A large body of research is devoted to understanding the spatial heterogeneity of natural conditions, human activities, and their interactions [1
]. However, such insights are seldom applied to disaster studies, such as those on floods, which are becoming one of the most severe disasters due to climate change and human activities [4
]. As one of the most frequently occurring natural disasters with severe impacts, flash floods (FFs) attract a lot of attention. Characterized by the rapid onset of flooding, FFs are a result of complex interactions between humans and the natural environment [5
]. This is particularly the case in China, where the frequency of FFs has increased in recent years owing to rapid economic growth, changes in the natural environment, and increases in extreme climate events [6
]. FFs were responsible for 62–92% of deaths attributed to flood disasters that occurred from 2010 to 2015 [7
]. There were 1500 deaths and 265 people missing as a result of the FF in Zhouqu, Gansu Province on 7 August 2010 [8
], which is one of the areas that often experiences FFs. Therefore, it is important to understand the driving forces behind the FFs [9
As FFs are nowadays reported in a timely manner and well documented, research on the influence of various temporal and spatial factors on flash floods has been carried out all over the world, such as in China, the United States, and other mountain areas. Significant progress has been made in analyzing influence factors, including the underlying surfaces, residential distribution, and precipitation [10
]. However, these analyses have mostly be carried out in particular regions [13
]. Gruntfest and Hamer [16
] pointed out that besides precipitation, human activity factors, such as river occupation, urbanization, and flood control measures have modified the natural characteristics of extreme floods. Tertl et al. [17
] explored the space–time characteristics of flood-related vulnerability to understand the human-related factors influencing FF events. Bloshcl et al. [18
] argued that the effects of land cover on FF events vary from humid climates to arid areas.
Although many studies have indicated that FFs are a comprehensive result of various factors, all of which include spatial attributes and typically differ in different regions [19
], there is little inquiry into quantitative comparison of the spatial heterogeneity of the influence of various factors in different regions [22
As hazard sources are dispersed in space [23
], it is difficult to determine why FFs often occur in particular areas. The investigation of spatial heterogeneity is of particular importance in advancing our knowledge of the spatial distribution and influential factors of FFs. FFs vary in space and time, making them difficult to forecast precisely [17
]. There is limited investigation of FFs and their spatial heterogeneity at the national scale to determine whether the driving factors differ in different regions. Further investigation will help improve FF prediction and the associated policy formulation and implementation. This paper aims to determine the spatial heterogeneity and associated factors causing FFs in China using historical records of FFs from 1950 to 2015.
Precipitation and landforms are the main factors that result in environments that are ecologically vulnerable to human activities. Accordingly, human activities significantly influence FFs; for example, the PD of the population density was as high as 0.501 and 0.384 in the NWAR and TP ecoregions, respectively (Figure 4
The spatial heterogeneity of the interactions is more significant than that of the factors (Figure 5
). The interaction of the six ecoregions in northwest China is bilinearly enhanced and that of the five ecoregions in southeast China is nonlinearly enhanced, meaning that the combined influence of multiple factors is substantially greater than that of a single factor. For instance, bilinear enhancement between precipitation and landforms was observed in NWAR, TP, Inner MP, and Northeast China regions, which seldom suffer from FFs, totaling approximately 10% of the occurrences.
The relationship between precipitation and landforms can be non-linearly enhanced in ecoregions mainly in the southern part of China (Figure 5
). Some other factors may be influential here because human activities are more diversified, such as urbanization, population growth, and industrial agglomeration, alongside complex natural conditions of sub-level landforms, climate change, and different terrains (Figure 4
). For instance, in South China, P(>250) and landforms are the primary factors, respectively, that can explain 40.1% and 12.6% of the FF occurrences. However, their interaction explains 64.1% of the FFs, which is greater than the effect of summation (52.6%).
In the traditional view, more precipitation will induce more serious FFs, whereas, by adding more factors such as natural conditions, economy and human effects in different ecoregions, the driving factors varied. It can be illustrated that other factors undoubtedly change the influence of precipitation on FFs in different ecoregions. Herewith, we consider that the result of our manuscript is innovative and useful in forewarning of FFs in special ecoregions.
As for the forces driving the heterogeneity of the spatial distribution of FFs, precipitation, especially heavy precipitation was the major driving force in eight ecoregions of China, and the power of determinants (PDs) were 0.176–0.756. Landform is another significant factor, which is the most influential factor in three ecoregions of Tibetan Plateau, North China and South China, and the PDs were 0.401–0.714. Furthermore, interactions of precipitation and landform have the strongest effect on the spatial distribution of FFs (e.g., 0.901 in Northwest Arid Region), although the degrees vary across ecoregions. The interactive influence of precipitation and landform was much greater than that of any single factor, with PDs of 0.478–0.901, which exceeded 0.8 in 8 of the 11 ecoregions. All these indicated that precipitation and landform were the major driving forces in China. However, human activities have a tangible relationship with flash floods, especially in ecologically vulnerable regions of Northwest Arid Region, Tibetan Plateau, and North China. Interestingly, the interaction between precipitation and landforms was found to be bilinearly enhanced in the six ecoregions of northwest China and nonlinearly enhanced in the five ecoregions in southeast China, implying that there are different interactions among the influential factors across ecoregions, which deserve further study. Based on the above, different strategies and proposals for preventing and controlling flash floods are also proposed.
FFs are one of main forms of disaster globally, dramatically affected by nature and human activities, and therefore the occurrence of FFs demonstrates spatial or regional heterogeneity. Availing of the data from the Investigation Project of Chinese Flash Floods, which is so far the largest and comprehensive dataset of FF records in China, this study explores the spatial variation of FF in China and assessed the driving force of various factors by using the Geodetector tool and considering 14 factors such as climate, natural environment, and human activities in 11 ecoregions in China. This contributes to understanding why FFs often occur in particular areas. The findings provide useful references for improving the prewarning system of FFs. Regional strategies are required to cope with the variation in these influential factors. Pre-warning systems in particular should pay attention to factors with high PD and the effects of their interaction.
The analysis may be limited owing to the choice of factors. It can be improved by including more variables to reflect and evaluate human activities. Nevertheless, they provide a new understanding of FFs from the perspective of spatial heterogeneity and will enable the development of regionally targeted strategies to cope with FFs. We hope the attempt at understanding the spatial heterogeneity of FFs and associated influential factors can improve our knowledge on how and why FFs occur in a particular ecoregion.