River Watershed Research Articles

Analysis Hydromorphometric of Qandil River Baisn

The watershed of the Qandil River is located in the northeast of Sulaimani province and the east of the Kurdistan Region. Physio-graphically, the study area is considered to be a rugged mountainous area, astronomically located between the latitudes (36 13 14–36 31 15) north and the longitudes (44 53 52–45 06 13) east. The area of the watershed is (219 km2) The main objective of this study is to identify the environmental characteristics of the study area and draw specific maps for each of them in order to take the necessary steps to analyze the hydromorphometric area. At the beginning of the study, the natural environment of the watershed of the Qandil River and its effects on hydromorphometric factors such as (Geology, altitude, and climate were analyzed. This is by analyzing the characteristics of each of these genders and their effects at different levels at the level of water resources. In the second part, focused on each of the most important geomorphology and morphometry of watersheds of the Qandil river watershed, which consists of two watersheds. In the first topic, after preparing the map of the river irrigation network, the most important geomorphological features of the watersheds are discussed, such as main rivers, branches, irrigation systems, streams and their types. In the second topic, the most important morphometric measurements were doing for watersheds. On this topic, emphasis was placed on the study of their characteristics (area, shape, altitude, and river network). The results of the study show that the natural characteristics of the study area play a major role in the richness of water resources and the rapid flow of streams, tributaries, and the main river of the watershed.

Hydrodynamic Groundwater Modeling and Hydrochemical Conceptualization of the Closure Mining Area of the WuMa River Watershed of China.

The WuMa River (WMR) watershed is located in Renhuai City, Guizhou Province of China, which is a first-class tributary of the Chishui River. The geochemical investigation mainly included the determination of groundwater pH, total hardness, total dissolution solid, major cationic and anionic, and the geochemical groundwater modeling. The principal component analysis (PCA) and Gibbs model were used to analyze the pollution type and geochemical composition. The geochemical investigation results show that the cations of groundwater are dominated by Ca2+ and the anions are dominated by HCO3-; therefore, two main hydrochemical types in the study area are identified as Ca2+-Mg2+-HCO3- and Ca2+-Mg2+-SO42-. The chemical composition of groundwater in this area is mainly controlled by weathering of the carbonate rocks. The ion concentration of groundwater in the study area exhibited significant spatial variability between dry and wet seasons, while temporal changes of cationic and anionic concentrations exhibited irregularities. In PCA and FA analysis, PC1, PC2, and PC3 were extracted, which could explain 51.92, 26.98, and 12.61% of the total information, respectively. F1 explained 67.44% of the total variance, among which Ca2+, Mg2+, K+, SO42-, and Cl- contributed the most among the factors and were the main factors controlling the chemical composition of groundwater. The relative error between the measured water level and the simulated water level is less than 2%, which meets the requirements of simulation accuracy. During the simulation period of the model, a total recharge of 339.05 × 104 m3 was observed in the simulated area, primarily attributed to infiltration from rainfall. The total excretion amounted to 330.78 × 104 m3, primarily through evaporation, with a minor amount of lateral outflow. The migration pathway of pollutants in groundwater primarily follows the direction of groundwater flow while diffusing vertically. The migration range of the pollutant is in accordance with the direction of groundwater flow and extends along the larger hydraulic gradient, demonstrating consistency. The findings of this study serve as a reminder that the closure of coal mines can constitute a significant source of water pollution. Simultaneously, they offer empirical data and theoretical references for the simulation and prediction of groundwater contamination in enclosed coal mines.

The role of changing land use and irrigation scheduling in groundwater depletion mitigation in a humid region

Many agricultural production regions in the world have been experiencing groundwater resource depletion, which threatens water and food security if mitigation practices are not developed and implemented. To understand how changing land use and irrigation schedule impact groundwater, a coupled SWAT-MODFLOW model was applied to determine groundwater depletion mitigation strategy in a humid region, the Big Sunflower River Watershed (BSRW) in Mississippi, USA. It was found that converting grasslands to forests contributed to reducing groundwater declining. Simulated results indicated that the watershed lost 749, 586, and 381 mm yr−1 of water through surface runoff in the wet, normal and dry years, respectively. The amount of groundwater that moved into the vadose zone to help satisfy crop water demand ranged from 700 to 750 mm yr−1. Precipitation increased the groundwater recharge during the rainy season from fall to spring. Annual recharge rate was only 34–50 mm. Groundwater level dropped 0.2–0.5 m in crop irrigation seasons (May to August). Land use dataset showed 81 % of the area is cropland, with soybean, corn, rice, and cotton accounting for 64 % of the total cropland area in BSRW. The planted area of corn and soybean significantly increased while the area of cotton area was tremendously reduced. Corn, soybean, and rice consumed approximately 96 % of the total amount of groundwater irrigation. This study indicated that irrigation scheduling based on plant water demand could save 47 % of groundwater currently used by conventional irrigation. The improved irrigation schedule could reduce groundwater decline by 0.01–2.05 m across the watershed, and mitigate the declines by 1.35–2.05 m in the depression cone in the central east part of the watershed. The results can assist with planning land and water use and developing sustainable groundwater management practices focused on locations of high groundwater withdrawals in other regions around the world.

Study of the effects of land use change on water yield in the Qilian Mountains in western China

The Qilian Mountains serve as significant ecological security barriers in the western region of China. Their continuous and stable water supply is essential for the sustainability of the human oasis in the Hexi Corridor, as well as for the maintenance of the desert ecosystem in the north. In the past three decades, land use in this area has changed significantly because of human activities, which has had a profound impact on water yield services. Based on the Water Yield module of the InVEST model, we evaluated the area and water yield of land use during 1990–––2020, and discussed the characteristics of water yield response to changes in land use. As a result of the study, it was found that in the Qilian Mountains during the period 1990–––2020: (1) the areas of swamp, unused land, medium coverage grassland, and woodland reduced, while the areas of high coverage grassland, low coverage grassland, cultivated land, construction land, glaciers, and water area increased, and each land use type exhibited a different degree of transformation. (2) In terms of total water yield, this declined by 1.09 × 108 m3, water yield of medium coverage grasslands, unused land, and swamp decreased, while water yield of other land uses increased, however, the responses to the change in water yield as a result of the change in land use were significant. (3) The areas with decreased water yield fall mainly within the high-altitude areas of the Qinghai Lake and Qaidam river watersheds, while the low-altitude areas were characterized by an increase in water yield. This study may provide decision-makers with guidance for protecting the ecosystem of the Qilian Mountains and developing a national park in the Qilian Mountains.

Analysis of Food Security of Farm Households in the Dodokan River Watershed Area, Lombok Island

The research aims to determine the level of food security and the factors that influence the level of food security of farming households in the Dodokan watershed. The topography of the watershed from upstream to downstream certainly influences the water supply in each part of the watershed, namely in the upstream, middle and downstream parts, which has implications for the way farmers carry out business on the land they work on, both cropping and cropping patterns. This of course raises the assumption that farmers in upstream and middle areas will be more prosperous because of a better supply of natural resources and whether this will have an impact on production levels and income of farmer households. This research used a household survey of 68 farmers selected using proportional sampling. Cross-classification between expenditure and portion of household energy adequacy levels is used to answer the first objective. The ordinal logistic model is used to answer the second objective. The results of the research show that 27.94% of farmer households have achieved food security levels, 30.88% have less, 38.24% are vulnerable, and 2.94% have food insecurity. Based on the results of ordinal logistics testing, household food security is positively influenced by household income, number of household members, household expenditure and negatively by the housewife's education.

Seasonal dynamics and key drivers of pharmaceutical pollution in a peri-urban watershed

Peri-urban ecosystems are strongly influenced by their natural environmental conditions and surrounding landscape. However, landscape patterns and landscape-related variables driving pharmaceutical pollution in peri-urban watersheds with rapid urbanization remain poorly understood. Herein, we investigated the occurrence and spatiotemporal distribution of 28 pharmaceuticals and their potential influencing factors in a peri-urban watershed (Zhangxi River Watershed) in Zhejiang province, Eastern China. Paraxanthine (detection frequency 97 %, mean concentration 223.07 ng/L) and anhydro-erythromycin (95 %, 4.01 ng/L) were the most prevalent compounds. Total pharmaceutical concentrations (sum of all target compounds) were significantly higher in the wet season (summer and autumn) than in the dry season (spring and winter; P < 0.05). Information theoretic-based analysis revealed that landscape pattern and dissolve organic matter were the main drivers of watershed-scale pharmaceutical pollution rather than water quality parameters and topographic characteristics. Correlation analysis showed that total pharmaceutical concentrations were more highly correlated with landscape pattern during the dry season than the wet season. The importance analysis and indicator interaction analysis revealed that interspersion and juxtaposition index (IJI), mean patch size (AREA-MN), patch density (PD), terrestrial humic-like substances C2, dissolved organic carbon (DOC) and fluorescent dissolved organic matter (FDOM) played a vital role in the occurrence and distribution of pharmaceutical in the watershed. Maintaining natural landscape is conducive to reduce antibiotic concentration in Zhangxi River. These results suggest that landscape patterns and dissolved organic matter strongly influence pharmaceutical pollution in the peri-urban ecosystem at a watershed scale.

A Quantitative Approach for Identifying Nitrogen Sources in Complex Yeongsan River Watershed, Republic of Korea, Based on Dual Nitrogen Isotope Ratios and Hydrological Model

Effective management of nitrate loading in complex river systems requires quantitative estimation to trace different nitrogen sources. This study aims to validate an integrated framework using soluble nitrogen isotope ratios (δ15N–NH4 and δ15N–NO3) and hydrological modeling (hydrological simulation program SPARROW) of the main stream and tributaries in the Yeongsan River to determine anthropogenic nitrogen fluxes among different land-use types in the complex river watershed. The δ15N–NH4 and δ15N–NO3 isotopic compositions varied across different land-use types (4.9 to 15.5‰ for δ15N–NH4 and −4.9 to 12.1‰ for δ15N–NO3), reflecting the different sources of nitrogen in the watershed (soil N including synthetic fertilizer N, manure N, and sewage treatment plant effluent N). We compared the soluble nitrogen isotopic compositions (δ15N–NH4 and δ15N–NO3) of the river water with various nitrogen sources (soil N, manure N, and sewage N) to assess their contribution, revealing that N from sewage treatment plant effluent as a point source was dominant during the dry season and N from forest- and soil-derived non-point sources was dominant due to intensive rainfall during the wet season. The coefficient of determination (R2) between the measured pollution load and the predicted pollution load calculated by the SPARROW model was 0.95, indicating a high correlation. In addition, the EMMA-based nitrogen contributions compared to the SPARROW-based nitrogen fluxes were similar to each other, indicating that large amounts of forest- and soil-derived N may be transported to the Yeongsan River watershed as non-point sources, along with the effect of sewage treatment plant effluent N as a point source. This study provides valuable insights for the formulation of management policies to control nitrogen inputs from point and non-point sources across different land-use types for the restoration of water quality and aquatic ecosystems in complex river systems. Given the recent escalation in human activity near aquatic environments, this framework is effective in estimating the quantitative contribution of individual anthropogenic nitrogen sources transported along riverine systems.

Fluvial flood adaptation using nature-based solutions: A comprehensive and effective assessment of hydro-meteorological risks

The growing prominence of Nature-based Solutions (NbS) for disaster risk reduction (DRR) has sparked increased interest. This study is motivated by the need to establish a quantifiable and standardized method for assessing the risks mitigated by NbS in engineering applications. The goal is to establish a comprehensive and effective system framework for assessing hydro-meteorological risks related to NbS in engineering applications. The proposed framework considers flood disaster mechanisms, uncertain factors, and ecosystem services, integrating them to comprehensively assess the benefits of NbS. Specifically, 2-D hydraulic analysis and an in-house adaptive Kriging-based reliability analysis are developed and applied to establish flood prevention standards for NbS. Additionally, the InVEST toolkit is utilized to evaluate ecosystem services. To demonstrate the applicability of the framework, the Baoli River Watershed located in Pingtung County of Taiwan is selected as a case study. It is found that NbS can effectively withstand a 25-year return period flood and reduce flooding on agricultural land by 46.03 %. Furthermore, the probability of flooding decreased from 100 % to 27 % for a 20-year return period flood. NbS was found to provide approximately NT$1.20–4.65 million more in total benefit value compared to the engineering governance strategy. The supporting source codes are available at https://github.com/johnthedy/Adaptive-Kriging-Using-PSO-HHs-in-HECRAS3D.git.

Carbon Storage Patterns and Landscape Sustainability in Northeast Portugal: A Digital Mapping Approach

This study investigated the impact of regional land abandonment in northeast Portugal. It specifically focused on carbon sequestration opportunities in the Upper Sabor River Watershed, situated in the northeast of Portugal, amidst agricultural land abandonment. The study involved mapping the distribution of soil organic carbon (SOC) across four soil layers (0–5 cm, 5–10 cm, 10–20 cm, and 20–30 cm) at 120 sampling points. The quantification of SOC storage (measured in Mg C ha−1) allowed for an analysis of its relationship with various landscape characteristics, including elevation, land use and land cover (LULC), normalized difference vegetation index (NDVI), modified soil-adjusted vegetation index (MSAVI), topographic wetness index (TWI), and erosion risk (ER). Six statistical tests were employed, including multivariate approaches like Cubist and Random Forest, within different scenarios to assess carbon distribution within the watershed’s soils. These modeling results were then utilized to propose strategies aimed at enhancing soil carbon storage. Notably, a significant discrepancy was observed in the carbon content between areas at higher elevations (&gt;1000 m) and those at lower elevations (&lt;800 m). Additionally, the study found that the amount of carbon stored in agricultural soils was often significantly lower than in other land use categories, including forests, mountain herbaceous vegetation, pasture, and shrub communities. Analyzing bi- and multivariate scenarios, it was determined that the scenario with the greatest number of independent variables (set 6) yielded the lowest RMSE (root mean squared error), serving as a key indicator for evaluating predicted values against observed values. However, it is important to note that the independent variables used in set 4 (elevation, LULC, and NDVI) had reasonably similar values. Ultimately, the spatialization of the model from scenario 6 provided actionable insights for soil carbon conservation and enhancement across three distinct elevation levels.

Investigating Urban Flooding and Nutrient Export under Different Urban Development Scenarios in the Rouge River Watershed in Michigan, USA

Adverse environmental impacts in the watershed are driven by urbanization, which is reflected by land use and land cover (LULC) transitions, such as increased impervious surfaces, industrial land expansion, and green space reduction. Some adverse impacts on the water environment include urban flooding and water quality degradation. Our study area, the Rouge River Watershed, has been susceptible to accelerated urbanization and degradation of ecosystems. Employing the Land Change Modeler (LCM), we designed four alternative urban development scenarios for 2023. Subsequently, leveraging the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), we utilized two models—Nutrient Delivery Ratio (NDR) and Flood Risk Mitigation (UFRM)—to evaluate and compare the performance of these scenarios, as well as the situation in 2019, in terms of nutrient export and urban flooding. After simulating these scenarios, we determined that prioritizing the medium- and high-intensity development scenario to protect open space outperforms other scenarios in nutrient export. However, the four scenarios could not exhibit significant differences in urban flooding mitigation. Thus, we propose balanced and integrative strategies, such as planning green infrastructure and compact development, to foster ecological and economic growth, and enhance the Rouge River Watershed’s resilience against natural disasters for a sustainable future.

New Graph-Based and Transformer Deep Learning Models for River Dissolved Oxygen Forecasting

Dissolved oxygen (DO) is a key indicator of water quality and the health of an aquatic ecosystem. Aspiring to reach a more accurate forecasting approach for DO levels of natural streams, the present work proposes new graph-based and transformer-based deep learning models. The models were trained and validated using a network of real-time hydrometric and water quality monitoring stations for the Credit River Watershed, Ontario, Canada, and the results were compared with both benchmarking and state-of-the-art approaches. The proposed new Graph Neural Network Sample and Aggregate (GNN-SAGE) model was the best-performing approach, reaching coefficient of determination (R2) and root mean squared error (RMSE) values of 97% and 0.34 mg/L, respectively, when compared with benchmarking models. The findings from the Shapley additive explanations (SHAP) indicated that the GNN-SAGE benefited from spatiotemporal information from the surrounding stations, improving the model’s results. Furthermore, temperature has been found to be a major input attribute for determining future DO levels. The results established that the proposed GNN-SAGE model outperforms the accuracy of existing models for DO forecasting, with great potential for real-time water quality management in urban watersheds.

Effect of varying hydrologic regime on seasonal total maximum daily loads (TDML) in an agricultural watershed

Rising hypoxia due to the eutrophication of riverine ecosystems is primarily caused by the transport of nutrients. The majority of existing TMDL models cannot be efficienty applied to represent nutrient concentrations in riverine ecosystems having varying flow regimes due to seasonal differences. Accurate TMDL assessment requires nutrient loads and suspended matter estimation under varying flow regimes with minimal uncertainty. Though a large database can enhance accuracy, it can be resource intensive. This study presents the design of an innovative modeling strategy to optimize the use of existing datasets to effectively represent streamflow-load dynamics while minimizing uncertainty. The study developed an approach to assess TMDLs using six different flux models and kriging techniques (i) to enhance the accuracy of nutrient load estimation under different hydrologic regimes (flow stratifications) and (ii) to derive an optimal modeling strategy and sampling scheme for minimizing uncertainty. The flux models account for uncertainty in load prediction across varying flow strata, and the deployment of multiple load calculation procedures. Further, the proposed flux approach allows the determination of load exceedance under different TMDL scenarios aimed at minimizing uncertainty to achieve reliable load predictions. The study employed a 10-year dataset (2009–2018) consisting of daily flow data (m3/sec) and weekly data (mg/L) for nitrogen (N), phosphorus (P) and total suspended solids (TSS) concentrations in three distinct agricultural sites in+ the Minnesota River Watershed. The outcomes were analyzed geospatially in a Geographic Information System (GIS) environment using the kriging interpolation technique. The study recommends (i) triple stratification of flows to obtain accurate load estimates, and (ii) an optimal sampling scheme for nitrogen and phosphorous with 30.6 % and 49.8 % datapoints from high flow strata. The study outcomes are expected to contribute to the planning of economically and technically sound combinations of best management practices (BMPs) required for achieving total maximum daily loads (TMDL) in a watershed.

Research on the Application of NbS in Watershed Ecological Restoration: A Case Study of Jiulong River Watershed Shan-Shui Initiative

Nature-based solutions (NbS) rapidly develop globally to address societal challenges and provide human well-being and biodiversity. Watershed restoration plays an essential role in enhancing the ecological and socio-economic benefits of the region. The design and implementation of watershed restoration projects are crucial to their effectiveness, and NbS has been applied as a concept in ecosystem-related projects. This paper proposes an evaluation method to assess the implementation of the Shan-Shui Initiative in the Jiulong River Watershed restoration projects based on the eight criteria proposed by the International Union for the Conservation of Nature (IUCN) Global Standard for Nature-Based Solutions. The aim is to standardize the implementation process of watershed restoration projects to achieve more significant benefits and practically apply the concept of NbS in watershed restoration. The implementation scheme of the Shan-Shui Initiative in the Jiulong River Watershed is designed to evaluate and improve the design and implementation scheme of ecological restoration projects in the actual basin. According to the assessment results, the degree of matching based on NbS for the implementation scheme of the Jiulong River Watershed Shan-Shui Initiative is 73%, which meets the criteria of NbS but needs to be improved in terms of monitoring and assessment, synergistic management, and benefit trade-offs.

The Relationship between Land Use Changes in the Increase of Runoff in the Gorgan River Watershed Using Satellite Image Data and Statistical Models

The Relationship between Land Use Changes in the Increase of Runoff in the Gorgan River Watershed Using Satellite Image Data and Statistical Models

The Surface Atmosphere Integrated Field Laboratory (SAIL) Campaign

Abstract The science of mountainous hydrology spans the atmosphere through the bedrock and inherently crosses physical and disciplinary boundaries: land–atmosphere interactions in complex terrain enhance clouds and precipitation, while watersheds retain and release water over a large range of spatial and temporal scales. Limited observations in complex terrain challenge efforts to improve predictive models of the hydrology in the face of rapid changes. The Upper Colorado River exemplifies these challenges, especially with ongoing mismatches between precipitation, snowpack, and discharge. Consequently, the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility has deployed an observatory to the East River Watershed near Crested Butte, Colorado, between September 2021 and June 2023 to measure the main atmospheric drivers of water resources, including precipitation, clouds, winds, aerosols, radiation, temperature, and humidity. This effort, called the Surface Atmosphere Integrated Field Laboratory (SAIL), is also working in tandem with DOE-sponsored surface and subsurface hydrologists and other federal, state, and local partners. SAIL data can be benchmarks for model development by producing a wide range of observational information on precipitation and its associated processes, including those processes that impact snowpack sublimation and redistribution, aerosol direct radiative effects in the atmosphere and in the snowpack, aerosol impacts on clouds and precipitation, and processes controlling surface fluxes of energy and mass. Preliminary data from SAIL’s first year showcase the rich information content in SAIL’s many datastreams and support testing hypotheses that will ultimately improve scientific understanding and predictability of Upper Colorado River hydrology in 2023 and beyond.

The importance of explicitly representing the streambed in watershed models

AbstractThe streambed is the critical interface between the aquatic and terrestrial systems and hosts important biogeochemical hot spots within river corridors. Although the streambed characteristics are significantly different from those of its surrounding soil, the streambed itself has not been explicitly represented in watershed models. Here, we explicitly incorporated a streambed layer into an integrated hydrologic model through model parameterization and discretization. We examined the hydrological effects of streambed characteristics, including hydraulic conductivity (K), layer thickness, and resolution, on the exchange fluxes across the streambed as well as the streamflow at the watershed outlet. The numerical experiments were performed in the American River Watershed, a headwater, mountainous watershed within the Yakima River Basin in central Washington. Despite having a negligible effect on the watershed streamflow, an explicit representation of the streambed with distinctive properties dramatically changed the magnitude and variability of the exchange flux. In general, a larger streambed K along with a thicker streambed layer induced larger exchange fluxes. The exchange flux was most sensitive to the streambed resolution. A finer streambed resolution increased exchange fluxes per unit area while reducing the overall exchange volumes across the entire streambed. The amount of baseflow decreased by 6% as the streambed resolution increased from 250 to 50 m. This finding is important because these hydrological changes may, in turn, affect the exchange of nutrients and contaminants between surface water and groundwater and the associated biogeochemical processes. Our work demonstrated the importance of representing streambeds in fully distributed, process‐based watershed models to better capture the exchange flow dynamics in river corridors.

Climate change, traditional ecological knowledge, and riverine biodiversity conservation: a case in Aklan, Central Philippines

AbstractWe framed climate change (CC) discourse through its disruptions to local culture and livelihood in a subsistence riverine fishing community in Central Philippines. Our main goal was contextualizing how local communities' traditional ecological knowledge (TEK) related to climate, fisheries, and taboos can strengthen freshwater fisheries management and biodiversity conservation. We adopted a mixed-method purposive sampling of the 126 fishing households in the Nabaoy River Watershed in the municipality of Malay in Aklan province. The high CC awareness was associated with the increasing frequency and intensity of extreme climatological events and erratic weather patterns. These CC-driven perturbations were primarily attributed to the ballooning human population and deforestation. These threats, in turn, were linked to the diminishing state of the Nabaoy River, heralded by the perceived marked decline of frog and dragonfly populations believed to be indicators of river health. Riverine biodiversity was also perceived as dwindling, with fish catch and their sizes shrinking. Furthermore, the observed fishing taboos guiding local informal (de facto) institutions corroborated formal (de jure) temporal and spatial fisheries management measures. Indeed, local communities have relevant long-term knowledge of management (e.g., TEK) and development-oriented structures and systems (e.g., informal institutions). These invaluable social capital assets are crucial in building resilient governance systems to address local conservation issues and concerns, particularly in data-deficient areas or lacking formal management contexts. Hence, formal management interventions should integrate TEK and the informal institution in which it is embedded and engage local TEK holders as partners in freshwater conservation efforts.

Analysis of Flood-Prone Areas on Bekasi River Watershed

Das Kali Bekasi is an area that has physical conditions that support the occurrence of local and natural flood disasters during the rainy season. This research aims to: (1) Determine the distribution of floodprone areas in the Bekasi River Watershed, (2) Find out the most dominant factors of flood vulnerability that occur in the Bekasi River Watershed. The method used in the research is quantitative descriptive analysis. Analyze the data to determine the distribution area prone to flooding by weighting scoring and overlaying rainfall, land use, slope, soil type, and river density. To find out the dominant factors that cause flood vulnerability, a correlation test is used. The results of the research are (1) Flood vulnerability in the Bekasi river basin, based on the results of this research, is divided into 3 classes, namely the not vulnerable class with an area of 82.61 Km² (5.93%), the moderately vulnerable class with an area of 323.85 Km² (23, 26%), very vulnerable class with an area of 985.96 Km² (70.81%). (2) Correlation test to determine the dominant factor causing flooding in the Bekasi River basin and it is known that the dominant factor is the slope parameter, followed by the river density parameter, soil type parameter, land use parameter, and rainfall parameter with the lowest correlation value.

The Effect of Climate Change on the Hydropower Potential in the Kunhar River Watershed, Pakistan

Climate change plays a vital role in the hydrology of any river basin, which may have multidimensional consequences. There is a need to conduct climate change impact assessment studies with updated models and scenarios. This study aimed to assess the impact of climate change on the streamflow and hydropower in Pakistan’s Kunhar River basin. Three general circulation models (GCMs), under two Shared Socioeconomic Pathway scenarios (SSPs 2–45 and 5–85), the Soil and Water Assessment Tool, and the flow duration curve were used to project the change in climatic parameters, streamflow, and hydropower potential, respectively. The findings indicated that in the 2080s, the precipitation, maximum, and minimum temperatures are projected to increase by 10%, 2.0 °C, and 3.0 °C under the SSP 2–45 scenario and are projected to increase by 8%, 3.7 °C, and 4.4 °C under the SSP 5–85 scenario, respectively. The annual streamflow may increase by 15 to 11%, and the seasonal fluctuations are more likely to be dominant compared with the annual fluctuations. The hydropower potential will probably increase by 24 to 16% under the SSP 2–45 and 5–85 scenarios in the 2080s. However, seasonal changes in streamflow and hydropower may impact the hydropower plant operation in the basin. The Kunhar River’s hydrology may change from snow-fed to a rainfall–runoff river.

Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model

Abstract. Convection-permitting regional climate models (RCMs) have recently become tractable for applications at multi-decadal timescales. These types of models have tremendous utility for water resource studies, but better characterization of precipitation biases is needed, particularly for water-resource-critical mountain regions, where precipitation is highly variable in space, observations are sparse, and the societal water need is great. This study examines 34 years (1987–2020) of RCM precipitation from the Weather Research and Forecasting model (WRF; v3.8.1), using the Climate Forecast System Reanalysis (CFS; CFSv2) initial and lateral boundary conditions and a 1 km × 1 km innermost grid spacing. The RCM is centered over the Upper Colorado River basin, with a focus on the high-elevation, 750 km2 East River watershed (ERW), where a variety of high-impact scientific activities are currently ongoing. Precipitation is compared against point observations (Natural Resources Conservation Service Snow Telemetry or SNOTEL), gridded climate datasets (Newman, Livneh, and PRISM), and Bayesian reconstructions of watershed mean precipitation conditioned on streamflow and high-resolution snow remote-sensing products. We find that the cool-season precipitation percent error between WRF and 23 SNOTEL gauges has a low overall bias (x^ = 0.25 %, s = 13.63 %) and that WRF has a higher percent error during the warm season (x^ = 10.37 %, s = 12.79 %). Warm-season bias manifests as a high number of low-precipitation days, though the low-resolution or SNOTEL gauges limit some of the conclusions that can be drawn. Regional comparisons between WRF precipitation accumulation and three different gridded datasets show differences on the order of ± 20 %, particularly at the highest elevations and in keeping with findings from other studies. We find that WRF agrees slightly better with the Bayesian reconstruction of precipitation in the ERW compared to the gridded precipitation datasets, particularly when changing SNOTEL densities are taken into account. The conclusions are that the RCM reasonably captures orographic precipitation in this region and demonstrates that leveraging additional hydrologic information (streamflow and snow remote-sensing data) improves the ability to characterize biases in RCM precipitation fields. Error characteristics reported in this study are essential for leveraging the RCM model outputs for studies of past and future climates and water resource applications. The methods developed in this study can be applied to other watersheds and model configurations. Hourly 1 km × 1 km precipitation and other meteorological outputs from this dataset are publicly available and suitable for a wide variety of applications.