Toward Understanding the Extreme Floods over Yangtze River Valley in June−July 2020:Role of Tropical Oceans

The extreme floods in the Middle/Lower Yangtze River Valley(MLYRV)during June−July 2020 caused more than 170 billion Chinese Yuan direct economic losses.Here,we examine the key features related to this extreme event and explore relative contributions of SST anomalies in different tropical oceans.Our results reveal that the extreme floods over the MLYRV were tightly related to a strong anomalous anticyclone persisting over the western North Pacific,which brought tropical warm moisture northward that converged over the MLYRV.In addition,despite the absence of a strong El Niño in 2019/2020 winter,the mean SST anomaly in the tropical Indian Ocean during June−July 2020 reached its highest value over the last 40 years,and 43%(57%)of it is attributed to the multi-decadal warming trend(interannual variability).Based on the NUIST CFS1.0 model that successfully predicted the wet conditions over the MLYRV in summer 2020 initiated from 1 March 2020(albeit the magnitude of the predicted precipitation was only about one-seventh of the observed),sensitivity experiment results suggest that the warm SST condition in the Indian Ocean played a dominant role in generating the extreme floods,compared to the contributions of SST anomalies in the Maritime Continent,central and eastern equatorial Pacific,and North Atlantic.Furthermore,both the multi-decadal warming trend and the interannual variability of the Indian Ocean SSTs had positive impacts on the extreme floods.Our results imply that the strong multi-decadal warming trend in the Indian Ocean needs to be taken into consideration for the prediction/projection of summer extreme floods over the MLYRV in the future.

The Coupling Effect of Flood Discharge and Storm Surge on Extreme Flood Stages: A Case Study in the Pearl River Delta, South China

The low-lying Pearl River Delta in South China is subject to severe flood threats due to watershed floods,sea level rise,and storm surges.It is still unknown to what extent and how far inland storm surges and sea level rise impact the extreme flood stages.This study investigated the coupling effect of flood discharge and storm surge on the extreme flood stages in the Pearl River Delta by using on site observations and simulations generated by the Hydrologic Engineering Center-River Analysis System model.The results show that flood discharges dominated the flood stages in the middle and upper Pearl River Delta,while the storm surges had maximum impact near the river mouth.The storm surges and flood stages showed a significant increase after 2002 in the Hengmen waterway.The design flood stages for the post-2002 period were 0.23–0.89 m higher than the pre-2002 ones at Hengmen at the six return periods from 5 to 200 years examined in this study.Their difference declined toward the upper waterway and reduced to zero about 23 km away from the Hengmen outlet.The coincidence of extreme flood discharges and storm surges further escalates the extreme flood stages in the lower 30 km of estuarine waterways.Our results quantify the severe threats due to sea level rise and intensified storm surges in the lower Pearl River Delta,and are significant for urban planning and designing and managing flood control facilities in the Pearl River Delta and in other coastal fluvial deltas.

Rainfall erosivity and sediment dynamics in the Himalaya catchment during the Melamchi flood in Nepal

Rainfall erosivity is an indicator of rainfall potential to cause soil erosion.The Melamchi extreme flood occurred on June-15 and recurred on July-31,2021 in Nepal.During these flooding events,a large volume of sediments were eroded,transported and deposited due to the high rainfall erosivity of the basin.In this study,the temporal and the spatial distribution of rainfall erosivity within the Melamchi River Basin was estimated and further linked to sediment discharge and concentration at various sites along the river segments.The daily rainfall data for the event year 2021 of the entire basin were used.Validation was performed by post-flooding grain size sampling.The result showed that rainfall and rainfall erosivity exhibit pronounced intensity within the Melamchi River basin,particularly at Sermathang and Tarkeghang,both located in the middle section of the basin.The average annual rainfall in the Melamchi region was 3140.39 mm with an average annual erosivity of 18302.06(MJ mm)/(ha h yr).The average daily erosivity of the basin was 358.67(MJ mm)/(ha h)during the first event and 1241(MJ mm)/(ha h)for the second event.In the upper section of sampling,the sediment size ranged from 0.1 mm to>8 mm and was poorly graded.However,the lower region had smaller sediment ranging from 0.075 mm to>4.75 mm and also well graded.The smaller size(<1 mm)sediment passing was much higher in the Chanaute(78%)and Melamchi(66.5%)river segments but the larger size(>100 mm)sediments were passed relatively higher from the Kiwil(8.20%)and Ambathan(8.39%)river segments.During premonsoon and monsoon seasons,the highest sediment concentration was found to be 563.8 g/L and 344.3 g/L in Bhimtar and the lowest was 238.5 g/L and 132.1 g/L at the Ambathan,respectively.The sediment concentration during the pre-monsoon was found to be higher than the sediment concentration during the monsoon season in the Melamchi River.The more erosive regions in the basin were associated with the presence of highly fractured rock,weathered rocks and a thrust(weak)zone.The higher rainfall erosivity at upstream and the higher sediment concentration at downstream during flooding events have coincided well in the basin.Thus,the estimation of rainfall erosivity at the catchment scale and its influences on sediment concentration in the river are crucial for erosion control measures during flooding times in the Himalaya.

G-WADI PERSIANN-CCS GeoServer for extreme precipitation event monitoring

The Center for Hydrometeorology and Remote Sensing at the University of California, Irvine （CHRS） has been collaborating with UNESCO＇s International Hydrological Program （IHP） to build a facility for forecasting and mitigating hydrological disasters. This collaboration has resulted in the development of the Water and Development Information for Arid Lands-- a Global Network （G-WADI） PERSIANN-CCS GeoServer, a near real-time global precipitation visualization and data service. This GeoServer pro- vides to end-users the tools and precipitation data needed to support operational decision making, research and sound water man- agement. This manuscript introduces and demonstrates the practicality of the G-WADI PERSIANN-CCS GeoServer for monitor- ing extreme precipitation events even over regions where ground measurements are sparse. Two extreme events are analyzed. The first event shows an extreme precipitation event causing widespread flooding in Beijing, China and surrotmding districts on July 21, 2012. The second event shows tropical storm Nock-Ten that occurred in late July of 2011 causing widespread flooding in Thailand. Evaluation of PERSIANN-CCS precipitation over Thailand using a rain gauge network is also conducted and discussed.

Prediction of the future flood severity in plain river network region based on numerical model: A case study

Suzhou is one of China＇s most developed regions, located in the eastern part of the Yangtze Delta. Due to its location and river features, it may at a high risk of flood under the climate change background in the future. In order to investigate the flood response to the extreme scenario in this region, 1-D hydrodynamic model with real-time operations of sluices and pumps is established. The rain-runoff processes of the urban and rural areas are simulated by two lumped hydrologic models, respectively. Indicators for a quantitative assessment of the flood severity in this region are proposed. The results indicate that the existing flood control system could prevent the Suzhou Downtown from inundation in the future. The difficulty of draining the Taihu Lake floods should be given attention to avoid the flood hazard. The modelling approach based on the in-bank model and the evaluation parameters could be effective for the flood severity estimation in the plain river network catchment. The insights from this study of the possible future extreme flood events may assist the policy making and the flood control planning.