Evidence map›Paper›PMID 40989904›Full record

ArticlePeerJ2025

Driving factors of runoff and sediment yield effects of various slope ecological restoration measures in the middle reaches of the Yellow River.

Xin Wang, Zhenqi Yang, Jianying Guo, Fucang Qin, Xinyu Liu, Dong Fan

Abstract read
In one paragraph

Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xin WangInner Mongolia Agricultural University, Hohhot, China.
Zhenqi YangInner Mongolia Agricultural University, Hohhot, China.
Jianying GuoInner Mongolia Agricultural University, Hohhot, China.
Fucang QinInner Mongolia Agricultural University, Hohhot, China.
Xinyu LiuMinistry of Water Resources Pastoral Area Water Conservancy Science Research Institute, Hohhot, China.
Dong FanInner Mongolia Agricultural University, Hohhot, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The middle reaches of the Yellow River, with an exceeding amount of coarse sediment compared to the stream flow and the lower reaches, with severe sediment deposition, are key regions for sediment control in the Yellow River Basin. Recent years have witnessed efforts to return farmland land to forest and grassland and the launch of the Three-North Shelterbelt Forest Program, but the effectiveness of these measures remains to be studied. Research on factors influencing runoff depth (RD) and sediment yield (SY) sheds light on the mechanism of soil erosion in the study area. The present study focuses on the standard runoff fields in the Kuye River Basin, where ecological restoration measures (arbor forest land, shrub grassland, natural grassland, artificial grassland, cultivated land, Bare land) for various slope steepness (S) have been taken. Based on a six-year observation of the SY and RD in these fields, we aim to identify the primary factors influencing soil erosion, based on rainfall data and slope gradients. Using rainfall data and slope steepness factors, we explored the dominant factors that influence runoff and SY. The results showed that: (1) the rainfall events with short-duration, medium rainfall, and medium rainfall intensity were the most frequent; (2) the rainfall events with medium duration, heavy rainfall, and heavy rainfall intensity produced the most serious runoff and sediment; (3) using machine learning methods, the researchers found that the gradient boosting decision tree (GBDT) model was the most suitable for the study area, as it provided the best simulation of soil erosion. The structural equation model reveals that there is a significant correlation between runoff depth (RD) and soil erosion modulus (SEM). Time of precipitation (T), average precipitation intensity (I

Indexed as

Conservation of Natural ResourcesEnvironmental Restoration and RemediationGeologic SedimentsRiversSoil ErosionChinaEcosystemEnvironmental MonitoringRainWater MovementsControl measuresMiddle reaches of the Yellow RiverRainfallSoil erosion

Identifiers

PMID40989904
PMCPMC12452948

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.