Soil And Water Assessment Tool Model Research Articles

Identifying critical source areas of non-point source pollution to enhance water quality: Integrated SWAT modeling and multi-variable statistical analysis to reveal key variables and thresholds

By integrating soil and water assessment tool (SWAT) modeling and land use and land cover (LULC) based multi-variable statistical analysis, this study aimed to identify driving factors, potential thresholds, and critical source areas (CSAs) to enhance water quality in southern Alabama and northwest Florida's Choctawhatchee Watershed. The results revealed the significance of forest cover and of the lumped developed areas and cultivated crops ("Source Areas") in influencing water quality. The stepwise linear regression analysis based on self-organizing maps (SOMs) showed that a negative correlation between forest percent cover and total nitrogen (TN), organic nitrogen (ORGN), and organic phosphorus (ORGP), highlighting the importance of forests in reducing nutrient loads. Conversely, Source Area percentage was positively correlated with total phosphorus (TP) loads, indicating the influence of human activities on TP levels. The receiver operating characteristic (ROC) curve analysis determined thresholds for forest percentage and Source Area percentage as 37.47 % and 20.26 %, respectively. These thresholds serve as important reference points for identifying CSAs. The CSAs identified based on these thresholds covered a relatively small portion (28 %) but contributed 47 % of TN and 50 % of TP of the whole watershed. The study underscores the importance of considering both physical process-based modeling and multi-variable statistical analysis for a comprehensive understanding of watershed management, i.e., the identification of CSAs and the associated variables and their tipping points to maintain water quality.

Evaluation of BMPs in Flatland Watershed with Pumped Outlet

The effectiveness of existing and potential best management practices (BMPs) to cropped lands in the Jeannette Creek watershed (Thames River basin, Ontario, Canada) in reducing P loads at its pumped outlets was assessed using the Soil and Water Assessment Tool (SWAT). Existing BMPs consisted of banded, incorporated, and variable phosphorus (P)-rate application, conservation tillage, cover crops, and vegetative buffer strips. Potential BMPs consisted of banded P application, no-till, and a cover crop following winter wheat. Two separately delineated sub-watersheds, J1 and J2, characterized by a flat topography and distinct pumped outlets, were selected for analysis. Despite challenges in delineation, the SWAT model was successfully set up to assess the impact of BMPs in reducing P loads in these sub-watersheds. Each BMP was systematically removed, and the resulting simulated P loads were compared with the baseline scenario. Compared to cover crops or vegetative buffer strips, the implementation of conservation tillage and no-till, along with altering the mode of P application, offered superior effectiveness in reducing the P load. On average, the annual reduction in total P (Ptot) loads under existing BMPs was 9.2% in J1 and 11.3% in J2, whereas, under potential BMPs, this reduction exceeded 60% in both watersheds.

Application of SWAT Model for Assessment of Surface Runoff in Flash Flood Areas

In addition to changes in the amount of rain, changes in land use upstream are considered a factor that directly affects the maximum runoff flow in a basin, especially in areas that have experienced floods and flash floods. This research article presents the application of the SWAT model to assess runoff in areas that have experienced flash floods, in order to analyze the proportion of land use change to the maximum runoff. Study areas that experienced flash floods were in three basins in Thailand (Lam Saphung Basin, Phrom River Basin, and Chern River Basin Part 1, which is a sub-basin of the Nam Chi River Basin). This study analyzed two main factors that influenced runoff in the river basin by considering two simulation situations: (1) changes in land use affecting runoff assessed by considering land use maps in 2006, 2008, 2010, 2015, 2017, 2019, and 2021 when using rainfall data only in the year 2021 for all cases and (2) changes in the amount of rainfall influencing runoff by considering the rainfall records in 2006, 2008, 2010, 2015, 2017, 2019, and 2021 when using the land use data only in the year 2021 for all cases. The results of the study found that the SWAT model can be effectively applied to estimate annual runoff in areas that have experienced flash floods under eight parameters with R2 values of 0.74, 0.82, and 0.74 for the Lam Saphung River Basin, Phrom River Basin, and Chern River Basin Part 1, respectively. In addition, it was found that the proportion of land use changes that involved changes from forested areas to residential areas was the greatest from 2008 to 2010 in the Phrom River Basin and Chern River Basin Part 1. This resulted in an increase in the maximum runoff amounts of 77.78% and 46.87%, respectively. When land use was constant, it was found that the rainfall in 2010, which was the highest, also had the greatest impact on the runoff in all three areas.

Water conservation pattern of Fangcheng River Basin in Beibu Gulf and its response to precipitation.

Assessing the spatiotemporal patterns of watershed water conservation under the influence of the South Asian monsoon climate and its response to precipitation is essential for revealing the evolving patterns of water conservation under different temporal scales. Following the principles of water balance and using the Soil and Water Assessment Tool (SWAT) model, we investigated the spatiotemporal patterns of water conservation and its response to precipitation in the Fangcheng River Basin of Beibu Gulf. The results showed that water conservation in Fangcheng River Basin calculated by SWAT model were 1637.4 mm·a-1, accounting for 50.7% of the mean annual precipitation. The variation of water conservation in different sub-basins was obviously different. Sub-basins with high forest coverage and steep slopes exhibited higher water conservation, while sub-basins with other land use types (such as cropland and grassland), gentle slopes, and intense human activities showed lower water conservation. At the monthly scale, both water conservation and its variation showed similar response characteristics to precipitation in the basin. The response of water conservation variation to sub-precipitation events could be classified into two types. For the short-term rainfall events (duration≤2 days), water conservation variation showed a linear relationship. For the medium to long-term rainfall events (2 days<duration≤10 days), water conservation variation showed a nonlinear curve, being influenced mainly by processes such as evapotranspiration. High-frequency short-duration precipitation events were more conducive to increasing ecosystem water conservation compared to the long-duration precipitation events.

Divergent path: isolating land use and climate change impact on river runoff

Water resource management requires a thorough examination of how land use and climate change affect streamflow; however, the potential impacts of land-use changes are frequently ignored. Therefore, the principal goal of this study is to isolate the effects of anticipated climate and land-use changes on streamflow at the Indus River, Besham, Pakistan, using the Soil and Water Assessment Tool (SWAT). The multimodal ensemble (MME) of 11 general circulation models (GCMs) under two shared socioeconomic pathways (SSPs) 245 and 585 was computed using the Taylor skill score (TSS) and rating metric (RM). Future land use was predicted using the cellular automata artificial neural network (CA-ANN). The impacts of climate change and land-use change were assessed on streamflow under various SSPs and land-use scenarios. To calibrate and validate the SWAT model, the historical record (1991–2013) was divided into the following two parts: calibration (1991–2006) and validation (2007–2013). The SWAT model performed well in simulating streamflow with NSE, R2, and RSR values during the calibration and validation phases, which are 0.77, 0.79, and 0.48 and 0.76, 0.78, and 0.49, respectively. The results show that climate change (97.47%) has a greater effect on river runoff than land-use change (2.53%). Moreover, the impact of SSP585 (5.84%–19.42%) is higher than that of SSP245 (1.58%–4%). The computed impacts of climate and land-use changes are recommended to be incorporated into water policies to bring sustainability to the water environment.

Assessing environmental sustainability of a vital crop in a critical region: Investigating climate change impacts on agriculture using the SWAT model and HWA method

Drought is an occurrence that brings about significant changes to the structure of areas. Its influence is especially noticeable in important regions with dry and semi-dry weather patterns, leading to a range of difficulties including interruptions in food distribution systems, lack of water, health problems, economic declines, increased migration, and inadequate energy supply. The Ardabil plain, located in Asia and the northern-western region of Iran, plays a pivotal role in crop productions within an arid environment and holds significant political importance for the country. The main objective of this study is to enhance environmental sustainability in this critical and vulnerable region, particularly in anticipation of imminent droughts. The study focuses on examining the financial impacts on agriculture and selection a crop using the SWAT model, HWA method and climate scenarios under the RCP8.5 pathway for the future period (2040–2050). Results for the near future indicate a notable decline in rainfall of around 38 %, a reduction in wheat production by approximately 25 %, and an increase in temperature of around 30 %. At present, the Ardabil Plain produces a total of 284,182 tons of wheat, with 204,980 tons from irrigated crops and 79,202 tons from rain-fed crops. However, the projected future scenario indicates a decrease in total wheat production to 202,926 tons, with 153,855 tons from irrigated crops and 49,071 tons from rain-fed crops. This decline in production is expected to lead to a total net income loss of approximately -$139,372,437, with -$87,690,344 attributed to irrigated crops and -$51,682,092 to rain-fed crops. The comprehensive hierarchy of crop choices yielded by the HWA method is outlined as follows: barley holds a superior position, followed by wheat, soybeans, and potatoes. The study findings suggest that the availability of water sources in certain regions may prompt a shift in farming land from the north to the south of the plain to promote environmental sustainability.

Delineation Suitable Rainwater Harvesting Sites in Wadi Al-Mohammadi, Iraq

Water harvesting has become one of the topics of concern to most water specialists, due to its importance in managing water and preserving it from squandering. Wadi Al-Mohammadi is an example of a valley that needs the application of water harvesting and the exploitation of rainwater at all levels, being one of the main valleys in the Iraqi desert where surface water is lacking. The outcomes for water harvesting were derived using the SWAT model. Morphometric, the basin’s shape is far from being circular. Climatologic, the trend line indicates a clear increase in the total rainfall, relative humidity, temperature, and solar radiation, while the trend line indicates a decrease in the wind speed during the observed period. The main contributor to the total flow of Wadi Al-Mohammadi basin was surface runoff of about 99%, the base flow of about 1%, while the groundwater flow did not contribute any amount of that water. The annual average flow discharge was 0.138 m3/s with the average annual water volume being about 4.366 Mm3, while the average annual water volume calculated from runoff was about 4.651 Mm3. Dam 1 is the best-selected site with a suitable index of 97.5 followed by Dam 5, and Dam 2 with a suitable index of 95 and 90, respectively. Hence it falls under the category of highly suitable. The Dam 3 site falls within the modestly suitable category. Finally, the site of Dam 4 could not be established, because they had a suitability index of less than 70.

Enhancing hydrological model calibration through hybrid strategies in data‐scarce regions

AbstractCalibration of a hydrological model is a challenging task, especially in basins that are data scarce. With the incorporation of regional information and integration with satellite data, the parameters of hydrological models can be estimated for a basin with scant or no discharge records. The main objective of this study is to calibrate and validate a hydrological model based on a limited amount of in‐situ measured and remote sensing satellite datasets in a data‐sparse region. Multiple techniques were applied for the model calibration: (1) stage‐discharge curves using a spatial proximity approach, (2) Simplified Surface Energy Balance actual evapotranspiration, (3) river discharge using a physical similarity regionalization approach, and (4) a new hybrid approach by integrating remote sensing datasets along with field measured river bathymetry data to estimate the river discharge. To demonstrate the methodology, we employed the widely used Soil and Water Assessment Tool (SWAT) hydrological model in Manipur River Basin, India. The sensitivity, calibration, and validation of the SWAT model were carried out by using the Sequential Uncertainty Fitting Technique. During calibration, the coefficient of determination (R2) and the Kling Gupta Efficiency (KGE) were found to be in the range of 0.46–0.81 and 0.41–0.83, whereas during validation R2 and KGE were found to be in the range of 0.40–0.79 and 0.53–0.77 for the four different techniques. Among all the four techniques applied in this study, calibration based on (i) stage‐discharge curve using spatial proximity approach and (ii) new hybrid approach by integrating remote sensing datasets and river bathymetry were found as the better approaches as indicated by the statistical indices. The performance evaluation of the model through a new hybrid approach by integrating remote sensing and in‐situ measured datasets for rivers with narrow width represents a promising technique for use in a data sparse region.

Quantification of the impact of land cover and climate change on water and sediment yield in sub-tropical Himalayas in upstream Teesta river basin, Sikkim

The assessment of isolated and combined impact of land cover (LULC) and climate change on water and sediment yield of hilly watershed is essential for sustainable land and water management and social developments. An improved hydrological modelling approach coupled with statistical tools was used to explore the role played by LULC and climate change on key water balance components and sediment yield (SY). The calibrated Soil and Water Assessment Tool (SWAT) model was used to simulate the key hydrological components and SY from 1990 to 2019 (historical) and 2020 to 2059 (near-future). The trends and slope analysis were carried out to understand the temporal shift in meteorological timeseries and to aid in interpretation of climate change impacts on variables.Historically, the LULC change led to decrease in actual evapotranspiration, streamflow, baseflow, and water yield (WY) (∼4 %) and increase in lateral flow, and SY (∼36 %). Consistent results were also obtained in all seasons. In near future, the impact of LULC change on these variables is anticipated to be negligible in all aspects. The climate change under historical scenario has substantially increased the magnitude of all variables at annual scale as well as in all seasons except winter season. The historical increase in annual WY and SY is ∼12 % and ∼25 %. Also, a substantial increase in magnitude of all variables is projected during monsoon under SSP2-4.8 and SSP5-8.5 emission scenario. The suggested approach has promising results in isolating the effect of LULC and climate change on SY, WY and some key hydrological components over upstream Teesta River basin supporting with consistent results from the previous studies from different areas.The SWAT model effectively captured streamflow and SY dynamics at daily timescales during calibration and validation. Additionally, our proposed approach demonstrated promising results in discerning the distinct impacts of LULC and climate variations on WY and SY.

Hydrological assessment of the Gundlakamma sub-basin through SWAT modeling: integration of land use land cover (LULC) and climate changes

Abstract Gundlakamma sub-basin faces challenges with increasing water demand and climate change impacts, requiring innovative solutions for sustainable water management. The study was conducted to improve the long-term utilization of water resources in Andhra Pradesh. To accomplish this, the study attempts to estimate LULC change detection and its impact on water resources by analyzing the performance of the soil and water assessment tool (SWAT) model. From 2005 to 2021, the amount of cropland decreased while built-up land increased, indicating urban growth. The SWAT model identifies hydrological processes and assesses the temporal and spatial distribution of water resources in the watershed. Statistical parameters results reveal that a good match was found between actual and modeled flows with Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R2) greater than 0.75 for both calibration and validation periods. The area has average annual precipitation, surface runoff, water yield, and actual evapotranspiration of 949.96, 215.6, 469.24, and 429.15 mm, respectively. The SWAT model's fascinating outcomes demonstrate that it could be a promising decision support tool for predicting water balance and water yield in other watersheds of Andhra Pradesh for sustainable water management of water resources where water quality and quantity are critical issues.

Improving rainfall-runoff modeling in the Mekong river basin using bias-corrected satellite precipitation products by convolutional neural networks

Accurate rainfall-runoff (RR) modeling is crucial for effective Mekong River Basin (MRB) water resource management. Satellite precipitation products (SPPs) can offer valuable data for such modeling; however, these products often exhibit biases that may adversely affect hydrological simulations. This study aimed to improve RR modeling using bias-corrected SPPs and the Soil and Water Assessment Tool (SWAT) model for MRB. A convolutional neural network-based deep learning framework was employed to correct biases in four SPPs (TRMM, PERSIANN-CDR, CHIRPS, and CMORPH), resulting in four respective bias-corrected SPPs (ADJ_TRMM, ADJ_CDR, ADJ_CHIR, and ADJ_CMOR). The bias-corrected products were compared against a gauge-based dataset in terms of rainfall analysis, and their performance within the SWAT model was assessed over calibration (2004–2013) and validation (2014–2015). Bias-corrected products demonstrated superior performance in rainfall analysis, with ADJ_TRMM outperforming other products. The SWAT model calibration results showed satisfactory performance across all stations, with a Nash-Sutcliffe Efficiency (NSE) ranging from [0.76–0.87]. Integrating bias-corrected SPPs into the SWAT model significantly increased the RR simulations in the MRB, indicated by higher NSE values [0.72–0.85] compared to uncorrected SPPs [-0.37 to 0.85] at the Kratie station. Besides, the inconsistent performance of bias-corrected products between rainfall analysis and RR modeling was observed, with ADJ_CDR outperforming ADJ_TRMM in the SWAT model. These results highlight the significance of using bias-corrected SPPs in hydrological modeling applications, especially in areas with limited ground-based precipitation data, and highlight the need for further research to refine bias correction methods and address the limitations of the SWAT model.

Impacts of land use and climate change on runoff in the Shaying River Basin based on SWAT model

Impacts of land use and climate change on runoff in the Shaying River Basin based on SWAT model

Hydrological Responses to Climate Change and Land-Use Dynamics in Central Asia's Semi-arid Regions: An SWAT Model Analysis of the Tuul River Basin

Hydrological Responses to Climate Change and Land-Use Dynamics in Central Asia's Semi-arid Regions: An SWAT Model Analysis of the Tuul River Basin

Multivariate adaptive regression splines-assisted approximate Bayesian computation for calibration of complex hydrological models

Abstract Approximate Bayesian computation (ABC) relaxes the need to derive explicit likelihood functions required by formal Bayesian analysis. However, the high computational cost of evaluating models limits the application of Bayesian inference in hydrological modeling. In this paper, multivariate adaptive regression splines (MARS) are used to expedite the ABC calibration process. The MARS model is trained using 6,561 runoff simulations generated by the soil and water assessment tool (SWAT) model and subsequently replaces the SWAT model to calculate the objective functions in ABC and multi-objective evolutionary algorithm (MOEA). In experiments, MARS can successfully reproduce the runoff time series simulations of the SWAT model at a low time cost, with a runoff variance determination coefficient of 0.90 as compared to the Monte Carlo method. MARS-assisted ABC can quickly and accurately estimate the parameter distributions of the SWAT model. The comparison of ABC with non-Bayesian MOEAs helps in the selection of an appropriate calibration approach.

Assessment of the response characteristics of pollution load in Huntai Basin under climate change.

This study establishes a calibrated SWAT (Soil and Water Assessment Tool) model for the Huntai Basin, driven by SSP126, SSP245, SSP585, and multi-model ensemble (MME) models in CMIP6 (Coupled Model Intercomparison Project-6), to investigate the effects of climate change on hydrological processes and pollution load in the Huntai Basin. The results show that the annual mean temperature and the annual precipitation will gradually increase. The nitrogen and phosphorus pollution loads in the basin exhibit a trend of decreasing-increasing-decreasing. The correlation between the nitrogen-phosphorus pollution load and the hydrological process strengthens with increasing radiative forcing. In the four scenarios, CO2 is a primary driving factor that contributes greatly to nitrogen and phosphorus pollution. The main differences are in the total driving factors, and SSP126 and SSP245 are less than those of other models. The total phosphorus and total nitrogen pollution in different climate models were higher than the average level during the benchmark period, except for ammonia nitrogen pollution, which was lower. The nitrogen and phosphorus pollution in SSP126 and SSP245 modes will reach the maximum in 2040s, and the pollution in other periods will be lower than that in SSP585 and MME scenarios. In the long run, the development state between SSP126 and SSP245 may be better appropriate for the Huntai Basin's future sustainable development. This paper analyzes the occurrence and influencing factors of nitrogen and phosphorus pollution under climate change to provide reference to the protection of water environment under changing environments.

The Ripple Effect of Climate Change: Assessing the Impacts on Water Quality and Hydrology in Addis Ababa City (Akaki Catchment).

This research aimed to evaluate the effects of climate change on the hydrology and water quality in the Akaki catchment, which provides water to Addis Ababa, Ethiopia. This was performed using the soil and water assessment tool (SWAT) model and an ensemble of four global climate models under two Shared Socioeconomic Pathways (SSP) emission scenarios from Coupled Model Intercomparison Project Phase 6 (CMIP6). The climate data were downscaled and bias-corrected using the CMhyd tool and calibrated and validated using the SWAT-CUP software package. Change points and patterns in annual rainfall and temperature were determined using the homogeneity test and Mann-Kendell trend test. Water quality data were obtained from Addis Ababa Water and Sewerage Authority (AAWSA), and more samples were taken and analyzed in accordance with APHA recommended procedures. The SWAT model output was then used to assess the impacts of climate change on hydrological components and water quality. Rainfall increased by 19.39 mm/year under SSP2-4.5 and 12.8 mm/year under SSP8.5. Maximum temperature increased by 0.03°C/yr for SSP2-4.5 and 0.04°C/yr for SSP5-8.5. Minimum temperature increased by 0.03°C/yr under SSP2-4.5 and 0.07°C/yr under SSP5-8.5. This warming will augment the evapotranspiration rate which in turn will have a negative impact on the freshwater availability. Streamflow will increase by 5% under SSP2-4.5 and 9.49% under SSP5-85 which may increase sporadic flooding events. Climate change is expected to contribute to the deterioration of water quality shown by 61%, 36%, 79%, 115%, and 70% increased ammonia, chlorophyll-a, nitrite, nitrate, and phosphorus loadings, respectively, from 2022. The increase in temperature results in increases in nutrient loading and a decrease in dissolved oxygen. Overall, this research demonstrated the vulnerability of the catchment to climate change. The findings of this research can offer vital knowledge to policymakers on possible strategies for the sustainable management of water.

A modeling approach for evaluating and predicting the impacts of land use land cover changes on groundwater recharge in Walga Watershed, Upper Omo Basin, Central Ethiopia

Study regionWalga watershed, Upper Omo basin, Ethiopia (2349 km2). Study focusThis research aimed to understand and predict the impacts of LULC changes on groundwater recharge in Walga watershed. Thus, the historical LULC changes in Walga watershed was assessed from Landsat: 4–5 TM, 7 ETM + and 8 OLI-TIRS (1990, 2006, and 2021), through Hybrid classification of unsupervised and supervised scheme using Erdas Image 2015, while future LULC was predicted using CA–Markov chain analysis approach in QGIS-MOLUSCE plugin. The LULC change impact scenarios on groundwater recharge was assessed using SWAT model. New hydrological insightsThe evaluation of LULC changes pointed out that Walga watershed has undergone high intensity of LULC changes (1990–2021) due to anthropogenic activities and predicted to instantly change in the coming (2021–2035). The hydrological assessments indicate that groundwater recharge was declined over the last three decades by 20.84 mm and predicted to decline in future (2021–2035) by 6.17 mm. This implies that the declined recharge was linked to LULC changes over time with deforestation and agricultural land expansion. This means due to changes in agriculture (+26.3 %, +15.4 %), mixed forest (−3.7, −2.3 %), rangelands (−23.8 %, −8.8 %), grazing land (−2.6 %, −2.0 %), and urban (+1.14 %, +0.46 %) during (1990–2021) and (2021–2035). These outcomes provide baseline information for decision makers concerning LULC and groundwater for better planning and management strategies in the watershed.

Effects of land use changes on green water along upper and middle reaches of Huaihe River Basin

Study regionThe Upper and Middle Reaches of the Huaihe River Basin Study focusThe examination of the ramifications of alterations in land utilization on terrestrial water resources holds paramount importance in the realm of agricultural water resource management. Despite progress in understanding the cumulative impacts of land use on terrestrial water bodies, the understanding of the exact impacts of a single land use on terrestrial water bodies is still insufficient. In this investigation, the SWAT model was employed to meticulously delve into the ramifications of modifications in land use on the quantity of green water in the middle and upper stretches of the Huaihe River, with a focus on simulating the hydrological cycle. Furthermore, this inquiry introduces a novel coefficient of impact to scrutinize the repercussions of specific land use changes on terrestrial water bodies. New hydrological insights for the regionThe outcomes of the study unveil that albeit the spatial expanse of certain land use categories is restricted, their repercussions on terrestrial water bodies reverberate extensively. Ultimately, the classification of forest land and agricultural acreage underwent refinement, incorporating considerations of vegetation cover and crop typology. The inquiry establishes that the extent of forest land and the genre of crops cultivated on agricultural land stand as pivotal determinants of terrestrial water dynamics.

A model for quantifying the effectiveness of leaky barriers as a flood mitigation intervention in an agricultural landscape

AbstractLeaky barriers have become an important mitigation option within natural flood management to reduce downstream flood risk. Modelling is a key tool to aid in the design of leaky barrier installations for flood mitigation, but there is limited evidence about the accuracy of model representations of the system. Here, the hydrological model SWAT was combined with a water routing model that simulates multiple leaky barriers as permeable sluice gates. Storage behind individual barriers was quantified using barrier dimensions and LIDAR topography. The model was applied to a series of 27 leaky barriers installed as part of a long‐term manipulation experiment into a 11‐km2 intensive lowland agricultural catchment in Leicestershire, England. Evaluation of the model against flow data collected before and after leaky barrier installation and time‐lapse photography taken across storm events at individual barriers demonstrated robust model performance (Nash‐Sutcliffe efficiency and R2 across 19 validation events were 0.84 ± 0.14 and 0.91 ± 0.08, respectively). Empirical and modelling data were then combined to demonstrate that the 17,700 m3 of water storage provided by the 27 leaky barriers reduced peak flows at the catchment outlet by 22 ± 6% and delayed the peak in flow by up to 5 h for 11 storm events recorded after all barriers had been installed. The volume of storage utilised prior to the flood event was a key factor influencing the reduction in peak flow, and a sensitivity analysis indicated that barriers should be permeable to accelerate drain‐down of the barrier and help to mitigate risk from multiple storm events occurring in sequence.

Quantifying the consequences of unsustainable sand mining and cascade dams on aspects in a tropical river basin

Human interventions at the river basin scale, such as sand mining and hydropower dam construction, have profoundly affected hydrological and hydraulic alteration regimes, sediment budgets, and morphological changes worldwide. Quantifying the consequences of unsustainable ongoing sand mining and hydropower is crucial for obtaining sediment load data and managing hydrogeomorphology. In this study, comprehensive long-term consecutive four-field monitoring, statistical methods, and hydrological models (SWAT) were applied to quantify the spatiotemporal changes in long-term discharge and sediment load from 1996 to 2020 for the tropical river of the Vu Gia Thu Bon (VGTB) in the central region of Vietnam. The SWAT model was calibrated from 1996 to 2010, validated from 2011 to 2020 and showed good performance for daily discharge and monthly sediment. The evolution of river bathymetric data (2010, 2015, 2018, and 2021) was analysed to clarify the upstream sediment supply trapped in the riverbed and how the sand mining volume was removed. The results showed that the mean annual sediment in the Vu Gia and Thu Bon Rivers decreased by 57.3% and 23.8%, respectively, in the postdam period compared with the predam period. The thalweg elevation decreased at the Ai Nghia and Giao Thuy stations from 2010 to 2021 by 1.8 m and 3.9 m, respectively. The water level decreased by 21.1% at Ai Nghia and 44.3% at Giao Thuy. Dam development, sand mining, and changes in land use are the main factors responsible for flow discharge and sediment morphodynamic alterations. Morphological change have increased the water transfer rate from the Vu Gia River to the Thu Bon River through the Quang Hue channel. Downstream of the Vu Gia River, water transfer and riverbed incision have decreased flow discharge and water level and increased saltwater intrusion in recent years. As a result, water shortages induced by saltwater intrusion during drought periods have emerged as a significant constraint in hindering the domestic water supply and agricultural production.