Flood Peak Flow Research Articles

Advancing Water Security and Agricultural Productivity: A Case Study of Transboundary Cooperation Opportunities in the Kabul River Basin

The Kabul River Basin (KRB) is witnessing frequent flood and drought events that influence food production and distribution. The KRB is one of the world’s poorest regions regarding food security. Food security issues in the KRB include shifts in short-term climate cycles with significant river flow variations that result in inadequate water distribution. Due to the lack of hydro-infrastructure, low irrigation efficiency, and continuing wars, the Afghanistan portion of the KRB has experienced low agricultural land expansion opportunities for food production. This research assesses the relationship between flood mitigation, flow balances, and food production and, cumulatively, assesses the social and economic well-being of the population of the KRB. SWAT modeling and climate change (CCSM4) implications are utilized to assess how these relationships impact the social and economic well-being of the population in the KRB. The intricacies of transboundary exchange and cooperation indicate that the conservation of ~38% of the water volume would nearly double the low flows in the dry season and result in the retention of ~2B m3/y of water for agricultural developmental use. Results show that the peak flood flow routing in reservoirs on the Afghanistan side of the KRB would have a substantial positive impact on agricultural products and, therefore, food security. Water volume conservation has the potential to provide ~44% more arable land with water, allowing a ~51% increase in crop yield, provided that improved irrigation efficiency techniques are utilized.

The Coupled Application of the DB-IWHR Model and the MIKE 21 Model for the Assessment of Dam Failure Risk

The phenomenon of global climate change has led to an increase in the frequency of extreme precipitation events, an acceleration in the melting of glaciers and snow cover, and an elevation of the risk of flooding. In this study, the DB-IWHR model was employed in conjunction with the MIKE 21 hydrodynamic model to develop a simulation system for the dam failure flow process of an earth and rock dam. The study concentrated on the KET reservoir, and 12 dam failure scenarios were devised based on varying design flood criteria. The impact of reservoir failures on flood-risk areas was subjected to detailed analysis, with consideration given to a range of potential failure scenarios and flood sizes. It was determined that under identical inflow frequency conditions, the higher the water level, the more rapid the breakout process and the corresponding increase in flood peak discharge. Conversely, for a given frequency of incoming water, an elevated water level results in a transient breach process, accompanied by a reduction in flood peak flow. Moreover, for a given water level, an increase in water frequency results in a reduction in breaching time, an extension of flood duration, and an increase in flood peak flow. The observed trend of flood spreading is generally north-south, and this process is highly compatible with the topographic and geomorphological features, demonstrating good adaptability.

Accurate simulation of extreme rainfall–flood events via an improved distributed hydrological model

Recently, the high incidence of extreme rainfall and flood events worldwide has severely harmed regional economies and societies. Therefore, flood simulations and forecasts, which can provide key technical support for regional flood control and disaster reduction, are urgently needed. The Liuxihe model, as a fully distributed, physically based hydrological model, was improved in this study to simulate extreme rainfall flood events in the Beijiang River Basin. This basin is a famous rainstorm centre in Guangxi Province, China. In this work, the Liuxihe model is improved in two aspects: first, its structure and runoff generation and confluence algorithm are improved, and second, the parameter calibration method is optimised. These two adjustments improve the flood simulation performance of the model and reduce the uncertainty of the simulation results. The results revealed that the flood simulated by the improved Liuxihe model was strongly consistent with the measured values, and the index values of the Nash coefficient, correlation coefficient, process relative error, and flood peak flow error performed very well in the scheme evaluation; in particular, the mean process relative error, flood peak error, and peak time difference decreased by 62%, 63%, and 80%, respectively, after model improvement. The error indicators of the simulation were within the allowable error range from the Standard for Hydrological Information and Hydrological Forecasting (GB/T-22482–2008), which meets the accuracy requirements of flood forecasting in the local hydrological department and can be used as a practical operational plan for flood forecasting. These satisfactory flood simulation results showed that the model and algorithm were improved; thus, the improved Liuxihe model can provide important theoretical guidance for regional flood forecasting and flood disaster mitigation.

Estimating Grain Stress and Distinguishing Between Mobility and Transportability Improves Bedload Transport Estimates in Coarse‐Bedded Mountain Rivers

AbstractEstimating sediment transport in mountain rivers is challenging because of sediment supply limitation, broad grain size distributions, complex flow hydraulics, and large form drag. Consequently, sediment transport equations are lacking for application in rivers where the bed is coarse and largely immobile, but small fractions of finer, transportable sized material contribute disproportionately to bedload transport. We introduce a framework for estimating sediment transport in mountain rivers that addresses two limitations: estimating the shear stress acting on mobile grains, and accounting for the difference between mobility of size fractions, that is, whether or not a specific grain size can move at a given flow, and transportability, which we define as how much of that size present in the bed will be recruited into transport. We use two bedload data sets to develop equations for predicting incipient motion and transport rates of each grain size fraction present in the bed. We tested the new equations against incipient motion and sediment transport data we collected from streams in the Rocky Mountains, USA, and against published regional sediment yield data. Using this method results in transport estimates where the finer fractions, despite being a small fraction of the bed surface, make up a large part of the total yield. Fractions greater than the median bed grain size are mobile only during peak flood flows, consistent with the existing mountain river bedload data sets. The approach is parsimonious, requiring only data that are often readily available or obtainable: a bed grain size distribution, hydraulic geometry measurements, and discharge.

Using Copula functions to predict climatic change impacts on floods in river source regions

Flood frequency in river source regions is significantly affected by rainfall and snowmelt as part of climatic changes. A traditional univariate flood frequency analysis cannot reflect the complexity of floods, and when used in isolation, it can only underestimate flood risk. For effective flood prevention and mitigation, it is essential to consider the combined effects of precipitation and snowmelt. Copula functions can effectively quantify the joint distribution relationship between floods and their associated variables without restrictions on their distribution characteristics. This study uses copula functions to consider a multivariate probability distribution model of flood peak flow (Q) with cumulative snowmelt (CSm) and cumulative precipitation (CPr) for the Hutubi River basin located in northern Xinjiang, China. The joint frequencies of rainfall and snowmelt floods are predicted using copula models based on the Coupled Model Intercomparison Project Phase 6 data. The results show that Q has a significant positive correlation with 24-d CSm (r = 0.559, p = 0.002) and 23-d CPr (r = 0.965, p < 0.05). Flood frequency will increase in the future, and mid- (2050–2074) and long-term (2075–2099) floods will be more severe than those in the near-term (2025–2049). The probability of flood occurrence is higher under the SSP2-4.5 and SSP1-2.6 scenarios than under SSP5-8.5. Precipitation during the historical period (1990–2014) led to extreme floods, and increasing future precipitation trends are found to be insignificant. Snowmelt increases with rising temperatures and occurs earlier than estimated, leading to an earlier flood period in the basin and more frequent snowmelt floods. The Q under the joint return period is larger than that during the same univariate return period. This difference indicates that neglecting the interaction between precipitation and snowmelt for floods leads to an underestimation of the flood risk (with underestimations ranging from 0.3% to 22%). The underestimations decrease with an increase in the return period. The joint risks of rainfall or snowmelt according to various flood periods should be considered for rivers with multi-source runoff recharge in flood control design. This study reveals the joint impact of precipitation and snowmelt on extreme floods under climate change in river source regions. This study also provides a scientific basis for regional flood prevention and mitigation strategies, as well as for the rational allocation of water resources.

Sedimentary Characteristics, Ages, and Environmental Significance of Gravel Deposits and Loess in Shandong, Eastern China: Regional Response to Global Change Since the Last Glacial Period

AbstractInvestigation of rarely studied gravel layers found in the loess in Shandong Province, eastern China, reveals the fabric characteristics of two gravel layers (G1, G2) and the sedimentary characteristics of loess at the typical and well‐preserved Heiyu section (HY), where, to determine the paleoclimatic changes during Marine Isotope Stage 3a. Optically stimulated luminescence dates of the HY formation range from 0.26 ± 0.02 ka to 39.00 ± 2.00 ka. In addition, the ages of G1 and G2 were estimated using the Bayesian model to be 39.60–40.50 and 29.00–29.50 ka. G1 and G2 are mainly composed of fine and medium gravel, both of which were subangular to subrounded limestone, with gravel directions to NE and E. The average flow velocity, average depth, and flood peak flow of G1 are 1.10 m/s, 0.49 m, and 37.04 m3/s, respectively, calculated using the flow energy method, whereas those of G2 are 0.98 m/s, 0.38 m, and 18.38 m3/s, respectively. Analysis of climate proxy indices show that the sedimentary environment of the gravel and loess in HY might be a regional response to global change.

Gumbel’s Extreme Value Distribution for Flood Frequency Analyses of Timis River

One of the major problems in the engineering design of water resource is the estimation of peak flood flows. In probability theory and statistics, flood frequency analysis is used to obtain the distribution of flood probabilities. Gumbel distribution represents distributions of extreme values ​​used in hydrological studies to predict flood peak, maximum rainfall, etc. This paper aims to analyses the frequency of floods, Gumbel's frequency distribution method, based on the maximum annual flows in the Timis River for the period of 30 years (1993 – 2022). For this analysis the return period (T) used is 5 years, 10 years, 50 years, 100 years, 150 years.

Modeling the Potential Influence of Subsurface Tile Drainage Systems on Downstream Flooding in a Midwestern Agricultural Watershed

Highlights Tile flow was simulated to study the impacts of tile drainage on watershed hydrology and downstream flood days. Three tile drainage scenarios with varied extents of drained land were compared with a baseline scenario. The depth of tile flow contributing to streamflow was found to increase as the area of drained land increased. Results suggest that drainage systems decrease flood days when compared to the baseline scenario. Abstract. Subsurface tile drainage systems are common in agricultural regions of the Midwestern United States. Drainage systems remove excess water from the surface and soil profile of agricultural fields, allowing crop production in previously unsuitable locations. However, these systems impact watershed hydrology and could influence flooding events. Therefore, this study aimed to determine whether tile drainage systems influence downstream flood days in a Midwestern agricultural watershed, specifically the Skunk Creek watershed. The Soil and Water Assessment Tool (SWAT) model was used to simulate the hydrologic processes of the Skunk Creek Watershed for an 18-year period (2004–2021). The model was calibrated and validated using observed daily streamflow data with the SWAT Calibration and Uncertainty Program (SWAT-CUP) software and through the manual modification of missed precipitation data. Three tile drainage scenarios—ranging from 15% to 75% tile-drained agricultural land—were individually incorporated into the model. Results indicated that with increased tile drainage, surface runoff, groundwater flow, deep aquifer recharge, and percolation decreased, whereas lateral soil flow, tile flow, evapotranspiration, and water yield increased. A comparison of tile drainage scenarios suggests that increasing the area of tile-drained agricultural land decreases total flood days. However, the impact of tile drainage systems on downstream peak flood flows varied by event, with large precipitation events initiating flood days across all scenarios. While tile flow decreased flood days on a daily time step, flash floods might have occurred on a sub-daily time step but were not captured in this study. Future studies can replicate the approach with a sub-daily time step for simulating hourly flood events with various tile drainage scenarios. Keywords: Midwestern United States, Streamflow, SWAT, Tile drainage, Watershed hydrology.

Stormwater Runoff Control and Water Resource Utilization Technology of Central China Normal University Based on Stormwater Flood Management Modeling

In recent years, more and more prominent urban flooding problems on campus drainage system planning and design put forward higher requirements. Sudden rainfall can have multiple negative impacts on campuses, but it is also an excellent opportunity to utilize rainwater resources. At present, the peak flow rate of urban drainage system in China is still mainly calculated by the inference formula method, and the design return period of municipal drainage system is also low, which may lead to campus flooding in case of large rainstorms. In this paper, using the Stormwater Flood Management Model (SWMM) as a platform, the Central China Normal University (CCNU) was selected to simulate the summer stormwater runoff process, and three different combinations of low-impact development (LID) facilities were applied to the campus stormwater runoff control, and the control effects of the different combinations on the flood peak flow abatement were compared. The results show that the selected LID deployment scheme is better than the single facility control effect. Finally, based on the results of the study, a technical solution for rainwater collection and reuse based on sponge campus was proposed to renovate and design the campus landscape of Central China Normal University. The economic, social and environmental benefits are significant and can provide a reference for rainwater collection on other campuses.

Impacts of climate change on streamflow of Qinglong River, China

Abstract Climate change significantly influences water resources and flood hazards in global watersheds. This study focuses on predicting the impact of climate change on the streamflow of the Qinglong River situated in northern China. The streamflow of the Qinglong River (2021-2100) under two climate change scenarios (RCP 4.5 and RCP 8.5) was mainly synthesized over multiple timescales. Meteorological data from 31 Global Climate Models (GCMs) in the Coupled Model Intercomparison Project Phase 5 (CMIP5) served as inputs for the Hydrological Simulation Program-Fortran (HSPF) to conduct hydrological simulations. Results show that: (1) The peak flood flow and average daily streamflow for the RCP4.5 scenario are at least 101.15% and 110.14% of the historical phase, and at least 108.89% and 121.88% of the historical phase for the RCP8.5 scenario. (2) Under both scenarios, the proportion of summer streamflow to the annual total is expected to increase from 61.46% (historical phase) to over 85%, while the proportion of winter streamflow to the annual total is expected to decrease from 8.84% (historical phase) to below 0.5%. (3) Compared to the historical period, the maximum increase in future multi-year average annual streamflow for the RCP4.5 and RCP8.5 scenarios is 30.34%, 31.48%, respectively.

The testing of a multivariate probabilistic framework for reservoir safety evaluation and flood risks assessment in Slovakia: A study on the Parná and Belá Rivers

Abstract Intense floods represent a challenge to risk management. While they are multivariate in their nature, they are often studied in practice from univariate perspectives. Classical frequency analyses, which establish a relation between the peak flow or volume and the frequency of exceedance, may lead to improper risk estimations and mitigations. Therefore, it is necessary to study floods as multivariate stochastic events having mutually correlated characteristics, such as peak flood flow, corresponding volume and duration. The joint distribution properties of these characteristics play an important role in the assessment of flood risk and reservoir safety evaluation. In addition, the study of flood hydrographs is useful because of the inherent dependencies among their practice-relevant characteristics present on-site and in the regional records. This study aims to provide risk analysts with a consistent multivariate probabilistic framework using a copula-based approach. The framework respects and describes the dependence structures among the flood peaks, volumes, and durations of observed and synthetic control flood hydrographs. The seasonality of flood generation is respected by separate analyses of floods in the summer and winter seasons. A control flood hydrograph is understood as a theoretical/synthetic discharge hydrograph, which is determined by the flood peak with the chosen probability of exceedance, the corresponding volume, and the time duration with the corresponding probability. The framework comprises five steps: 1. Separation of the observed hydrographs, 2. Analysis of the flood characteristics and their dependence, 3. Modelling the marginal distributions, 4. A copula-based approach for modelling joint distributions of the flood peaks, volumes and durations, 5. Construction of synthetic flood hydrographs. The flood risk assessment and reservoir safety evaluation are described by hydrograph analyses and the conditional joint probabilities of the exceedance of the flood volume and duration conditioned on flood peak. The proposed multivariate probabilistic framework was tested and demonstrated based on data from two contrasting catchments in Slovakia. Based on the findings, the study affirms that the trivariate copula-based approach is a practical option for assessing flood risks and for reservoir safety.

Sequential riparian vegetation alteration in Japanese river landscapes

Bare gravel bed channels have been a common landscape feature of the middle reaches of rivers throughout Japan. They are disappearing these days because of vegetation colonization. Vegetation coverage of the riparian zones in the midstream reaches of rivers distributed throughout Japan was investigated using aerial photo images taken in 1946, 1975, and 2010. It was then compared with hydrological and water quality records, locations of dams and weirs, residential conditions of the surrounding areas, sediment yields, and forest coverage of the upstream mountainous areas. Riparian vegetation coverage has substantially increased in the last 70 years, from nearly 0 to 30-40%. Herbaceous vegetation coverage is higher than tree coverage. The total vegetation coverage did not correlate with water quality parameters. However, vegetation coverage had a significant negative correlation with the upstream basin's sediment yield and a slight negative correlation with the maximum flood peak flow rate. It was positively correlated with the terrestrial area fraction between levees. Riparian vegetation coverage was high within the 2 km downstream of dams or weirs, intercepting sediment flows. These results indicated that the gravelly sediment supplied from the upstream and deposited in the midstream at flood time has been the major contributor to keeping the vegetation coverage low rather than flushing by flood water. Reforestation since World War II has reduced the coarse sediment supply into the midstream river channels. This reforestation, together with gravel mining and intercepting sediment flow by dams and weirs, has caused the recent increase in vegetation coverage of the riparian zones. Human intervention can affect the vegetation conditions in riparian zones by decreasing sediment supply to river channels.

Different responses of event-based flood to typhoon and non-typhoon rainstorms under land use change in Xixi Basin of southeastern China

There are two major types of rainstorms in the Asia-Pacific region –typhoon induced rainstorm and non-typhoon rainstorm. This study investigated and separated the different flood responses to these two types of rainstorms, based on a scheme that combined the classification of typhoon and non-typhoon rainstorm floods, the simulation from a distributed hydrological model, and a method to forward restore the impact of land use change on flood frequency analysis. For flood events in a typical basin on the southeast coast of China, the flood characteristics in response to typhoon and non-typhoon rainstorms were significantly different in three aspects: (1) The key parameters in the HEC-HMS model were systematically different. The initial loss and wave velocity of the model were apparently larger for the typhoon rainstorm flood than for the non-typhoon rainstorm flood. (2) The impacts of land use change were different, with smaller effect on typhoon induced floods than on non-typhoon floods under the same magnitude of flood peak flow. (3) Classification of two types of floods resulted in more reasonable frequency analysis affected with the land use change because the annual maximum flood series is the mixture of typhoon and non-typhoon rainstorms. Frequency analysis for the forward-restored mixture flood series showed that the land use change with the decrease in the area of forest land and the increase of garden and construction land resulted in the increase of the mean maximum flow from 2266.6 to 2510.19 m3/s, but the values of coefficient of variation were slightly altered, the ratio of skewness coefficient to variation coefficient were unchanged. The results provide new ideas and methods for a deeper understanding of the impact of land use change on flooding in typhoon and non-typhoon co-action regions.

A distributed hydrological model for semi-humid watersheds with a thick unsaturated zone under strong anthropogenic impacts: A case study in Haihe River Basin

In the past decades, human activities, including hydraulic structure construction and operation, and groundwater overexploitation have largely changed the land surface conditions and correspondingly altered the natural rainfall-runoff processes. These changes make the traditional operational flood forecasting models without considering these anthropogenic impacts fail to capture these changes, leading to a downgraded forecasting capability. To improve the accuracy of flood forecasting in semi-humid watersheds under strong aboveground and underground anthropogenic impacts, the widely used operational flood forecasting model, the Xin’anjiang model, was chosen as a basis to build a new distributed hydrological model accounting for these anthropogenic impacts. To characterize the runoff generation process under the condition of a thick unsaturated zone caused by groundwater overexploitation, this study developed a runoff generation algorithm based on an idea that conceptualizes the soil free-water storage into two virtual reservoirs. To characterize the impacts of manmade reservoirs on the runoff concentration process, we modified the Muskingum method. In addition, we further developed a priori estimation method for deriving the spatial distribution of the tension water storage capacity by considering the anthropogenic impacts and geographical conditions. Based on the above work, a Grid Xin’anjiang-Haihe model (GXH) was developed. In this study, the Qingshui River, which is a tributary of the Haihe River Basin and a typical semi-humid medium-sized watershed in China with poor flood forecasting accuracy, was selected as the study area to test the effectiveness of the model. The results show that the GXH model can simulate the flood peak flow and peak time with higher accuracy than the current operational flood forecasting models and several other models. In addition, the parameter estimation method developed in this study has also proven to be superior in theory and practice.

Bivariate copula for flood frequency analysis in Johor river basin

Flooding is a multi-attribute event that is described by many factors such as peak flow and flood volume. It is extremely vital to consider both the flood volume and the flood peak while studying the flood frequency analysis as the univariate analysis cannot accurately portray the flood issue and suffers from an underestimation and an overestimation problem. Traditional univariate and multivariate modeling techniques have several mathematical shortcomings including the inability to distinguish between the marginal and joint behavior of the variables under study. Therefore, the copula function was introduced to tackle the above restriction. Six copula models will be applied in this study to find the best bivariate distribution between the flood variables in Johor River Basin, Malaysia, including Gaussian, Student-t, Clayton, Gumbel, Frank, and Joe. Before that, several marginal distributions were fitted to select the most appropriate distribution for flood variables. It was found that the Pearson Type-III fits both the flood peak flow and the flood volume best. The evaluation of the best univariate marginal distribution and the copula model will be based on Akaike Information Criterion (AIC). Our findings suggested that Frank Copula is more suited to represent the relationship between peak flow and flood volume as it portrays the lowest AIC values of -69.41 and highest log-likelihood values of 35.7, where both values outperform the other proposed copula models. However, future research which considers all three flood variables which are peak flow, volume, and duration should be conducted to attain a more reliable result.

A WRF/WRF-Hydro Coupled Forecasting System with Real-Time Precipitation–Runoff Updating Based on 3Dvar Data Assimilation and Deep Learning

This study established a WRF/WRF-Hydro coupled forecasting system for precipitation–runoff forecasting in the Daqing River basin in northern China. To fully enhance the forecasting skill of the coupled system, real-time updating was performed for both the WRF precipitation forecast and WRF-Hydro forecasted runoff. Three-dimensional variational (3Dvar) multi-source data assimilation was implemented using the WRF model by incorporating hourly weather radar reflectivity and conventional meteorological observations to improve the accuracy of the forecasted precipitation. A deep learning approach, i.e., long short-term memory (LSTM) networks, was adopted to improve the accuracy of the WRF-Hydro forecasted flow. The results showed that hourly data assimilation had a positive impact on the range and trends of the WRF precipitation forecasts. The quality of the WRF precipitation outputs had a significant impact on the performance of WRF-Hydro in forecasting the flow at the catchment outlet. With the runoff driven by precipitation forecasts being updated by 3Dvar data assimilation, the error of flood peak flow was decreased by 3.02–57.42%, the error of flood volume was decreased by 6.34–39.30%, and the Nash efficiency coefficient was increased by 0.15–0.52. The implementation of LSTM can effectively reduce the forecasting errors of the coupled system, particularly those of the time-to-peak and peak flow volumes.

Comparative Study of Flood and Long-term Mean Monthly Flow Estimation Approaches: Case Studies of Six Basins in Nepal

&#x0D; &#x0D; &#x0D; Most of Nepal's river basins have poor hydro- meteorological databases, with several river basins being ungauged. Thus, hydrological parameters need to be estimated using different types of computation methods. The primary goal of this study is to identify the most accurate method for calculating peak flood and long-term mean monthly flow among the most commonly used methods in Nepal. We compared the peak flood calculated using various flood computation formulas, such as Hydest, Modified Hydest, MHSP (Medium Hydropower Study Project) 1997, Modified Dickens, PCJ (Prem Chandra Jha) 1996, Rational, and Specific Discharge, to the flood calculated using gauged discharge data frequency analysis. We find that it is wise to use the Modified Hydest method in the khokana basin for all Return Periods (RPs) and in the Belkot basin (for RP ≤ 100 years), the Specific Discharge method in the Jamu basin, the MHSP 1997 method in the Belkot basin (for RP ≤ 100 years) and the Bagasoti Gaun basin (for RP ≤ 20 years). The PCJ 1996 method having the lowest cumulative value of Root Mean Square Error (RMSE) for the six studied catchments is suitable for Rabhuwa Bazar (for RP &gt; 50 years) and Bagasoti Gaun (for RP &gt;20 years). Similarly, the Modified Dickens method is suitable in the Bagasoti Gaun basin for RP ≤ 50 years. This paper also shows the performance of the Hydest and MHSP 1997 mean flow estimation methods and suggests different coefficients or constants to be used with the MHSP 1997, Modified MIP (Medium Irrigation Project), and Hydest methods to obtain more reliable long-term mean monthly flows. Overall, our study will help the designer choose a reliable method for design flow estimation. This study also shows that the flow obtained from even the most suitable methods needs to be adjusted. As a result, intensive research is required to adjust previous methods and develop the new one.&#x0D; &#x0D; &#x0D;

Flood Control Optimization of Reservoir Group Based on Improved Sparrow Algorithm (ISSA)

The optimal control problem of reservoir group flood control is a complex, nonlinear, high-dimensional, multi-peak extremum problem with many complex constraints and interdependent decision variables. The traditional algorithm is slow and easily falls into the local optimum when solving the problem of the flood control optimization of reservoir groups. The intelligent algorithm has the characteristics of fast computing speed and strong searching ability, which can make up for the shortcomings of the traditional algorithm. In this study, the improved sparrow algorithm (ISSA) combining Cauchy mutation and reverse learning strategy is used to solve the flood control optimization problem of reservoir groups. This study takes Sanmenxia Reservoir and Xiaolangdi Reservoir on the mainstream of the Yellow River as the research object and Huayuankou as the downstream control point to establish a joint flood control optimization operation model of cascade reservoirs. The results of the improved sparrow algorithm (ISSA), particle swarm optimization (POS) and sparrow algorithm (SSA) are compared and analyzed. The results show that when the improved ISSA algorithm is used to solve the problem, the maximum flood peak flow of the garden entrance control point is 11,676.3 m3, and the peak cutting rate is 48%. The optimization effect is obviously better than the other two algorithms. This study provides a new and effective way to solve the problem of flood control optimization of reservoir groups.

Remote Sensing-Supported Flood Forecasting of Urbanized Watersheds—A Case Study in Southern China

Urbanization has significant impacts on watershed hydrology, but previous studies have been confirmatory and not comprehensive; in particular, few studies have addressed the impact of urbanization on flooding in highly urbanized watersheds. In this study, this effect is studied in Chebei Creek, a highly urbanized watershed in the Pearl River Delta, southern China. Landsat satellite images acquired in 2015 were used to estimate land use and cover changes using the Decision Tree (DT) C4.5 classification algorithm, while the Liuxihe model, a physically based distributed hydrological model (PBDHM), is employed to simulate watershed flooding and hydrological processes. For areas with high degrees of urbanization, the duration of the flood peak is only 1 h, and the flood water level shows steep rises and falls. These characteristics increase the difficulty of flood modeling and forecasting in urbanized areas. At present, hydrological research in urbanized watersheds generally focuses on the quantitative simulation of runoff from urban areas to the watershed, flood flows, peak flood flow, and runoff depth. Few studies have involved real-time flood forecasting in urbanized watersheds. To achieve real-time flood forecasting in urbanized watersheds, PBDHMs and refined underlying surface data based on remote sensing technology are necessary. The Liuxihe model is a PBDHM that can meet the accuracy requirements of inflow flood forecasting for reservoir flood control operations. The accuracies of the two flood forecasting methods used in this study were 83.95% and 97.06%, showing the excellent performance of the Liuxihe model for the real-time flood forecasting of urbanized rivers such as the Chebei Creek watershed.

Study on Waterlogging Reduction Effect of LID Facilities in Collapsible Loess Area Based on Coupled 1D and 2D Hydrodynamic Model

The accurate evaluation method of LID toward the attenuation of urban flood is still a hot issue. This paper focuses on a coupled 1D and 2D hydrodynamic model, investigating the model parameters set in a collapsible loess area, and the changes in the surface runoff, waterlogged area, and drainage network indicators under different rainfall patterns. The results show that the coupled model can effectively simulate the effect of LID facilities under unaltered and retrofitted conditions. It is found that the infiltration parameters in a collapsible loess area are higher than in other eastern cities by calibration and validation. After implementing the LID facilities, the total runoff, peak flood flow, waterlogged area, runoff coefficient, and drainage pressure under different rainfall patterns have all been reduced. With the increases in the rainfall return period, the waterlogging reduction effect of LID facilities would gradually weaken. The rainfall return period has a great impact on the indicators of surface runoff, waterlogged area, and drainage capacity. The coefficient of rainfall peak has a relatively big impact on indicators of pipelines, such as the proportion of overflow nodes, the proportion of fully loaded pipelines, and the average full-load duration. The rainfall duration has a major impact on the total runoff quantity, runoff coefficient, and average full-load duration.