The main aim of this study was the quantitative assessment of desertification process in the case study area of the Fidoye-Garmosht plain (Southern Iran). Based on the MEDALUS approach and the characteristics of study area a regional model developed using GIS. Six main factors or indicators of desertification including: soil, climate, erosion, plant cover, groundwater and management were considered for evaluation. Then several sub-indicators affecting the quality of each main indicator were identified. Based on the MEDALUS approach, each sub-indicator was quantified according to its quality and given a weighting of between 1.0 and 2.0. ArcGIS 9 was used to analyze and prepare the layers of quality maps using the geometric mean to integrate the individual sub-indicator maps. In turn the geometric mean of all six quality maps was used to generate a single desertification status map. Results showed that 12% of the area is classified as very severe, 81% as severe and 7% as moderately affected by desertification. In addition the plant cover and groundwater indicators were the most important factors affecting desertification process in the study area. The model developed may be used to assess desertification process and distinguish the areas sensitive to desertification in the study region and in regions with the similar characteristics.

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Evapotranspiration (ET) is a key component of the hydrological cycle however it is also the most difficult factor to quantify. In recent decades, estimating ET has been improved by advances in remote sensing, particularly in agricultural studies. However, quantifying ET from mixed vegetation environs, particularly urban parklands, is still challenging due to the heterogeneity of plant species, canopy covers, microclimates, and because of costly methodological requirements. Several studies have recently been conducted in agriculture and forestry which may be useful for mixed landscape vegetation studies with some modifications. This review describes general remote sensing-based approaches to estimate ET and describes their advantages and disadvantages. Most of these approaches need extensive time investment, medium to high skill levels and are quite expensive. However, in addition to the reviewed methods, the authors recommend combining remotely sensed vegetation indices and ground-based techniques for ET estimation of mixed landscape vegetation such as urban parklands.

This study was carried out to evaluate the influence of porous check dam location on the retention of fine sediments in the Droodzan watershed in Southern Iran. Five long streams with several porous check dams that were more than 27 years old were studied. In each stream three check dams: at the very upstream section, at the middle section and at the far downstream section were selected for analysis. A number of samples from trapped sediments and from the undisturbed soils in the stream banks (adjacent to the check dams) were collected. Laboratory analysis showed that the soil samples taken from undisturbed banks have smaller particle sizes compared to the trapped sediments. The results indicated that the check dams located at the far downstream sections were more efficient at trapping fine sediment than those located at the middle sections. Also the check dams located at the middle sections were more effective than those located at the upstream sections. Comparison of sediment texture also showed that the portion of clay and silt trapped by the check dams decreased from the downstream sections toward the upstream sections. Hence, whenever, the retention of fine sediments is the primary function of the check dams, it appears that they should be located in the far downstream sections of a stream. The experimental analysis indicated that using broken and angular rocks instead of rounded rocks in porous check dam's construction improves the effectiveness of the check dams for the retention of fine sediments. The analysis of the failed check dams also showed that erosion of the bank sides underneath the check dams is the primary cause of dam collapse.