Short-time Heavy Rainfall Research Articles

RETRACTED ARTICLE: Research on Construction Risks and Countermeasures of Concrete Dam

The harsh environment will reduce the interlayer bonding quality of mass concrete and cause plastic cracking. These defects will seriously affect the safety and durability of the structure. This study tested the layer state (water content and penetration resistance), interlayer mechanical properties, and early-age crack resistance of concrete to evaluate the impact of extreme weather on concrete interlayer properties and crack resistance. Furthermore, the interlayer splitting tensile strength of concrete under different treatment measures (covering insulation quilts and artificial grooves) was analyzed to find a method to reduce the construction risk of mass concrete. At the same time, the early-age crack resistance of concrete under different treatment measures (covering insulation quilts and adding PVA fibers) was evaluated. The results showed that the interlayer splitting tensile strength of concrete decreased by 50%, 40%, 29%, and 70%, respectively, compared with bulk concrete under extreme weather conditions (high temperature, strong winds, steep descent in temperature, and short-time heavy rainfall). Covering insulation quilts can reduce the construction risk of concrete under extreme weather conditions such as high temperature, strong winds and steep descent in temperature. This is mainly due to the fact that insulation quilt reduces the impact of the external environment on the concrete and effectively prevents the evaporation of moisture inside the concrete. In addition, covering insulation quilts can reduce the total cracking area of concrete under extreme weather conditions (strong winds and dry-heat, strong winds and cold waves, and short-time heavy rainfall) by 85–100%. At the same time, adding PVA fibers can inhibit the generation and expansion of micro-cracks on the concrete surface. This is due to the bridging and cracking resistance of PVA fibers.

Prediction of Short-Time Rainfall Based on Deep Learning

Short-time heavy rainfall is a kind of sudden strong and heavy precipitation weather, which seriously threatens people’s life and property safety. Accurate precipitation nowcasting is of great significance for the government to make disaster prevention and mitigation decisions in time. In order to make high-resolution forecasts of regional rainfall, this paper proposes a convolutional 3D GRU (Conv3D-GRU) model to predict the future rainfall intensity over a relatively short period of time from the machine learning perspective. Firstly, the spatial features of radar echo maps with different heights are extracted by 3D convolution, and then, the radar echo maps on time series are coded and decoded by using GRU. Finally, the trained model is used to predict the radar echo maps in the next 1-2 hours. The experimental results show that the algorithm can effectively extract the temporal and spatial features of radar echo maps, reduce the error between the predicted value and the real value of rainfall, and improve the accuracy of short-term rainfall prediction.

Analysis on the Influence of Topography on a Short-Time Local Heavy Rainfall Forecast in Western Xinjiang

Based on the prediction results of RmAPs-CAV1.0, a short time heavy rainfall in western Xinjiang was simulated and analyzed. By comparing the forecast results with the actual precipitation, it is found that RMAPS-CAV1.0 can accurately reflect the important forecast parameters of the short-time heavy precipitation system, such as precipitation level and starting time. Contrast observation and prediction results found that the terrain has forced effect to the surface wind field, the precipitation process in Yili valley special opening of the west mountain terrain, the center is located in Kazakhstan in central Asia low vortex cause lower for the westerly Yili river valley, the center is located in the Tarim Basin of central Asia for Piandongfeng middle low vortex makes the Yili river valley, cause the Yili river valley and the lower levels of vertical wind shear reinforcement; In the Yili River Valley, the combination of topography and the central Asian vortex circulation in Kazakhstan forms a low-altitude convergence line. The low-level westerly winds transport water vapor into the valley, and the northerly airflow in the valley and the northern margin of the Taklamakan Desert converge near the windward slope, and the enhanced upward movement results in the uplift of the water vapor accumulated in the valley. The result analysis of RMAPS-CAV1.0 shows that the warm and cold airflow and water vapor under the action of topography have important contributions to the generation of this precipitation.

Application of radar data assimilation on convective precipitation forecasts based on water vapor retrieval

Based on a short-time heavy rainfall in Anhui and the weather research and forecasting (WRF) model, the water vapor in the initial field of the model is retrieved using the statistical relationships of the reflectivity factor from the Doppler weather radar with the relative humidity and hydrometeor. Three-dimensional variational (3DVAR) assimilation method is used to assimilate the radar reflectivity factor and radial velocity, and then the impact of assimilating retrieved water vapor on the analysis and forecast of the torrential rain is assessed. The results show that, after assimilating the retrieved water vapor, the water vapor field in the model is significantly improved. The water vapor content in the middle layer of the model in the analyzed field is increased, corresponding well with the convective region. Meanwhile, the precipitation distribution during this weather process is successfully simulated. The mesoscale characteristics are better presented by the imageries of radar reflectivity factor, and false echoes are partially reduced. Besides, the prediction of short-time heavy rainfall regions is closer to the actual observations. After assimilating the retrieved water vapor, the simulated one-hour accumulated rainfall is closer to the actual observation, and the fraction skill score (FSS) is higher.

Characteristics Analysis on Short-Time Heavy Rainfall during the Flood Season in Shanxi Province, China

In order to provide a reference for the correct forecasting of short-term heavy rainfall and better disaster prevention and mitigation services in Shanxi Province, China, it is very important to carry out systematic research on short-term heavy precipitation events in Shanxi Province. Based on hourly precipitation data during the flood season (May to September) from 109 meteorological stations in Shanxi, China in 1980-2015, the temporal and spatial variation characteristics of short-time heavy rainfall during the flood season are analyzed by using wavelet analysis and Mann-Kendall test. The results show that the short-time heavy rainfall in the flood season in Shanxi Province is mainly at the grade of 20 - 30 mm/h, with an average of 97 stations having short-time heavy rainfall each year, accounting for 89% of the total stations. The short-time heavy rainfall mainly concentrated in July and August, and the maximal rain intensity in history appeared at 23 - 24 on June 17, 1991 in Yongji, Shanxi is 91.7 mm/h. During the flood season, the short-time heavy rainfalls always occur at 16 - 18 pm, and have slightly different concentrated time in different months. The main peaks of June, July and August are at 16, 17 and 18 respectively, postponed for one hour. Short-time heavy rainfall overall has the distribution that the south is more than the north and the east less than the west in Shanxi area. In the last 36 years, short-time heavy rainfall has a slight increasing trend in Shanxi, but not significant. There is a clear 4-year period of oscillation and inter-decadal variation. It has a good correlation between the total precipitation and times of short-time heavy rainfall during the flood season.

Spatio-temporal Characteristics of the Short-time Heavy Rainfall in the East of Northwest China

Spatio-temporal Characteristics of the Short-time Heavy Rainfall in the East of Northwest China

Characteristic analysis of rainstorm-induced catastrophe and the countermeasures of flood hazard mitigation about Shenzhen city

ABSTRACTBased on the statistical data of rainstorm-induced catastrophe about Shenzhen city during 1980–2014, this paper constructs a calculation model of disaster magnitude, which includes three influence factors: death toll, direct economic loss and disaster affected population. At the same time, the relationship between the disaster magnitude and the temporal, spatial and cause of the rainstorm-induced catastrophe about Shenzhen city is analysed, The results show that (1) The classification of catastrophe risk is carried out by the result of the disaster magnitude model. (2) The region where the disaster occurs frequently and seriously is located in the Midwest, and the disaster occurs infrequently and lightly is located in the south-east. (3) The rainstorm-induced catastrophe about Shenzhen City is mostly caused by persistent short-time heavy rainfall. While it occurs most frequently in July, and the most serious in September affected by the typhoon. (4) The main reasons for the occurrence of rainstorm-induced catastrophe about Shenzhen City are flood, waterlogging, tide and typhoon, of these factors waterlogging is the primary one. Finally, this paper puts forward the corresponding countermeasures of flood hazard mitigation in Shenzhen City.

Effects of rainy weather on traffic accidents of a freeway using cellular automata model**Project supported by the National Natural Science Foundation of China (Grant No. 50478088) and the Natural Science Foundation of Hebei Province, China (Grant No. E2015202266)

The aim of this work is to investigate the influence of rainy weather on traffic accidents of a freeway. The micro-scale driving behaviors in rainy weather and possible vehicle rear-end and sideslip accidents are analyzed. An improved CA model of two lanes one-way freeway is presented, where some vehicle accidents will occur when the necessary conditions are simultaneously satisfied. The characteristics of traffic flow under different rainfall intensities are discussed and the accident probabilities are analyzed via the simulation experiments by using variable speed limit (VSL) and incoming flow control. The results indicate that the measures are effective especially during heavy rainstorms or short-time heavy rainfall. According to different rainfall intensities, an appropriate strategy should be adopted in order to reduce the probability of vehicle accidents and enhance traffic flux as well.

The formation of runoff-generated debris flow in Southwestern of China: take Gangou as an example

In the mountain area of Southwestern China, there are large quantities of runoff-generated debris flows that are threatening the local people and facilities seriously. Gangou is a typical runoff-generated debris flow; its source is old deposit from floods and the debris flows downstream of the channel. On June 30, 2005, Gangou occurred debris flow, the debris flow destroying the road, the communications facilities and the farmland at the gully mouth. Unlike the formation mechanisms of other debris flows, the formation of 2005 debris flow in Gangou has its distinctive characteristics as follows. (1) The supply of the loose sources is intensive and distribute near the mouth of the gully; it is rare to see any debris flow initiate at such a lower location. (2) The debris flow finishes its initiation, flow and deposition around the 700-m-long channel, accompanied with the blocking process in the gully when the debris flow ran out; however, 10 min later, it releases and amplifies the peak flow about three times. (3) The topographic condition of the basin does not contribute much to the formation of the 2005 debris flow; instead, its formation is the result of the co-effort of continuous rainfall and a short-time heavy rainfall. In other words, the previous cumulative precipitation enables the moisture content of the soil on the right bank of the gully to reach saturation; then the soil slides into the channel under the action of the heavy rainfall at a later time. Meanwhile, the heavy rainfall accelerates the formation of gully run-off and initiates the loose mass in the channel from slide, thus forming the debris flow.

Severe hail identification model based on saliency characteristics

There are always high false alarm ratios when warning against the severe hail with the severe hail index (SHI) which is supplied by digital weather radar system. To solve this problem, the extraction algorithm with several novel features, such as "overhang", is designed and realized, and these features can describe the severe hail conceptual model from different aspects. Then we take short-time heavy rainfall cells which are easy to be confused with severe hail cells as counter examples to perform statistic analysis for these features and the SHI. Test results show that they have more significant difference between two kinds of samples and hence each of them can reflect one aspect characteristic of severe hail cells. Then a severe hail recognition model that is the Support Vector Machine with radial primary kernel function is learned. Finally, the normalized distance between the sample to be recognized and the optimal separating hyper-plane is determined as a new SHI for warning against the severe hail. Experimental results show that the method proposed in this paper makes severe hail hit ratio higher than the SHI being used and the false alarm ratio is reduced substantially.

Numerical investigation of the performance of covers with capillary barrier effects in South China

A cover with capillary barrier effects (CCBEs) is a promising final cover for controlling water infiltration into a waste containment system. A CCBE consisting of a layer of fine soil and a layer of coarse soil relies on the particle size contrast of the two soils. Although CCBEs have been successfully used in dry climate, their performance under high precipitation intensities and high evaporation conditions (e.g., in South China) is still unclear. This paper aims to evaluate the performance of the CCBE in high-precipitation areas and propose appropriate combinations of local soils for constructing a CCBE in South China. Several combinations of lean clay, clayed sand, and silty sand with gravel are examined using saturated/unsaturated seepage analysis. Two contrasting conditions, i.e., a drizzle lasting for a long time and an intense storm lasting for a short time, are applied to the covers. The covers perform well when subject to prolonged small rainfall at an initial maximum suction of 150kPa. When subject to a short-time heavy rainfall, breakthrough occurs in the cover consisting of clayed sand overlying silty sand with gravel. Of the three covers, a CCBE consisting of lean clay overlying silty sand with gravel performs well under both prolonged light rainfall and short time heavy rainfall conditions. This CCBE has the longest period of time before breakthrough and the least amount of percolated water under prolonged heavy rainfall.

The Stability Studies of Soil Slope under the Action of Short-Time Heavy Rainfall

Based on the saturated-unsaturated seepage theory and the unsaturated shear strength, the numerical simulations of soil slope seepage field in short-time heavy rainfall was carried out, and on this basis calculated the slope safety coefficient at different rainfall time. The research shows that: the rainfall infiltration will cause the slope soil matrix suction decreased or even disappeared which leads to the slope shear strength reduce; Rainwater infiltration increases the transient water load of infiltration area; and under the dual role of matrix suction reduction and transient water load increasing, the slope safety coefficient has the downward trend obviously.

Bioavailable phosphorus transport from a hillslope cropland of purple soil under natural and simulated rainfall

To further understand the mechanism of bioavailable total P (BAP) and bioavailable dissolved P (BDP) transport by overland and subsurface flow, we exposed a runoff plot 4.5 m long × 1.5 m wide × 0.6 m deep to simulated and natural rainfall in order to study the effects of rainfall type, rainfall intensity, and vegetation cover on BAP and BDP transport. The results showed that vegetation cover could alleviate the discharge of overland flow and sediment transport and enhance subsurface flow. BAP transport significantly increased with elevated rainfall intensity. Vegetation cover reduced the BAP transport by overland flow and increased it by subsurface flow. BDP transport showed no significant relationship with vegetation cover and rainfall type. The bioavailable particulate P (BPP) transport by overland flow contributed to no less than 90% by weight of total BAP, and the BPP transport by subsurface flow contributed to no less than 60% by weight of total BAP. Short-time heavy rainfall caused more BAP transport and accelerated non-point source pollution.