Very Low Low Medium High Very High Selection Part NMDESS Education Analysis Deliberation Watershed Management Recommendation 020Kilometers4010 References Arnold, J. G., Srinivasan, R., Ramanarayanan, T. S., Bednarz, S. T. 1998. Large Area Hydrologic Modeling and Assessment Part II : Model Application. Journal of the American Water Resources Association. 34. 1. 91 Communityviz. 2004. (http://www.communityviz.com/index.asp?circuit=2&fuse=detail&cid=395) CE-QUAL-W2 Water Quality Model. 2002. (http://www.cee.pdx.edu/w2/,Web site designed by Kyle Muramatsu | Summer ASE 2002) Power, D. J.1998. What is a DSS. The online Executive Journal for Data-Intensive Decision Support.1. No 3. (http://dssresources.com/papers/whatisadss/index.html) Santhi, C., Arnold. J. G., Williams. J. G., Dugas. W. A., Srinivasan. R., and Hauck. L. M. 2001. Validation of the SWAT model on a large river basin with point and nonpoint sources. Journal of the American Water Resources Association. 37. (5): 1169-1188 Storm, D. E., White, M. J., Smolen, M. D., Zhang, H. 2001. Modeling Phosphorus Loading for the Lake Eucha Basin. Final Report. Oklahoma State University. Biosystems and Agricultural Engineering Department. 1. (http://biosystems.okstate.edu/home/dstorm/eucha/modeling/OSU_EuchaReport__ExecutiveSum mary_110101.pdf) Storm, D. E., White, M. J., Smolen, M. D. 2002. Modeling the Lake Eucha Basin Using SWAT 2000. Final Report. 4 (http://biosystems.okstate.edu/home/dstorm/eucha/modeling/Eucha_OSU_2002_SWAT2000.pdf) Wagner, K. and Woodruf, S. 1997. Phase 1 clean lakes project diagnostic and feasibility study of Lake Eucha. Final Report. Executive Summary. 1-148 Objectives The objectives of this study are to: Develop NMDESS to provide risk based information on nutrient sources and fate within Eucha watershed, Develop a stakeholder input and advisory structure to guide the development and implementation of NMDESS, Evaluate the effectiveness of NMDESS in the Eucha Watershed to develop management alternatives for implementation. Modeling System The modeling system consists of a watershed model (SWAT), a reservoir model (CE-QUAL-W2) and a decision support model (Scenario 360). SWAT Model SWAT (Soil and Water Assessment Tool) is a continuous daily time-step model which simulates the impacts of alternative land management practices on surface and ground water quality (Arnold et al., 1998), The model operates on a daily time step and allows a basin to be subdivided into grid cells or natural sub- watersheds (Santhi et al., 2001), SWAT model is the watershed model backbone for the NMDESS. It will be linked with a risk based scenario generator to predict flow, nutrient and sediment load from the watershed. The model will be calibrated and validated with available measured data. Table 1 lists the example land management scenarios that will be analyzed by the linked modeling system. Land cover Forest Pasture Urban Water Different export rates of litter 25% 50% 75% 100% Various grazing management Optimum grazing Over grazing No grazing Different soil nutrient status 100 soil test P 300 soil test P 500 soil test P 750 soil test P >1000 soil test P Point source reduction N and P 25% reduction 50% reduction 75% reduction 100% reduction Soluble P in the litter Table 1: List of scenarios and SWAT model outputs requested Expected Results NMDESS will be created to integrate data, information, physical simulation models and economic analysis for solving specific watershed problems, to evaluate the source, transport, and impact of N and P on lake water quality and to protect the intended uses of the lake (Figure 4). The NMDESS interface will be created to assist stakeholder in analyzing various scenarios and drop down menus and buttons to select watershed, farm or field within the watershed and input any scenario from the list developed by stakeholders. Advisory groups will be organized in the watershed and NMDESS using stakeholder feedback will be developed. Hydrologic and watershed factors regulating nutrient retention and loading to Lake Eucha will be identified, and will be incorporated in NMDESS. Description of Eucha Watershed Eucha watershed is approximately 1079 km 2 drainage basin, located in Mayes County and Delaware County, Oklahoma, and Benton County, Arkansas (Figure 1), The land use distribution in Eucha watershed is 50.9 % forest, 42.7 % pasture, 0.3 % brushy rangeland, 1.5 % urban, 1.9 % water, and 2.7 % row crop (Figure 2) (Storm et al., 2002), Poultry is the major agricultural product in the watershed (Wagner and Woodruff et al., 1997), The observed average total phosphorus loading to Lake Eucha is estimated 47600 kg per year (Storm et al., 2001), Total Phosphorus load to Lake Eucha is estimated approximately 27 % from the City of Decatur wastewater treatment plant (Storm et al., 2001), Total Phosphorus load to Lake Eucha is estimated approximately 73 % from the nonpoint sources (Storm et al., 2001). CE-QUAL-W2 Model CE-QUAL-W2 is a two dimensional water quality and hydrodynamic model for estuaries, lakes, reservoirs and river basin systems (CE-QUAL-W2 Water Quality Model, 2002), Temperature-nutrient-algae-dissolved oxygen- organic matter and sediment relationships are W2 models basic eutrophication processes (CE-QUAL-W2 Water Quality Model, 2002), CE-QUAL-W2 will be calibrated for Lake Eucha and will be used to analyze reservoir response to changes in watershed management strategies. Figure 2 : Classification of land use in Eucha Watershed Oklahoma Arkansas Figure 1: Location of Eucha Watershed in Arkansas and Oklahoma Spatial Database Decision Design Scenario Analysis Models Graphical User Interface (GUI) Data Entry Arc-IMS Output Results SW1 (25 % increase in litter application) SW1 (Current in litter application) SW1 (50 % increase in litter application) Objective 2: Develop Stakeholder Structure Objective 1: Develop DSS Analysis Scientists, engineers and policy makers collect, analyze data, present to stakeholders Deliberation Stakeholders review and interpret data, inform scientists and policymakers Objective 4: Evaluate DSS Nutrient Management Strategy for Lake Eucha Objective 3: Develop Lake Nutrient Load Endpoints Evaluation Performed by stakeholders, policy makers, Coop Extension Figure 4 : Process diagram of project activities 020 Kilometers 4010 Management Practice Scenarios Kilometer 30 50 60