Davood Mokhtari; Aliakbar Rasouli; Monire Moosabeigi
Abstract
Introduction: One of the most influential factors in the occurence of a flood in the spillway basins is proposed to be the unsuitable or exorbitanceuse use of lands. One of the flood management solutions is to optimize the land use allocation by considering multiple objectives and parameters. In this ...
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Introduction: One of the most influential factors in the occurence of a flood in the spillway basins is proposed to be the unsuitable or exorbitanceuse use of lands. One of the flood management solutions is to optimize the land use allocation by considering multiple objectives and parameters. In this regard, GIS capabilities could be applied as one of the novel scientific and technical methods along with taking the advantage of Artifcial intelligence capabilities, such as multi-objective genetic algorithm. This research aimed to model the land use allocation in GIS platform using NSGA-II algorithm to monitor flood crisis. Material and methods: In the designed model, using the interruptive method, land’s ecological capability was extracted and then using NSGA-II algorithm capabilities, optimal applications were obtained for various parts of the area in order to decrease the flood height as well as to increase the economic profit with the least difficult change of utilities. In the designed model, the curve number parameter (CN) was used to investigate the role of land use on the flood. Results and discussion: The results of the designed model are represented in several optimal patterns that have the same applicable value. Based on the present conditions of the studied region and the expert’s opinion, the optimal model could be executed. To evaluate the capability of the designed model, the Taleghan basin was selected which is located in Alborz Province; CN range of the study area was 83 in the searching space, while in designed output models, the lowest amount of CN, with 11% decrease compared to the current situation, was about 74.5%. Also, the economic profit growth was 52.19% in this land synthetic pattern. Conclusion: The results and achievements of this study include proposing a land use optimization model based on a multi-objective genetic algorithm for flood reduction, integrated river basin management, as well as programming in an expansive form to use in future studies.
Monireh Mosa Beigi; Fatemeh Mirza Beigi
Volume 14, Issue 4 , January 2017, , Pages 175-188
Abstract
Introduction: Forests are natural resources most of which are destroyed each year by fire. One way to deal with forest fires is to identify the hot spots in forest fires in the region.This phenomenon destroys hectares of trees, shrubs and plants annually, with an annual average of six to fourteen million ...
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Introduction: Forests are natural resources most of which are destroyed each year by fire. One way to deal with forest fires is to identify the hot spots in forest fires in the region.This phenomenon destroys hectares of trees, shrubs and plants annually, with an annual average of six to fourteen million hectares of the world's forests estimated to be damaged by fires. This reveals the need for research in this area in order to preserve this invaluable resource. Manesht and Qalarang Protected Area is located in the northern Province of Ilam, covering Chardaval and Ivan. The research aims to assess the level of fire hazard in this protected area using network analysis and geographic information systems.Materials and Methods: This will apply the most important factors in the process of forest fires according to experts and researchers in these areas, including 9 factors, such as the density of vegetation, rainfall, temperature, slope, aspect, distance from the road, distance from the village height and distance from the river. In the process of modelling for the evaluation of forest fire risk, a sensitivity model network analysis was conducted over three stages and, in this way, the structure of the model was formed in the SuperDecisions software. The matrix of pairwise comparisons was performed using all of 1 to 9 and, then, the super matrix was prepared. Finally, the criteria weighting was determined.Results and Discussion: The results from this study showed that weighting of criteria for density of vegetation, rainfall, temperature, slope, aspect, distance from the road, distance from the village, elevation and distance from the river to the values were 0.294, 0.226, 0.134, 0.121,0.075,0.051, 0.041, 0.29 and 0.025, respectively; hence, density of vegetation, rainfall, temperature and slope had the greatest weight. Finally, by combining the layers according to the weights obtained in ARC GIS software, a zoning map was prepared. The results showed that the top 50% of regions with dense vegetation, southerly directions and slopes greater than 20 percent are prone to fire hazard. The southerly and easterly directions were determined as receiving the maximum amount of sunlight. Approximately 30 square kilometers (10 percent) of the total area of the 62 square-kilometer area were in the very high risk class (20%) in terms of the probability of fire. So it is essential that measures be taken to prevent the occurrence of fire in these areas.Conclusion: In this research, the zoning map was classified in the five classes of very small, low, medium, high and very high. The results showed that, according to maps from the running model, slopes greater than 20 percent, southerly and easterly directions and areas where vegetation density is over 50 percent are among the areas with high and very high risk of likelihood of fires occurring. It is therefore essential that in these areas the necessary measures be taken to prevent the possibility of fire.
