Flooding and its relationship with land cover change, population growth, and road density

Bangladesh experiences frequent hydro-climatic disasters such as flooding.These disasters are believed to be associated with land use changes and climate variability.However,identifying the factors that lead to flooding is challenging.This study mapped flood susceptibility in the northeast region of Bangladesh using Bayesian regularization back propagation(BRBP)neural network,classification and regression trees(CART),a statistical model(STM)using the evidence belief function(EBF),and their ensemble models(EMs)for three time periods(2000,2014,and 2017).The accuracy of machine learning algorithms(MLAs),STM,and EMs were assessed by considering the area under the curve—receiver operating characteristic(AUC-ROC).Evaluation of the accuracy levels of the aforementioned algorithms revealed that EM4(BRBP-CART-EBF)outperformed(AUC>90%)standalone and other ensemble models for the three time periods analyzed.Furthermore,this study investigated the relationships among land cover change(LCC),population growth(PG),road density(RD),and relative change of flooding(RCF)areas for the period between 2000 and 2017.The results showed that areas with very high susceptibility to flooding increased by 19.72%between 2000 and 2017,while the PG rate increased by 51.68%over the same period.The Pearson correlation coefficient for RCF and RD was calculated to be 0.496.These findings highlight the significant association between floods and causative factors.The study findings could be valuable to policymakers and resource managers as they can lead to improvements in flood management and reduction in flood damage and risks.

1998’s floods in the Changjiang River and the land use/land cover change in the upper and middle-lower reaches in the past 50 years

Flood of Changjiang River (the Yangtze) in 1998 is so serious that it arouses our keen concern about its causes. In this paper, the authors bring out a brief history of the flood disaster happened to the Changjiang River Valley in the last six centuries and analyze the causes for the frequent flood disaters based on the land use and land cover change in the upper and middle-lower reaches of the Changjiang River.

Flood basalt hosted palaeosols:Potential palaeoclimatic indicators of global climate change

Since continental sediments （in addition to the marine geological record） offer important means of deciphering environmental changes, the sediments hosted by the successive flows of the continental flood basalt provinces of the world should be treasure houses in gathering the palaeoclimatic data. Palaeosols developed on top of basalt flows are potentially ideal for palaeoenvironmental reconstructions because it is easy to determine their protolith geochemistry and also they define a definite time interval. The present paper summarizes the nature of the basalt-hosted palaeosols formed on the flood basalts provinces from different parts of the ~lobe havin~ different ages.

Application and comparison of coaxial correlation diagram and hydrological model for reconstructing flood series under human disturbance

Intense human activities have greatly changed the flood generation conditions in most areas of the world, and have destroyed the consistency in the annual flood peak and volume series. For design flood estimation, coaxial correlation diagram and conceptual hydrological model are two frequently used tools to adjust and reconstruct the flood series under human disturbance. This study took a typical mountain catchment of the Haihe River Basin as an example to investigate the effects of human activities on flood regime and to compare and assess the two adjustment methods. The main purpose is to construct a conceptual hydrological model which can incorporate the effects of human activities. The results show that the coaxial correlation diagram is simple and widely-used, but can only adjust the time series of total flood volumes. Therefore, it is only applicable under certain conditions(e.g. There is a strong link between the flood peaks and volumes and the link is not significantly affected by human activities). The conceptual model is a powerful tool to adjust the time series of both flood peak flows and flood volumes over different durations provided that it is closely related to the catchment hydrological characteristics, specifically accounting for the effects of human activities, and incorporating expert knowledge when estimating or calibrating parameters. It is suggested that the two methods should be used together to cross check each other.

Using modified Soil Conservation Service curve number method to simulate the role of forest in flood control in the upper reach of the Tingjiang River in China

To improve flood control efficiency and increase urban resilience to flooding,the impacts of forest type change on flood control in the upper reach of the Tingjiang River(URTR) were evaluated by a modified model based on the Soil Conservation Service curve number(SCS-CN) method. Parameters of the model were selected and determined according to the comprehensive analysis of model evaluation indexes. The first simulation of forest reconstruction scenario,namely a coniferous forest covering 59.35km^2 is replaced by a broad-leaved forest showed no significant impact on the flood reduction in the URTR. The second simulation was added with 61.75km^2 bamboo forest replaced by broad-leaved forest,the reduction of flood peak discharge and flood volume could be improved significantly. Specifically,flood peak discharge of 10-year return period event was reduced to 7-year event,and the reduction rate of small flood was 21%-28%. Moreover,the flood volume was reduced by 9%-14% and 18%-35% for moderate floods and small floods,respectively. The resultssuggest that the bamboo forest reconstruction is an effective control solution for small to moderate flood in the URTR,the effect of forest conversion on flood volume is increasingly reduced as the rainfall amount increases to more extreme magnitude. Using a hydrological model with scenarios analysis is an effective simulation approach in investigating the relationship between forest type change and flood control. This method would provide reliable support for flood control and disaster mitigation in mountainous cities.