جستجوی مقالات مرتبط با کلیدواژه « پهنه بندی » در نشریات گروه « آب و خاک »

Determination of the physico-chemical characteristics of soil for sustainable agriculture on large scales is an important factor in achieving a precision agriculture. Different land use and management practices greatly impact soil properties, and knowledge of the variation in soil properties within different land uses, is essential in determining production constraints related to soil characteristics. Laboratory analyses of the soil properties are usually expensive and time consuming. Surmounting these problems is possible using geostatistics. This study was conducted to assess geostatistical methods for the spatial distribution of some soil properties of Darengan region with different land uses in Fars province. 134 surface soil samples at an interval of 1.0 × 1.0 km on a grid design were taken from pasture and agricultural land uses. Physico-chemical characteristics of the soil samples were analyzed. According to the results, the best spatial structure model with the highest accuracy was exponential model for the variables of sand, EC, CCE, pH, and BD, rational quadratic model for silt, and spherical model for clay, OC, and CEC. The spatial structure was weak for CCE, medium for organic carbon, and strong for the other variables. Among the characteristics studied, the variables of silt, clay and cation exchange capacity have the lowest range, and EC has the highest range. Based on the zoning map of the studied properties, the areas with agricultural land use had greater OC, clay, CEC, EC and lower pH. Understanding soil properties with their spatial dependency is of crucial importance for understanding the behavior of soil and hence providing better soil management.

Given its location in the arid belt, South Khorasan Province faces an increasing demand for water due to the simultaneous growth and development of the agricultural and industrial sectors. This necessitates proper management tailored to the region's climatic conditions. Therefore, a quantitative and qualitative study of the region's water is essential for appropriate utilization and optimal management. Various indices exist to assess the quality of groundwater for drinking purposes, including GQI and WQI. In this article, a 10-year qualitative study of groundwater quality using WQI and GQI indices was conducted based on data from 29 well rings, which included parameters such as Na, Mg, Ca, Cl, SO4, TDS, HCO3, NO3, and pH. Raster maps depicting the concentration of these parameters were prepared using the Inverse Distance Weighting (IDW) method in GIS software. The GQI values for the Birjand Plain for the periods 87-90, 90-93, 93-96, and 96-97 ranged between 87-94, 85-93, 85-94, and 86-94, respectively. The WQI value for the period 87-97 ranged from 56 to 84. In conclusion, it can be inferred that the study area ranges from acceptable to suitable in terms of the GQI index, and from poor to very poor in terms of the WQI index.

The purpose of this research is to analyze the quality of groundwater in Khanmirza, Lordegan, Borujen, Ardal, and Kiar cities based on WQI and GWQI indicators based on the Iran Standard and Industrial Research Institute (ISIRI) and World Health Organization (WHO) standard. In this research, 28 samples of groundwater (wells) were collected from different places in Khanmirza, Lordegan, Borujen, Ardal, and Kiar cities from 2020 to 2022 and 10 qualitative parameters HCO3, K, pH, TDS, EC, Ca, Na, Mg, Cl, and SO4 were chemically analyzed in the laboratory. After analyzing the data, the spatial distribution map of the index was prepared for the study area by using the inverse distance weighting interpolation method. The results showed that according to GWQI and WQI indicators, most of the samples were in the good quality category. By examining the Pearson correlation between WQI and GWQI indices and the parameters used, it was found that the two parameters TDS and EC with coefficients of 0.982 and 0.989 have the highest correlation at a significant level of 1% with the WQI index. Also, TDS and Ca parameters with coefficients of 0.975 and 0.979 have the highest correlation with the GWQI index at a significant level of 1%. The results of this research have shown that the combined use of GIS, WQI, and GWQI indicators in evaluating the quality of groundwater and their spatial distribution in the studied area is useful and effective in selecting water resources for drinking purposes.

Given the importance of water resources, especially groundwater resources, the application of appropriate management methods in quantitative and qualitative areas is well understood. The purpose of this study is to determine the most appropriate interpolation method to investigate the spatial and temporal changes in water quality in the Qaen plain aquifer. In the present study, in order to evaluate water quality, the values of 10 water quality parameters including: concentration of calcium, magnesium, sodium, chlorine, potassium, bicarbonate, sulfate, salinity, TDS and acidity ions, using IDW, LPI, GPI, OK and SK interpolation methods. It has been interpolated and researched in 2009 and 2017. The results of comparing 5 intermediate methods using RE and RMSE values showed that for most of the quality parameters studied, IDW method with the lowest error rate is the most suitable method for intermediation. It was also found that the highest error rate was related to the LPI intermediate method for the hco3 parameter with a value of 11.84 and the lowest error value was related to the IDW method for the EC and Cl parameters with a value of 0.01 . By comparing IDW zoning maps in 2009 and 2017, it was found that the concentration of most of the studied quality parameters has increased in the statistical period under study. The upward trend in Qaen aquifer in the northeastern part is more intense and the highest upward trend in this part of the aquifer is related to the concentration of calcium ions, chlorine and salinity.

As one of the most necessary human needs, groundwater resources play a key role in the economic and political processes of societies. Climatic and land-use changes made serious challenges to the quantity and quality of groundwater resources in the Tehran-Karaj study area. The main objective of the present study is to develop a method based on individual intelligent models, including adaptive neural-fuzzy inference system (ANFIS), gene expression programming (GEP), and combined-wavelet (WANFIS, WGEP) methods for temporal and spatial estimation of total hardness (TH), total dissolved solids (TDS), and electrical conductivity (EC) variables in the groundwater resources of the Tehran-Karaj area for statistical period of 17 years (2004-2021). The results showed that 
combined-wavelet models have higher performance than individual models in estimating three selected variables. So that the performance improvement percentage of the WANFIS model compared to ANFIS and WGEP model compared to GEP, taking into account the evaluation index of root mean square error (RMSE) were obtained (23.713%, 18.018%), (12.581%, 33.116%), and (6.433%, 12.995%) for TH, TDS, and EC variables, respectively. The results indicated a very high spatial and temporal compatibility of the estimated values of the WGEP model with the observed values for all three qualitative variables in the Tehran-Karaj area. The results showed that the concentration of qualitative variables of groundwater resources from the north to the south of the study area has an upward trend for all three qualitative variables. In urban areas, pollution caused by sewage and population increase, as well as in agricultural areas, the use of chemical fertilizers and their continued infiltration into groundwater resources and 
over-extraction of groundwater resources aggravate their pollution. Therefore, in the study area, climatic changes and the type of land use are strongly related to the quality of groundwater resources.

Flooding in urban areas is increasing due to population growth with improper land use planning and climate change-induced increase in extreme rainfall events. Flood risks have affected the largest proportion of the world's population (45%) compared to other natural disasters and caused 5424 recorded deaths between 2000 and 2017, and if our cities are to be resilient and better able to deal with the consequences of floods. city to cope, it is expected that they will adopt sustainable strategies to adapt to the new climatic and socio-economic conditions. Accordingly, the purpose of this research is to evaluate the resilience of Shiraz city against floods in order to identify areas of low resilience and take the necessary measures to increase it. Their resilience should be done.

The research method of this research is descriptive-analytical and practical in terms of purpose. Based on the background of the research and refinement of the variables based on the conditions of the research area, four dimensions and 24 criteria were determined, including demographic (8 variables), economic (3 variables), environmental (4 variables) and infrastructure (9 variables).

AHP method was used for weighting and access to critical infrastructure for action and recovery has the highest weight with a weight of 0.115, and infrastructure with a weight of 0.395 has the highest weight. The estimated CR of the model is equal to 0.07, which it shows the acceptable accuracy of the model. For zoning, the Vikor model has been used, and based on the output of the model, 9.92% of the area is in the zone with low resilience, where about 16.63% of the population of Shiraz lives in this zone, and about 75.43% of the area is in the zone with medium resilience. 74.56% of the population lives in it, and the area with high resilience is 14.65%, where 8.81% of the population of Shiraz lives.

The objective of the current study was to zone flood probability in the Marzdaran watershed. Since the allocated budget for management work is limited and it is not possible to carry out operations in the whole area, having a map that has prioritized different areas in terms of the probability of flood occurrence will be very useful and necessary. A well-known data mining model namely MaxEnt (ME) is applied due to its robust computational algorithm. Flood inventories are gathered through several field surveys using local information and available organizational resources, and the corresponding map is created in the geographic information system. The twelve predisposing variables are selected and the corresponding maps are generated in the geographic information system by reviewing several studies. The area under the curve (ROC) is used to evaluate the modeling results. Then, the most prone areas of flood occurrence which are prioritized for management operations are identified based on the prepared map. Based on the results, about 100 km2 of the study area is identified as the most prone area for management operations. The results showed that the accuracy of the maximum entropy model is 98% in the training phase and 95% in the validation phase. The distance from the river, drainage density, and topographic wetness index are identified as the most effective factors in the occurrence of floods, respectively.

Precipitation is one of the main elements of the Earth's hydro-climatic cycle and its variability depends on the complex and non-linear relationships between the climate system and environmental factors. Understanding these relationships and doing environmental planning based on them is difficult. Therefore, classifying data and dividing information into homogeneous and small categories can be helpful in this regard. In the present study, an attempt was made to prepare precipitation, altitude, slope, slope direction, and station density data for 3423 synoptic, climatological, and gauge stations in Iran in the 1961-2015 years’ period. These data were entered into fuzzy (FCM), self-organizing map neural network (SOM-ANN) models and precipitation-spatial zoning. The outputs of the two models were compared in terms of accuracy and efficiency. The results obtained from the output of the models have divided the rainfall conditions of Iran into four zones concerning environmental factors. Evaluations also showed that both models had high accuracy in classifying precipitation parameters; However, the fuzzy model has a relative advantage over the neural network model in the accuracy of results.

 order to study the spatial patterns and prepare spatial distribution maps, point data are generalized to the surface by moving away from the site in the interpolation process. The values ​​of indefinite points are estimated by using the measured values at definite points. There are different methods for spatial data interpolation and any major defect in the spatial distribution of climatic factors and slight inattention to the appropriate method of interpolation method can lead to errors in the design estimates. So far, many researches have been done in the field of climate data interpolation in the world. The aim of this paper is determining the most appropriate method of rainfall extension pattern and fitting the best distribution function to the annual average rainfall data. In addition to the performances of different interpolation methods, the choice of the optimal model for zoning rainfall amounts in different time periods is the goal of paper.

Iran is located in West Asia and borders the Caspian Sea, Persian Gulf, and Oman. With an area of 1,648,000 square kilometers (636,000 sq. mi), Iran ranks seventeenth in size among the countries of the world. The study area is located between 32° 25' 14.67" N and 53° 40' 58.86" E. Iran has a variable and continental climate in which most of the relatively scant annual precipitation falls from October through April. The average elevation of this plateau is about 900 meters (2,953 ft.), but several of the mountains that tower over the plateau exceed 3,000 meters (9,843 ft.). Volcanic Mount Damavand, 5,610 meters (18,406 ft.), located in the center of the Alborz, is not only the country's highest peak but also the highest mountain on the Eurasian landmass west of the Hindu Kush .The monthly precipitation data from 79 synoptic stations with at least 30 years during the period from 1988 to 2017 were used. Very severe drought years and SPI values identified in the intervals of 3, 5 and 8 months until the end of May were extracted from monthly rainfall data in each year and in three ten-year steps. In order to determine the distribution of rainfall in 10-year time periods in the lack of data points, the indices of mean absolute value of relative error (MARE), mean bias error (MBE), mean absolute percent error (MAPE) and the root mean squared error (RMSE) has been used.

In general, using the above errors in the quarterly, five-month and eight-month periods between definitive interpolation methods, radial basis functions (RBF) and local polynomial interpolation (LPI) compared to the other two methods (IDW, GPI) has provided proper results that is consistent with the results of Misaghi (2006) and Eivazy (2012). Regarding the method of radial functions, the quadratic interpolation method had the lowest correlation for all variables except rainfall with a period of 3 months. Kriging methods have given better results compared to IDW method, which is consistent with the results of Soleimani et al. (2004) and Zabihi et al. (2011). The methods of kriging, simple kriging method (second-order logic) in the interpolation parameters of mean rainfall, (3 and 5 months), simple kriging method (exponential) in the interpolation variables precipitation with a period of 8 months were the best methods. Therefore, kriging method has presented relatively more accurate results, which is consistent with the results of Mirmousavi et al. (2010).

The results showed that the most droughts occurred in the second decade of the third decade, the trend is still less severe drought is occurring and the lowest is in the first decade. In order to study the effect of SOI and NAO on drought and wet years in the country, the correlation matrix was determined to investigate the drought and wet periods. Then, geostatistical modelings were performed to describe these effects. Finally, based on the study of stations and zoning models, it can be stated that the Lanina phenomenon has a little effect on drought and annual rainfall and the El Nino phenomenon has a relatively greater effect. The results show that GPI and IDW methods are not considered as good performance. These methods are based on the fit of polynomial functions on spatial data. According to the results obtained in every area and for different parameters, a single method cannot be selected as the most appropriate method and the most appropriate method can be selected. Based on the results, the most appropriate choice depends on the characteristics of the regions and a single method cannot be selected for all regions. The results show that GPI and IDW methods are not suitable and modeling in these two methods is based on fitting polynomial functions to spatial data. RBF and LPI methods have provided better output rather than other methods because the results of the 3 and 5 month periods were above 62% and the 8 months were above 72%.

Groundwater monitoring has long been considered as one of the main sources of agricultural water supply. . In this regard, indiscriminate harvesting of this God-given resource, as well as the construction of unauthorized wells and lack of rainfall have caused the water level to drop in many aquifers of the country. The plains of Kermanshah province with its good climate and fertile soil are the agricultural and horticultural hubs of Iran. Therefore, in this study, piezometric well data in the period 1360-1397 and GRACE satellite data with a resolution of one degree in the period 2002 to 2020 with JPL, GFZ and CSR methods were used to study the changes in groundwater levels of aquifers in Kermanshah province. The amount of soil moisture was extracted from Google Earth Engine cloud computing environment using GLDAS model with a resolution of one degree. Zoning maps of all aquifers in the province for the years 1395 and 1397 were drawn by kriging method in ARC GIS software. The results showed that a number of aquifers, including Hassanabad-Shian, Sanjabi and Dinehvar are in critical condition. Long-term monthly and annual water level data of aquifers for different plains according to their effective areas have also been calculated and displayed by Thissen method. The map of changes in soil moisture, actual evapotranspiration, and cumulative precipitation in Kermanshah province was extracted by TERRA satellite with a resolution of 0.04 degrees equivalent to 4 km by 4 km, which shows the changes in these parameters in December 2019. The values ​​of TWS groundwater level changes were plotted by subtracting soil moisture values ​​against the aquifer observational data and the changes in groundwater level decreasing trend in Kermanshah province indicate a decrease of -1.5 cm and -3.8 cm in the period 2002 to 2016 by GRACE satellite and observational values respectively While from 2016 to 2020, groundwater level changes have been increasing.

The reduction of groundwater level in the plains of Khorasan Razavi Province has caused the destruction of groundwater quality and salinity of water resources. This has happened more intensely in Mehvalat plain. Since groundwater in this plain is often used for agriculture and drinking, so knowing the quality of groundwater for use in these two sections is important. Therefore, the purpose of this study is to evaluate and zone water quality variables for two types of drinking and agriculture consumption.

PH, permeability index (PI), sodium absorption ratio (SAR), and electrical conductivity (EC) variables have been selected to evaluate the water quality suitable for agriculture and irrigation. Also, the quality of drinking water was compared with the international and national standard indicators. Spatial interpolation methods are now widely used to monitor spatial variations in water quality. In order to zone water quality parameters, a kriging method that is preferable to other geostatistical methods was used.

SAR in irrigation water can be used as an indicator to determine the risks of soil sodium contamination. This index was studied for Mehvalat-Feyzabad water wells and is in the middle range. 68% of the study area is in the appropriate class in terms of irrigation water PI and 32% is in the relatively suitable range and no points were found in the inappropriate class. According to the spatial zoning map, pH is in the allowable range of 7 to 8.5 and the EC of water is in the range of low salinity to very saline. The best EC linear relationship with cations, anions, and TDS (Total Dissolved Solids) was presented for the study area in this study. Examining the relationship between these three variables shows that the increase in EC indicates an increase in the amount of cations, anions, and TDS and will affect the consumption of this water for agriculture and drinking in the future.

Due to the fact that the salinity of water for agricultural use was assessed from low salinity to very saline, so leaching and drainage should be done and the type of cultivation should be selected according to the salinity. For areas that are in the very saline group, it is necessary to use salinity-resistant plants with good drainage and low planting frequency. Examination of drinking water quality in the area showed that its use is not suitable for drinking.

Nowadays, one of the main problems of water resources in the country is the decline of water resources quality. The increasing demand for water has led to untapped groundwater exploitation and constant water loss in aquifers and as a result environmental problems including the quality of groundwater have been endangered and have created a destructive process. In this study,using the collected data from Neyshabour plain , relationship between groundwater level and increase salinity was determined. In order to investigate the quantity and quality of groundwater in the Neyshabour plain, using the data of surface water level and electrical conductivity, the map of changes in the water level and the qualitative variables were determined in the ArcGIS 10.2 software using a Geostatistics method. The results of the spatial zonation mapping of the quantity and quality of groundwater in wells showed that the water level decreased with the passage of time in the specified period and consequently its amount quality decreased.

Evaluation of groundwater quality indices and their zoning has an important role in the optimal management of aquifer. For this purpose, quality indices related to groundwater irrigation of West Azarbayjan province, were evaluated. Related to existing data, quality statistics of 21 wells during2001-2011 were extracted. Pearson correlation index was used to determine the relationship between indices and Wilcox diagram to determine groundwater quality. Kriging geostatistical method was used to study the spatial changes of the indices in the study area. The results of Pearson correlation between the calculated indices showed a significant relationship,at the 95% confidence level, between the values of all indices, except the pH index. Groundwater quality assessment by Wilcox diagram showed that 43% of the studied are located in C3S1 class, 38% of the studied area are located in C2S1 class and 19% of the studied area are located in three classes C3S2, C4S3 and C4S2. Spatial study of all indices showed that the groundwater in the northern and southeastern parts of the province and around Lake Urmia, for agriculture use, is worse than the middle and western parts.

Delineation of gully erosion susceptible areas by using statistical models, as well as optimum usage of existing data and information with the least time and cost and more precision, is important. The main objective of this study is to determine the areas accuracy to gully erosion and susceptibility mapping by using data mining of the bivariate Dempster-Shafer, linear multivariate statistical methods and their integration in Semirom watershed, southern Isfahan province. First, the geographical location of a total of 156 randomly gullies were mapped using preliminary reports, satellite imagery interpretation and field survey. In the next step, 14 conditioning parameters of the gullies in the study area were selected including the topographic, geomorphometric, environmental, and hydrologic parameters using the regional environmental characteristics and the multicollinearity test for modeling. Then, the Dempster-Shafer statistical, linear regression, and ensembled methods were developed using 70% of the identified gullies and 14 effective parameters as dependent and independent variables, respectively. The remaining 30% of the gully distribution dataset were used for validation. The results of the multivariate regression model showed that land use, slope and distance to drainage network parameters have the most significant relation to gully occurrence. The gully erosion susceptibility maps were prepared by individual and ensemble methods and they were divided to 5 classes of very low to very high rate. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to validate gully erosion susceptibly maps. The verification results showed that the AUC of ensemble method (0.948) is higher than Dempster-Shafer (0.924) and Multivariate regression (0.864) methods. Also, the the seed core area index (SCAI) value of the ensembled model from very low to very high susceptible classes have a decreasing trend that indicating a proper separation of susceptible classes by this model.

This study aim was to evaluate the relationship between the drinking water quality in Arak city regions and the drinking water sources to identify areas with inappropriate quality drinking water and its zoning with the geographic information system (GIS) and planning to address drinking water quality problems. In this research, drinking water from 18 areas in the city was sampled to measure physical and chemical parameters during 2016. Parameter analysis was carried out by the standard water and wastewater. To extract the contamination maps, IDW method was used in GIS environment. The drinking water quality parameters average  for pH, TDS, EC, TH, F, Cl, NO3 and SO4 was 7.4, 50.67(mg/l), 28.840(µS/cm), 28.38(mg/lCaCO3), 17.0(mg/l), 15.95(mg/l), 19.66(mg/l) and 27.49 (mg/l) respectively. The results showed that the highest concentration of pH, TDS, and EC was in the east.  TH is located in the south. The highest amount of F is in the west of the city and F is highest in the south, the highest NO3 and SO4 are located in the south. In general, the comparison of measured values ​​with the set value indicates that the average value of all elements was lower than national standards, but the mean of TDS, TH, and NO3 is higher than global standards.

The purpose of this research is to present a method based on global and experimental algorithms for estimating relative humidity in Sistan and Baluchestan province. For this purpose, Terra MODIS images and products (MOD05, MOD07) of 10-years (1-Jan-2009 to 31-Des-2018) under cloudless conditions were used as selected data. To validate the obtained layers (near ground surface temperature, ground surface pressure, total perceptible water, TPW, and relative humidity), the ground station and the radio sound data were used. The R2 and REMS values of the recorded layers from the sensor and the ground data were acceptable and the sensed data were in good agreement with ground station measurements. Results show that the altitude factor play an important role in temperature measurement. The minimum amount of TPW has been recorded to be 6 mm in the Khash, Mir Java and Saravan regions in the cold season and the maximum amount of TPW has been recorded to be 49 mm in the coastal areas in the warm season. The average relative humidity in the province is in equilibrium in the cold season, while it is out of equilibrium in the hot season, so that it is above 60% on the coast of Oman and less than 10% in the central province (Khash, Mir Java and Zahedan).

Soil erosion is the most widespread form of soil degradation jeopardizing food security worldwide. In Iran, gully erosion is important because about 90% of the country has arid and semi-arid climates and rainfall is not adequately distributed. In such conditions, the absence or lack of vegetation cover with increasing runoff causes more than 2 billion tons of soil losses annually. Therefore, conducting basic and applied researches on soil erosion via different methods for comprehensive management of natural resources is emphasized. The prerequisite for all kinds of erosion, such as gully erosion, is the prediction of the risk of gully formation in different areas susceptible to erosion. The study area is located in Ghaleh Gorg watershed which sub-basin of Shahid Modarres that large part of these farmlands has been destroyed by gully erosion. The purpose of this study was to apply fuzzy logic operators for gully erosion zoning. In this research, six effective parameters on soil erosion including mean weight diameter of aggregate, sodium adsorption ratio, salinity, percent of fine sand, silt and clay were determined according to standard laboratory methods. After re-classification, standardization of prepared layers was carried out by the Fuzzy method. Hence, Fuzzy-based layers were integrated using operators of Fuzzy algebraic sum, Fuzzy algebraic production and Fuzzy gamma with 0.2, 0.5, 0.8, 0.9 values and the obtained results were evaluated. The validation of prepared maps was done based on two methods of map matching percentage of areas with very high and high sensitivity with gullies map of the study area and quality sum index (Qs). The Fuzzy results of raster layers showed the relative accumulation of silt, clay and fine sand grains in the middle to western parts of the region due to leaching and soil aggregation of Aghajari formation with a high slope of >20%. The deposition of this sediments was with 0-5% slope in the middle and western part of the basin. Results of layer integration indicated the fact that the fuzzy summation and multiplication method are not suitable approaches for final mapping because of their high increasing and decreasing effects, respectively. About Fuzzy Gamma operator 0.2, the results revealed that about 17.07% of the area was in the high and very high-risk zone and 67.07% of the area was in the low risk zone. In Fuzzy Gamma 0.5, about 31.16% of the area was in high risk and 55.38% in low risk zone. And only 60.38 percent of the gullies was in the high-risk area. Thus, these both operators 0.2 and 0.5 cannot be an acceptable method for preparing the final fuzzy map. The results of gamma operator 0.8 showed that about 43.21% of the area was in high and very high risk classes and 42.45% of the area was in low and very low risk classes. In the gamma operator 0.9, about 60.92% of the area was in high and very high risk zone and 17.1% of the area was in low and very low-risk zone. Also, regarding the distribution range of gullies, 94.93% of gullies was in high and very high risk classes, which is more acceptable and better than gamma 0.8. According to the obtained results, Fuzzy gamma 0.9 with 94.93 matching percentage of areas containing very high and high sensitivity and maximum quality sum index (0.73) among different operators was selected as the best method for preparing Fuzzy map in the study area. According to the results of this study and its comparison with field observations, effective factors contributing to the initiation and development of gully erosion were sensitivity of the geological formations, soil texture type, salinity and alkalinity and non-implementation of biological and biomechanical operations to the soil and vegetation cover restoration. Around 3855 hectares (60.38%) out of 6327.5 hectares of the total studied area were at high and very high erosion risk. Furthermore, 2056 hectares (94.93%) out of the 2166 hectares of the gullies area were at high and very high risk of erosion, denoting the high accuracy of the final map. Among the available methods, Fuzzy Gamma 0.9 with the highest overlap between the area of high and very high-risk classes of the gully map (94.93%), and the highest qualitative sum index (0.73), was selected as the best fuzzy method for zoning in the study area.

In this study, for study the effect of rainfall changes on groundwater quality in dry and semi-arid climate of Isfahan province, six basins with high concentration of wells and meteorological stations were selected. Data from 72 meteorological stations of Isfahan province during the statistical period of 2003-2013 and data from 350 wells were used to study the changes in groundwater quality. Subsequently, data with the lowest quality of EC, Ca, Mg, pH, Na, Cl parameters were recorded in Excel software, and ArcGIS software and the changes were zoned. In studying the meteorological drought, rainfall of September as the representative of the driest months of Isfahan, DIP software, analysis of time series 6, 12, 18 and 24-month and the time series with the highest correlation in the zonation were used. Then a correlation time series was zoned in different sections of the six study basins in ArcMap software. The results of Pearson statistical method showed a positive correlation between the drought of meteorology and groundwater quality in the 18-month time series. In summary, with the negative trend of precipitation, the positive trend of salinity, calcium, magnesium, acidity, chlorine and sodium in groundwater was observed from the western areas to the eastern regions. The results show that the minimum variation of millimeters in rainfall from a basin to another basin in Isfahan province affects groundwater quality in each of the six basins and leads to a downward trend in groundwater quality following drought events.

This research was an attempt to investigate the quality and quantity of groundwater resources in Yazd-Ardakan plain as the biggest watershed in Yazd Province and its relationships with the geological formations. For this purpose, qualitative data of the wells in the plain for the decades of 80 and 90 (according to the Iranian calender for the pre- and post-water transfer from Zayandehroud River to Yazd) were studied. Furthermore, the geological formations map of the region was prepared based on the geological maps and Google-Earth images. Then, the type and facies of water for each well was determined using Aq.QA 1.1 software. The suitability of water usage for agriculture and drinking purposes was also evaluated. Results showed that the chloride type of the groundwater was dominant in the southern and central parts of the watershed and also in 90s rather than 80s. Results of the qualitative zoning showed that the amount of EC was increased as 3 dSm-1 from 80s to 90s. Quantitative zoning of the groundwater showed that the elevation of the water surface decreased toward northern part of the watershed. The water depth in the wells was also decreased on the average of 10 m from 80s to 90s. Results also showed that the wells were dug often on the alluvium formations. Correlation analysis between water quality and frequency percentages of geologic formations revealed that the highest correlation (r=0.99) was observed between calcareous geologic (Ktl) unit and EC of the groundwater; whereas, there was the least correlation between Acidic volcanic rocks (Pc-cr) geologic unit and EC of the groundwater (r=0.07).

Considering the importance and special status, the critical conditions of water scarcity in production systems, and the lack of traceability of wheat water in Khuzestan, in this study, green, blue and gray water footprints of wheat product were estimated. The studied areas were Ahvaz, Dezful, Shooshtar, Behbahan, Izeh and Khorramshahr. The total water footprint of wheat was obtained from the sum of green, blue and grey water footprint. Then, the relationship between wheat water footprint and actual yield was compared. The results showed that among the study areas, Khorramshahr needed more water (1704 m3 t-1) to produce the product and thereafter, Ahvaz (1228 m3 t-1), Behbahan (1083 m3 t-1), Izeh (1012 m3 t-1), Dezful (959 m3 t-1) and Shushtar (915 m3 t-1). To produce 1 ton of wheat, Izeh needs 778 cubic meters of green water, and after that, Khorramshahr was ranked second with 458 cubic meters of green water. However, Izeh had the lowest blue water footprint, and the zoning of Khuzestan province in terms of the blue water footprint of wheat showed that the blue water footprint in the southern half of the province is more than the northern half. Grey water footprints also follow a similar blue-water trend. Whereas Shooshtar has the lowest water footprint with the highest yield, and Khorramshahr has the lowest wheat yield and the highest water footprint among the other studied cities.