Search Results (252)

Rapid climate change and increasing water use have led to various problems in small- and medium-sized urban streams during dry periods, such as stream drying, water pollution, and ecological degradation, reducing their physical and ecological functions. Ensuring adequate baseflow and improving water quality during these critical periods are essential for maintaining urban stream health. While previous studies have explored the effects of Low Impact Development (LID) techniques (e.g., green roof, rainwater harvesting system, permeable pavement, infiltration trench) on infiltration and groundwater recharge, they have primarily focused on general flow regimes rather than dry and low-flow periods. This study specifically evaluates the effects of LID techniques on securing baseflow and improving water quality during dry periods, utilizing the SWAT-MODFLOW model and the Web-based Hydrograph Analysis Tool (WHAT) system. The results show that LID techniques reduce peak flow by an average of 27% and secure an additional 43% of baseflow during dry periods. Suspended solids (SS) and total phosphorus (T-P) concentrations were reduced by 15% and 41%, respectively. These findings demonstrate the effectiveness of LID techniques not only in managing stormwater runoff during flood events but also in maintaining baseflow and water quality during dry periods, thus providing valuable insights for sustainable urban watershed management. Full article

Global urbanization, population growth, and climate change have considerably impacted water resources, making sustainable water resource management (WRM) essential. Understanding the changes in hydrological components is important for effective WRM, particularly in cities such as Higashi-Hiroshima, which is known for its saké brewing industry. This study used the Soil and Water Assessment Tool (SWAT) with Hydrological Response Units (HRUs) to achieve high spatial precision in assessing the impacts of land use change and climate variability on hydrological components in a suburban catchment in western Japan. Over the 30-year study period (1980s–2000s), land use change was the main driver of hydrological variability, whereas climate change played a minor role. Increased surface runoff, along with decrease in groundwater recharge, evapotranspiration, and baseflow, resulted in an overall reduction in water yield, with a 34.9% decrease in groundwater recharge attributed to the transformation of paddy fields into residential areas. Sustainable WRM practices, including water conservation, recharge zone protection, and green infrastructure, are recommended to balance urban development with water sustainability. These findings offer valuable insights into the strategies for managing water resources in rapidly urbanizing regions worldwide, emphasizing the need for an integrated WRM system that considers both land use and climate change impacts. Full article

Revealing the spatiotemporal variation in baseflow and its underlying mechanisms is critical for preserving the health and ecological functions of alpine rivers, but this has rarely been conducted in the source region of the Yangtze River (SRYR). Our study employed the Soil and Water Assessment Tool (SWAT) model coupled with two-parameter digital filtering and geostatistical approaches to obtain a visual representation of the spatiotemporal heterogeneity characteristics of the baseflow and baseflow index (BFI) in the SRYR. The SWAT model and multiple linear regression model (MLR) were used to quantitatively estimate the contribution of climate change and human activities to baseflow and BFI changes. The results underscore the robust applicability of the SWAT model within the SRYR. Temporally, the precipitation, temperature, and baseflow exhibited significant upward trends, and the baseflow and BFI showed contrasting intra-annual distribution patterns, which were unimodal and bimodal distribution, respectively. Spatially, the baseflow increased from northwest to southeast, and from the watershed perspective, the Tongtian River exhibited higher baseflow values compared to other regions of the SRYR. The baseflow and BFI values of the Dangqu River were greater than those of other tributaries. More than 50% of the entire basin had an annual BFI value greater than 0.7, which indicates that baseflow was the major contributor to runoff generation. Moreover, the contributions of climate change and human activities to baseflow variability were 122% and −22%, and to BFI variability, 60% and 40%. Specifically, precipitation contributed 116% and 60% to the baseflow and BFI variations, while the temperature exhibited contributions of 6% and 8%, respectively. Overall, it was concluded that the spatiotemporal distributions of baseflow and the BFI are controlled by various factors, and climate change is the main factor of baseflow variation. Our study offers valuable insights for the management and quantitative assessment of groundwater resources within the SRYR amidst climate change. Full article

Understanding the recharge–discharge system of a catchment is key to the efficient use and effective management of groundwater resources. The present study focused on the estimation of groundwater recharge using Soil Moisture Balance (SMB) and Baseflow Separation (BFS) methods in the Gilgel Gibe catchment where water demand for irrigation, domestic, and industrial purposes is dramatically increasing. The demand for groundwater and the existing ambitious plans to respond to this demand will put a strain on the groundwater resource in the catchment unless prompt intervention is undertaken to ensure its sustainability. Ground-based hydrometeorological 36-years data (1985 to 2020) from 17 stations and satellite products from CHIRPS and NASA/POWER were used for the SMB method. Six BFS methods were applied through the Web-based Hydrograph Analysis Tool (WHAT), SepHydro, BFLOW, and Automated Computer Programming (PART) to sub-catchments and the main catchment to estimate the groundwater recharge. The streamflow data (discharge) obtained from the Ministry of Water and Energy were the main input data for the BFS methods. The average annual recharge of groundwater was estimated to be 313 mm using SMB for the years 1985 to 2020 and 314 mm using BFS for the years 1986 to 2003. The results from the SMB method revealed geographical heterogeneity in annual groundwater recharge, varying from 209 to 442 mm. Significant spatial variation is also observed in the estimated annual groundwater recharge using the BFS methods, which varies from 181 to 411 mm for sub-catchments. Hydrogeological conditions of the catchment were observed, and the yielding capacity of existing wells was assessed to evaluate the validity of the results. The recharge values estimated using SMB and BFS methods are comparable and hydrologically reasonable. The findings remarkably provide insightful information for decision-makers to develop effective groundwater management strategies and to prioritize the sub-catchments for immediate intervention to ensure the sustainability of groundwater. Full article

There is a growing need for proactive planning for natural hazards in a changing climate. Computational modeling of climate hazards provides an opportunity to inform planning, particularly in areas approaching ecosystem state changes, such as Interior Alaska, where future hazards are expected to differ significantly from historical events in frequency and severity. This paper considers improved modeling approaches from a physical process perspective and contextualizes the results within the complexities and limitations of hazard planning efforts and management concerns. Therefore, the aim is not only to improve the understanding of potential climate impacts on streamflow within this region but also to further explore the steps needed to evaluate local-scale hazards from global drivers and the potential challenges that may be present. This study used dynamically downscaled climate forcing data from ERA-Interim reanalysis datasets and projected climate scenarios from two General Circulation Models under a single Representative Concentration Pathway (RCP 8.5) to simulate an observational gage-calibrated WRF-Hydro model to assess shifts in streamflow and flooding potential in three Interior Alaska rivers over a historical period (2008–2017) and two future periods (2038–2047 and 2068–2077). Outputs were assessed for seasonality, streamflow, extreme events, and the comparison between existing flood control infrastructure in the region. The results indicate that streamflow in this region is likely to experience increases in seasonal length and baseflow, while the potential for extreme events and variable short-term streamflow behavior is likely to see greater uncertainty, based on the divergence between the models. Full article

After peak snowmelt, baseflow is the primary contributor to streamflow in snow-dominated watersheds. These low flows provide important water for municipal, agricultural, and recreational purposes once peak flows have been allocated. This study examines the correlation between peak snow water equivalent (SWE), post-peak SWE precipitation, and baseflow characteristics, including any yearly lag in baseflow. To reflect the hydrologic processes that are occurring in snow-dominated watersheds, we propose using a melt year (MY) beginning with the onset of snowmelt contributions (the first deviation from baseflow) and ending with the onset of the following year’s snowmelt contributions. We identified the beginning of an MY and extracted the subsequent baseflow values using flow duration curves (FDCs) for 12 watersheds of varying sizes across Colorado, USA. Based on the findings, peak SWE and summer rain both dictate baseflow, especially for the larger watersheds evaluated, as identified by higher correlations with the MY-derived baseflow. Lags in the correlation between baseflow and peak SWE are best identified when low-snow years are investigated separately from high-snow years. The MY is a different and more effective approach to calculating baseflow using FDCs in snow-dominated watersheds in Colorado. Full article

Land use and land cover (LULC) changes alter the structure and functioning of natural ecosystems, impacting the potential and flow of ecosystem services. Ecological restoration projects aiming to enhance native vegetation have proven effective in mitigating the impacts of LULC changes on ecosystem services. A key element in implementing these projects has been identifying priority areas for restoration, considering that resources allocated to such projects are often limited. This study proposes a novel methodological framework to identify priority areas for restoration and guide LULC planning to increase the provision of water ecosystem services (WESs) in a watershed in southeastern Brazil. To do so, we combined biophysical models and multicriteria analysis to identify priority areas for ecological restoration, propose environmental zoning for the study area, and quantify the effects of LULC changes and of a planned LULC scenario (implemented environmental zoning) on WES indicators. Previous LULC changes, from 1985 to 2019, have resulted in a nearly 20% increase in annual surface runoff, a 50% increase in sediment export, a 22% increase in total nitrogen (TN) export, and a 53% increase in total phosphorus (TP) export. Simultaneously, they reduced the provision of WESs (baseflow −27%, TN retention −10%, and TP retention −16%), except for sediment retention, which increased by 35% during the analyzed period. The planned LULC scenario successfully increased the provision of WESs while reducing surface runoff and nutrient and sediment exports. The methodology employed in this study proved to be effective in guiding LULC planning for improving WES. The obtained results provide a scientific foundation for guiding the implementation of WES conservation policies in the studied watershed. This method is perceived to be applicable to other watersheds. Full article

Traditional univariate drought indices may not be sufficient to reflect comprehensive information on drought. Therefore, this paper proposes a new composite drought index that can comprehensively characterize meteorological and hydrological drought. In this study, the new drought index was established by combining the standardized precipitation index (SPI) and the standardized baseflow index (SBI) for the Jiaojiang River Basin (JRB) using the copula function. The prediction model was established by training random forests on past data, and the driving force behind the combined drought index was explored through the LIME algorithm. The results show that the established composite drought index combines the advantages of SPI and SBI in drought forecasting. The monthly and annual droughts in the JRB showed an increasing trend from 1991 to 2020, but the temporal characteristics of the changes in each subregion were different. The accuracies of the trained random forest model for heavy drought in Baizhiao (BZA) and Shaduan (SD) stations were 83% and 88%, respectively. Furthermore, the Local Interpretable Model-Agnostic Explanations (LIME) interpretation identified the essential precipitation, baseflow, and evapotranspiration features that affect drought. This study provides reliable and valid multivariate indicators for drought monitoring and can be applied to drought prediction in other regions. Full article

Baseflow is the part of streamflow that is mainly replenished by groundwater. The protection of the biological environment and the growth of its water resources greatly depend on the spatial and temporal evolution of baseflow. Therefore, the Baizhiao (BZA) and Shaduan (SD) catchments of the Jiaojiang River Basin (JRB) in the Zhejiang province of China were selected as study areas. The ABCD model and Eckhardt method were used to calculate baseflow and baseflow index (BFI). The temporal and spatial evolution patterns of baseflow were analyzed through statistical analysis and the Mann–Kendall test. The results showed that the ABCD model performs well in simulating overall hydrological processes on the monthly streamflow at BAZ and SD stations with NSE (Nash–Sutcliffe Efficiency) values of 0.82 and 0.83 and Pbias (Percentage Bias) values of 9.2% and 8.61%, respectively. The spatial–temporal distribution of the BFI indicates the higher baseflow contribution in upstream areas compared to downstream areas at both stations. The baseflow and BFI had significant upward trends at the BZA and SD stations in the dry season, while their trends were not uniform during the wet period. These findings are essential guidance for water resource management in the JRB regions. Full article

Groundwater-influenced ecosystems (GIEs) are increasingly vulnerable due to groundwater extraction, land-use practices, and climate change. These ecosystems receive groundwater inflow as a portion of their baseflow or water budget, which can maintain water levels, water temperature, and chemistry necessary to sustain the biodiversity that they support. In some systems (e.g., springs, seeps, fens), this connection with groundwater is central to the system’s integrity and persistence. Groundwater management decisions for human use often do not consider the ecological effects of those actions on GIEs. This disparity can be attributed, in part, to a lack of information regarding the physical relationships these systems have with the surrounding landscape and climate, which may influence the environmental conditions and associated biodiversity. We estimate the vulnerability of areas predicted to be highly suitable for the presence of GIEs based on watershed (U.S. Geological Survey Hydrologic Unit Code 12 watersheds: 24–100 km²) and pixel (30 m × 30 m pixels) resolution in the Atlantic Highlands and Mixed Wood Plains EPA Level II Ecoregions in the northeastern United States. We represent vulnerability with variables describing adaptive capacity (topographic wetness index, hydric soil, physiographic diversity), exposure (climatic niche), and sensitivity (aquatic barriers, proportion urbanized or agriculture). Vulnerability scores indicate that ~26% of GIEs were within 30 m of areas with moderate vulnerability. Within these GIEs, climate exposure is an important contributor to vulnerability of 40% of the areas, followed by land use (19%, agriculture or urbanized). There are few areas predicted to be suitable for GIEs that are also predicted to be highly vulnerable, and of those, climate exposure is the most important contributor to their vulnerability. Persistence of GIEs in the northeastern United States may be challenged as changes in the amount and timing of precipitation and increasing air temperatures attributed to climate change affect the groundwater that sustains these systems. Full article

Environmental flow assessment is an essential tool in water resource management. This study employs a holistic approach to evaluate the environmental flow in the Yen Basin, Thanh Hoa, Vietnam. Based on information gathered from a field survey, the Yen River system is divided into five reaches, and environmental objectives and ecological assets are identified in each reach. Hydrological and hydraulic mathematical models are applied to simulate the flow regime in the river, demonstrating their potential to assess environmental flow, especially in basins with limited data. The detailed results from the mathematical model facilitate selecting environmental flow components to address specific objectives for each river reach. By analyzing and selecting the flow regime, this study aims to ensure environmental protection while also considering basin development requirements, laying the groundwork for defining prescribed flow regimes in basin water management. Full article

Our study aims to understand how the hydrological cycle is affected by climate change in river basins. This study focused on the Karnali River Basin (KRB) to examine the impact of extreme weather events like floods and heat waves on water security and sustainable environmental management. Our research incorporates precipitation and temperature projections from ten Global Circulation Models (GCMs) under the Coupled Model Intercomparison Project Phase 6 (CMIP6). We applied thirteen statistical bias correction methods for precipitation and nine for temperatures to make future precipitation and temperature trend projections. The research study also utilized the Soil and Water Assessment Tool (SWAT) model at multi-sites to estimate future streamflow under the Shared Socioeconomic Pathway (SSP) scenarios of SSP245 and SSP585. Additionally, the Web-based Hydrograph Analysis Tool (WHAT) was used to distinguish between baseflow and streamflow. Our findings, based on the Multi-Model Ensemble (MME), indicate that precipitation will increase by 7.79–16.25% under SSP245 (9.43–27.47% under SSP585) and maximum temperatures will rise at rates of 0.018, 0.048, and 0.064 °C/yr under SSP245 (0.022, 0.066, and 0.119 °C/yr under SSP585). We also anticipate that minimum temperatures will increase at rates of 0.049, 0.08, and 0.97 °C/yr under SSP245 (0.057, 0.115, and 0.187 °C/yr under SSP585) for near, mid, and far future periods, respectively. Our research predicts an increase in river discharge in the KRB by 27.12% to 54.88% under SSP245 and 45.4% to 93.3% under SSP585 in different future periods. Our finding also showed that the expected minimum monthly baseflow in future periods will occur earlier than in the historical period. Our study emphasizes the need for sustainable and adaptive management strategies to address the effects of climate change on water security in the KRB. By providing detailed insights into future hydrological conditions, this research serves as a critical resource for policymakers and stakeholders, facilitating informed decision-making for the sustainable management of water resources in the face of climate change. Full article

Large-scale vegetation restoration has caused complex changes in ecosystem service (i.e., ES) interactions. However, current analysis on the spatial interactions of ESs and their driving mechanisms remains deficient, limiting the adaptive management in vegetation restoration areas. This study focused on a representative restoration area (Yan’an) to analyze the relationships among carbon sequestration, water yield, baseflow regulation, and soil conservation from 1990 to 2020. Employing the bivariate boxplot and spatial autocorrelation methods, we identified the overall changes and spatial patterns of ES interactions. The geographically and temporally weighted regression (i.e., GTWR) model was applied to elucidate the driving factors of these spatial ES interactions. The results indicated the following: (1) Over the past three decades, synergies between carbon sequestration and water yield emerged as the joint results of spatial ‘low–low’ interactions and ‘high–high’ interactions between the two ESs, while other ES pairs generally exhibited comparatively weaker synergies, due to their spatial ‘low–high’ interactions in southern semi-humid areas. (2) In the northern semi-arid areas, both fractional vegetation cover (i.e., FVC) and climatic factors consistently exerted negative influences on all ‘low–low’ ES interactions, which caused a reduced area in synergies, while in the southern semi-humid areas, FVC suppressed the ‘low–high’ trade-offs between ESs, indicating the adaptability of grassland restoration efforts. (3) The impact of human activities on ES interactions has increased in the last 10 years, and exhibited positive effects on the ‘low–low’ ES interactions in northern semi-arid areas. However, the expansion of trade-off between soil conservation and carbon sequestration warrants attention. This study offers important insights into understanding the spatial interactions among carbon, water, and soil-related ESs in drylands. Full article

In this study, we aimed to verify the two relationships on large wood export, as follows: (1) the relationship between large wood recruitment and landslides triggered by intense rainfalls and (2) the relationship between large wood export and the long-term large wood budget on an annual scale, based on the direct export of large wood caused by an increase in large wood recruitment with extreme rainfall events, as well as the baseflow of large wood, which is mainly old large wood recruitment stored at the slopes and in the stream. To reproduce these two relationships, the model consisted of two frameworks, as follows: (1) the rainfall-induced analytical shallow landslide model, with 30 m spatial resolution for large wood recruitment and (2) the double/triple storage function, with the lumped hydrological method at a watershed scale for large wood entrainment. Application of the model to 212 dam reservoir watersheds across Japan resulted in reproducibility in the estimation of large wood export volumes in 134 of the target dam reservoir watersheds, which contribute 63.2% of the target basins. This indicated that our results verified these two relationships as primary relationships. To analyse the difference in large wood export systems, a frequency analysis was conducted using correlation analysis based on large wood export volume and the cumulative values of six patterns of large wood recruitment volumes. The results indicated that there might be differences in large wood export systems between the watersheds represented by the double storage function model and those represented by the triple storage function model. Full article

This hydrological study investigated a combined rating methodology tested on a 14,090 km² area in Southwest Florida. The approach applied the Hydrological Simulation Program-Fortran (HSPF) over a 23-year period and was validated by 28 stream gauging stations. The regional hydrological complexity includes natural and agricultural areas, as well as extensive phosphate mining and urbanizing areas. This application is a novel and efficient methodology for generating stage–storage–discharge relationships using a geographic information system (GIS), empirical equations, and spreadsheets for 148,000 isolated and connected alluvial wetlands within the model domain. The validation metrics used to evaluate the applied methodology for populating the stage–storage–discharge relationship demonstrated the model effectiveness in simulating a range of hydrological events across various regions. For discharge prediction, the Nash–Sutcliffe efficiency values surpassed 0.7 at most stations, with an average of 0.67, and the average R squared was 0.74. This methodology, when applied, achieved a root-mean-square error of 4 m³/s for discharge prediction and 0.47 m for stage prediction. However, limitations emerged in simulating baseflow (low flows), highlighting the need for integrated modeling approaches to accurately capture groundwater–surface water interactions. The research provides an improved means for modeling regional water resources and lays the groundwork for enhanced hydrological modeling in watersheds with complex alluvial and isolated wetland systems. Full article