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The productivity of olive in the northwestern coastal zone of Egypt is significantly constrained by drought and low organic matter in the soil. This study addresses these challenges by exploring the synergistic effects of olive mill wastes (OMW) application and micro-catchment water harvesting techniques on soil properties, runoff, moisture storage, and rainwater harvesting efficiency. Field experiments were conducted over two winter seasons, employing different micro-catchment structures (semi-circular and triangular bunds) and OMW applications. The results revealed that the integration of semi-circular bunds with OMW application (T4) substantially increased rainwater harvesting efficiency by 67.7% and 46.4% in the first and second seasons, respectively. Additionally, T4 and T5 exhibited reduced runoff by 47.8% and 41.3% in the first season and 49.4% and 38.9% in the second season, respectively. T4 significantly enhanced soil organic matter, soil macronutrients (N, P, and K), and micronutrients (Fe, Mn, Zn, and Cu) compared to the control (T1). The study highlights the effectiveness of T4 in improving soil moisture, reducing soil erosion, and enhancing soil fertility. This integrated approach involving OMW application within a semi-circular bund as a water harvesting system proves to be a promising strategy for sustainable olive cultivation in arid conditions. [ABSTRACT FROM AUTHOR]

Flooding poses a severe global threat, necessitating advanced methodologies to assess and manage its risks effectively. This study introduces a novel approach that integrates Geographic Information System (GIS) with hydrologic-hydraulic modeling to evaluate the combined drivers of current and future flood risks. The method is applied to the development Bonita Bay in southwest Florida. It occurs in a region highly susceptible to flooding due to its low elevation and proximity to tidal waters. The innovative integration of GIS with hydrologic-hydraulic models enables detailed assessment and visualization of flood inundation areas under multiple flood drivers including design storms, land use changes, groundwater rise, and sea-level rise. This allows for the seamless simulation of complex flood interactions with only minor adjustments to the model for the identified drivers. The results indicate significant increases in initial water storage caused by sea and groundwater level rise and amplified storm runoff from land use changes. A 2% increase in flooded areas is projected with stronger design storms, and a 5% increase by 2,100 compared to 2024. This approach provides a robust framework for developing tailored flood mitigation strategies and can be adapted to various coastal regions globally. [ABSTRACT FROM AUTHOR]

Highway stormwater (HSW) runoff is among the environment's most important sources of microplastics. This study aimed to characterize via vibrational spectroscopy and quantify SMPs (small microplastics < 100 µm) in HSW runoff from a trafficked highway entering a facility equipped with a filtration system and in those flowing out to the receiving water body near agricultural activities. Samples of the inlet runoff (from the highway) and outlet runoff (the discharge into the environment) were collected in different periods to investigate potential seasonal and spatial differences. The sampling, methodology, and analysis were thoroughly carried out to quantify and simultaneously identify SMPs via Micro-FTIR to obtain a specific novel dataset to assess the environmental quality of highway pollution. A significant difference between inlet and outlet samples was reported; the highest abundance in inlet samples was 39813 ± 277 SMPs L.1 (SW10 IN; average length of 77 µm), while the highest one in outlet samples was 15173 ± 171 SMPs L−1 (SW10 OUT; SMPs' average length of 63 µm). Polyamide 6 (PA 6) and High-Density Polyethylene (HDPE) were predominant. Our results show that these HSW treatment plants, designed for managing regulated pollutants, can intercept SMPs, improving the quality of HSW runoff discharged into the environment. [ABSTRACT FROM AUTHOR]

Reliable hydrological simulations require accurate precipitation data. However, data uncertainties due to the indirect nature of satellite estimates can propagate through hydrological models and lead to simulation errors. This study assesses the accuracy of Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) products, comparing them directly with ground-based precipitation data and evaluating their performance in rainfall–runoff modelling across Great Britain. Three IMERG V06 products (IMERG-Early, IMERG-Late, and IMERG-Final) are examined. Utilizing the simple water balance model (SWBM), the analysis covers 250 basins, revealing that the SWBM performs well in over 50% of the basins. Runoff estimations show that European Observation (E-OBS) ground-based data yield the highest Nash-Sutcliffe efficiency (NSE) score (0.91), followed by IMERG-Final (0.85), IMERG-Late (0.82), and IMERG-Early (0.73). The findings underscore IMERG's utility in hydrological modelling for ungauged or poorly gauged basins. [ABSTRACT FROM AUTHOR]

The aim of this study was to identify anatomical and clinical factors associated with limb-based patency (LBP) loss, major adverse limb events (MALEs), and poor amputation-free survival (AFS) after an infrapopliteal arterial bypass (IAB) surgery according to the Global Limb Anatomic Staging System. A retrospective analysis of patients undergoing IAB surgery between January 2010 and December 2021 at a single institution was performed. Two-year AFS, freedom from LBP loss, and freedom from MALEs were assessed using the Kaplan–Meier method. Anatomical and clinical predictors were assessed using multivariate analysis. The total number of risk factors was used to calculate risk scores for subsequent categorization into low-, moderate-, and high-risk groups. IABs were performed on 103 patients. The rates of two-year freedom from LBP loss, freedom from MALEs, and AFS were 71.3%, 76.1%, and 77.0%, respectively. The multivariate analysis showed that poor run-off beyond the ankle and a bypass vein caliber of < 3 mm were significantly associated with LBP loss and MALEs. Moreover, end-stage renal disease, non-ambulatory status, and a body mass index of < 18.5 were significantly associated with poor AFS. The rates of freedom from LBP loss and MALEs and the AFS rate were significantly lower in the high-risk group than in the other two groups (12-month low-risk rates: 92.2%, 94.8%, and 94.4%, respectively; 12-month moderate-risk rates: 58.6%, 84.6%, and 78.3%, respectively; 12-month high-risk rates: 11.1%, 17.6%, and 56.2%, respectively; p < 0.001, p < 0.001, and p < 0.001, respectively). IAB is associated with poor clinical outcomes in terms of LBP, MALEs, and AFS in high-risk patients. Risk stratification based on these predictors is useful for long-term prognosis. [ABSTRACT FROM AUTHOR]

The present study assessed the heavy metal pollution in sediment samples collected from the Noyyal River basin (river and lake sediments) during the monsoon and summer seasons. The geo-accumulation index (Igeo) categorizes metals as extremely polluted during monsoon and heavily contaminated to extremely contaminated during summer. The enrichment factor (EF) of metals Mn during monsoon and Cd during summer indicates extremely severe enrichment (EF > 50) and Mo exhibited very high contamination (CF > 6) throughout the basin during monsoon. The average risk index of heavy metal in the basin followed the order Cd (164.15) > Ni (14.82) > Co (4.84) > Cr (2.55) > Cu (1.89) > Zn (1.38) > Mn (0.40) during monsoon and Cd (153.07) > Ni (7.96) > Cu (5.13) > Co (4.63) > Cr (1.89) > Zn (1.21) > Mn (0.3) during summer showing that the PERI of each element was minimal except for Cd. Adverse health-related effects are confirmed by the cumulative total hazard index (THI) for children with HQ ingestion and HI values >1 in all sample locations over both seasons. Principal component and cluster analysis show metals accumulate in sediments mainly through industrial wastewater discharge and also experience significant natural source weathering through rainfall runoff. This research emphasizes the need for enhanced wastewater treatment facilities in metropolitan areas situated along the Noyyal River to potentially reduce the release of heavy metals from both domestic and industrial sources. [ABSTRACT FROM AUTHOR]

Jeddah is the most important port city in the Kingdom of Saudi Arabia. The climate of Jeddah is mostly dry; however, events of intensive rainfall followed by urban flooding have been reported in recent history. These floods interrupt the logistics and lifelines of the city. In this study runoff analysis and Flash Flood management by the green roof low impact development (LID) control system, was performed using United States Environmental Protection Agency (EPA)'s Stormwater Management Model (SWMM). Six middle districts of Jeddah city had been selected and modeled in five sub-catchment areas. The local soil and geographic conditions were incorporated into the model. The effect of the soil-based, rooftop, LID system has been emphasized in the analysis. In flood simulations, 30–70% of the impervious area of each sub-catchment has been treated with LID. It has been observed that the LID application can significantly reduce the overall flood flow. Thus, simple but well-planned LID control systems can be effectively utilized for the flood management of heavily urbanized regions. [ABSTRACT FROM AUTHOR]

Dissolved organic matter (DOM) is a crucial quality indicator for water health. However, it remains unknown how organic–inorganic fertilization differently shifts the DOM chemodiversity in cropland‐impacted runoff, especially the roles of terrestrial nutrient stoichiometry. Here, a field experiment subjected to 7‐year history of four fertilization regimes, that is, unfertilized (CK), chemical fertilization (NPK), straw return (SR), and NPK + SR, was conducted to examine the quantity and chemodiversity of runoff DOM in tropical China. Moreover, the ecological relationships between runoff DOM properties and soil C:N:P stoichiometry were evaluated. Relative to the control treatment, the carbon content (DOC) of runoff DOM increased by 29.20% and 48.82% under SR and NPK + SR treatments, but remained unchanged in NPK treatment. Conversely, the DOM nitrogen content (TDN) only elevated in NPK treatment (262.58%). For DOM chemodiversity, SR treatment was rich in methyl carbon and protein‐like substances, but lacked fulvic‐/humic‐like compounds. NPK treatment increased the hydrophilic compounds like amino acids and polysaccharides, while reducing aromaticity. NPK + SR treatment enhanced DOM's aromaticity, molecular weight and humification due to the enrichment of quinone, ketone and fulvic‐like substances, possibly shaping an oligotrophic aquatic microbial community. Further study revealed that the occurrence of aromatic DOM was positively correlated with soil moisture content, TK (total potassium), total organic carbon and stoichiometric N:P ratio, indicating the contribution of terrestrial straw‐decomposed products. Inversely, the accumulation of hydrophilic substances (e.g., TDN) correlated positively with soil NO3‐N and C:P ratio, indicating the contribution of endogenous DOM. [ABSTRACT FROM AUTHOR]

Climate change scenarios have been used to evaluate future climate change impacts and develop adaptation measures to mitigate potential damage. This study investigated strategies to reduce nonpoint source loads in an agriculturally dominated watershed and adapt to climate change despite uncertainty. We also investigated strategies for adapting to future meteorological conditions characterized by uncertainty. We utilized the latest future climate change scenarios—shared socioeconomic pathways—and explored measures to reduce nonpoint source loads by implementing nonpoint pollution abatement facilities in a watershed model. The simulation results indicate that the future frequency of rainfall events may decrease based on observations and the types and features of rainfall events in the scenarios. However, the variability of runoff loads in the context of future climate scenarios may increase because of factors influencing surface runoff, including the amount and intensity of rainfall. Nonpoint source loads are expected to exhibit high uncertainty in the future. Finally, the optimal solution can be determined through a simulated evaluation of the cost–benefit of installing the abatement facilities, considering the abatement efficiency and maintenance period. Overall, implementing effective management practices is crucial for reducing nonpoint source loads resulting from agricultural activities while adapting to increasingly variable meteorological conditions. [ABSTRACT FROM AUTHOR]

Predicting flood events is complex due to uncertainties from limited gauge data, high data and computational demands of traditional physical models, and challenges in spatial and temporal scaling. This research innovatively uses only three remotely sensed and computed factors: rainfall, runoff and temperature. We also employ three deep learning models—Feedforward Neural Network (FNN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM)—along with a deep neural network ensemble (DNNE) using synthetic data to predict future flood probabilities, utilizing the Savitzky–Golay filter for smoothing. Using a hydrometeorological dataset from 1993–2022 for the Nile River basin, six flood predictors were derived. The FNN and LSTM models exhibited high accuracy and stable loss, indicating minimal overfitting, while the CNN showed slight overfitting. Performance metrics revealed that FNN achieved 99.63% accuracy and 0.999886 ROC AUC, CNN had 95.42% accuracy and 0.893218 ROC AUC, and LSTM excelled with 99.82% accuracy and 0.999967 ROC AUC. The DNNE outperformed individual models in reliability and consistency. Runoff and rainfall were the most influential predictors, while temperature had minimal impact. [ABSTRACT FROM AUTHOR]

Like many small island communities, the U.S. Virgin Islands (USVI), an unincorporated territory of the U.S., is naturally freshwater scarce. In recent decades, rapid land development in the USVI has increased water demand considerably, exerting extra pressure on freshwater resources. Freshwater quantity and quality data for the USVI are very scarce and scattered, which limits freshwater management capabilities. We draw attention to this information deficit and discuss its implications by reviewing the current state of knowledge of surface and groundwater quantity and quality for the USVI. Our review confirms that long‐term records of surface and groundwater quantity and quality are limited and unreliable. For example, streamflow was most recently monitored in 2006, and the most extensive surface water quality records are from the 1960s and 1980s. Since 2016, mean groundwater levels have been recorded daily, but only for three wells (one on each island of the USVI). Importantly, this lack of information threatens water security for the territory and limits our understanding of how development has impacted water quality and availability over time. This could be addressed using models, such as a groundwater recharge model, in combination with remote sensing and updated field data (i.e., streamflow, groundwater, and ecohydrological characterizations of land use change). [ABSTRACT FROM AUTHOR]

The partial detonation of munitions used in military exercises leaves behind energetic particles on the surface of soil. Energetic particles deposited by incomplete detonations can then dissolve and be transported by overland flow and potentially contaminate ground and surface waters. The objective of this study was to evaluate the mechanisms of transport of Composition B, a formulation that includes TNT (2,4,6-trinitrotoluene) and RDX (hexahydro-1,3,5- trinitro-1,3,5-triazine) during overland flow. The transport of Composition B was examined using a rill flume with three flow rates (165-, 265-, and 300-mL min-1) and four energetic particle sizes (4.75--9.51 mm, 2.83--4.75 mm, 2--2.83 mm, and <2 mm). After each erosion simulation, energetic particles remaining on the soil surface were measured along with energetics dissolved in runoff, in suspended sediment, and in infiltration. Smaller particle sizes led to greater transport in both solution and sediment. The properties of the energetic compounds also influenced transport. More TNT was transported in runoff than RDX, likely due to TNT's higher solubility and dissolution rates, however, overall, dissolved energetics in runoff and infiltration accounted for very little of the total transport. Most transport of Composition B was the result of the physical movement of energetic particles and flakes by erosion forces. This study's results allow for improved prediction of Composition B transport during overland flow. [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]

ABSTRACT Accurate runoff projections are vital for developing climate adaptation strategies, yet significant uncertainties persist. The commonly employed approaches to constrain these uncertainties rely on the stationarity of climate biases and runoff sensitivity, which may not hold for climate‐sensitive regions (e.g., semi‐arid regions). This study investigates the validity of the stationarity assumption across 29 CMIP6 models, encompassing diverse climate biases (Dry Warm, Wet Warm, Dry Cold, and Wet Cold), utilising a semi‐arid region in central India as a testbed. The implications of this assumption on runoff projection uncertainties were comprehensively assessed across the runoff modelling chain for three time periods (the 2030s, 2060s and 2090s) based on the Soil and Water Assessment Tool (SWAT) simulations. The results highlight the non‐stationary nature of climate biases and runoff sensitivity under future scenarios, challenging the widespread applicability of common uncertainty‐constraining approaches. Moreover, the impact of non‐stationarity on runoff projection uncertainty was found to be strongly influenced by the choice of GCMs, preprocessing methods and climate change scenarios. In the 2030s, GCMs dominate runoff uncertainty, with dry models exhibiting ~10%–15% higher uncertainty compared to warm models, which is further amplified when interacting with warm biases. However, from the mid‐century onwards, the bias‐adjustment approaches and climate change scenarios significantly shape runoff projection uncertainties under non‐stationary conditions. These findings emphasise the potential of climate bias and runoff sensitivity‐based GCM selection for reducing runoff uncertainty in near‐future assessment (2030s). For mid‐term and long‐term runoff projections, addressing diverse climate biases through bias‐adjustment approaches is more viable. This study offers critical insights to prioritise the development of a non‐stationarity‐based approach for reliable runoff projections in climate‐sensitive regions. [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]

SUMMARY The circadian clock organizes physiological processes in plants to occur at specific times of the day, optimizing efficient use of resources. Nitrate is a crucial inorganic nitrogen source for agricultural systems to sustain crop productivity. However, because nitrate fertilization has a negative impact on the environment, it is important to carefully manage nitrate levels. Understanding crop biological rhythms can lead to more ecologically friendly agricultural practices. Gating responses through the circadian clock could be a strategy to enhance root nitrate uptake and to limit nitrate runoff. In Arabidopsis, the NITRATE TRANSPORTER 2.1 (NRT2.1) gene encodes a key component of the high‐affinity nitrate transporter system. Our study reveals that NRT2.1 exhibits a rhythmic expression pattern, with daytime increases and nighttime decreases. The NRT2.1 promoter activity remains rhythmic under constant light, indicating a circadian regulation. The clock‐associated transcription factor LUX ARRHYTHMO (LUX) binds to the NRT2.1 promoter in vivo. Loss‐of‐function of LUX leads to increased NRT2.1 transcript levels and root nitrate uptake at dusk. This supports LUX acting as a transcriptional repressor and modulating NRT2.1 expression in a time‐dependent manner. Furthermore, applying nitrate at different times of the day results in varying magnitudes of the transcriptional response in nitrate‐regulated genes. We also demonstrate that a defect in the high‐affinity nitrate transport system feeds back to the central oscillator by modifying the LUX promoter activity. In conclusion, this study uncovers a molecular pathway connecting the root nitrate uptake and circadian clock, with potential agro‐chronobiological applications. [ABSTRACT FROM AUTHOR]

Fluvial sediment dynamics in mountain rivers are changing rapidly in a degrading cryosphere, raising the potential for erosive rainfall and runoff and detrimental effects on downstream areas. Hence, we need to understand better what characterises and drives episodic pulses of water and suspended solids in rivers. Here, we infer different types of such sediment-discharge events from 959 automatically detected events based on 16 metrics derived from 15 min time series of streamflow and suspended sediment concentrations from Vent–Rofental in the high Ötztal Alps, Austria. We use principal component analysis to extract uncorrelated event characteristics and cluster event types with a Gaussian mixture model. We interpret the thus inferred event types with catchment metrics describing antecedent conditions, hydrometeorological forcing, and fraction of catchment area with freezing temperatures and snow cover. We find event magnitude, hysteresis, and event shape complexity to be the main factors characterising the overall event regime. The most important characteristics distinguishing the event types are suspended sediment and streamflow magnitude and complexity of the hydro- and sedigraphs. Sediment-discharge hysteresis is less relevant for discerning event types. We derive four event types that we attribute to (1) compound rainfall–melt extremes, (2) glacier and seasonal snowmelt, (3) freeze–thaw-modulated snowmelt and precipitation events, and (4) late-season glacier melt. Glacier and snowmelt events driven by warm conditions and high insolation were the most frequent and contributed some 40 % to annual suspended sediment yield on average; compound rainfall–melt extremes were the rarest but contributed the second-highest proportion (26 %). Our approach represents a reproducible method for objectively estimating the variety of event-scale suspended sediment transport conditions in mountain rivers, which can provide insights into the contribution of different drivers to annual sediment yields in current and future regimes. Our findings highlight the importance of both meltwater and rainfall–runoff as drivers of high-magnitude suspended sediment fluxes in mountain rivers. [ABSTRACT FROM AUTHOR]

The assessment of trends in hydroclimatic characteristics averaged over the watershed area and changes in the fields of the hydrological cycle components in the 21st century in a large river basin of the Nizhnekamskoye Reservoir was carried out on the basis of a model approach combining regional space distributed hydrological model and global climate models. It is shown that a slight decrease by 8% is expected in the area-averaged specific runoff by the end of the century according to the Representative Concentration Pathway 8.5 scenario. However, in various parts of the watershed both a slight increase by 3–6% and a significant decrease in the mean annual runoff by 22% can occur, depending on physiographic conditions. Moreover, climatic changes can increase contrasts in the ecological status of the territory: warm regions in the steppe zone become even hotter and more arid, and the moisture availability of wetter territories in the centre and east of the basin increases even more. [ABSTRACT FROM AUTHOR]

Urban areas continue to be affected by flooding, necessitating more sustainable and effective adaptation strategies and mitigation initiatives. This study investigates the potential flood reduction capability achieved through implementing various green infrastructures known as low-impact development (LID). The Bendung watershed, in the center of Palembang City, with a total area of 18.37 km2, is used as the study area to evaluate the performance of LID infrastructure in reducing flood parameters, including total runoff volume, peak runoff discharge, runoff coefficient, and flooding area. Five types of LID infrastructure were simulated, namely bio-retention cells, rain gardens, permeable pavements, rain barrels, and recharge wells. The flood simulations were performed using four design storms with 2-, 5-, 10-, and 25-year return periods. Hydrologic and hydraulic modeling and simulations were carried out using PCSWMM Professional 2D, and the results were integrated with ArcMap to map the flood inundation. The results of this study demonstrate that with only 9.81 percent of the area occupied by LIDs, a flood reduction of more than 30% can be achieved. In addition, implementing LIDs can help restore the watershed's hydrological condition to its natural state, as indicated by the decrease in the runoff coefficient. Thus, implementing LIDs in a sustainable urban drainage system must be widely promoted in many urban areas, especially in developed countries like Indonesia. This study can be used as a reference for the local government and authorities to create policies and regulations to establish sustainable flood mitigation measures in Palembang City. [ABSTRACT FROM AUTHOR]

This study examines the influence of climate change on hydrological processes, particularly runoff, and how it affects managing water resources and ecosystem sustainability. It uses CMIP6 data to analyze changes in runoff patterns under different Shared Socioeconomic Pathways (SSP). This study also uses a Deep belief network (DBN) and a Modified Sparrow Search Optimizer (MSSO) to enhance the runoff forecasting capabilities of the SWAT model. DBN can learn complex patterns in the data and improve the accuracy of runoff forecasting. The meta-heuristic algorithm optimizes the models through iterative search processes and finds the optimal parameter configuration in the SWAT model. The Optimal SWAT Model accurately predicts runoff patterns, with high precision in capturing variability, a strong connection between projected and actual data, and minimal inaccuracy in its predictions, as indicated by an ENS score of 0.7152 and an R2 coefficient of determination of 0.8012. The outcomes of the forecasts illustrated that the runoff will decrease in the coming years, which could threaten the water source. Therefore, managers should manage water resources with awareness of these conditions. [ABSTRACT FROM AUTHOR]

Thermo-erosion gullies (TEGs) are one of the most common forms of abrupt permafrost degradation. They generally form in ice-wedge polygonal networks where the interconnected troughs can channel runoff water. Although TEGs can form within a single thawing season, it takes them several decades to stabilize completely. While the inception of TEGs has been examined in several studies, the processes of their stabilization remain poorly documented, especially the cryostructures that form following permafrost aggradation in stabilizing TEGs. For this study, we investigated the impacts of two TEGs in the Canadian High Arctic (Bylot Island, NU, Canada) on ground ice content, cryostratigraphic patterns, and geomorphology to examine permafrost recovery following thermal erosion in ice-wedge polygonal tundra. We sampled 17 permafrost cores from two TEGs – one still active (since 1999) and one stabilized (> 100 years old) – to describe the surface conditions, interpret the cryostratigraphic patterns, and characterize the state of permafrost after TEG stabilization. Although the TEG caused discernable cryostratigraphic patterns in permafrost, ground ice content and thaw front depth in the TEGs were comparable to measurements made in undisturbed conditions. We also noted that, once stabilized, TEGs permanently (at the Anthropocene scale) alter landscape morphology and hydrological connectivity. We concluded that, although the formation of a TEG has profound effects in the short and medium term (years to decades) and leaves near-permanent geomorphological and hydrological scars in periglacial landscapes, in the long term (decades to centuries), High Arctic permafrost can recover and return to geocryological conditions similar to those pre-dating the initial disturbance. This suggests that, in stable environmental conditions undergoing natural variability, permafrost can persist longer than the geomorphological landforms in which it forms. [ABSTRACT FROM AUTHOR]

Objectives: The Greenland ice sheet is one of the main contributors to the global sea level rise, and the mass loss caused by its surface melting and meltwater runoff accounts for about 60% of the total mass loss of the ice sheet, so it is of great significance to study the surface melting of the Greenland ice sheet. Methods: Based on the 37 GHz vertical polarization passive microwave data of special sensor microwave imager sounder, the advanced diurnal amplitude variations (ADAV) method is proposed to detect the surface melting of the Greenland ice sheet. Results: Compared with the air temperature data of automatic weather stations, the average accuracy of the detection results of the ADAV method using dynamic threshold is better than that of the traditional diurnal amplitude variations method using a fixed threshold, and the passive microwave data time has no obvious influence on the detection accuracy. Conclusions: The freezethaw analysis of the Greenland ice sheet based on this method found that in 2019, the area with the most melting days on the ice sheet melted up to 165 d. The melting area reached the maximum on July 31st, accounting for 67% of the total ice sheet area. Three melting peaks arose in summer, and there were sever winter melting events on the south coast. The ADAV method and its application to high spatial resolution passive microwave data have promoted the development of refining ice sheet freezing and thawing observations. [ABSTRACT FROM AUTHOR]

Urban Land Surface Models (ULSMs) simulate energy and water exchanges between the urban surface and atmosphere. However, earlier systematic ULSM comparison projects assessed the energy balance but ignored the water balance, which is coupled to the energy balance. Here, we analyze the water balance representation in 19 ULSMs participating in the Urban‐PLUMBER project using results for 20 sites spread across a range of climates and urban form characteristics. As observations for most water fluxes are unavailable, we examine the water balance closure, flux timing, and magnitude with a score derived from seven indicators expecting better scoring models to capture the latent heat flux more accurately. We find that the water budget is only closed in 57% of the model‐site combinations assuming closure when annual total incoming fluxes (precipitation and irrigation) fluxes are within 3% of the outgoing (all other) fluxes. Results show the timing is better captured than magnitude. No ULSM has passed all water balance indicators for any site. Models passing more indicators do not capture the latent heat flux more accurately refuting our hypothesis. While output reporting inconsistencies may have negatively affected model performance, our results indicate models could be improved by explicitly verifying water balance closure and revising runoff parameterizations. By expanding ULSM evaluation to the water balance and related to latent heat flux performance, we demonstrate the benefits of evaluating processes with direct feedback mechanisms to the processes of interest. Plain Language Summary: Urban environments have their own local climates including typically higher nocturnal temperatures compared with rural areas. Ideally, modeling cities should capture their influences on the atmosphere above them. As the energy and water balances are linked by evaporation, a good water balance representation will support a good energy balance simulation. Focusing on the water balance, we find the water balance in models could be improved by paying attention to closure and runoff. Key Points: We evaluate the water balance in 19 urban land surface models (ULSM) from the Urban‐PLUMBER projectULSMs capture the timing of water fluxes more accurately than their magnitudeThe water balance appears unclosed in 43% of the model runs (19 models at 20 sites) [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]

The accuracy of long-term runoff models can be increased through the input of local weather variables and global climate indices. However, existing methods do not effectively extract important information from complex input factors across various temporal and spatial dimensions, thereby contributing to inaccurate predictions of long-term runoff. In this study, local–global–temporal attention mechanisms (LGTA) were proposed for capturing crucial information on global climate indices on monthly, annual, and interannual time scales. The graph attention network (GAT) was employed to extract geographical topological information of meteorological stations, based on remotely sensed elevation data. A long-term runoff prediction model was established based on long-short-term memory (LSTM) integrated with GAT and LGTA, referred to as GAT–LGTA–LSTM. The proposed model was compared to five comparative models (LGTA–LSTM, GAT–GTA–LSTM, GTA–LSTM, GAT–GA–LSTM, GA–LSTM). The models were applied to forecast the long-term runoff at Luning and Pingshan stations in China. The results indicated that the GAT–LGTA–LSTM model demonstrated the best forecasting performance among the comparative models. The Nash–Sutcliffe Efficiency (NSE) of GAT–LGTA–LSTM at the Luning and Pingshan stations reached 0.87 and 0.89, respectively. Compared to the GA–LSTM benchmark model, the GAT–LGTA–LSTM model demonstrated an average increase in NSE of 0.07, an average increase in Kling–Gupta Efficiency (KGE) of 0.08, and an average reduction in mean absolute percent error (MAPE) of 0.12. The excellent performance of the proposed model is attributed to the following: (1) local attention mechanism assigns a higher weight to key global climate indices at a monthly scale, enhancing the ability of global and temporal attention mechanisms to capture the critical information at annual and interannual scales and (2) the global attention mechanism integrated with GAT effectively extracts crucial temporal and spatial information from precipitation and remotely-sensed elevation data. Furthermore, attention visualization reveals that various global climate indices contribute differently to runoff predictions across distinct months. The global climate indices corresponding to specific seasons or months should be selected to forecast the respective monthly runoff. [ABSTRACT FROM AUTHOR]

The Arabian Gulf, a semi-enclosed basin in the Middle East, connects to the Indian Ocean through the Strait of Hormuz and is surrounded by seven arid countries. This study examines the water cycle of the Gulf and its surrounding areas using data from the GRACE and GRACE Follow-On missions, along with ERA5 atmospheric reanalysis data, from 05/2002 to 05/2017 and from 07/2018 to 12/2023. Our findings reveal a persistent water deficit due to high evaporation rates, averaging 370 ± 3 km3/year, greatly surpassing precipitation, which accounts for only 15% of the evaporative loss. Continental runoff provides one-fifth of the needed water, while the remaining deficit, approximately 274 ± 10 km3/year, is balanced by net inflow of saltwater from the Indian Ocean. Seasonal variations show the lowest net inflow of 26 ± 49 km3/year in March and the highest of 586 ± 53 km3/year in November, driven by net evaporation, continental input, and changes in the Gulf's water budget. This study highlights the complex hydrological dynamics influenced by climate patterns and provides a baseline for future research in the region, which will be needed to quantify the expected changes in the hydrological cycle due to climate change. [ABSTRACT FROM AUTHOR]

Making accurate and reliable predictions for monthly runoff in data scarce basins is still a major challenge. In this study, a new model, the CL-NDM, is developed by combining Convolutional Neural Network-Long Short-term Memory (CNN-LSTM) and a nonlinear dynamic model. The CL-NDM can overcome the deficiency of observed data by fusing spatial and temporal dependencies in runoff sequences at different stations. First, phase space reconstruction is used to enlarge the dimensions of the runoff sequences and reconstruct the attractors of the runoff sequences. Then, the CNN-LSTM is employed to construct the mapping between non-delay and delay attractors. Finally, the prediction set of the target variable is obtained by embedding multiple times. The CL-NDM is performed for monthly runoff prediction at eleven hydrological stations in the Weihe River, China. Compared with the CNN, LSTM and CNN-LSTM models, which require a large amount of training samples, the CL-NDM behaves much better, especially in situations with small training sample sizes. The maximum increase in R is 74%, and the maximum NSE is as large as 0.8. The maximum improvement in RMSE and MAPE is 53% and 88%, respectively. The CL-NDM has stronger ability to capture peak value while LSTM, CNN-LSTM and CNN models show obvious time lag in the prediction of peak point. The improved nonlinear dynamical model may provide a valuable method for runoff prediction in data-scarce regions. [ABSTRACT FROM AUTHOR]

Previous studies have proven the efficiency of LID practices in mitigating surface runoff in urban watersheds; however, the impact of their placement strategy over the urban drainage system, under continuous temporal hydrological simulation, has not been explored yet. This study simulated, under continuous time scale, five LID practices and four LID placement strategies (downstream, center, upstream and uniformly) on the drainage system of the Universidade Federal de Lavras urban area, in the state of Minas Gerais, Brazil. Under the conditions analyzed, it was found that there were no significant statistical differences between the efficiency of the different LID practices, individually or combined, within the same placement strategy. The uniform placement strategy proved to be more efficient, but in soils with higher Ksat values, other strategies showed better results. Therefore, it was found that soil Ksat is a parameter that should be carefully analyzed for LID practices implementation. [ABSTRACT FROM AUTHOR]

This study evaluated the performance of a pre-treatment facility for SuDS water quality improvement designed to handle the stormwater runoff of a 200 m2 parking lot, using synthetic runoff and a statistical model of two levels of operation and four variables. The prototype consisted of an inlet ramp, sedimentation and filtration tank, and a recirculation system. The results showed that the removal efficiency of total suspended solids (TSS) and fats and oils concentration in the effluent are not affected by influent variations in flow rate, pH, temperature, TSS, fats and oils, and lead concentration. For the 32 measurements taken, an average of 82.9% (SD 3.6%) was obtained regarding total suspended solids removal. Lead retention possibilities were also observed. The TSS removal efficiencies were above 90.6% for precipitation events, generating peak flows of up to 5 L/s and a duration of 21 minutes, controlling the diffuse pollution peak. [ABSTRACT FROM AUTHOR]

[Objective The aims of this study are to analyze the response of farmland surface runoff and sediment loss to rainfall patterns under different planting modes, to explore the laws of farmland surface runoff and sediment transport in the Poyang Lake plain area under new circumstances, and to provide scientific basis for preventing and controlling farmland surface soil erosion, [Methods] 64 rainfall events were classified using K-means clustering method, and combined with monitoring data such as runoff and sediment production in runoff plots, the impact of surface runoff and sediment losses in different rainfall types of farmlands under three planting modes were analyzed. Results] (1) The duration, rainfall and maximum rainfall intensity of 30 minutes were taken as the rainfall characteristic indicators. The rainfall could be divided into 4 types (type A: 'medium duration, small rainfall and light rainfall intensity', type B: 'short duration, small rainfall and medium rainfall intensity', type C: 'long duration, heavy rainfall and medium rainfall intensity', and type D: short duration, medium rainfall and heavy rainfall intensity'). (2) The variation of runoff and rainfall of each planting mode was basically the same, and the runoff was also more when the rainfall was larger. In each month dry farming mode produced the most runoff, (3) No matter what type of rainfall, the runoff and sediment losses of dry farming mode were the highest. Under the types A and C. the runoff and sediment yields of water farming mode were the lowest. Under the type B. the runoff reduction effect of water and dry rotation mode was the best. (4) There were significant differences in the total runoff and sediment loss under different planting modes, and the performance followed the order: dry farming mode paddy upland rotation mode paddy farming mode. [Conclusion In conclusion. compared with the dry farming model, the water farming model has certain advantages in reducing runoff and sediment, especially when dealing with type A and type C. the effect of runoff and sediment reduction is more obvious. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to assess the accuracy of soil erodibility K calculated by different methods in the key soil loss areas of Anhui Province, and to refine each calculation method based on the measured erodibility K. [Methods] The Nomo equation, modified Nomo equation, EPIC model, DG model and Torri model were utilized to estimate the soil erodibility K values. Based on monitoring data from runoff plots in Huoshan County, Guangde County, Yuexi County and She County, the actual erodibility factor K values were obtained to evaluate the effectiveness of each method. [Results] The soil erodibility K values in Huoshan County, Guangde County, Yuexi County and She County were 0.033~0.035, 0.018, 0.021 and 0.041 (thm² h)/(hm² MJ mm), respectively. The differences in soil erodibility K values derived from different methods were significant, with all methods greatly overestimating the K values. The overall ranking of the methods in terms of soil erodibility followed the order: K Torri> K Noma> KM-Nomo >K DG> K Epic. The methods of calculating K values for each were improved, in which the improved Nomo equation and the modified Nomo equation showed superior performance. [Conclusion] The improved Nomo equation and modified Nomo equation are recommended to apply in the key soil loss areas of Anhui Province. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the influence of slope, rainfall pattern and sugarcane growth period on soil erosion and nutrient loss on slope surface, and to provide theoretical basis for the mechanism improvement and prevention of soil erosion in sugarcane planting area of lateritic soil. [Methods] In-situ observation method in runoff area was used to explore the characteristics of soil erosion and loss of nitrogen nutrients (nitrate nitrogen and ammonium nitrogen) at different slopes (5° and 10°) under different rain types and sugarcane growth period. [Results] (1) The runoff in each growth period decreased in the order; extension period tillering periodseedling period mature period, and the nitrogen loss in tillering period was significantly higher than that in the other three periods (2.6~905.2 times). The sediment yield and their nitrogen nutrient loss followed the order: tillering stage extension period seedling period maturity period, the sediment yield of sugarcane in the tillering stage was significantly higher than that in other periods (2.9~71.4 times), and the difference was more obvious under the 10° slope. (2) Type B (medium rainfall depth, short duration, strong rainfall intensity) and type C (great rainfall depth, short duration, extremely strong rainfall intensity) were the main rainfall pattern that caused soil erosion and the nitrogen nutrient loss in sugarcane in the research area, contributing more than 70% of the slope runoff, sediment yield and nitrogen loss. In different slope treatments, there were significant differences in the sediment amount under type C, sediment ammonium nitrogen loss under type A and runoff ammonium loss under type B. (3) Rain pattern and sugarcane growth period had significant effects on runoff, sediment and those nitrogen loss on sugarcane slope (p<0.01), and the effect was higher than that of slope, interaction between slope and rain pattern, interaction between slope and growth period. Compared with runoff and those nitrogen loss, slope and its interaction with rain pattern and growth period showed more prominent effects on erosion sediment and nitrogen loss. [Conclusion] The slope had a more significant influence on the sediment and nitrogen nutrient loss process of sugarcane slope. The soil erosion and nitrogen nutrient loss were greatest in the tillering period, mainly contributed by type B and type C. [ABSTRACT FROM AUTHOR]

Serang Welahaan Drainage (SWD) 1 River is located in one of those floodprone areas in Central Java that generates flood hazards causing high risk to the surrounding rice fields and communities. However, a comprehensive study of flood hazards in SWD1 River has never been conducted. Nowadays, previous comprehensive flood studies in Indonesia only available for several very developed areas, such as the Jakarta, Bandung Flood and Solo Flood, or new iconic area for mangrove conservation such as Langsa City . Most previous studies conclude that flood hazards in Indonesia are commonly generated by rain runoff, tides, and dam break flows, or a combination of these generators . Existing conditions show that SWD 1 is unable to accommodate runoff from the Wulan River, causing flooding. Based on rainfall data from BMKG, the maximum rainfall per month for a year reaches 323 mm. This study is an effort to analyze the impact of land use change to know Flood impact.T.The research method used analysis of the influence of changes in CN (Curve Number) due to changes in land use on flood discharge as shown through changes in the Soil Conservation Service (SCS-CN) hydrograph on discharge and runoff volume. The selection of the SCS-CN method is due to its widespread adoption in various regions, its extensive use in numerous analytical studies, and its suitability for the characteristics of the watershed under review.The analysis results show that there has been a change in flood discharge from 2019 and 2022 with values of 366.920 and 371.154 m3/second. The discharge values did not change significantly because the CN values were as follows, 83.25 and 83.36. Through analysis, it can be seen that an increase in discharge of 1.14% from 2011 to 2022.The several alternatives are needed to reduce flooding, such as watershed conservation upstream, minimizing land use changes and building flood mitigation infrastructure downstream. [ABSTRACT FROM AUTHOR]

Changes in the ecological environment quality (EEQ) in the main inland Tarim River Basin in China substantially impact the regional development. Indeed, comprehensive ecological environment measures have been implemented in the Tarim River Basin since 2000. In this context, the main objective of the present study was to investigate the spatiotemporal evolution of the EEQ and monitor the effectiveness of ecological restoration measures in the Tarim River Basin over the 2000–2020 period using remote sensing data. First, a Remote Sensing Ecological Index (RSEI) was constructed based on the Moderate Resolution Imaging Spectroradiometer remote sensing data. Second, the spatial distributions and factors of the RSEI were analyzed by using Moran's Index and Geodetector. The results indicated that the overall RSEI values for the Tarim River Basin increased from 0.22 in 2000 to 0.25 in 2020. Moreover, the values for areas with poor EEQ decreased from 50.7% to 44.73%, while those with moderate EEQ increased from 11.45% to 16.91%. Therefore, the results demonstrated a slight overall improvement in the EEQ of the study area over the 2000–2020 period. On the other hand, the EEQ in the Tarim River Basin exhibited a significant spatial autocorrelation in the 2000–2020 period, with a relatively stable overall spatial distribution. Areas with high–high aggregation were distributed in the high-elevation mountainous areas in the western, northern, and southern parts of the study area. In contrast, areas with low–low aggregation were observed in the central and eastern low-elevation desert areas. The EEQ in the Tarim River Basin was driven by the interactions of several factors, including the normalized difference vegetation index, land surface moisture, land surface temperature, normalized differential build-up and bare soil index, and elevation. In particular, heat was the main driving factor that severely impacted the EEQ in the study area. Indeed, increase in the heat values could directly enhance meltwater runoff from glaciers in the basin, thereby resulting in short-term improvement in the basin EEQ. Furthermore, rapid urbanization from 2015 to 2020 resulted in a decrease in the average RSEI value of the Tarim River Basin by 0.1 over this period, consequently, the EEQ level decreased slightly. Briefly, the EEQ in the Tarim River Basin showed an overall increasing trend from 2000 to 2020, further demonstrating the effectiveness of a series of implemented ecological restoration measures in the Tarim River Basin over this period. [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]

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]

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]

The use of green roofs, a low-impact development practice, can be an effective means of reducing direct runoff in urban centers. Green roof modeling can enable efficient design by preliminarily grasping the behavior of the green roof system according to specific configurations. In this study, we aimed to find appropriate evapotranspiration and parameter optimization schemes for HYDRUS-1D, a commonly used modeling tool for green roofs. Comparative studies of this sort in the context of green roof runoff modeling have not been conducted previously and are important in guiding users to overcome the difficulties of choosing the right numerical schemes for an accurate prediction of runoff from a green roof. As a study site, the Portland Building Ecoroof in Portland, Oregon, USA, was chosen, as green roof configurations and observed data for climate and runoff were available. From the simulation results of the runoff volume, the Blaney–Criddle method, which was considered an alternative, was found to be appropriate for calculating evapotranspiration from a green roof (R2 = 0.82) relative to the Hargreaves method built in HYDRUS-1D (R2 = 0.46). In addition, this study showed that the optimization method using the harmony search algorithm, which was proposed as an alternative optimizer, was better (R2 = 0.95) than that of the HYDRUS-1D's own optimization module (R2 = 0.82) in calibrating HYDRUS-1D for green roof runoff. The findings are thought to be useful in guiding modelers who are considering using HYDRUS-1D for green roof runoff simulations. [ABSTRACT FROM AUTHOR]

Surface water availability in arid regions like the Riyadh region of Saudi Arabia is a significant concern due to its low and highly variable rainfall. This study represents the first comprehensive attempt to estimate surface runoff in the Riyadh region by integrating satellite data with field measurements, including dam observations, for enhanced accuracy. Utilizing the advanced Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Dynamic Infrared Rain Rate near-real-time (PDIR-Now) dataset, the study covers a 23-year period from 2001 to 2023. The research aimed to determine runoff coefficients, which are critical for predicting how much rainfall contributes to surface runoff. Analysis of annual runoff volumes and rainfall data from 39 dams, divided into calibration and validation sets, led to a runoff coefficient of 0.059, indicating that 5.9% of rainfall contributes to runoff. The calibration process, validated by statistical measures such as mean bias (0.23 mm) and RMSE (0.94 mm), showed reasonable model accuracy but also highlighted areas for refinement. With an average annual rainfall of 89.6 mm, resulting in 1733.1 million cubic meters (mil. m3) of runoff, the study underscores the importance of localized calibration and ongoing model refinement to ensure sustainable water management in the face of environmental and climatic challenges. [ABSTRACT FROM AUTHOR]

Runoff in high-latitude water towers is crucial for ecological and human water demands during freeze–thaw periods but is highly sensitive to climate change and human activities. This study focuses on Changbai Mountain, the source of the Songhua, Tumen, and Yalu rivers, analyzing runoff variation and its environmental responses using the modified Mann–Kendall method and the water–energy balance equation. The results show significant non-stationarity in runoff trends, with an increasing trend in the Yalu River basin (p < 0.05), a decreasing trend in the Tumen River basin (p < 0.05), and complex trends in the Songhua River basin. Additionally, the relationship between runoff and driving factors during freeze–thaw periods was quantized. When the snowfall, potential evapotranspiration (E0), and subsurface changes increased by 1%, the snowmelt runoff changes were 1.58~1.96%, −0.58~−1.96%, and −0.86~−1.11% in the Yalu River basin; 2.16~2.35%, −1.04~−1.35%, and −1.56~−1.95% in the Tumen River basin; and 1.44~2.41%, −0.44~−1.41%, and −0.72~−1.62% in the Songhua River basin. The increased snowfall was the most prominent reason for the increase in snowmelt runoff during spring. The results of this study will benefit ecosystem conservation and the stability of downstream water supply in this high-latitude water tower. [ABSTRACT FROM AUTHOR]

Rain-on-snow (RoS) events in regions of ephemeral snowpack – such as the northeastern United States – can be key drivers of cool-season flooding. We describe an automated algorithm for detecting basin-scale RoS events in gridded climate data by generating an area-averaged time series and then searching for periods of concurrent precipitation, surface runoff, and snowmelt exceeding predefined thresholds. When evaluated using historical data over the Susquehanna River basin (SRB), the technique credibly finds RoS events in published literature and flags events that are followed by anomalously high streamflow as measured by gauge data along the river. When comparing four different datasets representing the same 21-year period, we find large differences in RoS event magnitude and frequency, primarily driven by differences in estimated surface runoff and snowmelt. Using dataset-specific thresholds improves agreement between datasets but does not account for all discrepancies. We show that factors such as meteorological forcing and coupling frequency, as well as choice of land surface model, play roles in how data products capture these compound extremes and suggest care is to be taken when climate datasets are used by stakeholders for operational decision-making. [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]

Thermal regimes can vary substantially across small geographic distances in rivers, and the factors responsible for creating a diverse thermal landscape can operate on multiple spatial and temporal extents. This short communication reports on the temperature dynamics in seasonal, off‐channel habitats in the lower reach of the Gudbrandsdalslågen River in South‐Eastern Norway (61 oN). The river is ordinarily characterized by a snowmelt‐driven hydrograph but was subjected to widespread, rain‐driven flooding in August 2023. At the onset of spring runoff in mid‐May, the differences between cooler and warmer sites exceeded 5°C (range 3–10°C) and continued to diverge until early July (range 6–21°C). Differences persisted through the regular rain‐driven spates in summer but were entirely diminished during the flood which started on August 7. By August 10, the water temperatures at all 14 sites had converged at 12.3°C. The homogenization was likely the result of the sheer volume of runoff through Gudbrandsdalslågen, overriding any locally modulating factors such as groundwater inputs and isolation from the main channel. This suggests a relatively strong influence of locally modulating factors in the study area under normal hydrological conditions in summer, and a complete dominance of runoff temperature during the flooding event. Disruptive events such as flooding can hence periodically revert the thermal heterogeneity by changing the relative importance of the factors that create patchy thermal regimes, with potential ramifications for aquatic organisms that occupy relatively warmer habitat patches in summer. [ABSTRACT FROM AUTHOR]

Long-term variations of ecological and hydrological parameters governing the natural reproduction of sturgeon are analyzed. It was found that long-term variations of hydrological characteristics are taking place against the background of cyclic development of phases with different water abundance and transformation of the annual redistribution of runoff. The contribution of long-term runoff regulation by the Iriklinskoe Reservoir to water regime variations in the Ural River is considered for its middle reaches. A conclusion is made regarding the need to restore the sturgeon herd in the Northern Caspian Sea. Recommendations are made regarding the priority measures for preserving the potential of sturgeon spawning grounds in the middle reaches of the Ural River. [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]

Grass‐planting measure is a crucial vegetation approach to mitigate understory soil erosion and improve ecological environment in the red soil region of southern China. This study aimed to quantify the effects of grass (Paspalum wettsteinii Hackel.)‐planting measures on runoff and sediment reduction on slopes of Masson pine plantations under rainstorm conditions. We conducted a rainfall simulation experiment at a rainfall intensity of 2.0 mm/min, comparing single strip (MT1, strip spacing: 145 cm), double strips (MT2, strip spacing: 70 cm), and triple strips (MT3, strip spacing: 45 cm) grass‐planting measures on slope surface runoff generation and soil erosion processes of the young Masson pine (MT0, no grass strip) plantation, and the bare slope (CK) was selected as the control. Results revealed that grass‐planting measures significantly decreased slope erosion parameters compared to CK and MT0. As the average grass coverage increased (MT1 from 10% to 25%, MT2 from 7.5% to 22.5%, MT3 from 7.3% to 25%), the slope surface erosion parameters under the grass‐planting measures decreased, resulting in significantly improved runoff and sediment reduction benefits. The runoff reduction effect could reach 32%, while the sediment reduction effect could reach 88%. Moreover, MT3 demonstrated superior performance over MT2 and MT1, with minimal runoff and sediment reduction effects observed for the MT0. Overall, this study suggests that grass‐planting measures, coupled with the increasing of grass coverage rates, significantly improve runoff and sediment reduction benefits on slopes in regions experiencing heavy rainfall. Among the tested configurations, MT3 emerged as most effective measure for controlling understory soil erosion in Masson pine plantations, especially when its average grass coverage rate reached 25%. These findings provide valuable insights for selecting appropriate grass‐planting strategies, as well as for understanding the underlying mechanisms of how these measures mitigate soil erosion. This scientific reference will aid in the design and implementation of soil and water conservation measures in the region. [ABSTRACT FROM AUTHOR]

This study employs the MIKE 3 Flow Model, incorporating forcing conditions such as inflow from 18 major rivers along the Bohai coast, wind, precipitation, evaporation, and solar radiation, to develop a hydrodynamic and temperature-salinity model for the Bohai Sea, using a finer mesh for more detailed simulation in Laizhou Bay. The residual current in the surface layer primarily flowed eastward, exhibiting coastal transport characteristics in the southern region, leading to the formation of a large low-salinity region. The bottom salinity distribution closely mirrored that of the surface, with the isohaline shifting shoreward due to the high-salinity Bohai Sea water transported by the residual current. By grouping major runoff sources according to river outlet locations and residual current patterns, the study analyzed the impact of freshwater plumes formed by runoff from different directions on the salinity distribution in Laizhou Bay. The results indicate that the influence of freshwater inputs on both the mean salinity and the area of low-salinity zones in Laizhou Bay, ranked from greatest to least, is as follows: the Yellow River, the southwest, and the southeast. The variation in the area of low-salinity regions is closely related to factors such as runoff volume, residual currents, and the selection of boundaries for the low-salinity regions. [ABSTRACT FROM AUTHOR]

Soil erosion by water and inappropriate land management practices result in poor agricultural production in the highlands of Ethiopia. Cover crops (CCs) are a promising cropping system to ameliorate soil health and agricultural production. A field plot experiment was carried out during the rainy seasons of 2019 and 2020 to assess the effects of CCs on runoff, soil loss, soil water content, and yield performance of barley in the Kasiry sub-catchment of Guder. The plot experiment contained four treatments: control, vetch (Vicia sativa L.), sweet lupin (Lupinus angustifolius L.), and bitter lupin (Lupinus albus L.); arranged in a randomized complete block design with three replications. Each 12 m2 plot had a runoff monitoring system. A total of 1080 soil samples were collected at depths of 0 to 0.5 m from each plot at intervals of 0.1 m for soil water analysis. Treatments with CCs showed significantly (P < 0.05) higher levels of soil organic carbon, total nitrogen, available phosphorus, and biomass compared to the control plot. Runoff and soil loss were also reduced (9.6% and 38.3%, respectively), with bitter lupin being the most effective. In contrast, soil water content did not differ significantly between CC and control treatments. The grain yield of barley increased from 38 to 64%, and a partial budget analysis showed that CCs increased overall net profit, with bitter lupin having the highest marginal rate of return (8608%). Generally, treatments with less runoff and soil loss rates and higher crop yield should be adopted and scaled up. [ABSTRACT FROM AUTHOR]

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