جستجوی مقالات مرتبط با کلیدواژه "kriging" در نشریات گروه "مهندسی آب"

Precipitation is one of the basic elements of Hydrometeorological studies. Due to the limited number of rain-gauging stations and the lack of meteorological stations in highland area, the use of satellite rainfall products as an effective tool in predicting the regional spatial distribution of precipitation data has attracted the attention of researchers. But its disadvantage is the high estimation error of rainfall estimation, which requires accuracy evaluating before using. For this purpose, based on the rainfall data of 21 meteorological stations of Mazandaran province from 1998-2018, the performance of TRMM data and two interpolation methods of kriging and inverse distance weighting were investigated. The results showed that contrary to the proper correlation of TRMM data with observed data, this network has a high bias error. For example, in the case of annual rainfall data, the network bias error reached 70 mm, which is approximately 30% of the annual error. The modification coefficients of TRMM data were found between 0 and 2, that most of the coefficients were higher than one, which indicates the TRMM data in Mazandaran mostly has an underestimation error. The comparison of modified TRMM with the interpolation methods showed that using the modified network instead of interpolation methods in estimation of rainfall data reduces the mean square error of annual rainfall from 237 to 186 mm.

Accurate spatial estimation of precipitation plays a key role in many hydrological modelling, water resources planning and agricultural management studies. In order to estimate high-resolution precipitation in the current research, an estimation model based on PRISM framework considering Digital Elevation Model (DEM) and other spatial attributes is developed and applied to Sefidroud basin during the years 2000-2015. In the first step, the monthly results were compared with modified Inverse Distance Weighted (IDW) as a benchmark method. Considering both models’ degrees of freedom, the parameters are calibrated with Genetic Algorithm in annual time scale and the obtained parameters are utilized to estimate model monthly cross validation error. According to the monthly results, both models had roughly same statistical performance in estimating precipitation at the selected rain gauges. In spite of similar statistical performance of the models, the spatial distribution of precipitation provided by the PRISM based method is more consistent with topographic pattern and existing evidences. In the next step the proposed model’s ability to estimate mean monthly precipitation is compared with ordinary kriging method and according to the results, in wet months the developed model and in dry months kriging method represents more optimal results. According to small amount of summer precipitation, PRISM based approach is considered to be a better tool for spatial interpolation of precipitation than kriging.

Design of the rain gauge network to increase accuracy and cost decrease in precipitation prediction value needs to find optimum location of the rain gauge station. Most precipitation prediction errors is due to location of the rain gage station that optimum design of the rain gauge stations can reduce precipitation prediction error. In this study used geostatistic methods named Kriging and cokriging to optimization of the Khuzestan rain gauge station network. 49 rain gauges used for 6 daily rainfall. After determination of the best model of semivariograms and the best geostatistic method, in the first step, the rain gauge which precipitation prediction in them has appropriate accuracy determined with the help of other rain gauge network. Result showed that kriging had more accuracy and most daily rainfalls was fitted with gaussian model. In the next step, using assessment of network prediction error value which remain from first step, the points that needs new rain gage determined. Finally7 unnecessary rain gage stations determined and 5 new rain gages added to the network.

Investigation and prediction of climatic extreme values especially temperature is necessary for identifying climatic bottlenecks and opportunities in an area. The increase in greenhouse gas concentrations due to human activities has resulted in global warming and consequently changes in climate extreme indices. For conducting this research, the daily meteorological data of the Iranian Meteorological Organization, including mean temperature, minimum temperature, maximum temperature data for the Khuzestan synoptic stations, for a period of 30 years (1987-2016) were used. Calculation of temperature indices as defined by 1ETCCDMI Expert Group was estimated using RClimdex software. Mann-Kendall nonparametric test was also used to investigate the trend of climate change. Regular and simple kriging method with different models was used to estimate the spatial statistics of temperature data. According to the obtained results, the conventional kriging method with Logical Quadratic Model 2 with the least error rate was selected. The effect of changing the fit indices on the mean monthly temperature ranges from 250 to 314 km. The results of temperature analysis showed that warm indices had an increasing trend which was significant for indices such as summer days, tropical nights, warm days and nights at 5% level. Cold indices have a decreasing trend over the period under study. The results of temperature analysis correspond to the warming of the area and show the decrease in intensity and frequency of cold days and nights.

The spatial variations of rainfall are due to differences and climatic variations, and to produce spatial variation maps and regional average estimates, it is necessary to interpolate the amount of precipitation between stations. In the present research, geostatistical and deterministic interpolation methods were developed for the spatial distribution map of the annual rainfall in Isfahan province. The data of 20 meteorological stations of Isfahan province were used during the period 1987 to 2017. Results show higher accuracy of geostatistical interpolation method. From this, the cokriging method has the most precision with the exponential model and the auxiliary variable of the station's height. According to the spatial distribution map of annual rainfall, which was prepared by the cokriging method, the highest mean annual rainfall (Pt) was found in south and west of Isfahan province. The lowest rainfall in the east and north of Isfahan province is due to the presence of dry plains and climates.

In this research, the goal of evaluating the accuracy of interpolation methods is for prediction of spatial distribution of some of the quality indices of groundwater in Urmia plain. In the beginning, the qualitative data of 20 wells in the year 2001-2014 were analyzed. The Kolmogorov-Smirnov test showed that the data were not normal and therefore the conversion of the box-cox was used to normalize, Then, using the GIS software, the best semivariogram model was fitted to the spatial structure of the data. The results showed that for qualitative parameters, circular, spherical, and exponential models are the best model for semivariogram. Then, their variation was study with different interpolation methods such as Kriging and Inverse Distance Weight with power of one to three. Then, the zoning maps of qualitative parameters were drawing with the most appropriate method in the ArcGIS software. Plain aquifer was also examined for Wilcox and Schoeller standards for agricultural and drinking purposes. The results of the Wilecox standard showed that 40% of the wells in the plain had brine and available for use in agriculture, and the results of the Schoeller diagram showed the good and acceptable quality of the groundwater for drinking water.

Groundwater quality assessment and site monitoring of these waters is very important for nitrate pollution. In this regard, the spatial variations of groundwater nitrate were investigated using interpolation methods and mapping of these changes. Made This cross-sectional descriptive-analytic study was conducted on drinking water sources in villages in Dezful. For this purpose, 20 drinking water wells were used according to the standard method and 80 samples for 4 season were analyzed. The results showed that the circle Kriging method with less error value than inverse distance weighting, spline and nearest neighborhood methods can perform the optimal zoning for the plain. The summer season has the lowest amount of nitrate and winter. Finally, by investigating the zoning map, it was determined that the eastern and central western regions had the highest amount of nitrate and the north of the plain had a desirable nitrate status.

Groundwater is known to be main resources of agricultural ýA change in groundwater quality due to wrong groundwater withdrawal management may ýbe caused to deteriorate other water resources. Quality assessment and precise monitoring ýof the groundwater table is of a great importance. so create a proper network for groundwater quality monitoring wells to determine the minimum number of samples saves costs as well. In this research, a ýmethod was used based on Kriging concept and probability function of normal distribution ýto evaluate the performance of Mashhad plain's observatory well. This approach is based on ýa percentage of region's area criteria with Ap accuracy compliance. first, spatial structure ýof the sampling well's chlorine concentration was extracted by analyzing them using grid ýsemi-variogram and then observation well network was evaluated using algorithm of the acceptance probability method. The results showed that the performance of the existing network or the acceptance accuracy at the probability of 80 percent to 72/1 percent is obtained. The results also showed that of 80 wells about the analysis, using only 35 wells carefully observed in the probability level service network eighty percent against all existing wells and the remaining wells 45 impact of very little increase in the accuracy of the estimation of the spatial variations of chlorine in the aquifer of Mashhad. As a result by performing optimization by the method described for the current network and with the 45-point displacement or removal, the number 16 proposed points increases the acceptance accuracy from 72/1% to 100%.

In order to use groundwater for agriculture, qualitative studies should be carried out. One of the most commonly used methods for evaluating is Wilcox method. In this research, the quality of groundwater of Golgir plain was investigated using 10 village wells for agricultural use with Wilcox chart. The EC and SAR parameters were evaluated and the samples were transferred to the Wilcox chart. The results showed that all specimens were placed on the C2S1 floor, which are in a small salinity range suitable for farming, so there is no limit to use in agriculture. Also, spatial mapping of EC and SAR parameters was provided by kriging geostatistical grounding method. The results showed that due to low parameters of parameters, there is no specific pattern in spatial changes and there is no need for special management and action, and underground water is the whole range that can be used in agriculture.

Due to the shortage of surface water resources and the increased demand for water, supply of drinking water from underground resources is very important. To use groundwater for drinking, it is important to evaluate the qualitative proportion of these resources and to plan the spatial distribution of quality parameters should be considered in order to manage its location. This article aims to investigate the quality of groundwater for drinking water. For this purpose, 10 rings of the wells were used in this plain for the parameters of TDS, total hardness, chlorine, sodium, calcium, magnesium, bicarbonate and sulfate. These parameters were evaluated based on the Schuler charts and were interpolated using ARC GIS software and analyzed by Kriging geostatistical method and the spatial distribution of the parameters in the plain was investigated. According to the Schuler chart, most of the parameters in most samples are placed on a good and acceptable floor and are suitable for drinking. Also, due to the qualitative changes in the groundhandling maps of Golgi Plain, the distribution of parameters in the plain has no specific pattern and almost groundwater is suitable for the area of the plain for drinking

Drought is a natural hazard with climatic nature. It caused by the precipitation anomalies and irregularities. This paper examines the phenomenon of drought and its spatial and temporal changes in Khuzestan province. In order to determine the severity of the drought, it used Standardized Precipitation Index (SPI) for spatial analysis benefits and temporal communication creation between occurrences of drought. In this study, 48 rain gauges and synoptic stations data from Khuzestan province have been used in years (1982-2014). Zoning maps of Standardized precipitation index (SPI) was drawn using ordinary kriging interpolation method during the study period and the driest and wettest years were identified. The 1999 and 2008 was severe drought years and extreme wet occurred in 1992. According to the results, 1999, 2007 and 2008 were years with the largest percentage of the area of drought and years 1991, 1992, 1997 and 2001 with the highest percentage of wet.

Optimization of monitoring network is the best possible process for decision-making among existing networks. Considering economical objectives and for reducing the cost of monitoring, optimization approach is based on decreasing monitoring stations in this study. Using an algorithm based on entropy and nitrate pollution index, optimizing the monitoring network was conducted with 287 wells in the period of 2002 to 2011. First, the average of each station rank was calculated based on statistical years. Then, some models were proposed for the network entropy in terms of stationnumbers and time. After fitting the best network entropy model, the results showed that 111 wells are sufficient as groundwater quality monitoring stations for Mashhad aquifer. In order to approve the proposed network, 111 randomnetworks were selected in each year, and by comparing the entropy of those networks to the proposed network, the performance of selected network was confirmed. Also, the selected network performance was confirmed for the future of Mashhad aquifer.

One of the most important techniques in climatology studies are various interpolation methods. Moreover, in order to prepare integrated maps and predict unknown values, interpolation methods are needed. Estimating the groundwater level in most parts of the area is costly and difficult and applying interpolation methods can solve this problem. Thus, to draw groundwater maps, one can use different Piezometric wells to estimate other regions by interpolation methods. In this study, ten Pizometric wells of Bazargan Keshmeshtape area located in West Azerbaijan have been used to interpolate groundwater level in 2011 and 2012. Then, using GS software, Kriging, advanced interpolation and Inverse distance methods, the groundwater level was interpolated in two years. The results showed that the groundwater level had the same distribution pattern in these two years and Kriging and advanced methods showed the same results with the most regression coefficients. Using these methods, groundwater level can be interpolated and using the interpolated maps, the water level of groundwater can be estimated in the areas in is no Piezometric well. This results can help to find the best positions to dig wells.

Existence of saline sediments in most plains of Iran affects the salinity of underground waters in these areas. Invasion of saline water into fresh water zones and uncertainty in saline-fresh water boundary cause some problems in management and exploitation of underground water resources.In this research, using geoelectrical technique, various alluvial layers in Khir plain were distinguished on the basis of their different resistivity. By geostatistical and variography methods the spatial correlation of resistivity data were investigated. The resistivity in unsampled area and their probability of saline water existence were estimated. The results showed that the maximum variation in resistivity exists in northeast-southwest direction and ordinary and indicator kriging methods can demonstrate a reasonable estimation of saline-fresh water boundary in this area.

Soil pollution, in general, and heavy metals contamination, in particular, are problems of modern life. In this context, surveying contaminated soils becomes essential for keeping away human food chains from dangerous heavy metals. This study was conducted to evaluate soil Cd-contamination in part of the arable lands in Bizaa, west of Shiraz. Soil samples were randomly collected from an area of 800,000 m2, prepared, and analyzed for Cd concentration. Analysis of variograms showed that the structural component moderately dominated the randomized component and that the range of special dependency was 2300 m. Ordinary kriging was used for mapping and estimation variances were calculated. Based on the Cd contamination standard threshold (3mg/Kg), the map thus prepared indicated that about 80 percent of the study area was polluted and that the hot point was located in the southern stretches of the study area. The non-existence of industrial activities and the absence of point Cd distribution indicated that soil pollution in the area must have been caused by human activities such as farming. The excessive consumption of chemical fertilizers, especially phosphates, in agricultural activities and sludge application seem to be the main suspects of soil Cd contamination. Further investigation is needed into the agricultural history of the area to determine the main causes of Cd contamination in this area.

Rainfall is a key factor for water resources management. Raingauge networks with accurate measurement and appropriate density are required for the estimation of the rainfall in ungauged sites in watersheds. This study aimed at assessing a method based on kriging and normal probability distribution function for evaluating raingauge network in GorganRud watershed (114000 km2). The concept is based on criterion that named percentage of the total area with acceptable accuracy (Ap). Spatial variability of annual rainfall is analyzed using dimensionless variogram then using a sequential algorithm 33 raingauges in the network is evaluated. Results showed the base network for annual rainfall comprises 21 gauges and 12 remaining gauges have little contribution to estimate areal rainfall in the watershed. After optimization the non-based raingauges reduced to 7 gauges and will be more effective to estimate areal rainfall in whole of watershed. Furthermore, Results showed that simplifying and using GIS software by developing a toolbox will make it easier for evaluating a raingauge network.

The water resources are limited and the groundwater levels decrease due to water abuse. This causes the lack of water problem in some regions of Iran. Therefore the hydrological and statistical methods needed for prediction of the water levels at a given location, region or times. The groundwater levels are variables changing by space and time, and their data can be considered as a spatial-temporal data set. Modeling of the correlation structures of such data is a major tool, for the prediction of unknown water level at some specified locations and times. This correlation structure is specified by fitting suitable variogram or covariogrammodels to the data. In this article some nonseparable covariance models were briefly reviewed. Then the spatial-temporal variogram of underground water levels were estimated as product and sum-product models. Finally the underground water levels of Birjand region was predicted using the universal kriging and give the contour map at the selected time. Moreover the prediction precision of different models were compared numerically.

Drought monitoring is quite important in planning for drought mitigation schemes. Drought indices are normally used for monitoring purposes. However, the indices are calculated at sites and it is required to estimate the spatial distribution of drought in the forms of maps. Geostatistical methods are among such tools that may be applied for preparing spatial distribution maps. In this research, several geostatistical methods including Kriging, Cokriging, TPSS with and without secondary variables as well as weighted moving average (WMA) were assessed with respect to derivation of drought index maps. Drought monitoring and mapping was conducted based on SPI and EDI indices using data of 43 rain gauge stations within Tehran province. The results indicated that although Kriging was the most accurate method, WMA provided reasonable accuracy blended with more efficient computer time, a major consideration in monitoring systems.