Naresh Pai

Field_SWAT: A tool for mapping SWAT output to field boundaries

The Soil and Water Assessment Tool (SWAT) hydrological/water quality model divides a watershed into hydrological response units (HRUs) based on unique land cover, soil type, and slope. HRUs are a set of discontinuous land masses that are spatially located in the watershed but their responses are not tied to any particular field. Field_SWAT, a simple graphical user interface (GUI)-driven tool, was developed to map SWAT simulations from the HRU layer to a user-defined field boundaries layer. This stand-alone tool ingests spatial and nonspatial SWAT outputs and helps in visualizing them at the field scale using four different aggregation methods. The tool was applied for mapping the SWAT models annual runoff and sediment outputs from 218 HRUs to 89 individual field boundaries in an agriculturally dominated watershed in Northeast Arkansas. The area-weighted spatial aggregation method resulted in a most suitable mapping between HRU and field outputs. This research demonstrates that Field_SWAT could potentially be a useful tool for field-scale targeting of conservation practices and communicating model outputs to watershed managers and interested stakeholders.

Identifying Priority Subwatersheds in the Illinois River Drainage Area in Arkansas Watershed Using a Distributed Modeling Approach

This article describes a modeling approach for prioritizing 12-digit hydrologic unit code subwatersheds for the Illinois River Drainage Area in Arkansas (IRDAA) watershed utilizing the soil and water assessment tool (SWAT) model output for sediment, total phosphorus (TP), and nitrate-nitrogen (NO3-N). The model was calibrated and validated at seven locations for total flow, base flow, and surface runoff and at three locations for water quality outputs. A multi-objective function consisting of percent relative error (RE), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), coefficient of determination (R2), and ratio of the root mean square error to the standard deviation of measured data (RSR) was used to guide model evaluations. The resulting priority subwatersheds comprised only 24% of the total area of the watershed but contributed 49% of sediment, 33% of TP, and 27% of NO3-N simulated loadings. Statistical relationships between priority subwatersheds and their various characteristics assisted with supporting the prioritization results. For the IRDAA, this approach produced results that could assist watershed management agencies in optimizing allocation of limited resources in addressing water quality issues.

Identifying Priority subwatersheds using distributed modeling approach

The SWAT2009 (Soil and Water Assessment Tool, version 2009) model was implemented for prioritizing 12-digit hydrologic unit code (HUC) subwatersheds based on average annual flow-weighted concentration of sediment, total phosphorus (TP), and nitrate-nitrogen (NO3-N) within the Arkansas part of Illinois River Drainage Area (IRDA). The model was set up to simulate change in land use and land cover conditions during 1992 to 2006 by using six remote sensing images for the years 1992, 1993, 1999, 2001, 2004, and 2006. The key model parameters for adjustment were identified by performing sensitivity analysis using a combination of Latin-Hypercube (LH) and one-factor-at-a-time (OAT) sampling methods. The model was calibrated for flow, sediment, TP, and nitrate-nitrogen outputs by optimizing parameter values at hydrologically disconnected gages using a multiobjective function. The multiobjective function consisted of percent relative error (RE), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and ratio of the root mean square error to the standard deviation of measured data (RSR). This function was also used for validating the model at spatially distributed nested gages in the watershed. The output of the validated model was used for identifying priority subwatersheds that can potentially be used for making appropriate decisions for mitigating pollution sources by planners and other interested stakeholders.

Developing Inventory of Riparian Buffer Cover in L’Anguille River Watershed using Geospatial Technologies

A watershed level analysis was conducted in East-central Arkansas along L’Anguille River and its major tributaries to assess vegetation composition in riparian buffer cover using two baselines – stream centerline and stream bank. The input data for the study comprised 1:24,000 scale National Hydrography Dataset Plus (NHDPlus) stream centerline, one meter resolution natural color digital ortho quarter quad (DOQQ) imagery, one meter resolution color infrared (CIR) DOQQ imagery, and 2006 land use-land cover (LULC) imagery. Since both the approaches required accurate stream centerline data, manual editing of NHDPlus stream centerline was performed to match streams with their actual locations. The edited stream location was verified by overlaying it on one meter color DOQQ imagery.