جستجوی مقالات مرتبط با کلیدواژه "interpolation" در نشریات گروه "آبخیزداری، بیابان، محیط زیست، مرتع"

Measuring the amount of runoff and soil loss per unit area is very important to evaluate the condition of erosion in different areas. The runoff is caused by the condition of the upstream watersheds, which has a different response in different time and space ranges of a watershed. Some hydrological responses may be considerable in the upstream areas of a basin, but the same responses cannot be identified in the downstream. These different responses among different regions are referred to as the scale effect, including the mismatch among runoff responses at different scales. In this context, the role of spatial scale is considered as a factor that directly affects the occurrence of various processes of runoff production. Therefore, assuming the uniformity of discharge changes on different scales leads to the application of a single plan and management strategy for the entire watershed area, which ultimately results in the failure to achieve the desired outcomes. On the other hand, an accurate estimation of the discharge status of watersheds provides a correct understanding of the underlying hydrological processes. Comprehending the accurate influence of spatial scale on runoff is essential for precise streamflow estimation in watersheds and their zoning across various spatial extents. This forms the foundation for optimal water and soil resources planning and management, particularly in basins facing serious soil erosion challenges. Therefore, the objective of the present study was to examine the effect of spatial scale on the specific discharge and zoning of discharge values within the Karkheh basin, based on data of 28 hydrometric stations.

Materials and methods :

In this research, the data used includes the average annual water discharge (Q) and the area of the basin and sub-basins (A). The data used was received from the Iranian Water Resources Management Organization. Subsequently, in order to identify the most suitable stations, any disturbances in the natural process of the basin processes were initially investigated. This process involved the identification and removal of stations that had the potential to alter the process. Finally, a total of 28 stations with an appropriate statistical period length and no upstream basin disturbances were selected. Also, in order to calculate the upstream area of each station, the Karkheh basin was divided into 28 sub-basins based on the location of existing hydrometric stations. This was achieved using the Arc Hydro extension and the digital elevation model. In addition, according to the topographical, Geomorphological and hydrological conditions, the Karkheh basin was divided into five main areas.In the following, according to the values of area (A) and specific discharge (Qs) in the sub-basins, Qs-A relationships were drawn under log-log coordinates to calculate a linear or non-linear regression equation between Q and A, the effect of the scale onthe amount the discharge in the main sub-basins should be specified. Finally, using the method provided by Church et al., the corrected specific discharge values were calculated for each of the main sub-basins and through interpolation, the specific discharge map of the basin was produced.

The results of investigating the effect of scale on specific discharge indicated that there was no proper regression relationship between Qs and A for the entire Karkheh basin as a single basin (R2=0.3). However, the regression relationships with a coefficient of determination ranging from 0.7 to 0.98 were obtained for the sub-basins.Other results showed that in the majority of sub-basins, there is a negative relationship between area and specific discharge. That is, as area increases, specific discharge decreases. However, in the Seimareh basin, the increase in area leads to an increase in specific discharge. The observed increase in discharge can be attributed to the reduction in the basin elevation and the broadness of the riverbed. In contrast to other sub-basins, the discharge in the Qarasu sub-basin exhibits a low initial value, followed by an increase and subsequent decrease. This phenomenon can be attributed to the location of the Qarasu sub-basin in the upstream region of the Karkheh basin, the topographical conditions, and the high slope of the area. In general, the results indicated that the specific discharge varies across sub-basins with different areas and spatial scales. So that, the highest specific discharge was observed in the vicinity of the Karkheh basin outlet. This can be attributed to a number of factors, including the high slope and rainfall intensity in the upstream areas, as well as the difference in climate conditions and vegetation cover between the downstream and upstream areas.

Conclusion :

A comprehensive understanding of river discharge and the impact of spatial scale on it is of paramount importance in various fields. It provides a profound insight into the consequences associated with this phenomenon. To sum up, it is critical to understand river discharge patterns and how spatial scale affects them in a variety of contexts, including water resource management, flood risk reduction, sustainable development, and environmental preservation. It gives us a thorough awareness of the resulting effects. The findings of this study indicate that as the area increases, the specific discharge tends to decrease. Based on these results, it can be inferred that spatial scale and the upstream watershed area can exert an influence on discharge. A substantial body of research has demonstrated that spatial scale and the upstream watershed area play a pivotal role in determining river discharge. However, it is crucial to acknowledge the influence of a multitude of factors, including vegetation cover, climate, topography, slope, soil infiltration, and precipitation intensity, on specific discharge across diverse watersheds. Therefore, when evaluating the hydrological conditions of large-scale watersheds, it is essential to pay particular attention to the impact of spatial scale as a crucial factor. It is noteworthy that recognition this phenomenon necessitates more in-depth and comprehensive investigations across various spatial scale levels.

Groundwater is important water resource supply, especially in arid and semi- arid regions. Increased utilization of the ground water aquifer leads to significant reduction in the storage of reservoirs. This study evaluates the hydrogeological drought in Garmsar plain using Groundwater Resource Index (GRI). First, we used 17 piezometric wells data over 2001-2011 statistical period to calculate GRI in the beginning, middle and end of the period. So, we used different interpolation method including geostatiscal method ordinary kriging (OK), simple kriging (SK) and deterministic methods including inverse distance weighting (IDW) to prepare the maps over three periods. The mean absolute error (MAE) and root mean square error (RMSE) indices were used to evaluate the accuracy of simple kriging, ordinary kriging and IDW classification based on the drought maps. The results showed that the values of MAE and RMSE criteria for simple Kriging is better than the other methods and indicates the suitability of this method for zoning GRI. According to the results, the most severe hydrogeological drought in Garmsar plain was at the end of 2011, that 91.16 % of the study area was suffered from severe drought. SPI was used for considering the effects of meteorological drought in the time scale of 3, 6, 9, 12, 24 and 48 months on groundwater. The correlation between SPI and GRI showed long-term timescale of 48 monthly has the greatest correlation with groundwater level.

IntroductionGroundwater is among the most precious natural resources for human health, economic development and environmental diversity. Since the measurement of groundwater parameters and water quality is difficult, costly and far from being available, interpolation techniques are an easy solution. At the same time, there is a strong correlation between groundwater quality and land use in areas with sensitive aquifers. Changes in land use caused by factors such as rapid growth and expansion of urban centers, rapid population growth, and the lack of land, the need for increased production and the evolution of technologies are important concerns. The literature review shows that the quantitative and qualitative decline in groundwater is a global crisis. As a result, the factors affecting the quantitative and qualitative decline in groundwater range from climate factors to socio-economic factors.In the current research, find an answer to the poor condition of the Isin Plain aquifer by looking at the relationship between some hydrological factors and changes in cultivation pattern of the region is the main goal. For this purpose, the water table and EC of groundwater were interpolated using geostatistical methods. Using satellite imagery, the trend of culture pattern changes over time was obtained. Finally, the relation between the factors on the Isin plain was established. Material and MethodsFor this purpose, the quantity and quality of groundwater in eastern and western Isin plains were interpolated using the Kriging and IDW methods, during the four statistical years of 2004, 2011, 2018, and 2021 and the time series of 2004-2021. The RMSE statistic was used to evaluate the performance of the methods.Then, satellite images and ground truth data was used for land use change classes to investigate the land use changes during the cropping season, along with the determination of changes in the quantity and quality of groundwater in the eastern and western Isin plains for the mentioned years. Satellite data including Landsat 5 multi-temporal satellite images in 2004, 2011, and 2018 and Landsat 8 and Sentinel 2 images for February 2021 were obtained from the USGS.Following preparation of the related images using the flash module, atmospheric and radiometric corrections were performed. Then, the corrections information was extracted into the text file appended to each image. With field survey, the coordinates of the representative pixels were determined and seven land use classes of gardens, vegetables, bare lands, residential and industrial areas, saline lands, and Prosopis Cineraria and Juliflora species were determined. The maximum likelihood classification method was used to separate seven main land use classes based on 127 training samples. For the purpose of assessing accuracy, an error matrix was created for the producer's accuracy, the user's accuracy, the overall accuracy, and the kappa coefficient calculation. Finally, to examine the relationship, the land use map and the groundwater and EC interpolation maps were overlapped into the Arc Map software environment. Results and DiscussionBy comparing the interpolation methods of IDW and Kriging with the RMSE validation technique, it was found that the best interpolation method for estimating water table and EC is Kriging, followed by the IDW method. A review of the land use maps of the Eastern and Western Plains of Isin showed the increase and decrease of different land use categories over the years under study. The overall accuracy and Kappa coefficient were over 82% and 0.79, indicating the acceptable accuracy of the classification and maps obtained. The results of overlapping land use maps and spatial changes in ground water indicate that the location of agricultural land, especially gardens in the eastern Isin plain and vegetables in the western Isin plain, is compatible with the areas of having low water table. The results of overlapping the land use map obtained from Landsat 8 data and EC spatial changes showed the highest amount of EC in can be observed in Prosopis Cineraria and Juliflora species and residential and industrial uses in eastern and western Isin plain. The results obtained from Sentinel2 indicate that the value of EC was significant in the bare lands of eastern Isin and in the saline lands of western Isin. However, the increase in agricultural use, especially for gardens and vegetables, and the pairing with areas with the lowest water table indicates an over-extraction of groundwater for agricultural purposes. On the other hand, the significant extent of bare lands and the upward trend of saline lands, residential and industrial areas, and matching with areas with high EC and the adaptation of maximum EC with Prosopis Cineraria and Juliflora species uses may be a warning for poor condition of the Isin plain aquifer.

The main source of water in the Arsanjan plain is underground water, which has been exploited in the past with Aqueduct and now with numerous wells. For knowing about the quality conditions of these sources; multivariate statistical analysis and interpolation methods were used in three years with different rainfall. Factor analysis determined the key indicators of underground water quality and mapping was done with interpolation methods. The maps were classified using the Jenks optimization method of classification and the area of each class in each year calculated. Based on the results of factor analysis, EC, TH and Sodium concentration were selected with factor loadings of 0.843, 0.889 and 0.991, respectively. The RBF interpolation method for the sodium parameter was suitable in all three years of the study. For parameters of EC and TH, RBF-MQ method and LIP method had the least error in 2014 and 2015. Mapping spatial changes of the three mentioned parameters showed that in 2015, when the rainfall was lower than the average, the area of the regions with low values decreased. Due to the quantity and quality of its changes, sodium concentration parameter has a good potential to be used as an indicator of changes of the quality of underground water in response to climatic or management factors. In general, it is suggested that in assessment of the groundwater quality of Arsanjan Plain, the proximity factor to Bakhtegan Salt Lake, in addition to factors related to climate and watershed, should be considered.

Due to the limited number of meteorological stations especially in mountainous areas, the use of satellite data to extract rainfall is very important. On the other hand, the lack of spatial appropriate rainfall data is one of the major challenges in flood or drought prediction and timely warning in this case. One of the available solutions in this case is to measure rainfall from space.

The aim of this study was to investigate the accuracy of rainfall data obtained from TRMM satellite images in Taleghan watershed on a monthly and annual time scale during the period 2010 to 2015. For this purpose, TRMM images with three-hour spatial resolution were received during the statistical period for the study area. Then using the sum of three hours rainfall, daily rainfall was estimated. In the following the adjustment coefficients were also presented to reduce the error of rainfall data, and finally the accuracy of satellite image data was compared with two common interpolation methods i.e. invers distance weighting and Kriging.

The results of error indices showed that the rainfall of TRMM images is well correlated with the data of ground stations, especially Joestan station, but in some months, there is a problem of under-estimation and over-estimation. For this reason, correction coefficients were applied to solve this problem, which on average in most months; this coefficient was calculated less than one, which indicates the overestimation of TRMM image precipitation data. Examination of the corrected data showed that by applying the estimation coefficients, in addition to solving the overestimation problem, the error rate was also reduced and the Nash-Sutcliffe performance index was somewhat improved. The root mean square error (RMSE) at Garab station also decreased from 88 to 26 mm in annual rainfall time scale by applying the adjustment coefficients, which indicates an increase in data efficiency after the application of correction coefficients. The results of comparing the modified data with interpolation methods showed that in all error indices, the modified TRMM data is more efficient in estimating rainfall.

Overall, it can be said that rainfall from TRMM images can give satisfactory results if adjustment coefficients are applied, and in areas with a shortage of meteorological and data stations, it can be a reliable source of rainfall data.

Knowing the temporal and spatial distribution of rainfall is one of the most important factors in implementing soil and water conservation, flood control, and drought management projects and one of the most important parameters for water resource planning. Given the significant variation in rainfall on the one hand and the shortage of rain gauge stations to record rainfall, on the other hand, the requirement of correlating the rainfall estimation model to the spatial is inevitable. In this regard, geostatistics is one of the most important methods for estimating the spatial distribution of rainfall. The purpose of this study was to evaluate the geostatistical methods in annual, monthly and maximum 24-h rainfall estimations in the Haraz Watershed in Mazandaran province and to study their spatial variations in the time period of the water year 1976-1977 to 2013-2014. In this research, 40 meteorological stations with 38-year statistical period into and around the mentioned watershed were used to compare the geostatistical methods including Kriging, Co-kriging, inverse distance weighting and radial basis function in the isohyetal map for the Haraz Watershed. For this purpose, using the cross-validation method, by removing the individual stations, their precipitation values were determined and compared with the observed values. The results showed that radial basis function for annual rainfall and simple Kriging for maximum 24-hour rainfall, and simple and ordinary Kriging, Co-kriging, inverse distance weighting and radial basis function for different monthly rainfall is the most appropriate method. There is the spatial rainfall dependency on a monthly scale from 11.6 to 99.2 km, annual scale with 35.9 km and maximum 24 hour rainfall with 21.3 km. These results can be used to design distance among meteorological stations for rainfall measurement.

Drought management is an essential task to exploit water resources. In this study, the monthly rainfall of 35 synoptic stations in Qazvin province during 30-year were considered for drought monitoring. In this study two drought monitoring indices including modified standard Precipitation index (MSPI) and Standardized Precipitation Index (SPI) are accomplished and compared to the reports of four indices in the study area. The obtained results showed that the MSPI is more accurate than the SPI and other indices. Having the drought conditions in the stations, zoning of drought were calculated by Interpolation methods such as IDW, Kriging, GPI, and RBF.The obtained results demonstrated that IDW method with first power is the best method in terms of average error. Moreover, zoning of the precipitation is conducted using Kriging interpolation then the MSPI value for each cell is computed for monthly precipitation. The results show that if the precipitation interpolation is conducted firstly, the drought index is calculated more accurately than the method that drought index calculated in the stations. In order to assess the drought condition more accurately, the vegetation condition index (VCI) is computed using monthly NDVI product of MODIS. The correlation between VCI and MSPI was calculated that the results illustrated that MSPI confirms the results obtained by VCI. As a result, VCI can be used to monitor drought in the watersheds which suffer from sufficient ground stations.

Rainfall erosivity is usually expressed in terms of erosion indices based on rainfall characteristics. Various indices have been presented so far, among which the erosive factor (R) in the global soil loss equation (RUSLE) is more popular in the world. The aim of this study is modeling of rainfall erosivity index using 27 sinoptic station and trend analysis with Mann-Kendal test during 1951-2014. A modified Fornier index, which can be calculated on the basis of monthly rainfall, was used by reviewing worldwide research and also by the lack of stations. After calculating the rainfall erosivity factor, the rainfall erosivity map was mapped and semi-variogram map with GS+ software was used to show the spatial correlation. For interpolation of erosivity index was used from IDW, GPI, LPI and Krigging. Root mean square error indices and mean absolute error values were used to select the best mediation method. The results showed that the Kriging method with root mean square error of 0.8 and absolute mean error of 0.8 is the best method. Thus, the country can be divided into five regions which semi-arid regions have the highest rainfall erosivity. Also, these regions have a increasing trend of rainfall erosivity

Nitrate is one of the most important pollutants of surface water and underground water resources which has adverse effects on the health of consumers. Due to lack of sufficient opportunity and budget, in practice, full and timely sampling of all wells in each area is not possible. So the amount of nitrate in certain parts according to the adjacent groundwater is of particular importance in studies. In this study, data from 55 observation wells at 902 Km2 of Ghaemshahr-Jouyar plain were used. The accuracy of deterministic methods and geomorphology were evaluated to determine the most suitable method for determining spatial variations of nitrate. Among all the methods of interpolation, simple co-krigination with auxiliary calcium was identified as the most appropriate method. RMSE value was obtained 7.45 mg/l, MAE equal 5.95 mg/l and The coefficient of determination 0.47 . J-Bessel variogram model has the most powerful spatial structure. Using the land use map of Mazandaran province in the Research area also showed that the highest nitrate values were observed in the urban area. The results showed that the highest nitrate pollution was in Behnamir and from the coastal areas of the Caspian Sea and in all areas it is within the permitted limits.

Results of urban growthing and increasing pollutants water leads to decreasing of quality and quantity of water resources. Quality and Quantities groundwater at Noorabad Plain are conducted in this study. For this purpose, traced the hitographs of rainfall from April 1997 to 2017. According to the drawn hitograph, the years 2004, 2010 and years 2014, 2017 were selected as rainy years and low rainfall years respectively. Spatial distribution’s map for concentration of groundwater quality parameters and groundwater level by Kriging method were created. In addition, the best of selection of model according to the assessment criteria (RMSES, RMSE, ASE and MSE) were created for these years. By dividing the product by the rank of each parameter in its average weight on the total number of parameters, the GQI index was prepared to study the groundwater quality in the years studied. The results show that: the water quality of this area is in a good grade during the studied years. In all of the examined years, the northern and southeast areas of the noorabad plain have better quality than other areas. By investigating of quantitative and qualitative maps, it was noted that, by increasing the distance of groundwater level from the ground, water quality becomes more appropriate.

Rainfall erosivity (RE) energy is an important factor on the soil detachment and transition of them implying an important role on the regional potential region erosion. . In this study SPI index was used in order to determine the climate condition and its consequent effects on RE in Fashand watershed, Elburz province. At first the drought, wet and normal periods were determined for four rain gage station and then, both EI30 and modified Fournier index (MFI) were calculated at each gauge station. The regression analysis was used to investigate the relationship between EI30, MFI and 24-hour rainfall as well as annual rainfall of data-logging rainfall stations. After that through applying the regression equation the EI30 was extrapolated for eleven typical rain gauges over the different climate periods. The best correlation was obtained between EI30 and annual rainfall (R2 = 0.71). The spatial zonation RE maps were extracted through Geostatistical analysis for drought, wet and normal condition . According to the findings the effects of climate variability on the amount of RE are significant. Maximum and minimum RE are related to the wet and dry period respectively. However the RE on the summer season of dry condition is more than the wet condition and such condition together with low vegetation cover related to the drought condition lead to complicated situation. Despite the popular thought that the low RE can be addressed into the drought condition the rainfall pattern affect the erosivity potential and not the amount of precipitation.

In groundwater resources management, continuous monitoring of wells discharge and charge and groundwater quantitative and qualitative variations are very important. Groundwater monitoring network could provide information on quantitative and qualitative variations in groundwater situations. Hence it would be used to predict the behavior of the aquifer in the future. This study describes an optimizing method to design the optimum groundwater-level monitoring network in aquifer of Eshtehard. Two scenarios were considered to optimize the locations of the observation wells: (1) exploring optimal locations of existing observation wells and (2) adding optimal observation wells to existing well network. Kriging method was utilized to estimate groundwater-level for preparing the database. Optimization of groundwater monitoring network with two objectives (1) minimizing root mean square error and (2) minimizing number of wells, was implemented by non-dominated sorting genetic algorithm (NSGA-II). The results show that by using this method it is possible to remove redundant wells in a monitoring network or to add new wells in case of shortage of observation wells in a network having acceptable accuracy.

A lot of part of Iran is covered by dry and semi-arid climate. In these regions, due to the lack of rainfall, agriculture is heavily dependent on groundwater resources. The continuing drought in recent decades and the excessive withdrawal of groundwater aquifers for agricultural development, has led to more land degradation and desertification. Understanding the quality and quantity of groundwater as one of the most important and most vulnerable sources of water supply in recent decades which is so necessary. For optimal groundwater management, it is necessary to collect sufficient information from a set of quantitative and qualitative characteristics of aquifers in different regions and to be evaluated in appropriate ways. Therefore, due to the importance of this issue (non-systematic use of water resources for agricultural activities), the present study aims to assess the process of ground water changes due to the agricultural activities in Dargaz county of Khorasan Razavi province along with the presentation and proposal of management plans for risk reduction Desertification was carried out. Demir et al. (2009) investigated the spatial variation of depth and salinity of groundwater in agricultural areas in northern Turkey using the statistical method of the earthquake. The results of their research showed that the eastern part of agricultural lands in the middle parts of the Black Sea, which has poor drainage, has the highest salinity risk. Akbari et al. (2009), using the Geographic Information System, studied the groundwater level in Mashhad Plain during the twenty years and estimated the average annual loss of 60 centimeters. Their results indicated that the increase in the number of wells in the area and drought, were the main causes of groundwater subsidence decline. The study area is located in northeastern part of Iran and in the north of Khorasan Razavi province. Dargaz County has an area of about 376459 ha. Dargaz Plain is considered as one of the agricultural poles in Khorasan Razavi province. In order to study the process of water change, two sub-criteria of groundwater quantity such as the groundwater table index, and quality indices were used such as water conductivity, sodium adsorption ratio, and chlorine index. For evaluation and zonation of quantitative indices of groundwater level, 124 wells and 111 aqueducts were used and the analyzed using geo-statistical interpolation such as Kriging method in GIS software environment. In addition, groundwater quality criteria has evaluated during the 20 years period of 1996-2016 and in the 5 years’ time period.

 The non-parametric Mann-Whitney Test (Mann and Whitney, 1947) in the Minitab environment was employed to test the model validity. The non-parametric Mann-Whitney test is used to compare two independent categorical groups. The Mann-Whitney test relies on these null and alternative hypotheses: H0: There is no difference between the two groups, H1: There is a difference between the two groups. In the Mann-Whitney test, N is the number of samples randomly selected from the map and sampled in the field. The Mann-Whitney value is compared with the value identified by consulting the significance table The results showed that the highest rate of groundwater was in the northwestern part of this region. The research area was not badly affected by changes in chlorine concentration and sodium absorption ratio in groundwater, and classified into very low and low. Finally, two quantitative and qualitative indicators of groundwater in the severity of the risk of desertification, the region is located in three low, moderate and severe risk classes, respectively. At present, uncontrolled management of underground water utilization, the development of agricultural land in the traditional way, and the release of lands, have made these areas one of the centers of the erosion crisis. The amounts of changes in the electrical conductivity index in the eastern parts of this region fluctuated from extreme to very intense. It has risen from 14 percent in 1996 to 32 percent in 2011 and finally reaches 23 percent at the end of the year (2016). This condition indicates an early warning stage for the salinity of irrigation water in this area. The results indicate that the rate of groundwater loss in the western and northwest parts of the study region is the highest, mostly, due to the deep and unannounced drilling of wells and the excessive removal of groundwater. Given the current situation and recent droughts, Dargaz Plain Underground Water Management should be considered as a priority for crisis management by officials and experts in executive agencies.

In this study, the effect of land use changes on groundwater resources as well as monitoring of spatial and temporal changes of groundwater quantitative and qualitative parameters were assessed in west basin of Jazmoryan Wetland. Landsat satellite images of TM 2002 and OLI 2015 sensors by applying of Maximum Likelihood Method were used to investigate land use changes trend. Also, information related to wells in years of 2002 to 2015 was used to assess groundwater quantitative and qualitative parameters. To do this, zoning maps of spatial and temporal changes of groundwater quantitative and qualitative parameters were prepared using the best interpolation method in ArcGIS software. The results related to evaluation of the best interpolation method showed that Kriging method had the least error. According to the results of this study, the area of agricultural and urban land uses has been increased, while the area of ephemeral stream, dam, rangelands, bare and mountain land uses has been decreased in 1394 compared to 1381.These changes indicate the increased degradation as well as unstable conditions of the region that adversely affect groundwater resources. As a result of these changes, groundwater quality in southern parts of the study area has been declined. Among the factor causing this declined groundwater quality are construction of Jiroft dam on Halil-rood permanent river, lack of water right and expanded urban and agricultural lands which have caused decrease in groundwater quality over time.

Land salinization is a major and destructive problem in the agricultural sector, which must be controlled by proper scientific management. The first step in this way is to identify and map the saline areas. Over the past few decades, the use of geostatistics and remote sensing techniques has been developed to map the soil salinity and monitor its changes. The purpose of this study was to compare the capability of different geostatistics methods to prepare soil surface salinity maps in a part of the Meyami plain, Semnan province. To do this, 225 soil samples were taken from a depth of 0-30 cm of soil from the intersection of regular grid lines of 600 * 600 meters using GPS. EC, pH and clay of soil samples were measured. The results showed that the Kriging method with an average absolute error of 2.29 was more accurate than other interpolation methods and, vice versa, the Spline Thin plate method with an average absolute error of 4.38 had the lowest accuracy. According to the map prepared, the highest, lowest and mean salinity in the Meyami plain were recorded to be 15.69 ds/m, 2.12 ds/m, and, 5.24 ds/m, respectively.

Rainfall variability and its impact on water resources are important climatic issues. Intra-annual variations in rainfall are characterized as precipitation concentration index (PCI). Another feature that directly correlates with the concentration of precipitation is the rain erosivity (Modified Fournier Index MFI). The aim of this study is to investigate the PCI and MFI indices and map their spatial variations. The Modified Fournier and precipitation Concentration indices were calculated using rainfall data from 55 meteorological stations located in Khuzestan province. To produce the spatial variations map, point information is converted to regional using geostatistical and deterministic methods. The results indicated that the ordinary and simple Kriging with Gaussian type have highest accuracy for interpolation of the PCI and MFI indices, respectively. According to the spatial variation map of the PCI, the highest values of that index are seen in the southern region and the lowest values are in the north and northeast of the Khuzestan province. The PCI values ranged between 20 and 31 indicating severe seasonality. The MFI values vary from 49 to 224 in which the highest values are for the northeast region of the province and the lowest ones are for the south and southwest zones. Generally Rainfall limited in a certain months.alues are for the northeast region of the province and the lowest ones are for the south and southwest zones. Generally Rainfall limited in a certain months.

Zonation of quality of drinking water sources is necessary for Water Management in Arid and Hyper Arid areas. In this research, spatial variations of quality characteristics of water (EC, Na, K, Mg, Ca, NO3, SO4, Alkalinity, Cl, TH and TDS were investigated in one-year period (2015-2016) based on the data collected from 55 drinking deep wells of Yazd Plain. In order to evaluate and select the best method of interpolation was used Simple kriging, Ordinary kriging and Inverse Distance Weighted and RMSE. Zoning maps showed that groundwater of Charkhab and Yazdgerd respectively are in the Southeast and Northwest of study area, which are affected by flow of the Mehriz and Taft river, that are higher quality than the middle part of study area.The changes in the main indicators of quality such as TDS are from less than 500 to more than 2500 mg/lit and EC from less than 700 to more than 3,500 micromhos/cm that this achievement reflects the need for utilization management and preparation of drinking water with best quality to enter the network. Also the wells in the center of study area such as 16 Silo, 12 Dehno, 13 Dehno and 24 Dehno in terms of quality parameters such as TDS, TH, EC and Cl have more than double the national standard limit, that is recommended to remove them or adjustment operation of wells in drinking water network.

Climate scientists have concluded that the air temperature of earth’s surface warmed to 0.6 during the 20th century, and that warming induced by increasing concentrations of greenhouse gases accompanied by changes in the precipitation and hydrologic cycle. Monthly, seasonal and annual precipitation trends of meteorological stations have been analyzed and interpolated in the northern part of Iran for three periods (30, 40, 50 years). The Mann-Kendall trend test was applied to examine the monthly precipitation data. Significant positive and negative trends at the 90, 95, and 99 percent confidence levels were detected for numerous stations. The detected trends were spatially interpolated by applying the inverse distance weighted (IDW) interpolation method. The amount of RMSE for different variables obtained using IDW less than 0.2, indicating the effectiveness of this method in the interpolation of rainfall. The results showed that the trend of variation, both in terms of time and spatial is different in the study area, as has experienced downward trend in cold season and upward trend in warm season which indicates the importance of climate change in the study area. The spatial variation trends results for mean annual precipitation of 30 and 40 years period showed that the east of region have downward trend and the west of region have the upward trend. For the 40-years period, downward trend of station nearly are situated in eastern part of region, as downward trend at 90% confidence level are evident for Talar basin. The western part of region experienced upward trend at 99% confidence level especially in Chaloos-roud basin. The results of this study indicated that the region has experienced the severe climatic change which the better understanding of the climate variation and its impacts on water recourses, natural environment and other related sector are necessary.

One of the most important consequences of soil erosion is sedimentation. The detection and surveying the type and amount of sediment is important because of its effects on irrigation networks, environment, and reservoirs. This study was performed in order to investigate the suspended sediment changes under the influence of rainfall erosivity cycle in Sorkhab- Keshvar watershed in the Lorestan province. For estimating the suspended sediment, we used a combination of sediment rating curve of mean loads within discharge classes and average daily discharge data. Monthly and semi-monthly EI30-based erosivity indices were calculated in 13 rain gauging stations inside and around of the watershead. In the next stage, erosivity maps based on kriging interpolation were produced in order to calculate the average monthly and semi-monthly rain erosivities. After calculating monthly and semi-monthly sediment loads, their correlations with corresponding erosivities were investigated. The results show that the maximum and minimum of suspended sediment occured in Azar and Shahrivar (Iranian month equal to Nov. 22 to Dec. 21 and Agu. 23 to Sep. 22) with the values of 246216 and 1272 ton, respectively. Also, the maximum and minimum of rainfall erosivity occured in Dey (Iranian month equal to Dec. 22 to Jan. 20) and summer respectively with the values of 182 and 0.01 MJmm ha-1 h-1.The highest values of semi-monthly erosivity and sediment observed in second half of Dey and Azar (Iranian month equal to Dec. 22 to Jan. 20 and Nov. 22 to Dec. 21) with the values of 104 MJmm ha-1 h-1 and 148241 ton, respectively.Sediment and erosivity showed two peaks in the watershed, two peaks of sediment occured in Azar and Farvardin (Iranian month equal to Nov. 22 to Dec. 21 and Mar.21 to Apr. 20) and for the reosivity occurred in Dey and Farvardin (Iranian month equal to Dec. 22 to Jan. 20 and Mar.21 to Apr. 20).