Future Land Use and Flood Risk Assessment in the Guanzhong Plain, China: Scenario Analysis and the Impact of Climate Change

Abstract

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.

Runoff and Sediment Deposition Characteristics of Gravel-Mulched Land: An Experimental Study

“…The flow of water on rough slopes, blocked by uneven gravel, consumes energy and slows down the flow rate. These combined effects cause a delay in runoff generation time and a reduction in runoff on gravelly soil slopes [65][66][67][68]. Increased soil surface gravel content increases soil porosity and considerably improves infiltration capacity, resulting in lower runoff [69].…”

Risk Assessment of Geological Landslide Hazards Using D-InSAR and Remote Sensing

“…Optical remote sensing data preprocessing mainly includes geometric correction, radiation correction, and mosaic, of which geometric correction uses the corrected 1:50,000 topographic map as a reference, and the RMS error falls within a pixel. Atmospheric radiation correction was completed in the FLASSH atmospheric correction module of the ENVI4.8 software to form the reflectivity image, and then the image was enhanced and cut [35][36][37][38]. Non-remote sensing information sources mainly include geological environment background data, topographic maps (1:50,000), geological maps, administrative division maps, and water system maps.…”

A Framework Based on LIDs and Storage Pumping Stations for Urban Waterlogging

“…Considering the limited land availability, many countries have proposed flood risk assessment methods [8] and urban waterlogging control measures [9], including America's Best Management Practices (BMP) [10], Low Impact Development (LID) [11], and Green Infrastructure (GI) [12]; Britain's Sustainable Urban Drainage Systems (SUDs) [13]; Australia's Water Sensitive Urban Design (WUDs) [14]; New Zealand's Low Impact Urban Design and Development (LIUDD) [15]; and China's Sponge City [16]. Most of the above measures are small-scale and dispersed green infrastructures at the source, demonstrating remarkable effectiveness in reducing rainwater and pollution load during light rainstorms but exhibiting limitations in heavy rainstorms.…”