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This study examined the sediment characteristics of areas where landslides occurred due to heavy rains between 2014 and 2019. A total of 13 lithotypes in five geographic regions in Japan were examined using LiDAR LP topography data before and after the disasters occurred to estimate the changes in elevation. In addition, the volume of sediment runoff for each case was estimated for basin areas ranging from 0.01 up to 0.1 km 2 . The influence of geological differences on the sediment runoff volume within the watershed using indicators such as the density of landslide occurrence, landslide volume, and watershed erosion intensity was also assessed. The results showed that, for all lithotypes, as the watershed area increases, the relief ratio decreases and the sediment runoff volume increases; however, the magnitude of this increase in sediment runoff volume differs depending on the underlying lithotypes. In addition, the density of landslide occurrence was high in plutonic and metamorphic rocks. The landslide volume and the total eroded sediment volume within a watershed generically [intercept set to zero] can be regressed using a linear equation. Since the average total eroded sediment volume within a watershed is approximately twice that of the landslide volume, there is a proportional relationship of 1:2. The relationship between the relief ratio and watershed erosion intensity shows that the watershed erosion intensity increases gradually as the relief ratio increases, and the rate of increase is larger in plutonic rocks (granite and granodiorite) than in the other groups.

With the acceleration of the urbanization process, urban waterlogging problems are becoming more and more serious in Nanjing, China. In order to mitigate the urban waterlogging problems, it is necessary to reduce surface runoff from the source by rainwater harvesting and utilization. An urban residential district with an area of 0.58 km 2 in Nanjing was selected as the study area. Based on a large-scale topographic map data and the long term rainfall data (1951–2008), the types of underlying surfaces were classified. The potentiality of collectable rainwater and the possibility of runoff volume reduction were calculated. The results showed that exploitation of rainwater harvesting from rooftops and other underlying surfaces has high potential. The annual collectable rainwater is approximately 372,284 m 3 , 314,034 m 3 and 275,180 m 3 under different cumulative frequency of rainfall at 20 %, 50 % and 75 %, respectively. The total capacity of cisterns under assumptions of return period of rainfall and rainfall duration with 5 years and 20 min is 11,022 m 3 . The cistern’s capacity which is used for roof rainwater harvesting is 4,083 m 3 , the cistern capacity for per unit roof area (1 m 2 ) is 0.0267 m 3 . The results of the feasibility analysis of setting up above-ground cisterns showed that 55 % of the total roof areas in the study area are available for setting up cisterns. In the three building types, 16 % of the commercial building’s roof areas and 77 % of that of the residential and the “others” buildings are available for setting up cisterns. Urban waterlogging problems can be effectively reduced through rainwater harvesting by 13.9 %, 30.2 % and 57.7 % of runoff volume reduction in three cases of the maximum daily rainfall (207.2 mm), the average annual maximum daily rainfall (95.5 mm) and the critical rainfall of rainstorm (50 mm).

It is urgent to effectively mitigate flood disasters in humid mountainous areas in southeastern China for the increasing flood risk under urbanization and industrialization. In this study, a rural district with an area of 13.39 km² that planning to build an industrial park covering an area of 7.98 km² in Changting was selected to estimate the potential of collectable rainwater and the extent to which runoff volume can potentially be mitigated by rainwater harvesting. In addition, the optimum cistern capacity of a rainwater harvesting system in the planned industrial park was evaluated using daily water balance simulation and cost-efficiency analysis. The results showed that rainwater harvesting in the planned industrial park has great potential. The annually collectable rainwater is approximately 9.8 × 10⁶ m³ and the optimum cistern capacity is determined to be 0.9 × 10⁶ m³. With the optimum cistern capacity, the annual rainwater usage rate is 0.99, showing neither financial savings nor deficits. Rainwater harvesting can reduce 100 % of runoff volume in the cases of critical rainfall storm (50 mm) and annual average maximum daily rainfall (111.2 mm), and 58 % of runoff volume in the case of maximum daily rainfall (233.6 mm), respectively. All surface runoff can be collected and stored in the cisterns when rainfall amount is less than 135.5 mm in a rainstorm event.

Un objetivo de los estudios hidrológicos es la estimación del volumen escurrido anual (VEA) de cuencas sin aforos. Datos que son básicos en el diseño de embalses. En este estudio, tal problema se resuelve por medio del análisis de frecuencias regional, con base en el método del índice de escurrimientos. Este enfoque se aplicó en la Región Hidrológica No. 10 (Sinaloa), México, procesando 22 registros de VEA, con amplitudes que variaron de 24 a 57 años. Por medio de la prueba de discordancia se eliminaron tres registros. La homogeneidad hidrológica regional se verificó con los 19 registros restantes y tres técnicas estadísticas: índices de estacionalidad, linealidad de los momentos ordinarios y regresión lineal entre momentos de probabilidad ponderada. Las pruebas de pérdida de homogeneidad de cada registro condujeron a eliminar cuatro, por mostrar tendencia lineal ascendente. Los 15 registros remanentes se procesaron de forma adimensional, al dividir sus datos entre su volumen escurrido medio anual (VEMA) y se concatenaron con el método de las estaciones-años, formando una serie de 539 datos. Para obtener la curva de crecimiento regional se aplicaron tres modelos probabilísticos: Pearson tipo III, Log-Normal y Transformación Potencial; adoptando el de menor error estándar de ajuste. El escalamiento de la distribución Log-Normal regional se logró con una relación logarítmica entre el VEMA y el área de cuenca de los registros procesados. Las Conclusiones detallan el procedimiento establecido y destacan la importancia de los resultados para generar secuencias sintéticas de VEA, igualmente probables de ocurrir. Por ello, se recomienda la aplicación sistemática del método del Índice de escurrimiento en otras regiones del país, para contar con tal método de estimación del VEA.

Urban stormwater runoff is a critical source of degradation to stream ecosystems globally. Despite broad appreciation by stream ecologists of negative effects of stormwater runoff, stormwater management objectives still typically center on flood and pollution mitigation without an explicit focus on altered hydrology. Resulting management approaches are unlikely to protect the ecological structure and function of streams adequately. We present critical elements of stormwater management necessary for protecting stream ecosystems through 5 principles intended to be broadly applicable to all urban landscapes that drain to a receiving stream: 1) the ecosystems to be protected and a target ecological state should be explicitly identified; 2) the postdevelopment balance of evapotranspiration, stream flow, and infiltration should mimic the predevelopment balance, which typically requires keeping significant runoff volume from reaching the stream; 3) stormwater control measures (SCMs) should deliver flow regimes that mimic the predevelopment regime in quality and quantity; 4) SCMs should have capacity to store rain events for all storms that would not have produced widespread surface runoff in a predevelopment state, thereby avoiding increased frequency of disturbance to biota; and 5) SCMs should be applied to all impervious surfaces in the catchment of the target stream. These principles present a range of technical and social challenges. Existing infrastructural, institutional, or governance contexts often prevent application of the principles to the degree necessary to achieve effective protection or restoration, but significant potential exists for multiple co-benefits from SCM technologies (e.g., water supply and climate-change adaptation) that may remove barriers to implementation. Our set of ideal principles for stream protection is intended as a guide for innovators who seek to develop new approaches to stormwater management rather than accept seemingly insurmountable historical constraints, which guarantee future, ongoing degradation.

As the largest city in northern China and the capital of China, the rapid increases in Beijing’s water consumption in recent years have made water resources provision an increasing problem. To rationally allocate water resources, it is important to obtain long‐term runoff information in Beijing. In this study we develop a 236‐year chronology of tree‐ring widths based on cores from Pinus tabuliformis from four sampling sites. The resulting regression model reconstructs December–July runoff of the Yongding River in Beijing, with 49.5% of the variance explained, back to 1786 CE. Among the last 236 years, 1868, 1956, 1991, 1998, 2018, and 2021 were extremely high runoff years; and 1900, 1906, 1999, and 2000 were extremely low runoff years. Comparison of the runoff reconstruction results with climate grid data demonstrated a large magnitude of climate change in North China during the study period. Linkage analysis between the reconstructed runoff and large‐scale water vapor indicated that the high runoff years occurred during negative phases of the Pacific Decadal Oscillation, which may be influenced by the East Asian Summer Monsoon. Projections indicate that the flow of the Yongding River will increase in the future. Supported by policies such as the Ecological Water Supply and South‐to‐North Water Diversion, regional vegetation productivity and Yongding River runoff have increased substantially since 2000. Vegetation growth interacts with runoff volume. It is unclear how long these increases will continue. Plain Language Summary As the largest city in northern China and the capital of China, Beijing has faced an increasingly water shortage problem in recent years. The Yongding River is an important river in the Beijing area and plays an important role in the local ecological system. In this study, we reconstructed the December–July runoff changes for the Yongding River using tree‐ring data from four sampling sites over the past 236 years. Under the influence of human water resource regulation, regional vegetation productivity and Yongding River runoff have increased significantly since 2000. Vegetation growth and runoff interact, and it is unknown how long these increases will last. Synoptic climatology analysis indicated that the high runoff years occurred during negative phases of the Pacific Decadal Oscillation, which may be influenced by the East Asian Summer Monsoon. Projections indicate that the flow of the Yongding River will increase in the future. Key Points Reflecting runoff changes in the Beijing area over the past 200 years, including extreme high and low runoff years Possible effects of atmospheric circulation on runoff changes in recent decades, links to the Pacific Decadal Oscillation, etc NDVI changes and trends in Beijing in recent years, as well as future flow changes

The accurate prediction of monthly runoff in the lower reaches of the Yellow River is crucial for the rational utilization of regional water resources, optimal allocation, and flood prevention. This study proposes a VMD-SSA-BiLSTM coupled model for monthly runoff volume prediction, which combines the advantages of Variational Modal Decomposition (VMD) for signal decomposition and preprocessing, Sparrow Search Algorithm (SSA) for BiLSTM model parameter optimization, and Bi-directional Long and Short-Term Memory Neural Network (BiLSTM) for exploiting the bi-directional linkage and advanced characteristics of the runoff process. The proposed model was applied to predict monthly runoff at GaoCun hydrological station in the lower Yellow River. The results demonstrate that the VMD-SSA-BiLSTM model outperforms both the BiLSTM model and the VMD-BiLSTM model in terms of prediction accuracy during both the training and validation periods. The Root-mean-square deviation of VMD-SSA-BiLSTM model is 30.6601, which is 242.5124 and 39.9835 lower compared to the BiLSTM model and the VMD-BiLSTM model respectively; the mean absolute percentage error is 5.6832%, which is 35.5937% and 6.3856% lower compared to the other two models, respectively; the mean absolute error was 19.8992, which decreased by 136.7288 and 25.7274 respectively; the square of the correlation coefficient ( R 2 ) is 0.93775, which increases by 0.53059 and 0.14739 respectively; the Nash–Sutcliffe efficiency coefficient was 0.9886, which increased by 0.4994 and 0.1122 respectively. In conclusion, the proposed VMD-SSA-BiLSTM model, utilizing the sparrow search algorithm and bidirectional long and short-term memory neural network, enhances the smoothness of the monthly runoff series and improves the accuracy of point predictions. This model holds promise for the effective prediction of monthly runoff in the lower Yellow River.

The regulation and spatial differences of urban runoffs are of great concern in contemporary hydrological research. However, owing to a shortage of basic data sources and restrictions on urban hydrological simulation functions, simulating and investigating the regulation mechanism behind rainfall-runoff processes remain significantly challenging. In this study, the Time Variant Gain Model (TVGM), a hydrological nonlinear system model, was extrapolated to the hydrodynamic model of an urban drainage network system by integrating it with the widely used Stormwater Management Model (SWMM) to adequately simulate urban runoff events while considering various underlying surfaces and runoff routing modes, such as surface, drainage network and river runoff, in urban regions (i.e., TVGM-SWMM). Moreover, runoff events were characterized using the following four runoff regime metrics: runoff coefficient, capture ratio of annual runoff volume, standardized flood timescale, and the ratio of occurrence time differences between flow and rainfall peak to event duration (peak flow delay time). The characteristics and spatial differences of urban runoff regulations were investigated, and the key impact factors and their relative contributions were identified using multivariate statistical analyses. Four communities were selected as our study areas, consisting of communities from Beijing, Shenzhen, Wuhan, and Chongqing. Our results showed that the TVGM-SWMM performed considerably better than SWMM alone. The comprehensive simulation accuracy of 60% of the events (12/20) improved by 486%, with the bias improving the most, followed by the efficiency coefficient. Barring the runoff coefficient, significant spatial differences were identified at the patch scale for the runoff regime metrics, with differences of 0.43, 0.22, and 0.16 ( p <0.05). The key impact factors were the pipe length ( r =0.51) in the drainage network system and the forest area ratios ( r =0.56), sponge measures ( r =0.52), grassland ( r =0.48), and impervious surface ( r =0.46) in the underlying surfaces. The contributions of the drainage network system and the underlying surfaces were 4.27% and 37.83%, respectively. Regulation in the Beijing community, dominated by grassland regulation, delayed and reduced the peak flow and total runoff volume. In the Shenzhen community, sharp and thin runoff events were mainly generated by impervious surfaces and were not adequately regulated. Forest regulation was the dominant regulation type in the Wuhan community, which reduced the total runoff volume and delayed the peak flow. Waterbody regulation was the primary regulation type in the Chongqing community, which reduced the total runoff volume and peak flow. This study aims to introduce a comprehensive theoretical and technical assessment of the hydrological effects of urbanization and the performance of sponge city construction and provide a reference for urban hydrological model improvements in China.

Rapid urbanization has increased impervious areas, leading to a higher flood hazard across cities worldwide. Low Impact Development (LID) practices have shown efficacy in reducing urban runoff; nevertheless, choosing the best combinations in terms of implementation cost and performance is of great importance. The present study introduces a framework based on green infrastructure, multi-objective optimization, and decision support tools to determine the most cost-effective LID solutions. The Storm Water Management Model (SWMM) was employed for rainfall-runoff and hydraulic modeling in Region 1, District 11 of Tehran, Iran. Six scenarios of different combinations of LID practices were developed. The system for Urban Stormwater Treatment and Analysis Integration (SUSTAIN) was used to optimize and evaluate each scenario. The selected solutions were imported to the SWMM to evaluate the stormwater system performance. Then, two multi criteria decision making (MCDM) models, including TOPSIS and COPRAS, were employed to rank the scenarios based on four technical and economic criteria. Results showed that scenario 4, consisting of rain barrels, porous pavements, and vegetated swales, had the best performance under TOPSIS with a 7.68 million USD and reduced the runoff volume and peak flow by 20.77% and 19.2%, respectively. However, Under the COPRAS method, Scenario 2 with a combination of rain barrels, bio-retention cells, and vegetated swales showed higher performance than the other scenarios with 3.25 million USD and led to a 15% reduction in the runoff volume and 4.30% in the peak flow. The COPRAS method was more sensitive to cost weights and chose the most economical scenario as the ideal. However, Scenario 4 concluded to be more feasible due to spatial limitations in the study area. The proposed SWMM—SUSTAIN—MCDM framework could be helpful to decision-makers in the design, performance evaluation, cost estimation, and selection of optimal scenarios.

Urban flooding problem has been exacerbated in recent times, especially in developing nations, due to haphazard changes in land use and land cover (LULC) resulting from rapid urban expansion, coupled with river encroachments and inadequately engineered river management structures. Kathmandu Valley Watershed (KVW), encompassing Kathmandu, Bhaktapur and Lalitur districts, the fastest growing cities in South Asia, is constantly growing, with a significant increase in urban areas. Due to urbanization, the watershed’s water storage capacity is diminishing, while surface runoff volume and rate are accelerating. We evaluated the isolated as well as the integrated impact of multiple scenarios of LULC change and river encroachment on flood inundation characteristics in KVW. LULC prediction revealed an increase in built-up areas by 113% between 1990 and 2020, which are further projected to increase by 29% by 2050. Inundation modeling using Rainfall-Runoff Inundation (RRI) model showed that rather than the increase in inundation extent, the depth of inundation is projected to increase in future as a result of increasing urban areas. Furthermore, our research highlighted that the impact of river width encroachment had a more substantial effect on flooding compared to changes in LULC alone. Similarly, integrated impact of LULC change and river encroachment was more pronounced than the impact of change in LULC alone. The aggregate of observations leads to the conclusion that the encroachment of rivers is the predominant factor contributing to the flooding issue within the KVW. The findings of the study is anticipated to assist policymakers in effective land use planning and in proposing appropriate development initiatives concerning the river environment.