Search Results (276)

This paper introduces a methodology for forecasting spring hydrographs based on projections from regional climate models. The primary study objective was to evaluate how climate change may affect spring discharge. A statistical–analytical modeling approach was developed and applied to the Jósva spring catchment in the Aggtelek Karst region of Hungary. Historical data served to establish a regression relationship between rainfall and peak discharge. This approach is particularly useful for predicting discharge in cases where only historical rainfall data are available for calibration. Baseflow recession was analyzed using a two-component exponential model, with hydrograph decompositionand parameter optimization performed on the master recession curve. Future discharge time series were generated using rainfall data from two selected regional climate model scenarios. Both scenarios suggest a decline in baseflow discharge during different periods of the 21st century. The findings indicate that climate change is likely to intensify hydrological extremes in the coming decades, irrespective of whether moderate or high CO₂ emission scenarios unfold. Full article

Elevated chloride (Cl⁻) concentrations in surface water and groundwater are an increasing concern in cold region urban environments, largely due to long-term road salt application. This study investigates the Cl⁻ distribution across southern Ontario, Canada, using geospatial methods to identify contamination hot spots and assess groundwater vulnerability at both regional and watershed scales. Chloride data from 2001 to 2010 and 2011 to 2020 were compiled from public sources and interpolated using inverse distance weighting. A regional-scale vulnerability index was developed using slope (SL), surficial geology (SG), and land use (LU) (SL-SG-LU), and compared it to a more detailed DRASTIC-LU index within the Credit River watershed. Results show that Cl⁻ hot spots are concentrated in urbanized areas, including the Greater Toronto Area and Golden Horseshoe, with some rural zones also exhibiting elevated concentrations. Vulnerability mapping corresponded well with the observed Cl⁻ patterns and highlighted areas at risk for groundwater discharge to surface waters. While the DRASTIC-LU method offered finer resolution, the simplified SL-SG-LU index effectively captured broad vulnerability trends and is suitable for data-limited regions. This work provides a transferable framework for identifying Cl⁻ risk areas and supports long-term monitoring and management strategies in cold climate watersheds. Full article

The semi-natural grasslands of the Aso Caldera, Japan, have historically played a key role in maintaining biodiversity, tourism, and water resources. However, they are now in decline due to a decrease in the number of agricultural workers and an aging workforce, as well as structural changes and stagnation in the agricultural and livestock industries. This study focused on the water resource maintenance function of grasslands by applying a water balance model to quantify the potential impact of grassland restoration on water resources in Nango-Dani, located in the southern part of the Aso Caldera. We simulated groundwater recharge, storage, spring discharge, and baseflow under multiple scenarios involving the conversion of coniferous trees to grasslands. According to the calculation results, replacing 10% of coniferous trees with grassland increased groundwater recharge by approximately 0.86 million m³. This increase is due to grasslands having a higher groundwater recharge capacity, owing to their higher canopy permeability and lower evapotranspiration. The storage volume increased by approximately 0.54 million m³, which is equivalent to the annual water usage of 6700 people. Furthermore, grassland restoration increased spring discharge and baseflow. These results quantitatively demonstrate a significant enhancement of regional water resource sustainability and provide scientific evidence to inform land-use policies. Full article

Accurate streamflow forecasting at fine temporal and spatial scales is essential to manage the diverse hydrological behaviors of individual catchments, particularly in rapidly responding mountainous regions. This study compares three forecasting models ARIMAX, LSTM, and HEC-HMS applied to the Posina River basin in northern Italy, using 13 years of hourly hydrological data. While recent literature promotes multi-basin LSTM training for generalization, we show that a well-configured single-basin LSTM, combined with a rolling forecast strategy, can achieve comparable accuracy under high-frequency, data-constrained conditions. The physically based HEC-HMS model, calibrated for continuous simulation, provides robust peak flow prediction but requires extensive parameter tuning. ARIMAX captures baseflows but underestimates sharp hydrological events. Evaluation through NSE, KGE, and MAE shows that both LSTM and HEC-HMS outperform ARIMAX, with LSTM offering a compelling balance between accuracy and ease of implementation. This study enhances our understanding of streamflow model behavior in small basins and demonstrates that LSTM networks, despite their simplified configuration, can be reliable tools for flood forecasting in localized Alpine catchments, where physical modeling is resource-intensive and regional data for multi-basin training are often unavailable. Full article

Climate-driven hydrological extremes and anthropogenic interventions are increasingly altering streamflow regimes worldwide. While prior studies have explored climate or regulation effects separately, few have integrated multiple teleconnection indices and reservoir chronologies within a cross-basin comparative framework. This study addresses this gap by assessing long-term streamflow nonstationarity and its drivers at two key stations—Khabarovsk on the Amur River and Datong on the Yangtze River—representing distinct hydroclimatic settings. We utilized monthly discharge records, meteorological data, and large-scale climate indices to apply trend analysis, wavelet transform, percentile-based extreme diagnostics, lagged random forest regression, and slope-based attribution. The results show that Khabarovsk experienced an increase in winter baseflow from 513 to 1335 m³/s and a notable reduction in seasonal discharge contrast, primarily driven by temperature and cold-region reservoir regulation. In contrast, Datong displayed increased discharge extremes, with flood discharges increasing by +71.9 m³/s/year, equivalent to approximately 0.12% of the mean flood discharge annually, and low discharges by +24.2 m³/s/year in recent decades, shaped by both climate variability and large-scale hydropower infrastructure. Random forest models identified temperature and precipitation as short-term drivers, with ENSO-related indices showing lagged impacts on streamflow variability. Attribution analysis indicated that Khabarovsk is primarily shaped by cold-region reservoir operations in conjunction with temperature-driven snowmelt dynamics, while Datong reflects a combined influence of both climate variability and regulation. These insights may provide guidance for climate-responsive reservoir scheduling and basin-specific regulation strategies, supporting the development of integrated frameworks for adaptive water management under climate change. Full article

Understanding groundwater and surface water interaction is critical for managing water resources, particularly in water-stressed and rapidly urbanizing areas, such as many parts of Africa. A survey was conducted of borehole, spring, seep and river water radon, δ²H, δ¹⁸O and field parameters in the Jukskei River catchment, Johannesburg. Average values of electrical conductivity (EC) were 274 and 411 μS·cm⁻¹ for groundwater and surface water, and similarly for radon, 37,000 and 1100 Bq·m⁻³, with a groundwater high of 196,000 Bq·m⁻³ associated with a structural lineament. High radon was a good indicator of baseflow, highest at the end of the rainy season (March) and lowest at the end of the dry season (September), with the FINIFLUX model computing groundwater inflow as 2.5–4.7 L·m⁻¹s⁻¹. High EC was a poorer indicator of baseflow, also considering the possibility of wastewater with high EC, typical in urban areas. Groundwater δ²H and δ¹⁸O values are spread widely, suggesting recharge from both normal and unusual rainfall periods. A slight shift from the local meteoric water line indicates light evaporation during recharge. Surface water δ²H and δ¹⁸O is clustered, pointing to regular groundwater input along the stream, supporting the findings from radon. Given the importance of groundwater, further study using the same parameters or additional analytes is advisable in the urban area of Johannesburg or other cities. Full article

Integrated hydrological modeling plays a crucial role in advancing sustainable water resource management, particularly in regions facing seasonal and extreme precipitation events. However, comprehensive studies that assess hydrological variability in temperate river basins remain limited. This study addresses this gap by evaluating the performance of the Soil and Water Assessment Tool (SWAT) in simulating streamflow, water balance, and seasonal hydrological dynamics in the Chikugo River Basin, Kyushu Island, Japan. The basin, originating from Mount Aso and draining into the Ariake Sea, is subject to frequent typhoons and intense rainfall, making it a critical case for sustainable water governance. Using the Sequential Uncertainty Fitting Version 2 (SUFI-2) approach, we calibrated the SWAT model over the period 2007–2021. Water balance analysis revealed that baseflow plays dominant roles in basin hydrology which is essential for agricultural and domestic water needs by providing a stable groundwater contribution despite increasing precipitation and varying water demand. These findings contribute to a deeper understanding of hydrological behavior in temperate catchments and offer a scientific foundation for sustainable water allocation, planning, and climate resilience strategies. Full article

The Chushandian Reservoir, a key control project on the Huaihe River, is vital for flood control, water allocation, and maintaining ecological baseflow. This study analyzes runoff evolution and provides predictive insights for sustainable water management. Methods employed include Extremum Symmetric Mode Decomposition (ESMD) for decomposing complex signals, a mutation detection algorithm to identify significant changes in time-series data, and cross-wavelet transform to examine correlations and phase relationships between time series across frequencies. Additionally, the hybrid models GM-BP and CNN-LSTM were used for runoff forecasting. Results show cyclical fluctuations in annual runoff every 2.3, 5.3, and 14.5 years, with a significant decrease observed in 2010. Among climate factors, the Atlantic Multidecadal Oscillation (AMO) had the strongest correlation with runoff variability, while ENSO and PDO showed more localized impacts. Model evaluations indicated strong predictive performance, with Nash–Sutcliffe Efficiency (NSE) scores of 0.884 for GM-BP and 0.909 for CNN-LSTM. These findings clarify the climatic drivers of runoff variability and provide valuable tools for water resource management at the Chushandian Reservoir under future climate uncertainties. Full article

Increasing forest destruction from land use and land cover change (LULCC) has altered catchment hydrological processes worldwide. This trend is also endemic to the Belize River Watershed (BRW), a significant source of land and water resources for Belize. This study aims to understand LULCC impacts on BRW hydrological responses from 2000 to 2020 by applying the widely used Soil and Water Assessment Tool (SWAT). This study identified historical trends in LULCC in the BRW and explored an alternative 2020 land cover scenario to elucidate the role of protected forests for hydrological response regulation. A SWAT model for the BRW was developed at the monthly timescale and calibrated on in situ streamflow using SWAT Calibrations and Uncertainty Programs (SWAT-CUP). The results showed that the BRW SWAT model performed satisfactorily for streamflow simulation at the Benque Viejo (BV) gauge station but performed variably at the Double Run (DR) gauge station. Overall, the findings revealed watershed-level increases in monthly average sediment yield (34.40%), surface runoff (24.95%), streamflow (16.86%), water yield (16.02%), baseflow (11.58%), and percolation (3.40%), and decreases in monthly average evapotranspiration (ET) (3.52%). In conclusion, the BRW SWAT model is promising for uncovering the hydrological impacts of LULCCs with opportunities for further model improvement. Full article

Accurately estimating storm hydrographs for various return periods is crucial for planning and designing hydrological infrastructure, such as dams and drainage systems. A key aspect of this estimation is the separation of baseflow from storm runoff. This study proposes a method for deriving storm hydrographs for different return periods based on hydrological station records. The proposed approach uses three baseflow separation methods: constant, linear, and master recession curve. A significant advantage of the proposed method over traditional rainfall–runoff approaches is its minimal parameter requirements during calibration. The methodology is tested on records from the Lengupá River watershed in Colombia, using data from the Páez hydrological station, which has a drainage area of 1090 km². The results indicate that the linear method yields the most accurate hydrograph estimates, as demonstrated by its lower root mean square error (RMSE) of 0.35%, compared to the other baseflow separation techniques, the values of which range from 2.92 to 3.02%. A frequency analysis of hydrological data was conducted using Pearson Type III and Generalized Extreme Value distributions to identify the most suitable statistical models for estimating extreme events regarding peak flow and maximum storm hydrograph volume. The findings demonstrate that the proposed methods effectively reproduce storm hydrographs for return periods ranging from 5 to 200 years, providing valuable insights for hydrological design, which can be employed using the data from stream gauging stations in rivers. Full article

Baseflow, the portion of streamflow sustained by groundwater discharge, is crucial for maintaining river ecosystems. Irrigation practices could influence baseflow, with varying impacts depending on the irrigation practices. This study evaluates the impact of irrigation expansion on baseflows, accounting for weather-driven irrigation demand. The SWAT+gwflow model was applied to the San Antonio Catchment (225 km²) in Uruguay, a region dominated by intensive horticulture and citrus farming reliant on groundwater. Irrigation expansion involves extending irrigated areas from 6193 to 8561 hectares, increasing average groundwater use by 18.4%. Model projections over 25 years indicate up to 1.2 m of annual groundwater depletion, including severe local reductions in monthly baseflow during dry years. Limitations have been discussed and compared with applications in other regions. These results have implications for water management, as current regulations ignore groundwater–surface water interactions and fail to account for variable irrigation water demand in high variable weather conditions. This approach provides a tool to anticipate the environmental effects of irrigation expansion and supports the development of adaptive regulations that better align with hydrological realities. Full article

The US state of Iowa has experienced profound historical changes in its streamflow and baseflow. While several studies have noted increasing baseflow and baseflow index (BFI) values throughout the 20th century, analyses quantifying BFI trends in recent years or exploring spatial differences in watersheds marked by varying land use and geologic properties have not been conducted. This study calculated annual values for BFI (and several other hydrologic metrics) using flow records from 42 Iowa stream gauges containing at least 50 years of uninterrupted measurements. While BFI overwhelmingly rose throughout the mid-1900s, circa 1990 it began to level off. In some areas of Iowa (e.g., the southwest), BFI has continued to rise over the past 30 years—albeit at a slower rate; in other regions, it has become stationary or declined. One site failed to follow this trend (Walnut Cr), the only basin to experience large-scale urbanization. Furthermore, BFI demonstrated a strong negative correlation to streamflow flashiness, indicating that rising baseflow has also made Iowa streams less dynamic. BFI was largely independent of overall streamflow. These results may suggest the increased influence of conservation practices and the diminishing impacts of tile drainage on the delivery of water to Iowa’s rivers. Full article

Baseflow is a crucial component of river flow in alpine inland basins, playing an essential role in watershed ecological health and water resource management. In high-latitude cold regions, seasonal freeze-thaw processes make baseflow formation mechanisms particularly complex. However, the dominant factors affecting baseflow and their relative contributions remain unclear, limiting the accuracy of flow estimation and effective water resource management. This study employed baseflow separation techniques and statistical methods, including the Mann-Kendall test, to investigate temporal trends and abrupt changes in baseflow and the baseflow index (BFI) at multiple time scales (annual, seasonal, and monthly) from 2005 to 2012. Additionally, the timing of snowmelt and its impact on baseflow were examined. Key findings include the following: (1) Baseflow and BFI showed distinct temporal variability with non-significant upward trends across all time scales. Annual BFI ranged from 0.48 to 0.61, contributing approximately 50% of total runoff. (2) At the seasonal scale, baseflow remained relatively stable in spring, increased in autumn, and showed non-significant decreases in summer and winter. Monthly baseflow exhibited an increasing trend. (3) The snowmelt period occurred between April and May, with baseflow during this period strongly correlated with climatic factors in the following order: winter precipitation > positive accumulated temperature > winter air temperature > negative accumulated temperature. The strongest positive correlation was observed between baseflow and winter precipitation (R = 0.724), while negative correlations were found with accumulated temperatures and winter air temperature. These findings offer valuable insights for predicting water resource availability and managing flood and ice-jam risks in cold regions. Full article

Soil controls water distribution, which is crucial for accurate hydrological modeling. MOHID-Land is a physically based, spatially distributed model that uses van Genuchten–Mualem (VGM) functions to calculate water content in porous media. The hydraulic soil parameters of VGM are dependent on soil type and are typically estimated from experimental data; however, they are often obtained using pedotransfer functions, which carry significant uncertainty. As a result, calibration is frequently required to account for both the natural spatial variability of soil and uncertainties estimation. This study focuses on a representative Atlantic Forest watershed. It assesses the sensitivity of channel flow to VGM parameters using a mathematical approach based on residuals derivative, aimed at enhancing soil calibration efficiency for MOHID-Land. The model’s performance significantly improved following calibration, considering only five parameters. The NSE improved from 0.16 on the base simulation to 0.53 after calibration. A sensitivity analysis indicated the curve adjustment parameter ($n$) as the most sensitive parameter, followed by saturated water content (${\theta }_s$) considering the 10% variation. Additionally, a combined change in ${\theta }_s$, $n$, residual water content (${\theta }_r$), curve adjustment parameter ($\alpha$), and saturated conductivity ($K_{sat}$) values by 10% significantly improves the model’s performance, by reducing channel flow peaks and increasing baseflow. Full article

Prioritizing agricultural land use is a significant challenge for sustainable development in the rapidly urbanizing, semi-arid riverine basins of South Asia, especially under climate variability and water scarcity. This study introduces a systematic framework combining remote sensing and geospatial data with the Soil and Water Assessment Tool (SWAT) model, morphometric analysis, and VIKOR-based Multi-Criteria Decision Analysis (MCDA) to effectively identify Agricultural Land Prioritization (AgLP) areas in the Upper Kansai Basin, India, while reducing the environmental impact, in line with Sustainable Development Goals (SDGs). The SWAT model simulation reveals varied hydrological patterns, with basin water yields from 965.9 to 1012.9 mm and a substantial baseflow (~64% of total flow), emphasizing essential groundwater–surface water interactions for sustainable agriculture. However, the discrepancy between percolation (47% of precipitation) and deep recharge (2% of precipitation) signals potential long-term groundwater challenges. VIKOR analysis offers a robust prioritization framework, ranking SW4 as the most suitable (Qi = 0.003) for balanced hydrological and morphometric features, in agreement with the SWAT outcomes. SW4 and SW5 display optimal agricultural conditions due to stable terrain, effective water retention, and favorable morphometric traits (drainage density 3.0–3.15 km/km²; ruggedness 0.3–0.4). Conversely, SW2, with high drainage density (5.33 km/km²) and ruggedness (2.0), shows low suitability, indicating risks of erosion and poor water retention. This integrated AgLP framework advances sustainable agricultural development and supports SDGs, including SDG 2 (Zero Hunger), SDG 6 (Clean Water), SDG 13 (Climate Action), and SDG 15 (Life on Land). Incorporating hydrological dynamics, land use, soil properties, and climate variables, this approach offers a precise assessment of agricultural suitability to address global sustainability challenges in vulnerable riverine basins of developing nations. Full article