فهرست مطالب maryam safavi gerdini

Potential evapotranspiration (PET) is an important parameter of the hydrologic cycle whose estimation is essential for irrigation and water facility schemes as well as drainage and hydrologic studies. The parameter represents potential losses from moist surface soil and vegetation cover. The present study uses different evapotraspiration estimation methods and compares the results obtained from each against those obtained from the FAO-Penman-Monteith method used as the reference in the environment of the Ref-ET software to determine the accuracy of each and to select the best method for estimating PET in Khorrambid Township, Fars Province. All the methods are evaluated in terms of their efficiency using the statistical parameters of Normalized Root Mean Square Error (NRMSE), Efficiency of Model (EF), Agreement Index (d), and Mean Bias Error (MBE). The results are found to rank the investigated methods in the following order: ASCE stPM, ASCE PM, ASCE PMrs, KPen (1972), FAO 24Pn, FP 17 Pen, KPen (1996), Pen (1948), Harg (1985), FAO 24Rd, FAO 24BC, Prs –Tylr, Makk (1957), Turc (1961), and FAO Pan in terms of the lowest MBE and NRMSE but the highest EF and d values recorded. Although the Penman-based equations are found capable of yielding more accurate estimates of evapotranspiration rates by using temperature, relative humidity, wind speed, and sunny hours, in the absence of such data, however, it is the Hargreaves-Samani empirical method that can be effectively used to estimate evapotranspiration in Khorrambid Township with a lower error level than other empirical methods.

In recent years, overuse of ground waters has led to a significant decrease in water levels and has also reduced groundwater quality. Therefore, qualitative analysis of ground water reservoirs is deemed necessary to manage exploitation of these resources and determine the most optimal and economic cropping patterns. Geostatistical methods are the most widely used and appropriate tools for monitoring qualitative variables. In this regard, the spatial variations of qualitative variables such as Na+, TH, EC, SAR, Cl-, SO42-, Mg2+, PH, TDS and K+driven from 70 wells on aquifers of Ghorveh and Dehgolan Plain located in Kurdistan province were studied. The statistical period of the data used in this study covers the years 1984-2012. After analyzing the variogram by GS+ software, data interpolation was performed using three methods of ordinary kriging, simple kriging, and inverse distance weighing with the powers of 1, 2 and 3, respectively. The results shows that the omni-directional semivariogram for all variables is nearly identical. The results also indicate that using ordinary kriging and simple kriging methodscause fewer errors in estimating most qualitative variables. The values of mean error (ME) statistics in the kriging method are close to zero, indicating the least bias in estimations. Also, water quality was classified in terms of Schuler and Will Cox terms methods, so that the results reveal that most of the wells are within an optimal range, yet a few are in medium and bad ranges. Zoning results demonstrated that groundwater quality in the western, southern, and southeastern zones is better than those of other sectors. Thus, it is necessary for management to reduce consumption and change cropping patterns to improve water quality in areas with poor water quality.