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Meta-Analysis and Visualization of the Literature on Early Identification of Flash Floods. REMOTE SENSING 2022. [DOI: 10.3390/rs14143313] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Flash flood is one of the extremely destructive natural disasters in the world. In recent years, extreme rainfall events caused by global climate change have increased, and flash flood disasters are becoming the main types of natural disasters in the world. Due to the characteristics of strong suddenness, complex disaster-causing factors, great difficulty in prediction and forecast, and the lack of historical data, it is difficult to effectively prevent and control flash flood disaster. The early identification technology of flash floods is not only the basis of flash flood disaster prediction and early warning, but also an effective means of flash flood prevention and control. The paper makes a meta-analysis and visual analysis of 475 documents collected by the Web of Science Document Platform in the past 31 years by comprehensively using Citespace, Vosviewer, Origin, etc. We systematically summarize the research progress and development trend of early identification technology of flash flood disasters from five key research subfields: (1) precipitation, (2) sediment, (3) sensitivity analysis, (4) risk assessment, (5) uncertainty analysis. In addition, we analyze and discuss the main problems encountered in the current research of several subfields and put forward some suggestions to provide references for the prevention and control of flash flood disasters.
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A GIS-Based Hydrological Modeling Approach for Rapid Urban Flood Hazard Assessment. WATER 2021. [DOI: 10.3390/w13111483] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Urban floods are detrimental to societies, and flood mapping techniques provide essential support for decision-making on the better management of flood risks. This study presents a GIS-based flood characterization methodology for the rapid and efficient identification of urban flood-prone areas, which is especially relevant for large-scale flood hazards and emergency assessments for data-scarce studies. The results suggested that optimal flood mapping was achieved by adopting the median values of the thresholds for local depression extraction, the topographic wetness index (TWI) and aggregation analyses. This study showed the constraints of the depression extraction and TWI methods and proposed a methodology to improve the performance. A new performance indicator was further introduced to improve the evaluation ability of hazard mapping. It was shown that the developed methodology has a much lower demand on the data and computation efforts in comparison to the traditional two-dimensional models and, meanwhile, provides relatively accurate and robust assessments of flood hazards.
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Risk Analysis Related to Impact of Climate Change on Water Resources and Hydropower Production in the Lusatian Neisse River Basin. SUSTAINABILITY 2020. [DOI: 10.3390/su12125060] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Water resources are one of the most important issues affected by climate change. Climate scenarios show that in the upcoming decades, further climate change can occur. It concerns especially air temperature and sunshine duration, whose prognosis indicates a significant rising trend till the end of the century. The goal of the paper was the evaluation of water resources and hydropower production in the future, depending on climate scenarios with a consideration of risk analysis. The analysis was carried out on the basis of observation data for the Lusatian Neisse river basin (Poland) for 1971–2015 and climate projections till 2100 for the RCP2.6 and RCP8.5 (representative concentration pathways) scenarios. The results of the research showed that, especially in terms of RCP8.5, very high risk of decrease in water resources and hydropower production is expected in the future. Therefore, recommendations for mitigation of the possible effects are presented.
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