Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms.

The Chinese project, better known as the Grain for Green Project (GGP), has changed the land-use type in the karst area of Puding county, Guizhou province, southwest China, and this study is aimed at evaluating the Hg distribution and determining factors in soils after the land-use change. A total of ten soil profiles were selected in the typical karst region, and the land-use types were divided into native vegetation land (NVL), farmland (FL), and abandoned farmland (AFL).

In recent years modern societies have attached a multifunctional requirement to the use of renewable resources, making their optimal sustainable management more complex. In the last decades, in many cases, this complexity is addressed by formulating management models with the help of the concepts and methods belonging to the well-known multicriteria decision-making (MCDM) paradigm. The purpose of this paper was to undertake a hermeneutic meta-analysis of the literature provided in primary journals on issues related to the management of these resources with the help of the MCDM paradigm.