nasim arman; Ali Shahbazi; mohammad faraji; somaieh dehdari
Abstract
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 ...
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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.
Narges Ghasemiamin; Nasim Arman; Hossein Zeinivand
Abstract
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 ...
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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.
Narges Ghasemiamin; Nasim Arman; Hossein Zeinivand
Abstract
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 ...
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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%.
Fatemeh Zandi Dareh Gharibi; Zohreh Khorsandi Kouhanestani; Maliheh Mozayan; Nasim Arman
Abstract
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 ...
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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.
Zahra Faghfouri; Nasim Arman; Mohammad Faraji; Zohreh Khorsandi
Abstract
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 ...
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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.
