Research

22 pages, 8147 KiB

Open AccessArticle

Assessing the Impact of Climate and Land-Use Changes on the Hydrologic Cycle Using the SWAT Model in the Mun River Basin in Northeast Thailand

by Dibesh Khadka, Mukand S. Babel and Ambili G. Kamalamma

Water 2023, 15(20), 3672; https://doi.org/10.3390/w15203672 - 20 Oct 2023

Cited by 3 | Viewed by 1479

Abstract

Climate change (CC) and land-use change (LUC) will alter a basin’s hydrological processes and water balance. Quantifying their significance is imperative in formulating appropriate countermeasures and management plans. This study assesses projected changes in hydrological variables under CC and LUC scenarios to provide [...] Read more.

Climate change (CC) and land-use change (LUC) will alter a basin’s hydrological processes and water balance. Quantifying their significance is imperative in formulating appropriate countermeasures and management plans. This study assesses projected changes in hydrological variables under CC and LUC scenarios to provide multi-dimensional insight into water balance relevant to an agricultural watershed in Northeast Thailand. The soil and water assessment tool (SWAT) is utilized to simulate hydrological variables (evapotranspiration, soil moisture, surface runoff, and water yield) for the baseline (1981–2010) and the near-future (2021–2050) after calibrating the model. CC projections considering the CMIP6 model ensemble for the high-emission scenario (SSP5-8.5) show the annual rainfall may not change significantly (0.5% increase compared to baseline). However, the surface runoff will likely increase by 33% due to the projected increase in rainfall intensity and extremes. The increase in urban areas due to LUC for the business as usual (BAU) scenario is also expected to boost surface runoff by 38–87%. Similarly, the LUC scenario with forest expansion will increase evapotranspiration by up to 1.3%. While CC is anticipated to raise water yield by 11%, LUC may reduce it by 6%. Under the combined scenario, the yield is expected to increase by 8%, indicating CC as the dominating driver. The results show that although CC governs the runoff from the basin, land-use change will also impact flows at a monthly scale. Importantly, soil moisture in the future will decrease (8–9%) under both stressors, which will reverberate in the basin’s agricultural livelihood and socioeconomic settings unless the appropriate adaptation measures are implemented. Full article

(This article belongs to the Special Issue SWAT Modeling - New Approaches and Perspective)

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23 pages, 9684 KiB

Open AccessArticle

Modeling Land Use and Management Practices Impacts on Soil Organic Carbon Loss in an Agricultural Watershed in the Mid-Atlantic Region

by Sadiya Baba Tijjani, Junyu Qi, Subhasis Giri and Richard Lathrop

Water 2023, 15(20), 3534; https://doi.org/10.3390/w15203534 - 10 Oct 2023

Cited by 2 | Viewed by 1109

Abstract

Measuring organic carbon (OC) losses from soils presents a challenge because of the intricate interplay of human-induced and biophysical processes. This study employs SWAT-C to simulate particulate OC (POC) and dissolved OC (DOC) losses from the Upper Maurice Watershed in the Mid-Atlantic Region. [...] Read more.

Measuring organic carbon (OC) losses from soils presents a challenge because of the intricate interplay of human-induced and biophysical processes. This study employs SWAT-C to simulate particulate OC (POC) and dissolved OC (DOC) losses from the Upper Maurice Watershed in the Mid-Atlantic Region. Simulation outcomes reveal that surface runoff was the primary contributor to the total DOC load (65%), followed by lateral flow (30%), and then groundwater (5%). Meanwhile, POC load was linked to erosion processes induced by surface runoff. Our findings indicate that agricultural land-use types exhibited the highest annual average DOC and POC loads. Forests and grasslands displayed intermediate loads, while barren land had the lowest load. Concerning seasonal fluctuations, agricultural land-use types exhibited distinct DOC and POC load patterns when compared to forest and grassland types, indicating the dominant role of management practices in determining soil OC (SOC) losses. Additional modeling of management practices’ impact on SOC budgets indicates maximal SOC sequestration with full irrigation, no-till (NT), and full fertilization. In contrast, the largest SOC depletion arises from combining conservation tillage (CT) and no fertilization, irrespective of irrigation. This study shows that SWAT-C can be used to simulate land use and management impacts on SOC dynamics. Full article

(This article belongs to the Special Issue SWAT Modeling - New Approaches and Perspective)

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18 pages, 3350 KiB

Open AccessArticle

Improved Representation of Groundwater–Surface Water Interactions Using SWAT+gwflow and Modifications to the gwflow Module

by Estifanos Addisu Yimer, Ryan T. Bailey, Lise Leda Piepers, Jiri Nossent and Ann Van Griensven

Water 2023, 15(18), 3249; https://doi.org/10.3390/w15183249 - 12 Sep 2023

Cited by 2 | Viewed by 2582

Abstract

Recent water availability and scarcity problems have highlighted the importance of surface–groundwater interactions. Thus, groundwater models are coupled with surface water models. However, this solution is complex, needing code modifications and long computation times. Recently, a new groundwater module (gwflow) was [...] Read more.

Recent water availability and scarcity problems have highlighted the importance of surface–groundwater interactions. Thus, groundwater models are coupled with surface water models. However, this solution is complex, needing code modifications and long computation times. Recently, a new groundwater module (gwflow) was developed directly inside the SWAT code to tackle these issues. This research assesses gwflow’s capabilities in representing surface–groundwater system interactions in the Dijle catchment (892.54 km²), a groundwater-driven watershed in Belgium. Additional developments were made in SWAT+gwflow to represent the interaction between the groundwater and soil (gwsoil). The model was calibrated for monthly mean streamflow at the catchment outlet (1983 to 1996) and validated for two periods (validation 1: 1975 to 1982 and validation 2: 1997 to 2002). It was found that the SWAT+gwflow model is better at representing the total flow (NSE of 0.6) than the standalone SWAT+ (NSE of 0.4). This was confirmed during two validation periods where the standalone model scored unsatisfactory monthly NSE (0.6 and 0.1), while the new model’s NSE was 0.7 and 0.5. Additionally, the SWAT+gwflow model simulations better depict the groundwater via baseflow and attain proper water balance values. Thus, in a highly groundwater-driven catchment, the simplified representation of groundwater systems by the standalone SWAT+ model has pitfalls. In addition, the modification made to the gwflow module (gwsoil) improved the model’s performance, which, without such adjustment, overestimates the streamflow via saturation excess flow. When including the gwsoil mechanism, thereby providing a more accurate representation of water storage and movement, groundwater is transferred to the soil profile, increasing the overall soil water content and thereby increasing lateral flow. This novel modification can also have implications for other distributed hydrological models to consider such exchanges in their modeling scheme. Full article

(This article belongs to the Special Issue SWAT Modeling - New Approaches and Perspective)

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14 pages, 4002 KiB

Open AccessArticle

Runoff Simulation and Climate Change Analysis in Hulan River Basin Based on SWAT Model

by Quanchong Su, Changlei Dai, Zheming Zhang, Shupeng Zhang, Ruotong Li and Peng Qi

Water 2023, 15(15), 2845; https://doi.org/10.3390/w15152845 - 06 Aug 2023

Cited by 2 | Viewed by 1286

Abstract

The shortage of water resources is a long-standing constraint on the development of the Chinese economy and society. In this paper, the climate change occurring in Hulan River Basin is analyzed using the data collected at Wangkui Meteorological Station from 1960 to 2020. [...] Read more.

The shortage of water resources is a long-standing constraint on the development of the Chinese economy and society. In this paper, the climate change occurring in Hulan River Basin is analyzed using the data collected at Wangkui Meteorological Station from 1960 to 2020. The overall temperature in the basin shows an upward trend, with a cumulative increase of 1.6 °C, as does the precipitation, which reaches 566.2 mm. In contrast, there is a downward trend shown by wind speed, with a cumulative decrease of 1.313 m/s. GIS remote sensing technology is applied to build a SWAT distributed hydrological model for the purpose of conducting runoff simulation in Hulan River Basin, and SWAT-CUP software is used to correct and analyze the simulation results. The parameters of snow melt are set to improve the accuracy of the model. The runoff data collected from Lanxi Hydrological Station from 2008 to 2020 are used to verify the model. The results show that the efficiency coefficient (NES) and correlation coefficient (R²) are 0.75 and 0.84, respectively, in the validation period from 2010 to 2013, while they are 0.77 and 0.93, respectively, in the correction period from 2014 to 2016, meeting the criteria of model evaluation. It can be seen from results noted above that SWAT is applicable in Hulan River Basin, providing a certain reference for the management of hydrological and water resources available in this region and for the construction of a distributed hydrological model of rivers in those high-latitude cold regions. Full article

(This article belongs to the Special Issue SWAT Modeling - New Approaches and Perspective)

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15 pages, 2447 KiB

Open AccessArticle

Assessing the Influence of a Bias Correction Method on Future Climate Scenarios Using SWAT as an Impact Model Indicator

by Tássia Mattos Brighenti, Philip W. Gassman, William J. Gutowski, Jr. and Janette R. Thompson

Water 2023, 15(4), 750; https://doi.org/10.3390/w15040750 - 14 Feb 2023

Cited by 6 | Viewed by 2514

Abstract

In this study, we evaluate the implications of a bias correction method on a combination of Global/Regional Climate Models (GCM and RCM) for simulating precipitation and, subsequently, streamflow, surface runoff, and water yield in the Soil and Water Assessment Tool (SWAT). The study [...] Read more.

In this study, we evaluate the implications of a bias correction method on a combination of Global/Regional Climate Models (GCM and RCM) for simulating precipitation and, subsequently, streamflow, surface runoff, and water yield in the Soil and Water Assessment Tool (SWAT). The study area is the Des Moines River Basin, U.S.A. The climate projections are two RCMs driven by two GCMs for historical simulations (1981–2005) and future projections (2030–2050). Bias correction improves historical precipitation for annual volumes, seasonality, spatial distribution, and mean error. Simulated monthly historical streamflow was compared across 26 monitoring stations with mostly satisfactory results for percent bias (Pbias). There were no changes in annual trends for future scenarios except for raw WRF models. Seasonal variability remained the same; however, most models predicted an increase in monthly precipitation from January to March and a reduction for June and July. Meanwhile, the bias-corrected models showed changes in prediction signals. In some cases, raw models projected an increase in surface runoff and water yield, but the bias-corrected models projected a reduction in these variables. This suggests the bias correction may be larger than the climate-change signal and indicates the procedure is not a small correction but a major factor. Full article

(This article belongs to the Special Issue SWAT Modeling - New Approaches and Perspective)

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17 pages, 3520 KiB

Open AccessArticle

Impacts of Spatial Interpolation Methods on Daily Streamflow Predictions with SWAT

by Micah Lourdes Felix and Kwansue Jung

Water 2022, 14(20), 3340; https://doi.org/10.3390/w14203340 - 21 Oct 2022

Cited by 2 | Viewed by 2229

Abstract

Precipitation is a significant input variable required in hydrological models such as the Soil & Water Assessment Tool (SWAT). The utilization of inaccurate precipitation data can result in the poor representation of the true hydrologic conditions of a catchment. SWAT utilizes the conventional [...] Read more.

Precipitation is a significant input variable required in hydrological models such as the Soil & Water Assessment Tool (SWAT). The utilization of inaccurate precipitation data can result in the poor representation of the true hydrologic conditions of a catchment. SWAT utilizes the conventional nearest neighbor method in assigning weather parameters for each subbasin; a method inaccurate in representing spatial variations in precipitation over a large area, with sparse network of gauging stations. Therefore, this study aims to improve the spatial variation in precipitation data to improve daily streamflow simulation with SWAT, even pre-model calibration. The daily streamflow based on four interpolation methods, nearest neighbor (default), inverse-distance-weight, radial-basis function, and ordinary kriging, were evaluated to determine which interpolation method is best represents the precipitation at Yongdam watershed. Based on the results of this study, the application of spatial interpolation methods generally improved the performance of SWAT to simulate daily streamflow even pre-model calibration. In addition, no universal method can accurately represent the long-term spatial variation of precipitation at the Yongdam watershed. Instead, it was observed that the optimal selection of interpolation method at the Yongdam watershed is dependent on the long-term climatological conditions of the watershed. It was also observed that each interpolation method was optimal based on certain meteorological conditions at Yongdam watershed: nearest neighbor for cases when the occurrence probability of extreme precipitation is high during wet to moderately wet conditions; radial-basis function for cases when the number of dry days were high, during wet, severely dry, and extremely dry conditions; and ordinary kriging or inverse-weight-distance method for dry to moderately dry conditions. The methodology applied in this study improved the daily streamflow simulations at Yongdam watershed, even pre-model calibration of SWAT. Full article

(This article belongs to the Special Issue SWAT Modeling - New Approaches and Perspective)

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22 pages, 7154 KiB

Open AccessArticle

Agricultural Irrigation Effects on Hydrological Processes in the United States Northern High Plains Aquifer Simulated by the Coupled SWAT-MODFLOW System

by Sijal Dangol, Xuesong Zhang, Xin-Zhong Liang and Fernando Miralles-Wilhelm

Water 2022, 14(12), 1938; https://doi.org/10.3390/w14121938 - 16 Jun 2022

Cited by 3 | Viewed by 2612

Abstract

Groundwater use for irrigation has a major influence on agricultural productivity and local water resources. This study evaluated the groundwater irrigation schemes, SWAT auto-irrigation scheduling based on plant water stress (Auto-Irr), and prescribed irrigation based on well pumping rates in MODFLOW (Well-Irr), in [...] Read more.

Groundwater use for irrigation has a major influence on agricultural productivity and local water resources. This study evaluated the groundwater irrigation schemes, SWAT auto-irrigation scheduling based on plant water stress (Auto-Irr), and prescribed irrigation based on well pumping rates in MODFLOW (Well-Irr), in the U.S. Northern High Plains (NHP) aquifer using coupled SWAT-MODFLOW model simulations for the period 1982–2008. Auto-Irr generally performed better than Well-Irr in simulating groundwater irrigation volume (reducing the mean bias from 86 to −30%) and groundwater level (reducing the normalized root-mean-square-error from 13.55 to 12.47%) across the NHP, as well as streamflow interannual variations at two stations (increasing NSE from 0.51, 0.51 to 0.55, 0.53). We also examined the effects of groundwater irrigation on the water cycle. Based on simulation results from Auto-Irr, historical irrigation led to significant recharge along the Elkhorn and Platte rivers. On average over the entire NHP, irrigation increased surface runoff, evapotranspiration, soil moisture and groundwater recharge by 21.3%, 4.0%, 2.5% and 1.5%, respectively. Irrigation improved crop water productivity by nearly 27.2% for corn and 23.8% for soybean. Therefore, designing sustainable irrigation practices to enhance crop productivity must consider both regional landscape characteristics and downstream hydrological consequences. Full article

(This article belongs to the Special Issue SWAT Modeling - New Approaches and Perspective)

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19 pages, 1784 KiB

Open AccessArticle

Simulation of Pesticide and Metabolite Concentrations Using SWAT+ Landscape Routing and Conditional Management Applications

by Hendrik Rathjens, Jens Kiesel, Maria Bettina Miguez, Michael Winchell, Jeffrey G. Arnold and Robin Sur

Water 2022, 14(9), 1332; https://doi.org/10.3390/w14091332 - 20 Apr 2022

Cited by 6 | Viewed by 2290

Abstract

The estimation of pesticide concentrations in surface water bodies with models is a critical component of the environmental and human health risk assessment process. The most recent version of the Soil and Water Assessment Tool (SWAT+) provides new features that are useful for [...] Read more.

The estimation of pesticide concentrations in surface water bodies with models is a critical component of the environmental and human health risk assessment process. The most recent version of the Soil and Water Assessment Tool (SWAT+) provides new features that are useful for pesticide exposure assessments. This research is the first SWAT+ pesticide simulation study and was conducted to evaluate SWAT+’s new features and to assess its ability to predict pesticide and metabolite concentrations. The evaluation was conducted based upon a comparison of the results from seven different model configurations with high-resolution monitoring data. The results showed that (1) SWAT+ is able to simulate the formation of degradation compounds and predict resulting concentrations in surface water, (2) an accurate representation of transport processes for pesticide exposure assessments is important, and (3) an appropriate degree of realism can be achieved with a rule-based probabilistic pesticide application schedule if information about the annual percent crop treated, a typical application rate, and a typical application window is available. The accuracy of the pesticide concentration simulations with the new features of SWAT+ in the present study demonstrates the model’s ability to provide more accurate estimates with reduced uncertainty compared to SWAT simulations. Full article

(This article belongs to the Special Issue SWAT Modeling - New Approaches and Perspective)

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