مجله علوم و مهندسی آبخیزداری ایران
پیاپی 15 (تابستان 1390)

Rainfall-runoff process is a non-linearity and complex phenomenon in hydrology. Comprehensive models are widely implemented for rainfall-runoff modeling. However, these models require a large number of detail information and their application are limited to just field scale studies. In case of lack of detailed data, black boxes model like artificial neural networks can be implemented to model the complex and nonlinearity relationships. To simulate the rainfall-runoff hydrograph in the kasilian basin a multi layer perceptron design of artificial neural network with architecture 9-10-7 was implemented. First precipitation data was divided into four groups to consider the temporal pattern of rainfall. For each group, rainfall distribution in different time quartiles, base flow of hydrograph, total depth of rainfall, and rainfall depth until time of concentration, rainfall duration and antecedent precipitation index was derived and inserted to the ANN model as an input parameters. The output of ANN model consists of peak discharge and its occurrence time, hydrograph base time, time of the 50 and 75 percent of peak discharge occurrence and hydrograph widths corresponding to these discharges. ANN model was executed for the different groups of data using the various activation functions in hidden and output layers. The results indicated that there is a strong correlation between model outputs and measured data. Correlations varies from 0.9107 (RMSE= 0.0882) for the first group to 0.99 (RMSE=0.0678) for the fourth group. These strong correlations confirm that in case of lack of detailed data, ANN model can be used for simulation of hydrological parameters.

Nowadays, soil erosion is one of the most important natural hazards in water and soil resources management. Therefore, having estimates of sediment yield are essential for the sustainable environment management. In this respect, proposing a novel method to estimate sediment yield at the scale of a watershed, utilizing a deep knowledge of variables controlling soil erosion and sediment delivery process, is needed. Generally, in the modeling of environmental processes (e.g. sediment yield), available datasets are imprecise, and their relationships are vague. Hence, the most adapted methods with these restrictions should be developed and used. This paper aims to develop a multiple fuzzy regression model for estimating the sediment yield of 29 sub-watersheds located in the north east of Iran. To do this, various morphometric, hydrologic, lithologic, climate and land use characteristics of each sub-watershed were analyzed. Then, the most controlling variables for different modes using multiple linear regression models were identified. Fuzzy least square regression models with fuzzy output and coefficients using selected most influential variables were then constructed. The results showed that the capabilities of the models predictions during wet months were enhanced, the period in which, the larger amount of events occurred. For instance, the models efficiency for prediction of average sediment yield over the whole year and wet months, in the conditions of 29 sub-watersheds, 17 large sub-watersheds and 12 small sub-watersheds increased from 0.85 to 0.88, 0.77 to 0.87 and 0.82 to 0.9, respectively.

Stable width of regime rivers is one of the most important features in watercourses on the basis of which design criteria is established. Up to now, many researchers have studied numerous approaches to predict river stable width. Herein this research, different approaches have initially been introduced and then 440 data points of gravel bed were used to derive regime equations for one, two and three variables with bankfull discharge, median bed material size and longitudinal channel shape, respectively. In this research, non-dimensional Parker's approach was applied to obtain new regime equations for the so-called database. Finally, the dimensional and non-dimensional derived equations, accompanied by others works, were tested with another database including 95 data points of different gravel bed rivers with 50% error bands. It was deduced that three-variable equation is most appropriate. Likewise, a comparison among introduced relationships were also made and indicated that Yalin dimensional equation and Arbeláez et al. non-dimensional equation are most appropriate to estimate stable width with 50% error bands.

Land use Changes generally will affect on soil physical and chemical properties and so will diminish soil quality. In this study, the effect of land use change on soil degradation in parts of northern Iran was investigated using aggregate stability index (MWD), soil erodibility, soil deterioration indicators and soil bulk density. For this reason, 120 soil samples from depth 0-10 and 10-20 cm were collected in three adjacent land uses in Kasilian Watershed including forest, grazing and agricultural area. The results of one- way analysis of variance (ANOVA) showed that soil erodibility, aggregate stability indices and soil bulk density have significant differences in two depths between three land uses at 99 percent level. To compare with forest, soil erodibility has increased in depth 0-10 in agriculture and grazing land by 85.7 and 114.3%, respectively. The results for depth 10-20cm were observed to be 9.09 and 72.72%. Soil aggregate stability also has increased by 52.17, 19.56 % in depth 0-10 cm and by 24.17, 55.48% in depth 10-20 cm for agriculture and grazing land, respectively, comparing with forests land. The results also illustrated negative values of soil Deterioration index in agriculture and grazing comparing with forest.

Determination of detention dam construction priority is important for selection of optimized method of time schedule for the construction. Since Tajrish watershed is in upstream of populous city of Tehran, its flood control is very important. It is necessary that detention dam priority indices be evaluated for studying the effect of flood control structure construction time scheduling. Therefore, the watershed flood has been simulated using HEC-HMS model and it has been calibrated by recorded rainfall and flood data. The 200 year-return-period flood was used to optimize the outlet of detention dam in according to the recommended water standard of Iran. In this paper, different indices are studied for determining detention dam priority, as follow: area, peak discharge, specific peak discharge, peak discharge reduction percentage due to omitting of a sub basin runoff (FI), specific peak discharge reduction percentage due to omitting of a sub basin runoff (fi), peak discharge reduction due to operation of a detention basin in a sub basin (Fm), specific peak discharge reduction due to operation of a detention basin in a sub basin (fm), total cost and unit flood reduction cost(ΔQC). The detention dam construction priorities have been determined using these indices. Fm and fm are new priority indices proposed in this paper. Furthermore unit flood reduction cost (ΔQC) index was used to rank priority indices. The results show that fm index has the minimum sum of absolute priorities differences (PIMC) with standard index (ΔQC) and the cost index has been the maximum one. fm and cost indices have PIMC equal to 6 and 80, respectively. So, they are the best and the worst indices, respectively.

In this paper, the hazard of landslide in Chehel-chay sub-watersheds was examined via weighted(AHP) bivariate statistical model in order to specify hazardous areas of landslide for risk and hazard management of watershed. First, landslide (number and area) were mapped through field observation and using GPS set. Then, distribution map of landslide was prepared for each sub watershed. Through reviewing literature and studying conditions of Chehel-chay watershed, 9 factors incude elevation, slope, aspect, lithology, distance from fault, stream and road, land use, and precipitation amount were chosen as an effective factors on landsliding (independent variable). Relative hazard map was prepared with 6 classes for each one. Results showed that there are significant differences between abundance and area of sliding in the Sub-watershed, between surface density among 4 sub-watersheds, between areas of hazard classes in each Sub-watershed and also area of each class among the sub-watersheds, in 1% probability level, but there was no significant difference in numerical density among 4 sub-watersheds. In 59% of classes in different sub-watersheds, there was no significant difference between area of landsliding and areas of different factors classes in 1% probability level. Also results showed that on the basis of percentage of high and very high hazards, Ghale Ghafe (51.6%), Khorooji (19.7%), Chamani (1%), and Dozin (0%) are in 1 to 4 ranks, respectively.

Iran encounters heavy damages due to the landslide occurrences because of topographic, geologic, and climatic conditions. In addition, incorrect principles in the development of residential areas, road building and etc can cause an increase in the risk, so recognizing of landslide susceptible areas are important. In this research, the landslide zonation map in Ilam dam basin presented by using SINMAP model. High rate of sediment load is entered to the river and finally is delivered to the reservoir of Ilam dam. For carrying out this research, first, 10 hill-slopes (stable and unstable) were selected randomly. Then, physical and mechanical characteristics of soils (like soil texture, hydraulic conductivity, internal friction angle and soil cohesion) were computed. The obtained results by running the SINMAP model, shows high accuracy for predicting the landslide in hill-slopes. Based on the landslide hazard map by using the SINMAP model, more than 65% of the study area has been located in stable class. The moderately stable and quasi-stable classes each cover 10% of the area. Moreover, unstable classes (instability less than 50% and completely unstable) cover more than 15% of the area in Ilam dam basin.

The present study was conducted to investigate the effects of watershed management activities on flood behavior through integrating HEC-HMS and HEC-RAS models for the residential reach of Jaghargh watershed in Khorasan Razavi Province. Towards this attempt, the models inputs were provided and subjected to calibration and validation stages. The response of the watershed at the study reach was then assessed. The results of the study showed that integration of models was useful in assessment of flood control measures and effects of flood measures on flood peak and inundation area have decreased with increase of return period. The maximum and the minimum effect of flood control activities were also observed on flood peak and inundation area, respectively.