پژوهشنامه مدیریت حوزه آبخیز
پیاپی 3 (بهار و تابستان 1390)

In this study, the relationship between the gully formation and some soil properties, climatic factors, land use and slope was investigated in Dareshahr Township in Ilam Province, Iran. Toward this attempt, 18 axial, digitated and frontal gullies were recognized. The soil samples were taken from the top and subsoil in the gully bank. The climatic, land use and slope information were obtained using Dareshahr Climatic Station and available maps, respectively. The relationship between gully erosion frequency and slope as well as land use was then studied using ANOVA and the most important factor was ultimately recognized by using principle component and regression analyses. The results of the study have shown that most numbers of gullies were formed in areas with slope less than 10% and land uses had no significant effect on gully formation. Besides that, the percentage of clay and sand as well as calcium content were found to be as most affective soil factors on gully formation. Among climatic factors, the rainfall depth and average intensity played important role in gully initiation. The results extracted from discriminate analysis also proved that the depth of rain is the most affective factor in gully formation in the study area.

Extensive areas of productive agricultural lands of river banks, due to flooding, destroy every year. Therefore, for river path training and management, beside evaluation of flow hydraulic behavior, flooding locations, flooded area percentage, flood height relative to land surface digital elevation, and flood characteristics during different return periods should be determined. Therefore, this research is aimed to map and delineate Babolrud flooding areas. For this purpose an attempt has been made to use GIS technique and HEC-RAS software for the assessment of flood risk zonation, from Anarestan to western Daroonkola village in a 4- kilometre length. To conduct this study digitalized topographic maps of 1:1000 scales were prepared and the TIN map of the mentioned area, was prepared using ARCVIEW and Hec-GeoRas environments. By identification of river and 113 cross sections geometry characteristics, the flow and Mining roughness coefficients were introduced to the model, therefore the flood return periods of 2, 5, 10, 25, 50, 100 and 200 years were calculated and ultimately flood zonation was determined. Finally, based on the flood zonation maps, it was determined that 80.3% of the flooded areas within the studied zone were affected with 25 years or less return periods. It reveals that the Babolrud banks are flat and more vulnerable to high frequent floods.

Quality of streamflow information for a given watershed or region is primary information needed for the sustainable designing and operation of water resources systems. For an optimal hydrometric network design, they should be reviewed periodically based on the information needs and future water resources development plans. This study evaluates regional values of streamgages in Bakhtegan-Maharlu basin using the discrete entropy. Discrete entropy can overcome limits of data normality assumption in past research and applications for hydrological variables. To determine the regional value of each station within a region, several information parameters such as marginal entropy, joint entropy, information send and received by stations and transinformation index between stations, were calculated to identify essential streamflow stations and critical area. Sensitive analysis to number of discrete intervals show that the entropy is sensitive to changes, but the ranks based on entropy indices appear to be less sensitive. Validation result confirms that the entropy is useful and comparable with correlation to characterize the essential and excess station in the region.

In hydrology, there has been a virtual explosion in the use of artificial neural networks (ANNs) over the last 10 years. However, most of the recent ANN research have been devoted to comparing ANNs and more established rainfall runoff models or to assessing ANN training algorithms, while norms are still lacking that would help hydrologists to create and train efficient ANN models in a systematic way. In the present study was used multi layer perceptron for forecasting of Bakhtiari's of daily inflow. For this purpose was examined role of antecedent precipitation index in rainfall runoff process and this parameter added to model inputs and considerable improvement was resulted in forecasting result (with determination coefficient of 0.94 in verification step). The results of sensitivity analysis verified that one day ago inflow and 7 days ago precipitation in Tangpanj station are important parameters in river daily inflow forecasting.

One of the effects of climate system change is the occurrence and intensification of drought phenomenon. Prediction of drought condition can play an important role in mitigation of its effects as well as effective management of the available water during the drought periods. Different approaches have been presented for evaluation of drought. Analysis of precipitation data is the general method for drought evaluation, as acceptable prediction of precipitation before its occurrence, would be necessary and effective for analysis of drought. The purpose of this research is the evaluation of the effect of data processing on applicability of two data mining models on drought prediction in Yazd station. In addition, during the recent decades some new computer based models have been developed for drought prediction and in most of the cases they have presented quite satisfactory results. In this research, prediction of precipitation, which is the main component on drought occurrence, has been carried out in Yazd synoptic meteorological station. Therefore, two data mining methods including Regression Decision Tree (RDT) and Artificial Neural Networks (ANN) have been used, and simulations were carried out in two different conditions. In the first condition, the measured values of some meteorological variables were used as inputs and the amount of precipitation was predicted 12 months in advance. However, In the second condition, 3-year moving average of data were the inputs of the models for prediction of precipitation amount 12 months before its occurrence. Finally for evaluation of the model performance in different conditions, statistical criterion including R and RMSE were employed. Results indicated that using moving average of data as inputs of the models has considerably improved the performance of the models. Both RDT and ANN methods are able to predict the amount of precipitation in Yazd station 12 months before its occurrence.

Reservoir optimum operation is one of the optimization issues in water resources engineering which has been evaluated by varios known optimization methods, yet. In this study firstly reservoir simulation was done based on standard operation policy (SOP). Then simulated annealing algorithm (SA) has been used as a numerical optimization method with inteligent random structure for optimal reservoir operation. Because of SA algorithm sensivity in input paratmeters, therefore sensivity analysis were done and appropriate combination of that parameters was selected. In order to validation of SOP-SA combined algorithm, asymptote method was applied. Results indicated capability of algorithm on global optimal finding. The SOP-SA combined algorithm was run with objective of annual deficit minimization with constraint and limitations such as reservoir storage and release volume for Doroodzan dam. After algorithm run, reservoir storage and dam release in operation period were studied. Results of Research shown that SOP-SA combined algorithm reduced deficit intensity in drought priod by distribution of deficit in different mounths. In addition, the number of months with a very low monthly supply probability percentage (less than 50 percent); 22 months in the SOP algorithm, were reduced to 10 months.

In this study, the relationship between the gully formation and some soil properties, climatic factors, land use and slope was investigated in Dareshahr Township in Ilam Province, Iran. Toward this attempt, 18 axial, digitated and frontal gullies were recognized. The soil samples were taken from the top and subsoil in the gully bank. The climatic, land use and slope information were obtained using Dareshahr Climatic Station and available maps, respectively. The relationship between gully erosion frequency and slope as well as land use was then studied using ANOVA and the most important factor was ultimately recognized by using principle component and regression analyses. The results of the study have shown that most numbers of gullies were formed in areas with slope less than 10% and land uses had no significant effect on gully formation. Besides that, the percentage of clay and sand as well as calcium content were found to be as most affective soil factors on gully formation. Among climatic factors, the rainfall depth and average intensity played important role in gully initiation. The results extracted from discriminate analysis also proved that the depth of rain is the most affective factor in gully formation in the study area.