Search Results (34)

High-mountain lotic ecosystems in the tropical Andes are increasingly threatened by agricultural expansion and seasonal hydrological variability. This study evaluates structural water quality shifts and benthic macroinvertebrate community assembly across an environmental degradation gradient in the La Chorrera micro-basin (Boyacá, Colombia). A weighted multiplicative Water Quality Index (mWQI), originally developed in previous literature, was implemented and validated alongside biotic scores (BMWP/Col) and Canonical Correspondence Analysis (CCA) across 16 sampling points during contrasting wet and dry seasons. The results demonstrate that intense precipitation during the wet season introduces a volumetric dilution effect, maintaining high ecological quality scores (mWQI > 80.0) even in deeply modified agricultural sectors. Conversely, severe baseflow contraction during the dry season triggers pollutant concentration, driving total phosphorus to hyper-eutrophic peaks (9.20 mg/L) and forcing a complete mathematical collapse of the index (mWQI = 0.00). The CCA biplot confirmed that seasonal chemical filters combined with hypoxia (<60% oxygen saturation) eliminate highly responsive macroinvertebrate orders (Ephemeroptera, Plecoptera, Trichoptera), leading to absolute dominance of hypoxia-tolerant opportunists (Chironomidae and Oligochaeta). The benthic community shifted from physical stress (sedimentation) during the wet season to chemical stress (nutrient toxicity and oxygen depletion) during the dry season. The multiplicative framework effectively isolates localized ecological tipping points, providing a high-sensitivity baseline tool for targeted watershed restoration in tropical alpine regions. Full article

Surface water–groundwater interactions within oasis–desert ecotones of arid regions play a pivotal role in sustaining regional water security and ecological stability. Taking the Niya River Basin in Xinjiang, Northwest China, as a representative inland watershed, this study systematically elucidates the mechanisms and seasonal dynamics of surface water–groundwater coupling under the combined influences of natural processes and anthropogenic activities. A total of 68 surface water and groundwater samples were collected during the dry, normal, and wet hydrological periods. Integrated hydrochemical characterization, mineral saturation index analysis, and stable isotope (δ²H and δ¹⁸O) mass balance modeling were employed to quantify recharge contributions and unravel hydrogeochemical evolution pathways. Results indicate that the waters in the study area are predominantly brackish to saline, with consistent dominant ionic assemblages (SO₄²⁻ and Na⁺) across all hydrological periods, highlighting evaporite dissolution as the primary control on solute composition. Hydrochemical evolution is jointly regulated by evaporation concentration, water–rock interactions, and cation exchange processes. Surface water chemistry reflects the combined effects of silicate weathering and evaporite dissolution, whereas groundwater chemistry is mainly governed by evaporite dissolution coupled with pronounced cation exchange. Stable isotope signatures reveal substantial secondary evaporation of regional precipitation prior to recharge. Frequent bidirectional recharge between surface water and groundwater was observed, exhibiting distinct seasonal transitions. During the dry period, groundwater provides significant baseflow support to surface water (48.6% in the oasis zone and 54.3% in the desert zone). In the normal period, recharge direction reverses, with surface water becoming the dominant source of groundwater recharge (99.0% in the oasis zone and 76.6% in the desert zone). In the wet period, spatial heterogeneity becomes evident: surface water continues to dominate groundwater recharge in the oasis zone (92.7%), whereas groundwater recharge to surface water prevails in the desert zone (50.5%). This study identifies a seasonally dynamic “discharge–infiltration–zonal regulation” bidirectional recharge pattern in arid inland river systems. The findings advance the mechanistic understanding of hydrological connectivity reconstruction within oasis–desert ecotones and provide a scientific basis for optimized regional water resource allocation and groundwater salinization risk mitigation. Full article

Distinguishing the hydrological impacts of anthropogenic groundwater withdrawal from natural climate variability is a critical yet complex challenge in sustainable water resource management. This study quantitatively evaluated the watershed-scale hydrological response to the increased groundwater abstraction in the Han River basin (35,770 km²) of South Korea using the Soil and Water Assessment Tool (SWAT). Groundwater use datasets for the 1970s and 2010s were constructed using groundwater statistical yearbooks. By applying the groundwater use datasets under 2010s weather conditions, we effectively isolated the specific effects of human usage. The results indicated that a rise in the annual groundwater abstraction from 9.6 to 22.3 million m³ reduced the average streamflow by 6.59%. The baseflow and groundwater recharge were identified as the most sensitive components, decreasing by 20.7% and 20.8%, respectively. Notably, intensive summer withdrawal (53% of the annual total) depleted aquifer storage, directly exacerbating streamflow reductions during the autumn and winter seasons. A flow duration analysis further confirmed that the duration of the dry season—defined by the flow exceeded for 275 days (Q₂₇₅)—extended by 13 days, as the exceedance duration for the specific flow duration shifted from Q₂₇₅ to Q₂₆₃. These findings highlighted that excessive groundwater withdrawal compromises seasonal hydrological stability, necessitating integrated management strategies to secure the streamflow during critical dry periods. Full article

This paper reports the findings of the first initiative of developing a year-round streamflow forecasting system using the HBV hydrologic model in a data-scarce Ruvu catchment in Tanzania. Considering the importance of the Ruvu catchment as the main source of water to the fast-growing mega city of Dar es Salaam, the researchers in this study made the most of the available data and their joint previous application experience of the modelling framework for the purpose of setting up a reliable operational model. In addition, the researchers adopted a phased approach of developing the streamflow forecasting system, using HBV as a hydrological model, which resulted in a simplified model structure with minimized complexity. For instance, the snow routine was removed as it is not relevant to the study area, and a few parameters were reduced to improve model efficiency. As a measure to demonstrate model performance, in addition to the Nash–Sutcliffe Efficiency (NSE) parameter used for model calibration and verification, several other error functions and graphical displays were used. The model performance values, as measured by NSE for calibration and verification periods, are 0.85 and 0.82 for Ruvu Roadbridge (1H8A), and 0.80 and 0.82 for Kidunda (1H3), respectively, and all are classified as “Very Good”. In addition, the PBIAS of less than ±5% in calibration indicates excellent water balance simulation. Furthermore, the forecast’s performance in this study is evidenced by an annual forecast R² of 0.933, with operational meteorological forecasts improving to 0.962 with “perfect” precipitation; dry season performance with R² of 0.964, demonstrating high skill in baseflow-dominated periods; and the PBIAS for forecasts of 0.866, indicating a slight systematic under-forecasting correctable by a ~15% precipitation adjustment. Although the Ruvu catchment has been characterized by this study as a data-scarce catchment, the results of the operational hydrological forecasting system vary with season and quality of forecast meteorological data, and the model is already launched for operational use. As evidenced by these study findings, the journey from data scarcity to operational forecast provision in the Ruvu catchment demonstrates that the principal barriers are fundamentally institutional and capacity-related. The authors suggest that any future forecasting initiative should put much emphasis on both the understanding of the modelling framework to be used and adequate data collection and analysis, in a synergetic manner with all relevant agencies. And it is also recommended to be vigilant regarding changes in the catchment characteristics and model performance during its life cycle, as the performance of the developed model is only valid under the condition that it was calibrated and validated. Full article

This study develops a conjunctive-use framework that couples a surface water allocation model with the MODFLOW groundwater model to evaluate the interactions between surface water operations and groundwater recharge and pumping. The framework enables coordinated surface–groundwater management through iterative feedback between allocation decisions and groundwater responses. Three representative managed aquifer recharge cases in Taiwan are examined, each reflecting a distinct operational logic: (1) a space-for-time strategy that extends wet-season benefits through distributed recharge using irrigation surplus; (2) a centralized support–distributed feedback approach in subsidence-prone areas, where concentrated surface water is delivered to targeted zones while maintaining flexibility for upstream allocation; and (3) a time-for-volume mechanism that converts short-duration flood events into stable, long-term baseflow supply. The simulation results show that these strategies reduce downstream irrigation deficit ratios (e.g., from 0.58 to 0.22), raise groundwater levels by up to approximately 3.5 m in subsidence-sensitive zones, and substantially enhance drought resilience by reducing extreme reservoir depletion during prolonged dry periods. Overall, the proposed framework provides quantitative evidence and a practical planning tool for surface water-oriented conjunctive use, supporting more sustainable and resilient multi-source water management. Full article

Accurate daily runoff forecasting is essential for flood control and water resource management, yet existing models struggle with the seasonal non-stationarity and inter-basin variability of runoff sequences. This paper proposes a Season-Aware Ensemble Forecasting (SAEF) method that integrates SVM, LSSVM, LSTM, and BiLSTM models to leverage their complementary strengths in capturing nonlinear and non-stationary hydrological dynamics. SAEF employs a seasonal segmentation mechanism to divide annual runoff data into four seasons (spring, summer, autumn, winter), enhancing model responsiveness to seasonal hydrological drivers. An Improved Arctic Puffin Optimization (IAPO) algorithm optimizes the model weights, improving prediction accuracy. Beyond numerical gains, the framework also reflects seasonal runoff generation processes—such as rapid rainfall–runoff in wet seasons and baseflow contributions in dry periods—providing a physically interpretable perspective on runoff dynamics. The effectiveness of SAEF was validated through case studies in the Dongjiang Hydrological Station (China), the Elbe River (Germany), and the Quinebaug River basin (USA), using four performance metrics (MAE, RMSE, NSEC, KGE). Results indicate that SAEF achieves average Nash–Sutcliffe Efficiency Coefficient (NSEC) and Kling–Gupta efficiency (KGE) coefficients of over 0.92, and 0.90, respectively, significantly outperforming individual models (SVM, LSSVM, LSTM, BiLSTM) with RMSE reductions of up to 58.54%, 55.62%, 51.99%, and 48.14%. Overall, SAEF not only strengthens predictive accuracy across diverse climates but also advances hydrological understanding by linking data-driven ensembles with seasonal process mechanisms, thereby contributing a robust and interpretable tool for runoff forecasting. Full article

Understanding and quantifying the coupled effects of land cover change and climate change on hydrological regimes is critical for sustainable water management in tropical mountainous regions. The Río Negro Basin in eastern Antioquia, Colombia, has undergone rapid urban expansion, agricultural intensification, and deforestation over recent decades, profoundly altering its hydrological dynamics. This study integrates advanced satellite image processing, AI-based land cover modeling, climate change projections, and distributed hydrological simulation to assess future streamflow responses. Multi-sensor satellite data (Landsat, Sentinel-1, Sentinel-2, ALOS) were processed using Random Forest classifiers, intelligent multisensor fusion, and probabilistic neural networks to generate high-resolution land cover maps and scenarios for 2060 (optimistic, trend, and pessimistic), with strict area constraints for urban growth and forest conservation. Future precipitation was derived from MPI-ESM CMIP6 outputs (SSP2-4.5, SSP3-7.0, SSP5-8.5) and statistically downscaled using Empirical Quantile Mapping (EQM) to match the basin scale and precipitation records from the national hydrometeorological service of the Colombia IDEAM (Instituto de Hidrología, Meteorología y Estudios Ambientales, Colombia). The TETIS hydrological model was calibrated and validated using observed streamflow records (1998–2023) and subsequently used to simulate hydrological responses under combined land cover and climate scenarios. Results indicate that urban expansion and forest loss significantly increase peak flows (Q90, Q95) and flood risk while decreasing baseflows (Q10, Q30), compromising water availability during dry seasons. Conversely, conservation-oriented scenarios mitigate these effects by enhancing flow regulation and groundwater recharge. The findings highlight that targeted land management can partially offset the negative impacts of climate change, underscoring the importance of integrated land–water planning in the Andes. This work provides a replicable framework for modeling hydrological futures in data-scarce mountainous basins, offering actionable insights for regional authorities, environmental agencies, and national institutions responsible for water security and disaster risk management. Full article

Understanding the spatiotemporal dynamics of runoff and its drivers is essential for water resources management in mid–high latitude basins. This study investigates runoff changes in the Songhua River Basin, Northeast China, during 1980–2022 using the Budyko framework, combined with Mann–Kendall trend analysis, Pettitt tests, Hurst index, and wavelet analysis. Results indicate significant climatic shifts, with basin-wide warming, heterogeneous precipitation changes, and declining relative humidity, leading to intensified cold-season drying. Temperature and evapotranspiration showed strong persistence, while precipitation exhibited high variability and periodicities linked to ENSO and East Asian monsoon anomalies. Runoff increased significantly in the mainstream Songhua and Nenjiang basins, especially in autumn, with abrupt changes clustered between 2009 and 2015. The Second Songhua Basin displayed weaker variability, largely influenced by reservoir regulation and land-use change. Attribution analysis confirmed precipitation as a primary driver, with elasticity coefficients exceeding 3 in the Nenjiang Basin during some summers, indicating extreme sensitivity. Evapotranspiration suppressed runoff under high temperatures, while freeze–thaw processes and human interventions became critical in spring and autumn. The aridity index revealed persistent winter deficits and rising spring–autumn drying trends after 2000, posing risks for snowmelt runoff and baseflow sustainability. Overall, runoff evolution reflects a shift from gradual to threshold-triggered regime changes driven by both climate variability and human regulation. These findings provide a basis for adaptive, basin-specific water management and climate resilience strategies in Northeast China. Full article

To promote sustainable development and guide the responsible use of natural ecosystems, the United Nations introduced the concept of ecosystem accounting. Ecosystem services are key components of ecosystem accounting. Water-related ecosystem services (ES) are of primary importance for Armenia due to relatively dry climate, and dependence on irrigation water for agriculture. This study aims to conduct a pilot-level quantitative scoping assessment and mapping of key water-related regulating ES in accordance with the SEEA-EA guidelines, and to offer recommendations to initiate their accounting in Armenia. We used three Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models—Seasonal Water Yield, Sediment Delivery Ratio, and Urban Flood Risk Mitigation. Input data for these models were sourced from global and national databases, as well as ESRI land cover datasets for 2017 and 2023. Government-reported data on river flow and water consumption were used to assess the ES supply–use balance. The results show that natural ecosystems contribute between 11% and 96% of the modeled ES, with the strongest impact on baseflow supply and erosion prevention. The average current erosion is estimated at 2.3 t/ha/year, and avoided erosion at 46.4 t/ha/year. Ecosystems provide 93% of baseflow, with an average baseflow index of 34%, while on bare ground it is only 3%. Changes in land cover from 2017 to 2023 have resulted in alterations across all assessed ES. Comparison of total water flow and baseflow with water consumption revealed water-deficient provinces. InVEST models show their general operability at the scoping phase of ecosystem accounting planning. Advancing ES accounting in Armenia requires model calibration and validation using local data, along with the integration of InVEST and hydrological and meteorological models to account for the high diversity of natural conditions in Armenia, including terrain, geological structure, soil types, and regional climatic differences. 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

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

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

Africa has the largest area of wetlands of international importance, and papyrus constitutes the most dominant species for many of these wetlands. This hydrological modelling study assesses and quantifies the impacts of these papyrus wetlands on historical baseflow and quickflow, as well as future flood and low flows in the Mpologoma catchment in Uganda. Assessment over the historic period shows that wetlands strongly attenuate quickflow while moderately enhancing baseflow. They play a moderating role in most months, except for the first dry season (June and July), due to the reversal of flows between wetlands and rivers that often occur during this period. Annual estimates show that wetlands are four times better at regulating quickflow than baseflow. Examination of changes at 2 and 4 °C global warming levels (GWLs) indicate that wetlands will play critical roles in mitigating flood risks, with a lesser role in supporting low flows. Wetlands are predicted to lower future mean flood magnitude by 5.2 and 7.8% at GWL2 and GWL4, respectively, as well as halving the average number of flood events in a year, irrespective of the warming level. This work shows that papyrus-dominated wetlands strongly influence catchment hydrology, with significant roles on quickflow, including floods, and highlights the need for their conservation and protection. Full article

Baseflow is a stable part of streamflow and the main component of streamflow during the dry season. Baseflow plays an important role in the water cycle, and in ecological environment protection of the Yellow River basin (YRB). Taking the Zuli, Kuye, and Tuwei basins, and the Jingle sub-basin as examples, the baseflow was separated using a recursive digital filtering method. The intra-annual, inter-annual, and chronological characteristics of baseflow and the baseflow index (BFI) were analyzed, and driving factors were analyzed from the perspective of climate-change and human-impact factors. The results showed that: (1) The annual baseflow of the basins mainly declined, trending downward in all four test basins, while the BFI increased in two of the basins and remained nearly constant in the other two basins; however, the distributions of baseflow and the BFI were more uniform. (2) The intra-annual patterns for baseflow and the BFI showed changes between earlier and later periods. (3) Precipitation and soil and water conservation measures were the primary driving forces of baseflow change in the basins. The influence of the former weakened while the latter strengthened, and coal mining in the Kuye River and Tuwei River basins also influenced baseflow significantly. (4) When the normalized difference vegetation index (NDVI) < 0.375, the BFI of test watersheds gradually decreased with the increase in the NDVI. When 0.375 < NDVI < 0.65, the BFI of the basins gradually increased with the increase in the NDVI and the underlying surface continued to improve. When NDVI > 0.65, the increase rate of the BFI decreased and the soil and water conservation capacity of the underlying surface tended to be stable. Full article

Changes in land use and climate can affect both the surface runoff and baseflow of streamflow. Baseflow significantly contributes to stream function in regions where climatic characteristics are seasonally distinct. Baseflow estimation depends on the observed streamflow in gauge water sheds, but baseflow estimations in data-poor or gauged watersheds depend solely on streamflow predicted from the hydrologic model. To accurately predict base runoff through the model, it is necessary to apply proper hydrological parameters. Accordingly, the objectives of this study are to (1) improve predictions of SWAT by applying the alpha factor estimated using BFLOW for calibration, and (2) evaluate streamflow and baseflow the effects of changes in land use and climate. The results show the alpha factor estimated using BFLOW in SWAT calibration improves the prediction for streamflow and recessions in the baseflow. In this study, streamflow increased due to land use change (impervious urban and agricultural areas), while baseflow decreased. The baseflow was more significant in the dry season than in the wet season, and the baseflow fluctuation was significant from February to May. Moreover, the changes in land use in the study area lead to differences in the seasonal characteristics observed for the temporal distribution of streamflow and baseflow. Full article