Rainstorm Waterlogging Research Articles

Regional assessment on ecological risk of ecosystems under natural hazards: an application in Guangdong Province (SE China)

Ecological risk studies have progressed significantly in recent decades. Although not completely theoretical compared with traditional fields of science, the ecological risk assessment, at practical level, shows very important to maintain a healthy ecosystem for human well-being. Ecological risk is a combination of hazard, vulnerability, and the exposed ecosystem values. By implementing this conceptual model, taking Guangdong Province in southeastern China as a case study, using the ArcGIS technique, an ecosystem-based assessment for ecological risks of tropical cyclones, rainstorm waterlogging, and geohazards, as well as their comprehensive ecological risk was applied to 21 administrative municipalities in the study area. The results show that Zhuhai, Jiangmen, Yangjiang, Zhanjiang, and Shenzhen were the top five municipalities with highest comprehensive hazards of multi-hazards. There were no high and very high grades of ecological risk for either single hazards or multi-hazards, but relatively, the four municipalities of Zhuhai, Jiangmen, Yangjiang, and Zhanjiang had the highest grades of moderate ecological risk in Guangdong Province. These findings intended to help with disaster mitigation and management decisions on a regional scale and hope to bring more attentions on ecological risk of ecosystems under natural hazards.

Multiscale Variability of Precipitation and Their Teleconnection with Large-scale Climate Anomalies: A Case Study of Xi'an City, China

Wang, X.; Jiang, R.; Xie, J.; Zhao, Y.; Li, F., and Zhu, J., 2019. Multiscale variability of precipitation and their teleconnection with large-scale climate anomalies: A case study of Xi'an city, China. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 417–426. Coconut Creek (Florida), ISSN 0749-0208.The changes of precipitation affect the urban rainstorm waterlogging and water resources management, which have important influences on the sustainable development of society. The primary objective of the paper is to provide theoretical basis for local water resources management and disaster prevention and reduction by analyzing the multiscale variability of precipitation and their teleconnection with large-scale climate anomalies in Xi'an city of China. The change characteristics of precipitation and extreme precipitation indices were investigated using Mann-Kendall test, Spearman's rank correlation and wavelet analysis. The cross wavelet transform and wavelet coherence were used to explore the correlations between the precipitation and large-scale teleconnection indices such as Arctic Oscillation (AO), Southern Oscillation Index (SOI), El Nino-Southern Oscillation (ENSO) and sunspot. Results indicate that: the precipitation was mainly concentrated in summer, followed by autumn. The annual, seasonal and monthly precipitation except June and August had decreasing trends, and the magnitudes of precipitation decrease were more pronounced in spring, April and November. The change patterns varied for extreme precipitation indices. The temporal variation in extreme precipitation indices indicated that the extreme precipitation events had mainly increased during 1971-1990 and 1991-2017, and decreased during 1951-1970 and 1951-2017, especially, increased more pronounced during 1991-2017 and decreased more pronounced during 1951-1970. The precipitation exhibited a fluctuant change from increase to decrease, then increase to decrease and finally increase trends, and there was an abrupt change point in 1965. The annual precipitation had statistically significant cycles of 3-5 year and 7-10 year at 5% significance level. The large-scale teleconnection indices affected the precipitation in Xi'an city. The phase differences between precipitation and teleconnection indices including AO and SOI were in-phase dominated, and anti-phase dominated between precipitation and teleconnection indices including ENSO and sunspot, indicating that the AO and SOI exerted positive climate impacts on the precipitation and vice-versa for ENSO and sunspot.

Simulation of Urban Rainstorm Waterlogging and Pipeline Network Drainage Process Based on SWMM

Urban flood has already become weaknesses of flood control system in China. Flood and pipeline drainage calculation based on hydraulics model plays a key role in flood monitoring, warning and control management. On the basis of the topographic maps (high-precision DEM), underground drainage networks, land use and rainfall data in Enshi City, a SWMM-based urban flood model is constructed, which is applied to calculating rainstorm waterlogging and pipeline drainage process under the designed storm probability of 0.01, 0.02 and 0.05, and the designed storm period of 1 hour and 3 hours. The pipeline drainage peak flow of different pipeline type is also retrieved. And results suggest that SWMM is a reliable urban storm water model, which is suitable for urban storm flood simulation and pipeline network drainage analysis.

A methodology for simple 2-D inundation analysis in urban area using SWMM and GIS

Urban waterlogging occurred frequently in recent years, causing serious social harms and huge economic losses. Accurate waterlogging warning is important for disaster prevention and mitigation. Urban rainstorm waterlogging processing based on Geographic Information System (GIS) and Storm Water Management Model (SWMM) can provide prediction and management of flood situation, but the previous methods of catchments from a single aspect of hydrology or geometry cannot reflect the dual impact of pipe networks and terrain to drainage, and the available inundation algorithms achieved some unreasonable results due to the artificial boundaries. In this paper, a methodology for simple 2-D inundation analysis in urban area using SWMM and GIS is introduced, which need not edit SWMM’s original code. Furthermore, a geometric method of catchments division and inundation algorithm are proposed to improve accuracy. The revised catchments division method provides a good result of supplementing the drainage of terrain, and the improved inundation algorithm can obtain a reasonable inundation distribution based on the principle of source diffusion and dynamic distribution without any boundary limit. The case study was performed in Longwen District of Zhangzhou, and good results are achieved: (1) The external outflow percentage of the revise method is always bigger than that of the geometric method, and the value of the revised method is 25.18%, while that of geometric method is only 19.56% at rainfall peak, and (2) the less the rainfall is, the less grids flooded in two algorithms there are with only 14.30% when the rainfall is 0.1 mm.

Integrated assessment of ecological risk for multi-hazards in Guangdong province in southeastern China

Guangdong Province is the most populous and economically developed province in southeastern China. Tropical cyclones, rainstorm waterlogging, and geohazards are the principal natural hazards in this region. Using information acquisition analysis, entropy weighting, the ArcGIS technique, the concept of hazard chains, the spatial heterogeneity of hazards, vulnerability, and ecological risk from single hazards and multi-hazards were determined for grids of 1 × 1 km2; the ecological risks for each administrative city were ranked. Jiangmen City was the top one ranking in the 21 cities with highest ecological risks for multi-hazards, tropical cyclones, and rainstorm waterlogging; Qingyuan City was the highest one for the ecological risk of geohazards. Areas with grades of very high, high, moderate, low, and very low ecological risk accounted for 1.78%, 7.10%, 18.22%, 34.39%, and 38.51% of Guangdong Province, respectively. Most areas of Guangdong Province had favorable ecological environments and low ecological risks. Natural hazard assessment greatly benefits from ArcGIS because spatial methodologies can be fully explored during the entire risk evaluation process, from data integration to risk appraisal, and finally for decision-making. This study concludes that integrated approaches to multi-hazard assessment may assist in risk management of natural hazards in Guangdong Province in southeastern China.

A dynamic impact assessment method for rainstorm waterlogging using land-use data

ABSTRACTAs a result of rapid urbanization and climate change, many large- and medium-sized cities in China frequently undergo urban disasters with severe impacts that result in many casualties, induce significant economic losses, and restrict sustainable social and economic development. Providing timely and accurate early warnings is the most effective measure for disaster prevention and mitigation before such disasters can impose severe impacts. In this study, we propose a dynamic impact assessment method for rainstorm waterlogging using land-use data. First, based on a detailed collection of disaster prevention and mitigation data, we construct an impact assessment index based on the assessment objects of this study. Then, a waterlogging simulation is performed, and the simulation results are found to meet the assessment requirements. Finally, we conduct an impact assessment every half hour during a heavy rainfall event and evaluate the performance of the proposed method by assessing the socioeconomic impact, object impact, industry impact, regional impact, and comprehensive impact of the event. These assessments produce valuable information for providing diverse and timely services in the event of urban waterlogging.

Spatiotemporal Variance Assessment of Urban Rainstorm Waterlogging Affected by Impervious Surface Expansion: A Case Study of Guangzhou, China

Urban rainstorm waterlogging has become a typical “city disease” in China. It can result in a huge loss of social economy and personal property, accordingly hindering the sustainable development of a city. Impervious surface expansion, especially the irregular spatial pattern of impervious surfaces, derived from rapid urbanization processes has been proven to be one of the main influential factors behind urban waterlogging. Therefore, optimizing the spatial pattern of impervious surfaces through urban renewal is an effective channel through which to attenuate urban waterlogging risk for developed urban areas. However, the most important step for the optimization of the spatial pattern of impervious surfaces is to understand the mechanism of the impact of urbanization processes, especially the spatiotemporal pattern of impervious surfaces, on urban waterlogging. This research aims to elucidate the mechanism of urbanization’s impact on waterlogging by analysing the spatiotemporal characteristics and variance of urban waterlogging affected by urban impervious surfaces in a case study of Guangzhou in China. First, the study area was divided into runoff plots by means of the hydrologic analysis method, based on which the analysis of spatiotemporal variance was carried out. Then, due to the heterogeneity of urban impervious surface effects on waterlogging, a geographically weighted regression (GWR) model was utilized to assess the spatiotemporal variance of the impact of impervious surface expansion on urban rainstorm waterlogging during the period from the 1990s to the 2010s. The results reveal that urban rainstorm waterlogging significantly expanded in a dense and circular layer surrounding the city centre, similar to the impervious surface expansion affected by urbanization policies. Taking the urban runoff plot as the research unit, GWR has achieved a good modelling effect for urban storm waterlogging. The results show that the impervious surfaces in the runoff plots of the southeastern part of Yuexiu, the southern part of Tianhe and the western part of Haizhu, which have experienced major urban engineering construction, have the strongest correlation with urban rainstorm waterlogging. However, for different runoff plots, the impact of impervious surfaces on urban waterlogging is quite different, as there exist other influence factors in the various runoff plots, although the impervious surface is one of the main factors. This result means that urban renewal strategy to optimize the spatial pattern of impervious surfaces for urban rainstorm waterlogging prevention and control should be different for different runoff plots. The results of the GWR model analysis can provide useful information for urban renewal strategy-making.

An Emergency Decision-Making Method for Urban Rainstorm Water-Logging: A China Study

With the rapid development of the urbanization process, rainstorm water-logging events occur more frequently in big cities in China, which causes great impact on urban traffic safety and brings about severe economic losses. Water-logging has become a hot issue of widespread concern in China. As one kind of natural disasters and emergencies, rainstorm water-logging has the uncertainties of occurrence, development, and evolution. Thus, the emergency decision-making in rainstorm water-logging should be carried out in stages according to its development trend, which is very complicated. In this paper, an emergency decision-making method was proposed for urban water-logging with a hybrid use of dynamic network game technology, Bayesian analysis, and multi-attribute utility theory. The dynamic game process between “rainstorm water-logging” and “decision-making group” was established and the dynamic generation of emergency schemes was analyzed based on Bayesian analysis in various stages of water-logging. In terms of decision-making attributes, this paper mainly considered two goals, i.e., ensuring smooth traffic and controlling emergency cost. The multi-attribute utility theory was used to select the final scheme. An example analysis in Guangzhou of China showed that the method is more targeted and can achieve emergency management objectives more effectively when compared with traditional methods. Therefore, it can provide reference for the scientific decision-making of emergency management in urban rainstorm water-logging.

A novel seed spread algorithm–based approach for the simulation of rainstorm water logging in urban area

A novel seed spread algorithm–based approach for the simulation of rainstorm water logging in urban area

天津武清区暴雨城市内涝风险阈值研究

天津武清区暴雨城市内涝风险阈值研究

INFLUENCE ANALYSIS OF WATERLOGGING BASED ON DEEP LEARNING MODEL IN WUHAN

Abstract. This paper analyses a large number of factors related to the influence degree of urban waterlogging in depth, and constructs the Stack Autoencoder model to explore the relationship between the waterlogging points’ influence degree and their surrounding spatial data, which will be used to realize the comprehensive analysis in the waterlogging influence on the work and life of residents. According to the data of rainstorm waterlogging in 2016 July in Wuhan, the model is validated. The experimental results show that the model has higher accuracy than the traditional linear regression model. Based on the experimental model and waterlogging points distribution information in Wuhan over the years, the influence degree of different waterlogging points can be quantitatively described, which will be beneficial to the formulation of urban flood control measures and provide a reference for the design of city drainage pipe network.

Coupling the Modified Linear Spectral Mixture Analysis and Pixel-Swapping Methods for Improving Subpixel Water Mapping: Application to the Pearl River Delta, China

High-resolution water mapping with remotely sensed data is essential to monitoring of rainstorm waterlogging and flood disasters. In this study, a modified linear spectral mixture analysis (LSMA) method is proposed to extract high-precision water fraction maps. In the modified LSMA, the pure water and mixed water-land pixels, which are extracted by the Otsu method and a morphological dilation operation, are used to improve the accuracy of water fractions. The modified LSMA is applied to the 18 October 2015 Landsat 8 OLI image of the Pearl River Delta for the extraction of water fractions. Based on the water fraction maps, a modified subpixel mapping method (MSWM) based on a pixel-swapping algorithm is proposed for obtaining the spatial distribution information of water at subpixel scale. The MSWM includes two steps in subpixel water mapping. The MSWM considers the inter-subpixel/pixel and intra-subpixel/subpixel spatial attractions. Subpixel water mapping is first implemented with the inter-subpixel/pixel spatial attractions, which are estimated using the distance between a given subpixel and its surrounding pixels and the water fractions of the surrounding pixels. Based on the initialized subpixel water mapping results, the final subpixel water maps are determined by a modified pixel-swapping algorithm, in which the intra-subpixel/subpixel spatial attractions are estimated using the initialized subpixel water maps and an inverse-distance weighted function of the current subpixel at the centre of a moving window with its surrounding subpixels within the window. The subpixel water mapping performance of the MSWM is compared with that of subpixel mapping for linear objects (SPML) and that of the subpixel/pixel spatial attraction model (SPSAM) using the GF-1 reference image from 20 October 2015. The experimental results show that the MSWM shows better subpixel water mapping performance and obtains more details than SPML and SPSAM, as it has the largest overall accuracy values and Kappa coefficients. Furthermore, the MSWM can significantly eliminate the phenomenon of jagged edges and has smooth continuous edges.

Study of risk and early warning index of rainstorm waterlogging in Wuhan City

In the present study, rainfall thresholds creating waterlogging and a waterlogging risk map were established by analyzing waterlogging monitoring and rainfall observation data in Wuhan City from 2011 to 2016. The study found that 1) Wuhan City rainstorm waterlogging occurred during the summer months, mostly in June and July, accounting for 90% of the total waterlogging; 2) Waterlogging generally occurred along the rivers and lakes near low-lying areas; 3) The longest continuous waterlogging time was greater than 10 h and the deepest water depth was 2 m; 4) The greater the cumulative rainfall over 24 h, 12 h, 6 h, or 3 h, the more severe the waterlogging was; 5) The thresholds of continuous 24 h rainfall of mild, moderate, and severe waterlogging in Wuhan City were 123, 163, and 196 mm, respectively, while 12 h cumulative rainfall thresholds were 86, 145, and 187 mm, respectively. The 6 h cumulative rainfall thresholds were 68, 113, and 135 mm, respectively, and 3 h cumulative rainfall thresholds were 40, 74, and 94 mm, respectively. If the city’s drainage capacity increases, the cumulative rainfall of waterlogging warning indicators will also need to be adjusted.

Upgrading to urban water system 3.0 through sponge city construction

Facing the pressure of excessive water consumption, high pollution load and rainstorm waterlogging, linear and centralized urban water system, system 2.0, as well as traditional governance measures gradually exposed characters of water-sensitivity, vulnerability and unsustainability, subsequently resulting in a full-blown crisis of water shortage, water pollution and waterlogging. To systematically relieve such crisis, we established urban water system 3.0, in which decentralized sewerage systems, sponge infrastructures and ecological rivers play critical roles. Through unconventional water resource recycling, whole process control of pollutions and ecological restoration, system 3.0 with integrated management measures, is expected to fit for multiple purposes which involve environmental, ecological, economic and social benefits. With advantages of flexibility, resilience and sustainability, water system 3.0 will show an increasingly powerful vitality in the near future.

Review and prospect of the emergency management of urban rainstorm waterlogging based on big data fusion

The frequent occurrence of urban rainstorm waterlogging is a severe challenge for China’s rapid urbanization, which demands prompt countermeasures. However, the fact is that the meteorological data, disaster data, and socio-economic data about rainstorm waterlogging have not been fused effectively at present, which makes it difficult to make emergency response plans in a quick and effective manner and thus hinders the emergency management. The emergency management of urban rainstorm waterlogging is a typical problem of multi-disciplines and big data, involved with meteorology, geography, information science, city planning, economics, management science and other disciplines. The great mass of related data possess rich resources, such as meteorological data, urban waterlogging data, socio-economic data, etc. As these data come from such different departments as water conservancy, meteorology, urban management, operators and Internet, with incompatible temporal and spatial scales as well as non-uniform format standards, thus bringing a huge obstacle to emergency decisions. Therefore, how to achieve the integration of the big data of disasters has become an urgent key issue. In the context of big data, urban rainstorm waterlogging ontology should be constructed in the first place, and then multi-source heterogeneous data should be effectively fused, big data dimension reduced and socio-economic losses assessed. Based on that, an emergency decision can be quickly formed with the help of expert decisions. This is concerned with such contents as large data ontology technology, data fusion methods, data dimension reduction and disaster identification, socio-economic loss assessment of disasters as well as the formation and evaluation of emergency responses. This paper, proceeding from the five parts of the big data fusion of urban rainstorm waterlogging, reviews such theoretical and practical development as ontology technology, data fusion method, data dimension reduction, disaster identification, socio-economic loss assessment of disasters, as well as the drawing up and assessment method of emergency response plans. Generally speaking, China is in urgent need of multi-disciplinary integration to collectively tackle critical problems. Future studies can be carried out in the following ways: First, design big data standard system of urban rainstorm waterlogging, so as to realize the semantic annotation of city waterlogging. Second, conduct in-depth researches on such three aspects as grid non-spatial attribute data, unified spatial coordinate system, together with the general algorithm of soft and hard data fusion, in order to solve the problems of the consistency and association between soft data and hard data. Third, extract complex changes in urban rainstorm waterlogging from multifarious data, so as to realize the dimension reduction of high dimensional data and the recognition of urban rainstorm waterlogging. Fourth, construct the risk database of urban rainstorm waterlogging disasters and assess the economic impacts of typical urban waterlogging on related regions, industries and departments, in order to provide data and scenario support for the emergency management of urban rainstorm waterlogging. Fifth, based on the fusion platform of meteorological data, urban waterlogging data and socio-economic data, by means of case-based reasoning (CBR), rule-based reasoning (RBR) and geographic information system (GIS), generate emergency response plans, and then evaluate and adjust them according to the scenario changes. Finally, what is pointed out is that the research should be carried out on the emergency management of urban waterlogging in the context of big data fusion, which can enrich the theories and methods of the emergency management of urban rainstorm waterlogging and set a typical example for the innovative exploration of the paradigm changes in big-data-driven management decisions, and for the multi-disciplinary development of management science, economics, meteorology and information science.

Deep Tunnel for Regulating Combined Sewer Overflow Pollution and Flood Disaster: A Case Study in Guangzhou City, China

The DongHaoChong (DHC) basin is located in the central city zone of Guangzhou City, China. Owing to the high density of buildings and low quality of the drainage pipe network in the city, diversion of rain and sewage is difficult. Waterlogging occurs frequently and combined sewer overflow (CSO) pollution is a serious problem during the rainy season. Therefore, a deep tunnel for the DongHaoChong basin has been planned and its construction is currently underway. An urban rainstorm model for the DongHaoChong basin was developed on the basis of the Storm Water Management Model (SWMM), and both the interception effect of CSO pollution and the degree of mitigation of flood were analyzed. Reasonable scenarios for the deep tunnel in terms of rainstorms with different design recurrence periods were evaluated. From the viewpoints of preventing rainstorm waterlogging disasters and protecting water quality in the region downstream of DongHaoChong River, the river flood control and drainage capacities of the region were improved to a 2-year rainstorm design recurrence period by the construction of the deep tunnel. Furthermore, the main pollutant load of the CSO is expected to be reduced by about 30%–40%.

Research of City Rainstorm Waterlogging Scene Simulation -- in Daoli District of Harbin City as an Example

As global warming urbanization process accelerated, urban waterlogging problem is increasingly serious, has become the research hotspot nowadays. City rainstorm waterlogging scene simulation is one of the important link in the research of the process in which residents shelter when city rainstorm waterlogging occurred. To develop urban rainstorm product scenario simulation study can guide us to determine the product elimination and influence range and location. This study using a one-dimensional and two-dimensional unsteady flow as the basic equation, with irregular grid as the basic frame, build urban rainstorm waterlogging deposition numerical simulation model, combining with the information diffusion theory calculation rainstorm probabilities in the study area, on this basis, set the study area rainstorm waterlogging situation, realized the different waterlogging scene simulation and visualization. The results show that the heavy rain that just sccumulate waterlogging disasters occurs once every five years in the study area, and depth of 0-0.47m,velocity between 0-0.43m/s.there is the biggest produce waterlogging which sccumulate with the heavy rain occurs once every 100 years, and the depth of 0-3m,velocity between 3-3.4m/s.

Evaluation of Resident Evacuations in Urban Rainstorm Waterlogging Disasters Based on Scenario Simulation: Daoli District (Harbin, China) as an Example

With the acceleration of urbanization, waterlogging has become an increasingly serious issue. Road waterlogging has a great influence on residents’ travel and traffic safety. Thus, evaluation of residents’ travel difficulties caused by rainstorm waterlogging disasters is of great significance for their travel safety and emergency shelter needs. This study investigated urban rainstorm waterlogging disasters, evaluating the impact of the evolution of such disasters’ evolution on residents’ evacuation, using Daoli District (Harbin, China) as the research demonstration area to perform empirical research using a combination of scenario simulations, questionnaires, GIS spatial technology analysis and a hydrodynamics method to establish an urban rainstorm waterlogging numerical simulation model. The results show that under the conditions of a 10-year frequency rainstorm, there are three street sections in the study area with a high difficulty index, five street sections with medium difficulty index and the index is low at other districts, while under the conditions of a 50-year frequency rainstorm, there are five street sections with a high difficulty index, nine street sections with a medium difficulty index and the other districts all have a low index. These research results can help set the foundation for further small-scale urban rainstorm waterlogging disaster scenario simulations and emergency shelter planning as well as forecasting and warning, and provide a brand-new thought and research method for research on residents’ safe travel.

Rainstorm waterlogging risk assessment in central urban area of Shanghai based on multiple scenario simulation

With the acceleration of the urbanization process, waterlogging problems in coastal cities are becoming more and more serious due to climate change. However, up until now, the common procedures and programs for rainstorm waterlogging risk assessment in coastal cities still have not formed. Considering a series of impact factors of rainstorm waterlogging in coastal city, the present study established a paradigm for rainstorm waterlogging risk assessment through the combination of hydrological modeling and GIS spatial analysis, and took the residence in central urban area of Shanghai as an example. First, the simplified urban waterlogging model was applied to simulate the depth and extent of rainstorm waterlogging under six hypothetic scenarios. Second, the residence exposed to rainstorm waterlogging was extracted and analyzed supported by spatial analysis module of ArcGIS. Then, stage-damage curves were applied to analyze the loss rate of structure and contents of residential building. Finally, the waterlogging loss maps of residence in different scenarios, the annual average loss, and the risk curve were taken as the expression of waterlogging risk. The results show that the inundated water depth, vulnerability, and losses of residence all increase as the intensity of rainstorm increases. The old-style residence is most vulnerable to rainstorm waterlogging, followed by the new-style residence, and villa is less vulnerable to rainstorm waterlogging. The annual average loss of residence in Shanghai central urban area was about CNY 22.25 million. The results also indicate high risk in Yangpu and Putuo districts, Xuhui, Hongkou, Changning and Zhabei districts come under medium-risk zone, and Jing’an, Luwan and Huangpu districts come under low-risk zone. These results provide important information for the local government, and the methodology can be applied in other cities to provide guidance on waterlogging risk governance.

Analysis and numerical study of a hybrid BGM-3DVAR data assimilation scheme using satellite radiance data for heavy rain forecasts

A fine heavy rain forecast plays an important role in the accurate flood forecast, the urban rainstorm waterlogging and the secondary hydrological disaster preventions. To improve the heavy rain forecast skills, a hybrid Breeding Growing Mode (BGM)- three-dimensional variational (3DVAR) Data Assimilation (DA) scheme is designed on running the Advanced Research WRF (ARW WRF) model using the Advanced Microwave Sounder Unit A (AMSU-A) satellite radiance data. Results show that: the BGM ensemble prediction method can provide an effective background field and a flow dependent background error covariance for the BGM- 3DVAR scheme. The BGM-3DVAR scheme adds some effective mesoscale information with similar scales as the heavy rain clusters to the initial field in the heavy rain area, which improves the heavy rain forecast significantly, while the 3DVAR scheme adds information with relatively larger scales than the heavy rain clusters to the initial field outside of the heavy rain area, which does not help the heavy rain forecast improvement. Sensitive experiments demonstrate that the flow dependent background error covariance and the ensemble mean background field are both the key factors for adding effective mesoscale information to the heavy rain area, and they are both essential for improving the heavy rain forecasts.