Using SWAT to simulate crop yields and salinity levels in the North Fork River Basin,USA

Crop yields and salinity levels in the North Fork of the Red River(North Fork River)basin,located in southwestern Oklahoma and the Texas Panhandle,were analyzed based on the diverse climate in the region.Saline irrigation water is a major problem in the basin.The Elm Fork Creek flows through salt deposits,making the creek and its receiving stream,the North Fork River,too saline to use for irrigation.This greatly reduces the number of hectares that can be utilized for agricultural crops within the basin.A baseline SWAT model was setup,calibrated and validated to simulate streamflow and wheat and cotton yields.The SWAT model and a regression equation were used to analyze variable weather impacts on crop yields and salinity levels.Using the weather generator WXGEN and 58 years of observed weather data,ten 50-year weather datasets were generated.Output from the weather generator was input into the calibrated SWAT model to simulate wheat and dryland and irrigated cotton yields for the ten weather scenarios.Using an empirical relationship between ionic strength and streamflow,salinity levels were estimated.Though the crop yields varied greatly from year to year,the yields were not significantly different over the 50-year simulation period.The electrical conductivity(EC,expressed in decisiemens per meter or dS/m)at the US Geological Survey gage station just downstream of the salt deposits was significantly different with levels ranging from 40 to 65 dS/m.Though the water in the Elm Fork is much too saline to use for irrigation,the water in the North Fork River may be used as long as the flow rates in the river are greater than 0.60 m3/s.In order to optimize the available cropland,a salinity control must be installed upstream of the salt deposits on the Elm Fork Creek.

Comparison of three regionalization techniques for predicting streamflow in ungaged watersheds in Nebraska,USA using SWAT model

This study compared three approaches,regional averaging,nearest neighbor,and donor techniques,to regionalize parameters in the Soil and Water Assessment Tool(SWAT)on eleven watersheds located in the Dissected Plains,Plains,and Rolling Hills Landforms in the eastern portion of the State of Nebraska,USA.Within the Rolling Hills Landform,three watersheds were randomly selected as calibration watersheds while two were randomly selected as validation watersheds.Two watersheds were randomly selected as calibration watersheds while one was randomly selected as a validation watershed within each of the Dissected Plains and Plains Landforms.The seven calibration watersheds were used to provide the necessary calibrated parameter sets to execute each of the regional approaches,while the four validation watersheds were used to assess the impact of applying each of these approaches to an uncalibrated watershed.Percent Bias(PBIAS)and the Nash Sutcliffe Coefficient of Efficiency(NSE)were used to assess model performance.Test results of this study show that all three methods performed poorly,since the majority of watersheds among each method tested exhibited PBIAS values greater than ±25% and/or NSE values less than 0.50,which were considered to be unsatisfactory in terms of model performance.The average regionalization,nearest neighbor and donor methods resulted in only four(two calibration and two validation),zero and one satisfactory set of simulated watershed results,respectively.The findings from this study indicate that although each watershed was successfully calibrated with NSE values ranging from 0.51 to 0.84,none of the three regionalization methods provided suitable calibration data sets to define parameter values for performing satisfactory simulations on ungaged watersheds across the eastern Nebraska landscape.