JOURNAL OF WATERSHED MANAGEMENT RESEARCH
Year:2014 | Volume:4 | Issue:7|Papers Count:15

Investigation of flooding potential of watershed basins is has considerable importance for identifying of site selection of watershed projects. For this purpose many different indices are used. Two of the most important and applicable indices are F and f indices which are based on derived peak flow from mathematical models. The objective of this study is selection of appropriate index of flooding potential for identifying of site selection of sensitive area to flood production in Jiroft dam basin. In this regard, we used rainfall-runoff (HEC-HMS) model and RS &GIS techniques. Results showed that the values derived using f index had a high correlation coefficient about 81% with values of curve number index, so that by varying of the modified curve number, values of this index also varies linearly. In this way f index was selected as a suitable index for flooding potential of region. Finally prioritize map of effective areas in flood peak was plotted in GIS environment.  

In the present study, by classifying the flow rate and dividing the time series, some statistical regression models are investigated and with the establishment of regression relationship between observed flow rate versus sediment rate and simulate it according to the least square error and USBR and FAO methods, the sediment rating curves are presented with the its statistical analysis. Then, the most appropriate model is selected according to statistical indexes viz. mean square error and determination coefficient. Moreover, the value of long term suspended sediment yield are estimated by combination of the proposed models and the type of flow rate such as flow integrated curve, mean daily flow rate and mean monthly flow rate. In this case, the daily measuring flow rate and sediment concentration for 23 years at Ghoran Talar Hydrometric station located in Babolrood River is used. Finally, the combined mid classes model according to FAO method with mean daily flow rate have been recommended as a suitable model.

Mass movement has effective role on destruction of roads, pastoral and residential areas and crating the erosion and sediment in watersheds. Many factors are associated with landslide, and study of landslide is differing based on scope and viewpoint. In this study, physical and mechanical properties of 24 sample soil were determined in homogenous units around the forest roads and soil analysis was done in soil laboratory. Results showed that this area is susceptible for landslide and occurrences the hazard increase in northern slopes and soft particles and increase the soil moisture content. Most samples had moderate liquid and plastic index, that increase the water in these soils led to increase the landslide occurrences. Our findings revealed that for road construction and each structure, special attention to physical and mechanical soil properties are necessity, and for each civil action, safety and controller precaution such as drainage and soil stabilization are essential for susceptible areas to mass movement.  

Discharge and rainfall are important factors in climate parameters, as their prediction and the identification of their behavior is important for water resources management. To evaluate the long-term changes in climatic factors, i.e. discharge and rainfall, in west Lake Urmia, six stations have been used over a period of 30 years from 1977-2007. In this research, the trend analysis is done by the R software and nonparametric statistical methods (Mann - Kendall and seasonal Kendall test) were studied. The results showed that the rainfall has no trend in some stations and with a negative trend in the others. But, discharge is in most cases has a significant decreasing trend. According to the study area, this decreasing trend is in agreement with the global climatic changes in the northern 30◦- latitude. The results of this study can be used for water management programs in future planning.

Gradual changes in global climate caused the repeated occurrence of droughts, floods and major sea storms. Iran is located at the dry belt of the world, including countries that their water resources, agriculture and vegetation are gradually destroying. In this study, the potential impact of climate change on variations of climatic homogeneous regions was investigated using climate change models and L-moments technique in Iran. For this purpose, the data of HadCM3 model that were resulted from GCM-runs based on the IPCC-SRES scenarios of A2 and B2 were acquired and analyzed for projection of daily Tmin, Tmax and precipitation for the projected period of 2010 to 2039. At the first, Homogeneity test was performed using Cluster Analysis (CA) measures for 40 stations of Iran in base data (1961-1990) and projected data (2039-2010) under two scenarios A2 and B2. Then Factor analysis was applied to determine main influencing variables on delineated homogeneous regions. Finally, homogeneity test was done using L-moments measures. The results illustrated that the Generalized Extreme Values (GEV) was the best-fit distribution for many homogeneity regions. The results showed climate change affects the classifying of homogeneous regions in the country. At the final step, the possible classification of homogeneous climatic regions were identified for the coming period of 2039-2010 and under two different climate scenarios A2 and B2 homogeneous 2012 regions were determined based on the 1990-1961 base period.

In hydrological analyses and flood risk studies, the application of probability laws and probability distribution functions is inevitable. Hence, in this study at the Karoon watershed, the regional method that has more accuracy compared to other methods along with the linear moment method was used. In this method, homogeneous units over the watershed area are firstly determined; and for each unit an appropriate distribution function is then sought. Using daily rainfall data of 38 rain gauge stations, 3 homogenous units were indentified in the study area. For each unit, an appropriate distribution function was determined using the linear moment method. The distribution functions of Gen. Logistic, Gen. Extreme Value and Gen. Logistic were introduced for homogenous units 1, 2 and 3 respectively. Using dimensionless values of the growth curve created for each homogenous unit and the average 24-hour rainfall in each rain gauge station, rainfall for different return periods were obtained. In addition to that, models were presented for calculating the mean rainfall. By comparing the values of rainfall in different return periods, the rainiest stations in short and long return periods were determined. In this research, the ratio between the average 24-hour rainfall and average annual rainfall was considered as a criterion in specifying stations with high flood risk. The stations with high flood risk may be given a higher priority in watershed management practices.

In Watershed management after of design planning stages, the most important step, select the best plan is among the watershed. In such circumstances faced with a decision we are affected by several criteria. Analytical Hierarchy Process (AHP) is one of the most comprehensive systems designed to make decisions with multiple criteria. Based on AHP technique to solve the problem or problems in the basin studied the first became selected number of options including: 1- Plan A- includes mechanical operations, 2- Plan B includes the biological operations and 3- Plan C- construction projects and services. Then in order to choose the best plan were considered four criteria including costs, soil conservation, flood reduction and water quality. Then Based on opinions of university professors and experts was attempted to evaluate options by couple comparison matrix by Expert choice software. The results showed that for cost criteria, biological operation were ranked as the best alternative plan with the relative weight 71.7% and the rate of inconsistency 0.09, for soil conservation criteria, mechanical operation were ranked as the best alternative plan with a relative weight 55.9% and the rate of inconsistency 0.08, for reducing flood criteria, biological operation were ranked as the best alternative plan with relative weight 58.2% and rate of inconsistency 0.03 and to water quality criteria, biological operation were ranked as the best alternative plan with the relative weight 59.2% and rate of incompatibility 0.01. After calculating the weight of each project respect to all of criteria, became specified contribution each of criteria in determining best plan. That most important criteria, is cost with relative Weighing 60.3% And best plan, Biological operation with relative weight 60.2% respectively.

Predicting flood height changes in reservoirs and rivers is done by routing. one can also estimate the maximum amount of the flood in a moment regarding to the size of the flood through the dam and flow rate reduction down the river and according to it and also the degree of importance of installations downstream, preventive actions can be identified. Reviewing the flood routing is possible in two ways called hydraulic and hydrologic. Hydrologic method is less precise in compare to the hydraulic one, but hydrologic method can simply be applied and has reasonable results. These characteristics cause to use the hydrologic method for different purposes like flood control, flood zoning, structure design. In this study we used some hydrological methods like Modified Att-Kin method and Muskingum for routing in a part of watershed forum located in Mazandaran province between Pol-Sefid and Shirgah. In our study Muskingum with RMSE=0.559 and =0.9 was more efficient than Att-Kin method.

Short-term runoff forecasting is very important due to direct relationship between mangers approach with loss of life by flood. In this study, daily rainfall-runoff modeling was carried out in Hajighoshan watershed using artificial neural networks (ANNs) and adaptive neuro-fuzzy interface system (ANFIS) with different inputs(current day rainfall; current rainfall and pervious day rainfall; current rainfall, pervious day rainfall and two previous day) methods. Also, the different functions i.e. Gaussian, Gaussian 2, Triangular, Gaussian Bell shape were used to ANFIS and number of neurons at hidden layer of ANNs were changed between 2 to 10 neurons. Root mean squared error (RMSE), mean absolute error (MAE) and correlation coefficient (R) statistics are employed to evaluate the performance of the ANNs and ANFIS models for runoff forecasting. Based on the results of test stage, ANFIS with RMSE=7.11, MAE=2.18 and R=0.60 is superior to rainfall-runoff modeling than the ANN with RMSE=6.03, MAE=1.97 and R=0.39.