Extreme rainfall erosivity: Research advances and future perspectives

The Science of The Total Environment, Год журнала: 2024, Номер 917, С. 170425 - 170425

Опубликована: Янв. 29, 2024

Язык: Английский

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Exploring future trends of precipitation and runoff in arid regions under different scenarios based on a bias-corrected CMIP6 model

Journal of Hydrology, Год журнала: 2024, Номер 630, С. 130666 - 130666

Опубликована: Янв. 24, 2024

Язык: Английский

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Rainfall erosivity across Austria's main agricultural areas: Identification of rainfall characteristics and spatiotemporal patterns

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 53, С. 101770 - 101770

Опубликована: Апрель 4, 2024

Target area of this study are the main agricultural production zones Austria. Most important croplands cover flat to pre-alpine areas concentrated in north, east, and southeast The novelty our is spatiotemporal assessment rainfall characteristics that drive erosivity at event level as well identification erosive distribution patterns within events. Our approach allows definition both typical extreme erosivity. Long-term high temporal resolution datasets were used apply a clustering approach, seasonal spatial analyses, distributions (isopleths) identified types (clusters). Three dominant event-types (clusters) strongly relate with Austria's seasonality complex topography. most events (cluster C1) characterized by intensity short duration. C1 have largest occurrence frequency southern Austria occur from May September. Unlike less more evenly distributed (C2 C3) highly pronounced maximum onset event.

Язык: Английский

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Evaluation of multiple time scale rainfall erosivity models: A case study of subtropical regions in Central China

Earth Surface Processes and Landforms, Год журнала: 2025, Номер 50(3)

Опубликована: Март 3, 2025

Abstract Rainfall erosivity is an essential factor affecting soil erosion, which expected to change under global climate change. Despite the existence of numerous rainfall models, there remains a scarcity research focusing on accuracy multi‐time scale models. In this study, subtropical regions central China (Hubei Province) were selected, where simulation performance six widely employed models was investigated using daily precipitation data from 70 meteorological stations spanning 2000 2020. Using optimal model, Kriging interpolation and Mann–Kendall test revealed significant temporal spatial variations in density. The results show that: (1) model more suitable for simulating Hubei Province. (2) mean annual Province 5894.25 MJ·mm·ha −1 ·h ·a , with large across regions. (3) density showed differences between different seasons, erosion most likely occur summer (June, July August). (4) distribution pattern highly consistent: long‐term high levels Xianning City, southeastern Province, risk high. findings study offer valuable insights into selection mountainous hilly areas provide reference assessing formulating control measures.

Язык: Английский

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Effect of tillage layer depth on erosion driven by surface-subsurface runoff coupling under rainfall simulation conditions

International Soil and Water Conservation Research, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

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Evaluating comprehensive watershed management sustainability based on the emergy ecological footprint model: A case study of Hainan Island, China

Ecological Modelling, Год журнала: 2025, Номер 505, С. 111120 - 111120

Опубликована: Апрель 8, 2025

Язык: Английский

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Impact of climate change on rainfall erosivity in the Amazon and Cerrado biomes under CMIP6 scenarios

Journal of Sedimentary Environments, Год журнала: 2025, Номер unknown

Опубликована: Май 14, 2025

Язык: Английский

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Evaluation of GPM IMERG-FR Product for Computing Rainfall Erosivity for Mainland China

Remote Sensing, Год журнала: 2024, Номер 16(7), С. 1186 - 1186

Опубликована: Март 28, 2024

Satellite precipitation products (SPPs) have emerged as an alternative to estimate rainfall erosivity. However, prior studies showed that SPPs tend underestimate erosivity but without reported bias-correction methods. This study evaluated the efficacy of two SPPs, namely, GPM_3IMERGHH (30-min and 0.1°) GPM_3IMERGDF (daily 0.1°), in estimating indices mainland China: average annual (R-factor) 10-year event (10-yr storm EI), by comparing with derived from gauge-observed hourly (Gauge-H). Results indicate yields higher accuracy than GPM_3IMERGHH, though both generally these indices. The Percent Bias (PBIAS) is −55.48% for R-factor −56.38% 10-yr EI using which reduces −10.86% −32.99% GPM_3IMERGDF. A method was developed based on systematic difference between SSPs Gauge-H. five-fold cross validation shows bias-correction, improve considerably, reduced. PBIAS decreases −0.06% 0.01%, −0.33% 0.14%, respectively, EI. estimated comparable obtained through Kriging interpolation Gauge-H better interpolated daily precipitation. Given their high temporal spatial resolution, timely updates, are viable data estimation bias correction.

Язык: Английский

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Monthly and annual rainfall erosivity in Poland: An empirical model including winter snowfall effect

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 56, С. 102076 - 102076

Опубликована: Ноя. 23, 2024

Язык: Английский

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Evaluating rainfall erosivity on the Tibetan Plateau by integrating high spatiotemporal resolution gridded precipitation and gauge data

The Science of The Total Environment, Год журнала: 2024, Номер 947, С. 174334 - 174334

Опубликована: Июнь 30, 2024

Язык: Английский

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