JWSS - Journal of Water and Soil Science

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To obtain soil-moisture characteristic curve experimentally is time-consuming and usually subject to considerable errors. So, many investigators have tried to predict soil-moisture characteristic curve by different models. One of these models predicts soil moisture characteristic curve based on soil particle size distribution and bulk density. In this model, soil particle size distribution curve is divided into a number of segments, each with a specific particle radius and cumulative particle mass greater than that of the radius. Using these data, soil-moisture characteristic curve was estimated. In this model, a scale factor, α, is used which may be considered as a constant, or obtained by logistic or linear procedures. The average values of α for clay, silty clay, sandy loam, two loam soils, and two silty clay loam soils were 1.159, 1.229, 1.494, 1.391, 1.393, 1.253 and 1.254, respectively. For most conditions, soil particle size distribution curve is not available, but only the percentages of clay, silt, and sand could be obtained using soil textural data, which is not enough to draw a precise soil particle size distribution curve. In this situation, a precise soil particle size distribution curve must be initially developed on the basis of which the soil moisture characteristic curve can be predicted. In this study, using soil textural data of seven different soils, soil moisture characteristic curve of each was estimated. In these estimations, logistic and linear methods were used to obtain the α value. Then, the results were compared with those of measured soil moisture characteristic curve. For estimation of soil particle size distribution curve, two extreme values for soil particle radius, 125 and 999 m, were used. The results indicated that using particle radius of 999 µm is more appropriate. On the other hand, it was found that for clay, silty clay, and sitly clay loam texture, it is more appropriate to employ a linear equation to determine for estimating soil-moisture characteristic curve while the logistic equation can be more appropriately used for loam and sand loam textures.

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The effect of Bacillus thuringiensis var. kurstaki on different larval instars of Colorado potato beetle, Leptinotarsa decemlineata (Say) and the role of two plant materials, namely, caffeine and aqueous neem extract, in the enhancement of it’s efficiency was investigated under laboratory conditions. The experiments were conducted at 25±4 ^oC, 65±5 %(RH) and photoperiod of 16:8 (L:D).The larvae were provided from the colony established and maintained on host plant. The different larval instars were distinguished by measuring head capsule width.To evaluate susceptibility of different instar groups of larvae to B.thuringiensis, LC₅₀ values on (1-4) instar groups were determined. LC₅₀ values for 1st, 2nd, 3rd and 4th instar groups were, 183.86, 377.03 ,1297 and 3096 ppm, respectively. The synergistic effect of caffeine and aqueous neem extract with B.thuringiensis was investigated separately on 3rd larvae instar. A completely randomized design with 6 treatments and 4 replications was used. The results revealed that there was a striking synergistic effect of caffeine and neem on B.thuringiensis.The larval mortality percentage for mixture 618ppm of B.thuringiensis and 4000ppm of caffeine was 80% however, this was 10% and 20% for caffeine B. thuringiensis respectively when these compounds were used alone.The initiation of larval mortalitry in all mixtures was earlier than other treatments.Also the larval mortality for mixture B. thuringiensis with 35000 ppm of aqueous neem extract was 77.5% after 144 hours however, it was 22.5 % and 25 % for B.t. and neem alone, respectively. The mean weight of larvae treated with all synergists was significantly less than the control cohort, (p<0.05).

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This research is aimed to predict erosion and sedimentation of Tang-e-Kenesht basin in Kermanshah province using MPSIAC and EPM models in GIS software. This basin has about 14348 hectare area. This region has various vegetation, geology and soil texture and land use types. The basin has divided into 9 sub-basins and its maximum and minimum elevations are 3300 and 1400 m, respectively. Needed data were collected in part through published reports, while the remainings were derived by field survey. Necessary maps in MPSIAC and EPM models were prepared in Autocad-2000 medium and were transported to Arc-Info, after some revisions to them. After constructing topologies for all polygons, we entered all layers weights in Arc-View software. Combinations of all layers were managed thereafter. Nine layers for MPSIAC model and three layers for EPM model were combined to result the final layer of erosion and sedimentation. Basin erosion was calculated as 1002.7 and 1739.2 m³/Km² by MPSIAC and EPM models, respectively. The result for basin sediment was 521.7 and 307.8 m³/Km², respectively. Thereafter, medium and high erosion classes were found for the two models under study, respectively. Due to not fully compatible tables for EPM model and its subjective nature, one can conclude that MPSIAC model may have better performance.

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Overgrazing is the most important agent which causes accelerated soil erosion and land degradation in arid and semi-arid zones of Iran. Appropriate planning and land use in these areas based on land suitability evaluation provide a suitable base for conserving the land and controling desertification. Land evaluation identifies possible alternatives in land use which will more effectively meet national or local needs and assists in assessing the consequences of these alternatives. Extensive grazing refers to the land utilization type in which animals feed in natural pastures. This study was performed to evaluate physical potential of the given watershed for grazing by sheep and goats, and assess the limiting factors for the land utilization type in Mehr watershed, Sabzevar, Khorasan province. Land qualities which were evaluated include accessibility to animals, soil erodibility, moisture availability, rooting conditions, salinity and alkalinity, and drinking water availability for animals. Above mentioned land qualities were assessed by appropriate land characteristics. The requirement of grazing land utilization type was defined in terms of rated land characteristics. Matching of requirements of LUT with the land qualities of each pixel of DEM (prepared in 200×200m by GIS software) resulted in a rating for every land characteristics. Some characteristics such as slope, aspect, and distance to drinking water for animals were calculated directly by GIS. Land index for every pixel was calculated by square root method. Finally, qualitative and physical land suitability classes were determined based on land indices and classified to polygons which would be suitable in grazing management. The results were interpreted under two different scenarios. In the first scenario, drinking water for animals was supplied by permanent sources and in the second one, the supplying of water was developed to temporary rivers besides the permanent sources. With the analysis of spatial modeling it was possible to assess the land suitability with higher accuracy. Overall results showed that the given area was not highly suitable for grazing at all. The most limiting factors included moisture availability for plant growth, slope, rock fragment and outcrops and distance to drinking water. Also during the late winter, spring and early summer, when the seasonal rivers were supplying the drinking water, the limitation of given area was decreased.

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  Soil particle size distribution and bulk density are used for estimating soil-moisture characteristic curve. In this model, soil particle size distribution curve is divided into a number of segments, each with a specific particle radius and cumulative percentage of the particles greater than that radius. Using these data, soil-moisture characteristic curve is estimated. In the model a scale factor, a , is used which may be considered as a constant, or obtained by logistic or linear procedures. F or most conditions, soil particle size distribution curve is not available, but only the percentages of clay, silt and sand could be obtained using soil textural data. In this situation, at first a precise soil particle size distribution must be developed, based on which the soil-moisture characteristic curve can be predicted. According to the previous studies, using particle radius of 999 µ m is more appropriate than radius 125 µ m. Also, adjusted coefficients for estimating soil particle size distribution curve for radii 1 to 20  µ m was obtained. In this study, using the soil textural data of 19 different soils from UNSODA database, soil-moisture characteristic curve of each was estimated with logistic and linear methods based on initial and adjusted soil particle size distribution estimation. The estimated values were compared with the measured data. The results indicated that for most soils, using the combination of logistic and adjusted particle size distribution estimation procedures is more appropriate than the previous methods.

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  Erosion features map is one of the basic maps in erosion and sediment studies considered important in watershed management programs. For preparing soil erosion features map (1:250000 scale), a study was conducted in Jajroud sub-basin of Tehran, Iran. Working unit maps were prepared from integrating: A) plant cover, geology and slope B) land-use, geology and slope C) land-use, rocks sensitivity to erosion and slope and D) land-use, rocks sensitivity to erosion and land units. Working unit maps obtained from integrating layers were compared with three other maps consisting of working units maps according to E) land units F) rocks sensitivity to erosion units and G) image photomorphic units. Erosion features intensities in 314 control points were controlled and erosion features ground truth map was prepared by Thiessen method and using satellite imagery. Erosion features map was crossed with different working unit maps. Results showed that D map was better than A, B and C maps with regard to economic considerations. Accuracy was 53.0 and 42.9% for methods of land unit and rock sensitivity which resulted in the maps not suitable for differentiating soil erosion features. Root Mean Squared Error of working units showed that the error of land unit and rock sensitivity methods was more than image interpretation and integrated layers methods. The highest coefficient of variation was related to land unit and rock sensitivity to erosion methods and was the least for image interpretation and integrated layers methods. The greatest precision, therefore, was related to image interpretation and integrated layers methods. In general, working unit map of image interpretation was the best method for preparing soil erosion features map.

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  This research was carried out to study the impacts of geomorphologic characteristics of claypan on land use and land degradation. Databank of the study area was constructed and digital terrain model of claypan was prepared. By using GIS techniques spatial distributions of the subsurface drainage network, sediment transportation index and wetness index were calculated. The results indicate that the depth to the claypan is between 0 (where the pan is exposed at the surface) to 605 cm. There are several depressions in the claypan which are filled by new sediments. Each depression has a catchment which is charged by the drainage water of its attributed lands. While a depression drains naturally or synthetically, the attributed soils over the depression are in non saline or moderate salinity condition otherwise, a marshland, a waterlogging area or a salt crust zone develops over there. The results also indicated that soil surface salinity is a function of depth to claypan and drainage condition of area. The trends of salinity extension are different for closed and open catchments and the depth to the claypan could be estimated using electrical conductivity. The results also show that analysis of microtopography of soil surface and soil stratification should be considered for designing irrigation and drainage networks.

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One of the most important cost factors in forest management, which involves a great deal of investment costs, is road construction. So evaluating forest roads and determining the best one can decrease costs. The objective of this study was to evaluate forest roads using Multi Criteria Evaluation with respect to costs. In Multi Criteria Evaluation method such factors as slope, aspect and soil type were used for suitability map. Then factors were compared in pair-wise comparison in the context of a decision-making process known as the Analytical Hierarchy Process (AHP) to develop weights of map layers. To do this, the opinions of some experts were collected using questionnaires and the results were integrated and factor weights were calculated. Then weights and their factors were entered into Multi Criteria Evaluation (MCE) Module to create final suitability map (factors were standardized before combining). Total costs of each variant were extracted from suitability map. After variant costs were obtained by dividing each variant total cost by its length, unit cost of each variant was calculated. Finally, unit costs were compared and the variant with the lowest costs was determined. The results showed that the slope had the greatest weight followed by soil and aspect. Also, variant 7 had the lowest cost and variant 8 the greatest cost. AHP method has the capability of considering qualitative and quantitative criteria so it is a proper method for weighting. Also MCE method in GIS environment has the capability of combining different factors. As it requires less time and cost, also has a higher precision, it is better to use MCE method in such studies.

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The present study discusses a method used to produce updated information about vegetation cover in arid and semi-arid zones, using RS data and GIS technique. In this method, Landsat ETM⁺ data in 2002 was collected in an area of about 60000 ha in Nodoushan basin, Yazd, Iran. To collect the necessary ground data, 50 sites of different vegetation types were selected and the percentage of vegetation cover in each one was determined. Also, different vegetation and soil indices were derived and crossed with located sampling points using ILWIS software capabilities. To get the best fitted curve, the relationship between vegetation cover, as a dependent variable, and satellite data bands, vegetation indices and environmental factors, as independent variables were assessed. Therefore, a multiple linear regression model was established for the prediction of vegetation cover percentage in the studied area. Finally, a vegetation cover map with high a precision was produced. As a conclusion, it can be said that mapping of vegetation cover via remote sensing is possible even if its vegetation cover is sparse.

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One of our first activities in natural resources management and development programs is to acquire knowledge on Landslide Susceptible areas. The aim of this research is landslide hazard zonation in some part of Haraz watershed between Vana village and Emam zadeh Ali, using fuzzy membership functions and fuzzy operators. At first landslide points were recognized using arial photography and field studies. Afterwards, the inventory map of landslide was prepared. Then, each effective element in landslide such as: slope, aspect, elevation, lithology, landuse, distance of road, distance of drainage, distance of fault and precipitation map was prepared in GIS environment.These data were saved in raster and vector format in ILWIS software and used for analysis with theory of fuzzy sets. Fuzzy analysis was made by IDRISI software, after assigning value and fuzzy membership functions. In this research we used different fuzzy operators such as (And, Or, Sum, Product and Gamma). Results showed Gamma fuzzy operator had the best accuracy ( ) in making landslide susceptibility map in study area.

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The genomic in situ hybridization (GISH) has been used to identify euploidy and aneuploidy in segregation generations of various plants. In this study, the GISH with minor modifications including, slide preparation of putative secondary Tritipyrum (F2) root meristemic cells, labeled genomic DNA of Thinopyrum bessarabicum by fluorescein 12-dUTP nucleotide as probe, genomic DNA of Thinopyrum bessarabicum for in situ hybridization on root meristemic cells of F2 (2n=6x=42, AABBDEb) and unlabeled Chinese Spring cultivar in pre hybridization, was carried out for the first time in Iran. The results not only indicated the various Eb chromosomes in putative 6x secondary Tritipyrum plants, but also showed different numbers of A, B and D chromosomes. The range of aneuoploidy in F2 genotypes was from %30 to %66.7, which could be due to various numbers of Eb and D chromosomes in each genotype. The selfing or back crossing of F2 plants with bread wheat varieties could lead to chromosomal stability and aneoploidy reduction in secondary Tritipyrum genotypes.

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Landscape ecology as a modern interdisciplinary science offers new concepts, theories, and methods for land evaluation and management. One main part of landscape ecology is describing patterns in the landscape and interpreting the ecological effects of these patterns on flora, fauna, flow of energy and materials. Landscape studies require methods to identify and quantify spatial patterns of landscape. Quantification of spatial patterns is essential to understand landscape functions and processes. Landscape indices as diversity and naturalness can provide quantitative information about landscape pattern. Remote sensing and GIS techniques have high ability for landscape researchers to specify, map and analyze landscape patterns. The objectives of the research include mapping and quantifing diversity and naturalness indices for Mooteh wildlife refuge by land use/land cover map derived from remote sensing images. Finally, diversity and naturalness were classified in 4 and 6 classes, respectively. Results showed that the intermediate and high diversity classes (class 1 & 2) have occupied the largest area in the study area. Among naturalness classes, class 1 which represents the high level of naturalness has taken the largest area in Mooteh W.R.

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In this research, logistic regression analysis was used to create a landslide hazard map for Sajaroud basin. At first, an inventory map of 95 landslides was used to preduce a dependent variable, which takes a value of 0 for absence and 1 for presence of landslides. Ten factors affecting landslide occurence such as elevation , slope gradient, slope aspect, slope curvature, rainfall, distance from fault, distance from drainage, distance from road , land use and geology were taken as independent parameters. The effect of each parameter on landslide occurrence was determined from the corresponding coefficient that appears in the logistic regression function. The interpretation of the coefficients showed that road network plays the most important role in determining landslide occurrence. Elevation, curvature, rainfall and distance from fault were excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. After transferring final probability function into Arc/view 3.2 software, landslide susceptibility map was prepared. The results of accuracy assessment showed that overall accuracy of produced map is 85.3 percent. Therefore, 53% of the area was located in very low hazard, 18.3% in low hazard, 21% in moderate hazard and 7.7 % residual area is located in high hazard regions. Model and then susceptibility map verity was assessed using -2LL, Cox and Snell R2, Nagelkerk R2, and was validated.

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Among the environmental pollutants, heavy metals according to their irresolvable and physiological effects on living organisms at low concentrations, are of special importance These elements due to low mobility are gradually accumulated in soil Being accumulated in soil, they eventually enter the food chains and threaten human health and other creatures Therefore, studying concentration distribution of heavy metals for soil pollution monitoring and maintaining environmental quality is essential In this study we investigated the effect of agricultural land use and geology on the concentration of heavy metals contamination of soil and spatial distribution map, using collected data, GIS and GeostatisticsUsing systematic stratified random sampling, 135 surface soil samples( 0-20 cm) from an area of 7262 sq km area and we measured total concentration of elements Nickel, Chromium and Cobalt and soil characteristics including pH, organic matter and texture. The mean value of elements concentrations turned out to be Cr: 88.9+22.7 Co: 17.6+3.5 Ni 63.1+17.7 mg per kg and the mean acidity is 7.8 which in the area is an indication …… property. Formetal concentrations interpolation procedures, Geostatistics was used. By the aid of spatial correlation analysis, appropriate interpolation method using functions mean absolute error and bias average error were selected. Interpolation map concentrations of heavy metals Chromium, Cobalt and Nickel with ordinary kriging method and the exponential model were developed Interpolation map analysis of heavy metals by the aid of geological and land use maps show that the distribution of the elements Chromium, Cobalt and Nickel are consistent with the geology classes However, they did not match the agriculture pattern Findings of this study in the area give us appropriate information about the concentration distribution of heavy metals Chromium, Cobalt and Nickel which can be used in monitoring and evaluation processes of heavy metals pollution in agricultural lands area. But on the other hand sampling in the areas far away from human effects, showed that the heavy metals concentration is naturally high.

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Digital soil mapping includes soils, spatial prediction and their properties based on the relationship with covariates. This study was designed for digital soil mapping using binary logistic regression and boosted regression tree in Zarand region of Kerman. A stratified sampling scheme was adopted for the 90,000 ha area based on which, 123 soil profiles were described. In both approaches, the occurrence of relevant diagnostic horizons was first mapped, and subsequently, various maps were combined for a pixel-wise classification by combining the presence or absence of diagnostic horizons. Covariates included a geomorphology map, terrain attributes and remote sensing indices. Among the predictors, geomorphology map was identified as an important tool for digital soil mapping approaches as it helped increase the prediction accuracy. After geomorphic surfaces, the terrain attributes were identified as the most effective auxiliary parameters in predicting the diagnostic horizons. The methods predicted high probability of salic horizon in playa landform, gypsic horizon in gypsiferous hills and calcic horizon in alluvial fans. Both models predicted Calcigypsids with very low reliability and accuracy, while prediction of Haplosalids and Haplogypsids was carried out with high accuracy.

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Soil characteristics are the most powerful factors in desertification phenomenon. The purpose of this study was investigating soil characteristics as indices for evaluating desertification intensity. The most important indicators of the soil that affect desertification were selected in the present study. Soil samples were taken from Segzi desert vicinity located in the east of Isfahan city with surface area of 112,167 ha. Soil indices such as Soil texture, soil gypsum percentage, the content of HCO3-1, electrical conductivity (EC), pH, the percentage of the organic matter, the content of the soil sodium, chloral and sodium absorption ratio (SAR) were selected. All of these indices were calculated on the thirty four soil samples. After ensuring of the normality of the samples by Klomogrov-Smirnov test, the mentioned indices were imported into GIS for delineating soil characteristics maps. To delineate distribution maps of each soil indice, inverse distance weighting and ordinary and discrete Kriging methods were applied, and appropriate method was selected. Each layer was scored based on MEDALUS model, and the final characteristic maps were then generated using soil geometric mean indices. Results showed that the affected areas of the average, severe and very severe classes of desertification were calculated about 66000, 45650 and 517 ha, respectively. The results also revealed that the indices of the organic matter, soil gypsum percentage, electrical conductivity and SAR were the most influential indicators, which affected desertification in the study area.

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Landslide as a global disaster causes great human and financial damages. Identification of landslide causes and zonation assist in instability control and construction projects siting. This study aimed to identify landslide causes and instability zonation in Ardal county, Chaharmahal va Bakhtiari province, Iran, using Analytical Hierarchy Process (AHP). Current landslides were delineated through field survey and interpretation of Earth Google images and geologic maps. By using Digital Elevation Model (DEM), slope, aspect, geologic, soil, distance to faults, distance to roads, distance to rivers and landuse/landcover maps and expert knowledge, the pairwise comparison matrix was designed. The weights for all the involved thematic maps were calculated and susceptible zones were mapped. The hazard map indicated more than 77% of current landslides are located in the severe and very severe hazard classes. Comparing landslide hazard map and trigger maps revealed the most influential factors in landslides are distance to roads and slope maps while distance to faults and aspect show the lowest impacts on landslides.

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Continuous decline of groundwater quality for agricultural purposes has become a major concern in extensive arid and semi-arid regions. Therefore, mapping the quality of groundwater on a broad scale is an essential step in land management. This study aimed to map spatial distribution of two important groundwater quality indices including EC and SAR in Isfahan province, Iran, using geostatistical techniques. Different techniques such as Kriging, IDW and RBF were applied to water quality data of 540 groundwater wells to map continuous variations of the EC and SAR indices in Arc GIS 9.3 environment. Among the interpolation methods, the Kriging by circular variogram model performed best and had the lowest RMSe error. Therefore, the produced maps from this technique were classified based on Wilcox method. Results showed that EC varies across the province from 392.2 in the west to about 17917.6 µmmhos/ cm in the northwest and eastern parts of the study area. The highest and lowest SAR values were estimated in the towns of Khour va Biabanak and Semirom, ranging from 38.9 to 0.13, respectively. According to the map of irrigation water quality based on Wilcox method, about 12.13 % of the region was classified as good, 16% as moderate, 17.5% as unsuitable and 54.35% as unusable category. In general, the quality of groundwater in Isfahan province decreases from west to east and also from south to north, especially in playas (non-agricultural lands) where the unusable class is dominant.

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The aim of this study was to assess the drinking quality of Shahrekord aquifer based on a GWQI (groundwater quality index) within a GIS framework. To do this, samples from 97 wells were analyzed for pH, Electrical Conductance (EC), Total Dissolved Solids (TDS), Total Suspended Solids (TSS), Turbidity, Ca2+, Mg2+, Na+, K+, Cl-, HCO3- and SO42-, and total hardness was also calculated. These water quality parameters were geostatistically mapped. Maps showed that maximum quality of water occurs in the northwest while the lowest quality occurs in the south of aquifer. To calculate GWQI index, each map was difference-normalized and converted to a rank map. Assuming the mean value of each rank map to be the weight of corresponding parameter, a GWQI map was created with values varying from 0 (lowest) to 99 (highest quality). Mean GWQI of 84 indicates a relatively good drinking quality of water in the aquifer. However, based on the GWQI map the quality of water declines from very good (GWQI=87) in northwest to a lower quality (GWQI= 80) in southern part of the aquifer. The lower quality of water in the southern part may have been caused by industrial activities, intensive animal husbandry, presence of wastewater plant, irrigation with treated municipal effluent and also by the inward hydraulic gradient. Map removal sensitivity analysis indicated that TSS and to some extent Na+ were important water parameters in this aquifer, which must be monitored with greater accuracy and frequency.

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Limitation of available water resources and crisis of water scarcity has been discussed in water conferences since a long time ago. In Iran’s climatic conditions, the most important problem for increasing agricultural production is limitation of available water resources. Drip irrigation methods are one of the suitable solutions for efficient use of water resources under a condition that selection, design, implementation and operation of drip irrigation systems would perform precisely. In this study, potential and suitability of drip irrigation systems in South Khorasan province was analyzed according to climatic conditions, quality of groundwater resources, topographical status and soil profile areas. To do this, all the effective parameters in drip irrigation are zonated and classified using software Arc GIS 9.3 and then using computational average method in AHP they are turned into a map to find suitable places for drip irrigation in the province. According to the study, about 50 percent of the land in South Khorasan province has the ability to use the drip irrigation system. The remaining 50 percent can also be used for drip systems if improved, with the exception of 9 plains. However, the performed drip irrigation plans are rare in this province and there should be more efforts to inform farmers to develop such systems in this province.