Reports demonstrate that floods are among the most prevalent and deadliest natural disasters affecting 520 million people annually. The present study seeks to evaluate flood forecasting using the weather research and forecasting (WRF) model and the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model. To this end, WRF and HEC-HMS were calibrated by comparing their results with the data observed at measuring stations. Then, the output rainfall data of the WRF model were implemented by the calibrated HEC-HMS model and were examined using the statistical indices, which were revealed to be 4.13, 3.42, and 2.67 for the flow volume and 6.2, 2.46, and 5.11 for the peak flow, suggesting the accurate performance of WRF model alongside HEC-HMS in the Talesh catchment.

Hydraulic conductivity (K) is one of the most important characteristics of soils in terms of groundwater movement and the formation of aquifers. Generally, it indicates the ease of infiltration and penetration of water in the soil. It depends on various factors, including fluid viscosity, pore size, grain size, porosity ratio, mineral grain roughness, and soil saturation level. Each of the empirical formulas used to calculate K includes one or more of the influencing parameters. In this study, pumping tests from an aquifer were performed by using a hydrology apparatus. Laboratory experiments were conducted on six types of soil with different grain sizes, ranging from fine sand to coarse sand, to obtain K. The experimental-based K values were compared with that of empirical formulas. The results demonstrate that Breyer and Hazen (modified) formulas adequately fit the laboratory values. The novelty of the present study is the comparison of the experimental formulas in completely similar conditions of the same sample, such as porosity, viscosity, and grain size, using the pumping test in a laboratory method, and the results show that the Hazen and the Breyer formulas provide the best results. The findings of this work will help in better development of groundwater resources and aquifer studies.

Groundwater depletion in arid regions requires reliable approaches for prioritising wells under competing hydrogeological, environmental, and economic constraints. This study develops a Technique for Order Preference by Similarity to Ideal Solution-based multi-criteria decision making framework to prioritise five existing observation wells for potential conversion into operational pumping wells in the water-stressed Yazd-Ardakan Plain, Iran. Nine criteria representing aquifer properties, groundwater conditions, well construction, spatial interactions, and economic factors were integrated, including hydraulic conductivity (K), groundwater level, aquifer sediment texture, and geological factors such as distance and density of neighbouring wells, drilling cost, and borehole screen quality, in addition to hydraulic gradient and bedrock slope to better represent regional hydrogeological and hydro-geomorphological conditions. Five candidate wells were evaluated using expert-derived weights and field-based data. The resulting ranking was Wells No. 5, 1, 2, 4, and 3, with Well No. 5 achieving the highest relative closeness coefficient (0.616). This result indicates the highest relative preference among the evaluated alternatives rather than independently validated pumping performance. By integrating hydrogeological, spatial, and economic criteria, the proposed model provides a transparent and practical decision-support tool for groundwater resource planning in arid regions, facilitating cost-effective and sustainable well placement.