Search Results (113)

The Cau River Basin in northeastern Vietnam is an ecologically and economically important watershed, yet it has lacked comprehensive hydrological modelling to date. Characterised by highly complex topography, diverse land use/land cover, and limited hydrometeorological data, the basin presents challenges for water resource assessment and management. This study applies the SWAT hydrological model to simulate streamflow dynamics in the Cau River Basin over a 31-year period (1990–2020) using multiple-source geospatial data, including a 30 m digital elevation model, official soil and land use maps, and daily climate records from six meteorological stations. Model calibration (1997–2008) and validation (2009–2020) were conducted using the SWAT-CUP tool, achieving strong performance with a Nash–Sutcliffe Efficiency (NSE) of 0.95 and 0.90, and R² of 0.95 and 0.91, respectively. Sensitivity analysis identified four key parameters most influential on streamflow (curve number, saturated hydraulic conductivity, soil evaporation compensation factor, and available water capacity), supporting a more focused and effective calibration process. Model results revealed substantial spatio-temporal variability in runoff, with annual surface runoff ranging from 19.8 mm (2011) to 56.4 mm (2013), generally lower in upstream sub-watersheds (<30 mm) and higher in downstream areas (>60 mm). The simulations also showed a clear seasonal contrast between the wet and dry periods. These findings support evidence-based strategies for flood and drought mitigation, inform agricultural and land use planning, and offer a transferable modelling framework for similarly complex watersheds. Full article

Flash floods, exacerbated by climate change and land use alterations, are among the most destructive natural hazards globally, leading to significant damage and loss of life. In this context, the Flash Flood Potential Index (FFPI), which is a terrain and land surface-based model, and Google Earth Engine (GEE) were used to assess flood-prone zones across North Macedonia’s watersheds. The presented GEE-based assessment was accomplished by a custom script that automates the FFPI calculation process by integrating key factors derived from publicly available sources. These factors, which define susceptibility to torrential floods, include slope (Copernicus GLO-30 DEM), land cover (Copernicus GLO-30 DEM), soil type (SoilGrids), vegetation (ESA World Cover), and erodibility (CHIRPS). The spatial distribution of average FFPI values across 1396 small catchments (10–100 km²) revealed that a total of 45.4% of the area exhibited high to very high susceptibility, with notable spatial variability. The CHIRPS rainfall data (2000–2024) that combines satellite imagery and in situ measurements was used to estimate peak 24 h runoff and discharge. To improve the accuracy of CHIRPS, the data were adjusted by 30–50% to align with meteorological station records, along with normalized FFPI values as runoff coefficients. Validation against 328 historical river flood and flash flood records confirmed that 73.2% of events aligned with moderate to very high flash flood susceptibility catchments, underscoring the model’s reliability. Thus, the presented cloud-based scenario highlights the potential of the GEE’s efficacy in scalability and robustness for flash flood modeling and regional risk management at national scale. Full article

The rising demand for freshwater, driven by population growth, economic development, and climate change, necessitates proactive watershed management. This study focuses on prioritizing the watersheds of the Doon Valley in the Indian Himalayan Region (IHR) using geospatial techniques. It involves a detailed morphometric analysis incorporating hydrological and topographical parameters, ranking the watersheds using the compound factor value (CFV), and prioritizing them based on the given CFV. The Doon Valley watersheds exhibit dendritic to parallel drainage patterns and moderate relief. The study identifies the Suswa watershed as the most susceptible, necessitating urgent conservation attempts to mitigate soil erosion and ensure sustainable land use. In contrast, the Song watershed, characterized by steep slopes and high relief, requires targeted management strategies to control rapid runoff and prevent potential flooding. The Asan watershed, with a medium priority classification, also requires intervention to prevent ecological degradation. Prioritization based on the CFV provides a strategic framework for targeted management, offering valuable insights for policymakers and planners. This research supports sustainable watershed management by guiding effective conservation practices and addressing the specific needs of each watershed. Full article

Under the global urbanization context, irrational land use patterns have exacerbated ecosystem imbalance. Developing watershed ecological risk assessment methods based on adaptive cycle theory holds significant scientific importance for flood risk prevention. This study established a watershed ecological risk assessment framework within the adaptive cycle framework, focusing on the Poyang Lake Ecological Economic Zone in the middle-lower Yangtze River Basin. The results revealed that high-risk ecological areas clustered around the Poyang Lake water system with scattered urban distribution, while medium-risk zones dominated the study area. Low-risk regions primarily concentrated in the Yuanhe Plain of southwestern region. The system exhibited significant spatial heterogeneity in “exposure” and “disturbance” risks. Medium–high exposure pixels accounted for 43.3% with a dispersed distribution, whereas disturbance pixels concentrated in Poyang Lake waters and developed urban areas (64.34%), indicating that disturbance exerted a stronger influence on risk assessment outcomes. Governance practices demonstrated that policy preferences may introduce biases into watershed ecological risk evaluations. Multi-scenario simulations using an Ordered Weighted Averaging (OWA) algorithm identified risk-uncertain zones in southeastern hilly areas and northern Poyang Lake waters, while distinguishing stable high/low-risk regions unaffected by decision-making influences. These findings provide critical references for formulating sustainable watershed management strategies. Full article

This study presents a multi-temporal analysis of vegetation cover changes in the Guayepo stream watershed (Cartagena de Indias, Colombia) for 2000, 2010, and 2020 and their impact on surface runoff generation. Hydrological data from 1974 to 2019 were processed to model intensity–duration–frequency (IDF) curves and simulate heavy rainfall events using six storms of nine-hour duration. Following the Soil Conservation Service guidelines, these were used to estimate runoff flows for return periods of 25, 50, and 100 years via the curve number method in HEC-HMS. Vegetation cover was assessed using the CORINE land cover methodology applied to official land use maps. The analysis revealed a significant loss of natural vegetation: dense forest cover declined dramatically from 14.38% in 2000 to 0% in 2020, and clean pastures were reduced by 46%. In contrast, weedy pastures and pasture mosaics with natural areas increased by 299% and 136%, respectively, reflecting a shift towards more degraded land cover types. As a result of these changes, total runoff flows of the model increased by 9.7% and 4.3% under antecedent moisture conditions I and II, respectively, for the 100-year return period. These findings reveal ongoing degradation of the watershed’s natural cover, linked to expanding agricultural uses and changes in vegetation structure. The decline in forested areas has increased surface runoff, elevating flood risk and compromising the watershed’s hydrological regulation. The study suggests that integrated land management and ecological restoration strategies could be key in preserving hydrological ecosystem services and reducing the negative impacts of land use change. Full article

Leaky dams have become essential nature-based solutions for flood management, providing sustainable alternatives to traditional engineered flood control methods. This review delves into the mechanisms by which leaky dams operate, including the regulation of water flow through velocity reduction and distribution across floodplains, effective sediment trapping and soil quality enhancement, and the facilitation of groundwater recharge and water table stabilization. These structures not only mitigate peak flood flows and reduce erosion but also contribute to enhanced biodiversity by creating diverse aquatic habitats and maintaining ecological connectivity. The effectiveness of leaky dams is assessed through various performance metrics, demonstrating significant reductions in peak flows, improved sediment management, and increased groundwater levels, which collectively enhance ecosystem resilience and water quality. However, the implementation of leaky dams presents several technical challenges, such as design complexity, hydrological variability, maintenance requirements, and socio-economic factors like land use conflicts and economic viability. Additionally, while leaky dams offer numerous environmental benefits, potential negative impacts include habitat disruption, sediment accumulation, and alterations in water quality, which necessitate careful planning and adaptive management strategies. Emerging trends in leaky dam development focus on the integration of smart technologies, such as real-time monitoring systems and artificial intelligence, to optimize performance and resilience against climate-induced extreme weather events. Advances in modeling and monitoring technologies are facilitating the effective design and implementation of leaky dam networks, promoting their incorporation into comprehensive watershed management frameworks. This review highlights the significant potential of leaky dams as integral components of sustainable flood management systems, advocating for their broader adoption alongside conventional engineering solutions to achieve resilient and ecologically balanced water management. Full article

Studying natural hazards in the context of human-induced landscape transformation is complex, especially in regions with limited information. The narratives of the elderly can play a role in filling these knowledge gaps at the multi-decadal timescale. Here, we build upon a citizen-based elderly approach to understanding natural hazard patterns and landscape transformation in a tropical mountainous environment, the Kigezi Highlands (SW Uganda). We engaged 98 elderly citizens (>70 years old) living in eight small watersheds with different characteristics. Through interviews and focus group discussions, we reconstructed historical timelines and used participatory mapping to facilitate the interview process. We cross-checked the information of the elderly citizens with historical aerial photographs, archives, and field visits. Our results show that major land use/cover changes are associated with a high population increase over the last 80 years. We also evidence an increase in reported natural hazard events such as landslides and flash floods from the 1940s until the 1980s. Then, we notice a stabilization in the number of hazard events per decade, although the two most impacted decades (1980s and 2000s) stand out. Despite this new information, an increase in natural hazard frequency due to land use/cover change cannot yet be quantitatively validated, especially when the probable modulator effect of climate variability is considered. Nevertheless, the increase in the exposure of a vulnerable population to natural hazards is clear, and population growth together with poor landscape management practices are the key culprits that explain this evolution. This study demonstrates the added value of historical narratives in terms of understanding natural hazards in the context of environmental changes. This insight is essential for governments and non-governmental organizations for the development of policies and measures for disaster risk reduction that are grounded in the path dependence of local realities. Full article

Changes in land use and land cover (LULC) and climate increasingly influence flood occurrences in the Gumara watershed, located in the Upper Blue Nile (UBN) basin of Ethiopia. This study assesses how these factors impact return period-based peak floods, flood source areas, and future high-flow extremes. Merged rainfall data (1981–2019) and ensemble means of four CMIP5 and four CMIP6 models were used for historical (1981–2005), near-future (2031–2055), and far-future (2056–2080) periods under representative concentration pathways (RCP4.5 and RCP8.5) and shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). Historical LULC data for the years 1985, 2000, 2010, and 2019 and projected LULC data under business-as-usual (BAU) and governance (GOV) scenarios for the years 2035 and 2065 were used along with rainfall data to analyze flood peaks. Flood simulation was performed using a calibrated Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) model. The unit flood response (UFR) approach ranked eight subwatersheds (W1–W8) by their contribution to peak flood magnitude at the main outlet, while flow duration curves (FDCs) of annual maximum (AM) flow series were used to analyze changes in high-flow extremes. For the observation period, maximum peak flood values of 211.7, 278.5, 359.5, 416.7, and 452.7 m³/s were estimated for 5-, 10-, 25-, 50-, and 100-year return periods, respectively, under the 2019 LULC condition. During this period, subwatersheds W4 and W6 were identified as major flood contributors with high flood index values. These findings highlight the need to prioritize these subwatersheds for targeted interventions to mitigate downstream flooding. In the future period, the highest flow is expected under the SSP5-8.5 (2056–2080) climate scenario combined with the BAU-2065 land use scenario. These findings underscore the importance of strategic land management and climate adaptation measures to reduce future flood risks. The methodology developed in this study, particularly the application of RF-MERGE data in flood studies, offers valuable insights into the existing knowledge base on flood modeling. Full article

With the intensification of climate change and human activities, the impacts of land use shifts on hydrological processes are becoming more pronounced, especially in regions with complex geographic, geological, and climatic conditions such as the Northeast Black Soil Region, China. This study quantitatively examines the variations in various land use types from 1980 to 2020 by means of a land use transfer matrix, and it incorporates the multi-year average runoff value to mitigate the interference of short-term climate fluctuations on the runoff trend, thereby enhancing the representativeness and stability of the simulation outcomes. The SWAT (Soil and Water Assessment Tool) model is employed to simulate land use alterations in different periods. The findings indicate that the area of farmland increased by 5.34% and the area of grassland decreased by 5.36% over 40 years. The areas of forest land and wetland have fluctuated significantly due to policy interventions and population growth. This study discovers that LUCC has resulted in a marginal increase in annual water yield. For instance, the water yield of paddy fields in 2020 amounts to 92.26 mm/year, which is 0.52–9.42% higher than the historical scenario and exhibits a notable upward trend in summer. Spatial analysis discloses regional disparities, with substantial changes in the hydrological behavior of northern watersheds (such as the Huma River) and southeastern regions (such as the Toudao River). The augmentation of wetland and forest coverage has effectively mitigated peak runoff, especially during extreme rainfall events. Wetlands have manifested strong water regulation capabilities and alleviated the impact of floods. This study quantitatively discloses the complex response pattern of LUCC to runoff by introducing a multi-scale analysis approach, which furnishes a scientific basis for flood risk assessment, land use optimization, and water resource management, and demonstrates the potential for extensive application in other countries and regions with similar climatic and topographic conditions. Full article

Floods are one of the most devastating natural hazards that have intensified due to land use land cover (LULC) changes in recent years. Flood risk assessment is a crucial task for disaster management in flood-prone areas. In this study, we proposed a flood risk assessment framework that combines flood vulnerability, hazard, and damages under long-term LULC changes in the Tajan watershed, northern Iran. The research analyzed historical land use change trends and predicted changes up to 2040 by employing a Geographic Information System (GIS), remote sensing, and land change modeling. The flood vulnerability map was generated using the Random Forest model, incorporating historical data from 332 flooded locations and 12 geophysical and anthropogenic flood factors under LULC change scenarios. The potential flood damage costs in residential and agricultural areas, considering long-term LULC changes, were calculated using the HEC-RAS hydraulic model and a global damage function. The results revealed that unplanned urban growth, agricultural expansion, and deforestation near the river downstream amplify flood risk in 2040. High and very high flood vulnerability areas would increase by 43% in 2040 due to human activities and LULC changes. Estimated annual flood damage for agriculture and built-up areas was projected to surge from USD 162 million to USD 376 million and USD 91 million to USD 220 million, respectively, considering 2021 and 2040 land use change scenarios in the flood-prone region. This research highlights the importance of land use planning in mitigating flood-associated risks, both in the studied area and other flood-prone regions. Full article

The hydrological cycle is altered by climate change and human activities, amplifying extreme precipitation and heightening the flood risk regionally and globally. It is imperative to explore the future possible alterations in flood risk at the regional scale. Focusing on the Hanjiang river basin (HRB), this study develops a framework for establishing a scientific assessment of spatio-temporal dynamics of future flood risks under multiple future scenarios. In this framework, a GCMs statistical downscaling method based on machine learning is used to project future precipitation, the PLUS model is used to project future land use, the digitwining watershed model (DWM) is used to project future runoff, and the entropy weight method is used to calculate risk. Six extreme precipitation indices are calculated to project the spatio-temporal patterns of future precipitation extremes in the HRB. The results of this study show that the intensity (Rx1day, Rx5day, PRCPTOT, SDII), frequency (R20m), and duration (CWD) of future precipitation extremes will be consistently increasing over the HRB during the 21st century. The high values of extreme precipitation indices in the HRB are primarily located in the southeast and southwest. The future annual average runoff in the upper HRB during the near-term (2023–2042) and mid-term (2043–2062) is projected to decrease in comparison to the baseline period (1995–2014), with the exception of that during the mid-term under the SSP5-8.5 scenario. The high flood risk center in the future will be distributed in the southwestern region of the upper HRB. The proportions of areas with high and medium–high flood risk in the upper HRB will increase significantly. Under the SSP5-8.5 scenario, the area percentage with high flood risk during the future mid-term will reach 24.02%. The findings of this study will facilitate local governments in formulating effective strategic plans for future flood control management. Full article

Enhancing flood resilience has become crucial for watershed flood prevention. However, current methods for quantifying resilience often exhibit coarse spatiotemporal granularity, leading to insufficient precision in watershed resilience assessments and hindering the accurate implementation of resilience enhancement measures. This study proposes a watershed flood resilience assessment method based on a system performance curve that considers thresholds of inundation depth and duration. A nested one- and two-dimensional coupled hydrodynamic model, spanning two spatial scales, was utilized to simulate flood processes in plain river network areas with detailed and complex hydraulic connections. The proposed framework was applied to the Hangjiahu area (Taihu Basin, China). The results indicated that the overall trend of resilience curves across different underlying surfaces initially decreased and then increase, with a significant decline observed within 20–50 h. The resilience of paddy fields and forests was the highest, while that of drylands and grasslands was the lowest, but the former had less recovery ability than the latter. The resilience of urban systems sharply declined within the first 40 h and showed no signs of recovery, with the curve remaining at a low level. In some regions, the flood tolerance depth and duration for all land use types exceeded the upper threshold. The resilience of the western part of the Hangjiahu area was higher than that of other regions, whereas the resilience of the southern region was lower compared to the northern region. The terrain and tolerance thresholds of inundation depth were the main factors affecting watershed flood resilience. The findings of this study provide a basis for a deeper understanding of the spatiotemporal evolution patterns of flood resilience and for precisely guiding the implementation and management of flood resilience enhancement projects in the watershed. Full article

Soil erosion is a global environmental problem, and soil conservation is the prevention of soil loss from erosion. The Ten Kongduis (kongdui is the translation of “short-term flood gullies” in Mongolian) are ten tributaries in the upper Inner Mongolia section of the Yellow River Basin. The study of the spatial and temporal variability in soil conservation in the Ten Kongduis is of extraordinary scientific significance both in terms of the discipline and for the ecological and environmental management of the region. With the InVEST model, the characteristics of the spatial and temporal variations in soil conservation service in the Ten Kongduis since 2000 and how rainfall and land use have influenced soil conservation were analyzed. The results show that both avoided erosion and avoided export varied considerably between years. The minimum values of avoided erosion and avoided export were both in 2015, with values of 17.59 × 10⁶ t and 0.92 × 10⁶ t, respectively. The maximum value of avoided erosion was 57.03 × 10⁶ t in 2020 and that of avoided export was 4.08 × 10⁶ t in 2000. Spatially, avoided export was primarily found in the upper reaches of the east–central portion of the study area, and avoided erosion, with values of >40 t·(ha·yr)⁻¹, was in the upper east–central portion of the study area, followed by the upper west–central portion. The difference between upstream and downstream was larger in the western part of the study area. The effect of rainfall was dominant and positive in both avoided erosion and avoided export. The relationships between the rain erosivity factor and the values of avoided erosion and avoided export were significantly positive. Where more erosion occurs, more erosion is retained. Soil that has been eroded away from slopes under vegetation or other water conservation measures may not necessarily be transported to the stream channel in the current year. These conclusions will help us to have a clearer understanding of where sediments are generated and transported and provide a scientific basis for soil and water conservation and ecosystem safety management of watersheds. Full article

Worldwide, the increase in impervious surfaces due to urbanization has led to significant water cycle issues such as groundwater depletion, urban heat islands, and flooding. To address these challenges, Low-Impact Development (LID) techniques are increasingly being applied in stormwater management. This study focuses on Ulsan, designated as a water cycle model city in South Korea, with a particular emphasis on the highly urbanized Okgyo drainage watershed. Using the Stormwater Management Model (SWMM) version 5.1, long-term runoff simulations were conducted to evaluate the effects of LID implementation on water cycle change rates and recovery rates. The model incorporates detailed hydrological and hydraulic parameters, including inflow, runoff, infiltration, and evapotranspiration for six subcatchments within the watershed. The SWMM was calibrated and validated using 30 years of historical rainfall data (1987–2016) from the Ulsan weather station. Calibration and validation processes used the NRCS-CN (Curve Number) method to ensure accuracy in simulating runoff patterns and water balance. The study specifically evaluated the effectiveness of two LID techniques: bioretention and permeable pavements. Three scenarios were modeled: bioretention applied to 5% of the area, permeable pavements applied to 5% of the area, and a combined application of both techniques. The results showed that the combined scenario provided the best outcome, with a 7.80% reduction in surface runoff and a 14.56% improvement in water cycle health. The LID application scenario confirmed the potential to achieve the water cycle management target of handling 25.5 mm of rainfall. These findings demonstrate that the introduction of LID techniques in public spaces can significantly enhance water management. This research provides insights into effective water cycle management methods tailored to specific urban land uses, laying a foundation for future urban planning and sustainable development. Full article

Extreme flood events present a significant challenge for operators and managers of large drinking water reservoirs. Detailed flood response analysis can predict the hydrology response of a reservoir to changing climate conditions and can aid in managing the reservoir in anticipation of extreme events. Herein, the Soil and Water Assessment Tool (SWAT), a watershed model, was used in conjunction with a reservoir management model, the Operational Analysis and Simulation of Integrated Systems (OASIS) model, to evaluate extreme flood events across a set of initial reservoir storage capacities across various CMIP6 climate scenarios. The SWAT model was calibrated and validated with PRISM climate data in conjunction with land and soil cover data and multi-site gauged stream discharges. The validated model demonstrated satisfactory performance (NSE = 0.55 and R² = 0.56) for total reservoir inflow. The resulting inflow values from SWAT were utilized to set up a calibrated/validated OASIS model (NSE = 0.55 and R² = 0.68). OASIS was then used to assess alternative operating rules for the reservoir under varying climate scenarios (RCP4.5 and RCP8.5) and extreme events (synthetic hurricanes). Focusing on a major reservoir in the Northeastern United States, the analysis of the reservoir response was based on (1) reservoir volume–elevation curve, (2) daily reservoir inflow, (3) daily precipitation, (4) spillway flow, and (5) reservoir evaporation. Projected future scenarios indicate a >20% increase in precipitation in April compared to historical records, coupled with likely reduced runoff from November to March. With extreme conditions most likely in the month of April, RCP4.5 and RCP8.5 projections suggest that most scenarios result in a 10–15% increase in the mean of 3D30Y runoff volumes, and a 150% increase under the most extreme conditions. For 7D30Y runoff volumes in April, the RCP4.5 and RCP8.5 analyses reveal an increased likelihood of the reservoir elevation reaching overspill flow levels during the latter half of the simulation period (2020 to 2080). Our findings indicate that simulations with SWAT coupled with OASIS can assist reservoir managers in regulating water levels in anticipation of extreme precipitation events. Full article