Flood Peak Discharge Research Articles

A numerical coupled atmospheric–hydrologic modeling system for probable maximum flood estimation with application to California's southern Sierra Nevada foothills watersheds

AbstractEstimation of probable maximum flood (PMF) is a crucial process in water resources management and in the design of large hydraulic structures. However, there are uncertainties in the estimation of hydrologic conditions that contribute to extreme floods. In particular, this is the case in snow‐dominated regions, as surface air temperature and wind speed are understood to have a substantial effect on the magnitude of a flood during a storm event. Motivated by the development of a new approach to investigate and estimate reliable PMF values and in an attempt to resolve the uncertainty issues, this study introduces a physically based modeling approach. For the case study, seven watersheds located in the Sierra‐Nevada mountain range of California, including Cosumnes, Mokelumne, Stanislaus, Tuolumne, Merced, Upper San Joaquin, and Upper Kings were selected. The hydroclimate model was first implemented over the physical boundaries of the study region, and then utilized to simulate possible maximum flood conditions with input from 10 extreme precipitation scenarios. The study results provide evidence of a nonlinear atmospheric–hydrologic system; the extreme 72‐h basin‐averaged precipitation depth was found not to be linearly proportional to 72‐h flow volume equivalent depth. It can also be concluded that a large precipitation depth may not be the sole reason for a large flood event. Temperature and other atmospheric variables also contribute significantly to the production of snowfall and liquid water available for runoff, and to the resulting hydrologic response, such as the flood peak discharge and volume.

Analysis of Flood Peak Discharge Based on Watershed Shape Factors

Regression analysis can develop unit hydrograph modeling by approaching the peak discharge (Qp) and time to peak (Tp) parameters. The main aim of this study is to design a model of peak discharge based on watershed shape factors. The watersheds used in this study are Bontojai Watershed, Jonggoa Watershed, Kampili Watershed, Maccini Sombala Watershed, and Jenelata Watershed, which have slopes criteria below 10% and have complete recorded data of Automatic Water Level Recorder (AWLR) and Automatic Rainfall Recorder (ARR). The validation results of corrected peak discharge data produce Root Mean Squared Error (RMSE). Then, the peak discharge model was conducted by regression analysis and validated with observed unit hydrographs. The results of this study indicate that the coefficient of determination R2 is 0.963. It means that the independent variable (x), namely the area of the watershed, the length of the main river, and the shape factor of the watershed, influences the peak discharge (Qp) of 96.3%

Analysing the Performance of Four Hydrological Models in a Chinese Arid and Semi-Arid Catchment

Frequent flood hazards in the Raoyang River Basin in western Liaoning, China, have posed serious threats to people’s lives and property. In an effort to study the simulation efficiencies of hydrological models in this arid and semi-arid catchment, this study examined the performance of the Xin’anjiang model, the Liaoning unsaturated model, and the DHF model in the Dongbaichengzi station watershed in the upper reaches of the Raoyang River, China. Additionally, this paper proposed an improved DHF model, which considers the impoundment and regulation of small- and medium-sized reservoirs in the upper reaches of the basin. The flood simulation results demonstrated that the Xin’anjiang model was difficult to apply in this area because the average value of its Nash–Sutcliffe efficiency (NSE) was as low as 0.31. Meanwhile, the simulation efficiencies of the Liaoning unsaturated model and the DHF model were higher than that of the Xin’anjiang model, but the relative error of flood peak discharge and runoff depth for most floods were still high and could not meet the actual forecast requirements by the Reservoir Administration Bureau of Liaoning Province. Overall, the improved DHF model showed the best efficiency, and the mean value of the NSE reached 0.79. Therefore, the improved DHF model has good applicability in the Dongbaichengzi station watershed in the upper reaches of the Raoyang River, China.

What Controls the Magnitude and the Shape of Landslide Dam-Breaching Flood Hydrograph? Case Studies of Emergent Forecasts for Outburst Floods of Jiala and Baige Barrier Lakes

Outburst floods released by failing barrier dams are likely to be catastrophic, posing high risk to downstream areas. However, emergent forecasting of the breaching process is still challenging due to the complex mechanisms as well as the lack of adequate data. During October and November 2018, four tremendous barrier lakes formed and breached on the Jinsha River and the Yarlung Zangbo River, China. In this paper, we present numerical simulations for three of these events (October 17 and October 29 at Jiala Village, Yarlung Zangbo; November 3 at Baige Village, Jinsha River), and investigate what factors control the magnitude and shape of the hydrograph of the outburst flood. A physically-based dam-breach model was established for the prediction. We first specified the model parameters based on the aerial images, DEM data and hydrological measurements during the emergency treatment. With these parameters, the model can successfully predict the breaching process of the two barrier dams in the Yarlung Zangpo, but underpredict the peak discharge of the outburst flood in the Jinsha River. The outburst flood in the Jinsha River, however, can be well-reproduced with refined information on dam height and grain size distribution. Moreover, both field data and our numerical simulation showed that the magnitude and shape of the outburst flood hydrograph can be affected by the dam morphology and the composition of dam material. Two patterns of outburst flood hydrographs with different symmetry characteristics were identified using statistical analysis. The approximately symmetrical breach hydrograph of the “November 3” Baige barrier lake could be partly attributed to the relatively fine grain size distribution of the dam material.

A short-term flood prediction based on spatial deep learning network: A case study for Xi County, China

Floods cause substantial damage across the world every year. Accurate and timely prediction of floods can significantly minimize the loss of life and property. Recently, numerous machine learning models have been used for flood prediction, showing that their performance is preferable to traditional statistical models. However, the existing models neglect the spatial features of floods, which drive flood generation and concentration. In this paper, the area of interest is divided into grids based on longitude and latitude, and the rainfall and discharge collected by stations are combined into tensors according to station coordinates. Different from one-dimensional time series, our input feature is a two-dimensional time series with spatial information. Hence, combining a Convolutional Neural Network (CNN) with a Long Short Term Memory Network (LSTM), we propose the convolution LSTM (ConvLSTM) to extract spatiotemporal features of hydrological information. The methodology is demonstrated using the hydrological data collected at the Xi County stations, located on the Huai River in Henan Province, China. Numerical results indicate that the relative error of arrival time is within 30%, and the relative error of peak discharge is within 20%, satisfying the 2005 Chinese Water Resource Standard on flood prediction permit error. The experiments also show that the ConvLSTM outperforms the recent models in terms of flood arrival time and peak discharge, thereby proving a promising alternative.

Long-period variability in ice-dammed glacier outburst floods due to evolving catchment geometry

Abstract. We combine a glacier outburst flood model with a glacier flow model to investigate decadal to centennial variations in outburst floods originating from ice-dammed marginal basins. Marginal basins can form due to the retreat and detachment of tributary glaciers, a process that often results in remnant ice being left behind. The remnant ice, which can act like an ice shelf or break apart into a pack of icebergs, limits a basin's water storage capacity but also exerts pressure on the underlying water and promotes drainage. We find that during glacier retreat there is a strong, nearly linear relationship between flood water volume and peak discharge for individual basins, despite large changes in glacier and remnant ice volumes that are expected to impact flood hydrographs. Consequently, peak discharge increases over time as long as there is remnant ice remaining in a basin, and peak discharge begins to decrease once a basin becomes ice-free. Thus, similar size outburst floods can occur at very different stages of glacier retreat. We also find that the temporal variability in outburst flood magnitude depends on how the floods initiate. Basins that connect to the subglacial hydrological system only after reaching flotation depth yield greater long-term variability in outburst floods than basins that are continuously connected to the subglacial hydrological system (and therefore release floods that initiate before reaching flotation depth). Our results highlight the importance of improving our understanding of both changes in basin geometry and outburst flood initiation mechanisms in order to better assess outburst flood hazards and their impacts on landscape and ecosystem evolution.

Quantifying the influence of urban development on runoff in South Africa

ABSTRACT It is widely accepted that urban development results in larger flood peak discharges with faster catchment response times, larger total runoff volumes and lower base flow volumes. However, these effects have not previously been studied in the context of the specific characteristics of fast-growing urban areas in developing countries, which are generally unregulated. This study quantifies the effects of urban development on runoff, including: a) runoff volumes, b) base flow volumes and c) flood peaks from eight South African catchments using the Mann–Kendall test and Kendall’s τ. Both total runoff and base flow volumes are found to increase with increased development levels and possible reasons for this are discussed. The flood peak analysis finds statistically insignificant trends in most catchments. However, there is an increasing trend in the catchment with the highest proportion of informal development. Recommendations are made for further investigation into reasons for the findings.

Selected Crater and Small Caldera Lakes in Alaska: Characteristics and Hazards

This study addresses the characteristics, potential hazards, and both eruptive and non-eruptive role of water at selected volcanic crater lakes in Alaska. Crater lakes are an important feature of some stratovolcanoes in Alaska. Of the volcanoes in the state with known Holocene eruptive activity, about one third have summit crater lakes. Also included are two volcanoes with small caldera lakes (Katmai, Kaguyak). The lakes play an important but not well studied role in influencing eruptive behavior and pose some significant hydrologic hazards. Floods from crater lakes in Alaska are evaluated by estimating maximum potential crater lake water volumes and peak outflow discharge with a dam-break model. Some recent eruptions and hydrologic events that involved crater lakes also are reviewed. The large volumes of water potentially hosted by crater lakes in Alaska indicate that significant flowage hazards resulting from catastrophic breaching of crater rims are possible. Estimates of maximum peak flood discharge associated with breaching of lake-filled craters derived from dam-break modeling indicate that flood magnitudes could be as large as 103–106 m3/s if summit crater lakes drain rapidly when at maximum volume. Many of the Alaska crater lakes discussed are situated in hydrothermally altered craters characterized by complex assemblages of stratified unconsolidated volcaniclastic deposits, in a region known for large magnitude (>M7) earthquakes. Although there are only a few historical examples of eruptions involving crater lakes in Alaska, these provide noteworthy examples of the role of external water in cooling pyroclastic deposits, acidic crater-lake drainage, and water-related hazards such as lahars and base surge.

Flood Generation Mechanisms and Potential Drivers of Flood in Wabi-Shebele River Basin, Ethiopia

Flood is a natural process generated by the interaction of various driving factors. Flood peak flows, flood frequency at different return periods, and potential driving forces are analyzed in this study. The peak flow of six gauging stations, with a catchment area ranging from 169 - 124,108 km2 and sufficient observed streamflow data, was selected to develop threshold (3rd quartile) magnitude and frequency (POTF) that occurred over ten years of records. Sixteen Potential climatic, watershed and human driving factors of floods in the study area were identified and analyzed with GIS, Pearson’s correlation, and Principal Correlation Analysis (PCA) to select the most influential factors. Eight of them (MAR, DA, BE, VS, sand, forest AGR, PD) are identified as the most significant variables in the flood formation of the basin. Moreover, mean annual rainfall (MAR), drainage area (DA), and lack of forest cover are explored as the principal driving factors for flood peak discharge in Wabi-Shebele River Basin. Finally, the study resulted in regression equations that helped plan and design different infrastructure works in the basin as ungauged catchment empirical equations to compute QMPF, Q5, Q10, Q50, and Q100 using influential climate, watershed, and human driving factors. The results of these empirical equations are also statistically accepted with a high significance correlation (R2 > 0.9).

Urban flood forecasting based on the coupling of numerical weather model and stormwater model: A case study of Zhengzhou city

Study regionUrban built-up area of Zhengzhou, China. Study focusA coupled urban flood forecasting model based on WRF-SWMM is proposed. Different spatial resolution data as input for WRF (Weather Research and Forecasting Model) to study the characteristics of forecasting precipitation, combined with measured precipitation series, the SWMM (Storm Water Management Model) was driven to forecast the urban flood process. New hydrological insights for the study regionUsing the WRF-SWMM coupling model to simulate flood disasters can effectively improve the timeliness of urban flood prediction. The results indicate that a spatial resolution of 0.25-degree improved the overall precipitation prediction results. With an increase in lead time, the prediction performance of the WRF decreased. The WRF model can simulate results effectively owing to its sensitivity to bimodal rainfall patterns. When the WRF model produces an overestimate (or underestimate), part of the urban canals in the SWMM model will also carry out a high forecast (or low forecast) output of flood peak discharge. The SWMM model also has a cumulative amplification effect on the results of flood simulation. In addition, the quantitative accuracy of precipitation forecasts plays a vital role in urban flood simulation, and the existing coupling models based on WRF-SWMM can generate reasonable forecasts 3–6 h in advance.

Urban flood susceptibility evaluation and prediction during 2010\u20132030 in the southern watersheds of Mashhad city, Iran

BackgroundUrban flood susceptibility evaluation (FSE) can utilize empirical and rational procedures to focus on the urban flood evaluation using physical coefficients and land-use change ratios. The main aim of the present paper was to evaluate a flood susceptibility model in the southern watersheds of Mashhad city, in Iran, for 2010, 2020, and 2030. The construction of the model depended on the utilization of some global datasets to estimate the runoff coefficients of the watersheds, peak flood discharges, and flood susceptibility evaluations.Results and conclusionsBased on the climatic precipitation and urban sprawl variation, our results revealed the mean values of the runoff coefficient (Cr) from 0.50 (2010) to 0.65 (2030), where the highest values of Cr (> 0.70) belonged to the watersheds with real estate cover, soil unit of the Mollisols, and the slope ranges over 5–15%. The averagely cumulative flood discharges were estimated from 2.04 m3/s (2010) to 5.76 m3/s (2030), revealing an increase of the flood susceptibility equal 3.2 times with at least requirement of an outlet cross-section by > 46 m2 in 2030. The ROC curves for the model validity explained AUC values averagely over 0.8, exposing the very good performance of the model and excellent sensitivity.

Changes in stream power and morphological adjustments at the event-scale and high spatial resolution along an ephemeral gravel-bed channel

Sediment budgets and morphological channel adjustments are closely related to changes in stream power. In ephemeral channels, whose geomorphic response depends on the magnitude and frequency of hydrological events isolated in time, such relationships are often difficult to establish. This study sought to quantitatively relate morphological adjustments to stream power along different reference channel reaches for the period 2018–2020 in the Azohía Rambla, a Mediterranean gravel-bed ephemeral stream in southeastern Spain. Very high resolution digital terrain models (VHR DTM) (at 1 to 2.5 cm pixel size), combined with ortophotographs and 3D point clouds, generated via SfM photogrammetry and terrestrial laser scanning (TLS) for pre- and post-event stages, together with ground-based surveys were used to estimate the spatial variability of morphological sediment budgets and to assess channel bed mobility and changes in net sediment flux during the study period in two spatial scenarios: reference channel reaches (RCRs) and pilot bed survey areas (PBSAs). The hydraulic variables (flow velocity, Froude number, shear stress, mean stream power and energy gradient, among other) were estimated using a 1D hydrodynamic model calibrated with field information. The high resolution maps allowed a spatially-explicit analysis of stream power and transport efficiency in accordance with the areas of erosion and deposition in each RCR. The incision and bed armoring processes showed different trends according to the stream power (ω), cumulative excess energy (εc), and relative bed stability (RBS). The greatest morphological adjustments at the event scale coincided with ω values above 300 W m−2, εc higher than 3 MJ, and RBS below 0.5. The relationships between the mean stream power gradient at peak flood discharges and the changes in bed elevation verified the bed aggradation (an average surface raising of 0.17 to 0.22 m for δω/δs of −6.2 to −14.5 W m−2 m−1) during the major flood and bed scour (average surface lowering of 0.16 to 0.19 m for δω/δs of 5.8 to 10.6 W m−2 m−1) in the moderated events at the bankfull and sub-bankfull stages. Furthermore, this study contributes new relevant data to the scarce existing literature on the relationships between stream power and morphosedimentary adjustments in a fluvial system highly sensitive and resilient to climate change, as is the case of ephemeral gravel-bed channels.

Integrating historical, geomorphological and sedimentological insights to reconstruct past floods: Insights from Kea Point, Mt. Cook Village, Aotearoa New Zealand

Flood reconstruction is essential for establishing magnitude-frequency relationships and assessments of contemporary geohazards and risks. Traditionally, flood reconstructions rely upon the analysis of evidence acquired from a single discipline. This lack of integration limits the insights into a flood's source, pathway, and receptors (i.e. impacts). Here, our aim is to test the integration of qualitative historical documentary material with quantitative geomorphological and sedimentological evidence to reconstruct glacial lake outburst floods (GLOFs) in 1913 at Kea Point, Mount Cook National Park, Aotearoa New Zealand. Written documentary records show that, following heavy rainfall, GLOF events occurred in January and March, after the temporary impoundment of water between the glacier surface and lateral moraine. Peak flood discharge was estimated from slope-area and exposed boulder measurements as 316–1077 m3s−1 and 496–1622 m3s−1 respectively. Sedimentological information, combined with geomorphic mapping, a DEM derived from Structure from Motion (SfM) photogrammetry, and satellite imagery was used to describe the overall physical impact of the GLOF. Information from written documentary records, however, enabled a more detailed reconstruction of the timeline of the two floods and their impacts proximate to the original ‘Hermitage Hotel’, which was subsequently relocated. Our integrated approach exemplifies the informative level of multi-faceted detail that can be retrieved for historical flood events. We propose a framework for future studies that seek to reconstruct flood events and their source, pathway and receptors through combining evidence from historical documents/artefacts, sedimentological/geomorphological data, and integration with environmental monitoring/modelling outputs.

The Upper Tail of Flood Peaks Over China: Hydrology, Hydrometeorology, and Hydroclimatology

AbstractCharacterizing the upper tail of flood peak distributions remains a challenge due to the elusive nature of extreme floods. China has experienced some of the most extreme floods on Earth and is therefore an important setting for extreme flood research. Here, we examine the upper tail of flood peaks over China based on a comprehensive flood dataset that integrates systematic observations from 1759 stream gaging stations and 14,779 historical flood surveys. Floods with large upper tail ratios (i.e., flood peak discharge normalized by sample 10‐yr flood) cluster spatially in the windward regions of mountainous terrain with basin mean annual rainfall of around 550 mm. Large upper tail ratio floods are associated with a mixture of rainfall generation processes. These processes are characterized by anomalous moisture transport (e.g., zonal water vapor pathways) and/or synoptic configurations (e.g., blocking), with respect to flood‐producing storms for annual flood peaks. Downscaling simulations with the Weather Research and Forecasting model for the 1939, 1963, and 2016 floods over the North China Plain region highlight the role of interactions between complex terrain and large‐scale environment in defining the world envelope curve of flood peaks. The upper‐tail floods demonstrate a combination of ingredients producing extreme rainfall. Our results provide important insights to extreme floods in China and a frame of reference for assessing the largest floods on Earth.

Improving regional flood risk assessment using flood frequency and dendrogeomorphic analyses in mountain catchments impacted by tropical cyclones

River floods frequently occur when tropical cyclones hit land. Nonetheless, systematic, long-term discharge data remain rather scarce in many tropical countries, which prevent proper analysis of peak discharges occurring during floods. The Térraba catchment is the biggest and most dynamic catchment in Costa Rica. In this study, we developed regional flood-frequency analyses combining tree-ring based estimation and measurement of peak discharge at monitoring stations during tropical cyclones to derive flood quartiles. Flood quartiles were combined with the Topographic Wetness Index (TWI) to determine regional flood hazards along floodplains. The flood risk assessment was based on a high-resolution mapping of infrastructure, population density (as a measure of exposure), and a social development index (to represent vulnerability). We show that peak discharge of cyclone-induced floods can be assessed accurately with flood-frequency analyses including dendrogeomorphic reconstructions and systematic discharge measurements. We also show that regional flood risk assessments can be performed in large-scale catchments if both coarse and detailed inputs are used. The results of this study will be useful for the development of flood risk schemes promoting resilience of local populations.

Weakening flood, intensifying hydrological drought severity and decreasing drought probability in Northeast China

Study regionNortheast China Study focusNortheast China is one of the largest agricultural regions in the world and a strategically important granary for China. Information on hydrological extremes is crucially important for water management. Yet, comprehensive studies on hydrological extremes, both extreme flood and drought events, based on hydrological gauge comprehensive and large coverage observations are still lacking in Northeast China. This study investigated observed hydrological extremes with 124 hydrological gauges in the region ranging from the 1950s to present for the first time. New hydrological insights for the regionWe find that flood extremes, mean discharge and standardized discharge are decreasing in over 80% of the gauges, and no gauges show significantly increasing flood extremes. The findings suggest that sustainable water management strategies should be employed to meet increasing water demand for long-term development. In addition, we find that flood peak discharge and flood volume are significantly correlated in all the gauges, motivating flood risk studies considering multiple flood variables together. Further, we quantify probability changes of severe and extreme hydrological droughts, and find that the probability of drought events is decreasing in most of the gauges, suggesting that the number of drought events is reducing. Data availabilityDischarge data are from the hydrology bureau, and can be found by contacting Songliao River Water Resources Commission, Ministry of Water Resources, the People’s Republic of China (http://www.mwr.gov.cn/english/).

Experimental Investigation of the Outburst Discharge of Landslide Dam Overtopping Failure

Research on the factors and mechanisms that influence outburst floods are essential for estimating outflow hydrographs and the resulting inundation. In this study, large flume tests are conducted to investigate the effects of the upstream inflow and the presence of loose erodible deposits on the breaching flow and the subsequent outburst floods. Experimental results reveal that hydrographs of the breaching flow and outburst flood can be divided into three stages where each stage is separated by inflection points and peak discharges. It is found that the larger the inflow discharge, the larger the peak discharge of the outburst flood and the shorter the time needed to reach the peak and inflection discharges of the outburst flood. The breaching flow decreases along the longitudinal direction at rates that increase with the inflow discharge. The ratio between the length of the upstream dam shoulder and the dam width is inversely related to the ratio of the outburst discharge to inflow discharge. We also show that the presence of loose deposits at the dam toe can amplify the peak discharge of outburst flood by increasing the solids content of the water flow.

Utilization and uncertainties of satellite precipitation data in flash flood hydrological analysis in ungauged watersheds

<p>Aim of the study is to examine the potential utilization of satellite precipitation data to estimate the peak discharges of flash floods in ungauged Mediterranean watersheds. Cumulative precipitation heights from local rain gauge and the GPM-IMERG were correlated in a scatter plot. The calculated linear equations were used to adjust the uncalibrated GPM-IMERG precipitation data in Thasos island (Northern Greece), to investigate the mechanisms of the flash floods recorded in November 2019 and to evaluate the significance of satellite precipitation data in hydrological modeling. The uncalibrated GPM-IMERG precipitation failed to explain the flash floods phenomena. The rain gauge data are reliable to accurately predict the peak discharges only in cases, where the rain gauges are within the study area. The strong correlation between ground rainfall data and satellite spatiotemporal precipitation data (R2 > 0.65), provides linear regression equations that, through their extrapolation and appliance to the rest of the flooded area, could adjust and correct the satellite data, optimizing the efficiency and accuracy of flash flood analysis, especially in ungauged watersheds. The proposed methodology could highly contribute to the optimization of flood mitigation measures establishment, flood risk assessment, hydrological and hydraulic simulation of flash flood events in ungauged watersheds.</p>

Towards Predicting Flood Event Peak Discharge in Ungauged Basins by Learning Universal Hydrological Behaviors with Machine Learning

AbstractIn the hydrological sciences, the outstanding challenge of regional modeling requires to capture common and event-specific hydrologic behaviors driven by rainfall spatial variability and catchment physiography during floods. The overall objective of this study is to develop robust understanding and predictive capability of how rainfall spatial variability influences flood peak discharge relative to basin physiography. A machine learning approach is used on a high-resolution dataset of rainfall and flooding events spanning 10 years, with rainfall events and basins of widely varying characteristics selected across the continental United States. It overcomes major limitations in prior studies that were based on limited observations or hydrological model simulations. This study explores first-order dependencies in the relationships between peak discharge, rainfall variability, and basin physiography, and it sheds light on these complex interactions using a multi-dimensional statistical modeling approach. Amongst different machine learning techniques, XGBoost is used to determine the significant physiographical and rainfall characteristics that influence peak discharge through variable importance analysis. A parsimonious model with low bias and variance is created which can be deployed in the future for flash flood forecasting. The results confirm that although the spatial organization of rainfall within a basin has a major influence on basin response, basin physiography is the primary driver of peak discharge. These findings have unprecedented spatial and temporal representativeness in terms of flood characterization across basins. An improved understanding of sub-basin scale rainfall spatial variability will aid in robust flash flood characterization as well as with identifying basins which could most benefit from distributed hydrologic modeling.

Climate More Important for Chinese Flood Changes Than Reservoirs and Land Use

AbstractRiver regulations and changing land management practices are generally perceived to be the dominant drivers of river flood changes in countries with rapid economic growth, such as China. Here, we demonstrate based on the most comprehensive flood database to date, that climate variations dominate the spatial pattern of changes in annual flood peak discharge in China, despite intense human alterations of the river and land systems over the past four decades. Regional flood increases are mainly associated with increasing precipitation due to changes in the East Asian Summer Monsoon, tropical cyclones and the subtropical westerly jet. Regional flood decreases are due to decreased soil moisture in the North China plain. Our results highlight the need for flood management policies to go beyond local measures and adapt to the effects of climate change.