مقالات رزومه زهرا شاهی

The wind, as one of the most effective factors on evaporation from the surface of water sources, such as reservoirs of dams, plays a significant role in estimating the volume of losses due to evaporation and thus protecting water resources. However, in most evaporation estimation methods, such as experimental relationships, evaporation pans, and even new methods such as the use of satellite images, wind is considered as a constant parameter. The wind parameter has a spatial distribution under the influence of the elevations overlooking the lake and water levels. On the other hand, simulating the spatial changes of the wind and investigating its effect on evaporation, as one of the factors affecting the water cycle, is time-consuming and difficult due to the complexity of the calculations. Failure to apply wind location changes will reduce the accuracy of the calculated evaporation and as a result, it will be difficult to access the exact amount of evaporation losses.

In this study, to calculate the effect of spatial changes of wind on evaporation losses from the Dez Dam reservoir located in Khuzestan province and the southwest of Iran, the combination of the CE-QUAL-W2 model and Bowen Ratio Energy Budget (BREB) method was used. The wind shelter coefficient (WSC) as one of the input parameters to the CE-QUAL-W2 model, makes it possible for the model to consider the wind shelter condition in different segments of water bodies differently. However, due to the lack of access to a suitable criterion to show the wind shelter condition in different segments, before this research, the value of WSC was considered constant in all or large parts of the water body. In this study, CE-QUAL-W2 model capability was used for reservoir segmentation, and wind shelter condition was determined in each segment, using the wind shelter index (Sx). Therefore, it was possible to assign different WSC values in each segment. In this way, the thermal profiles in each of these segments, under the influence of two conditions of constant and variable wind (constant and variable WSC), were extracted and entered into the BREB method to calculate evaporation.

The results showed that the application of spatial wind changes compared to constant wind conditions, improved the performance of the CE-QUAL-W2 model by 45% in the temperature calibration stage. Also, the monthly evaporation from the lake increased by 13%.

This study, introduced a standardized method for simulating the effect of spatial wind changes on evaporation from water surfaces. So that, it was possible to quantify the effect of wind on evaporation and as a result water losses from the lake, by comparing two conditions of variable and constant wind, in different segments of the studied lake.

In dry farming, reduction of soil water losses is one of the most important factors of success. In this study, to investigate the effect of different levels of gravel and soil texture on evaporation and soil water content of bare soil, an experiment was conducted in a completely randomized design with 12 treatments and 3 replications. Soil textures were sandy loam, loam and silty clay contain 0, 10, 20 and 30% volumetric gravel. Results showed that soil texture and gravel resulted in significant effect on the amount of content soil water. Maximum and minimum soil water loss was occurred in silty clay soil with 20% volumetric gravel (99.4%) and loam soil with 10% volumetric gravel (88.1%), respectively. The effect of interaction between texture and gravel content was only significant in cumulative evaporation from soil surface. As the amount of gravel increased, the amount of soil decreased. Therefore, soil water content and evaporation decreased. Therefore. collecting gravels from the field and using them as mulch, or cultivating in areas with low gravels level can be resulted in soil water saving in dry farming.

To calculate the wind shelter index (Sx) for points in a region, the wind shelter index values are calculated for each set of points in different lengths and directions. Among these lengths, the length of the Sx corresponding to it has the highest wind shelter and is known as an effective length. Winstral et al. (2002), Winstral and Marks (2002), Erickson et al. (2005), Molotch et al. (2005), Molotch and Bales (2006), Sharifi et al. (2007), Litaor et al. (2008), Tabari et al. (2009) and Maroufi el al. (2010) in order to determine the effective length in snowy areas inevitably used the correlation of Sx values for each desired length and depth of snow. Winstral et al. (2009) in study of wind speed distribution methods determined the effective length by establishing the relationship between the difference in the values of the Sx and the difference in the velocity of the wind. Farokhzadeh et al. (2014) also succeeded in determining the effective length by examining the correlation between a parameter named average wind shelter slope and Sx, provided that the selected points were in wind conditions. Therefore, due to the limitation in the method proposed by Farokhzadeh et al. (2014) for calculating the Sx in non-snow areas such as lake levels, the use of a specific type of algorithm for determining the effective wind shelter length seems necessary (Shahi, 2017). Therefore, in this study, according to the existing conditions, a method was proposed for selecting the effective length of the shelter.