Review of methods of spatio-temporal evaluation of rainfall erosivity and their correct application

被引:16
|
作者
Brychta, Jiri [1 ]
Podhrazska, Jana [1 ]
Stastna, Milada [1 ]
机构
[1] Mendel Univ Brno, Fac Agrisci, Dept Appl & Landscape Ecol, Zemedelska 1, Brno 61300, Czech Republic
关键词
Rainfall erosivity; R factor; C factor; USLE; RUSLE; Erosion rainfall; COVER-MANAGEMENT FACTOR; KINETIC-ENERGY RELATIONSHIPS; MONTHLY PRECIPITATION DATA; ANNUAL SEDIMENT YIELD; SOIL-EROSION; CLIMATE-CHANGE; SPATIAL-DISTRIBUTION; REGIONAL-SCALE; RAINDROP-SIZE; TIME-SERIES;
D O I
10.1016/j.catena.2022.106454
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Rainfall erosivity factor (R) is the key part of both the Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE). Its accuracy is related to the rainfall kinetic energy equation, the number of rain gauge stations, spatial distribution of rain gauge stations network, type of rain gauges, recording temporal resolution, the time step of rainfall intensity used, used time period, type of interpolation method, used covariates for determination of R values at unmeasured places, and way of regionalisation of R values or its determination for a given locality. These aspects are described, compared and discussed, including several common discrepancies and distortions. All approaches to R factor computation and estimation are presented with a focus on central Europe. The approaches were divided into two groups: the first low temporal resolution approach (yearly daily rainfall totals), and the second high temporal resolution approach (1-60 min rainfall totals). The relationship between the spatio-temporal distribution of R-and cover-management factor (C) values is described, including other methods of C-factor estimation. Several methods of R-and C-factor estimation and calculation were developed due to the lack of optimal data required by the original methodology or due to incorrect interpretation of given parameters or criteria. Also, inappropriate integration with the geographical information system (GIS) tools and Remote Sensing (RS) data may cause many simplifications and distortions of the original principles of the USLE/RUSLE. This review should help to choose the appropriate methodology of R-and C factor calculation in the field of water erosion risk assessment and help to reach a more appropriate allocation of financial expenses of erosion control measures.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Comment on "Review of methods of spatio-temporal evaluation of rainfall erosivity and their correct application" by Brychta et al. (2022), Catena 217, 106454
    Bezak, Nejc
    Chen, Walter
    CATENA, 2023, 223
  • [2] Spatio-temporal analysis of rainfall erosivity and erosivity density in Greece
    Panagos, Panos
    Ballabio, Cristiano
    Borrelli, Pasquale
    Meusburger, Katrin
    CATENA, 2016, 137 : 161 - 172
  • [3] Rainfall erosivity in Italy: a national scale spatio-temporal assessment
    Borrelli, Pasquale
    Diodato, Nazzareno
    Panagos, Panos
    INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2016, 9 (09) : 835 - 850
  • [4] Spatio-temporal dynamics of rainfall erosivity due to climate change in Cameron Highlands, Malaysia
    Nuraddeen Mukhtar Nasidi
    Aimrun Wayayok
    Ahmad Fikri Abdullah
    Muhamad Saufi Mohd Kassim
    Modeling Earth Systems and Environment, 2021, 7 : 1847 - 1861
  • [5] Spatio-temporal dynamics of rainfall erosivity due to climate change in Cameron Highlands, Malaysia
    Nasidi, Nuraddeen Mukhtar
    Wayayok, Aimrun
    Abdullah, Ahmad Fikri
    Kassim, Muhamad Saufi Mohd
    MODELING EARTH SYSTEMS AND ENVIRONMENT, 2021, 7 (03) : 1847 - 1861
  • [6] Methods to analyze spatio-temporal rainfall variability: application to the Pajeú river basin, Pernambuco
    de Assis, Janaina Oliveira Maria
    Menezes, Athos Farias
    de Souza, Weronica Meira
    Sobral, Maria do Carmo Martins
    REVISTA BRASILEIRA DE CIENCIAS AMBIENTAIS, 2021, 56 (04): : 577 - 588
  • [7] Crop-management Factor Calculation Using Weights of Spatio-temporal Distribution of Rainfall Erosivity
    Brychta, Jiri
    Janecek, Miloslav
    Walmsley, Alena
    SOIL AND WATER RESEARCH, 2018, 13 (03) : 150 - 160
  • [8] Review of Spatio-temporal Data Modeling Methods
    Li X.
    Liu Y.
    Data Analysis and Knowledge Discovery, 2019, 3 (03) : 1 - 13
  • [9] Evaluation of spatio-temporal rainfall variability and performance of a stochastic rainfall model in Bangladesh
    Chowdhury, A. F. M. Kamal
    Kar, Kanak Kanti
    Shahid, Shamsuddin
    Chowdhury, Rezaul
    Rashid, Md. Mamunur
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2019, 39 (11) : 4256 - 4273
  • [10] Spatio-temporal variation in rainfall erosivity during 1960-2012 in the Pearl River Basin, China
    Lai, Chengguang
    Chen, Xiaohong
    Wang, Zhaoli
    Wu, Xushu
    Zhao, Shiwei
    Wu, Xiaoqing
    Bai, Wenkui
    CATENA, 2016, 137 : 382 - 391