Second-Order Autoregressive Model-Based Likelihood Function for Calibration and Uncertainty Analysis of SWAT Model

Water Supply issues a formal withdrawal in relation to the above article by Cen Li, Xin Guo, Liping Chen, Majid Khayatnezhad and Fatemeh Gholinia. This decision has been made due to concerns that were raised regarding potential citation manipulation due to inappropriate references, and significant authorship changes during peer review. The journal did not receive a satisfactory response to these concerns and as such the Editors-in-Chief no longer have confidence in the integrity of the article.

The Soil and Water Assessment Tool (SWAT) model has been successfully used to predict alterations in streamflow, evapotranspiration and soil water; however, it is not clear how effective or accurate SWAT is at predicting crop growth. Previous research suggests that while the hydrologic balance in each watershed is accurately simulated with SWAT, the SWAT model over or under predicts crop yield relative to fertilizer inputs. The SWAT model now has three alternative N simulation options: 1) SWAT model with an added flush of N (SWAT-flush); 2) N routines derived from the CENTURY model (SWAT-C); and 3) a one-pool C and N model (SWAT-One). The objective of this study was to evaluate the performance of SWAT-flush, SWAT-C, and SWAT-One as they affect wheat yield prediction. Simulated yields were compared to wheat yields in a 28-year fertilizer/wheat yield study in Lahoma, OK. Simulated yields were correlated with actual 28-year mean yield; however, none of the available N cycling models predicted yearly yields. SWAT-C simulated average yields were closer than other N sub-models to average actual yield. Annually there was a stronger correlation between SWAT-flush and actual yields than the other submodels. However, none of the N-cycling routines were able to accurately predict annual variability in yield at any fertilizer rate. We found that SWAT-C or SWAT-flush are the most viable choices for accurately simulating long-term average wheat yields although annual variations in yield prediction should be taken into consideration. Further research is needed to determine the effectiveness of SWAT-C and SWAT-flush in determining average and annual yield in various farming regions and with numerous agronomic crops.

The Citanduy Watershed is one of the largest watersheds on Java Island and is in critical condition. The Upper Citanduy Sub-watershed is the main sub-watershed in the Citanduy Watershed, which needs attention because it greatly affects the quantity and quality of its water. The Soil and Water Assessment Tool (SWAT) model, which is a hydrological model developed in the United States, can be used to predict the quantity of water. However, the water balance in the SWAT model uses the water balance for plants planted on dry land (up land) and is less suitable for watersheds that have rice fields (low land). For watersheds that have rice fields, pot hole and modified SWAT features have been tried and developed. This study aims to analyze the performance of the SWAT model with original features, pot hole features, and modified features in the QSWAT program to predict water discharge in the Upper Citanduy Sub-watershed. The results of the study indicate that the modified SWAT has the best performance compared to the original SWAT and pot-hole SWAT, as indicated by the NSE and R2 values. The NSE values of the original SWAT, pot hole SWAT, and modified SWAT were 0.70, 0.73, and 0.75, respectively. The R2 values of the modified SWAT, Original SWAT, and pot hole SWAT were 0.94, 0.93, and 0.94, respectively.

The study has shown the integration of Arc SWAT with Arc GIS and remote sensing tool are helpful analyze and evaluate both spatial and temporal land use/cover dynamics. It has also shown that Arc SWAT is an effective tool in analyzing the impacts of land use/cover changes on stream flow in areas with limited readily available data. This study is mainly focusing on the investigation of the impacts of land use / land cover changes on the stream flow of Muga watershed which is located in the East Choke Mountains watersheds, Upper Abbay Basin, East Gojjam Zone, Amhara Regional state, Ethiopia. Soil and Water Assessment Tool (SWAT) model were used it investigate the impact of land cover change on the stream flow. For this study SWAT Simulation is used in identifying the most vulnerable sub basins to the stream flow and sediment load changes of Muga watershed. The model was calibrated and validated using historic Stream flow data. The model was calibrated using stream flow data from 1993 to1998, validated from 1999 to2002. The R 2 and NSE values were used to examine model performance and the result indicates 0.81 and 0.87 to R 2 and 0.80 and 0.86 to NSE during calibration and validation respectively. The result of this analysis indicated that the mean monthly stream flow for wet months had increased by 17.75m 3 /s while the dry season decreased by 12.76m 3 /s during the 1995-2013 period due to the land use and land cover change. The highest annual surface runoff was attributed by sub basin 5 whereas sub basin 6 contributes the highest ground water respectively for 1995, 2003 and 2013 land cover maps. In terms of sediment yield, sub basin 1 contributes a maximum load for the study periods. Keywords : Arc SWAT, Arc GIS, Land Use /land cover change, Muga Watershed DOI: 10.7176/CER/13-2-01 Publication date: April 30 th 2021

Knowledge of the shallow water table depth (wtd) is crucial in many studies, including determination of optimum irrigation and drainage management systems for agricultural production, farm machine trafficability, and water quality due to agricultural chemical transport and soil salinity. Therefore, it is essential for hydrologic models to accurately simulate wtd. A shallow wtd algorithm, herein called the modified DRAINMOD approach, that relates drainage volume (vol) to wtd, was recently incorporated into the Soil and Water Assessment Tool (SWAT) model. In the modified DRAINMOD approach, wtd is computed as a function of vol and a water table factor (wt_fctr), which converts vol into wtd. The constant wt_fctr is currently a calibration parameter. However, at the watershed scale where there are many fields (hydrologic response units, HRUs), it is difficult if not impossible to determine an optimum wt_fctr value for each HRU through the calibration process. The objectives of this study were to: (1) revise the modified DRAINMOD wtd algorithm in SWAT so that wt_fctr is automatically computed by the model as a function of soil physical properties in order to eliminate determination of wt_fctr through the calibration process, and (2) evaluate the revised modified DRAINMOD wtd algorithm within SWAT using measured wtd data for three observation wells located in forest fields within the Muscatatuck River basin in southeast Indiana. On average, the calibrated wt_fctr yielded daily NSE values of 0.64 and 0.41, PBIAS values of -13% and -4%, and RMSE values of 0.41 m and 0.59 m during the calibration and validation periods, respectively, for the three observation wells. The automatically computed variable wt_fctr yielded daily NSE values of 0.66 and 0.58, PBIAS values of 4% and 10%, and RMSE values of 0.40 m and 0.50 m during the calibration and validation periods, respectively, for the same observation wells. Based on these model performance results, there were no significant differences between the wtd simulated using the manually calibrated constant and the automatically computed variable wt_fctr values. The automatically computed variable wt_fctr will enable the revised modified DRAINMOD shallow wtd algorithm to be used at the watershed scale.

Occurrence frequency of flood and drought tends to increase in last a few decades, leading to social and economic damage since the abnormality of climate changes is one of the causes for hydrologic facilities by exceedance its designed tolerance. Soil and Water Assessment Tool (SWAT) model was used in the study to estimate temporal variance of groundwater recharge and baseflow. It was limited to consider recession curve coefficients in SWAT model calibration process, thus the recession curve coefficient was estimated by the Baseflow Filter Program (BFLOW) before SWAT model calibration. Precipitation data were estimated for 2014 to 2100 using three models which are GFDL-ESM2G, IPSL-CM5A-LR, and MIROC-ESM with Representative Concentration Pathways (RCP) scenario. SWAT model was calibrated for the Soyang watershed with NSE of 0.83, and <TEX>$R^2$</TEX> of 0.89. The percentage to precipitation of groundwater recharge and baseflow were 27.6% and 17.1% respectively in 2009. Streamflow, groundwater recharge, and baseflow were estimated to be increased with the estimated precipitation data. GFDL-ESM2g model provided the most large precipitation data in the 2025s, and IPSL-CM5A-LR provided the most large precipitation data in the 2055s and 2085s. Overall, groundwater recharge and baseflow displayed similar trend to the estimated precipitation data.

The Soil and Water Assessment Tool (SWAT) model was used to assess the impacts of different land use scenarios on hydrological processes in the Fuhe watershed in Poyang Lake Basin, East China. A total of 12 model parameters were calibrated with observed monthly runoff data for 1982-1988 and validated for 1991-1998 for baseline conditions. The baseline test results of R2 and Nash-Sutcliffe model efficiency (NSE) values ranged between 0.88 and 0.94 across the calibration and validation periods, indicating that SWAT accurately replicated the Fuhe watershed streamflow. Several different land use scenarios were then simulated with the model, focusing on the impacts of land use change on the hydrology of the watershed. The results of hypothetical scenario simulations revealed that surface runoff declined while groundwater recharge and evapotranspiration (ET) increased, as forest land, agriculture land and/or grassland areas increased, as well as when paddy field and urban areas decreased. These results further showed that forest land has a higher capacity to conserve the water as compared to pasture land. The results of the real scenario simulations revealed that urbanization is the strongest contributor to changes in surface runoff, water yield, and ET. Urbanization can be considered as a potential major environmental stressor controlling hydrological components. Keywords: SWAT model, land use, streamflow, water budget, scenario simulation, Poyang Lake, Fuhe watershed DOI: 10.3965/j.ijabe.20150803.1132 Online first on [2015-03-17] Citation: Tao C, Chen X L, Lu J Z, Gassman P W, Sabine S, Jose-Miguel S P. Assessing impacts of different land use scenarios on water budget of Fuhe River, China using SWAT model. Int J Agric & Biol Eng, 2015; 8(3): 95－109.

The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the U.S. Department of Agriculture (USDA), Agricultural Research Service. SWAT has gained international acceptance as a robust interdisciplinary watershed modeling tool, as evidenced by international SWAT conferences, hundreds of SWAT-related papers presented at numerous scientific meetings, and dozens of articles published in peer-reviewed journals. The model has also been adopted as part of the U.S. Environmental Protection Agency's BASINS (Better Assessment Science Integrating Point &amp; Nonpoint Sources) software package and is being used by many U.S. federal and state agencies, including the USDA within the Conservation Effects Assessment Project. At present, over 250 peer-reviewed, published articles have been identified that report SWAT applications, reviews of SWAT components, or other research that includes SWAT. Many of these peer-reviewed articles are summarized here according to relevant application categories such as streamflow calibration and related hydrologic analyses, climate change impacts on hydrology, pollutant load assessments, comparisons with other models, and sensitivity analyses and calibration techniques. Strengths and weaknesses of the model are presented, and recommended research needs for SWAT are provided.

The impact of climate change on hydrological processes and nutrient input is one of the major uncertainties in projecting future global warming. The Soil and Water Assessment Tool (SWAT) model is applied to simulate the effects of temperature on the hydrology and sediment and nutrient load in the lower Pearl River Basin, South China. Calibration and validation results for SWAT showed that the Yamen estuary is appropriate for simulating the impacts of temperature change on both hydrological processes and nutrient input. The possible temperature change scenarios were set at T–2, T–1.5, T–1, T–0.5, T+0.5, T+1, T+1.5, T+2, T+2.5, T+3°C compared to the current temperature, T°C. The results showed that the relative variation of discharge with temperature was slight. The sediment load at T+3°C is increased by 13.58% compared to that at T°C. Inorganic N and P inputs to the Yamen estuary showed an increasing trend with the temperature increase from T–2°C to T+3°C. Global warming can reduce the vegetation land cover by slowing plant growth, which will aggravate the water and soil loss. Temperature changes would have an effect on mineralization and nitrification by changing soil temperature and temperatures. The warming is projected to cause an increase of sediment and nutrient load into the estuary and accelerate eutrophication in the coastal area. Citation Li, Y., Chen, B.-M., Wang, Z.-G. & Peng, S.-L. (2011) Effects of temperature change on water discharge, and sediment and nutrient loading in the lower Pearl River basin based on SWAT modelling. Hydrol. Sci. J. 56(1), 68–83.

An increase in broiler chicken production has recently occurred in the Brazos-Navasota RiverWatershed (BNRW) in east central Texas. At present, over 8 million broiler chickens are producedannually in the Duck Creek Watershed (DCW), the most intensive production area of any of the BNRWsub-watersheds. Concern exists regarding the potential degradation of water quality within the BNRWdue to nutrient runoff from land-applied broiler litter. Thus a simulation study was initiated to determinethe potential impacts of current and alternative litter management practices. The application ofAgricultural Policy eXtender (APEX) and the Soil and Water Assessment Tool (SWAT) models to assesswater quality impacts for DCW baseline (current) conditions is reported here. The results of twosimulation approaches are described: APEX run in combination with SWAT and SWAT without APEX.

In this study, a 1-D Ensemble Kalman Filter (EnKF) has been used to update the soil moisture states of the Soil and Water Assessment Tool (SWAT) model predictions. Experiments were conducted for the Cobb Creek Watershed in southeastern Oklahoma for 2006–2008. Assimilation of in situ data proved limited success in the top layers only, due to the weak surface and root-zone coupling of SWAT. Negative impact on stream flow and especially storm-scale runoff result from degraded deep-layer soil moisture prediction. This indicates that although the model is calibrated for stream flow, the parameters are not tuned to represent the realistic physical coupling of the system. Therefore the improved surface soil moisture failed to produce better runoff and flow estimates. Synthetic twin study proved the potential of assimilating remotely sensed surface soil moisture in improving SWAT's hydrologic predictions (root-zone soil moisture, evapotranpiration, surface runoff and stream flow) with EnKF. However, perturbations used to generate ensemble trajectories could result in systematic biases in model states and degradation of certain variables that cannot be corrected with EnKF. The mechanisms causing such biases and the methods to correct them need to be further investigated.

Advancing the SWAT model to simulate perennial bioenergy crops: A case study on switchgrass growth

Abstract. The eco-hydrological model SWAT (Soil and Water Assessment Tool) is a useful tool to simulate the effects of catchment processes and water management practices on the water cycle. For each catchment some model parameters (e.g. ground water delay time, ground water level) remain constant and therefore are used as constant values; other parameters such as soil types or land use are spatially variable and thus have to be spatially discretized. SWAT setup interfaces process input data to fit the data format requirements and to discretize the spatial characteristics of the catchment area. The primarily used configuration is the sub-watershed discretization scheme. This spatial setup method, however, results in a loss of spatial information which can be problematic for SWAT applications that require a spatially detailed description of the catchment area. At present no SWAT interface is available which provides the management of input and output data based on grid cells. To fill this gap, the authors developed a grid-based model interface. To perform hydrological studies, the SWAT user first calibrates the model to fit to the environmental and hydrological conditions of the catchment. Compared to the sub-watershed approach, the grid-based setup significantly increases model computation time and hence aggravates calibration according to established calibration guidelines. This paper describes how a conventional set of sub-watershed SWAT parameters can be used to calibrate the corresponding grid-based model. The procedure was evaluated in a sub-catchment of the River Elbe (Northern Germany). The simulation of daily discharge resulted in Nash-Sutcliffe efficiencies ranging from 0.76 to 0.78 and from 0.61 to 0.65 for the calibration and validation period respectively; thus model performance is satisfactory. The sub-watershed and grid configuration simulate comparable discharges at the catchment outlet (R2 = 0.99). Nevertheless, the major advantage of the grid-based set-up is an enhanced spatial description of landscape units inducing a more realistic spatial distribution of model output parameters.

Highland agriculture is intensifying rapidly in South‐East Asia, leading to alarmingly high applications of agrochemicals. Understanding the fate of these contaminants requires carefully planned monitoring programmes and, in most cases, accurate simulation of hydrological pathways into and through water bodies. We simulate run‐off in a steep mountainous catchment in tropical South‐East Asia. To overcome calibration difficulties related to the mountainous topography, we introduce a new calibration method, named A Nash–Sutcliffe Efficiency Likelihood Match (ANSELM), that allows the assignment of optimal parameters to different hydrological response units in simulations of stream discharge with the Soil and Water Assessment Tool (SWAT) hydrological model. ANSELM performed better than the Parasol calibration tool built into SWAT in terms of model efficiency and computation time. In our simulation, the most sensitive model parameters were those related to base flow generation, surface run‐off generation, flow routing and soil moisture change. The coupling of SWAT with ANSELM yielded reasonable simulations of both wet‐season and dry‐season storm hydrographs. Nash–Sutcliffe model efficiencies for daily stream flow during two validation years were 0.77 and 0.87. These values are in the upper range or even higher than those reported for other SWAT model applications in temperate or tropical regions. The different flow components were realistically simulated by SWAT, and showed a similar behaviour in all the study years, despite inter‐annual climatic differences. The realistic partitioning of total stream flow into its contributing components will be an important factor for using this hydrological model to simulate solute transport in the future. Copyright © 2014 John Wiley &amp; Sons, Ltd.

Model calibration and validation are challenging in poorly gauged basins. We developed and applied a new approach to calibrate hydrological models using distributed geospatial remote sensing data. The Soil and Water Assessment Tool (SWAT) model was calibrated using only twelve months of remote sensing data on actual evapotranspiration (ETa) geospatially distributed in the 37 sub-basins of the Lake Chad Basin in Africa. Global sensitivity analysis was conducted to identify influential model parameters by applying the Sequential Uncertainty Fitting Algorithm–version 2 (SUFI-2), included in the SWAT-Calibration and Uncertainty Program (SWAT-CUP). This procedure is designed to deal with spatially variable parameters and estimates either multiplicative or additive corrections applicable to the entire model domain, which limits the number of unknowns while preserving spatial variability. The sensitivity analysis led us to identify fifteen influential parameters, which were selected for calibration. The optimized parameters gave the best model performance on the basis of the high Nash–Sutcliffe Efficiency (NSE), Kling–Gupta Efficiency (KGE), and determination coefficient (R2). Four sets of remote sensing ETa data products were applied in model calibration, i.e., ETMonitor, GLEAM, SSEBop, and WaPOR. Overall, the new approach of using remote sensing ETa for a limited period of time was robust and gave a very good performance, with R2 &gt; 0.9, NSE &gt; 0.8, and KGE &gt; 0.75 applying to the SWAT ETa vs. the ETMonitor ETa and GLEAM ETa. The ETMonitor ETa was finally adopted for further model applications. The calibrated SWAT model was then validated during 2010–2015 against remote sensing data on total water storage change (TWSC) with acceptable performance, i.e., R2 = 0.57 and NSE = 0.55, and remote sensing soil moisture data with R2 and NSE greater than 0.85.