Flood level indicators of southwest provinces were built in this study by using daily precipitation data of 341 weather stations in southwest agricultural areas from 1961 to 2010 combined with grey correlation analysis. In the process of building the indicators, we took single station flood indicators of Chongqing as the prototype. Through increasing and decreasing the precipitation threshold of Chongqing indicators by the amplitude of -50-+50 mm and the step size of 1 mm, each province got 101 groups of flood indicators. Based on the correlation between flood intensity calculated by all the indicators and crop flood real seriousness, coincidence between indicators and historical flood records and the comparability of different province indicators, we finally constructed agricultural flood level indicators of each province step by step. According to the flood indicators, we also analyzed temporal-spatial distribution features of flood disaster in southwest agricultural areas. The results were as follows: the final indicators of Yunnan were the original indicators plus 16 mm, while it was plus 30 mm for Guizhou and plus 40 mm for Sichuan-Chongqing. The correlation coefficients between flood index defined by indicators and affected ratio were 0.314 (P < 0.05), 0.553 (P < 0.01) and 0.305 (P < 0.05), respectively. The coincidence was relatively high between indicators and historical flood records. The ages in which flood disaster appeared very serious were 1980s in Yunnan, 1990s in Guizhou and 1980s and 2000s in Sichuan-Chongqing in the nearly 50 years. In the southwest and southeast of Yunnan, southwest of Guizhou and west and northeast of Sichuan Basin, the flood disaster was prevalent.
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Health Econ
January 2025
Department of Economics, Federal University of Pelotas (UFPEL), Pelotas, Brazil.
The Northeast region of Brazil is characterized by long periods of drought. However, the region is also frequently affected by floods. The socioeconomic characteristics of the locality make the population more vulnerable to the impacts of these disasters.
View Article and Find Full Text PDFAm J Bot
January 2025
Pacific Biosciences Research Center, University of Hawai'i at Mānoa, Honolulu, HI, USA.
Premise: The ability of plants to adapt or acclimate to climate change is inherently linked to their interactions with symbiotic microbes, notably fungi. However, it is unclear whether fungal symbionts from different climates have different impacts on the outcome of plant-fungal interactions, especially under environmental stress.
Methods: We tested three provenances of fungal inoculum (originating from dry, moderate or wet environments) with one host plant genotype exposed to three soil moisture regimes (low, moderate and high).
BMC Public Health
January 2025
Department of Applied Social Sciences, Hong Kong Polytechnic University, Hong Kong, China.
Background: This study investigates the relationships between resilience dimensions, coping strategies, and prior disaster experience, focusing on disaster preparedness and avoidance behaviors in Taiwan.
Methods: A total of 550 participants were surveyed, with 57.82% being female and the majority aged between 21 and 40 years.
Sci Rep
January 2025
Business School, Sichuan University, 610059, Chengdu, China.
The comprehensive benefit evaluation of LID based on multi-criteria decision-making methods faces technical issues such as the uncertainties and vagueness in hybrid information sources, which can affect the overall evaluation results and ranking of alternatives. This study introduces a multi-indicator fuzzy comprehensive benefit evaluation approach for the selection of LID measures, aiming to provide a robust and holistic framework for evaluating their benefits at the community level. The proposed methodology integrates quantitative environmental and economic indicators with qualitative social benefit indicators, combining the use of the Storm Water Management Model (SWMM) and ArcGIS for scenario-based analysis, and the use of hesitant fuzzy language sets and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for decision-making.
View Article and Find Full Text PDFSci Total Environ
January 2025
Guangzhou Huadu district drainage management center, Guangzhou 510800, China.
Rapid urbanization has significantly altered surface landscape configurations, leading to complex urban climates. While much attention has been focused on impervious surfaces' impact on extreme precipitation, a critical gap remains in understanding how various 2D urban landscape components influence extreme precipitation across different durations. Through an analysis of the non-stationarity and spatiotemporal variations in extreme precipitation across the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 1990 to 2020, we constructed the non-stationary Generalized Additive Models for Location Scale and Shape (GAMLSS) model by introducing six urban landscape structural metrics as explanatory variables for each of the 27 meteorological stations in the GBA.
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