Baharak Motamedvaziri

Dear Editor, This paper has an interesting topic describing the role of climate change and wildfires and presents potential strategies for adaptation and mitigation. This paper is a review paper; while the review is well-written, I found that it ha...

Lake Urmia has experienced climate change over the last decades, dramatically reducing the water level. This study applies the Soil and Water Assessment Tool (SWAT) to evaluate runoff management strategies under different climate change scenarios in the Zarrineh River Basin. We examined two runoff management strategies: the projected runoff based on the business-as-usual (BAU) trend and the Changes in Cropping Pattern (CCP). The climate variables were downscaled and projected using Climate Change Toolkit (CCT) for the near future (2025–2049) and the far future (2075–2099) periods under two Representative Concentration Pathway (RCP) scenarios (2.6 and 8.5). The results revealed that runoff decreased by 6–23 and 9–52% for the near and far future, respectively, under the BAU scenario compared to the baseline period. Antithetically, it increased by 3.5–21 and 13–55% for the near and far future periods, respectively, based on the CCP strategy estimated up to 30% higher than the BAU strategy. The findings suggested that the CCP strategy can be considered a pragmatic management strategy since the surcharged runoff collected into Lake Urmia caused the mitigation of the imminent environmental disasters in the region and provided the environmental needs of its ecosystems.

Heuristic and statistical groundwater quality assessment models are efficient tools in the zoning of groundwater vulnerability to contamination. An important reciprocal methodology, yet neglected in Iran, was conducted to assess the performance of three groundwater vulnerability models, namely GODS, SI, and DRASTIC, and a data mining model for groundwater potential, maximum entropy (MaxEnt). For both the training and validation stages for the MaxEnt model, the Mahalanobis distance technique was adopted. The vulnerability rates obtained from the DRASTIC model with a coefficient of determination (R²) value of 0.76 had a statistically significant correlation with nitrate concentrations in the 21 wells, compared to SI and GODS. The DRASTIC model can better reflect the vulnerability of groundwater resources to contamination. The impact of the vadose zone with an average effective weight of 33 is more important than other parameters, followed by depth than groundwater (D) (32.01), net recharge (R) (28.95), and the aquifer media (A) (18.1). These weights may not be changed. MaxEnt showed significant performance in both the training and validation stages with the respective area under the receiver operating characteristic curve (AUROC) values of 0.907 and 0.901. A reciprocal analysis between the vulnerability map in the superior model and the groundwater potential map derived from MaxEnt revealed that areas with high groundwater potential are still in safe state but require more attention as the top priority for amendment practices. In addition, approximately 8.7% of the entire study area has a high vulnerability to contamination, which requires immediate pragmatic actions.