Today, urban and regional issues related to sustainable development is a key challenge for policy-makers, planners and specialists in various disciplines. Geomorphologic studies can be useful and effective in analyzing and deriving acceptable means to assess the growth and development of the city, and to set criteria to determine the directions of urban development. Landslides range of motions not only affect the human structures such as roads, rail lines and residential areas, but also lead to casualties. Tehran metropolis mountainous basins, including Kan, Vesk, Farahzad, Darake, Velenjak, Darband, Golabdare, Darabad, Sorkheh-Hesar, and Sohanak due to the lithology, geologic structure, weathered sediments, steep slope, rainfall and poor urban development are considered as one of the places where landslides are a range of geomorphologic processes can be studied. At this research, using Fuzzy and AHP methods and by the use 8 factor variables such as lithology, elevation, slope, aspect, annual rainfall, maximum daily rainfall, distance from fault and drainage system. the map of landslide zonation hazard in mountainous areas of the city is prepared to determine risky strips. After the standardization of the criteria for the occurrence of landslides and using frequency ratio method and fuzzy model and functions, Landslide hazard zonation maps was prepared for evaluating from the fuzzy sum, fuzzy product and fuzzy gamma operator 0.8 and 0.9. Then the final map of landslide zonation, obtained from the above-mentioned method matched with the map of urban regions in mountainous areas. In this way the constructed region have been distinguished from very high and very low hazard zonation. Lithological studies showed that most of the basin areas covered by Karaj Formation. About 45/7 percent of units with sliding movement in areas with "rock crystal tuff and tuff lytic green, with the layers of limestone" (unit Et2) of the intermediate tuff formation occurred. Cross of faults distance map with landslide density map showed that about 33/1 percent of landslides occurred within 200 m of the fault lines and 78/4 percent of landslides occurred within 500 m of drainage network. Most sliding movements (60/2 percent) in the range of 1900 to 2500 meters altitude and about 35/3 percent of this type of range of motion in height of 1500 to 1900 meters occurred. This area is about 81/6 percent of sliding movements in slopes between 15 and 40 degrees (26/8 to 83/9 percent) and about 17/6 percent on slopes less than 15 degrees (26.8 percent) occurred. In the aspect, sliding movements of the basin, mainly in the south-western slopes (about 23/2 percent), the South (about 17/5 percent), West (about 16/6 percent) and Southeast (about 77/1 percent), northwest (about 33/1 percent) occurred. About 88/9 percent of sliding movements in areas with average annual rainfall of 244 to 280 mm occurred. According to the zoning map, 12 percent of mountainous basins area (approximately 10,057 acres) is in the zone of very high risk, 33 percent (approximately 27,723 acres) is in high risk areas, 20.5 percent (approximately 17,143 acres) in the moderate risk zone, 30/ 7 percent (approximately 25,672 acres) in area and 3.8 percent of the total area of the basin, low risk (approximately 3172 acres) located in low risk areas. The results showed that approximately 5.2 hectares (about 0/05 percent) of the urban in zones with a huge landslide, about 51/5 acre (approximately 1 percent) in zones with high landslide risk and about 821 acres (equivalent to 25/16 percent) in the medium risk landslide zones are located and developed. The final results indicate that some mountainous regions of Tehran Metropolis are apt to landslide with middle to high risk. (Apart from strengthening the vulnerable area) avoiding these areas is an important solution to decrease damages caused by landslide.
Tectonic geomorphology is part of Earth Sciences, which deal with study of the interaction of tectonic and geomorphology. In other words it studies the effective tectonic processes in forming and changing the landforms. Geomorphic and morphometric indicators are suitable tools to the morphotectonic analysis for different areas. These indicators are used as the base tool to identify and recognition of tectonic deformation or estimates of the relative instability of tectonic activity in a particular region. Some of geomorphic indicators has been widely used, then the results of research projects are used to obtain comprehensive information about active tectonics. Full assessment of contemporary tectonics and tectonic activities, especially the young tectonic and its hazards need to Full understanding of geomorphologic processes speed and made for this purpose, geomorphological methods play an important role in this context.
This research uses a descriptive-analytical approach, using library studies and aims at determininge the activity of Neotectonic in 7 Watersheds of Tehran metropolis (from west to east: Kan, Vesk, Farahzad, Darakeh, Velenjak, Darband and Darabad). In the first step, using topographic and geological maps of under the studied area, faults, drainage networks and watersheds are identified, then to evaluation the indicators of Mountain Front sinuosity (Smf), the main river sinuosity (S), the drainage watershed asymmetry (Af), rivers density index (D), hypsometric integral (HI), the ratio of the watershed shape (BS), the ratio of valley floor width to valley height (Vf), river longitudinal gradient index (SL) and Index active Tectonic(IAT) have been determined. Survey of these indicators by topographic and geologic maps and Google Earth images of the under studied area using software of Google Earth, Arc GIS and Global Mapper are derived and calculated. In the following, parameters and how they are calculated are given:
-Mountain Front sinuosity is the result from equation (1):
Smf = Lmf / Ls (1)
In the equation (1), Smf is index of sinuosity Mountain Front. Lmf is the front along the foothills and mountains of the specified slope failure and Ls: straight line along the front of the mountain.
- The main river sinuosity index is as follows: S = C / V. In this formula, S is main river sinuosity. C: along of the river. V: valley along of the straight line.
- Rivers density index, drainage density is obtained from the formula:
µ=
Li is length in kilometers of drainage Watershed, A is area in square kilometers, μ is total drainage watershed in terms of kilometers per square kilometer.
- Hypsometric integral is an indicator which represents the distribution of surface heights variation from equation (2) is obtained:
HI= H - Hmin / H max – H min (2)
In this equation Hi is hypsometric integral, Hmin and Hmax respectively are the minimum and maximum height and H is the height of watershed.
- The ratio of width to height of the valley floor is another geomorphologic parameters to investigate the tectonic forces in the region .This index is obtained from the equation (3):
VF = (3)
VF, represents the relationship of the valley floor width to valley height, VFW: the valley, Eld and Erd to the height of the left and right and Esc is valley floor elevation valley.
- The ratio of the area ratio of the area and the equation (4) is obtained:
BS= Bl / BW (4)
-BS; the shape of the watershed; Bl; length dividers watershed of water to the bottom of the watershed outlet and BW: width of the flat portion of the watershed.
-The longitudinal gradient index (SL) for a range of drainage path is calculated and determined by the relationship: SL = (ΔH / Δ L) * L. In this regard, SL: the longitudinal gradient index, ΔH: height difference between two points measured, ΔL: during the interval and L: total length of the specified channel to assess where the index to the highest point of the canal.
The classification provided for indicators Sl, Smf, Vf, Bs, Af by Homduni et al (2008), this indicator is obtained based on the amount of 1, 2, 3 classified in three classes. Index of active tectonic (Iat) Geomorphic indicators by means of different classes Calculated based on the value of (S /n) is divided into four classes, That the division are characterized by class 1 with very high activity Neotectonic, Class 2 with high Neotectonic activity, Class 3 with medium Neotectonic activities and and Class 4 with low Neotectonic activity. In this classification of Class1 have the highest and Class 3 have the lowest Neotectonic activities (Table11).
On the basis of Iat indicator Neotectonic activities in the under studied area were assessment and results were is in table (13). Based on the data in Table (13) , watersheds of Kan and Darband hava a high Neotectonic activities and located in Class 2 and watersheds of Vesk, Frahzad, Darakeh, Velenjak and Darabad have a medium Neotectonics activities and and located in Class 2, and Neotectonic activities are a high relative tectonic activity in all watersheds. Geomorphic indicators are reflecting activities in the metropolitan Tehran watersheds can say that tectonically active watershed has not yet reached stability and tectonic activity are relatively high. Geomorphologic indicators drainage watershed asymmetry, the main river sinuosity, the valley floor width to height ratio of density of rivers and valleys, structural geology and tectonic activity in the7watersheds of Tehran metropolis better show it.
The results show that Tehran metropolis Watersheds have a high relative tectonic activity in all watersheds, because of the proximity to the major faults (such as Mosha- Fasham and North Tehran faults) and minor faults, tectonic activity exists. Finally it can be stated that, due to the presence of multiple faults and background seismicity and tectonic activity in Tehran metropolis and its watersheds, occurrence of earthquakes in the study area is not unexpected and this issue requires serious consideration and management.
Drought is a concept that is generally understood on a basic level, but is difficult to quantify. Palmer defined a drought as a meteorological phenomenon that is characterized by ‘‘prolonged and abnormal moisture deficiency. A drought can alternatively be broadly defined as a temporary, recurring reduction in the precipitation in an area.
Aridity and drought are not synonymous. Aridity is a measure of long-term average climatic conditions. Both humid and arid regions experience droughts. However, the inter-year variation in precipitation is greater in arid regions and there is a greater probability of below average precipitation in any particular year. Arid regions are thus more prone to droughts and may experience more severe impacts from droughts.
In this research was used temperature and precipitation monthly data of Urmia, Tabriz, saghez, Maragheh, and Mahabad station in statistically period 1985-2014. Run test was used to study the homogeneity of data. Randomness and homogeneity of data was approved.at a confidence level of %95. SEPI Index and ANFIS model was used for determining and forecasting drought in Urmia lake basin. SEPI index is more complete than SPI. Results of SEPI were used in ANFIS model.
Fuzzy index SEPI[1]: Standardized precipitation index and evapotranspiration (SEPI) to address some of the disadvantages of SPI index is provided. Evapotranspiration and precipitation index SPI index and SEI standardized integration is achieved. The index is the result of drought monitoring phase of architectural models using fuzzy logic in a fuzzy inference system is designed. How to design this model and determine SEPI is described below.
Fuzzy architecture drought monitoring: for derivatization indices SPI and SEI using Fuzzy Inference System, Due to the structure of fuzzy models were considered.
SPI index[2]: Standardized Precipitation Index is an indicator widely used in Drought Monitoring. This index is one of the few indicators drought monitoring and could even say the only indicator that the time scale is considered. Depending on the time scale to determine the effect of different sources of agricultural drought, hydrological and so determined. Time scale can be determined from one month to several years. SPI index is used to calculate the only element rainy climate. Monthly precipitation amounts for each station in the desired time scale is calculated.
SEI index[3]: Since the index SPI Single Entry, rain, The SPI index values under the influence of changes in temperature and evapotranspiration parameter that is powerful factor in the drought, it will not be. So to enter the effect of temperature and evapotranspiration in SPI, SEI (evapotranspiration index Standard) To calculate this index, before any measures should reference evapotranspiration for the period to be estimated.
define the rules for combining indicators SPI and SEI: Different classes index SPI and SEI rules or the same combination of conditional statements in the form if, as a class of SEPI index in the lead, is defined. This rule only a combination of different modes SPI and SEI indices that lead to SEPI index shows. In this regard, the rules can be combined to fit different for successive written and stored in the knowledge base. Since the output of the resultant composition, indices SPI and SEI are involved in determining the status of SEPI, Weight each of the indicators with regard to the effect of precipitation and temperature parameters on the severity of the drought was considered As a result, SPI indices and weights 0.667 and 0.333, respectively SEI were included in the calculations.
According to the results, according to the research, education Anfis model with 75 percent of the data series is well done SEPI and much has been done to ensure education is nearly 100 percent. So that the graphic maximum of 0.26 percent error in saghez station on a scale of 6 months and the lowest average error of 0.10 percent in Urmia station is on a scale of 6 months. In modeling, validation data, the average error modeling is naturally higher than the average training error. Most average forecast error saghez on a scale of 6 months at the station 0.34 percent and 0.10 percent, the lowest on a scale of Urmia station is 6 months. But the coding maximum of 0.65 percent error in saghez station on a scale of 6 months and the lowest average error of 0.32 percent in Tabriz station is on a scale of 6 months. SEPI index in the time scale of 6 and 12 months is used for investigate the characteristics of adaptive neuro-fuzzy inference system in order to drought and drought forecasting model. According to the findings in this study, the frequency of drought in the stations of Urmia and Saghez and Maragheh on a scale of 6 months is more than the scale of 12 months in the basin of Lake Urmia but in Tabriz and Mahabad Stations situation is the vice versa. The drought in Urmia Lake basin is increasing trend but temperature has increasing trend with more intensity. The highest and lowest percentage of drought was seen in Urmia and Mahabad station respectively. The results of the forecasting of index by ANFIS model showed that the most training error is in Tabriz station (0.51) and the lowest training error is in Maragheh station (0.36) in a scale of 12 months in coding. In validation data modeling the average of modeling error is higher than the average training error naturally. According to the definition of drought SEPI was presented based on amounts of 0.73 or higher or mild drought to higher floors as dry conditions arise The scale of 6 months in Urmia station with 13.14 percent to 10.89 percent saghez station, Tabriz stations with 5.58 percent, with a 5.1% Mahabad station and Maragheh with the amount of 4.82 percent, the drought has occurred. The time scale of 12 months in Tabriz station by 9%, saghez station with 7.26 percent, with 6.11 percent of Urmia station, Maragheh with 5.5% and the amount of Mahabad stations with a 3.44 percent, from months of study in the series, drought has occurred.
Results of SPEI are:
Results of ANFIS Model are:
In study area and in ANFIS model whatever forecasting coming years is shorter; confidence of forecasting will be more.
Due to the errors amount obtained in model validation, in study area forecasting of drought by ANFIS model was done with confidence 94%.
[1] - The combination of indices SPI (Standardized Precipitation Index) and SEI (evapotranspiration index standard) based on the rules of the Fuzzy Inference System.
[2] - Standardized Precipitation Index
[3] - Standardized Evapotranspiration
Landslide susceptibility mapping is essential for land use planning and decision-making especially in the mountainous areas. The main objective of this study is to produce landslide susceptibility maps (LSM) at Dalahoo basin, Iran using two statistical models such as an index of entropy and Logistic Regression and to compare the obtained results. At the first stage, landslide locations identified by Natural Resources Department of Kermanshah Province is used to prepare of LSM map. Of the 29 lanslides identified, 21 (≈ 70%) locations were used for the landslide susceptibility maps, while the remaining 8 (≈ 30%) cases were used for the model validation. The landslide conditioning factors such as slope degree, slope aspect, altitude, lithology, distance to faults, distance to rivers, distance to roads, land use, and lithology were extracted from the spatial database. Using these factors, landslide susceptibility and weights of each factor were analyzed by index of entropy and Logistic Regression models. Finally, the ROC (receiver operating characteristic) curves for landslide susceptibility maps were drawn and the areas under the curve (AUC) were calculated. The verification results showed that the index of entropy model (AUC = 86.08%) performed slightly better than conditional probability (AUC = 80. 13%) model. The produced susceptibility maps can be useful for general land use planning in the Dalahoo basin, Iran.
Ecologically-based Management Factors and criteria of River-Valleys in Tehran metropolis-Case Study: River-Valleys of Kan
Abstract:
Iran has seasonal rivers because of dry climate, low rainfall and different topography. These river- valleys have main role in forming, genesis, and sustainability of human settlements and provide different ecological services. The main services include beauty, store of green spaces, water supply, reduce and create temperature differences, local air flow and natural ventilation which are part of the functions. Tehran is roughly the same area as 730 square kilometers and its population is 8.7 million people. It is located in51° and 17´ to 51° and 33´ east longitude and 35° and 36´ to 35° and 44´ north latitude. The height of this city is 900 to 1800 meters. The north and north east of this city are located in peculiarity range of the southern part of the middle Alborz. This city includes 7 river valleys to the names Darabad, Golabdareh, Darband, Velenjak, Darakeh, Farahzad and Kan. The ecological role of these river valleys is reduced because of non- ecological axis developmental interventions by urban management and citizens. These interventions have changed river valleys to high risk space of skirt movements and flood. Kan is the most important river valley because of the breadth of the basin and permanent water discharge rate. The part of this river valley has changed to park (Javanmardan) by municipality. The purpose of this research is that to provide factors and criteria of ecosystem based management to organize this river valley.
ANP has been used in this research. To use this method for analyzing factors and criteria of ecosystem based management to organize this river valley, firstly, these factors have been identified by library studies and scrolling. These factors include 4 criteria (natural: 15 sub criteria, social: 3, management: 6, economic: 2). the books, journals, reports, maps, aerial photos, satellite images and internet sites have been studied in library studies. In site studies, some information from library studies have been edited. After that, the findings of these two methods in form of questionnaire called factors and criteria of ecosystem based management to organize Kan River valley, was in charge academics and professionals. They were elected among pundits of urban management science, urban planning, geography and environment in Tehran. At first the number of them was 30 people came to agreement in two process about 4 factors and 18 criteria and determined importance and priority by Delphy method. Findings in Delphy method were analyzed through ANP and SUPER DECISIONS. In this process, firstly, a conceptual model and relation inter and intra clusters and nodes determined. These relations in this process are very important because paired comparison depends on this process. Assumption of equality of effects and similar relations in these factors is illogical because there are the grading of effects and relations in this research. Second, the factors have been compared to each other to create a super matrix based on paired comparison. Generally, in this process decision makers compare two different factors to each other and paired comparisons have grading of between1to9. In double- sided valuation, each factor is used to show initial inverse comparison. Inconsistent rate in paired comparison must be less than 0.1 like AHP. Third initial super matrix is created. It is the weights created from paired comparison and identified the importance of each factor in each cluster. Forth, the weighted super matrix was created. The weights of clusters was calculated in this process to identify the weight of final super matrix. Fifth, limited super matrix was created. The weighted super matrix reached for infinity band each row convergenced to a number and that number was the weight of factor. By this way limited super matrix was reached.
Based on ANP and table 1, management: 46%, natural – ecological: 26% and economic and social factors: 14% are important respectively in ecosystem based management to organize Kan River valley. Based on reached results, inconsistent rate is 0.003 and it shows that the weight is valid and review is not necessary. Among sub criteria in management factor, organizational pattern: 32%, method of management: 23% and policies: 21% are the most important respectively in ecosystem based management to organize Kan River valley. Among sub criteria in natural- ecological factor, flood, domain movements and building and texture of soil are the most important respectively 23%, 18% and 11.5% also in social factor, participation, security and public trust have the importance respectively equal to 49% 31% 19%. In economic factor, environmental assets and stakeholder’s economic participation have the same importance.
Based on this research, management factor (organizational pattern and the method of management) is the most important in ecosystem based management. But this approach, the management pattern and intervention to organize this river valley, need comprehensiveness and integrity of the subject (nature, society, management and economic), purpose (protection, resuscitation and use), factors (government, city council, municipality, private sector and people), duties (policy making, planning, designing and perform), method (collaborative), tools (knowledge, skill, rule, program, budget, machinery and materials) and management domain. Use of these factors and criteria need some infrastructure and reforms. The most important reform is reform of management structure, production of subject matter and topical program special to organize river valleys by ecological approach to release Kan of loading and contradictory grabbing.so this management can follow protection, resuscitation, sustainable use and continuity of ecological services.
Key words: ecosystem, ecosystem based management, analytic network process, river valley of Kan
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