مجله علوم و مهندسی آبخیزداری ایران
پیاپی 21 (تابستان 1392)

The regional frequency analysis is one of the methods that estimates maximum daily rainfall in regions where no data is available. Cluster analysis is used to identify hydrologically homogeneous regions in regional studies. In this study، fuzzy cluster analysis was applied to identify hydrologically homogeneous regions at the southern coast of Caspian Sea in the Golestan، Mazandaran and Gilan provinces. The homogeneity of each region identified by cluster analysis was checked by Hosking-Wallis heterogeneity measures. Then، suggestions were proposed for adjusting the homogeneity of the regions. The best regional statistical distribution was selected based on the goodness of fit test. The generalized logistic distribution was chosen as the best regional statistical distribution with different parameters for each homogenous region in this study. Finally، parameters of maximum daily rainfall were estimated by the L-moment method.

Sediment yield prediction is one of the important factors in watershed management. So far many different techniques viz. artificial neuron network (ANN) and regression models have been used to predict sediment yield. However، the performance of the models has not been evaluated. The present study therefore aimed to model storm wise sediment yield from small plots located in disturbed and undisturbed forest areas in three replicates in Educational and Research Forest Watershed of Tarbiat Modares University، Kojour، which was undertaken between October 2008and April 2009. The modeling was conducted using two methods of ANN and bi، and multivariate regression models. The performance of the models was checked using RMSE، R2 and coefficient of efficiency. The results of this study showed that the multivarite regression model with three input variables of rain depth، runoff volume and runoff coefficient outperformed other multivarite regression models. Similarly، the ANN model with the same input variables had better performance compared to other ANN models. In overall، the ANN models with the same input variables outperformed multivariate regression models in the study treatments.

Generally، the particles start moving by force of surface water flow stress which is driven by the rainfall. Rills start to appear when the erosivity of the overland flow surpasses the resistance of the soil to detachment. The expansion of the rills depends on parameters such as water shear force (flow shear stress) and soil resistance. Furthermore، shear stress required for particles detachment is a function of runoff rate، slope steepness، and hydraulic characteristics of the surface. This research aims to obtain a better understanding of the rill formation process under different rainfall and hill slope characteristics (e. g. flow shears stress and soil loss) on Gy1 Marl Formation of the Taleghan basin. To do this، two different slopes and three rainfall intensities were considered، and all experiments were undertaken in the Institute of Soil Conservation and Watershed Management. The average flow shear stress required for rill formation was determined to be between 0. 21 to 1. 38 Pa. The effect of slope، rainfall intensity factors and their interaction effect on the rill formation were statistically meaningful at a 0. 01 significance level. The distance from the top of the slope to the point of rills formation was exponentially related، and it decreased with an increase in the slope and rainfall intensity. The average of soil loss under the rainfall intensities of 10، 55 and 110 mm/h was estimated to be 0. 45، 7. 3 and 25. 6 Kg، respectively. Thus، it can be concluded that both factors individually as well as interactively affect the values of shear stress and، in turn، soil loss.

There are several methods for regional assessment of landslide. The most popular one is based on the preparation of the zoning map of landslide hazard and risk. In recent years، the application of new technologies has resulted in the increase of the precision of landslide hazard zoning models. In these methods، the effective factors on landslide instability are ranked and based on these ranking and some simple rules the necessary maps will be produced. The review of previous works shows that due to the direct effect of experts'' judgment (human error) the results of these methods/models are not satisfactory consistent with observed landslides. On the other hand، the large scale landslide hazard maps which are expected to have higher accuracy than the small scale ones need more accurate site data that is not usually available in most regions or their provision is not cost effective. It seems that most part of this differences and error arises from inappropriate evaluation of geology and engineering geology factors. In this study the method of “Paleo-morphology” is suggested for preparing landslide zonation maps. This method is based on the study of the source of deposited material. In this method، after a careful study of a selected area the geomorphological map of the present circumstance will be prepared. Then، by considering the basic structural geology of the region، the paleo structure of the region will be reconstructed. Susceptibility of different formations to generate sand، silt or clay-rich layers through mechanical and chemical weathering is the main factors that have to be taken into account. The source of eroded material from different formation can be recognized by comparing these two maps. Then، by simple evaluation of the geotechnical characteristics of the same weathered and eroded material، the ranks of masses can be used for improving the models. The method and its application in Alborz Mountain، northern Iran is introduced in this paper. First، this area was studied and its hazard zonation map was prepared using conventional models such as the Anbalagan method. Then the method of scoring was modified using the “Paleo-morphology” method. Finally، the hazard zonation map was prepared based on the modified method. Comparison of the outputs using the Anbalagan and Paleo-morphology methods showed a meaningful and great improvement in the precision of the results obtained from the Paleo-morphology method.

The long-term monitoring and forecasting of climatological parameters in each zone can be a suitable technique to deal with the consequence of climatic fluctuations such as drought، flood and etc. The purpose of this study was to identify the Zayanderoud watershed drought and the effect of Southern Oscillation Index (SOI) and the North Atlantic Oscillation (NAO) on climate conditions and climatical parameters such as precipitation. To do this، the long-term time series (1970-2009) of synoptic and climatology stations and the data of NAO and SOI were provided from the site of NOAA. To determine the extent and impact of the NAO and SOI on drought، the correlation between the standard precipitation index at the end of May for 3-، 5- and 8-month time scales and SOI and NAO indices were estimated. Also، the correlation coefficients between seasonally and monthly precipitation in this watershed and the associated indices were calculated. The results showed that the precipitation of Meime، Najaf abad، Freydan، Freydoonshahr، Daran، Chadegan، Koohrang has statistically a significant negative correlation with SOI. However، Esfahan، Freydan and Freydoonshahr have statistically a significant negative correlation with NAO. Shahreza، Abade and Varzane that are located in the dry zone showed no statistically significant correlation with any signals and SOI and NAO indices. The mentioned indices in both synchronized and unsynchronized states showed to have a statistically significant correlation with seasonally and monthly precipitation in different parts of this watershed.

Gully erosion is one of important erosion forms in Dareshahr، the Ilam province. The present study therefore aimed to recognize the watershed characteristics affecting gully development and dominant processes in gully initiation. Towards this attempt، 18 gullies with three types distributed in different topographic and soil characteristics were selected. Their associated relationships were then established. The results of topographic characteristics showed that the relation between slope and drainage area of linear gullies in rangeland areas was negative. The critical threshold area for gully development in slope of 12% was 6ha، highlighting the important role of surface runoff in the formation and development of gullies. However، no meaningful relationship could be established between slope and drainage area of frontal and digitated gullies. This confirms the significant effect of other factors compared to surface runoff influence. The study of gullies in different geologic formations also revealed that the sub-surface runoff plays an important role in Gsachsaran and Quaternary formations in the formation and development of gullies. In contrast، the Hortonian runoff was responsible for gully development in Pabadeh geologic formation. Soil sodium، silt and sand contents were also factors affecting gully topography with a reverse relationship with drainage area of the gullies.

Study of spatial variability of runoff and soil loss and the understading of their distribution is vital for strategic planing in water and soil conservation. In this study spatial variability of runoff and soil loss were investigated in summer rangeland of Nesho in the Mazandaran province. For To do this، 110 runoff and sediment yield samples were collected by a systematic sampling strategy on a regular grid with a dimension of 30×30 m using simulated rainfall with a 2 mm/min intensity and 11-minute duration on 0. 09 m2 plots. All the samples were transported to the laboratory، and their characteristics including sediment yield and concentration were analyzed. After data normalization، classical statistical analysis was used to describe runoff and soil loss properties. Geo-statistical analysis was also applied to illustrate the spatial correlation of runoff and soil loss so that their spatial distribution was finally mapped using the kriging technique. The highest and lowest coefficient of variation was related to sediment yield and time to runoff generation with 93. 75 and 28. 43 percent، respectively. Fitted models for runoff and sediment characteristics were spherical and exponential models، respectively. Based on the results of variography، runoff volume and sediment concentration with 1010. 90 and 831 meters showed to respectively have the highest and lowest impacts on runoff and sediment characteristics. Given the strong spatial dependancy of these variables، it can be stated that kriging method has high cabability in estimating these variables at unsampled points as well as their zoning.

HEC-HMS and Artificial Neural Network (ANN) were applied to simulate the rainfall-runoff process in the Kasilian basin. The study site is located at north of Iran with an area of 68 km2. The ANN has high capability in establishing connection between input and output data and the HEC-HMS model has shown its capability in optimizing simulated hydrographs. Initial loss is a quantitative parameter which is dependent on three main factors including soil، vegetation and Antecedent Moisture Conditions (AMC). In this study after optimizing the initial loss parameter using the HEC-HMS model، this parameter along with incremental rainfall were applied qua inputs in the ANN to simulate runoff or discharge values. Comparison of the obtained results under two scenarios of optimized and non optimized initial loss showed that optimized initial loss highly enhance the accuracy of simulated runoff and flood hydrograph by 100% in some events.

Irregular temporal and spatial distribution of rainfall in arid and semi-arid regions leads to not only devastating floods but also losses of surface runoff. Hence، the control and utilization of surface water in order to feed groundwater can be a good solution to prevent losses of surface water runoff. The flood spreading is a well know approach in this regard and the main challenge for doing that is to find the suitable location for such projects. In this study، the Chrdavl watershed in the Ilam province was selected. After selecting the effective criteria in locating flood spreading projects such as slope، land use، lithology، rainfall، drainage and alluvium thickness، for each of these criteria a data layer was created in GIS. To overlay the data layers the Boolean Logic Model، BLM، was used. Results showed that north Janjan village، Zanjireh plain and south Moshakan village with an area of 3095 ha are the best locations for flood spreading and artificial recharge in this region.