Flood risk and its reduction in China

Flash floods in mountainous catchments are often caused by the rainstorm, which may result in more severe consequences than plain area floods due to less timescale and a fast-flowing front of water and debris. Flash flood forecasting is a huge challenge for hydrologists and managers due to its instantaneity, nonlinearity, and dependency. Among different methods of flood forecasting, data-driven models have become increasingly popular in recent years due to their strong ability to simulate nonlinear hydrological processes. This study proposed a Support Vector Regression (SVR) model, which is a powerful artificial intelligence-based model originated from statistical learning theory, to forecast flash floods at different lead times in a small mountainous catchment. The lagged average rainfall and runoff are identified as model input variables, and the time lags associated with the model input variables are determined by the hydrological concept of the time of response. There are 69 flash flood events collected from 1984 to 2012 in a mountainous catchment in China and then used for the model training and testing. The contribution of the runoff variables to the predictions and the phase lag of model outputs are analyzed. The results show that: (i) the SVR model has satisfactory predictive performances for one to three-hours ahead forecasting; (ii) the lagged runoff variables have a more significant effect on the predictions than the rainfall variables; and (iii) the phase lag (time difference) of prediction results significantly exists in both two- and three-hours-ahead forecasting models, however, the input rainfall information can assist in mitigating the phase lag of peak flow.

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Flash flood forecasting using Support Vector Regression model in a small mountainous catchment.

Recent years have witnessed considerable developments in multiple fields with the potential to enhance our capability of forecasting pluvial flash floods, one of the most costly environmental hazards in terms of both property damage and loss of life. This work provides a summary and description of recent advances related to insights on atmospheric conditions that precede extreme rainfall events, to the development of monitoring systems of relevant hydrometeorological parameters, and to the operational adoption of weather and hydrological models towards the prediction of flash floods. With the exponential increase of available data and computational power, most of the efforts are being directed towards the improvement of multi-source data blending and assimilation techniques, as well as assembling approaches for uncertainty estimation. For urban environments, in which the need for high-resolution simulations demands computationally expensive systems, query-based approaches have been explored for the timely retrieval of pre-simulated flood inundation forecasts. Within the concept of the Internet of Things, the extensive deployment of low-cost sensors opens opportunities from the perspective of denser monitoring capabilities. However, different environmental conditions and uneven distribution of data and resources usually leads to the adoption of site-specific solutions for flash flood forecasting in the context of early warning systems.

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Recent Advances in Real-Time Pluvial Flash Flood Forecasting

Flash floods occur frequently and distribute widely in mountainous areas because of complex geographic and geomorphic conditions and various climate types. Effective flash flood forecasting with useful lead times remains a challenge due to its high burstiness and short response time. Recently, machine learning has led to substantial changes across many areas of study. In hydrology, the advent of novel machine learning methods has started to encourage novel applications or substantially improve old ones. This study aims to establish a discharge forecasting model based on Long Short-Term Memory (LSTM) networks for flash flood forecasting in mountainous catchments. The proposed LSTM flood forecasting (LSTM-FF) model is composed of T multivariate single-step LSTM networks and takes spatial and temporal dynamics information of observed and forecast rainfall and early discharge as inputs. The case study in Anhe revealed that the proposed models can effectively predict flash floods, especially the qualified rates (the ratio of the number of qualified events to the total number of flood events) of large flood events are above 94.7% at 1–5 h lead time and range from 84.2% to 89.5% at 6–10 h lead-time. For the large flood simulation, the small flood events can help the LSTM-FF model to explore a better rainfall-runoff relationship. The impact analysis of weights in the LSTM network structures shows that the discharge input plays a more obvious role in the 1-h LSTM network and the effect decreases with the lead-time. Meanwhile, in the adjacent lead-time, the LSTM networks explored a similar relationship between input and output. The study provides a new approach for flash flood forecasting and the highly accurate forecast contributes to prepare for and mitigate disasters.

https://www.mdpi.com/2073-4441/12/1/109/pdf

Flash Flood Forecasting Based on Long Short-Term Memory Networks

A systematic review of the health co-benefits of urban climate change adaptation

This paper summarizes the main flash flood early-warning systems of America, Europe, Japan, and Taiwan China and discusses their advantages and disadvantages. The latest development in flash flood prevention is also presented. China’s flash flood prevention system involves three stages. Herein, the warning methods and achievements in the first two stages are introduced in detail. Based on the worldwide experience of flash flood early-warning systems, the general research idea of the third stage is proposed from the viewpoint of requirements for flash flood prevention and construction progress of the next stage in China. Real-time dynamic warning systems can be applied to the early-warning platform at four levels (central level, provincial level, municipal level, and county level) . Through this, soil moisture, peak flow, and water level can be calculated in real-time using distributed hydrological models, and then flash flood warning indexes can be computed based on defined thresholds of runoff and water level. A compound warning index (CWI) can be applied to regions where rainfall and water level are measured by simple equipment. In this manner, flash-flood-related factors such as rainfall intensity and antecedent and cumulative rainfall depths can be determined using the CWI method. The proposed methodology for the third stage could support flash flood prevention measures in the 13th 5-Year Plan for Economic and Social Development of the People’s Republic of China (2016–2020). The research achievements will serve as a guidance for flash flood monitoring and warning as well as flood warning in medium and small rivers.

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A review of advances in China’s flash flood early-warning system

Research on flash flood disaster warning index: Case study of Luoning County

The utility model relates to a chain bag of assembled flood control small dike Its purpose is in order to provide a simple structure, the chain bag of effect of flood prevention flood control small dike good, that application scope is wide The utility model discloses a chain bag unit of multiunit, the chain bag unit of every group include again that the chain bag body draws windbreak with carrying The long cubic structure of chain bag body top end opening, the border position of the chain bag body left and right sides is provided with braced frame The chain internal portion of bag is provided with a plurality of division board bags along the extending direction of the chain bag body, and the division board bag becomes a plurality of cavitys along vertical direction and chain bag bag body connected, each division board bag with the internal part of chain bag The border position interval of both sides is provided with a plurality of carrying and draws windbreak around the chain bag body top, puies forward the one end and chain bag bag body connected of drawing windbreak, carries the other end that draws windbreak and is provided with and prevent wind the ring, thereby consolidate the chain bag body subaerial through preventing wind the ring to fix, connects gradually between the chain bag unit of multiunit

Chain bag of assembled flood control small dike

Groundwater is almost the unique source of water for Weizhou Island. Groundwater overexploitation has caused the groundwater level gradually dropping these years, causing many environmental problems such as seawater intrusion. On the basis of previous water resources survey and the understanding of the water cycle of Weizhou Island, the precipitation-runoff and variable-density groundwater flow analysis model in Weizhou Island was established. Model parameters were identified by historical rainfall and groundwater level data.

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Analysis of Water Cycle in Weizhou Island of Beihai City, Guangxi Province, Part I: Theory and Model Parameter Identification

To relieve the drop of groundwater and seawater intrusion in Weizhou Island caused by overexploitation, the analysis model of precipitation-runoff and variable-density groundwater flow in Weizhou Island was established and the model’s parameter identification results were used to investigate groundwater level and seawater/freshwater interface changes under different groundwater exploitation plans. Thereafter, a rational groundwater exploitation plan could be made to prevent the lowering of groundwater levels caused by ground water overexploitation and ecological deterioration caused by seawater intrusion. This could help accelerating the recovery of ground water and maintaining ecological system.

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Zhang Shunfu

Papers

A review of advances in China’s flash flood early-warning system

Research on flash flood disaster warning index: Case study of Luoning County

Chain bag of assembled flood control small dike

Analysis of Water Cycle in Weizhou Island of Beihai City, Guangxi Province, Part I: Theory and Model Parameter Identification

Analysis of Water Cycle in Weizhou Island of Beihai City, Guangxi Province, Part II: Study On Groundwater Exploitation Plan