JWSS - Journal of Water and Soil Science

Concerning the drying problem of the Lake Urmia in Iran, so far the relevant scientific research has not been conducted based on watershed management principles. The surface solar radiation (Rs) is one of the key input parameters in most of reference evapotranspiration (ET0) prediction models. In the present research, four solar radiation models were evaluated to predict the monthly-mean values of daily ET0 at seven synoptic stations located in the Lake Urmia basin during the 1985-2005 period. For the ET0 prediction, we applied the Penman-Monteith-FAO 56 model (PMF56). At first, we evaluated four radiation models consisting of Hybrid: H, Ångström-Prescott: AP, Modified Daneshyar: MD, and Modified Sabbagh: MS. Four statistical criteria used included the mean error (ME), the mean absolute error (MAE), the root mean square error (RMSE), and the mean percentage error (MPE). The mean RMSE value of hybrid model was 1.7 MJ/m2/day while the RMSEs for the AP, the MD and the MS models were 2.9, 2.3, and 2.9 MJ /m2/day, respectively. The results revealed a higher performance of hybrid model to predict the monthly radiation. In addition, the Rs models used in the original PMF56 model were compared with a case in which the measured daily Rs data was used. Finally, by integrating the hybrid model and the PMF56, we developed a coupled model as PMF56-Hybrid. The application of the Hybrid and the MD models resulted in a decrease in the RMSEs. The AP model used in the PMF56 showed about 19% overestimation.

The aim of this study is to prepare the groundwater spring potential map using Weight of Evidence, logistic regression, and frequency ratio methods and comparing their efficiency in Chehlgazi watershed, province of Kurdistan. At first, 17 effective factors in springs occurrence including geology, distance to fault, fault density, elevation, relative permeability of lithological units, slope steepness, slope aspect, plan curvature, profile curvature, precipitation, distance to Stream, drainage Stream density, Sediment Transport Capacity Index (STCI), Stream Power Index, topographic wetness index (TWI) and land use/land cover (LU/LC) were selected. The validation processes of methods were conducted by relative performance characteristic curve (ROC). The area under an ROC curve (AUC) for the weight of evidence, logistic regression and frequency ratio was 85/8%, 79% and 89%, respectively. The results showed that all methods are suitable estimator for mapping the groundwater spring potential in the study area. But the frequency ratio method with the most amounts is the best method to produce and map the groundwater spring potential. Also, validation of the mappings based on the percentage of pilot springs, training springs and all springs showed that the logistic regression, WoE and frequency ratio, with 45, 56 and 45 percent of spring occurrence on the high potential classes respectively, had the highest validation.