Comparison of Evapotranspiration Simulation Performance by APEX Model in Dryland and Irrigated Cropping Systems

Accurate estimation of evapotranspiration (ET) is essential to improve water use efficiency of crop production systems managed under different water regimes. The Agricultural Policy/Environmental eXtender (APEX) model was used to simulate ET using four potential ET (ET_p) methods. The objectives were to determine sensitive ET parameters in dryland and irrigated cropping systems and compare ET simulation in the two systems using multiple performance criteria. Measured ET and crop yield data from lysimeter fields located in the United States Department of Agriculture‐Agricultural Research Service Bushland, Texas were used for evaluation. The number of sensitive parameters was higher for dryland (11–14) than irrigated cropping systems (6–8). Only four input parameters: soil evaporation plant cover factor, root growth soil strength, maximum rain intercept, and rain intercept coefficient were sensitive in both cropping systems. Overall, it is possible to find a set of robust parameter values to simulate ET accurately in APEX in both cropping systems using any ET_p method. However, more computation time is required for dryland than irrigated cropping system due to a relatively larger number of sensitive input parameters. When all inputs are available, the Penman–Monteith method takes the shortest computation time to obtain one model run with robust parameter values in both cropping systems. However, in areas with limited datasets, one can still obtain reasonable ET simulations using either Priestley–Taylor or Hargreaves. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Sediment measurement and transport modeling: impact of riparian and filter strip buffers

Well-calibrated models are cost-effective tools to quantify environmental benefits of conservation practices, but lack of data for parameterization and evaluation remains a weakness to modeling. Research was conducted in southwestern Oklahoma within the Cobb Creek subwatershed (CCSW) to develop cost-effective methods to collect stream channel parameterization and evaluation data for modeling in watersheds with sparse data. Specifically, (i) simple stream channel observations obtained by rapid geomorphic assessment (RGA) were used to parameterize the Soil and Water Assessment Tool (SWAT) model stream channel variables before calibrating SWAT for streamflow and sediment, and (ii) average annual reservoir sedimentation rate, measured at the Crowder Lake using the acoustic profiling system (APS), was used to cross-check Crowder Lake sediment accumulation rate simulated by SWAT. Additionally, the calibrated and cross-checked SWAT model was used to simulate impacts of riparian forest buffer (RF) and bermudagrass [ (L.) Pers.] filter strip buffer (BFS) on sediment yield and concentration in the CCSW. The measured average annual sedimentation rate was between 1.7 and 3.5 t ha yr compared with simulated sediment rate of 2.4 t ha yr Application of BFS across cropped fields resulted in a 72% reduction of sediment delivery to the stream, while the RF and the combined RF and BFS reduced the suspended sediment concentration at the CCSW outlet by 68 and 73%, respectively. Effective riparian practices have potential to increase reservoir life. These results indicate promise for using the RGA and APS methods to obtain data to improve water quality simulations in ungauged watersheds.     

Reservoir Sedimentation Rates in the Little Washita River Experimental Watershed,Oklahoma: Measurement and Controlling Factors

Forty‐five flood control reservoirs, authorized in the Watershed Protection and Flood Prevention Act 1954, were installed by United States Department of Agriculture (USDA) between 1969 and 1982 in the Little Washita River Experimental Watershed (LWREW), located in central Oklahoma. Over time, these reservoirs have lost sediment and flood storage capacity due to sedimentation, with rates dependent on upstream land use and climate variability. In this study, sedimentation rates for 12 reservoirs representing three major land use categories within LWREW were measured based on bathymetric surveys that used acoustic profiling system. Physiographic and climate attributes of drainage area of surveyed reservoirs were extracted from publicly available data sources including topographic maps, digital elevation models, USDA Natural Resource Conservation Service soils, and weather station databases. Correlation, principal component analysis, and stepwise regression were utilized to analyze the relationship between normalized reservoir sedimentation rates (ReSRa) and the drainage area characteristics to determine the major variables controlling sedimentation within the LWREW. Percent of drainage area with extreme slopes, saturated hydraulic conductivity, and maximum daily rainfall event recorded in spring explained most of the variability in ReSRa. It was also found that percent reduction in reservoir surface area can be used as a surrogate for estimating ReSRa. The implications of the results are discussed.     

Impact of Length of Dataset on Streamflow Calibration Parameters and Performance of APEX Model

Due to resource constraints, long‐term monitoring data for calibration and validation of hydrologic and water quality models are rare. As a result, most models are calibrated and, if possible, validated using limited measured data. However, little research has been done to determine the impact of length of available calibration data on model parameterization and performance. The main objective of this study was to evaluate the impact of length of calibration data (LCD) on parameterization and performance of the Agricultural Policy Environmental eXtender model for predicting daily, monthly, and annual streamflow. Long‐term (1984‐2015) measured daily streamflow data from Rock Creek watershed, an agricultural watershed in northern Ohio, were used for this study. Data were divided into five Short (5‐year), two Medium (15‐year), and one Long (25‐year) streamflow calibration data scenarios. All LCD scenarios were calibrated and validated at three time steps: daily, monthly, and annual. Results showed LCD affected the ability of the model to accurately capture temporal variability in simulated streamflow. However, overall average streamflow, water budgets, and crop yields were simulated reasonably well for all LCD scenarios.     

A Parallel Computation Tool to Enable Dynamic Sensitivity and Model Performance Analysis of APEX: Evapotranspiration Modeling

Global sensitivity analysis can be used for assessing the relative importance of model parameters on model outputs. The sensitivity of parameters usually indicates a temporal variation due to variation in the environmental conditions (e.g., variation in weather or plant growth). In addition, the size of averaging window by which the outputs of a model are aggregated or averaged may impact parameter sensitivities. In this study, temporal variation of parameters sensitives, model performance, as well as the impact of the size of time‐averaging window on evapotranspiration (ET) prediction using the Agricultural Policy/Environmental eXtender (APEX) model are investigated. To achieve these goals, an open‐source package named PARAPEX was developed in R and used to perform dynamic sensitivity and model performance analysis of APEX using parallel computation. PARAPEX reduced the computation time from 5,939 to 379 s (using 20 and 1 computation nodes, respectively). The sensitivity analysis results indicated the parameters accounting for the reducing effect of plant cover on evaporation from the soil surface, the effect of soil on the plant root growth, and the effect of cycling and transformation dynamics of organic matter at the top soil layer as the top sensitive parameters based on the mean daily simulated ET and the Nash–Sutcliffe model performance measure. The dynamic performance analysis indicated poor ET predictions by APEX during the growing seasons. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin,Mexico

Assessment of water resources requires reliable rainfall data, and rain gauge networks may not provide adequate spatial representation due to limited point measurements. The Tropical Rainfall Measuring Mission (TRMM) provides rainfall data at global scale, and has been used with good results. However, TRMM data are an indirect measurement of rainfall, and therefore must be validated for its proper use. In this work, a validation scheme was designed and implemented to compare the TRMM Version 7 (V7) monthly rainfall product at different time frames with data measured in two hydrologic subregions of the Santiago River Basin (SRB) in Mexico: Río Alto Santiago and Río Bajo Santiago (RBS). Additionally, three physio‐climatic regions provide an assessment of the interplay of topography, distance from coastal regions, and seasonal weather patterns on the correspondence between both datasets. The TRMM V7 rainfall product exhibited good agreement with the rain gauge data particularly for the RBS and for the whole SRB during wettest summer and autumn seasons. However, strong regional dependence was observed due to differences in climate and topography. Overall, in spite of some noted underestimations, the monthly TRMM V7 rainfall product was found to provide useful information that can be used to complement limited monitoring as is the case of RBS. An improved combined rainfall product could be generated and thus gaining the most benefits from both data sources.     

Spatial Considerations in Wet and Dry Periods for Phosphorus in Streams of the Fort Cobb Watershed,United States

The Fort Cobb Watershed in Oklahoma has diverse biogeophysical settings and provides an opportunity to explore the association of water quality with a diverse set of landscapes during both wet (April 2007‐December 2009) and dry (January 2005‐March 2007) periods. The objective of this work was to identify spatial patterns in phosphorus (P) (soluble reactive P [SRP] and bioavailable P [BAP]) associated with landscape metrics for two distinct streamflow regimes. Spatial autocorrelation of P was evaluated using contiguous (side‐by‐side) and upstream (upstream:downstream) connectivity matrices. Biogeophysical metrics were compiled for each contributing area, and were partitioned based on association to P concentrations. Results for both SRP and BAP indicated that spatial autocorrelation was present (p < 0.05). There was more spatial autocorrelation and stream P concentrations were three to five times higher in the Wet phase than in the Dry phase (p < 0.05). Analysis with recursive partitioning resulted in higher R² with spatial autocorrelation than without spatial autocorrelation and indicated that lateral metrics (topography, soil, geology, management) were better predictors for SRP than instream metrics. During Wet phase, lateral metrics indicative of rapid surface and subsurface water movement were associated with higher P stream concentrations. This research demonstrated that we can detect landscapes more vulnerable to P losses and/or contaminations in either drought or very wet periods.     

SWAT‐LUT: A Desktop Graphical User Interface for Updating Land Use in SWAT

Long‐term simulations of agricultural watersheds have often been done assuming constant land use over time, but this is not a realistic assumption for many agricultural regions. This paper presents the soil and water assessment tool (SWAT)‐Landuse Update Tool (LUT), a standalone, user‐friendly desktop‐based tool for updating land use in the SWAT model that allows users to process multi‐year land use data. SWAT‐LUT is compatible with several SWAT model interfaces, provides users with several options to easily prepare and incorporate land use changes (LUCs) over a simulation period, and allows users to incorporate past or emerging land use categories. Incorporation of LUCs is expected to provide realistic model parameterization and scenario simulations. SWAT‐LUT is a public domain interface written in Python programming language. Two applications at the Fort Cobb Reservoir Experimental Watershed located in Oklahoma and pertinent results are provided to demonstrate its use. Incorporating LUCs related to implementation of recommended conservation practices over the years reduced discharge, evapotranspiration, sediment, total nitrogen, and total phosphorus loads by 59%, 9%, 68%, 53%, and 88%, respectively. The user’s manual is included in this article as Supporting Information. The SWAT‐LUT executable file and an example SWAT project with three land use rasters and the user’s manual are available at the United States Department of Agriculture‐Agricultural Research Service Grazinglands Research Laboratory website under Software. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.