Analyses of water dependency of Haloxylon ammodendron in arid regions of Iran using stable isotope technique.

The complex relationships within desert ecosystems and their environmental conditions are reflected in patterns of plant water use. Thus, understanding the sources of water used by plants in these areas is crucial for effective resource management. In this study, we investigated the water use pattern of Haloxylon ammodendron in Semnan province, in the central plateau of Iran, using the stable isotope analysis.

Assessing data mining algorithms to predict the quality of groundwater resources for determining irrigation hazard.

This study aims to compare three popular machine learning (ML) algorithms including random forest (RF), boosting regression tree (BRT), and multinomial logistic regression (MnLR) for spatial prediction of groundwater quality classes and mapping it for salinity hazard. Three hundred eighty-six groundwater samples were collected from an agriculturally intensive area in Fars Province, Iran, and nine hydro-chemical parameters were defined and interpreted. Variance inflation factor and Pearson's correlations were used to check collinearity between variables.