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The objective of this study was to assess the drought risk management in the region under study. The SPI method was adopted for drought monitoring in Hamadan Province, Iran. The temporal and spatial extent of the area vulnerable to drought was delineated using AEZ model, GIS and other softwares. Five zones were recognized based on the drought severity index. Selection of compatible crops with respect to climate and land production capability of a region specially in drought condition is one of the effective elements to increase the water productivity in agriculture, based on Agro-ecological Zoning(AEZ) model, developed by FAO, suitable spatial extension of wheat cultivation, which is the main crop in Hamadan Province, were delineated. According to this study the most suitable lands potentially available for wheat production are located in the north-east region and a part of the central region, where as, least suitable ones can be observed in the north-east and the south - east regions. The results of the risk analysis study show that south-east, north and central regions are susceptible to longest duration intense droughts where as long duration droughts are intensive in north, west and south-east regions. The overlaid and integrated maps of risks with the maps obtained after applying the AEZ model resulted into the map of spatial suitability of potential crop production for each class of risk (longest duration and most intensive durations). This enables the decision makers to define spatial priority of crop cultivation and manage various potential regions susceptible to drought risks. [ABSTRACT FROM AUTHOR]

Water productivity is a suitable indicator in water potential analysis at a location in a region. In this study, changes in water use productivity are studied in spatial and temporal scale simultaneously. To evaluate temporal changes in water productivity in Hamadan region (Iran), Standard Precipitation Index (SPI) was analyzed and evaluated for drought, wet and normal conditions. To estimate regional water productivity, GIS and Kassam methods were coupled to estimate the Potential yield of rain-fed wheat in a developed rasterized grid network with 30 x 30 -km resolution. Results of this study indicate that the amount of water productivity in drought condition in comparison with the other two conditions was higher and from geographical point of view the southern parts of the region have higher potential production with compare to other locations of the province. The analysis shows the variation in amount of active radiation received by the earth surface is causing these differences. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is a significant parameter for many applications. Many studies have proposed various algorithms, such as the split-window method, for retrieving surface temperatures from two spectrally adjacent thermal infrared bands of satellite data. Each algorithm is developed for a limited study area and application. In this paper, as part of developing an optimal split-window method in the southeast of Tehran province, Iran, four commonly applied algorithms to retrieve the LST from AVHRR were compared. This study was carried out in a wheat farm site located in the Pakdasht Agricultural Region. Measurements of LST over the farm were made with a manual infrared radiometer at the time of NOAA overpass for 18 days of May to June 2004. These days were cloud free over the study area. A total of 18 NOAA images were acquired for the days that LST measurements were made. The temperatures derived by the different split-window algorithms were compared to ground truth measurements. The performance of the split window algorithms was checked with three statistical indices: root mean square error (RMSE), mean bias error (MBE) and coefficient of determination (R2). The results showed that the Ulivieri split-window algorithm produced the lowest value of RMSE and MBE (2.71 and 0.26 K, respectively) and its highest value of R2 (0.92) gave more accurate results than the other algorithms. [ABSTRACT FROM AUTHOR]