High-Resolution Digital Mapping of Soil Erodibility in China DOI

Longhui Sun,

Feng Liu,

Xuchao Zhu

и другие.

Опубликована: Янв. 1, 2023

Soil erodibility (K) refers to the resistance of soil erosion and is an important factor in forecasting erosion. The accuracy K determines predictions loss effective deployment measures for conserving water. China has no high-resolution map distribution at national scale due uncertainty obtaining limitation complex diverse topographic conditions. We used most recent soil-sampling data (4710 profile points), calculated point-scale using erosion-productivity impact calculator (EPIC), random-forest method predict across by combining soil-landscape relationships environmental variables determined theory formation. mean predicted was 0.035 t ha h ha-1 MJ-1 mm-1, with a range from 0.015 0.061. small Northwest sandstorm region Qinghai-Tibet Plateau (means 0.032 0.031, respectively) large Loess 0.040 0.042, respectively), which were different natural geographic conditions soil-forming environments each region. highly accurate, 10-fold cross-validation model 0.49, root square error (RMSE) 0.0077, absolute (MAE) 0.0059. represented feature details spatial continuity better than traditional polygon-linking had higher spatial-modeling did ordinary-kriging (R2random forest = 0.49 > R2ordinary kriging 0.42). Elevation, solar radiation, wind speed, surface reflectance primary affecting K, increase (%IncMSE) 32.98, 30.69, 30.03, 28.33%, respectively, indicating influence factors on evolution formation current physicochemical properties. This study provides first national-scale China, can provide basis predicting regional planning conservation

Язык: Английский

Biocrusts protect the Great Wall of China from erosion DOI Creative Commons
Yousong Cao, Matthew A. Bowker, Manuel Delgado‐Baquerizo

и другие.

Science Advances, Год журнала: 2023, Номер 9(49)

Опубликована: Дек. 8, 2023

The Great Wall of China, one the most emblematic and historical structures built by humankind throughout all history, is suffering from rain wind erosion largely colonized biocrusts. However, how biocrusts influence conservation longevity this structure virtually unknown. Here, we conducted an extensive biocrust survey across found that cover 67% studied sections. Biocrusts enhance mechanical stability reduce erodibility Wall. Compared with bare rammed earth, biocrust-covered sections exhibited reduced porosity, water-holding capacity, erodibility, salinity 2 to 48%, while increasing compressive strength, penetration resistance, shear aggregate 37 321%. We further protective function mainly depended on features, climatic conditions, types. Our work highlights fundamental importance as a nature-based intervention Wall, protecting monumental heritage erosion.

Язык: Английский

Процитировано

25
An advanced global soil erodibility (K) assessment including the effects of saturated hydraulic conductivity DOI Creative Commons
Surya Gupta, Pasquale Borrelli, Panos Panagos

и другие.

The Science of The Total Environment, Год журнала: 2023, Номер 908, С. 168249 - 168249

Опубликована: Окт. 31, 2023

USLE-type models are widely used to estimate average annual soil loss at large scales, with the erodibility factor (K) being sole component that accounts for soil's susceptibility erosion. The includes information on permeability in equation, however, most definitions of K consider hydrological influence only very crudely and indirectly. Thus, direct impact surface runoff infiltration drainage erosion is largely neglected. objective this study incorporate hydraulic properties map by merging available global-scale measured saturated conductivity (Ksat) data texture organic carbon into a modified factor. To achieve this, Wischmeier Smith (1978) texture- permeability-based equation (KWischmeier factor) was include Ksat, called Kksat Using Random Forest machine learning algorithm, KWischmeier were each correlated remote sensing covariates spatial extrapolation two independent maps 1 km resolution. We noted clear decrease mean value (0.023 t ha h ha-1 MJ-1 mm-1) compared (0.027 mm-1). reduction values pronounced tropical regions reflecting difference (e.g., clay iron), whereas other climate showed relatively minor changes comparison as well recent global modeling Borrelli et al. (2017) (KGloSEM maps). As many studies discussed an overall overestimation (R)USLE based rates measurements, might improve modeled right direction. marks important initial step integrating can prove their significance future studies.

Язык: Английский

Процитировано

24
Global soil erodibility factor (K) mapping and algorithm applicability analysis DOI
Miaomiao Yang, Qinke Yang, Keli Zhang

и другие.

CATENA, Год журнала: 2024, Номер 239, С. 107943 - 107943

Опубликована: Март 12, 2024

Язык: Английский

Процитировано

9
High-resolution digital mapping of soil erodibility in China DOI Creative Commons

Longhui Sun,

Feng Liu, Xuchao Zhu

и другие.

Geoderma, Год журнала: 2024, Номер 444, С. 116853 - 116853

Опубликована: Март 12, 2024

Soil erodibility (K) is the intrinsic susceptibility of a soil to water erosion. Currently, its detailed and accurate spatial distribution information especially over large areas urgently required for national regional erosion assessment conservation decision making. This study combined pedotransfer function with digital mapping techniques develop high-resolution map across China. The First, based on recent survey, we adopted erosion-productivity impact calculator (EPIC) calculate values at 4710 sampling points. Then, caclulated points, used five including polygon linking (PL), ordinary kriging (OK), Cubist, extreme gradient boosting (XGBoost), random forests (RF) generate erodibility. three latter machine learning modeled quantitative relationships between set environmental covariates. results showed that methods exhibited much more details than PL OK did. Among RF achieved highest accuracy R2 0.49 RMSE 0.0077 t ha h ha−1 MJ−1 mm−1 10-fold cross-validation. Spatial uncertainty analysis predictions high uncerntainty occurred in northwestern China low center southeast. We found topographical climatic variables are major factors indirectly controlling variation while particle composition SOC contents directly influence variation.

Язык: Английский

Процитировано

9
Geospatial modeling and mapping of soil erosion in India DOI
Ravi Raj, Manabendra Saharia, Sumedha Chakma

и другие.

CATENA, Год журнала: 2024, Номер 240, С. 107996 - 107996

Опубликована: Март 25, 2024

Язык: Английский

Процитировано

4
Assessing the declining trend in soil erodibility across China: A comparison of conventional and digital K-factor maps DOI Creative Commons
Zhiyuan Tian, Yan Zhao, Longxi Cao

и другие.

International Soil and Water Conservation Research, Год журнала: 2024, Номер 13(1), С. 15 - 26

Опубликована: Май 29, 2024

Soil erodibility is a measure of soil susceptibility to water erosion and serves as an essential element, also known the K-factor, in empirical prediction models, such USLE, RUSLE, CSLE. The currently available map K-factor for China was generated based on conventional polygon linkage method species survey 1980s. For update, investigation 4,262 samples from series 2010s random forest regression model were used generate new China. A digital at 250 m spatial resolution by calculating K values points training data using environmental information predictive variables. comparison results between maps show that there has been decreasing trend recent decades. value decrease mainly due update (the mean changed 0.03193 t·ha·h/(MJ·mm·ha) database 0.02988 series) less influenced replacement mapping methods 0.03197 forest). This study quantified sources change previous updated national demonstrated values, which consistent with increasing organic matter improved ecological environment

Язык: Английский

Процитировано

4
Climate Crisis Impact on Ecosystem Services and Human Well-Being DOI
Aju David Raj,

R. Padmapriya,

Anu David Raj

и другие.

Climate change management, Год журнала: 2024, Номер unknown, С. 3 - 36

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

3
Vascular plants and biocrusts ameliorate soil properties serving to increase the stability of the Great Wall of China DOI
Yanping Liu,

Jing Ren,

Wanfu Wang

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 951, С. 175506 - 175506

Опубликована: Авг. 15, 2024

Язык: Английский

Процитировано

3
Optimal Mapping of Soil Erodibility in a Plateau Lake Watershed: Empirical Models Empowered by Machine Learning DOI Creative Commons
Jiaxue Wang, Yujiao Wei, Zheng Sun

и другие.

Remote Sensing, Год журнала: 2024, Номер 16(16), С. 3017 - 3017

Опубликована: Авг. 17, 2024

Soil erodibility (K) refers to the inherent ability of soil withstand erosion. Accurate estimation and spatial prediction K values are vital for assessing erosion managing land resources. However, as most K-value models empirical, they suffer from significant extrapolation uncertainty, traditional studies on focusing individual empirical have neglected explore pattern differences between various models. This work proposed a universal framework selecting an optimal soil-erodibility map using enhanced by machine learning. Specifically, three models, namely, erosion-productivity impact calculator model (K_EPIC), Shirazi (K_Shirazi), Torri (K_Torri) were used estimate values. Random Forest (RF) Gradient-Boosting Decision Tree (GBDT) algorithms employed develop which led creation maps. The distribution associated environmental covariates also investigated across varying Results showed that RF achieved highest accuracy, with R2 K_EPIC, K_Shirazi, K_Torri increasing 46%, 34%, 22%, respectively, compared GBDT. And distinctions among variables shape patterns been identified. K_EPIC K_Shirazi influenced porosity moisture. is more sensitive moisture conditions terrain location. More importantly, our study has highlighted disparities in Considering data distribution, measured values, outperformed others estimating plateau lake watershed. aimed create maps offered scientific accurate method assessment

Язык: Английский

Процитировано

3
Impact of Slope Cutoff Factor on Soil Erosion Estimates: A Hilltop Mine‐Based Comparative Geospatial Study DOI Open Access

Thappitla Srinivas Rohit,

Vasanta Govind Kumar Villuri

Land Degradation and Development, Год журнала: 2025, Номер unknown

Опубликована: Янв. 20, 2025

ABSTRACT The task of soil erosion estimation received a significant push by integrating remote sensing and geographical information systems (GIS) with the Revised Universal Soil Loss Equation (RUSLE) in early 1990s due to its ease applicability. Topographic (LS) factor played quintessential role loss determination, especially for undulating regions. In most worldwide studies, topographic extracted from Digital Elevation Model (DEM) using “LS equations” failed account varying slopes before material joins stream or river. this study, slope length (L) steepness (S) derived without cutoff are compared analyzed hilltop mine. results reflect that LS and, ultimately, over‐estimated owing absence any limits on terrains when used conventionally GIS environment. mean estimated is 252.26 ton ha −1 year , whereas 332.81 conventional application same equation. overestimation was reduced 35% as per volume‐based validation study. Thus, study proves usefulness factor, which, date, has mostly been neglected research studies terrains. pattern also highlights negating impact vegetation steep slopes, cementing their Nature based Solution (NbS) dynamic landscapes like Mines.

Язык: Английский

Процитировано

0