فهرست مطالب داوود خدادادی دهکردی

This study is focused on the treatment and reuse of agricultural drainage water using permeable reactive barriers (PRBs). To construct the physical model, a cubic iron tank with dimensions of 1×1×1 is used. Drainage pipes with a standard diameter of 16 mm are installed at a depth of 20 cm. To determine the depth of the static level, piezometer tubes are used in the model. After permeability tests and evaluating the obtained results as well as considering the availability of materials, the mixture weight ratios of the materials in PRB are selected as follows: 25% sand, 25% anthracite, 20% zeolite, 20% iron borings, and 10% poplar wood sawdust. The permeability coefficient of the PRB with this mixture after complete saturation over 24 hours is equal to 0.0322 cm/s. An initial nitrate concentration of 100 mg/liter is considered for the column to obtain the break through curve of the synthetic wastewater. It takes 15 minutes to detect the nitrate breakthrough. The breakthrough curve is considered a normal curve, and the only unknown of the problem, i.e., the longitudinal diffusion coefficient (D_L), is obtained by trial and error as 1.5×〖10〗^(-7) m^2⁄s, which is an acceptable value. The Peclet number for the proposed PRB is 14.344, which indicates the identical effects of the dispersion and diffusion processes. In this study, the drainage filter, which includes PRB and sandy loam soil, is able to eliminate nitrate by 99.44% after 24 days.

Stochastic models have been used as one technique to generate scenarios of future climate change. Temperature and precipitation are among the main indicators in climate study. The purposes of this study is analysis of the status of climatic parameters of monthly precipitation and mean monthly temperature, years of drought and years of wetness due to precipitation deficiency, simulation and forecasting using stochastic methods. In this study, the 21 year data on the precipitation and mean monthly temperature at shiraz synoptic station are used and based on ARIMA model, the autocorrelation and partial autocorrelation methods, evaluation of all possible models regarding their invariability, examination of parameters and types of model, the suitable models for prediction of monthly precipitation: ARIMA (0 0 0)(2 1 0) 12 and for forecasting of the mean monthlytemperature: ARIMA (2 1 0)(2 1 0) 12 were obtained. After validation and evaluation of the model, the forecasting for the agriculture years 2008-09 and 2009-10 were made. In view of the forecasting made, despite of a continuing drought, it is likely that the precipitation will improve. As regards the mean monthly temperature, the trend of increasing temperature, especially in recent years, has continued and the findings of the forecasting show an increase in temperature along with a narrowing of the range of variations.

Soil surface moisture and it's spatial and temporal variability is one of the most importantenvironmental variables. Due to the difficult, costly and time consuming measurements of field studies, this parameter has not been used widely in climate models. Nowadays, with the increasing development of science, adoption of new technologies for proper management of limited water and soil resources is necessary. The objective of this research was to analyze the application of MODIS images for estimating the soil surface moisture in arid and semiarid rangelands with ephemeral vegetation cover using TVX. Field data measurments of soil surface moisture and some daily meteorological parameters in three station of Mashhad, Golmakan and Neyshaboor of Khorasan province were used for more accurate estimate of soil surface moisture from 2003 to 2005. NDVI, Brightness Temperature of the bands (BT31, BT32) and Land Surface Temperature (LST) were derived from MODIS images and TVX slope was calculated. Different regression models were fitted to assess the relationship between TVX slope and soil surface moisture. According to the results, soil surface moisture in arid and semiarid climate showed a good correlation with TVX slope.