The Critical Rainfall Characteristics for Torrents and Debris Flows in the Wenchuan Earthquake Stricken Area

Critical rainfall assessment is a very important tool for hazard management of torrents and debris flows in mountainous areas. The Wenchuan Earthquake 2008 caused huge casualties and property damages in the earthquake-stricken area,which also generated large quantities of loose solid materials and increased occurrence probabilities of debris flows. There is an urgent need to quantify the critical rainfall distribution in the area so that better hazard management could be planned and if real time rainfall forecast is available,torrent and debris flow early-warning could be issued in advance. This study is based on 49-year observations (1954-2003) of up to 678 torrent and debris flow events. Detailed contour maps of 1 hour and 24 hour critical rainfalls have been generated (Due to the data limitation,there was insufficient 10 minute critical rainfall to make its contour map). Generally,the contour maps from 1 hour and 24 hours have similar patterns. Three zones with low,medium and high critical rainfalls have been identified. The characteristics of the critical rainfall zones are linked with the local vegetation cover and land forms. Further studies and observations are needed to validate the finding and improve the contour maps.

A multiobjective evolutionary optimization method based critical rainfall thresholds for debris flows initiation

At present,most researches on the critical rainfall threshold of debris flow initiation use a linear model obtained through regression.With relatively weak fault tolerance,this method not only ignores nonlinear effects but also is susceptible to singular noise samples,which makes it difficult to characterize the true quantization relationship of the rainfall threshold.Besides,the early warning threshold determined by statistical parameters is susceptible to negative samples(samples where no debris flow has occurred),which leads to uncertainty in the reliability of the early warning results by the regression curve.To overcome the above limitations,this study develops a data-driven multiobjective evolutionary optimization method that combines an artificial neural network(ANN)and a multiobjective evolutionary optimization implemented by particle swarm optimization(PSO).Firstly,the Pareto optimality method is used to represent the nonlinear and conflicting critical thresholds for the rainfall intensity I and the rainfall duration D.An ANN is used to construct a dual-target(dual-task)predictive surrogate model,and then a PSO-based multiobjective evolutionary optimization algorithm is applied to train the ANN and stochastically search the trained ANN for obtaining the Pareto front of the I-D surrogate prediction model,which is intended to overcome the limitations of the existing linear regression-based threshold methods.Finally,a double early warning curve model that can effectively control the false alarm rate and negative alarm rate of hazard warnings are proposed based on the decision space and target space maps.This study provides theoretical guidance for the early warning and forecasting of debris flows and has strong applicability.

Response of Flash Flood Early Warning Critical Rainfall to Storm Pattern in South Branch of Censhui Watershed

Critical rainfall estimation for early warning of rainstorm-induced flash flood is an inverse rainstorm-runoff process based on warning discharge threshold for a warning station of interest in a watershed. The key aspects of critical rainfall include rainfall amount and rainfall duration. Storm pattern affects highly the estimation of critical rainfall. Using hydrological modeling technique with detailed sub-basin delineation and manual for design rainstorm-runoff computation, this study first introduced basic concept and analysis methods on critical rainfall for flash flood early warning, then, investigated the responses of flash flood warning critical rainfall to storm pattern. Taking south branch of Censhui watershed in China as an example, critical rainfall in case of typical storm patterns for early warning of rainstorm-induced flash flood were estimated at 3 warning stations. This research illustrates that storm pattern plays important role in the estimation of critical rainfall and enough attention should also be paid to storm pattern when making a decision on whether a warning to be issued or not.

Critical Rainfall Analysis on Flash Flood Early Warning for South Branch of Censhui Watershed

Critical rainfall for flash flood early warning is a converse result of precipitation-runoffprocess based on warning discharge threshold for a warning station of interest in a watershed; the key aspects of critical rainfall include rainfall amount and rainfall duration Using hydrological modeling technique with detailed sub-basin delineation and manual for design precipitation-runoff computation, this study introduces basic concept and methods of analyzing critical rainfall for flash flood early warning. Taking South Branch of Censhui watershed in China as an example, typical critical rainfalls for flash flood dynamic early warning were estimated for 3 warning stations located in the watershed. This research illustrates that detailed watershed characteristics in the context of several warning stations can be modeled in-depth by further delineating the watershed into smaller sub-basins to simulate spatial distribution of various basin parameters. It further confirms that time of concentration of a watershed is an important factor to rainfall duration determination, and the antecedent soil moisture condition of a watershed has significant impact on critical rainfall for same rainfall duration.

Estimation of Critical Rainfall for Flood Disasters in the Qinghai-Tibet Plateau

According to the results of The Second Comprehensive Scientific Expedition on the Qinghai-Tibet Plateau,the balance of solid and liquid water on the Qinghai-Tibet Plateau is disturbed,and a large amount of solid water,such as glaciers and perpetual snow,is transformed into liquid water,which aggravates the risk of flood disasters in the Plateau.Based on the historical flood disaster records of the Qinghai-Tibet Plateau,this paper analyzed the temporal and spatial distribution characteristics of the flood disasters in the Plateau,and estimated the critical rainfall for the flood disasters combined with precipitation data from the meteorological stations in each basin of the Qinghai-Tibet Plateau.The results show that most of the flood disaster events in the Plateau are caused by precipitation,and the average annual occurrence of flood disasters is more than 30 cases and their frequency is on the rise.The high frequency areas of flood disasters in the Qinghai-Tibet Plateau are mainly in the Hehuang Valley and the Hengduan Mountains area;the secondary high frequency areas are located in the valley area of South Tibet and the peripheral area of the Hehuang valley.Finally,we found that the highest critical rainfall value of flood disasters in the Qinghai-Tibet Plateau is in the southern area of the plateau,followed by the eastern and southeastern parts of the plateau,and the lowest values are in the central,western and northern parts of the Plateau.

Critical rainfall intensity for safe evacuation from underground spaces with flood prevention measures

Underground space in urban areas has been expanding rapidly during recent decades, and so has the incidence of fatal accidents and extensive damage to facilities resulting from underground flooding. To evaluate the safe evacuation potential of individual underground spaces in flood-prone urban areas, the hydraulic effects of flood prevention measures, e.g., stacked flashboards or sandbags and elevated steps, were incorporated in a proposed formula for estimating the depth of inundation of an underground floor. A mathematical expression of the critical rainfall intensity for safe evacuation from underground space was established and then evaluated for two types of underground spaces, an underground shopping mall and a building basement. The results show that the critical rainfall intensity for any individual underground space can be determined easily using the proposed analytical or graphical solution. However, traditional underground flood prevention measures cannot improve safety if people refuse to evacuate immediately once water intrudes into the underground space.