Modelling soil thickness using environmental attributes in karst watersheds-Reference-Cited by-同舟云学术

Modelling soil thickness using environmental attributes in karst watersheds

Published:2022-05 Issue: Volume:212 Page:106053
ISSN:0341-8162
Container-title:CATENA
language:en
Short-container-title:CATENA

Author:

Zhang Yaohua,Xu Xianli,Li Zhenwei,Yi Ruzhou,Xu Chaohao,Luo Wei

Funder

Chinese Academy of Sciences

Youth Innovation Promotion Association of the Chinese Academy of Sciences

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Earth-Surface Processes

Reference63 articles.

1. Akaike, H., 1973. Information theory and an extension of the maximum likelihood principle. 2nd International Symposium on Information Theory 73, 1033-1055.

2. Digital soil mapping using artificial neural networks;Behrens;J. Plant Nutr. Soil Sci.,2010

3. A physically based, variable contributing area model of basin hydrology / Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant;Beven;Int. Assoc. Sci. Hydrol. Bull.,1979

4. Mapping soil depth classes in dry Mediterranean areas using terrain attributes derived from a digital elevation model;Boer;Geoderma,1996

5. Random forests;Breiman;Mach. Learn.,2001

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Prediction and mapping of soil thickness in alpine canyon regions based on whale optimization algorithm optimized random forest: A case study of Baihetan Reservoir area in China;Computers & Geosciences;2024-09

2. Quantitatively Distinguishing the Factors Driving Runoff and Sediment Yield Variations in Karst Watersheds;Water Resources Research;2024-08

3. Overestimating the involvement of nitric acid derived from nitrification in carbonate dissolution under a calcareous soil system;Environmental Technology & Innovation;2024-08

4. A comparative study of empirical and machine learning approaches for soil thickness mapping in the Joshimath region (India);CATENA;2024-06

5. Quantifying the water use efficiency of karst ecosystems and response to environmental factors;Journal of Hydrology: Regional Studies;2024-06