Spatio-temporal Pattern and Trend Prediction of Soil Erosion in Kuye River Basin

[Objective] Kuye River Basin is the main source of erosion in the coarse sand area in the middle reaches of the Yellow River. The study is aimed at elucidating the spatio-temporal pattern of soil erosion, predicting the development trend of soil erosion in Kuye River Basin and providing decision support for the comprehensive control of soil erosion in the future. [Methods] Based on the multi-source data from 2010 to 2020, the spatial distribution of soil erosion in the Kuye River Basin was studied, and the characteristics of soil erosion intensity change were analyzed by using quantitative indicators such as dynamic degree of soil erosion intensity, information entropy of soil erosion intensity, comprehensive index of soil erosion intensity and transfer matrix. The CA-Markov model was established to predict the soil erosion in 2025. [Results] (1) The soil erosion intensity in the study area was mainly in micro and mild erosion, accounting for more than 70% of the total area, and stronger erosion was mainly distributed in the middle and lower reaches of the basin and tributary Beiniuchuan. From 2010 to 2020, the average soil erosion decreased from 1 955.56 t/(km2·a) to 892.98 t/(km2·a), the area of micro erosion increased significantly, and the area of other erosion intensity decreased correspondingly. The soil erosion intensity remained unchanged or decreased in most regions, and only less than 3% of the regions experienced increased erosion intensity. (2) The dynamic degree of intensity, extreme intensity and extreme erosion in Kuye River Basin changed greatly, the information entropy of soil erosion intensity decreased steadily from 1.29 to 0.81, the comprehensive index of soil erosion intensity decreased from 178.96 to 76.61 and the decline rate was higher in the first five years, and the change of soil erosion intensity in the basin to the weakening direction mainly occurred between the two adjacent erosion intensity levels. (3) CA-Markov model simulation shows that, it is expected that by 2025, the soil erosion situation in the basin will be further improved, with the proportion of micro erosion accounted more than 75%. [Conclusion] From 2010 to 2020, the soil erosion situation in the study area continued to improve, and the control efficiency of soil erosion in the next five years was higher, and the soil erosion situation in the basin would be further improved in 2025.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
DOI
https://doi.org/10.13870/j.cnki.stbcxb.2024.05.028
Citations
1
Primary Topic
Soil erosion and sediment transport
Type
article
Field-Weighted Citation Impact
0.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatio-temporal Pattern and Trend Prediction of Soil Erosion in Kuye River Basin

1 citations
SHILAP Revista de lepidopterología
Soil erosion and sediment transport
0.33
article

Spatio-temporal Pattern and Trend Prediction of Soil Erosion in Kuye River Basin

article en
1 citations

Abstract

[Objective] Kuye River Basin is the main source of erosion in the coarse sand area in the middle reaches of the Yellow River. The study is aimed at elucidating the spatio-temporal pattern of soil erosion, predicting the development trend of soil erosion in Kuye River Basin and providing decision support for the comprehensive control of soil erosion in the future. [Methods] Based on the multi-source data from 2010 to 2020, the spatial distribution of soil erosion in the Kuye River Basin was studied, and the characteristics of soil erosion intensity change were analyzed by using quantitative indicators such as dynamic degree of soil erosion intensity, information entropy of soil erosion intensity, comprehensive index of soil erosion intensity and transfer matrix. The CA-Markov model was established to predict the soil erosion in 2025. [Results] (1) The soil erosion intensity in the study area was mainly in micro and mild erosion, accounting for more than 70% of the total area, and stronger erosion was mainly distributed in the middle and lower reaches of the basin and tributary Beiniuchuan. From 2010 to 2020, the average soil erosion decreased from 1 955.56 t/(km2·a) to 892.98 t/(km2·a), the area of micro erosion increased significantly, and the area of other erosion intensity decreased correspondingly. The soil erosion intensity remained unchanged or decreased in most regions, and only less than 3% of the regions experienced increased erosion intensity. (2) The dynamic degree of intensity, extreme intensity and extreme erosion in Kuye River Basin changed greatly, the information entropy of soil erosion intensity decreased steadily from 1.29 to 0.81, the comprehensive index of soil erosion intensity decreased from 178.96 to 76.61 and the decline rate was higher in the first five years, and the change of soil erosion intensity in the basin to the weakening direction mainly occurred between the two adjacent erosion intensity levels. (3) CA-Markov model simulation shows that, it is expected that by 2025, the soil erosion situation in the basin will be further improved, with the proportion of micro erosion accounted more than 75%. [Conclusion] From 2010 to 2020, the soil erosion situation in the study area continued to improve, and the control efficiency of soil erosion in the next five years was higher, and the soil erosion situation in the basin would be further improved in 2025.

SHILAP Revista de lepidopterología
Institute of Soil and Water Conservation (CN), Nanjing Hydraulic Research Institute (CN), Northwest A&F University (CN)
Life in Land
Openalex Percentile: Top 31%
Soil erosion and sediment transport
0.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.