Search

Continuously global warming and landscape change have aggravated the damage of flood disasters to ecological safety and sustainable development. If the risk of flood disasters under climate and land-use changes can be predicted and evaluated, it will be conducive to flood control, disaster reduction, and global sustainable development. This study uses bias correction and spatial downscaling (BCSD), patch-generating land-use simulation (PLUS) coupled with multi-objective optimization (MOP), and entropy weighting to construct a 1 km resolution flood risk assessment framework for the Guanzhong Plain under multiple future scenarios. The results of this study show that BCSD can process the 6th Climate Model Intercomparison Project (CMIP6) data well, with a correlation coefficient of up to 0.98, and that the Kappa coefficient is 0.85. Under the SSP126 scenario, the change in land use from cultivated land to forest land, urban land, and water bodies remained unchanged. In 2030, the proportion of high-risk and medium-risk flood disasters in Guanzhong Plain will be 41.5% and 43.5% respectively. From 2030 to 2040, the largest changes in risk areas were in medium- and high-risk areas. The medium-risk area decreased by 1256.448 km2 (6.4%), and the high-risk area increased by 1197.552 km2 (6.1%). The increase mainly came from the transition from the medium-risk area to the high-risk area. The most significant change in the risk area from 2040 to 2050 is the higher-risk area, which increased by 337 km2 (5.7%), while the medium- and high-risk areas decreased by 726.384 km2 (3.7%) and 667.488 km2 (3.4%), respectively. Under the SSP245 scenario, land use changes from other land use to urban land use; the spatial distribution of the overall flood risk and the overall flood risk of the SSP126 and SSP245 scenarios are similar. The central and western regions of the Guanzhong Plain are prone to future floods, and the high-wind areas are mainly distributed along the Weihe River. In general, the flood risk in the Guanzhong Plain increases, and the research results have guiding significance for flood control in Guanzhong and global plain areas. [ABSTRACT FROM AUTHOR]

Droughts have emerged as a global problem in contemporary societies. China suffers from different degrees of drought almost every year, with increasing drought severity each year. Droughts in China are seasonal and can severely impact crops. This study used spatiotemporal trend and characteristics analysis of drought disaster data from 1991 to 2018 in Chinese provinces, in addition to the Mann–Kendall test and wavelet analysis. The drought disaster data included the crop damage area, drought-affected area of the crops, and crop failure area. The outputs of the crops decreased by 10%, 30%, and 80%, respectively. The population with reduced drinking water caused by drought, and the domestic animals with reduced drinking water caused by drought, were numbered in the tens of thousands. The results of the study show that the crop damage areas owing to drought disasters, drought-affected areas of crops, and crop failure areas in China were mainly distributed in the northern, eastern, northeaster, and southwestern regions. The number of people and domestic animals with reduced drinking water owing to drought in China were mainly concentrated in the northern and southwestern regions. These indicators showed a general increasing trend. Tibet, Fujian, Shandong, Jiangsu, Anhui, and Henan provinces and autonomous regions also showed a slightly increasing trend. In particular, the number of domestic animals with reduced drinking water caused by drought in the Inner Mongolia Autonomous Region showed a clear increasing trend with a significant Z-value of 2.2629. The results of this research can be used to provide scientific evidence for predicting future trends in drought and for practising the best management of drought prevention and resistance. [ABSTRACT FROM AUTHOR]

Climate change and urbanization are causing increasingly frequent urban flooding in countries around the world. Various innovative approaches have emerged to address this challenge. In China, the Sponge City was first proposed in 2012 to achieve an urban hydrological balance through natural storage, natural infiltration and natural purification. This article presents a comparative investigation (using a survey method) of new and old communities in Xixian New District and Xi'an in September 2021 to investigate public awareness of the Sponge City and understand levels of satisfaction and acceptance. Individuals of the same age or education residing in the Sponge City generally know more about the Sponge City and were more willing to accept it than those in traditional cities. Moreover, the residents of Sponge City understand the Sponge City concept well, with a majority of the respondents (71.82%) expressing clear understanding on the conception of Sponge City. However, residents in a traditional city exhibited much less understanding of the concept (44.24%). Furthermore, for those living in the same area, people who are younger or have higher education exhibited a clearer understanding of and acceptance of the Sponge City and local government. In this survey, the average scores (assign values to the different responses, then average and percent it) of respondents in Xixian New District with master's degrees, bachelor's degrees and high school degrees or below were evaluated at 76.88, 67.94 and 62.15, respectively, compared to 62.07, 50.18 and 50.78 in Xi'an. Lastly, we found that differences in living environment have a significant influence on residents' perceptions. Residents living in the Sponge City are generally satisfied with the travel and living conditions and greatly support the local government. Meanwhile, this study will help relevant authorities pay more attention to residents' opinions and help them to formulate policies to spread the concept of Sponge City and encourage residents' participation. [ABSTRACT FROM AUTHOR]

As an essential part of the hydrological cycle, precipitation is usually associated with floods and droughts and is increasingly being paid attention to in the context of global warming. Analyzing the change trends and correlation of temperature and extreme precipitation indicators can effectively identify natural disasters. This study aimed to detect the correlation and change trends of temperature and extreme precipitation indicators in Inner Mongolia from 1960 to 2019. Panel vector autoregression (PVAR) models based on Stata software were used to detect the correlation between temperature and extreme precipitation indicators at 35 climatological stations throughout Inner Mongolia. The temperature and extreme precipitation indicator trends were analyzed using the Mann–Kendall test and Sen's slope method. The spatial distribution characteristics of the annual precipitation and rainfall intensity were more significant in the southeast and more minor in the northwest, while an increase in the annual wet days was noticeable to the northeast. The Granger cause tests of the temperature and the extreme precipitation indicators showed a correlation between each indicator and temperature at the significance level of 1%. The temperature positively correlated with only the rainfall intensity while negatively correlating with the remaining indicators. There is no doubt that trend analysis showed significant increasing trends in rainfall intensity at all stations, which means increased risk in extreme precipitation events. By contrast, the annual precipitation and annual wet days showed significant decreasing trends, which means that the precipitation is concentrated, and it is easier to form extreme precipitation events. The study can provide a basis for decision-making in water resources and drought/flood risk management in Inner Mongolia, China. [ABSTRACT FROM AUTHOR]

Multivariate statistical methods including cluster analysis (CA), discriminant analysis (DA) and component analysis/factor analysis (PCA/FA), were applied to explore the surface water quality datasets including 14 parameters at 28 sites of the Eastern Poyang Lake Basin, Jiangxi Province of China, from January 2012 to April 2015, characterize spatiotemporal variation in pollution and identify potential pollution sources. The 28 sampling stations were divided into two periods (wet season and dry season) and two regions (low pollution and high pollution), respectively, using hierarchical CA method. Four parameters (temperature, pH, ammonia-nitrogen (NH4-N), and total nitrogen (TN)) were identified using DA to distinguish temporal groups with close to 97.86% correct assignations. Again using DA, five parameters (pH, chemical oxygen demand (COD), TN, Fluoride (F), and Sulphide (S)) led to 93.75% correct assignations for distinguishing spatial groups. Five potential pollution sources including nutrients pollution, oxygen consuming organic pollution, fluorine chemical pollution, heavy metals pollution and natural pollution, were identified using PCA/FA techniques for both the low pollution region and the high pollution region. Heavy metals (Cuprum (Cu), chromium (Cr) and Zinc (Zn)), fluoride and sulfide are of particular concern in the study region because of many open-pit copper mines such as Dexing Copper Mine. Results obtained from this study offer a reasonable classification scheme for low-cost monitoring networks. The results also inform understanding of spatio-temporal variation in water quality as these topics relate to water resources management. [ABSTRACT FROM AUTHOR]