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Under the influence of climate change, the hydrological processes of glaciers have undergone significant changes, a fact which is seriously affecting agricultural production in the downstream region of the Tianshan Mountains, China. In order to explore the intrinsic relationship between climate change and hydrological elements, we proposed an “evaluation-driving-prediction” system to study it. First, we constructed a glacier-enhanced soil and water assessment tool model (GE-SWAT) and used a two-stage calibration method to optimize the model parameters. Next, a scenario analysis was used to evaluate the driving factors of historical runoff changes. Finally, we projected future runoff changes using bias-corrected regional climate model (RCM) outputs. The results of the case study on the Jinghe River Basin in the Tianshan Mountains show that from 1963 to 2016, total runoff increased by 13.3%, 17.7% of which was due to increasing precipitation and 1.8% of which was negated by rising temperatures. The glacier runoff increased by 14.5%, mainly due to the rising temperatures. A 3.4% reduction in snowmelt was caused by a lower snowfall/precipitation ratio, which significantly reduced the snowfall from June to August. The RCM projection indicated that the warming and humidification phenomenon in the study area will continue at least through to the mid-21st century. A consistent increase in glacier runoff and total runoff is projected, but the contribution rate of the glacier runoff will have little to no change under the RCP4.5 and RCP8.5 emission scenarios. Our research demonstrates the simulation performance of the GE-SWAT model in a basin with moderate glacier cover. This method is shown to be efficient in quantifying the impact of climate change on glacier hydrological processes and predicting future streamflow changes, providing a good research reference for similar regions.

Best management practices (BMPs) provide a feasible solution for non-point source pollution problems. High sediment and nutrient yields without retention control result in environmental deterioration of surrounding areas. In the present study, the soil and water assessment tool (SWAT) model was developed for El Beal watershed, an anthropogenic and ungauged basin located in the southeast of Spain that drains into a coastal lagoon of high environmental value. The effectiveness of five BMPs (contour planting, filter strips, reforestation, fertilizer application and check dam restoration) was quantified, both individually and in combination, to test their impact on sediment and nutrient reduction. For calibration and validation processes, actual evapotranspiration (AET) data obtained from a remote sensing dataset called Global Land Evaporation Amsterdam Model (GLEAM) were used. The SWAT model achieved good performance in the calibration period, with statistical values of 0.78 for Kling–Gupta efficiency (KGE), 0.81 for coefficient of determination (R2), 0.58 for Nash–Sutcliffe efficiency (NSE) and 3.9% for percent bias (PBIAS), as well as in the validation period (KGE = 0.67, R2 = 0.83, NS = 0.53 and PBIAS = −25.3%). The results show that check dam restoration is the most effective BMP with a reduction of 90% in sediment yield (S), 15% in total nitrogen (TN) and 22% in total phosphorus (TP) at the watershed scale, followed by reforestation (S = 27%, TN = 16% and TP = 20%). All effectiveness values improved when BMPs were assessed in combination. The outcome of this study could provide guidance for decision makers in developing possible solutions for environmental problems in a coastal lagoon.

The Soil and Water Assessment Tool (SWAT) model has emerged as one of the most widely used water quality watershed- and river basin–scale models worldwide, applied extensively for a broad range of hydrologic and/or environmental problems. The international use of SWAT can be attributed to its flexibility in addressing waterresource problems, extensive networking via dozens of training workshops and the several international conferences that have been held during the past decade, comprehensive online documentation and supporting software, and an open source code that can be adapted by model users for specific application needs. The catalyst for this special collection of papers was the 2011 International SWAT Conference & Workshops held in Toledo, Spain, which featured over 160 scientific presentations representing SWAT applications in 37 countries. This special collection presents 22 specific SWAT-related studies, most of which were presented at the 2011 SWAT Conference; it represents SWAT applications on five different continents, with the majority of studies being conducted in Europe and North America. The papers cover a variety of topics, including hydrologic testing at a wide range of watershed scales, transport of pollutants in northern European lowland watersheds, data input and routing method effects on sediment transport, development and testing of potential new model algorithms, and description and testing of supporting software. In this introduction to the special section, we provide a synthesis of these studies within four main categories: (i) hydrologic foundations, (ii) sediment transport and routing analyses, (iii) nutrient and pesticide transport, and (iv) scenario analyses. We conclude with a brief summary of key SWAT research and development needs.

Based on the principle of water supply and demand flow and the natural flow of water, this paper analyzes the flow direction and discharge of water resources in the study area. In order to provide scientific and systematic implementation suggestions for regional water resource protection management and ecological compensation, a SWAT (Soil and Water Assessment Tool) model was constructed to quantify the water resource supply of the upper Hanjiang River basin at three spatial scales: pixel, sub-basin, and administrative unit. The water demand at the three spatial scales was calculated using the LUCC (Land Use and Land Coverage) and water consumption index. The supply and benefit zones under different spatial and temporal scales were obtained. Simultaneously, this study uncovered the spatiotemporal dynamics inherent in water resource supply and demand, alongside elucidating the spatial extent and flow attributes of water supply. The ecological compensation scheme of water resource supply–demand was preliminarily determined. The findings indicate an initial increase followed by a decrease in both the water supply and demand in the upper reaches of the Han River, accompanied by spatial disparities in the water supply distribution. The direction of the water supply generally flows from branch to main stream. The final ecological compensation scheme should be combined with natural conditions and economic development to determine a reasonable financial compensation system.

Nitrous oxide (N2O) is a long-lived greenhouse gas that contributes to global warming. Emissions of N2O mainly stem from agricultural soils. This review highlights the principal factors from peer-reviewed literature affecting N2O emissions from agricultural soils, by grouping the factors into three categories: environmental, management and measurement. Within these categories, each impact factor is explained in detail and its influence on N2O emissions from the soil is summarized. It is also shown how each impact factor influences other impact factors. Process-based simulation models used for estimating N2O emissions are reviewed regarding their ability to consider the impact factors in simulating N2O. The model strengths and weaknesses in simulating N2O emissions from managed soils are summarized. Finally, three selected process-based simulation models (Daily Century (DAYCENT), DeNitrification-DeComposition (DNDC), and Soil and Water Assessment Tool (SWAT)) are discussed that are widely used to simulate N2O emissions from cropping systems. Their ability to simulate N2O emissions is evaluated by describing the model components that are relevant to N2O processes and their representation in the model.

Future changes in streamflow and sediment, influenced by anthropogenic activities and climate change, have a crucial role in watershed management. This study aimed to quantify the effects of anthropogenic and natural drivers on future streamflow and sediment changes in the tropical Sai Gon Dong Nai River basin using the Soil and Water Assessment Tool (SWAT) model. Specifically, the model incorporated thirty-six reservoirs and analyzed twenty future climate projected scenarios from four Coupled Model Intercomparison Project Phase 6 (CMIP6) General Circulation Models (GCMs) for 2023–2100. These models include BCC-CSM2-MR (China), CanESM5 (Canada), MIROC6 (Japan), and MRI-ESM2-0 (Japan). Our findings indicate that (1) dam operation and diversion lead to a 0.5% decrease in streamflow during the dry season and a 4.1% increase during the rainy season compared to those in scenarios without dams; (2) there is a 37.4% decrease in annual sediment across the entire basin under same climate conditions; and (3) rainfall is projected to decrease (24.6% – 6.2%), resulting in a decrease in streamflow (0.2 – 32.2%) and sediment (39.3 – 56.0%) compared to historical records. Streamflow is expected to decrease during the rainy season (16.7 – 23.1%) and increase during the dry season (14.5 – 25.4%). Further potential degradation of the environmental conditions and water mismanagement are caused by the synergies between too much and too little rainfall conditions. The anticipated reductions in future streamflow and sediment could adversely affect ecological streamflow, water security, and sediment dynamics in the Sai Gon Dong Nai River basin. Our approach effectively identifies future changes in streamflow and sediment due to the combined effects of climate change and reservoir operations, providing valuable insights for integrated water resource management in tropical regions.

This study presents a robust approach to assess climate change impact variability on future extreme events (e.g., rainfall depth and river discharge) over Dehbar catchment in Iran. Climate change impact is assessed using five general circulation models (GCMs) including EC-EARTH, GFDL-CM3, HadGEM2-ES, MIROC5, and MPI-ESM-MR with several emission scenarios (e.g., RCP26, RCP45, and RCP85). Daily discharge data is simulated based on the distributed rainfall-runoff model called Soil and Water Assessment Tool (SWAT), while calibration and validation phases are performed using SWAT-CUP. Future annual extreme events (i.e., rainfall depth and river discharge) are computed by means of frequency analysis. Results show that future annual maximum values are increased significantly, where the most increase occurs in the future annual river discharge and rainfall depth according to the EC-EARTH-RCP85 as 142% and 81% with MPI-ESM-MR-RCP85 model. The highest future extreme river discharge and rainfall depth values through different return periods (50–1000 year) are obtained from EC-EARTH-RCP85 as 6.8~8.08 cms and 57.41~105.76 mm based on EC-EARTH-RCP45 model. Uncertainty analysis results indicate that climate models/scenarios have significant effect on the future extreme events variability, while the same for extreme river discharge is the least sensitive to different return periods.

Application of integrated hydrological models to manage a watershed’s water resources are increasingly finding their way into the decision-making processes. The Soil and Water Assessment Tool (SWAT) is a multi-process model integrating hydrology, ecology, agriculture, and water quality. SWAT is a continuation of nearly 40 years of modeling efforts conducted by the United States Department of Agriculture (USDA) Agricultural Research Service (ARS). A large number of SWAT-related papers have appeared in ISI journals, building a world-wide consensus around the model’s stability and usefulness. The current issue is a collection of the latest research using SWAT as the modeling tool. Most models must undergo calibration/validation and uncertainty analysis. Unfortunately, these sciences are not formal subjects of teaching in most universities and the students are often left to their own resources to calibrate their model. In this paper, we focus on calibration and uncertainty analysis highlighting some serious issues in the calibration of distributed models. A protocol for calibration is also highlighted to guide the users to obtain better modeling results. Finally, a summary of the papers published in this special issue is provided in the Appendix.

Upper-Brantas watershed in East Java, Indonesia, is a tropical watershed experiencing rapid landscape change, a phenomenon typical to developing countries. This study demonstrates the impact of Land Use Land Cover (LULC) changes on surface runoff in a tropical, urbanized, and data scarce watershed. The LULC changes were quantified between 1995 and 2015 and their impact on the hydrological processes was analyzed using the Soil and Water Assessment Tool (SWAT) model. During the study period, the watershed experienced an increase in settlement and dryland agriculture, and a decrease in the forest, rice field, and sugarcane plantation. The SWAT model results for the calibration (2003–2008) and validation (2009–2013) periods matched observed values [R2 > 0.91 and NSE (Nash-Sutcliffe Efficiency) >0.91]. In the long-term, the model predicted changes in runoff (+8%), water yield (+0.28%), groundwater (−1.8%), and evapotranspiration (−1.15%) due to changes in LULC. LULC changes showed a linear relationship with runoff generation, and the most significant factors affecting surface runoff were changes in the forest, agriculture, and settlements. Increasing urbanization, industrialization, and agricultural intensification will increase runoff which in turn will enhance the flow of nutrients and sediments into the water bodies.

Soil moisture is widely recognized as a key parameter in the mass and energy balance between the land surface and the atmosphere and, hence, the potential societal benefits of an accurate estimation of soil moisture are immense. Recently, scientific community is making great effort for addressing the estimation of soil moisture over large areas through in situ sensors, remote sensing and modelling approaches. The different techniques used for addressing the monitoring of soil moisture for hydrological applications are briefly reviewed here. Moreover, some examples in which in situ and satellite soil moisture data are successfully employed for improving hydrological monitoring and predictions (e.g., floods, landslides, precipitation and irrigation) are presented. Finally, the emerging applications, the open issues and the future opportunities given by the increased availability of soil moisture measurements are outlined.