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Drought and floods seriously affect agriculture across the world. It is of great importance to lower down the agricultural vulnerability to disasters to build climate-resilient agriculture. The paper aims to investigate the spatio-temporal changes of agricultural vulnerability to drought and floods in the world in the period 2003-2019. Research results show that (1) the agricultural vulnerability to drought and floods is at a low level across the globe owning to the dual effects of decreasing exposure and increasing adaptability; (2) the northern parts of United States, northeastern parts of China, and the border between Russia and Kazakhstan are identified as most vulnerable areas to drought and floods; and (3) spatio-temporal mismatch of precipitation is the main factor to cause floods and drought while better adaption is beneficial to minimize the adverse effects of disasters. Based on analysis on the drivers and spatial patterns of drought and floods risk in all dimensions, tailored measures and policies are put forwards to make adaptive strategies of agriculture to climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Climate change is altering urban rainfall characteristics, leading to extreme urban stormwater and, particularly, more frequent flooding. Due to the uncertainty of climate change, the responses of urban drainage systems to climate change are becoming more complicated. This complexity makes it difficult for decision makers to assess whether urban infrastructure is sufficiently resilient to cope with flood risks. In this study, the Xiao Zhai area, a high-density urban area of China, was used as an example. A quantitative method for assessing these risks and the resilience of urban drainage systems to future urban stormwater was developed. First, based on the Coupled Model Intercomparison Project Phase 6 (CMIP6), the variation and uncertainty of future rainfall in the study area were analysed. A high-fidelity hydro-hydraulic model was developed to analyse the influence of climate change on future urban stormwater. Finally, the relationship between urban flood risk and the resilience of urban drainage systems was evaluated. The results show that the temporal distribution of future rainfall from 2023 to 2100 is relatively uniform. However, the number of heavy rainfall events increases significantly during this period. The flood risk caused by future rainfall was one level higher than the historical flood risk. For example, the flood risk caused by future 5a rainfall is equal to the flood risk from historical 10a rainfall. The correlations between the spatial distributions of flood risk and resilience are 0.49-0.63. Urban drainage systems urgently need to be improved and refined in areas with flood risk and low resilience to become more resilient to climate change. Rational planning of grey-green rainwater facilities in flood risk and low resilience areas can improve the rainwater system's resilience to 0.67-0.95 for climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Projecting future changes in extreme flood is critical for risk management. This paper presented an analysis of the implications of the Fifth Coupled Model Intercomparison Project Phase (CMIP5) climate models on the future flood in the Jinsha River Basin (JRB) in Southwest China, using the Xinanjiang (XAJ) hydrologic model. The bias-corrected and resampled results of the multimodel dataset came from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Relatively optimal general circulation models (GCMs) were selected with probability density functions (PDFs)-based assessment. These GCMs were coupled with the XAJ model to evaluate the impact of climate change on future extreme flood changes in the JRB. Two scenarios were chosen, namely: a midrange mitigation scenario (Representative Concentration Pathway 4.5, RCP4.5) and a high scenario (RCP8.5). Results show that: (1) The XAJ model performed well in simulating daily discharge and was suitable for the study area, with E NS and R ² higher than 0.8; (2) IPSL-CM5A-LR and MIROC-ESM-CHEM showed considerable skill in representing the observed PDFs of extreme precipitation. The average skill scores across the total area of the JRB were 0.41 to 0.66 and 0.53 to 0.67, respectively. Therefore, these two GCMs can be chosen to analyze the changes in extreme precipitation and flood in the future; (3) The average extreme precipitation under 20- and 50-year return period across the JRB were projected to increase by 1.0⁻33.7% under RCP4.5 and RCP8.5 during 2020 to 2050. The Upper basin is projected to experience the largest increase in extreme precipitation indices, possibly caused by a warmer climate. The extreme flood under 20- and 50-year return period will change by 0.8 to 23.8% and -6.2 to 28.2%, respectively, over this same future period. Most of scenarios projected an increase during the near future periods, implying the JRB would be likely to undergo more flooding in the future.

On 20 July 2021, an extreme rainstorm battered Zhengzhou in China's Henan Province, killing 302 people, including 14 individuals who drowned in a subway tunnel and 6 who drowned in a road tunnel. As the global climate warms, extreme weather events similar to the Zhengzhou flood will become more frequent, with increasingly catastrophic consequences for society. Taking a case study-based approach by focusing on the record-breaking Zhengzhou flood, this paper examines the governance capacity of inland cities in North China for managing extreme precipitation and flooding events from the perspective of the flood risk management process. Based on in-depth case analysis, our paper hypothesizes that inland cities in North China still have low risk perceptions of extreme weather events, which was manifested in insufficient pre-disaster preparation and prevention, poor risk communication, and slow emergency response. Accordingly, it is recommended that inland cities update their risk perceptions of extreme rainfall and flooding events, which are no longer low-probability, high-impact "black swans", but turning into high-probability, high-impact "gray rhinos." In particular, cities must make sufficient preparation for extreme weather events by revising contingency plans and strengthening their implementation, improving risk communication of meteorological warnings, and synchronizing emergency response with meteorological warnings. [ABSTRACT FROM AUTHOR]

In frequency analysis of annual maximum flood series (AMFS), it is mechanism‐based and significant to incorporate the information of the underlying "ordinary" daily streamflow events for improving accuracy of flood risk estimation and appropriate management. In previous studies related to flood nonstationarity, the classical norming constants method (C‐NCM) has been used to derive statistical parameters of annual maximum flood distribution from daily streamflow distribution. However, C‐NCM does not flexibly consider the feasible range of the scale parameter of annual maximum flood distributions, which can result in the inability to provide sufficient and reliable models to fit AMFS. This paper aims to investigate the potential of two alternative norming constants methods in fitting annual maximum floods, namely the Hall's norming constants method (H‐NCM) and the Fisher and Tippetts' norming constants method (FT‐NCM) respectively. A comparative study of these three methods was carried out using hydrological streamflow series of 77 stations in the Yangtze and Yellow River basins, China. The results found that H‐NCM outperforms both C‐NCM and FT‐NCM for the stations with relatively low‐skewness coefficient of AMFS. Therefore, H‐NCM is recommended to prioritize for practical applications when considering daily streamflow rather than small samples of flood events. Furthermore, if the skewness coefficient exceeds Cs,Gumbel≈1.14, the overall modelling performance of these three methods is significantly deteriorated. This can provide some reference for the applicability of the norming constants method in flood frequency analysis. [ABSTRACT FROM AUTHOR]

China is one of the countries that are most severely affected by floods worldwide. Due to the geographical and climatic environment, floods frequently occur in China. Rapid socioeconomic growth and urban sprawl in the past decades have significantly changed both exposure and vulnerability dimensions of flood risk in China. In response to high risks of flood, the Chinese government has adopted a series of effective measures, such as the "Spongy City" Program and building many large dams and reservoirs, and some measures have achieved significant results. However, there is still a lack of studies with an integrated view on analyzing the causes, socioeconomic impact trends, and disaster risk reduction (DRR) measures of flood risk in China in the past decades. Accordingly, this paper aims to fill in the gap and provides some new insights into China's contributions in DRR over the period of 1950–2019. Our results show that annual flood-induced fatalities and socioeconomic vulnerability to floods have significantly decreased in China, owing to a range of structural and non-structural measures. Nevertheless, China still faces the complex coupling effects of climate change and urbanization, and thus threats from extreme floods. In addition, China needs to further improve its flood risk management system. [ABSTRACT FROM AUTHOR]

The coincidence of flood flows in a mainstream and its tributaries may lead to catastrophic floods. In this paper, we investigated the flood coincidence risk under nonstationary conditions arising from climate changes. The coincidence probabilities considering flood occurrence dates and flood magnitudes were calculated using nonstationary multivariate models and compared with those from stationary models. In addition, the "most likely" design based on copula theory was used to provide the most likely flood coincidence scenarios. The Huai River and Hong River were selected as case studies. The results show that the highest probabilities of flood coincidence occur in mid-July. The marginal distributions for the flood magnitudes of the two rivers are nonstationary, and time-varying copulas provide a better fit than stationary copulas for the dependence structure of the flood magnitudes. Considering the annual coincidence probabilities for given flood magnitudes and the "most likely" design, the stationary model may underestimate the risk of flood coincidence in wet years or overestimate this risk in dry years. Therefore, it is necessary to use nonstationary models in climate change scenarios. [ABSTRACT FROM AUTHOR]

A mega-flood in 1998 caused tremendous losses in China and triggered major policy adjustments in flood-risk management. This paper aims to retrospectively examine these policy adjustments and discuss how China should adapt to newly emerging flood challenges. We show that China suffers annually from floods despite large-scale investments and policy adjustments. Rapid urbanization and climate change will exacerbate future flood risk in China, with cascading impacts on other countries through global trade networks. Therefore, novel flood-risk management approaches are required, such as a risk-based urban planning and coordinated water governance systems with public participation, in addition to traditional structural protection. [ABSTRACT FROM AUTHOR]

• The extent of flooding in China is greater than in any other country. • Nearly 66% of China's landmass is submerged by flooding. • Financial toll of flooding accounts for approximately 1.42% of the annual GDP. • Various forms of climatic change contribute to flooding. The extent of flooding in China is more significant than in any other country. Our research reveals that approximately 66 % of China's landmass is submerged by flooding, affecting about 50 % of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42 % of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. The floods in Henan province in 2021 caused considerable damage, including impacting nearly 15 million people, resulting in almost 400 deaths, damaging over 10,000 square kilometers of agricultural land, causing almost $19 billion in economic losses, and leading to the collapse of over 35,000 households and damage to various properties. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. We found that rainstorms have significantly increased to 10 % in the last 60 years in China. In this paper, we delved into exploring the existing published articles, reports, and government and authoritative legal texts to analyze the causes and impacts of flooding in China's flood-prone regions and potential mitigation strategies to reduce the repercussions of distressing flood events. We believe this study will help policymakers by providing new insights while formulating policy to reduce the loss caused by high-level flooding. [ABSTRACT FROM AUTHOR]

Sea level rise (SLR) and storm surge have significant impacts on tourism properties and activities in the low-lying coastal region. Coastal tourism in Zhejiang Province, China, is physically and socioeconomically susceptible to the flood risk posed by accelerated SLR and intensified storm surge. In this paper, within a scenario design of SLR and storm surge, a GIS-based dataset of major coastal tourist attractions in coastal Zhejiang is created to assess their potential flood risk by using a simple inundation model and a risk matrix. It is estimated that only two resorts would be directly flooded by a SLR of 1-2 m, but extensive inundation of coastal tourism communities may occur during low-frequency surges, especially after adding predicted 1-m SLR. The risk assessment further shows that a majority of the exposed sites is subject to moderate and low risk at current state but would be at higher (moderate and high)-risk categories in the future. In the long term, a combination of adaption measures is presented for policy-makers and other stakeholders for sustainable flood risk management in coastal tourism destinations. [ABSTRACT FROM AUTHOR]

[Display omitted] • We develop a framework to estimate future Flood Regulation Service (FRS) dynamics. • The framework considers the joint impacts of both climate change and urbanization. • Future FRS supply–demand imbalance will continue to intensify. • Future impacts of climate change in Baiyangdian Lake Basin cannot be ignored. • Cities should actively adapt to climate change to reduce flood risks in the future. Estimating the supply–demand relationship's future dynamics and trend of Flood Regulation Service (FRS) is important for preventing flood risks and choose an appropriate future development path. Less attention has been given to assessing the future trends in this relationship under the joint influence of climate change and urbanization. This paper aims to quantify future trends in the FRS supply–demand relationship under the joint impacts of climate change and urbanization. To this end, we took the Baiyangdian Lake Basin as an example and developed a "Climate Change-Urbanization-FRS supply and demand" framework by combining future climate scenarios from the ScenarioMIP (Scenario Model Intercomparison Project) dataset and socioeconomic data from the SSPs (Shared Socioeconomic Pathways) to estimate the FRS supply and demand dynamics during the period from 2020 to 2050. The results show that the framework has a reasonable ability to estimate the FRS supply–demand relationship. The correlation coefficients between estimated supply–demand ratios and the historical values exceeded 0.9. The average FRS supply–demand ratio among the four scenarios shows a significantly downward trend between 2020 and 2050. The FRS is expected to decrease by 0.159 (36.6 %), resulting in the imbalanced area increasing from 38.3 km2 (4.1 % of the whole basin) to 11049.7 km2 (36.2 %). We believe that although urbanization is the dominant factor contributing to the intensified imbalance trend (with a contribution of 71.2 %), influences from climate change also cannot be ignored (with a contribution of 28.8 %). Therefore, adaptation actions to climate change should be actively taken to reduce urban flood risks in the future. [ABSTRACT FROM AUTHOR]

ABSTRACT Heavy rain events or rainstorms of various scales often occur in Hong Kong from April to September. In extremes cases, they lead to serious landslides and flash floods resulting in loss of life, and damage to property and infrastructure. With climate change, extreme rain events are projected to be more frequent and more intense in this region. A system to gauge and label the severity of rainstorms would be useful for identifying and communicating extreme conditions in warning and disaster prevention operations. In parallel, a better understanding of the characteristics of rainstorms would also be important for impact assessments and engineering design purposes. This paper formulates a practical framework to index the magnitude and severity of rainstorms in Hong Kong. An index termed as the Severity Index combining the magnitude of different rainstorm attributes is devised for quantifying the overall severity of rainstorms. This index is flexible to allow tuning for specific applications. [ABSTRACT FROM AUTHOR]

Global flood management is a major issue for most cities which have to deal with worsening factors such as climate change and fast urban growth. Computer models have been used to model and understand urban flooding on a local scale in cities (25–50 km2). It has been practically impossible to model bigger cities in one go in sufficiently high resolution due to the heavy computations involved. The present paper describes a new modelling approach for urban flooding which allows modelling on large city scale (1000 km2) while keeping sufficient resolution, e.g. 5 m or 10 m grid. The multicell approach is applied for the city of Beijing for July 21st, 2012 flood event. Model results are compared to testimonials from the 2012 event. Comparison to traditional 2D urban flood computations shows that the multicell approach is much faster than standard detailed models while keeping a suitable level of precision. [ABSTRACT FROM AUTHOR]

The accurate design flood of hydraulic engineering is an important precondition to ensure the safety of residents, and the high precision estimation of flood frequency is a vital perquisite. The Xiangjiang River basin, which is the largest river in Hunan Province of China, is highly inclined to floods. This paper aims to investigate the annual maximum flood peak (AMFP) risk of Xiangjiang River basin under the climate context employing the Bayesian nonstationary time-varying moment models. Two climate covariates, i.e., the average June-July-August Artic Oscillation and sea level pressure in the Northwest Pacific Ocean, are selected and found to exhibit significant positive correlation with AMFP through a rigorous statistical analysis. The proposed models are tested with three cases, namely, stationary, linear-temporal and climate-based conditions. The results both indicate that the climate-informed model demonstrates the best performance as well as sufficiently explain the variability of extreme flood risk. The nonstationary return periods estimated by the expected number of exceedances method are larger than traditional ones built on the stationary assumption. In addition, the design flood could vary with the climate drivers which has great implication when applied in the context of climate change. This study suggests that nonstationary Bayesian modelling with climatic covariates could provide useful information for flood risk management. [ABSTRACT FROM AUTHOR]

The hydrologic data series are nonstationary due to climate change and local anthropogenic activities. The existing nonstationary design flood estimation methods usually focus on the statistical nonstationarity of the flow data series in the catchment, which neglect the hydraulic approach, such as reservoir flood regulation. In this paper, a novel approach to comprehensively consider the driving factors of non-stationarities in design flood estimation is proposed, which involves three main steps: (1) implementation of the candidate predictors with trend tests and change point detection for preliminary analysis; (2) application of the nonstationary flood frequency analysis with the principle of Equivalent Reliability (ER) for design flood volumes; (3) development of a nonstationary most likely regional composition (NS-MLRC) method, and the estimation of a design flood hydrograph at downstream cascade reservoirs. The proposed framework is applied to the cascade reservoirs in the Han River, China. The results imply that: (1) the NS-MLRC method provides a much better explanation for the nonstationary spatial correlation of the flood events in Han River basin, and the multiple nonstationary driving forces can be precisely quantified by the proposed design flood estimation framework; (2) the impacts of climate change and population growth are long-lasting processes with significant risk of flood events compared with stationary distribution conditions; and (3) the swift effects of cascade reservoirs are reflected in design flood hydrographs with lower peaks and lesser volumes. This study can provide a more integrated template for downstream flood risk management under the impact of climate change and human activities. [ABSTRACT FROM AUTHOR]

Surface water flooding is currently viewed as the most serious water-related issue in many of the China’s large cities due to rapid urbanization, land-use change and the process of rapid socio-economic development. In 2014, the People’s Republic of China established the concept of the ‘Sponge City’, which will be used to tackle urban surface-water flooding and related urban water management issues, such as purification of urban runoff, attenuation of peak run-off and water conservation. The concept is being developed to make use of ‘blue’ and ‘green’ spaces in the urban environment for stormwater management and control. It is envisaged that related practices will enhance natural ecosystems and provide more aesthetically pleasing space for the people that live and work in urban environments, in addition enabling nature-based solutions to improve urban habitats for birds and other organisms. Until recently, grey infrastructure and hard engineering-based management approaches have been adopted in the rapidly developing Chinese urban environment as urban flood and drainage issues are predominantly managed by municipal water engineers. The Sponge City concept and related guidelines and practices will provide multiple opportunities to integrate ideas from eco-hydrology, climate change impact assessment and planning, and consideration of long-term social and environmental well-being, within the urban land-use planning process. This paper aims to explicate the Sponge city concept and its development, and consider the implications of the transformation of urban land-use planning and urban-water management practice in China. To achieve the dual goals of sustainable water-use and better flood control (as targeted by the Sponge City concept), more effective development and implementation of land-use guidance and assessment tools (with explicit integration of urban flood-risk assessment, land-drainage guidance, climate projection methods, and assessment of long-term sustainability) are recommended. [ABSTRACT FROM AUTHOR]

Analyzing trends in flood magnitude changes, and their underlying causes, under climate change, is a key challenge for the effective management of water resources in arid and semi-arid regions, particularly for inland rivers originating in the Qilian Mountains (QMs). Sen's slope estimator and the Mann–Kendall test were used to investigate the spatial and temporal trends in flood magnitude, based on the annual maximum peak discharge (AMPD) and Peaks Over Threshold magnitude (POT3M) flood series, of twelve typical rivers, from 1970 to 2021. The results showed that, in the AMPD series, 42% of the rivers had significantly decreasing trends, while 8% had significantly increasing trends; in the POT3M series, 25% of the rivers had significantly decreasing trends, while 8% had significantly increasing trends. The regional differences in the QMs from east to west were that, rivers in the eastern region (e.g., Gulang, Zamu, and Xiying rivers) showed significantly decreasing trends in the AMPD and POT3M series; most rivers in the central region had non-significant trends, while the Shule river in the western region showed a significantly increasing trend. Temperatures and precipitation showed a fluctuating increasing trend after 1987, which were the main factors contributing to the change in flood magnitude trends of the AMPD and POT3M flood series in the QMs. Regional differences in precipitation, precipitation intensity, and the ratio of glacial meltwater in the eastern, central and western regions, resulted in the differences in flood magnitude trends between the east and west. [ABSTRACT FROM AUTHOR]

Under the background of global climate change and rapid development of urbanization, urban extreme occurs more frequently. In consideration of the existing problems in the emergency management decision-making of urban rainstorm and flood disasters in China, this study put forward the decision-making method of urban rainstorm and flood disaster emergency management based on similar cases analysis method. Based on the evolution process of urban waterlogging disaster, the problem attribute system of urban rainstorm and flood disasters was established. The case-based reasoning (CBR) method was used to calculate the global similarity to determine the best historical case. The case-based decision theory (CBDT) method was used to calculate the comprehensive utility value of alternative cases to determine the optimal alternative cases. The empirical analysis was took in Xi'an city, one of the national center cities of China. Results show that the CBR method was used to obtain the highest similarity of historical case P3, which is 0.481. The CBDT method was used to calculate the high similarity of historical cases P3 and P4 to form the similar case set, with the similarity of 0.820 and 0.851, respectively. Combined with the event development, the comprehensive utility values were calculated. When the decision-maker pays the same attention to the emergency effect and response cost, the comprehensive utility value of P3 and P4 is 0.922 and 0.900, respectively, and P3 is the best reference scheme. By comparison, the latter is more suitable. The results can provide scientific basis for emergency management of urban rainstorm and flood disasters. [ABSTRACT FROM AUTHOR]

Precipitation data from 30 stations in the Huaihe River basin (HRB), a climatic transitional zone in east China, were used to investigate the spatiotemporal variability and trends of extreme precipitation on multitimescales for the period 1961–2010. Results indicated that (1) the spatial pattern of the annual precipitation, rainy days, extreme precipitation, and maximum daily precipitations shows a clear transitional change from the south (high) to the north (low) in the HR; it confirmed the conclusion that the HRB is located in the transitional zone of the 800 mm precipitation contour in China, where the 800 mm precipitation contour is considered as the geographical boundary of the south and the north. (2) Higher value of the extreme precipitation intensity mainly occurs in the middle of the east and the central part of the basin; it reveals a relatively distinct west-east spatial disparity, and this is not in line with the spatial pattern of the extreme precipitation total, the sum of the precipitation in 95th precipitation days. (3) Annual precipitation of 22 stations exhibits increasing trend, and these 22 stations are located from the central to the northern part. There is no significant trend detected for the seasonal precipitation. The summer precipitation exhibits a larger change range; this might cause the variation of the flood and drought in the HBR. However, the increasing trend in winter precipitation may be beneficial to the relief of winter agricultural drought. Rainy days in 12 stations, mostly located in and around the central northeastern part, experienced significant decreasing trend. Extreme precipitation days and precipitation intensity have increasing trends, but no station with significant change trend is detected for the maximum precipitation of the basin. (4) The spatiotemporal variability in the HRB is mainly caused by the geographic differences and is largely influenced by the interdecadal variations of East Asian Summer Monsoon in eastern China. The output of this paper could provide references for the practical decision making and integrated basin management of Huaihe River basin. [ABSTRACT FROM AUTHOR]

As a globally important sugarcane-producing region, Southern China (SC) is severely affected by various agrometeorological disasters. This study aimed to comprehensively assess multiple sugarcane agrometeorological disasters with regards to sugarcane yield in SC. The standardized precipitation evapotranspiration index and the heat degree-days were employed to characterize drought, flood, and high temperature (HT) during sugarcane growth stages in three provinces in SC in the period 1970–2020. Moreover, the relationships between sugarcane climatic yield and disaster intensities were investigated. The results indicated that the most recent decade witnessed the most intensive sugarcane agrometeorological disasters; sugarcane drought and HT intensities significantly (p < 0.05) increased in one and two provinces, respectively. Central and western SC was most drought-prone, while eastern SC was most flood-prone; sugarcane HT was concentrated in southwestern SC. The mature stage exhibited the greatest monthly intensities of drought and flood; the most HT-prone growth stage varied with provinces. The relationships between drought/flood intensity and sugarcane climatic yield were significant in seven districts; the yield-reducing effect of sugarcane flood was more obvious than that of drought. In conclusion, this study provides references for agrometeorological disaster risk reduction for sugarcane in SC. [ABSTRACT FROM AUTHOR]

Land subsidence is impacting large populations in coastal Asia via relative sea-level rise (RSLR). Here we assesses these risks and possible response strategies for China, including estimates of present rates of RSLR, flood exposure and risk to 2050. In 2015, each Chinese coastal resident experienced on average RSLR of 11 to 20 mm/yr. This is 3 to 5 times higher than climate-induced SLR, reflecting that people are concentrated in subsiding locations. In 2050, assuming these subsidence rates continue, land area, population and assets exposed to the 100-year coastal flood event is 20%-39%, 17%-37% and 18%-39% higher than assuming climate change alone, respectively. Realistic subsidence control measures can avoid up to two thirds of this additional growth in exposure, with adaptation required to address the residual. This analysis emphasizes subsidence as a RSLR hazard in China that requires a broad-scale policy response, utilizing subsidence control combined with coastal adaptation. Chinese coastal populations are concentrated in subsiding locations, and also subject to sea-level rise. Here the authors find that more areas, population and assets are exposed to coastal flooding by 2050 but realistic subsidence control measures can avoid additional risks. [ABSTRACT FROM AUTHOR]

This study presents a review of recent rainwater harvesting (RWH) research by a bibliometric analysis (based on performance analysis and science mapping method). Following the inclusion/exclusion criteria, a total of 3226 publications were selected for this bibliometric analysis. From the selected publications, the top journals were identified according to number of publications and number of citations, as well as the authors with the highest number of publications. It has been found that publication rate on RWH has been increasing steadily since 2005. Water (MDPI) journal has published the highest number of publications (128). Based on the literature considered in this review, the top five authors are found as Ghisi, E., Han, M., Rahman, A., Butler, D. and Imteaz, M.A. in that order. With respect to research collaborations, the top performing countries are USA–China, USA–Australia, USA–UK, Australia–UK and Australia–China. Although, the most dominant keywords are found to be 'rain', 'rainwater', 'water supply' and 'rainwater harvesting', since 2016, a higher emphasis has been attributed to 'floods', 'efficiency', 'climate change', 'performance assessment' and 'housing'. It is expected that RWH research will continue to rise in future following the current trends as it is regarded as a sustainable means of water cycle management. [ABSTRACT FROM AUTHOR]

Coastal flood regimes have been irreversibly altered by both climate change and human activities. This paper aims to quantify the impacts of multiple factors on delta flood. The Pearl River Delta (PRD), with dense river network and population, is one of the most developed coastal areas in China. The recorded extreme water level (m.s.l.) in flood season has been heavily interfered with by varied income flood flow, sea-level rise, and dredged riverbeds. A methodology, composed of a numerical model and the index R, has been developed to quantify the impacts of these driving factors in the the PRD. Results show that the flood level varied 4.29%–53.49% from the change of fluvial discharge, 3.35%–38.73% from riverbed dredging, and 0.12%–16.81% from sea-level rise. The variation of flood flow apparently takes the most effect and sea-level rise the least. In particular, dense river network intensifies the impact of income flood change and sea-level rise. Findings from this study help understand the causes of the the PRD flood regimes and provide theoretical support for flood protection in the delta region. [ABSTRACT FROM AUTHOR]

Under climate change, flash floods have become more frequent and severe, and are posing a danger to society, especially in the ungauged catchments. The objective of this paper, is to construct a simple and early warning system, serving for flash floods risk management in the ungauged catchments of the Loess Plateau in China, and offer a reference for flash flood warning in other areas in the world. Considering the absence of hydrological data in the ungauged catchments, the early warning system for flash floods is established by combining the regional or watershed isograms of hydrological parameters and local empirical formulas. Therein, rainfall and water stage/flow are used as warning indices for real-time risk estimation of flash flood. For early warning, the disaster water stage was first determined according to the protected objects (e.g., residents and buildings), namely the critical water stage. The critical flow (flow threshold), was calculated based on the water stage, and the established relationship between water stage and flow using the cross-sectional measured data. Then, according to the flow frequency curve of the design flood, the frequency of critical flow was ascertained. Assuming that the rainfall and the flood have the same frequency, the critical rainfall threshold was calculated through the design rainstorm with the same frequency of the design flood. Due to the critical rainfall threshold being sensitive with different soil conditions, the design flood and frequency curve of flood flow were calculated under different soil conditions, and thus the rainfall threshold was given under different soil condition for early warning of the flash flood disaster. Taking two sections in Zichang County (within the Loess Plateau) as an example, we set the rainfall and water stage/flow thresholds to trigger immediate or preparation signals for the migration of the population along the river. The application of this method to the 7.26 flood events in 2017 in China, shows that the early warning system is feasible. It is expected that this simple early warning system can provide early warnings of flash floods in ungauged catchments in the Loess Plateau and other similar areas. [ABSTRACT FROM AUTHOR]

Flood disasters have occurred frequently in recent years, but there is no consensus on the mechanism and influencing factors. Taking the upper reaches of Weihe River Basin as a case in Western China, a soil and water assessment tool (SWAT) model was established to quantitatively simulate the impact of land use and climate change on runoff changes, while 4 extreme land-use scenarios and 24 temperature and precipitation scenarios assumptions were proposed to simulate the response of runoff to land use and climate changes. The SWAT simulation results showed that the sensitivity parameters affecting the model simulation were the CANMX, CN2, SOL_K, CH_N2, and SOL_AWC. The correlation index R2 and the efficiency coefficient ENS of the upper Weihe River were both in the range of 0.75–0.78, the relative error PS between the simulated results and the measured runoff was below 10%, suggesting the good applicability of the SWAT model in this study area. Using the improved SWAT model to simulate the peak runoff (flood) simulation value is generally smaller than the measured value, and the absolute value of the error is less than 6%. The expansion of wasteland increased the runoff by over 90% on average, the expansion of cultivated land increased the runoff by 8% on average, and the expansion of woodland and grassland increased the surface runoff by 6% on average. When the precipitation decreased by 25% and the temperature increased by 22%, the smallest runoff was obtained in the simulation. Accordingly, when the precipitation increased by 25% and the temperature decreased by 22%, the maximum annual runoff was obtained. By decomposing the contribution rate of human activities and climate change to runoff, it showed that the contribution rate of human activities to the reduction of runoff was greater than that of climate change. This study can provide scientific reference for the simulation and prediction of future floods. [ABSTRACT FROM AUTHOR]

Changes in river floods under a changing climate are of worldwide concerns, but relevant knowledge is limited especially over the East Asia monsoon region. Here we examine changes in flood peak timing based on the most comprehensive flood data set to date across China during 1961–2017. The temporal shifts of Chinese flood peak timing range from −19.0 days earlier to +14.0 days later per decade. Earlier flood occurrences are mainly observed in northern China, with delayed flood occurrences in the south. The spatial pattern of reversed latitudinal changes in flood timing leads to growing spatial extents of concurrent river floods over China. Soil moisture plays an important role in modulating such changes, despite precipitation determines the climatological mean dates of flood occurrences. Our results highlight a strong climate signal on the changes in flood timing over China, and call for coordinated efforts in alleviating expanding flood hazards related to the changes in flood timing. Plain Language Summary: Changes of river floods under a changing climate are of worldwide concerns, but relevant knowledge is still limited especially over East Asian monsoon region. Changes in dates of flood peak occurrences are preferably investigated to understand how climate change affects river floods. This is because flood peak timing, compared to flood peak magnitude, is less affected by water (e.g., dams) and land (e.g., urbanization) management practices. Based on the most comprehensive Chinese flood data set, we identify a strong climate signal on the changes in flood peak timing over China for the first time. Chinese floods tend to occur later in the south but earlier in the north over the past several decades. Considering floods in southern China are typically earlier than those in northern China, the reversed latitudinal changes in flood peak timing lead to enhanced temporal concentration of flood occurrences (i.e., seasonality) over China, and is further responsible for flooding with larger spatial extents across China. While monsoon rainfall largely determines the flood seasonality, we highlight the role of antecedent soil wetness in modulating changes in flood peak timing. Our results call for trans‐basin efforts in alleviating widespread flood hazards over the East Asian Monsoon region. Key Points: Southern (Northern) China witness delayed (earlier) annual flood peaks in the past six decadesReversed latitudinal changes in flood peak timing lead to the growing spatial extents of synchronous flooding over ChinaWeak temporal correlation between flood and rainfall synchrony scale highlights the role of soil moisture in modulating flood peak timing [ABSTRACT FROM AUTHOR]

Floods in river deltas are driven by complex interactions between astronomical tides, sea levels, storm surges, wind waves, rainfall‐runoff, and river discharge. Given the anticipated increase in compound flood hazards in river deltas in a warming climate, climate‐informed regional to local extreme water levels (EWLs) is thus critical for decision‐makers to evaluate flood hazards and take adaptation measures. We develop a simple yet computationally efficient stress test framework, which combines historical and projected climatological information and a state‐of‐the‐art hydrodynamic model, to assess future compound coastal‐fluvial flood hazards in river deltas. Our framework is applied in the world's largest single urban area, China's Pearl River Delta (PRD), which is also characterized by densely crossed river network. We find that extreme sea level is the dominant driver causing the compound coastal‐fluvial flood in the PRD over the past 60 years. Meanwhile, there is large spatial heterogeneity of the individual and compound effects of the typhoon intensity, local sea‐level rise, and riverine inflow on coastal‐fluvial floods. In a plausible disruptive scenario (e.g., a 0.50 m sea‐level rise combined with a 9% increase in typhoon intensity in a 2°C warming), the EWL will increase by 0.76 m on average. An additional 1.54 and 0.56 m increase in EWL will occur in the river network and near the river mouth, respectively, if coastal floods coincide with the upstream mean annual flood. Findings from our modeling framework provide important insights to guide adaptation planning in river deltas to withstand future compound floods under climate change. Plain Language Summary: Compound floods pose serious threats to the dense population living in river deltas worldwide. Climate change could increase the compound flood hazards through stronger tropical cyclones, sea level rise, higher extreme precipitation, and river flows. It is urgent to understand how the so‐called grey swan events will evolve under a changing climate in these already flood‐prone areas. Here, grey swan events are high‐consequence events that are beyond people's experience but may be foreseeable and thus can be systematically prepared for. In this study, a storyline‐based framework is proposed to assess the potential grey swan compound floods under a warming climate. We apply this framework to China's Pearl River Delta, the world's largest single urban area. In a plausible disruptive scenario (e.g., a 0.50 m sea‐level rise combined with a 9% increase in typhoon intensity in a 2°C warming), we find that extreme water levels will increase by 0.76 m on average. Our flexible and computationally efficient storyline‐based framework could guide coastal planners to prepare for the grey swan compound flood hazards under climate change. Key Points: A quantitative stress test framework is proposed to assess the compound coastal‐fluvial flood in the river delta at minimal costA state‐of‐the‐art unstructured mesh generation technology is applied to develop an objective and reproducible hydrodynamic modelCompound effects of typhoon intensity, local sea‐level rise, and river inflow on coastal‐fluvial floods are systematically investigated [ABSTRACT FROM AUTHOR]

Hydropower dams are proliferating in the riparian countries of the Lancang‐Mekong River Basin (LMRB) driven by the pursuit of renewable electricity and societal resilience to flooding. However, the tradeoffs between hydropower production and flood control are unclear in a changing environment. Here, we use a hydrological variable infiltration capacity model combined with a reservoir module to quantify the relative effects of climate change and reservoir operation on flood and hydropower generation in LMRB. Results show that while climate change would increase flood magnitude and frequency, adaptive reservoir operation can reduce flood magnitude by 5.6%–6.4% and frequency by 17.1%–18.9% at the cost of 9.8%–14.4% of basin‐wide hydropower generation. Particularly, upstream reservoirs suffer more hydropower loss (5.4 times) than downstream ones when flood control is prioritized in reservoir regulation. Our findings have implications for integrated water and energy management at the transboundary river basin under climate change. Plain Language Summary: Dams and reservoirs provide two important services, i.e., flood control and hydropower generation. In this study, we seek to understand the future tradeoff between these two services provided by reservoir regulation in the transboundary Lancang‐Mekong River Basin. Using a modeling based approach, we find that climate change will likely lead to more frequent and larger flood events, but reservoir operation, by regulating water discharges and levels in streams, can effectively reduce flood frequency and magnitude at the expense of hydropower generation. Our results highlight the importance of coordinating water and energy management across countries in this transboundary river basin. Key Points: Reservoir can mitigate future flood risk from climate change at the cost of reducing hydropower generation in the Lancang‐Mekong River BasinReservoir regulation can delay the timing when flood risk exceeds the historical baseline by at least 20 years in Laos and ThailandFlood control measures would reduce hydropower at a magnitude of 5.4 times in China than downstream countries [ABSTRACT FROM AUTHOR]

The persistence over space and time of flash flood disasters – flash floods that have caused either economical losses or loss of life or both – is a diagnostic measure of areas subjected to hydrological risk. The concept of persistence can be assessed via clustering analyses, performed here to analyze the national inventory of flash flood disasters in China that occurred in the period 1950–2015. Specifically, we investigated the spatiotemporal pattern distribution of the flash flood disasters and their clustering behavior by using both global and local methods: the first based on Ripley's K function, and the second on scan statistics. As a result, we could visualize patterns of aggregated events, estimate the cluster duration and make assumptions about their evolution over time, also with respect to the precipitation trend. Due to the large spatial (the whole Chinese territory) and temporal (66 years) scale of the dataset, we were able to capture whether certain clusters gather in specific locations and times but also whether their magnitude tends to increase or decrease. Overall, the eastern regions in China are much more subjected to flash flood disasters compared to the rest of the country. Detected clusters revealed that these phenomena predominantly occur between July and October, a period coinciding with the wet season in China. The number of detected clusters increases with time, but the associated duration drastically decreases in the recent period. This may indicate a change towards triggering mechanisms which are typical of short-duration extreme rainfall events. Finally, being flash flood disasters directly linked to precipitation and their extreme realization, we indirectly assessed whether the magnitude of the trigger itself has also varied through space and time, enabling considerations in the context of climatic change. [ABSTRACT FROM AUTHOR]

As atmospheric moisture holding capacity is positively dependent on temperatures, a large intensification of precipitation extremes is projected under foreseeable climate warming. Flooding that is mainly attributed to extreme storms usually accounts for an ambitious target in weather‐related hazard mitigation over China. Previous works seldom focused on flooding evolution patterns under climate change at a national scale, and fewer flooding projections considered the estimation uncertainty sourced from limited samples. This study systematically projected changes in flood quantiles based on annual maximum series and seasonality and also evaluated the variations of sampling uncertainty for 151 catchments over mainland China under the emission scenario of representative concentration pathway (RCP) 8.5. In order to project future streamflow series, the bias‐corrected outputs of six global climate models (GCMs) were input into a best‐performing hydrological model, which was selected from four calibrated hydrological models based on the KGE criteria. The Pearson type‐III (P‐III) distribution and L‐moments (L‐M) method were employed to derive the flood quantiles for different return periods during historical (1961–2005) and future (2056–2100) periods, and the bootstrapping method was applied to estimate the sampling uncertainty. A regression trend method was used to track the variations of flood seasonality in the context of climate warming. Our results project earlier flood timing and larger flood quantiles for most catchments in future period than those in the historical period, despite being accompanied by substantial spatial variations. We also project that the sampling uncertainty in estimating flood quantiles is increased in a warming future. Many catchments are exposed to dramatic changes in both flood quantile and estimation uncertainty by over 50%, while only a few catchments are projected to have decreasing flood risks. These results suggest an urgent need to improve the functionality of early warning systems and increase societal resilience to warming climates over China. [ABSTRACT FROM AUTHOR]

• Farmers with more secure property rights are more likely to take action to adapt to climate change. • Security of property rights has an impact on managerial decisions concerning operational matters. • Farmer adaption is influenced by government provision of public goods and by the local extent of social capital. • Policy reform to add to the security of land tenure to support adaptation to climate change is important. Improving land rights in China is often considered as an important factor that facilitates farmers' investments in agriculture. However, whether securing land rights is important for farmers' adaptation to changing climate or not has not been addressed in the literature, particularly with respect to management decisions. This paper examines the relationship between land tenure types and farmer adaptation through management decisions in response to extreme weather events in Guangdong Province in China. Based on a household survey of rice farmers, our results show that compared to a normal year with minor weather events farmers with contracted land are more likely to implement adaptation measures in response to extreme weather events than those who have rented their land from the collective and from other farmers. The results suggest that farmers' adaptive behaviour in response to extreme weather events is significantly different from their day-to-day adaptation to ongoing changes in climate. Farmers' adaptive capacity is also positively influenced by age, the public provision of information, by the presence of social capital, and by plot quality. The results of this study highlight the importance of properly defined land rights for the likelihood of adaptation, and thereby increasing agricultural productivity and ensuring food security in the context of a changing climate. [ABSTRACT FROM AUTHOR]

The history of coastal catastrophic floods was reconstructed for the first time using the geochemical proxy in shelf sediments. The reconstruction is based on the identification of sediment layers accumulated on the shelf during the intensive discharge of the river runoff suspended matter from the land which does not contain bromine. The set of isotopic (AMS 14C, 210Pb, 137Cs), tephrastratigraphic, and paleomagnetic methods was used for the detailed chronology of sediments. The scanning of chemical composition of sediments with the step of 0.5–0.8 mm is performed using the synchrotron radiation X-ray fluorescence in the VEPP-3 storage of the Institute of Nuclear Physics of Siberian Branch of Russian Academy of Sciences. The history of catastrophic floods for the past 1800 years is reconstructed based on the typical variations in bromine concentration in one of the cores from the Amur Bay (the Sea of Japan). New methodological approaches to the flood signal extraction are proposed. The revealed inverse correlation between the frequency of floods caused by typhoons over the coast of the Sea of Japan and southern China agrees with the existing assumption on the change in their trajectories in different periods of global climate change. [ABSTRACT FROM AUTHOR]

Understanding the temporal variations of extreme floods that occur in response to climate change is essential to anticipate the trends in flood magnitude and frequency in the context of global warming. However, long-term records of paleofloods in arid regions are scarce, thus preventing a thorough understanding of such events. In this study, a reconstruction of paleofloods over the past 300 years was conducted through an analysis of grain sizes from the sediments of Kanas Lake in the Altay Mountains of northwestern China. Results showed that grain parameters and frequency distributions can be used to infer possible abrupt environmental events within the lake sedimentary sequence, and two extreme flood events corresponding to ca. 1736-1765 AD and ca. 1890 AD were further identified based on canonical discriminant analysis (CDA) and coarse percentile versus median grain size (C-M) pattern analysis, both of which occurred during warmer and wetter climate conditions by referring to tree-ring records. These two flood events are also evidenced by lake sedimentary records in the Altay and Tianshan mountains. Furthermore, through a comparison with other records, the flood event from ca. 1736-1765 AD in the study region seems to have occurred in both the arid central Asia and the Alps in Europe, and thus may have been associated with changes in the North Atlantic Oscillation (NAO) index. [ABSTRACT FROM AUTHOR]

In 2015, China’s national government initiated a Sponge City Programme to address its urban flood issues. A sponge city is a city built around the concept of managing water in an ecologically sustainable way. The intention is to improve urban resilience through rainwater capture, storage and use. This article applies a four-mode governance framework to analyze the programme. It identifies the strengths and weaknesses of the programme implementation and provides recommendations. [ABSTRACT FROM AUTHOR]

This study analyzes the variation and risk changes of extreme precipitation under nonstationarity conditions using the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) and the Mann-Kendall (MK) test. The extreme precipitation series is extracted from the observations during the second flood season (July-September) from 1960 to 2012 derived from 86 meteorological stations in the southeastern coastal region of China. The trend of mean (Mn) and variance (Var) of extreme precipitation is detected by MK. Ten large-scale circulation variables and four greenhouse gases are selected to construct a climate change index and a human activity index, which are based on principal component analysis. The recurrence risk of extreme precipitation is calculated by GAMLSS while considering climate changes and human activities. The results demonstrate that the nonstationarity characteristic of extreme precipitation is widespread in this region. A significant increasing trend of Mn is found in Shanghai, eastern Zhejiang, and northern and southern Fujian. An enhanced Var is found in eastern Guangdong. A significant positive correlation exists between climate changes/human activities and Mn/Var, especially in Zhejiang and Fujian. Generally, the contribution of climate changes and human activities to Mn is greater than it is to Var. In this region, the precipitation amount of high-frequency (2-yr return period) and low-frequency (100-yr return period) events increases from inland to coastal and from north to south. The government should pay careful attention to these trends because the intensity of extreme precipitation events and their secondary disasters could result in serious losses. [ABSTRACT FROM AUTHOR]

A timescale decomposed threshold regression (TSDTR) downscaling approach to forecasting South China early summer rainfall (SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR. The two models are developed based on the partial least squares (PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915-84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation (PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985-2006, compared to other simpler approaches. This study suggests that the TSDTR approach, considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions. [ABSTRACT FROM AUTHOR]

The torrential flooding and debris flow disasters associated with global climate change pose not only serious threat to individual lives and property, but also impact economic development. Accurately simulating flood scenarios can help to reduce the losses caused by torrential flooding and debris flow by making early warning, evacuation planning, and risk analysis possible. In this study, HEC-RAS software and HEC-GeoRAS module were employed in GIS (geographic information system) to simulate the flood overtopping in the Mengzong Gully of Batang River in flood scenarios occurring once in 20, 50, and 100 years, respectively. The simulated floods provided valuable information including scope and depth of submersion via 2D visualization. [ABSTRACT FROM PUBLISHER]

Future changes in floods and water availability across China under representative concentration pathway 2.6 (RCP2.6) and RCP8.5 are studied by analyzing discharge simulations from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) with the consideration of uncertainties among global climate models (GCMs) and hydrologic models. Floods and water availability derived from ISI-MIP simulations are compared against observations. The uncertainties among models are quantified by model agreement. Only model agreement >50% is considered to generate reliable projections of floods and water availability and their relationships with climate change. The results show five major points. First, ISI-MIP simulations have acceptable ability in modeling floods and water availability. The spatial patterns of changes in floods and water availability highly depend on the outputs of GCMs. Uncertainties from GCMs/hydrologic models predominate the uncertainties in the wet/dry areas in eastern/northwestern China. Second, the magnitudes of floods throughout China increase during 2070-99 under RCP8.5 relative to those with the same return periods during 1971-2000. The increase rates of larger floods are higher than those of the smaller ones. Third, water availability decreases/increases in southern/northern China under RCP8.5, but changes negligibly under RCP2.6. Fourth, more severe floods in the future are driven by more intense precipitation extremes over China. The negligible change in mean precipitation and the increase in actual evapotranspiration reduce the water availability in southern China. Fifth, model agreements are higher in simulated floods than water availability because increasing precipitation extremes are more consistent among different GCM outputs compared to mean precipitation. [ABSTRACT FROM AUTHOR]

Copula-based bivariate frequency analysis can be used to investigate the changes in flood characteristics in the Huai River Basin that could be caused by climate change. The univariate distributions of historical flood peak, maximum 3-day and 7-day volumes in 1961-2000 and future values in 2061-2100 projected from two GCMs (CSIRO-MK3.5 and CCCma-CGCM3.1) under A2, A1B and B1 emission scenarios are analyzed and compared. Then, bivariate distributions of peaks and volumes are constructed based on the copula method and possible changes in joint return periods are characterized. Results indicate that the Clayton copula is more appropriate for historical and CCCma-CGCM3.1 simulating flood variables, while that of Frank and Gumbel are better fitted to CSIRO-MK3.5 simulations. The variations of univariate and bivariate return periods reveal that flood characteristics may be more sensitive to different GCMs than different emission scenarios. Between the two GCMs, CSIRO-MK3.5 evidently predicts much more severe flood conditions in future, especially under B1 scenario, whereas CCCma-CGCM3.1 generally suggests contrary changing signals. This study corroborates that copulas can serve as a viable and flexible tool to connect univariate marginal distributions of flood variables and quantify the associated risks, which may provide useful information for risk-based flood control. [ABSTRACT FROM AUTHOR]

A growing number of studies on streamflow projection in the context of global climate change have been widely reported in past years. However, current knowledge on the role of different hydrological models to estimate future climate impact on flood in the Tibet Plateau is still limited so far. In this work, a group of hydrological models in conjunction with statistical downscaling outputs (SDSM and ANN) from the HadCM3 GCM model are used to evaluate the impacts of climate change on floods in the 21st century over the headwater catchment of Yellow River, the Tibet Plateau. The influence of different hydrological models on flood projection and quantile estimation are addressed. The results show that: (1) three hydrological models generate acceptable results of flood magnitude and frequency at Tangnaihai station during the past 50 years; (2) quite similar projections for future floods are obtained by means of different hydrological models, decreasing flood magnitude corresponding to the 2-, 5-, 10- and 50-year return periods is found under most scenarios in the 21st century. Meanwhile, flood frequency is likely to reduce in response to climate change; (3) the uncertainty in projected flood quantile by three different hydrological models increases with recurrence interval in term of relative length of confidence interval (RL). Besides, RL for flood quantile in future climate scenarios is likely to become larger than the baseline period. The results are valuable to improve our current knowledge of climate impact research in the alpine regions. [ABSTRACT FROM AUTHOR]

Flood frequency analysis is concerned with fitting a probability distribution to observed data to make predictions about the occurrence of floods in the future. Under conditions of climate change, or other changes to the water cycle that impact flood runoff, the flood series is likely to exhibit non-stationarity, in which case the return period of a flood event of a certain magnitude would change over time. In non-stationary flood frequency analysis, it is customary to examine only the non-stationarity of annual maximum flood data. We developed a way of considering the effect of non-stationarity in the annual daily flow series on the non-stationarity in the annual maximum flood series, which we termed the norming constants method (NCM) of non-stationary flood frequency analysis (FFA). After developing and explaining a framework for application of the method, we tested it using data from the Wei River, China. After detecting significant non-stationarity in both the annual maximum daily flood series and the annual daily flow series, application of the method revealed superior model performance compared to modelling the annual maximum daily flood series under the assumption of stationarity, and the result was further improved if explanatory climatic variables were considered. We conclude that the NCM of non-stationary FFA has potential for widespread application due to the now generally accepted weakness of the assumption of stationarity of flood time series. [ABSTRACT FROM AUTHOR]

Climate change has had a huge impact on Southwest China, where extreme weather events have taken on an increasing trend. The region lies in the transition zone of three monsoons (East Asian, Indian, and Tibetan Plateau). We analyzed long-term trends of drought and flood disasters using sequential data on China's drought and flood incidence over 500 years (1501-2000), as well as precipitation records from 45 weather stations during 1961-2010. Results show that both types of disaster became more frequent. During 1501-2000, drought frequency rose from 2.12 to 4.15 per century to 9.03 and flood frequency from 2.06 to 5.09 per century to 11.94. For the 10 decades during 1900-2000, droughts exhibited a significant increasing trend ( R = 0.4491), while floods showed a slight increasing trend ( R = 0.0346). For extreme floods and droughts in 1961-2010, precipitation records revealed that most (2/3) areas in the region had increasing drought or flood frequencies. Generally, both frequency and intensity of these weather hazards conspicuously increased in Southwest China during 1501-2000. [ABSTRACT FROM AUTHOR]

Recent evidences of the impact of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, identification of nonstationarity was conducted in the form of both trend and change point in the mean of the annual maximum flood magnitudes, using Mann-Kendall and Pettitt test, respectively in Wangkuai reservoir watershed, China. The annual maximum flood series exhibited a significant decreasing trend, and the timing of change point was detected in 1979, which was consistent with the construction of large numbers of check dams and small hydraulic structures. A correlation test (Pearson correlation test) between large-scale oceanic-atmospheric patterns (El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Pacific Oscillation (NPO), North Atlantic Oscillation (NAO), Atlantic Oscillation (AO)) and annual maximum flood peaks was adopted to assess the climatic causes of nonstationary flood series. It was found that NPO, NAO and AO had significant correlations with flood peak, but ENSO and PDO could not explain the variations of flood peak. In the case of human-induced nonstationarity, we proposed 2 new indices to represent the effect of human activities on flood. The new indices were proposed based on the storage capacity and drainage area of the large numbers of check dams and small hydraulic structures which were estimated with no observed data. The identification of nonstationarity for flood series and the climatic and human-induced causes could provide useful information in nonstationary flood frequency analysis. [ABSTRACT FROM AUTHOR]

As climate change becomes increasingly widespread, rapid, and intense, the frequency of heavy rainfall and floods continues to increase. This article establishes a prediction system using feature sets with multiple data dimensions, including meteorological data and socio-economic data. Based on data of historical floods in 31 provinces and municipalities in China from 2006 to 2018, five machine learning methods are compared to predict the direct economic losses. Among them, GBR performs the best with a goodness-of-fit of 90%. Combined with the input-output (IO) model, the indirect economic losses of agriculture to other sectors are calculated, and the total economic losses caused by floods can be predicted effectively by using the GBR-IO model. The model has a strong generalization ability with a minimum requirement of 80 pieces of data. The results of the data show that in China, provinces heavily reliant on agriculture suffered the most with the proportion of direct economic losses to provincial GDP exceeding 1‰. Therefore, some policy implications are provided to assist the government to take timely pre-disaster preventive measures and conduct post-disaster risk management, thereby reducing the economic losses caused by floods. [ABSTRACT FROM AUTHOR]

In recent years, the intensified influences of global climate change and human activities have increased the frequency of large-scale debris flow disasters. As a result, main river channels often become blocked, thus forming a disaster chain of rivers dammed by debris flow followed by outburst flooding. In order to quickly and easily reveal the dynamic process of a debris flow dam breach, and quantitatively predict the outburst flood hazard, this study takes the Zhouqu "8.8" debris flow barrier dam in Western China as an example. Based on a stability assessment, China Institute of Water Resources and Hydropower Research's Dam Breach Slope (DBS-IWHR), China Institute of Water Resources and Hydropower Research's Dam Breach (DB-IWHR), and Hydrologic Engineering Center's River Analysis System (HEC-RAS) were integrated to simulate the development of dam breach, breach flood, and outburst flood evolution, respectively, under different scenarios. The simulated peak discharge flow of the actual spillway was 317.15 m3/s, which was consistent with the actual discharge of 316 m3/s. The results under different scenarios showed that, with the increased inflow of the barrier lake, the erosion rate of the dam increased, the peak discharge of the dam break flood increased, the peak arrival time shortened, and the downstream flooding area increased. These findings could provide scientific support for risk management and emergency decision-making with respect to barrier dam failure. [ABSTRACT FROM AUTHOR]

Urban flood-related issues are substantial in China, arising from rapid construction of megacities over decades with insufficient flood control, all being made worse by climate change. Since Sponge City (SC) options are primarily effective at maintaining the water balance at the surface, flooding continues. In response, the One Water concept is used to demonstrate the need to respond to dimensions beyond SC and shown herein to have potential to reduce the impacts of major storms (e.g., suppress 100-year flooding to a 25-year flooding equivalent). However, climate change causes more intense storms, indicating the intensity of the 100-year storm will increase by ~0.23% annually over the next 70 years. Hence, given sufficient SC options, the 100-year storms may only be effectively reduced to a 50-year storm, at best by SC options. "One Water" is utilized as a concept to demonstrate structured thinking about how each dimension of the hydrologic cycle can be employed to consider the degree of interconnection, allowing improved assessment of various components of the hydrologic cycle and SC options. Examples are used to demonstrate how the concept of One Water links the array of components of the hydrologic cycle together, generating a holistic view of urban water resource security. [ABSTRACT FROM AUTHOR]

Flooding caused by unpredictable high-intensity rainfall events in urban areas has become a global phenomenon due to the combined effect of urbanization and climate change. There are numerous hydrodynamic models for urban flooding simulation and management. However, it is difficult for most of these models to simplify the surface runoff process and still provide high simulation accuracy. In this study, an improved simplified urban storm inundation model (SUSIM) that integrates urban terrain, precipitation, surface runoff and inundation models was proposed to quickly and accurately simulate the different inundation conditions by modifying the urban terrain and catchments. Haining City, China, was selected as a case study in which SUSIM was tested and validated. The results were as follows: (1) Detailed locations and depths of inundation were quickly calculated with high correlation coefficient (≥75%) compared to three actual rainfall events. (2) Four scenarios under different rainfall intensities (5-, 10-, 20- and 50-year return period, respectively) were designed. The maximum inundation depths significantly increased from 403 mm to 1522 mm and the maximum inundation area increased from 2904 m2 to 7330 m2. According to the simulation results, Haining Avenue, the West Mountain Park and the old urban area in the northeast part of the city would encounter the most extensive and severe inundation. The result reveals that the SUSIM could find inundation locations and calculate inundation depth and area quickly. It provides better insights and tools for urban inundation simulation and planning strategies. [ABSTRACT FROM AUTHOR]

Migration is one way in which rural households can seek to reduce their vulnerability to climate change. However, migration also carries risks and costs, such that vulnerability may not be reduced. This article constructs an index of rural households' vulnerability to extreme weather events, in order to explore how key components of vulnerability relate to migration. Applied to case studies in China and India, the study finds that the effect of remittances is non‐linear. Although overall, in Assam, few differences were found in the vulnerability of households that did and did not receive remittances, in Yunnan, remittance‐recipient households were found to have less adaptive capacity in response to drought. However, those who had received remittances over longer periods were found to have improved adaptive capacity in both case studies, and in Yunnan, their exposure to such events was also lower. Meanwhile in Assam, longer distance migration was associated with reduced exposure to flooding and with specific forms of adaptation. The vulnerability index developed has capacity to be used in assessments of effects of migration on vulnerability elsewhere. [ABSTRACT FROM AUTHOR]

In recent years, alternating periods of floods and droughts, possibly related to climate change and/or human activity, have occurred in the Liao River Basin of China. To monitor and gain a deep understanding of the frequency and severity of the hydro-meteorological extreme events in the Liao River Basin in the past 30 years, the total storage deficit index (TSDI) is established by the Gravity Recovery and Climate Experiment (GRACE)-based terrestrial water storage anomalies (TWSAs) and the general regression neural network (GRNN)-predicted TWSA. Results indicate that the GRNN model trained with GRACE-based TWSA, model-simulated soil moisture, and precipitation observations was optimal, and the correlation coefficient and the root mean square error (RMSE) of the predicted TWSA and GRACE TWSA for the testing period equal 0.90 and 18 mm, respectively. The drought and flood conditions monitored by the TSDI were consistent with those of previous studies and records. The extreme climate events could indirectly reflect the status of the regional hydrological cycle. By monitoring the extreme climate events in the study area with TSDI, which was based on the TWSA of GRACE and GRNN, the decision of water resource management in the Liao River Basin could be made reasonably. [ABSTRACT FROM AUTHOR]