scholarly journals Spatial-temporal changes of rainfall erosivity in the loess plateau, China: Changing patterns, causes and implications

CATENA ◽  
2018 ◽  
Vol 166 ◽  
pp. 279-289 ◽  
Author(s):  
Saiyan Liu ◽  
Shengzhi Huang ◽  
Yangyang Xie ◽  
Guoyong Leng ◽  
Qiang Huang ◽  
...  
Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2392
Author(s):  
Liang ◽  
Jiao ◽  
Dang ◽  
Cao

Obtaining practical thresholds for erosive rainfall plays a crucial role in calculating rainfall erosivity and predicting water erosion. Nevertheless, the study of thresholds on subwatershed and watershed scales remains scarce. Given this, we presented the critical rainfall that generated the outflows of subwatersheds and watersheds as the threshold of sediment-generating rainfall. On the basis of the observation of twelve nested topographical units at the Peijiamaogou watershed in the Loess Plateau of China, we fitted regression relationships between rainfall indexes (rainfall amount, maximum 30-min intensity, maximum 60-min intensity, rainfall amount multiply maximum 30-min intensity, and rainfall amount multiply maximum 60-min intensity) and the proportion of cumulative sediment yield to the total sediment yield. We determined the thresholds of sediment-generating rainfall and explored the variabilities of thresholds across different spatial scales. Moreover, the covering area proportion (CAP) with rainfall indexes higher than the thresholds was also employed as thresholds at the subwatershed and watershed scales. The thresholds of CAP for P and I30 were 50.5% and 47.6% at the subwatershed scale, while 31.0% and 30.3% at the watershed scale. The thresholds of P and I30 at the subwatershed scale were higher than those of hillslope scale, while the threshold of I30 at the watershed scale was smaller compared to the other scales. In general, I30 was viewed as the best threshold among single rainfall indexes across different spatial scales, while P was not recommended as a practical threshold. This study can improve the prediction accuracy of water erosion across different spatial scales and develop the spatial scale effect of sediment yield in the loess hilly areas.


CATENA ◽  
2022 ◽  
Vol 210 ◽  
pp. 105931
Author(s):  
Lu Jia ◽  
Kun-xia Yu ◽  
Zhan-bin Li ◽  
Peng Li ◽  
Jun-zheng Zhang ◽  
...  

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1217
Author(s):  
Chaoxing Sun ◽  
Guohe Huang ◽  
Yurui Fan

Extreme precipitation can seriously affect the ecological environment, agriculture, human safety, and property resilience. A full-scale and scientific assessment in extreme precipitation characteristics is necessary for water resources management and providing decision-making support to mitigate the potential losses brought by extreme precipitation. In the present study, a multidimensional risk assessment framework is developed to investigate the spatial–temporal changes in different extreme precipitation indicators. The Gaussian mixture model (GMM) is applied to fit the distribution for each indicator and carry out single index risk assessment. The joint probabilistic features of multiple extreme indicators can be explored through coupling the GMM distributions into copulas. In addition, the moving window approach and the Mann–Kendall test are integrated to examine non-stationary risks (evaluated by “AND”, “OR”, and Kendall return periods) of multidimensional indicators along with their changing trends and significance. The proposed assessment framework is applied to the Loess Plateau, China. Four extreme precipitation indicators are characterized: the amount (P95), the number of days (D95), the intensity (I95), and the proportion (R95) of extreme precipitation. The spatial–temporal changes of these indicators and their multidimensional combinations (including six two-dimensional and three three-dimensional combinations) are fully identified and quantitatively evaluated.


2020 ◽  
Vol 51 (5) ◽  
pp. 1048-1062
Author(s):  
Yongsheng Cui ◽  
Chengzhong Pan ◽  
Chunlei Liu ◽  
Mingjie Luo ◽  
Yahui Guo

Abstract Rainfall erosivity is an important factor to be considered when predicting soil erosion. Precipitation data for 1971–2010 from 39 stations located in the Loess Plateau of China were collected to calculate the spatiotemporal variability of rainfall erosivity, and the long-term tendency of the erosivity was predicted using data from the HadGEM2-ES model. Statistical analyses were done using Mann–Kendall statistic tests and ordinary Kriging interpolation. The results showed that the annual mean rainfall erosivity in the Loess Plateau decreased from 1,286.02 MJ mm hm−2 h−1 a−1 in 1971–1990 to 1,201.46 MJ mm hm−2 h−1 a−1 in 1991–2010 and mainly occurred in July to August. The rainfall erosivity decreased from the southeast to the northwest of the Loess Plateau and was closely related to the annual precipitation amount. However, the effect of annual precipitation on rainfall erosivity weakened under climate change: the annual precipitation increased and the rainfall erosivity decreased. Climate change, however, had little influence on the spatial variation in rainfall erosivity in the Loess Plateau. The results obtained can facilitate the prediction of spatial and temporal variations in soil erosion in the Loess Plateau.


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