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Research and Full Length Article: Site Selection for Rainwater Harvesting for Wildlife using Multi-Criteria Evaluation (MCE) Technique and GIS in the ,

Masoud Jafari ShalamzariA*, Atefeh GholamiB, Shahram Khalighi SigaroudiC, Afshin Alizadeh ShabaniD, Hosein ArzaniE A PhD, Attended University of Agriculture and Natural Resources, Gorgan, Iran, *(Corresponding Author), email: [email protected] B PhD Candidate, University of Agriculture and Natural Resources, Gorgan, Iran, C Associate Professor, Watershed Management, University of D Associate Professor, Wildlife Ecology- Landscape Ecology, University of Tehran, Iran E Professor, Range Management, University of Tehran, Iran

Received on: 17/01/2017 Accepted on: 17/06/2017

Abstract. This research is an integration of GIS and multi-criteria decision making into a joint framework for identifying suitable areas for rainwater harvesting structures. The Kavir National park in Iran has been evaluated for suitability of rainwater harvesting. To this end, slope gradient, distance to guarding stations, distance to watering points for transporting collected water, distribution of wildlife species of interest, access to roads, evaporation, elevation, water scarcity index, and annual precipitation during rainy season were incorporated. Data collection and field visits took place during 2014-2015. Rainwater harvesting in this area is primarily intended for Ovis orientalis, Gazella dorcas and Acinonyx jubatus known as Persian Cheetah. The primary layers were standardized using a proper Fuzzy Membership Function, which assigns a weight between 0 and 1 to each layer, to include the inherent tradeoff between data layers in producing the final suitability map. The results suggested that precipitation and water scarcity (each by the relative weights of 0.3 and 0.2, respectively) were the most influential factors. The northern foothills of the Mount Siahkouh have shown to hold the highest suitability for rainwater harvesting. The suitability changes from lower than 100 to the east to higher than 200 to the west. The result of this study might be used to guide future endeavors for rainwater harvesting for wildlife on the ground. The methodology adopted here could be replicated in other studies with respect to its simplicity and practicality. This is recommended to run pilot small-scale rainwater harvesting practices and receive the outcomes and then, in case of a positive feedback, extend its application to other areas identified in this research.

Key words: Rehabilitation, MCE, Wildlife, Water Development, Kavir National Park, GIS

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Introduction and consuming considerable amounts of Water is the vital element of life (Matlock, water could result in both water quality 1981). However, water supplies in arid and deterioration and shortage in places mostly semi-arid areas are often scarce, and highly needed for wildlife. Wurtsbaugh et al. variable and of inferior quality (Goodall et (2016) reported on the attempts to revive al., 2009). Climate changes have resulted the Salt Lake in the USA, which in an increased number of drought events previously started to move towards and greater intensities (Nabhan, 2013). The desiccation. They believe that agriculture situation is compounded by human by consuming 63% of the resources interventions and mismanagement of water feeding the lake was the one to blame for resources (Foltz, 2002). the lowering levels of the Salt Lake, and Water is an essential component of the possible future issues. Beside water wildlife habitat. It attracts a wonderful utilization, human intervention through variety of wildlife from songbirds to small water governance could also lead to water mammals, reptiles, amphibians and scarcity for wildlife. For instance, beneficial insects (Dodson, 2000). Huntsinger et al. (2017) argue that strict Availability of water largely determines water governance could cause the the distribution and abundance of animals unintended consequences for biodiversity in arid and semi-arid environments, and environmental quality. They believe influencing the carrying capacity of that measures considered to increase water protected areas (Wolff, 2001). Lack of price and prevent water leakage have water prevents wildlife from reaching its resulted in water shortage for California optimum population within the habitat Black Rail (Laterallus jamaicensis (Deal, 2010) and will definitely result in an coturniculus). uneven utilization of habitat’s resources if Water development for wildlife is not preventing all (Bone et al., 1992). As increasingly gaining favor during the an extra burden, human use of nature has recent decades, yet in some cases without a narrowed down the field not only for sense of realism (Matlock, 1981). Where human itself, but also for wildlife to meet water is lacking but other habitat essentials its demands. Human utilizes nature are available to benefit wildlife, water may indiscriminately while neglecting the be developed using artificial or natural others' rights to live. Consuming surface means or by a combination thereof and underground water reservoirs from (Brigham and Stevenson, 2003). Tavasoli wells and dams has limited water et al. (2016) investigated a number of accessibility for wildlife. As a good case in islands in the , Iran and point, Daniali et al. (2009) evaluated the proposed rainwater harvesting through role of illegal water extraction from rock catchments and subsurface barriers as springs and wells on wildlife in the the good practices for providing water for Ghamishloo National Park, Iran and wildlife. Artificial or modified water reported fragmentation and loss of wildlife sources (i.e., catchments) are widely used of the area. On the other hand, human for wildlife management in the arid intervention in nature such as constructing western United States, where thousands of roads and utility lines has resulted in the such catchments have been built to fragmentation of wildlife habitats, enhance wildlife populations and disappearance of animal corridors, and less compensate for the loss of natural water reproduction rates (Leslie and Douglas, sources (Krausman et al., 2006; Harrison, 1980). Batool and Hussain (2016) believe 2016; Kluever et al., 2016; Kluever and that agriculture and urban expansion are Gese, 2016). In spite of the existence of the main causes of water pollution and some controversy around water scarcity for wildlife. Releasing nutrients development for wildlife, most studies

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testify the acceptance of these watering runoff towards a tank – usually 8.5 m3 in sources from different wildlife species volume, or an adjacent location to be fed to (Dolan, 2006; Bone et al., 1992; Manning the water trough via a floating switch and Edge, 2001; Kluever et al., 2016) ). (Kinkade-Levario, 2013). There are not many options before the Many spatial decision-making managers to decide how to provide wildlife problems such as site selection for water water demand. Inter alia, rain harvesting, guzzlers in this case require the decision- dew and fog harvesting, solar distillation maker to consider the impacts of difference and pumping, wind pumps, rock factors and multiple dimensions (Fisher, catchments and small surface and sub- 2006; Forzieri et al., 2008). This process surface dams may be regarded as the could be aided by the application of the possible ways to overcome the situation Multi-Criteria Decision Support Systems while satisfying both economic and (MCDS). ecological conditions (Burkett and Site selection is a generic term noticing Thompson, 1994; Halloran and Deming, the process of finding locations or features 1958; Jafari Shalamzari et al., 2015). meeting specified conditions. For various Rainwater harvesting in its broadest purposes, it is often expressed as site sense can be defined as the collection of suitability. Site suitability is the process of rainwater run-off for domestic water finding the most suitable location(s) for a supply, agriculture and environmental particular purpose (Davis, 2001). One management (Worm, 2006). Rainwater major drawback of spatial multi-criteria harvesting has proven to be a good, low- decision making methods is their required cost, and simple water supply technology time. GIS enables the managers to for domestic, agricultural and implement these types of analysis in a environmental purposes (UNEP, 2003). timely manner as it can analyze the spatial Rain water harvesting (hereafter referred to data which may be available from various as RWH) is an attractive option because sources in an integrated and graphical way the water source is near and convenient (Ray and Acharya, 2004). and requires minimum energy to collect. Far too little attention has been paid to However, the main disadvantage of RWH site selection for rainwater harvesting is that one can never be sure how much structures especially for wildlife water rain will fall (Worm, 2006). provision. There remains a paucity of Though rain falls infrequently in arid evidence on the successful application of lands, it comprises considerable amount of multi-criteria decision making analysis in water; 10 mm of rain equals 100,000 L of this context. Thus, this study set out to water per ha. Harvesting this can provide determine the most suitable sites to plan water for regions where other sources are structures for artificial RWH systems for too distant or too costly to collect, or wildlife in an arid area inside Iran. Here, where wells are impractical because of Rainwater harvesting as a permanent unfavorable geology or excessive drilling resource could provide enough water for costs (National Research Council, 1974). the wildlife of the area. Using a simple Human-made rainwater harvesting systems water budget, water deficit is determined are collectively known as guzzlers. These and a remote attempt to locate suitable are mobile structures that can be relocated places for RWH is carried out. This study if needed, and can help to re-establish considers the application of a joint venture wildlife that has previously left because of of GIS, field works and multi-criteria water scarcity and drought. Guzzlers decision making. include a solid roof-like structure, a tank and a float switch, and gravity feed. Roof- like structure is a tilted plain which directs

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Materials and Methods of Iran. The park is already lacking in Study area water resources for wildlife. A large Located south of Tehran city, Kavir proportion of the area is flat with scarce National Park comprises an area exceeding topographic outcrops like SiahKouh in the 6810 km2. The outer limits are located west and some negligible elevations in the between 51o25’10’’ to 53o03’05’’eastern east. The dominant wildlife species of the longitudes and 34o17’15’’ to 35o12’30’’ park include Ovis orientalis (with body northern latitudes. Based on the statistics weight between 25-85 Kg), Gazella dorcas provided by the Semnan Weather (with body weight between 15-25 Kg) and Organization, precipitation mainly Acinonyx jubatus (with body weight occurring during winter in the Kavir between 20-72 Kg) known as Persian National Park reaches up to merely 100 Cheetah (Semnan Department of mm. Hot and harsh summers and bitterly Environment, 2005). The sketch of the area cold winters are typical of the central parts is illustrated in Fig. 1.

Fig. 1. Location of the study area related to the Kavir National Park’s and Iran’s boundary

Wildlife and water shortage in the obtaining food change. In summer, gazelle area dig holes in the sand to feed on stems and According to the latest statistics of the bulbs. After winter rains, they eat fresh Semnan Department of Environment sprouted leaves (Lawes and Nanni, 1993). (direct interviews), Kavir National Park is They are tolerable animals and can endure the home to 13 cheetahs, 900 Gazella high temperatures and water scarcity. dorcas and 2100 Ovis orientalis. Gazelles Gazella dorcas drinks water as much as are diurnal, mostly active at dawn and 10% of its body weight (depending on the dusk. They may become nocturnal under body condition and temperature) or 2.5 pressure from diurnal predators. Gazelles liters per day. This animal can get as far as feed on Gramineae and Zygophyllum 5.6 Km from its water sources (according to direct observations). (Mendelssohn et al., 1995). bighorn Depending on the season, methods for sheep )Ovis orientalis) are mainly diurnal

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and spend most of their day foraging. They Multi-criteria Decision Making presumably feed on grasses and shrubs and Decisions about the allocation of land prefer steep to undulating grassy terrain. typically involve the evaluation of multiple Their lifespan ranges between 8-12 years criteria according to several, often (Valdez et al., 1982). These sheep require conflicting, objectives. With the advent of a minimum of 3–4% of their body mass in GIS, we now have the opportunity for a water/day and drink water for at least 2-3 more explicitly reasoned environmental minutes at a rate of 2.8 liter per minute decision making process (Eastman et al., (Bashari and Hemami, 2013). During 1995). Consideration of different choices summer, drinking occurs at dawn and or courses of action becomes a multiple dusk. These sheep can walk as long as 3.2 criteria decision making (MCDM) problem km from water sources (Dolan, 2006). when there may exist such standards which Acinonyx jubatus preferred habitats conflict to a substantial extent (Belton and including grassland and (Caro, Stewart, 2002). There are two categories 1994). They live approximately 6-8 years within MCDM, namely, multiple objective and maintain a territory. They have a decision making (MODM), and multiple carnivorous diet, of which a large portion attribute decision making (MADM often includes gazelles and obtain water from referred to as multi-criteria evaluation their prey or by concentrating urine. (MCE)). MODM refers to select the best Water shortage in the area is more alternative subject to certain constraints. acute during dry period covering June MADM is applied to the problem of through October which is totally 150 days. selecting the best alternative among a set As a rough estimate during hot season in of finite alternatives (Herath and Prato, which water is scarce, these animals are in 2006). In this paper, a raster-based MCE is demand of 1867.5 m3 water. Based on the applied to identify suitable areas for using discharge of all springs, fresh water rainwater harvesting. There are two distribution in whole area was interpolated fundamental classes of multi-criteria using Inverse Distance Weighting evaluation methods in GIS: the Boolean Interpolation Technique (known as the overlay operation (non-compensatory IDW technique). The IDW is a method for combination rules) and the weighted linear multivariate interpolation with a known combination (WLC) method scattered set of points. The assigned values (compensatory combination rules) to unknown points are calculated with a (Malczewski, 2006b). The approach weighted average of the values available at adopted in this paper is based on the the known points see (Vieux, 2004). The combination of standardized and weighted resulting raster layer was divided by the raster layers based on the weighted linear total water demand for wildlife to produce combination in Arc GIS 10.2. The the water scarcity layer. weighted overlay function, embodied in the Arc GIS toolbox, enabled the eq. 1 combination of layers. The distribution of wildlife species as a Boolean layer was Where: superimposed on the final suitability map WSI= the water scarcity index to exclude the areas outside the animal TDW= the total discharged water presence’s boundary. during the warmest months, and WD= the water demand for wildlife Standardization of Criteria Maps during the same period, which is calculated First step in using MCE method is to based on the number of animals multiplied define a set of decision criteria in line with the daily water requirement times the decision maker’s objectives. Next, one duration of period. needs to develop a suitable GIS database

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for the layers (Salim, 2011). To be able to applying weights on the layers and utilize criteria and their spatial summing the results to yield a suitability representation, they should be associated map as given in Eq. 2: with a common scale of measurement. The process of translating the various inputs of eq. 2 a decision problem to a common scale to Where: allow for comparison, analysis and synthesis is termed standardization S= suitability score, i th (Voogd, 1983). Among different W = the weights of factor for the i standardization schemes, the Fuzzy factor and i Membership function was used to X = the score for the certain factor. transform the input data to a 0 to 256 scale. The whole process is described in A value of 256 indicates full membership Fig. 2. in the fuzzy set while membership decreasing to 0 indicates that it is not a Site Selection Criteria member of the fuzzy set 1. Different studies have used various criteria for rain water harvesting. Weerasinghe et Definition of WLC al. (2011) believe that elevation, soil Weighted linear combination (WLC) depth, soil type, land use and land cover together with the analytic hierarchy are determinant factors for RWH. Rishab process (AHP) has been widely used for and Khitoiiya (2006) in a review proposed different spatial analyses (Chandio and Bin rainfall volume and intensity, vegetation Matori, 2011, Malczewski, 2006a, cover percent, land use, slope gradient and Gorsevski et al., 2012, Şener et al., 2010). length, evaporation rate, soil type, socio- In this theme, different data layers are economic factors and ecologic combined linearly with the assigned consequences of action as the influential weights attached to them denoting the factors for RWH site selection. Mbilinyi et priority of one layer in determining final al. (2007) reported that precipitation decision to define appropriate sites for volume, soil texture and depth, slope, land making use of rainwater (Mbilinyi et al., use and cover and drainage network have 2007). The assigned weights were to be included for a RWH site selection calculated on the basis of the AHP method study. In this study, slope gradient, firstly proposed by Saaty (1980). The AHP distance to guarding stations, distance to decision making technique uses weights on watering points for transporting collected a continuous scale from 1-9 or equally water, distribution of species of interest, important to absolutely most important. access to roads, evaporation, elevation, Relative influence of each raster layer was water scarcity index, and annual determined with the aid of questionnaires precipitation during rainy season were distributed among managers and experts of incorporated to locate the suitable areas for wildlife management. the installation of water guzzlers. Slope WLC procedure allows full tradeoff gradient was calculated in percentage from among all factors. The amount any single the digital elevation model and fuzzified factor can compensate for another is, using the MSmall fuzzy membership however, determined by its factor weight function (FMF) where higher slopes (the (Eastman, 2003). WLC is on the basis of steep slopes of the Siahkouh Mountain and the eastern elevations of the area) becomes increasingly unsuitable for RWH 1 Adopted from the ArcGis 10.3 manual available at: structures, either for the installation of http://desktop.arcgis.com/en/arcmap/10.3/tools/spat equipment or inaccessibility of the areas. ial-analyst-toolbox/how-fuzzy-membership- During the field visits, the location of works.htm

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guarding stations were recorded via GPS adopted for data standardization. As there and introduced into the Arc GIS. This layer is no weather stations in the area, was then converted to a Euclidean distance precipitation layer was prepared based on map where farther areas are considered the established relationship with elevation. less suitable. This was carried out via the This layer was standardized using MLarge Small FMF. The data on access roads were membership functions. Water scarcity acquired from the Natural Conservation layer (as previously explained) was Service in Semnan Province and converted standardized so that the areas with higher to a distance map using a similar approach. scarcity values receive higher priority. This Data on watering points (wells, springs, layer was standardized using Small FMF. and water troughs) were acquired from the Distribution of wildlife species was Natural Conservation Service and then determined during the field visits and similarly converted to a distance map. improved by the incorporation of the Evaporation was measured from the data opinions of the guards. This layer was available for the evaporation gauging converted into a layer of 0 and 1 to be stations and converted to an interpolated further applied on the final suitability map surface using the Kriging technique. as the limiting factor. The final suitability Higher evaporation levels are considered formula has been obtained as following unsuitable as it would result in the loss of (eq. 3): stored water. Thus, an MSmall FMF was

FS=(0.1×DG+0.05×Evap+0.05×DR+0.1×Sl+0.3×Precp+0.2×WS+0.1×DWS+0.1×Elev)×WDM eq. 3

Where: DG= distance to guarding posts (m), Evap = evaporation (mm), Dr =distance to roads, Sl =slope (%), Prec =precipitation during the wet season (mm), WS =water scarcity, DWS =distance to watering points (m), Elev =elevation (m), and WDM =wildlife distribution layer.

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Fig. 2. Flow chart for identification of potential sites for RWH systems for wildlife

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Results provided in Fig. 4 illustrates a range of The final suitability map was the result of 90-181 for the total suitability within the the integration of nine data layers boundary of wildlife distribution. As including slope gradient, elevation, illustrated, highly suitable areas evaporation, distance to roads, distance to correspond to the foothills of the Mount watering points, distance to guarding Siahkouh and the mountain ranges posts, distribution of water scarcity, towards the east of the area. Yet, neither precipitation, and wildlife distribution. elevation nor slope gradient resulted in The values of each map were ranked on a the limitation of RWH installation. It continuous fuzzy scale of not suitable (0) seems that the final suitability map has to highly suitable (256), and a relative been mainly the product of the annual weight was then assigned to each layer. precipitation and water scarcity. There is The corresponding fuzzified maps are a general increasing trend in water provided in Fig. 3. scarcity from the eastern parts towards c Based on the results of the AHP the western areas. This trend, however, is method (calculated according to the not observable for precipitation as it results of the questionnaires filled by the mainly depends on elevation. Less experts in the fields of hydrology, distance to roads, watering points and wildlife management, climatology, and guarding posts also contributed to high watershed management), 0.3 of the total suitability values in the western parts. weight was assigned to precipitation, 0.2 The eastern to north-eastern areas have to water scarcity, 0.1 to distance to obtained lower suitability values that are watering sources, 0.1 to elevation, 0.1 to the result of a combination of factors, slope gradient, 0.1 to distance to guarding mainly less access to roads, guarding posts, 0.05 to distance to roads, and 0.05 posts, water scarcity and watering to evaporation. Based on the WLC sources. Evaporation also appeared to method, layers were integrated based on have the least effect on the final their weight to produce the final suitability. suitability map. The final map which is

(A) (B)

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(C) (D)

(E) (F)

(G) (H)

(I) (J)

Fig. 3. Factor layers for the determination of suitable areas for RWH structures, A: wildlife presence in Boolean (limiting factor); B: water distribution fuzzified; C: temperature fuzzified (evaporation was subsequently used as a proxy of temperature and water loss); D: slope gradient fuzzified; E: distance to guarding posts fuzzified; F: precipitation fuzzified; G: evaporation fuzzified; H: elevation fuzzified; I: distance to watering sources fuzzified; J: distance to roads fuzzified.

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Fig. 4. Map of potential sites for RWH structures in the Kavir National Park

Discussion precipitation events include erratic and The integration of GIS and decision high-intensity rainfalls with heavily support systems in this paper has been biased spatial distribution which successful in the identification of suitable significantly reduces the total suitability areas for the installation of RWH due to its high weight (Amarasinghe and structures. The methodology applied in Sharma, 2007). An innovative criterion this paper has prioritized the large extent was used in this study to prioritize the of the Kavir National Park (larger than areas. This factor, which is formed by 6810 km2) in a quick and efficient dividing the total water available by the manner. This paper is unique in total water demand during the period of combining GIS and MCDM techniques interest, was ranked as the second for site selection for wildlife water important determiner of RWH suitability development. We believe that GIS can be (by the weight of 0.2). The results very useful in water development and suggested that water scarcity is ruling conservation planning (Nikolakaki, 2004; mostly in the western part of the region. Singh et al., 2017). Of total area, 3697 km2 falls into water Nine thematic maps were used to scare category and is in need of providing produce the final suitability including fresh water for wildlife. Evaporation is slope gradient, elevation, evaporation, also believed to affect the suitability for distance to roads, distance to watering RWH (see the studies by Li and Gong points, distance to guarding posts, (2002), Farreny et al. (2011) and distribution of water scarcity, Mahmoud (2014) for more information precipitation, and wildlife distribution. on the importance of considering the loss Precipitation in the area ranges from 100 of stored water). Evaporation increases to 270 mm with the highest precipitation from 830mm in the west and falling in the Mount Siahkouh area. southwestern areas to more than 1100 Almost all of the precipitation in the area mm in the eastern and north-eastern parts occurs from December to May. The of the Kavir National Park. Areas with

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less evaporation were assigned higher percolation tanks and 33 sites for check priority for RWH during the dams. Sayl et al. (2016) used an RS-GIS- standardization process. One important based method to identify potential areas criterion was suggested by Malesu (2007) for RWH. Adham et al. (2016) also as the ratio of P/ETP of 60% for suitable employed GIS and MCDM to identify areas for rainwater harvesting. Yet, no suitable sites for traditional runoff part of the area was found to be satisfying harvesting structures such as Tabia and the criterion. However, high-intensity Jesst. They finally found 58 potential rainfalls could compensate for the gap sites for developing RWH structures. between precipitation and evaporation in However, to the time of writing this the area up to an extent. Mbilinyi et article, our attempts to find similar al.(2007), Malesu (2007) and Mahmoud studies for wildlife water development (2014) have suggested the slopes of less were futile. than 30% as the suitable areas for The major recommendation arising rainwater and runoff harvesting. Except from this article is that GIS and MCDM for the minor elevations, more than 80 techniques, when integrated, are powerful percent of the area is flat with slopes less tools at the disposal of managers to than 30%, and this factor poses no produce suitability maps for water limitation on the final suitability. harvesting projects. Yet, the application Distance to roads, guarding posts, and of this technique and the possible watering points also did not seem to pose consequences of artificial rainwater any limitation, except for some areas in development for wildlife are the two the north-eastern parts of the Park. The major areas needing further studies. findings of this study suggested that Sharing water resources between wildlife suitability for RWH mainly follow the species and local livestock could result in general trend of precipitation and water the transmission of diseases, and care scarcity, and other constituents are of less must be taken to avoid the unintended importance to the final results. Most results (Carrasco-Garcia et al., 2016). suitable areas are concentrated in the The chance for the hunters (both western part of the Kavir National Park carnivores and humans) increases as the where suitable precipitation and higher result of wildlife crowding near artificial water scarcity have provided the water sources (Ndaimani et al., 2016). condition for RWH for wildlife. Thus, the implementation of RWH Providing information on the spatial techniques must be considered with distribution of RWH suitability is a vital utmost care, and it is recommended not to step for promoting rain harvesting rely solely on the results of site selection. technologies (De Winnaar et al., 2007). Other important measures include socio- This study benefits from using an economic aspects of water harvesting, integration of the MCDM techniques and hygiene aspects of water storage and GIS for finding suitable areas for conveyance, cost to benefit ratios, etc. rainwater harvesting for wildlife. Although the approach employed here is Acknowledgement not unique, the application for wildlife We owe debts of gratitude to Majid water development is distinctive in this Ghandali, staff of Environmental regard. There are ample research articles Protection Organization, without whom, related to the application of GIS and this study couldn’t have reached its MCDMS for RWH. Singh et al. (2017) purpose. We hereby appreciate used the same approach to identify areas Department of the Arid and Mountainous for rainwater harvesting and artificial Areas, University of Tehran for its recharge. They found 69 suitable sites for provisions and helps.

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مکانیابی استحصال آب باران برای حیات وحش با استفاده از روش آنالیز چند معیاره و سامانه اطالعات جغرافیایی در پارک ملی کویر

مسعود جعفری شلمزاری ،الف* عاطفه غالمیب، شهرام خلیقی سیگارودیج، افشین علیزاده شعبانید، حسین ارزانیه الف دانش آموختهی دکتری بیابانزدایی دانشگاه علوم کشاورزی و منابع طبیعی گرگان )نویسنده مسئول(، ایمیل: [email protected] ب دانشجوی دکتری بیابانزدایی دانشگاه علوم کشاورزی و منابع طبیعی گرگان ج دانشیار دانشکده منابع طبیعی دانشگاه تهران د استادیار دانشکده منابع طبیعی دانشگاه تهران ه استاد تمام دانشکده منابع طبیعی دانشگاه تهران

تاریخ دریافت: 5931/57/68 تاریخ پذیرش: 5932/79/60

چکیده. این مطالعه به ترکیب دو رویکرد چند معیاره و سیستم پشتیبان تصمیم برای شناسایی مناطق مناسب برای گردآوری آب باران میپردازد. برای این هدف، شیب، بازه تا ایستگاه نگهبانی، بازه تا آبشخور برای انتقال آب انبار شده، پراکنش گونههای حیات وحش مورد نظر، دسترسی به جاده، بلندی، شناسه کمبود آب، و میزان بارش ساالنه در فصل بارندگی برای شناسایی این مناطق استفاده شدند. گردآوری دادهها و بازدید میدانی در سالهای 5939-5931 در منطقه پارک ملی کویر انجام شد. شایستگی منطقه از نظر گردآوری باران برای سه گونه جانوری Gazella dorcas ،Ovis orientalis و Acinonyx jubatus )یوز ایرانی( مورد بررسی قرار گرفت. الیههای ابتدایی با استفاده از تابع فازی بهنجار سازی شده و وزنی بین صفر و یک به هر الیه داده شده تا به توان میزان اهمیت هر شناسه را مشخص کرد. یافتههای این پژوهش نشان داد که بارش و کمبود آب )هرکدام با وزن 9/7 و 6/7( اثر گذارترین شناسهها بودند. دامنه شمالی سیاهکوه بیشترین شایستگی برای گردآوری باران را داشت. تغییر شایستگی از 577 در شرق تا 677 در غرب متغییر بود. یافتههای این پژوهش را میتوان در برنامهریزی برای اجرایی ساختن گردآوری آب باران برای حیات وحش در آینده به کار بست. با نگاه به سادگی و کارا بودن رویکرد، روش پردازش اطالعات در این پژوهش را میتوان در دیگر برنامههای پژوهشی مورد استفاده قرار داد. با این وجود پیشنهاد میشود، چنین برنامههایی در مقیاس کوچک انجام شده و در صورت بازخورد مناسب، به دیگر مناطق شناسایی شده در این پژوهش گسترش داده شود.

کلمات کلیدی: بازسازی، MCE، حیاتوحش، گسترش منابع آب، پارک ملی کویر، GIS