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The Atlantic Forest biome has lost a significant portion of its natural habitat and little research has studied how deforestation impacts the biome's local water balance. The objective of this research is to understand how the hydrological cycle of the region is affected by the change in land use. For this, the INLAND (Integrated Model of Surface Processes) surface model was calibrated and validated for the biome. Subsequently, changes in precipitation in the biome and the influence of deforestation on the surface components of the hydrological cycle were analyzed. To determine the influence of deforestation on the surface components of the hydrological cycle, two scenarios were simulated and compared, a deforestation scenario and a pasture scenario. The results showed that the total runoff in the deforestation scenario between 1951–1960 was, on average, 16.82% lower than the values found from 1971 to 1980. The use of modeling also made it possible to estimate the behavior of the difference between evapotranspiration and total runoff simulated with the occurrence of deforestation and with the area preserved in its entirety. It was observed that the biome has a certain resilience to deforestation up to a particular point, after which evapotranspiration decreases and the total runoff increases. [ABSTRACT FROM AUTHOR]

Central Europe and other parts of the world have experienced numerous extreme floods and prolonged periods of very low water discharges. With the increasing length and availability of hydrological data time series, it is now possible to analyse a larger volume of data. This paper presents long-term of changes in seasonal and maximum discharges. This paper aims to comprehensively assess the hydrological regime changes of Slovak rivers, using data from 26 gauging stations based on 90 years of observation. The study's first part explores monthly flow changes within each year for selected Slovak rivers. The second part identifies changes in the maximum daily discharges, their long-term trends, and their occurrences. Additionally, we have compared the variability of the hydrological regime of the Slovak rivers with the variability of the hydrological regime of selected gauging stations on the Danube River and its tributaries, such as the Drava, Sajó, and Tisa rivers, to understand broader regional patterns. The findings show that the rivers selected exhibit relatively high intra-annual runoff variability, with various changes in the runoff regime curve based on the long-term monthly Pardé coefficient. For the Slovak region, maximum annual runoff variability is observed in the Krupinica and Plašťovce rivers (reaching a maximum of 12.1 during the period 1930–1960), while minimum annual runoff variability is observed in the Biely Váh River (2.205 for the period 1930–1960). The long-term trend analysis of the Burn index time series for maximum daily discharges over the entire period from 1930/31 to 2019/20, as well as the significance of trends during the summer-autumn and winter-spring seasons, shows that stations exhibited decreasing, stable, or increasing trends. The most significant increasing trend was observed at sixteen of the stations analyzed: at seventeen stations during the summer-autumn season and at nine stations during the winter-spring season over the period from 1930/31 to 2019/20. [ABSTRACT FROM AUTHOR]

Estimates of precipitation, evaporation, river runoff, potential evaporation, and components of basin water reserves were obtained for the territories of Crimea and/or several its river basins. The period of 2014–2021 was characterized by higher aridity than 2001–2013, as can be seen from a decrease in precipitation and river runoff and an increase in the evaporation depth. The balance of the channel flow tends to decrease from the upper parts of the basin to its lower parts. The only exception is the Belbek River basin, where runoff losses are concentrated in the middle part of the drainage area. The analysis of changes of the measured and climatic runoff over the two periods showed an increase in runoff losses not associated with evaporation in many mountain and piedmont areas, which is likely due to a decrease in groundwater inflow and an increase in water intake. It is possible that in the lowland parts of the catchment areas of the Alma, Chernaya, Belbek, and Kacha, as well as the upper reaches of the Salgir, the river runoff increased due to groundwater extraction and the further release of wastewater into the rivers. The decrease in runoff in the Salgir basin by 0–40 mm can be partly explained by the closure of the North Crimean Canal in 2014. The decrease in groundwater reserves in Crimea over 2003–2020 was estimated at about 150 mm. [ABSTRACT FROM AUTHOR]

Water runoff components were evaluated for experimental river basins in the Mountain Crimea based on a two-tracer mixing model with three recharge sources. The identified recharge sources for river runoff in karstified catchments were found to include: epikarstic waters, soil-slope waters, and baseflow waters, circulating at the contact with underlying impermeable rocks. Epikarstic waters account for a considerable portion of the runoff of small rivers. Their proportions in the outlet sections increase during floods and steadily increase with an increase in water discharge, obeying logarithmic relationships. The proportions of baseflow water decrease compared with those of epikarstic waters. [ABSTRACT FROM AUTHOR]

The curve number (CN) equation is a semiempirical, event-based model commonly used to estimate rainfall runoff. This model was originally developed in the 1950s to estimate storm runoff from 24-h rainfall events from small catchments. The model consists of two parameters: (1) the curve number (CN), which represents soil type, land use, and land cover; and (2) the initial abstraction (Ia), i.e., the amount of rain that needs to accumulate before storm runoff begins. Despite its narrow-intended use, the CN model is widely used for many applications from engineering design to hydrologic modeling and uses parameter tables and guidelines developed in the mid-20th century. Changes in land management and hydrological science pose questions about the continued relevancy of the model in general and the tabulated parameters specifically. We used Catchment Attributes and Meteorology for Large-Sample Studies (CAMELS), a recently collated data set of watershed characteristics and performed regression analyses on the watershed attributes to determine whether the CN and Ia parameters can better fit a wider range of attributes than can the currently used tables. Our analyses focused on 5–35 year peak runoff events. We considered 333 small to medium watersheds distributed across the contiguous US and more than 40 watershed characteristics. We found that the CN model generally worked best if Ia was much smaller than traditionally assumed. Indeed, Ia=0 generally worked well. We also found that CN -values generally correlated well with climate (elevation, average precipitation) and soil permeability (sand fraction, saturated hydraulic conductivity). Our results suggest that the CN model can work relatively well for engineering purposes in ungauged watersheds and that the expanding stream of remotely sensed geographic data may allow for better CN -values than those from the current tables. We suggest that this study be expanded to include a wider range of watershed and storm characteristics. [ABSTRACT FROM AUTHOR]

In hydrological modeling, the accuracy of precipitation data and the reflection of the model's physical mechanisms are crucial for accurately describing hydrological processes. Identifying reliable data sources and exploring reasonable hydrological evolution mechanisms for hydrology and water resources research in high-altitude mountainous regions with sparse stations and limited data constitute a significant challenge and focus in the field of hydrology. This study focuses on the Yarkant River Basin in Xinjiang, which originates from glaciers and contains a substantial amount of meltwater runoff. A dynamic glacier melt module considering the synergistic effects of multiple meteorological factors was developed and integrated into the original Soil and Water Assessment Tool (SWAT) model. Four precipitation datasets (ERA5-land, MSWEP, CMA V2.0, and CHM-PRE) were selected to train the model, including remote sensing precipitation products and station-interpolated precipitation data. The applicability of the improved SWAT model and precipitation datasets in the source region of the Yarkant River was evaluated and analyzed using statistical indicators, hydrological characteristic values, and watershed runoff simulation effectiveness. The optimal dataset was further used to analyze glacier evolution characteristics in the basin. The results revealed the following: (1) The improved model fills the gap in glacier runoff simulation with respect to the original SWAT model, with the simulation results more closely aligning with the actual runoff variation patterns in the study area, better describing the meltwater runoff process. (2) CMA V2.0 precipitation data has the best applicability in the study area. This is specifically reflected in the rationality of the spatial and temporal distribution patterns of the inverted precipitation, the accuracy observed in capturing precipitation events and actual precipitation characteristics, the goodness of fit in driving hydrological models, and the observed precision in reflecting the composition of watershed runoff, all of which are superior to those pertaining to other precipitation products. (3) The glacier melt calculated using the improved SWAT model informed by CMA V2.0 shows that during the study period, the basin formed a pattern with a positive–negative glacier balance demarcation at 36.5° N, featuring melting at higher latitudes and accumulation at lower latitudes. The results of this study are of significant importance for hydrometeorological applications and hydrological and water resources research in this region. [ABSTRACT FROM AUTHOR]

Natural fluctuations in river flow are central to the ecosystem productivity of basins, yet significant alterations in daily flows pose threats to the integrity of the hydrological, ecological, and agricultural systems. In the dammed Lancang–Mekong River (hereafter LMR), the attribution of these large daily flow changes to upstream regions remains mechanistically unexamined, a factor blamed on challenges in estimating the time required for large daily shifts in upstream river flow to impact the downstream stations. Here, we address this with a newly developed subbasin modeling framework that integrates 3D hydrodynamic and response time models, together with a hydrological model with an embedded reservoir module. This integration allows us to estimate the time required between two hydrological stations and to distinguish between the contributions of subbasins and upstream regions to large daily river flow alterations. The findings revealed a power correlation between upstream river discharge and the time required to reach downstream stations. Significant fluctuations (greater than 1 m) in the river's daily flow were evident before the advent of the era of human activities, i.e., before 1992, with around 92 % of these fluctuations occurring during the wet season, particularly in June, July, and August. This pattern persisted throughout subsequent periods, including the growth period (1992–2009) and the mega-dam period (2010 to 2020), with minimal variation in the frequency of events. The Lancang basin contributed approximately 33 %–42 % of these large river fluctuations at the Chiang Saen station. We found that daily-scale water level and runoff might not fully capture dynamic river flow changes, as significant differences were observed between daily and subdaily river flow profiles. Subbasins significantly contributed to mainstream discharge, leading to substantial shifts in mainstream daily river flows. The outcomes and model derived from the subbasin approach have significant potential for managing river fluctuations and broader applicability beyond the specific basin studied. [ABSTRACT FROM AUTHOR]

The Topo River basin, located in the tropical region of Ecuador, is considered a little-known and well-preserved basin, with limited access conditions and scarce data that hinder its hydrological understanding. However, this gap can be addressed through this study, which evaluates morphometric and hydrometeorological factors, relating them to water storage in the Topo River basin and comparing these results with other watersheds. The aim is to identify the morphometric and hydrometeorological factors that control the variability in water storage. Firstly, a morphometric characterization was conducted. Then, a hydrometeorological characterization was carried out based on climatic data from a single station with less than two years of data, along with the calculation of the water balance. Finally, water storage in the Topo basin was compared with the main morphometric and hydrometeorological characteristics of other basins. The results showed that the Topo River basin stores 9.1 mm annually (0.20% of its precipitation), and this storage is the result of its high runoff coefficient. It was concluded that basins with lower precipitation, higher evapotranspiration ranges, larger areas, gentler slopes, smaller altitude ranges, longer rivers, and basins that are narrow and oval-shaped may have higher water storage capacity. [ABSTRACT FROM AUTHOR]

Riverine export of carbon (C) is an important part of the global C cycle; however, most riverine C budgets focus on individual forms of C and fail to comprehensively measure both organic and inorganic C species in concert. To address this knowledge gap, we conducted high frequency sampling of multiple C forms, including dissolved organic C (DOC), inorganic carbon (as alkalinity), particulate organic C (POC), coarse particulate organic C (CPOC), and invertebrate biomass C across the main run-off season in a predominantly rain-fed watershed in Southeast Alaska. Streamwater concentrations were used to model daily watershed C export from May through October. Concentration and modeled yield data indicated that DOC was the primary form of riverine C export (8708 kg C/km2), except during low flow periods when alkalinity (3125 kg C/km2) was the dominant form of C export. Relative to DOC and alkalinity, export of particulate organic C (POC: 992 kg C/km2; CPOC: 313 kg C/km2) and invertebrates (40 kg C/km2) was small, but these forms of organic matter could disproportionately impact downstream food webs because of their higher quality, assessed via C to nitrogen ratios. These seasonal and flow driven changes to C form and export likely provide subsidies to downstream and nearshore ecosystems such that predicted shifts in regional hydroclimate could substantially impact C transfer and incorporation into aquatic food webs. [ABSTRACT FROM AUTHOR]

Rising atmospheric CO2 is anticipated to influence global runoff through its radiative effect and physiological effect, thereby resulting in profound impacts on water availability and security. While existing literature has explored the two effects on global total runoff, there is still a lack of attention to changes in runoff components (surface and subsurface runoff). Here, based on idealized 1% yr−1 CO2 increase experiments and 14 Earth system models, we decouple the two effects on changes in runoff components and disentangle the contributions of three influencing factors, namely water supply, atmospheric water demand, and vegetation regulation, which are closely intertwined with the two effects. Global total runoff is expected to increase with rising CO2, and this increase mainly comes from subsurface runoff, leading to an elevated subsurface runoff ratio. Vegetation regulation emerges as the most important factor for the increase in subsurface runoff ratio, with the contribution of 49.3%, followed by water supply (41.7%) and atmospheric water demand (8.9%). Increased total runoff implies potentially more flood risk, while the increase in subsurface runoff ratio could decrease some of the risk. The results indicate the necessity of emphasizing changes in subsurface runoff under climate change. Plain Language Summary: Runoff components comprise surface runoff and subsurface runoff. Surface runoff reaches the stream quickly, and efficiently carries soil and nutrients. Subsurface runoff represents the watershed's slow response to precipitation events and is crucial for maintaining continuous river flow and water supply. Here, based on idealized 1% yr−1 CO2 increase experiments and 14 Earth system models, we explore the trend and influencing factors of runoff components with rising atmospheric CO2. Global surface and subsurface runoff are expected to increase, with subsurface runoff increasing faster than surface runoff. Vegetation regulation plays a crucial role in the increase of subsurface runoff ratio, which is of great significance in reducing the potential flood risk caused by the increase in global total runoff. Key Points: Subsurface runoff ratio is expected to increase with rising CO2Vegetation regulation is the most critical factor, contributing about half of the increaseWater supply contributes 41.7%, and atmospheric water demand contributes 8.9% to the increase in subsurface runoff ratio [ABSTRACT FROM AUTHOR]

Land use change, as a major driving factor of watershed hydrological process, has a significant influence on watershed hydrological change. In addition, a series of hydrological models, as important tools for simulating hydrological impacts, are widely employed in studying land use change. However, when employing hydrological model to analyse the hydrological impacts of land use changes, most previous studies focused on the evolution of historical land use change and lacked reasonable predictions of future land use. Therefore, it is necessary to extend such studies to future scenarios to cope with possible future hydrological variations in the basin. Given this, this paper making the Wuwei section of Shiyang River Basin as the study area, coupled the SWAT (Soil and Water Assessment Tool) model for hydrological simulation with the CA‐Markov (cellular automata‐Markov chain) model for future land use prediction to analyse the regional hydrological effects caused by historical and future land use changes. In addition, the general CA‐Markov model directly uses a system‐generated suitability atlas. In contrast, this study applied logistic regression and Multi‐criteria evaluation (MCE) methods to construct the suitability atlas, thereby establishing the Logistic‐CA‐Markov and MCE‐CA‐Markov models. Based on the model results, the main results are as follows: (1) The land use in study area is mainly grassland and barren, accounting for more than 80%. Additionally, forest is changing at the highest rate among all land use types. (2) In terms of the percentage of grassland and forest, the future land use predicted by MCE‐CA‐Markov (Multi‐criteria evaluation‐cellular automata‐Markov chain) has the largest forest and grassland coverage (57.78%), whereas the future land use predicted by Logistic CA‐Markov has the lowest (54.69%), indicating that the former pays more attention to the sustainable development of ecological environment. (3) The study area's R2 = 0.83, NSE = 0.79, PBIAS = −18.6%, and validation R2 = 0.81, NSE = 0.76, PBIAS = −17.8% demonstrate the favourable application of the SWAT model. (4) Based on simulated runoff results under historical and future land use scenarios, the amount of increasing grassland and forest coverage in the study area would eventually rise water yield (WYLD) by increasing lateral runoff (LATQ), increasing subsurface runoff (GWQ), and reducing surface runoff (SURQ). The study contributes to a better understanding of the impact of land use change on regional water resources and water balance, thus guiding regional water resources management and sustainable development. [ABSTRACT FROM AUTHOR]

The Arctic river basins, among the most sensitive regions to climate warming, are experiencing rapid temperature rise and permafrost thawing that profoundly affect their hydrological and hydrochemical systems. However, our understanding of chemical export from Arctic basins to oceans remains limited due to scarce data, particularly in permafrost-dominated regions. This study examines the spatiotemporal variations and seasonal dynamics of major ions (Na+, K+, Mg2+, Ca2+, Cl−, SO42−) and dissolved organic carbon (DOC) concentrations across three river basins with varying permafrost extents: the Severnaya Dvina (2006–2008, 2012–2014), the Pechora (2016–2019) and the Taz Rivers (2016–2020). All the data were sourced from published Chemical Geological researches and were taken from Mendeley and PANGAEA datasets. Our results showed that DOC concentrations ranged from 1.75 to 26.40 mg/L, with the Severnaya Dvina River exhibiting the highest levels of DOC concentrations, alongside significantly elevated ion concentrations compared to the other two basins. A positive correlation was observed between DOC concentrations and river discharge, with peaks during the spring flood and summer baseflow due to leaching processes. The Severnaya Dvina and Pechora Rivers exhibited the highest DOC values during the spring flood, reaching 26.40 mg/L and 8.07 mg/L, respectively. In contrast, the Taz River had the highest runoff during the spring flood season, but the DOC concentration reached its highest value of 11.69 mg/L in the summer. Specifically, a 1% increase in river discharge corresponded to a 1.25% rise in DOC concentrations in the Severnaya Dvina River and a 1.04% increase in the Pechora River, while there was no significant correlation between runoff and DOC concentrations in the Taz River. Major ion concentrations demonstrated a negative correlation with river discharge, remaining relatively high during winter low-flow period. A robust power-law relationship between river discharge and concentration of DOC and major ions was observed, with distinct variations across the three river basins depending on permafrost extent. The Pechora and Taz Rivers, characterized by extensive permafrost, exhibited increasing trends in river discharge and DOC concentrations, accompanied by decreasing major ion concentrations, whereas the non-permafrost-dominated Severnaya Dvina River basin showed the opposite pattern. The Taz River, with the most extensive permafrost, also displayed a delayed DOC peak and more complex seasonal ion concentration patterns. These findings highlight the importance of varying permafrost extents and their implications for water quality and environmental protection in these vulnerable regions. [ABSTRACT FROM AUTHOR]

Under the dual impacts of global climate change and human activities, how to accurately and quantitatively assess and identify changes in watershed runoff is crucial to the rational development and utilization of water resources. Different methods of identifying runoff change attribution are applicable to different environments. In this study, we used five different methods, including the double mass curve (DMC), the soil and water assessment tool (SWAT), and the three Budyko hypotheses based on Fu, Choudhury‒Yang, and Milly‒Zhang formulas to explore the impact of human activities and climate change on runoff change in the Jinghe River basin (JRB). The results show that annual runoff of the JRB decreased considerably, and human activities accounted for more than 90%. Specifically, the results of the SWAT model and the three Budyko hypotheses are highly consistent except for the DMC method, which is not recommended in basins with significant changes in factors other than precipitation. More importantly, the Budyko hypothesis based on the Milly‒Zhang formula uses the vegetation water utilization coefficient to consider the impact of vegetation change on runoff, which is most consistent with the simulation results of the SWAT model and is recommended for the attribution analysis of changes in the Loess Plateau represented by the JRB. [ABSTRACT FROM AUTHOR]

The Hydrologic Modeling System (HEC-HMS), designed to accurately simulate precipitation-runoff processes in various watershed types, was employed in our study to establish a model for a particular watershed. Consequently, we planned to create a rainfall-runoff model to investigate the specific characteristics of floods, assess some pre-diction models, and issue assumptions about their viability, which could be beneficial in establishing flood warning systems. The model was developed using daily precipitation data collected from different rain gauge stations in the Gilort watershed, located in southern Romania. The study employed the HEC-GeoHMS terrain processing tool, utilizing a digital elevation design to build a hydrological model. The statistical indicators used to evaluate the runoff mechanisms, specifically regression, coefficient of determination, correlation coefficient, index of agreement (Willmott index), and the root mean squared error (RMSE), showed a strong relationship between the simulated and recorded flow of the watershed. The leaking model was assessed using other statistical parameters, including the deviation of runoff volumes (Dv = 6.40%), Nash-Sutcliffe efficiency (NSE = 0.908), and Kling-Gupta efficiency (KGE = 0.901). These parameters confirmed that the simulated data closely matched the observed data, indicating an effective association, and were considered reliable indicators of the model's goodness of fit, ensuring its reliability and efficacy. [ABSTRACT FROM AUTHOR]

Glacier meltwater is an indispensable water supply for billions of people living in the catchments of major Asian rivers. However, the role of glaciers on river runoff regulation is seldom investigated due to the lack of annual glacier mass balance observation. In this study, we employed an albedo-based model with a daily land surface albedo dataset to derive the annual glacier mass balance over the Tuotuo River Basin (TRB). During 2000–2022, an annual glacier mass balance range of −0.89 ± 0.08 to 0.11 ± 0.11 m w.e. was estimated. By comparing with river runoff records from the hydrometric station, the contribution of glacier mass change to river runoff was calculated to be 0.00–31.14% for the studied period, with a mean value of 9.97%. Moreover, we found that the mean contribution in drought years is 20.07%, which is approximately five times that in wet years (4.30%) and twice that in average years (9.49%). Therefore, our results verify that mountain glaciers act as a significant buffer against drought in the TRB, at least during the 2000–2022 period. [ABSTRACT FROM AUTHOR]

The Zandvlei Estuary is the only functioning estuary along the False Bay coastline of Cape Town and is therefore of extreme local ecological importance. The most significant problems are eutrophication and siltation caused by the increased total inorganic nitrogen (TIN) and soluble ready phosphorus (SRP) levels due to urban development and the associated increased impervious surface area in the catchment that drains into it. In South Africa, stormwater drainage systems conventionally channel everything they collect into receiving water bodies without significant treatment. Sustainable drainage systems (SuDS) provide an alternative approach to managing stormwater runoff. They are designed to manage both stormwater quality and quantity while potentially improving biodiversity and amenity. This project modelled the potential improvement in the quality of the water entering Zandvlei Estuary resulting from the implementation of selected SuDS control measures in Zandvlei’s Diep River catchment using the software program, PCSWMM. SRP, TIN, total phosphorus (TP) and total suspended solids (TSS) were selected as pollutant indicators. Treatment trains that included a large, constructed wetland at the bottom of the catchment will likely provide the greatest improvements to the water quality entering Zandvlei – potentially reducing SRP, TIN, TP and TSS by approximately 59%, 53%, 53%, and 66%, respectively – as well as potentially reducing the runoff by 48%. [ABSTRACT FROM AUTHOR]

[Objective] This study examines the impact of climate change and human activities on baseflow variability across four representative watersheds within the Loess Plateau: the Wuding River, Kuye River, Yan River, and Tutai River. Methods］ Utilizing daily flow data from 1965 to 201 7 for the Wuding, Kuye, and Yan rivers, and from 1 983 to 2017 for the Tutai River, alongside multi-site meteorological data, we evaluated the applicability of nine baseflow separation methods and characterized baseflow variations. Contributions of climate change and human activities to baseflow changes were quantified using the elasticity coefficient method within the Budyko framework. Results］ The F4 digital filtering method exhibited superior performance in terms of stability, dispersion, and error metrics, making it the most suitable method for the typical watersheds of the Loess Plateau. Trends in annual baseflow depth. annual runoff depth. and annual baseflow index were consistent across the four watersheds. with multi-year average baseflow indices (BFT) of ().64, ().42, 0.28. and ().49, respectively. Significant decreasing trends (/><(). ()1) were observed in both annual baseflow depth and runoff depth. while the annual baseflow index showed increasing trends. The contributions of precipitation. potential evapotranspiration, and human activities to the changes in baseflow ranged from --56.72% to 33.92%, --0.81 % to 55.16% - and 10.92% to 1 ()4.37%, respectively. Conclusion] The findings underscore that human activities are the principal drivers influencing baseflow evolution in the Loess Plateau area» offering theoretical support for integrated water resource management in the region. [ABSTRACT FROM AUTHOR]

Modelling streamflow in snow-covered mountainous regions with complex hydrology and topography poses a significant challenge, particularly given the pronounced influence of temperature lapse rate (TLAPS) and precipitation lapse rate (PLAPS). The Present study area covers 54,990 km2 in the western Himalayas, including the Tibetan Plateau and the Indian portion of the USRB up to Bhakra Dam in Himachal Pradesh. In order to estimate the snowmelt and rainfall runoff contributions to the catchment, an integrated Soil and Water Assessment Tool (SWAT) model incorporates a Temperature Index with an Elevation Band approach. The uncertainty analysis of the SWAT model has been conducted using the Sequential Uncertainty Fitting algorithm (SUFI-2). Furthermore, machine-learning models such as Long Short-Term Memory (LSTM) neural networks and Random Forest (RF) are integrated with the SWAT model to enhance the accuracy of streamflow predictions resulting from snowmelt. The performance indices of a model for the monthly calibration period are R2 = 0.83, NSE = 0.82, P-BIAS = 2.3, P-factor = 0.82, and R-factor = 0.81. The corresponding values for the validation period are R^2 = 0.78, NSE = 0.77, P-BIAS = 5.7, P-factor = 0.72 and R-factor = 0.66. The results show that 63.08% of the Bhakra gauging station's annual streamflow has attributed to snow and glacier melt. The highest snow and glacier melt occur from May to August, while the minimum is observed from November to February. Regarding snowmelt forecasting, the LSTM model outperforms the RF model with an R2 value of 0.86 and 0.85 during training and testing, respectively. Additionally, sensitivity analysis highlights that soil and groundwater flow parameters, specifically SOL_K, SOL_AWC, and GWQMN, are the most sensitive parameters for streamflow modelling. The study confirms the effectiveness of SWAT for water resource planning and management in the mountainous USRB. [ABSTRACT FROM AUTHOR]

Te Currently, one of the major problems of industrial and urban societies is the occurrence of floods and the collection of urban runoff, which requires the calculation of the amount of runoff from urban watersheds and the use of advanced models.In this research, the flood control nodes of the drainage network in Khako (Faqhireh-Khizr) urban area of Hamedan were measured and evaluated using the SWMM model.First, the equivalent width parameters, the percentage of impervious areas, pond storage, the roughness coefficient of the areas within the range of permissible range changes, were calculated in the soil area, and then in order to simulate and calibrate the model in the SCS and Horton methods, in the conditions before and after calibration, the coefficient Nash-Sutcliffe efficiency was used.The results showed that the infiltration and runoff height of the project in SCS method are equal to 50.86 and 16.14 mm, respectively and indicates that the SCS method evaluates the values of infiltration and runoff for Hamedan urban watershed more accurately and has an acceptable efficiency.The results show that out of the total rainfall of 120 mm, 33 mm is related to infiltration losses and 87 mm is related to surface runoff, and the volume of flow is equal to 2.41 million cubic meters, of which 1.98 million cubic meters is related to Faqireh sub-basin and 0.43 million cubic meters is related to Khizr sub-region.According to the efficiency coefficient of NS, which is calculated for the peak flow rate of 0.66 and for the flood volume of 0.73, these numbers are acceptable.The results showed that the highest amount of project rainfall runoff with 1.28 million cubic meters is related to Faqirah sub-basin due to the physical development of Hamadan city in recent years in this subbasin and the lowest amount with 0.46 million cubic meters is related to Khizrkhako sub-basin that the reasons for the decrease in runoff production in the Khako urban watershed, we can point out the presence of natural cover, increased infiltration, and pond storage.The results of this research showed that residential uses have the largest share in the flood potential of the study area. [ABSTRACT FROM AUTHOR]

This study explored the impacts of various rainfall input types on short-term runoff simulations using the Cell2Flood model in the Waryong Reservoir Basin, South Korea. Six types of rainfall data were assessed: on-site gauge measurements, spatially interpolated data from 39 Automated Synoptic Observing System (ASOS) and 117 Automatic Weather System (AWS) stations using inverse distance weighting (IDW), and Hybrid Surface Rainfall (HSR) data from the Korea Meteorological Administration. The choice of rainfall input significantly affected model accuracy across the three rainfall events. The point-gauged ASOS (P-ASOS) data demonstrated the highest reliability in capturing the observed rainfall patterns, with Pearson's r values of up to 0.84, whereas the radar-derived HSR data had the lowest correlations (Pearson's r below 0.2), highlighting substantial discrepancies. For runoff simulation, the P-ASOS and ASOS-AWS combined interpolated dataset (R-AWS) achieved relatively accurate predictions, with P-ASOS and R-AWS exhibiting Normalized Peak Error (NPE) values of approximately 0.03 and Peak Time Error (PTE) within 20 min. In contrast, the HSR data produced large errors, with NPE up to 4.66 and PTE deviations exceeding 200 min, indicating poor temporal accuracy. Although input-specific calibration improved performance, significant errors persisted because of the inherent uncertainty of rainfall data. These findings underscore the importance of selecting and calibrating appropriate rainfall inputs to enhance the reliability of short-term flood modeling, particularly in ungauged and data-sparse basins. [ABSTRACT FROM AUTHOR]

This study investigates the hydrological dynamics of the Pativilca Basin in the Southern Hemisphere using the SWAT (Soil and Water Assessment Tool) model. Seventy-seven watersheds across a mountainous region were analyzed using elevation data, land cover, soil type, and gridded meteorological products (RAIN4PE and PISCO) for hydrological simulations. Watershed delineation, aided by a Digital Elevation Model, enabled the identification of critical drainage points and the definition of Hydrological Response Units (HRUs). The model calibration and validation, performed using the SWAT-CUP with the SUFI-2 algorithm, achieved Nash–Sutcliffe Efficiency (NSE) values of 0.69 and 0.72, respectively. Cluster analysis categorized the watersheds into six distinct groups with unique hydrological and climatic characteristics. The results showed significant spatial variability in the precipitation and temperature, with pronounced seasonality influencing the daily flow patterns. The higher-altitude watersheds exhibited greater soil water storage and more effective aquifer recharge, whereas the lower-altitude watersheds, despite receiving less precipitation, displayed higher flows due to runoff from the upstream areas. These findings emphasize the importance of incorporating seasonality and spatial variability into water resource planning in mountainous regions and demonstrate the SWAT model's effectiveness in predicting hydrological responses in the Pativilca Basin, laying the groundwork for future research in mountain hydrology. [ABSTRACT FROM AUTHOR]

The inland river basin in Hexi, Gansu Province, is extremely short of water resources. There are certain differences in the changes of mountain runoff between the central and western and eastern water systems in the basin. Studying the changes in mountain runoff and the contribution rates of different factors is of great significance for ensuring the sustainable development and utilization of regional water resources. Based on the data of mountain runoff and precipitation and temperature in the main runoff producing areas from 1956 to 2021, various trends and mutation tests, cumulative slope change rate methods, and combined with the characteristics of runoff supply, the changes in mountain runoff and their responses to changes in precipitation and temperature in the three major water systems were analyzed. The results show that: 1 the average annual mountain runoff of the Shiyang River system was 1.36 billion m³, showing a non-significant decreasing trend over the years and a non-significant increasing trend in precipitation, The significant increase in temperature leads to an increase in evaporation, resulting in a decrease in runoff; 2 The average annual runoff from the Heihe River system has increased from 3.062 billion m³ before the mutation point in 2006 to 3.56 billion m³ after the mutation point. The contribution rate of precipitation to runoff changes is 16.7%, and the temperature has significantly increased, enhancing the impact on runoff changes; 3 The average annual runoff from the Shule River system has increased from 1.422 billion m3 before the mutation point in 1998 to 17.93 m3 after the mutation point. The impact of precipitation and temperature on runoff changes is similar, with contribution rates of 30.4% and 30.2%, respectively. There are certain differences in run-off supply characteristics and climate conditions among the three major inland river systems in Hexi, resulting in inconsistent responses of runoff to different driving factors. [ABSTRACT FROM AUTHOR]

Accurate forecasting of mid to long-term runoff is essential for water resources management. However, the traditional model cannot predict well and the precision of runoff forecast needs to be further improved. Here, we proposed a novel data-driven model aimed at enhancing the performance of the Gated Recurrent Unit (GRU) through the integration of Robust Local Mean Decomposition (RLMD) and the Slime Mould Algorithm (SMA). The objective is to improve mid to long-term runoff prediction in three hydrographic stations: Heishiguan, Baimasi, and Longmenzhen, located within the Yiluo River Watershed in central China. The model leverages monthly runoff data spanning from 2007 to 2022 to achieve this objective. The results indicated that (1) the new data-driven model (RLMD -SMA-GRU) had the highest monthly runoff prediction accuracy. Both RLMD and SMA can improve the accuracy of the model (NSE = 0.9466). (2) The precision of the models in wet season outperformed in dry season. (3) The hydrological stations with large discharge and stable runoff sequence have better forecasting effect. The RLMD-SMA-GRU model has good applicability and can be applied to the monthly runoff forecast at watershed scale. [ABSTRACT FROM AUTHOR]

Severe fire on steep slopes increases stormwater runoff and the occurrence of runoff‐initiated debris flows. Predicting locations of debris flows and their downstream effects on trunk streams requires watershed‐scale high‐resolution topographic data. Intense precipitation in July and September 2013 following the June 2011 Las Conchas Fire in the Jemez Mountains, New Mexico, led to widespread debris flows in the watershed of Rito de los Frijoles. We differenced lidar Digital Elevation Models (DEMs) collected in 2010 and 2016 to map subwatersheds experiencing debris flows and changes in elevation of the trunk stream. Debris flow occurrence was well predicted by previous assessments of debris‐flow hazard; debris flows occurred in 7 of 9 sub‐basins where the debris‐flow hazard was above 60% for the 25‐year rainfall event, and in 0 of 21 basins where debris flow hazard was less than 60%. Debris flows resulted in fan deposition at the confluence with the trunk stream followed by transport during three documented floods. The bed of the 22 km trunk stream increased in elevation by a mean of 0.29 m, but the local change in thalweg elevation was controlled by inputs of water and sediment and longitudinal variation in gradient. Downstream of the mouths of tributaries with debris flows, the thalweg of the trunk stream rose as much as 2 m. Downstream of the mouths of tributaries without debris flows the thalweg of the main stem degraded by as much as 2 m, mobilizing sediment that was then deposited further downstream where the gradient of the trunk stream decreases. In conclusion, the transport of sediment generated by debris flows was predictably related to spatial variation in sediment supply, discharge and gradient. [ABSTRACT FROM AUTHOR]

The identification of the onset and retreat dates of the monsoon season is a crucial and intricate phenomenon, given its annual spatiotemporal variability. The monsoon season contributes significantly to rainfall, replenishing water sources and hydrological systems but causes hydrological extremes, especially for the high‐altitude watersheds in Southeast Asia. Global Circulation Model (GCM)‐Coupled Model Intercomparison Project Phase 6 (CMIP6)‐based rainfall and temperature data are helpful for adequately representing present and future climate scenarios. However, the usability of uncorrected GCM‐CMIP6 datasets needs to be assessed regionally. This study focuses on identifying the best‐suited GCM‐CMIP6 based on the monsoon onset (MO) and retreat (MR) dates along with other climatological temporal parameters. A numerical definition for MO and MR has been formulated to find the best‐suited GCM‐CMIP6 (i.e., CMCC‐ESM2). In this context, runoff simulation is carried out using the meteorological inputs of the monsoon onset‐retreat (MOR)‐based best‐suited GCM to evaluate its usability. A multi‐model simulation approach has been carried out for runoff estimation based on observed datasets to find a better‐suited hydrological model. The proposed overall methodology is tested in a hydrological extreme‐prone ungauged watershed (i.e., Ranikhola). CMCC‐ESM2 and SSP2‐4.5 has been identified as best‐suited SSP based on statistical evolution (R2 [0.693], NSE [0.662] and RSR [0.581]) for future daily runoff prediction. Future hydrological analysis shows that the average monsoon peak runoff magnitude will increase from the calibrated period (2015–2020) by 18.01% in the coming years (2021–2049). [ABSTRACT FROM AUTHOR]

The article discusses the importance of setting expectations for hydrologic model performance using an ensemble of simple benchmarks. It highlights the limitations of traditional metrics and the need for objective benchmarks to assess model performance. The study demonstrates that relying on the mean annual flow as a benchmark is insufficient, and an ensemble of simple benchmarks provides a more accurate context for model performance evaluation. The use of benchmark models helps in understanding regional differences in model predictability and provides a basis for comparing model performance against simpler models. [Extracted from the article]

Urbanization is known to increase the volume of stormwater runoff and peak flow rates, which leads to changes in the natural flow regime and increases the likelihood of flooding. Low-impact development (LID) practices seek to reduce runoff volume and peak flow and are generally considered to be a more sustainable solution for urban stormwater management. In this study, we present a systematic approach to address nuisance flooding issues in small cities and communities. As an application, the effectiveness of two LID practices, rain barrels and permeable pavements, were explored in mitigating the urban flooding problem of a highly urbanized small coastal watershed in Alabama, USA. The EPA Stormwater Management Model (SWMM) was first calibrated for water depth using data collected at multiple sites within the watershed during the 2014–2015 period. The calibrated model was then used to first identify the areas prone to flooding using design storms with 1, 2, 5-, 10-, 50-, and 100-year return periods. Floodplain maps were generated for those design storms with HEC-RAS. Next, LID options upstream of those flood-prone areas were assessed to potentially minimize the flooding risks. The results indicate that LID controls can have considerable benefits for stormwater management by reducing runoff volume (1–24%), peak flow rates (18–25%), and water depth (5–15%), potentially returning watersheds to their natural flow regimes, thereby minimizing the flooding risk in urbanized areas. However, the effectiveness of LIDs, especially for the runoff volume, quickly diminishes as the return periods of the storms increase. Rain barrels were identified as the most economical and effective LID within the drainage system. [ABSTRACT FROM AUTHOR]

Quantifying suspended sediment concentration‐runoff (SSC‐Q) hysteresis can help to understand the source and transport mechanism of sediment. Due to the unique lithology, shallow soil, high infiltration capacity, complex geomorphology and heterogeneous landscape of karst watersheds in southwestern China, SSC‐Q hysteresis patterns remain unclear in this region. In the present study, the hysteresis index (HI) was used to quantify the SSC‐Q hysteresis pattern. The effects of rainfall and runoff on the HI were also evaluated from 2014 to 2019 in the Mahuangtian (2.26 km2) and Muzhaihe (0.09 km2) karst watersheds. The results showed that the clockwise loops accounted for more than 60% of the total hysteresis patterns in the two karst watersheds. In contrast, the counter‐clockwise and figure‐eight loops occupied no more than 30% and 10% of the total hysteresis patterns, respectively. These differences in the hysteresis patterns probably resulted from the spatial distribution of sediment sources and hydrological connectivity. The HI was significantly affected by the maximum discharge in the Mahuangtian watershed (P < 0.05) and by the flashiness index in the Muzhaihe watershed. This may be attributed to their different 3D hydrogeological structure, lithology and watershed size. This study can facilitate a better understanding of suspended sediment dynamics and provide important guidance for accurately implementing soil and water conservation strategies in karst areas. [ABSTRACT FROM AUTHOR]

The Thoubal river catchment (TRB) and Iril river catchment (IRB), which are two major adjoining subbasins of the Manipur river basin in India, were selected for this study. A GIS-based semi-distributed hydrological model soil and water assessment tool (SWAT) was used to derive the hydroclimatic parameters such as surface run-off, evapotranspiration. The present study aims to calibrate and validate the SWAT model using streamflow and satellite soil moisture data, as well as to examine the hydroclimatological responses in the two adjacent basins, and compare the relative changes in treating the Iril-Thoubal river basin jointly and as two separate entities. The model was calibrated and validated using the SUFI-2 tool. During calibration and validation, both IRB and TRB showed good model performance. This study shows that in a poorly gauged river basin with scarce data, remotely sensed soil moisture data may be effectively applied for the calibration and validation of hydrological models. The novel aspect of this study is the efficient calibration and validation of a hydroclimatic model for subtropical river sub-basins with limited hydrological ground data reinforced with open-source satellite-derived soil moisture datasets. [ABSTRACT FROM AUTHOR]

The ENSO (El Niño-Southern Oscillation) cycles have a significant impact on runoff evolution in the Yangtze River basin, highlighting the importance of analyzing runoff patterns and teleconnection mechanisms. This study uses a Nonhomogeneous Hidden Markov Model (NHMM) to dynamically simulate sea surface temperature anomalies (SSTA) in the Pacific Ocean, identifying five distinct ENSO states and analyzing the associated runoff, precipitation, and circulation data. The results show that during strong El Niño events, moisture convergence and anticyclonic conditions in Eastern China lead to substantial moisture transport to the middle and lower reaches of the Yangtze River, causing anomalous rainfall and increased runoff. In contrast, during strong La Niña events, the southwest and northwest regions of the Yangtze River basin experience anomalous rainfall due to a significant moisture belt and cyclonic activity around 10°N. The vertical atmospheric velocity (Omega) and geopotential height (GPH) align with water vapor transport. This study enhances the accuracy of runoff forecasting and provides technical support for disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

The present study analyzed sensitivity of flow parameters using SWAT and effect of climate change on surface water resources, considering uncertainty with Monte Carlo. For this purpose, output of nine-model related to fifth-climate change-report during baseline period 1971–2000 was weighted. Using Monte Carlo, 100 samples of probabilistic distribution of basin temperature and rainfall were generated. LARS-WG model was used for downscaling, then temperature and precipitation were calculated under RCP2.6 and RCP8.5 for future periods 2040–2069 and 2070–2099. SWAT was calibrated using observational-data and the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) (NCEP CFSR) global climate datasets and sensitivity of parameters affecting flow was analyzed. Results showed that observed-data had better performance than NCEP CFSR. Finally, future runoff was calculated under RCP2.6 and RCP8.5 for 2040–2069 and 2070–2099. Results showed that average annual runoff decreased by 84, 80, 82 and 80%, for 2040–2069 (RCP2.6 and RCP8.5) and for 2070–2099 (RCP2.6 and RCP8.5) relative to baseline, respectively. [ABSTRACT FROM AUTHOR]

Snowmelt erosion and rainfall erosion are important components of soil erosion in Northeast China. Studying how snowmelt and rainfall affect runoff and sediment yield is essential to control soil erosion in this region. Based on the soil and water loss observation data in small watershed during snowmelt and rainfall periods, snowmelt and rainfall erosion processes were studied. The runoff–sediment relationship was analyzed. The results indicate that 13 snowmelt runoff events and 14 rainfall runoff events were recorded. During the snowmelt period, runoff depth (RD) and sediment yield (SY) exhibited a slow increase (early stage), rapid increase (middle stage), and then rapid decrease (late stage) trend. RD and SY in the middle stage were higher than those in the early and late stages. Moreover, during the rainfall period, soil erosion mainly occurred from July to August; during these two months, the rainfall and rainfall erosivity accounted for 66.0 and 91.1% of the total rainfall and rainfall erosivity, respectively; and the RD and SY in this period accounted for 88.4 and 89.8% of total amounts in the whole rainfall period, respectively. In addition, the contributions of snowmelt and rainfall to RD and SY were 18.6 and 81.4%, and 3.8 and 96.2%, respectively. Hysteresis analysis suggested that clockwise hysteresis loop was the dominant pattern, followed by eight-shaped anticlockwise loop, and complex anticlockwise loop. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Resources & Ecology is the property of Journal of Resources & Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The runoff estimation process is extremely complicated, nonlinear, and dynamic in nature, which depends on the meteorological and various physical features of the catchment area. Rainfall causes runoff, and the occurrence and quantity of runoff are determined by the features of the rainfall event, which is the most significant hydrological process. Water resource planners typically utilize hydrological modelling to simulate the hydrological response in a basin according to the precipitation. The objective of the study is to develop a rainfall runoff model for Purna River basin using HEC-HMS model. In this study, Digital elevation model was used to delineate the watershed and consider outlet at Mahuwa gauging site, also prepared a thematic map by using Arc-GIS (10.3). HECHMS 4.6.1 model is used to rainfall runoff process. The Green Ampt method was utilized in this research to account for loss. SCS unit hydrograph and Synder Unit hydrograph methods are compared and both methods used for accounting the transform method and best suitable method is being used for final simulation. After optimization of the model result shows that, in SCS unit hydrograph, coefficient of determination (R-squared) was 0.9680 for year 2007 and value of Nash-Sutcliffe efficiency (NSE) and Root mean squared standard deviation (RMSE std. dev.) at Mahuwa outlet were 0.928 and 0.3 respectively. Whereas, the performance of the model was evaluated by Synder unit hydrograph which gave R-squared value varies between 0.7 to 0.9. Regression analysis indicate that both the methods have shown the good performance in predicting the runoff events in the study area based on the rainfall events. However, performance of the SCS unit hydrograph is better than Synder unit hydrograph. Thus, SCS unit hydrograph can be applied for the accurate prediction of the runoff. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of South-Central Minzu University (Natural Science Edition) is the property of Journal of South-Central Minzu University (Natural Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Significant advancements in satellite‐based precipitation retrieval algorithms have led to the development of continuous, quasi‐global precipitation products, offering unique opportunities for hydrometeorological and climate research. In this context, six satellite‐based precipitation products (SPPs), including CHIRPS, CMORPH, GSMaP, IMERG, MSWEP, and PERSIANN, were thoroughly investigated for their application in hydrological simulations over the Wardha River basin in India. The observed gridded precipitation product developed by India Meteorological Department (IMD) has been used as reference data to evaluate the performance of SPPs. Hydrological variables such as runoff, soil moisture (SM) and evapotranspiration (ET) were simulated using the Variable Infiltration Capacity model. The performances of SPPs are critically assessed using various statistical metrics, including Pearson's correlation coefficient (R), Klinga‐Gupta Efficiency (KGE), Percent Bias (PBIAS), root mean square error (RMSE), and the RMSE to standard deviation ratio (RSR). The model‐simulated discharge was compared with streamflow observations at a single gauging site, while a spatially distributed comparison was conducted between simulated SM and ET and satellite‐based SM and ET. The IMD dataset consistently shows superior performance for discharge simulation at both daily and monthly scales, with KGE values of 0.85 and 0.91, respectively. Among SPPs, MSWEP and CHIRPS excel in simulating daily and monthly discharge, respectively. For ET simulation, CHIRPS outperforms IMD and other SPPs, achieving an overall KGE value of 0.37. In contrast, PERSIANN is the most effective for simulating SM compared to other precipitation products. [ABSTRACT FROM AUTHOR]

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Frequent soil erosion disasters in the middle reaches of the Yellow River (MRYR) have a profound effect on the sediment load of the river. This paper addresses the intertwined effects of human activities and climate change on river runoff and sediment load. Therefore, runoff and sediment loads from hydrological stations along the main and tributary rivers within the MRYR were used. The Mann–Kendall (M–K) trend test and the double mass curve analysis, among other analytical tools, were used to examine the erosion patterns of these rivers from 1950 to 2022, as well as the main factors driving these changes. The results showed that the runoff depth of the Yan River tended to decrease, and there was a significant decrease in the mainstream and nine other tributaries, with a significant decrease in the sediment transport modulus for both the mainstream and tributaries. In the main river, human activities contributed between 69.99% and 94.69% to the runoff and between 88.52% and 98.49% to the sediment load, while in the tributaries, the contribution of human activities was greater. The annual runoff and annual sediment load in the MRYR showed a decreasing trend, with a discernible impact of human activities. The results of this research are of great significance for erosion control and the restoration of the ecological balance in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

In this study, the impact of change in land use and land cover (LULC) on runoff estimation in the Kidangoor watershed was assessed using the SCS-CN technique. Recent flood-like natural disasters in Kerala are thought to be driven by changes in rainfall patterns and LULC. The accurate calculation of runoff from watersheds is urgently needed. In ArcGIS 10.5, the supervised classification approach is used to classify satellite images from 2000, 2011, 2013, and 2017. Similarly, the Inverse Distance Weighted (IDW) technique is used to produce spatial distribution maps of rainfall for each antecedent moisture condition (AMC). The runoff maps were generated by superimposing the distributed rainfall, LULC, and Hydrological Soil Group (HSG) maps. It was observed that the built-up area expanded by 168% between 2000 and 2017, whereas other classes decreased by 10-23%. However, compared to 2000, both with and without a change in LULC, runoff generation increased by just 31%, and 27% in 2017. The SCS-CN technique for runoff estimation indicates that the change in LULC in the Kidangoor watershed is insignificant. Thus, this study will help land use planners and decision-makers in limiting the potential damage from flooding when it comes to flood management techniques. [ABSTRACT FROM AUTHOR]

Wildfire disturbance propagation along fluvial networks remains poorly understood. We use incident, atmospheric, and water-quality data from the largest wildfire in New Mexico's history to quantify how this gigafire affected surface runoff processes and mobilized wildfire disturbances into fluvial networks after burning 1382 km2. Surface runoff post-fire increased compared to pre-fire conditions, and precipitation events that are frequently observed in the affected watershed (<2-year recurrence) and fell during the post-fire first rainy season resulted in uncorrelated, less frequently observed runoff events (10-year recurrence). Besides these shifts in runoff generation, the magnitude and fluctuation of daily water quality parameters and relevant ecosystem processes also shifted over multiple months, even at sites located >160 km downstream of the burn perimeter. Our findings emphasize the need to incorporate spatially resolved longitudinal sampling designs into wildfire water quality research and highlight the spatiotemporal co-dependency among atmospheric, terrestrial, and aquatic processes in defining the net outcome of wildfire disturbance propagation along impacted fluvial networks. This study quantifies how the largest wildfire in New Mexico's history altered runoff processes and generated water quality disturbances that propagated along hundreds of kilometers and over multiple months, affecting key aquatic ecosystem processes. [ABSTRACT FROM AUTHOR]

This study analyzed 61 years of hydrological data from the Minhe and Xiangtang Hydrological Stations (1956–2016) to examine hydrological changes and ecological flow assurance rates in the Huangshui River Basin, China. Using the Mann–Kendall trend test, IHA/RVA method, and ecological flow calculation methods, the study revealed the following results: (1) After 1994, increased human activity in the Datong River led to a measured runoff decrease compared to natural runoff. Although human activities in the Huangshui River's main stream were present before 1972, after 1972, these activities intensified, resulting in a more pronounced decrease in the measured runoff. (2) Ecological flow analysis indicated that the main stream of the Huangshui River and the Datong River have ecological flow assurance rates of 100% for all but a few months, where the rates are 98%. The water volume is sufficiently abundant to meet ecological water demands. [ABSTRACT FROM AUTHOR]

Debris flow mobility can vary during propagation due to changes in flow volume and bulk flow behavior resulting from the absorption of water from runoff. This study aims to investigate the effect of runoff on debris flow propagation by presenting an integrated model that considers the processes of rainfall, vegetation interception, soil infiltration, runoff generation, and debris flow propagation. Specifically, the study adopts an elevation-based empirical formula to evaluate the spatial distribution of rainfall and introduces a parameter for water absorption rate into the depth-averaged two-layer model that is used for describing the dynamics of runoff and debris flow. Through alternative simulations of the 2020 debris flow in the Meilong catchment, the study illustrates the significant effects of water absorption on debris flow propagation. The results indicate that as the water absorption rate of the debris mass increases, debris flow mobility also increases, since more mass and energy are transferred from runoff to debris flow. In addition, the spatial and temporal patterns of rainfall intensity can modify the propagation velocity of debris flow by influencing runoff dynamics. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the change characteristics and driving factors of runoff and sediment load in the Weihe River Basin, and to provide scientific basis for water resource management and ecological environment construction in the Weihe River Basin. [Methods] Based on the measured precipitation, runoff and sediment load data of Huaxian and Zhuangtou hydrological stations in the Weihe River Basin from 1957 to 2019, the trend and the change-point year of annual precipitation, runoff and sediment load were analyzed by modern mathematical statistical. The contribution rates of runoff and sediment load reduction in Weihe River Basin were calculated. The main influencing factors of human activities on runoff and sediment load changes in the Weihe River were discussed. [Results] There was a strong decreasing trend in runoff and sediment load of Weihe River Basin from 1957 to 2019 (p<0.01), and the annual precipitation fluctuated randomly and had no obvious change trend. Abrupt year analyses showed that more rapid declines for runoff began in 1990 (p<0.01), and sediment load began in 1996 (p<0.01). The contribution rates of precipitation to the reduction of runoff and sediment load were 19% and 17%, respectively. The contribution rates of runoff and sediment load reduction caused by human activities were 81% and 83%, respectively. [Conclusion] Human activities are the main reason for the significant reduction of runoff and sediment load in the Weihe River Basin. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to analyze the runoff and sediment under different land use types and slopes in the loess hilly area of western Henan, and to provide scientific basis for quantitative evaluation of soil erosion and comprehensive prevention of soil erosion. [Methods] Based on the observation data of 12 runoff plots from 2011 to 2020 at the monitoring site of soil and water conservation in Hugou small watershed, Songxian County, Henan Province, the pattern of runoff and sediment under different land use was revealed. Correlation analysis was used to detect the relationship between rainfall characteristics, slope, land use, runoff and sediment yield. [Results (1) Compared with bare land plot, grassland plot had the greatest effect on runoff and sediment reduction. The average annual runoff reduction effect of grassland was 78.6%~85.9%, and the maximum sediment reduction effect was 100%. The runoff reduction effect of forestland was 32.9%~51.3%, and the sediment reduction effect was 55.3%~78.9%. (2) Runoff and sediment in each runoff plot and the slope were closely related. There was no significant difference between the runoff and sediment on the slopes of 10° and 15°, however, it increased significantly on the slope of 25°. In addition, with the increase of slope gradient, the soil and water conservation effect of forestland and grassland also reduced. (3) The correlation between runoff depth and maximum 30-minute rainfall intensity (130) and soil loss and rainfall erosivity were the most significant. [Conclusion] In areas where runoff and sediment localization observation is lacking in the loess hilly region of western Henan Province, rainfall process information can be used to estimate the runoff and soil loss under certain slope and vegetation conditions. [ABSTRACT FROM AUTHOR]

For water management and ecological security, it's essential for identifying the influence of human activities on the rainfall-runoff relationships. The univariate and bivariate approaches were used to examine evolution of the rainfall-runoff relationship in Minjiang River Basin and tributaries at different time scales. The former approach with integrated Trend Free Prewhitening Mann–Kendall (TFPW-MK) and three mutation methods, and the latter approach with double mass curve (DMC) where the break points were determined by three mutation methods reasonably and with copula, were applied based on rainfall and runoff data during 1960–2019. The influence of human activities including land use and reservoir construction on the rainfall-runoff relationship were analyzed. Results showed that: (1) The changes of rainfall-runoff relationship at different time scales were different. The runoff changes during non-flood seasons and the minimum month in most tributaries were more obvious than the rainfall, while the runoff over inter-annual and flood season were basically unchanged; (2) The intra-annual changes of rainfall-runoff relationship were mainly due to reservoir construction. The sudden step in the cumulative capacity of the large and medium reservoirs basically corresponded to change points of the double mass curve approach (DMC) in the non-flood season and the monthly minimum; The significant increase in runoff during low-flow period and the notable reduction in maximum monthly runoff in mainstream were due to the reservoir regulation; (3) The combination of univariate and bivariate approaches can distinguish the impact of climate change and human activities on rainfall-runoff relationship, and identify clearly the influence of human activities. [ABSTRACT FROM AUTHOR]

The Palopo City watershed could not accommodate the high discharge of rainfall that had fallen previously. The Green Open Space (GOS) had an ecological function by absorbing rainwater. Urban green open spaces absorbed surface flow water in the past, reducing the risk of flooding. In the past, this research measured the effectiveness of three green open spaces (Islamic Center, Pancasila Field, and Salubulo Field) in reducing flooding in Palopo City. We collected data on vegetation types, infiltration capacity, and runoff discharge. Data analysis involved the analysis of infiltration capacity (F), runoff discharge (Q), and green open space effectiveness. In the three green space locations, the following vegetation types were found: Katapang (Terminalia catappa), Palm (Dypsis lutescens), Trambesi (Samanea Saman), and Grass (Cyperus rotundus). The highest total infiltration capacity in the Salubulo Field Green Space resulted in 155 m³/hour (fast category). In the past, the most significant runoff discharge's total value was GOS Pancasila Field: 713.4 mm³/minute. The study concluded that the Salubulo Field Green Space had the highest infiltration capacity (160 m³/hour) and runoff discharge (69 mm³/minute), making it the most effective in reducing flooding in Palopo City in the past. This was > 1 (effectiveness criteria achieved), and the space was dominated by vegetation (trees and grasses). [ABSTRACT FROM AUTHOR]

Copyright of Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)