مجله علوم و مهندسی آبخیزداری ایران
پیاپی 16 (پاییز 1390)

The Soil erodibility Factor is one of the important and effective factor that is used for estimating water erosion by USLE model and its different versions. The main topic of this paper is the spatial distribution of K factor and knowing its effective factors. One of the factors which is usually ignored for K stimation,is the desert pavement density as the natural factor of soil conservation. The other purpose of this paper is the estimating of the variations of K factor due to landuse change, land plowging and combination with sub-layers soil. For doing that in cross-section of Yazd-Ardakan plain (including Coarse grain plain, Medium grain plain and fine grain plain) with different pavement density, by random classification sampling method, the soil samples were collected in 37 points from 0-10 cm of surface soil in each parts of plain. The rate of infiltration was measured by using double ring method. Desert pavement cover in to conditions (natural and disturbed) was measured using the exist scales in Munsell’s notebook. Grain size distribution by hydrometry method and organic matter by standard methods were analyzed. Then the spatial pattern of variations by ArcGIS9.3 and Surfer9.0 softwares and zonation by kriging method for K factor and its effective parameters were determined. To evaluate the obtained semivariogram, some statistical indices like MAE(Mean Absolute Error), MBE(Mean Bias Error), MSE(Mean Square Error), RMSE(Root Mean Square Error) and determination coefficient were applied. The results show that in fine grain plains due to decreasing the desert pavement until less than %20, it can not be considerd as the conservation factor and the relation between pavement desert and K factor is not sufficient. On the other hand, in Coarse grain and Medium grain plains (that desert pavement is more than %50), the K factor lies in the low until very low. The conservative role of desert pavement in Coarse grain and Medium grain plains that by combining pavement, the K factor is increased 10 times more than natural conditions. The results of model fitting on spatial changes show that Gaussian model is the best. Totally, ordinary kriging is suitable method for spatial variability description of K and its effective factors.

Drought monitoring has a key role in drought management. The meteorological drought monitoring in regions without enough data is always influenced by the Lack of meteorological data and deficiency in statistical data. On the other hand rainfall data is not a good indicator for rangeland drought evaluation, because of its temporal and regional distribution. In this research, variation of rangeland drought is investigated by MODIS data with 250m spatial resolution that collected in the duration of 2007-2009 fromwest part of Iran. Due to effects of drought on the quality and quantity of vegetation cover, NDVI (Normalized Difference Vegetation Index) was used as important indicators of rangeland drought. NDVI is used as vegetation index of growth season in rangelands and grasslands. So, Standard Precipitation Index (SPI) was calculated as meteorological drought index to monitor drought impact on the variation of vegetation cover. Thus, annual analysis was done to show the general trend of drought in the study area. Then the monthly analysis also applied to obtain the correlation (R) between NDVI and cumulative precipitation, SPI in different time lags. As final result, the best correlation accrued in 6 months lag and the most growth of correlations happened between 1 and 2 months. This research also presents the daily MODIS data is useful for drought study in the area with no reliable data.

Marl units with high contents of soluble salts are highly susceptible to erosion. These units produce and enter high amounts of sediment to Sorkhe artificial recharging system every year. Thus, identification of effective agents on susceptibility to erosion of marls is an essential subject. Statistical methods to determine effective factors is based on mean comparison and correlation matrix between data. The correlation matrix tables are very large and complex because so many variables are involved. Therefore, determining main variable and amount of their effect and also relationship between erosion groups is not possible with high accuracy. The aim of this study, is to determine main chemical variables on erosion by Discriminate Analysis and separating increaser and decreaser factors in erosion using SPSS software. The results showed that low rate of erosion in low to moderate surface erosion group (1) and severe surface erosion group (3) is due to TNV, HCO3 and OC correlation between two mentioned groups. On the other hand, high level of erosion in rill erosion group (2) is due to no relation with variables of groups 1 and 3 and high values of CaSO4 and SO4. As well as, atterberg limits have positive correlation with reduction erosion factors. Then by using method we can determine the effective factors fast and accurately.

Avalanche occurrence is one of the natural disasters that caused loss of life and damages in most mountainous areas of the world every year. Phenomenon of avalanche downfall in Iran is caused to irreversible damages, specially on residents and passing travelers through mountainous roads (Dizin - Gagereh, Haji Abad - Dizin, beginning Karaj - Chalus, Karaj - Chalus middle, Haraz and Imam Zadeh Davoud) in Tehran province. Unknowing the time of avalanche occurrence, exceeds the damages. Then, forecasting the avalanche occurrence probability in the avalanche paths help to reduce human and financial damages of passengers and residents. For investigation the probability of avalanche occurrence in this region, the nearest neighbor method was used. This method carried out based on the avalanche information and daily data of snow in the 22 snow stations during 10 years (from 1377-78 to 1387-88). In this method, the number of similar snowy days that were created former avalanches was determined using ArcGIS software. Then, by snow zoning in different months of investigative year by using kriging method, the rate of snow depth variations (that generates avalanche) were obtained. Thereafter, warning level, positive neighbor's ratio (NN ratio) and probability of avalanche occurrence were characterized in the every path. The results showed that in most communication paths, avalanche phenomenon has occurred in snowy months and probability in month of March is more than other months. The important reason of this phenomenon is high snow depth and increasing the temperature. Finally, probability of avalanche occurrence in Dizin – Gajereh path and Karaj – Chalous path was predicted very high. The reason of this point could be topographic conditions (high slope, slope subject to the sun), rock and mostly climate conditions (high snow depth, snow wind and temperature). The results of this research project can help to managers of avalanche control, effectively as they warn people to avoid from non - essential travels in that time or choose the other paths.

Wind erosion is one of the most important natural processes in semi arid, arid and hyper arid regions. This process occurs in conditions that wind has considerable speed and abundance in addition to existence of sensitive soil. Bafgh city is one of the arid regions of Central Iran has low rainfall and poor plant cover. Strong winds blowing on the surface of these non-coverage land causing soil erosion and other problems. Identify Storm prone areas could reduce its risks and losses. So identification and controlling of storm prone areas, the wind erosion threshold velocity should be determined in different facies foremost. In this study, the threshold velocity of each facies was measured by using of wind erosion meter (W.E. meter), and the iso-threshold velocity map of wind erosion was provided. For analyzing critical wind speed and aspect, the anemometers data of Bafgh synoptic station during 14 years statistical period was used. Grueling winds condition of this region was studied by Wind Rose (WRPLOT view 5.2.1) and Sand Rose (Sand Rosegragh 3.0) software. Results showed gruelling winds blow from Northeast in 39 percent of the study area are fine grain plain facies with parabolic surfaces and Nebka, sand dunes facies gardens and residential areas, and medium grain plain with medium reg and oued. The threshold velocity in these areas was 7 to 16 meters per second.

Desertification process as a continuous and destructive phenomenon and as a global scourge, not only developing countries but also developed countries threatens. Successful projects and control desertification and reduce risk factors inhibit desertification requires proper understanding of cause and effect relationship between desertification and existing processes, but it is obviously what the process and accelerate out of its normal effect of making human factors.In The case study Desertification procesure in the framework of work units assessed applying different valuable and available indexes of erosion including: kind and density of water erosion, drainage net density, major landuses, green cover, appearance of erodiblity formations, soil cover, number of days with dust storm. Map of desertification map for the watershed generated and overlayed with current landuse map. Finaly desertification procesure involving landuse were assessed in categorized geomorphological units; mountain, pedimont and playa. Results showed that the dominant form of erosion in mountain is water one. Over the pedimont and playa, because of erosion activities in highlands and focusing land exploitations in lowlands, desertification is more intense and both water erosion and wind erosion are active.

Runoff is a key factor in watershed management and it is valuable for suitable programming to improve watershed condition. Also, runoff estimation in watersheds is important for water resources studies and design of the flood control structures. Flexibility of Artificial Neural Networks (ANNs), its low cost and high capability for monthly runoff estimation was considered to using capability of these networks for monthly runoff estimation in the upstream sub basins of the Zayandehrud Dam. Moreover, Zayandehrud Dam Basin has important role for water supply of urban, agriculture and industrial sectors. In this study, two types of neural networks; including multilayer perceptron (MLP) and time lag neural networks (TLNNs) was evaluated in basins of Samandegan, Plasjan and Zayandehrud. Results indicated that TLNN model has high capability for runoff estimation, although this structure involves high sensitivity during training stage. Also this model had lower error compared with MLP Model. These networks (TLNNs) can estimate monthly runoff with suitable training and implementing inputs of 3 or 4 rain gauges and 2 or 3 temperature stations. TLNNs are suitable simulator of watershed response to the inputs such as rainfall and temperature, due to its high flexibility.

Qaleshahrokh watershed with an area of 150980.1 hectares was selected for investigating the relation between land use changes and watershed hydrologic behavior. From satellite data, land use, curve number maps and runoff coefficients were obtained for 1975, 1990 and 2002. Results show that most of the land use changes occurred through converting rangelands to dry lands and irrigated agriculture. Weighted means of CN and C was 85.9 and 0.55, 87 and 0.58, 87.24 and 0.6, in 1975 to 2002 respectively. Also runoff depth increased 0.25 mm per year between 1975-1990 and 0.075 mm/year between 1990-2002.