Spatial-temporal changes in rainfall erosivity in Turkey using CMIP5 global climate change scenario

Kiliç, Orhan; Günal, Hikmet

doi:10.1007/s12517-021-07184-2

Cited by 14 publications

(4 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hydrological factors included the rainfall erosivity ( R ), the topographic wetness index (TWI), the stream power index (SPI), and the stream transport index (STI). R was used to reflect the potential erosivity of the rainfall (Kili & Gunal, 2021; Shi et al, 2021). TWI considers the effect of topography on the hydrological processes (Rahmati, Kalantari, et al, 2019), and SPI reflects stream power (Khosravi et al, 2018).…”

Section: Methodsmentioning

confidence: 99%

“…where SAN, SIL and CLA are the content of sand fraction, silt fraction, clay fraction, respectively (%); C is the soil organic carbon content (%); SN1 equal to 1 À SAN=100 Noori et al (2019); Pourghasemi, Yousefi, et al (2020) erosivity of the rainfall (Kili & Gunal, 2021;Shi et al, 2021). TWI considers the effect of topography on the hydrological processes (Rahmati, Kalantari, et al, 2019), and SPI reflects stream power (Khosravi et al, 2018).…”

Section: Determination Of Influencing Factorsmentioning

confidence: 99%

See 1 more Smart Citation

Recognition of suitable small watersheds for check dam construction on the Loess Plateau

Chen,

Bai,

Jiao

et al. 2023

Land Degrad Dev

View full text Add to dashboard Cite

Check dams are used for soil and water conservation worldwide, especially on the Chinese Loess Plateau, which has suffered from severe soil and water loss. To promote ecological conservation and high‐quality development in the Yellow River basin, considerable effort should be devoted to building check dams in the small watersheds where the conditions permit on the Loess Plateau. Therefore, suitable small watersheds must be identified for constructing new check dams. In this study, the weighted overlay method (WOM) of the multi‐criteria decision‐making analysis method, the random forest (RF), and the support vector machine (SVM) of machine learning methods were first applied to simulate the suitability of small watersheds for check dam construction in the Ganguyi upstream area of the Yanhe River basin on the Loess Plateau. Accuracy assessment showed that the accuracy of the three models was almost perfect and RF had the highest accuracy of 0.95, followed by SVM (0.87), and WOM (0.83). Meanwhile, the impacts of topographic factors and soil erodibility were found to be generally higher than those of the other factors, and 56% of small watersheds had high and very high suitability for check dam construction, 67% of these small watersheds have already been built as check dams. Finally, a total of 108 small watersheds were found to be suitable in the study area when considering their environmental characteristics. The methodology developed in the study can be used as a preliminary planning step for check dam construction and as a foundation for detailed field investigations in the future, which help to realize the sustainable use of soil and water resources.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Determination Of Influencing Factorsmentioning

confidence: 99%

Recognition of suitable small watersheds for check dam construction on the Loess Plateau

Chen,

Bai,

Jiao

et al. 2023

Land Degrad Dev

View full text Add to dashboard Cite

show abstract

“…Changes in precipitation patterns caused by climate change will significantly affect future rainfall erosivity. Several existing studies have predicted future changes in rainfall erosivity in the United States [11], Turkey [15], Europe [16], Australia [17], China [18], and India [19]. Most of these studies believe that future rainfall erosivity will increase significantly at the regional scale.…”

Section: Introductionmentioning

confidence: 99%

Rainfall Erosivity Characteristics during 1961–2100 in the Loess Plateau, China

Li,

Xiao,

Hao

et al. 2024

Remote Sensing

View full text Add to dashboard Cite

Rainfall erosivity, which signifies the inherent susceptibility of soil erosion induced by precipitation, plays a fundamental role in formulating a comprehensive soil loss equation (RUSLE). It stands as a crucial determinant among the foundational factors considered in a comprehensive soil loss equation’s establishment. Nonetheless, the prediction and quantification of future alterations in rainfall erosivity under the influence of global warming have been relatively limited. In this study, climate change was widely evaluated and 10 preferred global climate models in the Loess Plateau were selected by using the data sets of 27 models simulating climate change and the CN05.1 data set provided by the latest CMIP6. The monthly precipitation forecast data were obtained by using the delta downscaling method. Combined with trend analysis, significance test, and coefficient of variation, the annual rainfall erosivity during 1961–2100 under four SSP scenarios was analyzed and predicted. Among the 27 GCM models used in this paper, the most suitable climate models for simulating monthly precipitation in the Loess Plateau were CMCC-CM2-SR5, CMCC-ESM2, TaiESM1, EC-Earth3, EC-Earth-Veg-LR, INM-CM4-8, CAS-ESM2-0, EC-Earth-Veg, ACCESS-ESM1-5, and IPSL-CM6A-LR. In comparison to the base period (1961–1990), during the historical period (1961–2014), the average annual rainfall erosivity on the Loess Plateau amounted to 1259.64 MJ·mm·hm−2·h−1·a−1, showing an insignificant downward trend. In the northwest of Ningxia, Yulin City and Yanan City showed a significant upward trend. In the future period (2015–2100), the annual rainfall erosivity continues to constantly change and increase. The potential average increase in rainfall erosivity is about 13.48–25.86%. In terms of spatial distribution, most areas showed an increasing trend. Among these regions, the majority of encompassed areas within Shanxi Province, central Shaanxi, and Inner Mongolia increased greatly, which was not conducive to soil and water conservation and ecological environment construction. This study offers a scientific reference for the projected future erosivity characteristics of the Loess Plateau.

show abstract

“…Temporal variations in rainfall erosivity are important for understanding changes in soil erosion and assessing the future climate change impact on the land degradation. At present, research on the temporal change of rainfall erosivity mainly focuses on past changes (Cao et al, 2018;Qin et al2016;Wang 50 et al, 2022;Yang, 2015;Zhang et al, 2010) and future projections (Kilic et al 2021;Panagos et al, 2022).…”

mentioning

confidence: 99%

The most extreme rainfall erosivity ever recorded in China: The "7.20" rainstorm in Henan Province

Xiao

Yin

et al. 2022

Preprint

View full text Add to dashboard Cite

Abstract. Severe water erosion occurs during extreme storm events. Such an extreme storm occurred in Zhengzhou in central China on 20 July 2021 (the “7.20” rainstorm). The magnitude and frequency of occurrence of this storm event were examined in terms of its erosivity values. To contextualize this extreme event, hourly rainfall data from 2420 automatic meteorological stations in China from 1951 to 2021 were analyzed to: (1) characterize the spatial and temporal distribution of rainfall and rainfall erosivity of the “7.20” rainstorm, (2) evaluate the average recurrence interval of the maximum daily and event rainfall erosivity, and (3) establish the geographical distribution of the maximum daily and event rainfall erosivity in China. The center of the “7.20” rainstorm moved from southeast to northwest in Henan province, and the most intense period of rainfall occurred in the middle and late stages of the storm. Zhengzhou meteorological station happened to be aligned with the center of the storm, with a maximum daily rainfall of 552.5 mm and a maximum hourly rainfall intensity of 201.9 mm"∙" h-1. The average recurrence interval of the maximum daily rainfall erosivity (43,354 MJ·mm·ha-1· h-1) and the maximum event rainfall erosivity (58 874 MJ·mm·ha-1·h-1) was estimated to be 109 079 and 154 154 years, respectively, assuming the generalized extreme value distribution, and these were the maximum rainfall erosivity ever recorded among 2420 meteorological stations in mainland China. The “7.20” rainstorm suggests that the most erosive of storms does not necessarily occur in the wettest places in southern China, and it can occur in mid-latitude around 35 °N with a moderate mean annual precipitation of 549.2 mm in Zhengzhou meteorological station.

show abstract

Spatial-temporal changes in rainfall erosivity in Turkey using CMIP5 global climate change scenario

Cited by 14 publications

References 37 publications

Recognition of suitable small watersheds for check dam construction on the Loess Plateau

Recognition of suitable small watersheds for check dam construction on the Loess Plateau

Rainfall Erosivity Characteristics during 1961–2100 in the Loess Plateau, China

The most extreme rainfall erosivity ever recorded in China: The "7.20" rainstorm in Henan Province

Contact Info

Product

Resources

About