ادغام مدل های تصمیم گیری چندمعیاره و تکنیک تجزیه‌وتحلیل منطقه ای سیلاب جهت اولویت بندی زیرحوزه ها برای کنترل سیل (مطالعه موردی: حوزه آبخیز دهبار خراسان)

امروزه یکی از مسائل مهم در پروژه های مهار سیلاب کشور، اولویت بندی حوزه ها برای تخصیص بودجه و عملیات سازه ای و غیرسازه ای است. با توجه به فقدان ایستگاه های هیدرومتری در بسیاری از زیرحوزه ها، تعیین میزان مشارکت زیرحوزه های مختلف یک حوزه آبخیز در ایجاد سیلاب را با مشکل مواجه می کند. بررسی پارامترهای موثر در بروز سیل از طریق رویکردهای تصمیم گیری چندمعیاره (mcdm) می تواند در تعیین نقش هر یک از زیرحوزه ها در بروز سیلاب راهگشا باشد. منطقه مورد مطالعه پژوهش حاضر (حوزه آبخیز دهبار در استان خراسان رضوی) به 10 زیرحوزه تقسیم شد. سپس 13 شاخص و معیار شامل مساحت، ضریب گراولیوس، تراکم زهکشی، ضریب گردی، ضریب فرم، شماره منحنی، نسبت انشعاب، طول آبراهه اصلی، شیب متوسط، ارتفاع متوسط، زمان تمرکز، بارندگی و ضریب رواناب انتخاب شدند و مقدار هرکدام برای هر زیرحوزه محاسبه گردید. وزن دهی این پارامترها با تکنیک فرآیند تحلیل سلسله مراتبی (ahp) انجام گردید. پس از وزن دهی به معیارهای ارزیابی و تهیه ماتریس تصمیم گیری، جهت اولویت بندی از مدل های vikor و permutation استفاده گردید. بعد از اولویت بندی، جهت ارزیابی و صحت سنجی این مدل ها از روش تجزیه‌وتحلیل منطقه ای سیلاب (براساس ایستگاه های موجود در حوزه) استفاده شد و دبی حداکثر سیلاب در دوره بازگشت های مختلف محاسبه گردید. درنهایت برون‌داد این سه روش با استفاده از روش میانگین رتبه ها ادغام گردید. نتایج نشان داد که زیرحوزه های شماره 1، شماره 3 و شماره 2 در رتبه‌های نخست قرار دارند و درنتیجه ازلحاظ ضرورت انجام اقدامات مدیریتی در اولویت هستند.

Combination of Multicriteria Decisionmaking Models and Regional Flood Analysis Technique to Prioritize Subwatersheds for Flood Control (Case study: Dehbar Watershed of Khorasan)

1 Introduction;The flood is one of the most important natural disasters, which is causing significant damage to affected areas. In flood management process, the factors which effectively responsible in flood formation are identified, and then areas with high potential for flood occurrence are identified. Because of the vast extent of catchment areas and the limited economic and administrative resources, the implementation of flood control projects in all floodproducing areas is not feasible. Therefore, prioritizing subwatersheds is one of the chief measures for sustainable management of watersheds, with the purpose of controlling the flood. Multicriteria decisionmaking (MCDM) methods such as the analytic hierarchy process (AHP) method and the analytic network process (ANP) are the techniques for identifying the areas with high floodproducing potential.;Since soil properties, infiltration rate, and quantitative geomorphological characteristics determine the amount of excess rainfall and runoff production, thus, the simultaneous application of morphometric analysis method and decision making models is very useful in the areas  with  data  scarcity. In morphometric analysis, the physiographic and morphological characteristics of the watershed are analyzed based on the digital elevation model and finally the subwatersheds are prioritized. Dividing large areas into multiple subwatersheds and prioritizing these subwatersheds reduce the time and cost of running watershed operations as well as making watershed projects more efficient.;The purpose of this study was to determine the subwatersheds with critical conditions in  terms  of  flooding  risk  in Dehbar watershed, Khorasane Razavi Province, Iran to reduce the costs of carrying out the watershed management projects focusing on flood control. It is worth noting that due to the lack of required data, morphometric and hydrologic analysis methods were used. In order to prioritize the subwatersheds of Dehbar watershed, multicriteria decisionmaking methods including AHP, VIKOR, and Permutation were employed. Afterwards, the results of these models were compared and verified by regional flood analysis method.;2 Materials and Methods;The study area was Dehbar watershed located in Torqabeh and Shandiz County, Khorasane Razavi Province, Iran. The area of the Dehbar watershed was estimated to be 115.73 km2. In order to better identify and evaluate runoff production capabilities, the watershed is divided into smaller hydrological units that have been separately investigated. This classification was made based on the location of the water resources, the location of the villages, the hydrographic network, the topographic contour lines, the satellite imagery, the field visit, and the integrative view in the GIS system, so that through the use of the  ArcHydro  extension  in ArcMap, the Dehbar watershed was divided into 6 hydrologic and 4 nonhydrologic subwatersheds.;The Dehbar watershed was divided into 10 subwatersheds. In the current study, 13 evaluation criteria including area, compactness coefficient, drainage density, circularity  factor, form factor, curve number, bifurcation ratio, main channel length, average slope, average height, time of concentration, rainfall and runoff coefficient were selected, and the amount of each for each subwatershed was calculated. The weight of parameters was derived by the AHP technique. After determining the weights of the evaluation criteria and the preparation of decision matrix, VIKOR and Permutation models were employed for prioritization. After prioritizing, the regional flood analysis method (based on existing stations in the watershed) was used to compute maximum flood discharge in different return periods in order to evaluate and validate the considered models.;To this end, a homogeneous area with hydrometric stations was first identified based on geographical and climatic conditions within the region of the study area. The outliers were then eliminated and the frequency analysis was performed for each station individually and the  bestfit statistical distribution was identified and selected. Finally, for regional flood analysis, a regression relation was acquired between peak discharges and contributing area in adjacent catchments; thus, it is possible to estimate peak discharge in the study area.;Finally, the outcomes of three employed multi criteria decision making methods were combined using the average rating method.;3 Results and Discussion;Pairwise comparisons between considered criteria were performed based on AHP method and the relative weight of each criterion was obtained. Runoff coefficient with the relative weight of 0.221 had the highest importance among the considered criteria. Subsequently, rainfall criterion, time of concentration criterion, and curve number criterion were in the following ranks with the relative weights of 0.148, 0.116 and 0.109, respectively. The criteria of average elevation and form factor also had the lowest relative weights. Meanwhile, the inconsistency rate in AHP method was 0.04, indicating that the decision making process is consistent.;After determining the relative weights of each criterion for each subwatershed, the VIKOR model was applied. According to this method, subwatershed No.1 ranked first with Q index of 0.9715, subwatershed No.3 ranked second with Q index of 0.8739, and subwatershed No. 2 ranked third with Q index of 0.6030. Therefore, these subwatersheds  should  gain  high  priority in watershed and flood control operations. Meanwhile, subwatershed No. 7 with Q index of 0.0312, subwatershed No. 10 with Q index of 0.0950 and subwatershed No. 9 with Q index of 0.3132 were in tenth, ninth and eighth priority, respectively. Thus, these subwatersheds had the lowest priority for implementing watershed management activities.;In the next step, the Permutation model was employed. According to the results of this model, subwatersheds No. 1, No. 3 and No. 2 were ranked first to third, respectively. This is due to the high amount of rainfall, runoff coefficient and curve number in these subwatersheds. Meanwhile, subwatersheds 5, 8 and 10 were in the lowest ranks.;In addition, the results of regional flood analysis showed that subwatersheds 1, 3, 8 and 2 had higher flood peak discharge, respectively. Meanwhile, subwatersheds 5, 10, 4 and 9 had lower flood peak discharge and were in the last priority in terms of potential for flood generation.;In the final step, in order to provide a proper ranking for subwatersheds, we used the average rating method to combine the obtained priorities by three different applied techniques. The outcomes showed that subwatersheds No. 1, No. 3, and No. 2 were in the first rank, and therefore, in terms of the need for watershed management measures were in the top priority.;4 Conclusion;The results of this study showed that the derived priority of the subwatersheds using morphometric and hydrological parameters as evaluation criteria to identify floodproducing  areas is a suitable and appropriate method. Therefore, it is recommended that, in order to reduce costs and gain optimal outcomes, watershed management projects focusing on flood control should be implemented in the identified subwatersheds which are in top priority in terms of generating flood discharge. The outcomes also showed that one or two factors alone could not determine the priority of floodproducing  capability of subwatersheds and a subwatershed with a larger area does not necessarily have the higher potential for generating flood, but the interaction of different factors ultimately determines the priority of the subwatershed in terms of floodproducing  potential.;