A SWAT model validation of nested-scale contemporaneous stream flow, suspended sediment and nutrients from a multiple-land-use watershed of the central USA

Enhanced SWAT calibration through intelligent range-based parameter optimization

Hydrological models are vital tools in environmental management. Weaknesses in model robustness for hydrological parameters transfer uncertainties to the model outputs. For streamflow, the optimized parameters are the primary source of uncertainty. A reliable calibration approach that reduces prediction uncertainty in model simulations is crucial for enhancing model robustness and reliability. The optimization of parameter ranges is a key aspect of parameter calibration, yet there is a lack of literature addressing the optimization of parameter ranges in hydrological models. In this paper, we introduce a parameter calibration strategy that applies a clustering technique, specifically the Self-Organizing Map (SM), to intelligently navigate the parameter space during the calibration of the Soil and Water Assessment Tool (SWAT) model for monthly streamflow simulation in the Baishan Basin, Jilin Province, China. We selected the representative algorithm, the Sequential Uncertainty Fitting version 2 (SUFI-2), from the commonly used SWAT Calibration and Uncertainty Programs for comparison. We developed three schemes: SUFI-2, SUFI-2-Narrowing Down (SUFI-2-ND), and SM. Multiple diagnostic error metrics were used to compare simulation accuracy and prediction uncertainty. Among all schemes, SM outperformed the others in describing watershed streamflow, particularly excelling in the simulation of spring snowmelt runoff (baseflow period). Additionally, the prediction uncertainty was effectively controlled, demonstrating the SM's adaptability and reliability in the interval optimization process. This provides managers with more credible prediction results, highlighting its potential as a valuable calibration tool in hydrological modeling.

Total nitrogen and phosphorus loads in surface runoff from urban land use (city of Lublin) under climate change

An expansion of impervious surfaces in urban areas leads to increases of nutrient loads discharged with the surface runoff to receivers. A study of a different density of urban development impact on total nitrogen (TN) and phosphorus (TP) loads from the city of Lublin (eastern Poland) with the use of the SWAT (Soil & Water Assessment Tool) model was performed. To distinguish between areas with high and low density of urban development (UHD and ULD), a special analysis of hydrological parameters has been proposed. Moreover, to investigate the impact of climate change, four variant scenarios were taken into account, combining the RCP (representative concentration pathway) 4.5 and 8.5 forecasts and the adopted time horizons (2026-2035 and 2046-2055). The results showed a much higher share of TN and TP from UHD compared to ULD (86%-32 022 kg/year and 89%-2574 kg/year, respectively). In addition, the variant scenarios showed that the forecasted increase in precipitation and temperature will result in increased loads of nutrients from UHD and ULD up to 30%. Furthermore, the current increase of inhabitant number, due to the Ukrainian war migration and the common tendency to convert agricultural land to residential areas, could contribute to further expansion of UHD and ULD areas and an additional increase of nutrient loads.

Predictive modeling of nitrogen and phosphorus concentrations in rivers using a machine learning framework: A case study in an urban-rural transitional area in Wenzhou China

Rapid urbanization in China since 1980 generated environmental pressures of non-point source pollution (NPSP) and increased wide public concerns. Excessive quantities of nitrogen (N) and phosphorus (P) is a significant source of aquatic pollution, despite of their roles as essential nutritional elements for aquatic life processes. In this study, we present a new framework using random forest (RF) as a powerful machine learning algorithm driven by geo-datasets to estimate and map the concentration of total nitrogen (TN) and phosphorus (TP) at a spatial resolution for the Wen-Rui Tang River (WRTR) watershed, which is a typically urban-rural transitional area in east coastal region of China. A comprehensive GIS database of 26 in-house built environmental variables was adopted to build the predictive models of TN and TP in open waters over the watershed. The performances of the RF regression models were evaluated in comparison with in-situ measurements, and the results indicated the ability of RF regression models to accurately predict the spatiotemporal distribution of N and P concentration in rivers. Charactering the explanatory variable importance measures in the calibrated RF regression model defined the most significant variables impacting N and P contaminations in open waters across the urban-rural transitional area, and the results showed that these variables are aquaculture, direct domestic sewage, industrial wastewater discharges and the changing meteorological variables. Besides, mapping of the TN and TP concentrations across the continuous river at high spatiotemporal resolution (daily, 1 km × 1 km) in this study were informative. The results in this study provided the valuable data to various different stakeholders for managing water quality and pollution control where similar regions with rapid urbanization and a lack of water quality monitoring datasets.

Evaluation of best management practices to reduce sediment yield in the upper Gilo watershed, Baro akobo basin, Ethiopia using SWAT

The increasing sediment yield in the watershed is caused by natural and human activities, which significantly shifts the hydro-meteorological in the watershed. The Modified Universal Soil Loss Equation (MUSLE) equation in the Soil and Water Assessment Tool (SWAT) was used to estimate sediment yields for each hydrological response unit (HRU) based on peak runoff, daily runoff volume, area of hydrological response unit, and other estimated and default hydrological model parameters. The amount of sediment yield from each HRU is then summed to give the total soil erosion for the watershed.The spatio-temporal variations of sediment yield in the Upper Gilo watershed was simulated to identify the hotspot area and select the effective management practices (BMPs) for reducing significant problems. Model calibration and validation were carried out using sediment yield data from 1990 to 2004 and 2005 to 2014. The results indicated that the watershed total sediment yield is 1021.8 tonnes/yr. Furthermore, 17 sub-basins (37.8% of total watershed area) are severely threatened by high soil erosion. According to the simulation results, the filter strips, terraces, and contours reduced the watershed sediment yield by up to 53.2%, 45.4%, and 48%. Overall, the selected BMPs are highly effective in reducing sediment yield in watershed-prone areas.

Modeling fate and transport of pesticides from dryland agriculture using SWAT model

The aim of this study was to understand pesticide fate and transport from dryland agriculture in a major drinking water basin using SWAT and to identify critical source areas in the basin. Hydrological calibration results indicated satisfactory simulation of hydrologic processes within the catchment. Long term average observed sediment values (0.16 ton/ha) were compared with the annual average simulated SWAT outputs (0.22 ton/ha). Generally, the simulated concentrations were higher than the observed values, but the distribution pattern and trends were similar among the months. Average concentrations in water were 0.036 μg/L and 0.006 μg/L for fenpropimorph and chlorpyrifos, respectively. Transfer rates of pesticides from landscape to rivers showed that 0.36% of fenpropimorph and 0.19% of the applied amount of chlorpyrifos were exported to the river. Higher amount of fenpropimorph transport from land to the reach was attributed to its lower K_oc (soil adsorption coefficient) value compared to chlorpyrifos. Higher amounts from HRUs were observed in the application month (April) and following month (May) for fenpropimorph, while the months after September showed higher amounts for chlorpyrifos. The specific HRUs (Hydrological Response Units) located in sub-basins 3, 5, 9 and 11 presented highest dissolved pesticide amounts, while HRUs in sub-basins 4 and 11 exhibited highest concentrations for adsorbed pesticides. Best management practices (BMPs) were recommended in critical subbasins to protect the watershed. Despite the limitations, the results demonstrate the potential contributions of modeling in terms of assessing pesticide loadings, critical zones and application timing.

Investigating impact of CORDEX-based predicted climatic and LCM-based LULC scenarios on hydrologic response of a semi-gauged Indian catchment

The present study aims at documenting the impact of different climate and land use change scenarios on runoff in the Kangsabati River basin. While the study relies on India Meteorological Department (IMD), National Oceanic and Atmospheric Administration's Physical Sciences Laboratory (NOAA-PSL), and a multi-model ensemble of six driving models from Coordinated Regional Downscaling Experiment-Regional Climate Models (CORDEX RCM) for climate data input, it depends on IDRISI Selva's Land Change Modeller (LCM) and Soil and Water Assessment Tool (SWAT) model to generate projected land use land change maps and simulate its streamflow response, respectively. A total of four land use and land cover (LULC) scenarios, representing four projected land use change, were modelled across three climatic scenarios, called Representative Concentration Pathways (RCPs). With runoff being predominantly impacted more by climate change than LULC, volumetric runoff is expected to be 12-46% higher than the baseline period of 1982-2017. Conversely, while surface runoff is expected to decrease by 4-28% in lower parts of the basin, it will increase by 2-39% in the rest of it, depending on the subtle alterations in land use and climatic variability.

A 22-Site Comparison of Land-Use Practices, E-coli and Enterococci Concentrations

Land-use practices can greatly impact water quality. Escherichia (E.) coli and Enterococcus are accepted water quality indicators. However, surprisingly little research has been conducted comparing both organisms' population density relationships to land use practices and water quality. Stream water grab samples were collected monthly (n = 9 months) from 22 stream monitoring sites draining varying land use practice types in a representative mixed-land-use watershed of the northeastern United States. E. coli and enterococci colony forming units (CFU per 100 mL) were estimated (n = 396) and statistically analyzed relative to land use practices, hydroclimate, and pH, using a suite of methods, including correlation analysis, Principal Components Analysis (PCA), and Canonical Correspondence Analysis (CCA). Correlation analyses indicated significant (p < 0.05) relationships between fecal indicator bacteria concentrations, water quality metrics and land use practices but emphasized significant (p < 0.05) negative correlations between pH and instream enterococci concentrations. PCA and CCA results indicated consistent spatial differences between fecal indicator bacteria concentrations, pH, and land use/land cover characteristics. The study showed that pH could be considered an integrated proxy variable for past (legacy) and present land use practice influences. Results also bring to question the comparability of E-coli and enterococci relative to dominant land use practices and variations in pH and provide useful information that will help guide land use practice and water pollutant mitigation decision making.

A review of non-point source water pollution modeling for the urban-rural transitional areas of China: Research status and prospect

China has experienced a rapid period of urbanization since the 1980s. Many traditional agricultural areas were transformed into the urban-rural transitional areas, in which both urban and rural characteristics exist. Non-point source pollution (NPSP) has become a major side effect of urbanization and agricultural production which caused wide public concerns. It is crucial to carry out research on identifying the spatiotemporal variation in NPSP in the urban-rural transitional area (especially in developing countries, e.g., in China), which is a prerequisite for improving water quality and guiding NPSP control efforts. Modeling approaches are great tools to provide quantitative information on NPSP and optimize the best management practices for NPSP control. We reviewed over twenty years of publications on NPSP modeling and applications in urban, rural and its transitional areas. The strengths and limitations of 20 commonly used NPSP models in China were concluded based on a brief introduction and the evolution history. Reporting the strengths and weaknesses of each NPSP model could enhance its utility in practice. In terms of the unique characteristics of urban-rural transitional areas, which are neither strictly urban nor rural, non-point source pollutants are often distinctly different between traditional pollutants from urban and agricultural areas since the great differences in the hydrological processes, and none of existing NPSP models are fully applicable to urban-rural transitional areas. Based on limited NPSP modeling studies in urban-rural transitional areas, the existing research insufficiency were technical and mechanism limitations of the model despite of numerous improvements in the past, concerns about simulation accuracy, limited investigations on new pollutants, and lack of monitoring data. Future development trend and concerns of NPSP models for urban-rural transitional areas were discussed, which could be of great help to the development of NPSP models and their applications in water quality management in the rapid urbanized China.

Impact assessment of on-site swine wastewater treatment facilities on spatiotemporal variations of nitrogen loading in an intensive livestock farming watershed

Excess nitrogen (N) resulting from human activity causes environmental issues, including eutrophication in agricultural watersheds with intensive livestock farming. Among the N sources in Korea, on-site swine wastewater treatment facilities (OSWTFs) tend to be densely distributed in watersheds with intensive livestock farming. Therefore, it is critical to sustainably manage livestock excreta. This study used the Soil and Water Assessment Tool (SWAT) to investigate the effects of various pollution sources, including OSWTFs, on N loads in rivers in the Cheongmi watershed, which is an intensive livestock farming and agricultural area in Korea. The simulated hydrological and water quality outputs were calibrated and validated for 2012-2019 using Sequential Uncertainty Fitting ver. 2 in the SWAT-Calibration and Uncertainty Program. The hydrological simulations agreed with the observations, with a correlation coefficient (R²) of ≥ 0.8 and Nash-Sutcliffe coefficient of 0.67-0.86. The simulated total N (TN) was also strongly correlated with the observed monthly average loading (R², 0.36-0.73) and annual average concentration (R² ≥ 0.5), demonstrating the reliability of the model constructed herein. A simulation of management scenarios indicates that, if the permissible N concentration in effluent from OSWTFs was reduced to 60 mg N/L, the TN concentrations in rivers would decrease by up to 50%. The findings of this study indicate that more stringent effluent water quality standards are required for OSWTFs to protect water quality and aquatic ecosystems in intensive swine farming watersheds.

Assessing the Effect of Land-Use and Land-Cover Changes on Discharge and Sediment Yield in a Rural Coal-Mine Dominated Watershed in Kentucky, USA

The Appalachian Mountain region of eastern Kentucky is unique and contains high proportions of forestland along with coal and natural gas depositaries. Landscape changes due to extreme mining activities can eventually threaten the downstream ecosystems, including soil and water quality, resulting in excessive runoff and sedimentation. The purpose of this study is to assess the impacts of land-use and land-cover (LULC) changes in streamflow and sediment yield in Yellow Creek Watershed, Kentucky, USA, between 1992 and 2016. LULC, digital elevation model, soil, and weather data were inputted into the Soil and Water Assessment Tool (SWAT) to simulate discharge and sediment yield. The model output was evaluated on several statistical parameters, such as the Nash-Sutcliffe efficiency coefficient (NSE), RMSE-observations standard deviation ratio (RSR), percent bias (PBIAS), and the coefficient of determination (R2). In addition, two indices, P-factor and R-factor, were used to measure the prediction uncertainty. The calibrated model showed an increase in surface runoff and sediment yield due to changes in LULC in the Yellow Creek Watershed. The results provided important insights for studying water management strategies to make more informed land management decisions and adaptive practices.

A Union of Dynamic Hydrological Modeling and Satellite Remotely-Sensed Data for Spatiotemporal Assessment of Sediment Yields

(1) The existing frameworks for water quality modeling overlook the connection between multiple dynamic factors affecting spatiotemporal sediment yields (SY). This study aimed to implement satellite remotely sensed data and hydrological modeling to dynamically assess the multiple factors within basin-scale hydrologic models for a realistic spatiotemporal prediction of SY in watersheds. (2) A connective algorithm was developed to incorporate dynamic models of the crop and cover management factor (C-factor) and the soil erodibility factor (K-factor) into the Soil and Water Assessment Tool (SWAT) with the aid of the Python programming language and Geographic Information Systems (GIS). The algorithm predicted the annual SY in each hydrologic response unit (HRU) of similar land cover, soil, and slope characteristics in watersheds between 2002 and 2013. (3) The modeled SY closely matched the observed SY using the connective algorithm with the inclusion of the two dynamic factors of K and C (predicted R2 (PR2): 0.60–0.70, R2: 0.70–0.80, Nash Sutcliffe efficiency (NS): 0.65–0.75). The findings of the study highlight the necessity of excellent spatial and temporal data in real-time hydrological modeling of catchments.

Evaluating the impact of interbasin water transfer on water quality in the recipient river basin with SWAT

During the second half of the 20th century in South Korea, interbasin water transfers (IBWTs) have been used to supply the water demands of basins with insufficient water using water from reservoirs in neighboring basins with ample water. However, since 2000, frequent droughts have resulted in water resource imbalances in donor basins, and basin residents have begun to claim their water rights. Recipient basins have also experienced water shortages and water quality deterioration due to gradual urban growth, agricultural activities, and climate change impacts. In this study, the Mangyeong River basin (1602 km²) was investigated. This basin has received 380 million m³/year of water since 2002 from the Yongdam multipurpose dam (YDD), which is located in another basin. For IBWT modeling, the Soil and Water Assessment Tool (SWAT) model and an inlet function were applied to model the recipient and donor water quality. Eight scenarios related to water transfer quantity and quality were applied with SWAT to analyze the effects of IBWT on the water quality in the recipient basin. The results showed that an increase in the IBWT amount helped to reduce the nutrient and suspended solids concentrations in the recipient basin when the donor's nutrient and suspended solids concentrations were lower than those in the recipient basin. The IBWT quantity scenarios had a greater impact on the water quality of the recipient basin than the IBWT quality scenarios. These results could provide basic information for use in deciding on the quantity and quality of IBWT between basins that are in conflict.

Prioritization of Sub-Watersheds to Sediment Yield and Evaluation of Best Management Practices in Highland Ethiopia, Finchaa Catchment

Excessive soil loss and sediment yield in the highlands of Ethiopia are the primary factors that accelerate the decline of land productivity, water resources, operation and function of existing water infrastructure, as well as soil and water management practices. This study was conducted at Finchaa catchment in the Upper Blue Nile basin of Ethiopia to estimate the rate of soil erosion and sediment loss and prioritize the most sensitive sub-watersheds using the Soil and Water Assessment Tool (SWAT) model. The SWAT model was calibrated and validated using the observed streamflow and sediment data. The average annual sediment yield (SY) in Finchaa catchment for the period 1990–2015 was 36.47 ton ha−1 yr−1 with the annual yield varying from negligible to about 107.2 ton ha−1 yr−1. Five sub-basins which account for about 24.83% of the area were predicted to suffer severely from soil erosion risks, with SY in excess of 50 ton ha−1 yr−1. Only 15.05% of the area within the tolerable rate of loss (below 11 ton ha−1yr−1) was considered as the least prioritized areas for maintenance of crop production. Despite the reasonable reduction of sediment yields by the management scenarios, the reduction by contour farming, slope terracing, zero free grazing and reforestation were still above the tolerable soil loss. Vegetative contour strips and soil bund were significant in reducing SY below the tolerable soil loss, which is equivalent to 63.9% and 64.8% reduction, respectively. In general, effective and sustainable soil erosion management requires not only prioritizations of the erosion hotspots but also prioritizations of the most effective management practices. We believe that the results provided new and updated insights that enable a proactive approach to preserve the soil and reduce land degradation risks that could allow resource regeneration.

Measuring and modeling event-based environmental flows: An assessment of HEC-RAS 2D rain-on-grid simulations

There is an immediate need to use available modeling tools to quantify environmental flows targets where changing climate and human activity has altered hydroecologically important streamflow regimes. A model performance assessment was undertaken using observed data collected from five nested gauging sites in a mixed land use watershed of the central US. An integrated modeling approach was used to couple The Soil and Water Assessment Tool (SWAT version 2012), and The Hydrologic Engineering Center's River Analysis System (HEC-RAS version 5.0.7). SWAT was used to generate effective rainfall needed to run HEC-RAS rain-on-grid two-dimensional hydrodynamic simulations. Model calibration results showed the potential usefulness of coupling SWAT and HEC-RAS using an integrated modeling approach. For example, PBIAS of 8.3%, NSE value of 0.84, and coefficient of determination (R²) value of 0.80 at a highly urbanized monitoring site used for model calibration. Split-site validation results showed PBIAS values that ranged from 10.4 to 33.8%, NSE values that ranged from 0.33 to 0.92, and R² values that ranged from 0.86 to 0.97. Results showed that 2D rain-on-grid HEC-RAS simulations can produce realistic simulations of stage hydrograph response when: (1) areal effective precipitation is used for 2D HEC-RAS rain-on-grid forcing's, (2) HEC-RAS is calibrated to observed data during the event of interest, (3) there are not substantial sources of backwatering from outside the models geometric data, and (4) during saturated antecedent soil moisture conditions surface DEM's adequately describe overland flow paths. This model performance assessment is among the first, if not the first, to show calibration and validation results associated with 2D HEC-RAS rain-on-grid simulations at a watershed scale. Results highlight the need for time-varying roughness coefficients to account for soil moisture conditions, and point to the efficacy of using a SWAT/HEC-RAS integrated modeling approach to generate event-based environmental flows information.

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the average runoff, high extreme runoff and intra-annual runoff distribution in the middle of the 21st century are analyzed. The following conclusions are obtained: (1) Compared with the base period (1970–1990), the average runoff of Tangnaihai, Toudaoguai, Sanmenxia and Lijin hydrological stations in the future period (2040–2060) all shows an increasing trend, and the probability of flood disaster also tends to increase; (2) Land use/cover change (LUCC) under the status quo continuation scenario will increase the possibility of future flood disasters; (3) The spring runoff proportion of the four hydrological stations in the future period shows a decreasing trend, which increases the risk of drought in spring. The winter runoff proportion tends to increase; (4) The monthly runoff proportion of the four hydrological stations in the future period tends to decrease in April, May, June, July and October. The monthly runoff proportion tends to increase in January, February, August, September and December.

Management of water quality targets based on river-lake water quality response relationships for lake basins - A case study of Dianchi Lake

In a lake basin, there is a mismatch between river and lake water quality targets and a method for setting specific water quality targets for these rivers is urgently needed. Using Dianchi Lake as an example, we proposed a lake basin water quality management system based on the river-lake water quality response relationship, coupled with a Soil and Water Assessment Tool (SWAT) basin hydrological model and Environmental Fluid Dynamics Code (EFDC) lake water quality hydrodynamic model. River water quality control requirements based on the river-lake water quality response were proposed, under the premise that the Dianchi Lake water quality reaches the required standard. Then, water quality control targets for rivers were determined, and corrected for influencing factors, such as current river water quality and composition of flow. Our systematic approach efficiently identified key lake basin pollution sources, and accurately located key points for water quality improvement and pollution control. Combined with a correction for clean water source and current water quality of each river, the proposed water quality targets were practical and operable. Meanwhile, the EFDC model was used to verify the entire process to ensure that river water quality targets could be set to achieve lake water quality targets. To ensure that Dianchi Lake water quality can reach Class IV standard, the Chemical oxygen demand (COD) concentration would need to be maintained under 30 mg/L,Waihai total nitrogen (TN) below 7 mg/L, total phosphorus (TP) below 0.2 mg/L, and ammonia nitrogen (NH₃-N) below 2 mg/L.

Hydro-climate and biogeochemical processes control watershed organic carbon inflows: Development of an in-stream organic carbon module coupled with a process-based hydrologic model

Dissolved organic carbon (DOC) in surface waters directly influences the speciation, transport, and fate of heavy metals, as well as the partitioning of organic contaminants. However, the lack of process-based watershed-scale models for simulating carbon cycling and transport has limited the effective watershed management to control organic carbon fluxes to source waters and throughout the river systems. Here, a process-based in-stream organic carbon (OC) module was developed, coupled with the physically process-based Soil and Water Assessment Tool (SWAT), and linked with its existing soil carbon module to simulate dynamics of both particulate organic carbon (POC) and DOC. The advanced model simulates a large spectrum of OC processes from landscapes to stream networks throughout the watersheds. In-stream organic carbon processes related to POC and DOC as state variables are modeled in the water column, and the transformations between different carbon species and interactions between OC with algae are considered. The module's ability to simulate total organic carbon (TOC) loads was assessed, and the monthly and seasonal variations were captured over 14 years. Simulations for TOC loads suggested that spring snowmelt and summer rainfall runoff events are the main driving forces behind TOC export in the watershed. The parameter sensitivity analysis and dynamic reaction rate simulated in the streams suggested that TOC dynamics in the study area are controlled by both landscape and in-stream processes. The spatiotemporal analysis of the simulated TOC load showed that 55.8% of total terrestrial OC exports into the streams are removed due to in-stream POC settling and DOC mineralization, confirming the necessity of integrating terrestrial and aquatic OC processes for process understanding and for modelling and management of water quality at the watershed scale. The developed OC module is a potentially effective tool for simulating the OC cycle at the watershed scale and can be applied further to water treatment plans and watershed management.

A Case-Study Application of the Experimental Watershed Study Design to Advance Adaptive Management of Contemporary Watersheds

Land managers are often inadequately informed to make management decisions in contemporary watersheds, in which sources of impairment are simultaneously shifting due to the combined influences of land use change, rapid ongoing human population growth, and changing environmental conditions. There is, thus, a great need for effective collaborative adaptive management (CAM; or derivatives) efforts utilizing an accepted methodological approach that provides data needed to properly identify and address past, present, and future sources of impairment. The experimental watershed study design holds great promise for meeting such needs and facilitating an effective collaborative and adaptive management process. To advance understanding of natural and anthropogenic influences on sources of impairment, and to demonstrate the approach in a contemporary watershed, a nested-scale experimental watershed study design was implemented in a representative, contemporary, mixed-use watershed located in Midwestern USA. Results identify challenges associated with CAM, and how the experimental watershed approach can help to objectively elucidate causal factors, target critical source areas, and provide the science-based information needed to make informed management decisions. Results show urban/suburban development and agriculture are primary drivers of alterations to watershed hydrology, streamflow regimes, transport of multiple water quality constituents, and stream physical habitat. However, several natural processes and watershed characteristics, such as surficial geology and stream system evolution, are likely compounding observed water quality impairment and aquatic habitat degradation. Given the varied and complicated set of factors contributing to such issues in the study watershed and other contemporary watersheds, watershed restoration is likely subject to physical limitations and should be conceptualized in the context of achievable goals/objectives. Overall, results demonstrate the immense, globally transferrable value of the experimental watershed approach and coupled CAM process to address contemporary water resource management challenges.

Sub-Daily Simulation of Mountain Flood Processes Based on the Modified Soil Water Assessment Tool (SWAT) Model

Floods not only provide a large amount of water resources, but they also cause serious disasters. Although there have been numerous hydrological studies on flood processes, most of these investigations were based on rainfall-type floods in plain areas. Few studies have examined high temporal resolution snowmelt floods in high-altitude mountainous areas. The Soil Water Assessment Tool (SWAT) model is a typical semi-distributed, hydrological model widely used in runoff and water quality simulations. The degree-day factor method used in SWAT utilizes only the average daily temperature as the criterion of snow melting and ignores the influence of accumulated temperature. Therefore, the influence of accumulated temperature on snowmelt was added by increasing the discriminating conditions of rain and snow, making that more suitable for the simulation of snowmelt processes in high-altitude mountainous areas. On the basis of the daily scale, the simulation of the flood process was modeled on an hourly scale. This research compared the results before and after the modification and revealed that the peak error decreased by 77% and the time error was reduced from ±11 h to ±1 h. This study provides an important reference for flood simulation and forecasting in mountainous areas.

The analysis of nitrogen load and simulation uncertainty using SWAT in a catchment with paddy field in China

Excessive load of nitrogen from anthropogenic sources is a threat to sustaining a healthy aquatic ecosystem. The difficulty in identifying the critical source areas (CSAs) of nitrogen load and apportioning the in-stream nitrogen to individual sources spatially and seasonally has made the Soil and Water Assessment Tool (SWAT) useful for analyzing nitrogen load at the catchment scale. However, the uncertainty of the nitrogen load simulated by SWAT has rarely been analyzed. The two simulations with the highest or the lowest PBIAS of total nitrogen (TN) load were proposed in this study to represent the range of the prediction uncertainty and therefore were used to generate the uncertainty of CSAs and nitrogen source apportionment. The model was set up for the Yuan River Catchment, which is under threat of extensive nitrogen load. Results indicated the highest nitrogen load was from downstream paddy fields with a denser population and 85% of the load was from fertilizer and feedlots. The relatively high prediction uncertainty was observed on both CSAs and source apportionment, which emphasizes the limitation of calibration only based on certain processes and the necessity to consider parameter uncertainty in the application of nitrogen load simulation.

Nitrate Runoff Contributing from the Agriculturally Intensive San Joaquin River Watershed to Bay-Delta in California

Nitrogen loading from agricultural landscapes can trigger a cascade of detrimental effects on aquatic ecosystems. Recently, the spread of aquatic weed infestations (Eichhornia crassipes, Egeria densa, Ludwigia spp., and Onagraceae) in the Sacramento-San Joaquin Delta of northern California has raised concerns, and nitrogen loading from California’s intensive farming regions is considered as one of the major contributors. In this study, we employed the Soil and Water Assessment Tool (SWAT) to simulate nitrogen exports from the agriculturally intensive San Joaquin River watershed to the Delta. The alternate tile drainage routine in SWAT was tested against monitoring data in the tile-drained area of the watershed to examine the suitability of the new routine for a tile nitrate simulation. We found that the physically based Hooghoudt and Kirkham tile drain routine improved model performance in representing tile nitrate runoff, which contributed to 40% of the nitrate loading to the San Joaquin River. Calibration results show that the simulated riverine nitrate loads matched the observed data fairly well. According to model simulation, the San Joaquin River plays a critical role in exporting nitrogen to the Delta by exporting 3135 tons of nitrate-nitrogen annually, which has a strong ecological implication in supporting the growth of aquatic weeds, which has impeded water flow, impairs commercial navigation and recreational activities, and degrades water quality in Bay-Delta waterways. Since nitrate loadings contributed by upstream runoff are an important nutrient to facilitate weed development, our study results should be seen as a prerequisite to evaluate the potential growth impact of aquatic weeds and scientific evidence for area-wide weed control decisions.

Impacts of climate change on streamflow and sediment concentration under RCP 4.5 and 8.5: A case study in Purna river basin, India

Climate change has a significant effect on various hydrological processes in a large river basin. The assessment of these processes is also useful for water resource management and long-term sustainability of any hydrological project. In this study, an attempt is made to quantify the effects of climate change on streamflow and sediment concentration in the Purna river basin, India. Three Regional Circulation Models (RCMs) with two Representative Concentration Pathways (RCPs) 4.5 and 8.5 for the four future periods of P1 (2009-2031), P2 (2032-2053), P3 (2054-2075) and P4 (2076-2099) are considered. Differences in scenarios are compared with the base period 1980-2005. The SWAT is used on monthly basis for the period 1980 to 2005 with calibration period 1980 to 1994 and validation period 1995 to 2005. The projected precipitation and temperature show a significant increasing trend compared to the baseline condition for both RCPs. Similarly, the average monthly streamflow is projected to increase by 24.47 to 115.94m³/s whereas average monthly sediment concentration by 32.58 to 162.96mg/l under RCP 4.5 and 8.5. In particular, streamflow and sediment are expected to increase significantly from June to September at the outlet of the basin. The study results give insight into future hydrological scenarios which will be useful for policy makers to implement effective water resource strategies.

Prediction of land use changes based on Land Change Modeler and attribution of changes in the water balance of Ganga basin to land use change using the SWAT model

Conflicts between increasing irrigated agricultural area, commercial crops, shifting cultivation and ever increasing domestic and industrial demand has already been a cause of tension in the society over water in the Ganga River Basin, India. For the development of sustainable water resource strategies, it is essential to establish interaction between landuse changes and local hydrology through proper assessment. Precisely, seeing how change in each LULC affects hydrologic regimes, or conversely evaluating which LULC shall be appropriate for the local hydrological regime can help decision makers to incorporate in the policy instruments. In this study, hydrologic regimes of the Ganga River basin have been assessed with landuse change. Catchment hydrologic responses were simulated using Soil and Water Assessment Tool (SWAT). Meteorological data from IMD of 0.25° × 0.25° spatial resolution were taken as the climate inputs. Simulated stream flow was compared at different gauge stations distributed across the Gang River and its tributaries. Urbanization has been the topmost contributor to the increase in surface runoff and water yield. While increased irrigation demands were the dominant contributor to the water consumption and also added to the increased evapotranspiration. This study can be important tool in quantifying the changes in hydrological components in response to changes made in landuse in especially basins undergoing rapid commercialization. This shall provide substantive information to the decision makers required to develop ameliorative strategies.

An integrated modeling approach for estimating hydrologic responses to future urbanization and climate changes in a mixed-use midwestern watershed

Future urban development and climatic changes are likely to affect hydrologic regimes in many watersheds. Quantifying potential water regime changes caused by these stressors is therefore crucial for enabling decision makers to develop viable environmental management strategies. This study presents an approach that integrates mid-21st century impervious surface growth estimates derived from the Imperviousness Change Analysis Tool with downscaled climate model projections and a hydrologic model Soil and Water Assessment Tool to characterize potential water regime changes in a mixed-use watershed in central Missouri, USA. Results for the climate change only scenario showed annual streamflow and runoff decreases (-10.7% and -9.2%) and evapotranspiration increases (+6.8%), while results from the urbanization only scenario showed streamflow and runoff increases (+3.8% and +9.3%) and evapotranspiration decreases (-2.4%). Results for the combined impacts scenario suggested that climatic changes could have a larger impact than urbanization on annual streamflow, (overall decrease of -6.1%), and could largely negate surface runoff increases caused by urbanization. For the same scenario, climatic changes exerted a stronger influence on annual evapotranspiration than urbanization (+3.9%). Seasonal results indicated that the relative influences of urbanization and climatic changes vary seasonally. Climatic changes most greatly influenced streamflow and runoff during winter and summer, and evapotranspiration during summer. During some seasons the directional change for hydrologic processes matched for both stressors. This work presented a practicable approach for investigating the relative influences of mid-21st century urbanization and climatic changes on the hydrology of a representative mixed-use watershed, adding to a limited body of research on this topic. This was done using a transferrable approach that can be adapted for watersheds in other regions.

Modeling pesticide diuron loading from the San Joaquin watershed into the Sacramento-San Joaquin Delta using SWAT

Quantifying pesticide loading into the Sacramento-San Joaquin Delta of northern California is critical for water quality management in the region, and potentially useful for biological weed control planning. In this study, the Soil and Water Assessment Tool (SWAT) was applied to model streamflow, sediment, and pesticide diuron loading in the San Joaquin watershed, a major contributing area to the elevated pesticide levels in the downstream Delta. The Sequential Uncertainty Fitting version 2 (SUFI-2) algorithm was employed to perform calibration and uncertainty analysis. A combination of performance measures (PMs) and standardized performance evaluation criteria (PEC) was applied to evaluate model performance, while prediction uncertainty was quantified by 95% prediction uncertainty band (95PPU). Results showed that streamflow simulation was at least "satisfactory" at most stations, with more than 50% of the observed data bracketed by the 95PPU. Sediment simulation was rated as at least "satisfactory" based on two PMs, and diuron simulation was judged as "good" by all PMs. The 95PPU of sediment and diuron bracketed about 40% and 30% of the observed data, respectively. Significant correlations were observed between the diuron loads, and precipitation, streamflow, and the current and antecedent pesticide use. Results also showed that the majority (>70%) of agricultural diuron was transported during winter months, when direct exposure of biocontrol agents to diuron runoff is limited. However, exposure in the dry season could be a concern because diuron is relatively persistent in aquatic system. This study not only provides valuable information for the development of biological weed control plan in the Delta, but also serves as a foundation for the continued research on calibration, evaluation, and uncertainty analysis of spatially distributed, physically based hydrologic models.