فهرست مطالب nasim arman

Flood spreading is one of the suitable methods for controlling and optimal use of flood in arid and semi-arid regions, and consequently, locating areas prone to flood spreading is very important. The purpose of this study is to locate areas prone to flood spreading in the Baghan Dam watershed of Jam city located in Bushehr province.

For this purpose, effective layers including slope, land use, geology, geomorphology and fault as standard options for physical properties, permeability layers and alluvial thickness as standard options for hydrological properties and distance from wells, aqueducts, City, village, and road were considered as options for the criteria of economic and social characteristics, as digital information layers, and were standardized by fuzzy logic. In the next stage, slope, land use, geology and geomorphology layers were standardized as Boolean logic as constraints. Based on the average of experts' opinions, the layers were weighted by hierarchical analysis (AHP) and the incompatibility rate (0.09) was calculated. The layers were combined by multivariate spatial evaluation (SMCE) and weighted linear composition (WLC) techniques and final maps of susceptible areas were prepared.

The results of hierarchical analysis (AHP) showed that the distance from the fault with a weight of 0.238 had the highest and the distance from the well with a weight of 0.005 had the lowest value in locating the flood spread in the watershed of Baghan dam. The incompatibility rate was calculated to be 0.09. Based on the results of combining the criteria by Terrset software, Baghan dam watershed into 5 areas unsuitable (88%), poor (0.10%), moderate (1.6%), good (5%) and very good (3.5%) (Figure 14) was divided.

Overall, the results showed that 88% of this area has poor capability, 0.1% has poor capability, 1.6% has moderate capability, 5% has good capability and 3.5% has very good capability for flood spreading. The final map with the current situation of the area was evaluated by 30 points. The evaluation results showed that there is no significant difference between the final map and the condition of the arena.

Shohada diversion dam was constructed on the border of agricultural lands of Behbahan plain (Khuzestan province, Iran) to divert the water of the Maroun River. This dam has a concrete-soil composite. The concrete part consists of an ogee spillway, a stilling basin, and two intake channels and sediments on the right and left sides. The height of the dam is 12.2 meters and its spillway length is 150 meters. The dam has a sloping basin and its capacity is 22 m3/sec. The longitudinal slope of this basin is 1 to 5 (vertical: horizon). The studies have shown that parts of downstream of the stilling basin are being eroded and scoured. Unless controlled properly, this will continue and might lead to the destruction of the basin or the main structure of the dam. Most of the stilling or apron basins used in the previous studies are horizontal and smooth, and no research has been conducted on scouring downstream of sloping basins so far. Therefore, the purpose of this research is to explore the causes of scouring downstream of the Shohada dam's stilling basin and its controlling factors to finally provide an appropriate strategy to prevent its spread.

Water harvesting and surface runoff control systems are the important components of urban planning and development and ignoring these issues is likely to raise crisis. In order to decrease the urban flood damages, the urban runoff is needed to be evaluated correctly. Today some of models are developed for urban runoff simulation. One of the most important models in evaluating and management of urban runoff is SWMM. The aim of this study is to evaluate SWMM efficiency on urban runoff simulation in Izeh urban basin. To define design rain, concentration time was computed while considering the duration of the cloudburst as equal to this time. Also three performance indexes of Nash-Sutklif, errors sum of squares and Bias were used in order to model calibration and validation. Moreover, areas of high susceptibility were determined for two, five, 10, 20 and 50 years of return periods. Later, it was found that the principle reason of inundation is the lack of sufficient capacity of water ways. In some points, even with sufficient capacity, inundation occurs, confirmed by model. In these cases the causes stem from the improper design and construction of bridges which has lessen the size of water ways and caused junk clogging. Three rainfall events were recorded on March 13, 2017, March 28, 2017 and April 6, 2017 which were considered in order to calibrate and evaluate the model performance. Along with that, the discharge, depth and velocity of water at the outlet were considered as well. The results of the SWMM application gave indication of a good matchup between discharge, depth and the velocity of runoff for observed and estimated data. In this case, this model could be utilized to well predict the inundation hazard, design and the estimation of the cost and volume of drainage systems, management of watershed and prioritization of region to address flooding issues.

To better managing of rangeland the vegetation map is one of major factors, because plant communities is planning units of rangeland management and vegetation map shows the current status of plant communities. This research was conducted to produce vegetation type's map using Landsat 8 image classification in Behbahan, Khuzestan province. Rangelands of the study region is warm semi steppe and winter grazing. Geometric correction of satellite image was performed by ground control points with an error of less than one pixel. Atmospheric correction of existing data using the dark object subtraction was done. Field visits for vegetation type's border controlling and sampling training area was conducted. Eight supervised classification algorithms included Parallelepiped (PP), Minimum Distance to mean (MD), Mahalanobis distance (MAH), Maximum Likelihood (ML), Neural Net (NN) and Support Vector Machine (SVM) was performed. The results showed that ML algorithm has the highest overall accuracy (87.5 percent) and kappa (0.867) and PP algorithm has the lowest overall accuracy (67.1 percent) and kappa (0.571). It is suggested that, along with digital methods of classification of satellite images, visual interpretation should be used to clarify the boundary of the obtained vegetation types map.

Land use involves exploitation type of land for resolving human different needs. Land use changes is the result of interaction between human and affective factors on environment which is considered in spatial and temporal scale. Awareness of land use rates and its change in time is one of the most important factors in planning and management. By knowing rate of land use changes time scale, forecasting feature changes will be possible and do appropriate act. In this research, 2014 land use map was prepared by RS with Kappa coefficient of 0.88 and overall accuracy of 0.86 which has high accuracy. For investigating each effective factor on land use in CLUE-S model logistic regression was used and for assessment of logistic regression, ROC curve was used. After determination of demand ratio according to past changes, land use map of 2025 was prepared. Assessment of CLUE-S model showed its high accuracy (Kappa coefficient is 0.88). Also, the results demonstrated that the most land use change are related to forests and ranges to farmlands, as range and forest lands decreases 28.12 and 82.20 present respectively and farmlands increases 10.33 percent until 2025.

The study aimed to evaluate the effects of Karon 3 and 4 dams on land use and cover changes, for this aim 4 images over 28 years (taken in 1985, 2003, 2009 and 2013) were obtained and geometric, atmospheric and topographic corrections were applied. Maximum likelihood and post-classification techniques were used to detect land use/cover changes and their accuracy then was assessed using topographic maps and field works. The overall classification accuracy and Kappa statistics for all the maps were more than 0.79 and 86.24% respectively. The classification map of year 2009 indicated that about due to Karron3 dam and 6734.88 hectares because of rangeland and forest were destroyed. Classificated map of 2013 indicated about 5127.39 hectares increased because of Karon 4 too. The overall findings of this study indicate that forest and range land degradation in the region, is due to the construction of Karun 3 and 4.

Land use and its fluctuations is one of the most important factors that affects on the natural cycle in the ecosystem. Land use changes cause change in watershed hydrological cycles, water balance between precipitation, evaporation, infiltration and runoff response. Understanding the relationship between land use changes and its factors and secondary effects on the hydrological regime provides the necessary information for planning of land use and sustainable management of natural resources. At first, land use maps related to years of 2000 and 2014 were prepared, then CLUE-s model was applied to simulate land use map of 2025. For simulating runoff, WetSpa model was employed to simulate daily runoff with land use maps related to years of 2000, 2014 and 2025. According to the results, the Nash-Sutcliffe evaluation criterion was calculated 68.26 % and 66.75 % for the calibration and validation periods, respectively. In addition, model Aggregate Measure (AM) was calculated 64 % and 54.15 % for the calibration and validation periods, respectively. Land use maps comparison showed, the main land use changes in Nojian Watershed was the conversion of forest and rangeland areas to agricultural lands .As a result of these changes the annual runoff volume, peak discharge, mean daily discharge increased to 16.20, 11.35 and 9.15 percent, respectively. Results of statistical analysis using paired t-test showed that land use change has effect on discharges in the study area at the level of 1%.

Modeling of the rainfall-runoff process is important. The Results of the rainfall-runoff models have been used directly on issues such as water resource management, flood control and design of hydraulic structures. According to variety of accessible rainfall runoff models, selecting an appropriate model for a basin is important in terms of productivity and water resources management. In this study the performance of two rainfall–runoff models, IHACRES and GR2M in simulation of monthly flow were evaluated in Darhe Tkaht basin between 2000 and 2013 time. The models in the study region were calibrated and validated. The error between observed and simulated flow values was estimated based on the criteria Nash, root mean square error and the total flow volume error. Simulations is indicative satisfactory performance of two models in monthly flow simulation. In addition, the results show that the HACRES model simulate monthly flow with The Nash coefficient 0.7 and RMSE 0.56, better than the GR2M model.

Run off simulation is one of the most important topics in hydrology And its study is based on rainfall- run off models. Several rain fall and run off models have been developed and the most appropriate model should be selected for each catchment. By applying the appropriate model the water consumption will be optimized. The model should be selected for each catchment based on the model abilities and limits. In this study, the performance of two rain fall and runoff models, GR2M and GR4J were compared in Darehtakht Basin in Lorestan Province during 1379 to 1392. The Nash coefficient was used as a decision criteria for comparing two model performances. Nash coefficient for GR4J and GR2M were 42.7 and 65.5, respectively. Results showed that both models can predict the performance of the catchment accurately, but, based on Nash coefficient the GR2M is more accurate than the GR4M.

Whereas investigation of effective factors in soil erosion and sediment yield, we can`t introduce specific factors basically as a main factors in water erosion. In fact, erosion condition in an area is a result of contract effect of impressive factors collection in erosion. In order to identify the effective factors in soil erosion and sediment yield in Seied Abad Basin, interrill erosion was determined by average intensity (30 min, 10 year: 40 mmhr-1) using rain simulator in 33 plots. Also, factor analysis, multivariate regression, logistic and Scalogram model were used. Using factor analysis (principal component analysis), between 15 effective variables in sediment ratio, six factors were selected. They were runoff coefficient, sand, rocks susceptibility, soil texture and land use that illustrate %82.009 of variation of data (KMO=0.53). The results of multivariate regression model were almost the same with factor analysis and the results of the Scalogram model confirmed this. Finally, runoff volume (0.02), rock susceptibility (0.001) runoff coefficient (0.00005), and sand percentage (0.00002) were effective factors in soil erosion and sediment yield. In this regard, regarding to these factors, we can conduct policy and planning for decreasing soil erosion and sediment yield.

Identification of homogenous watershed sub basins allows generalization of environmental study results. For this purpose, first available data for 27 selected watersheds in North Alborz regarding 21 variables including physiographic and climatic characteristics was gathered. The most important factors impacting upon soil erosion and sediment yield were equivalent rectangular length, mean annual precipitation, rock susceptibility, aspect and drainage density which were identified using factor analysis (Principle Component Analysis : PCA) and a 80.72 percent variation of data was observed (KMO =0.516). For determination of homogenous region, different methods of cluster analysis (hierarchical, K-means and two step clustering) were used and three homogeneous regions were specified. Discriminant function analysis was employed and confirmed the results of cluster analysis in homogenous region. On the other hand, based on these five factors, a discriminant function was defined and canonical correlation, chi-square, wilks’ lambda values revealed that three homogenous regions were quite separate.