جستجوی مقالات مرتبط با کلیدواژه « ordinary kriging » در نشریات گروه « آبخیزداری، بیابان، محیط زیست، مرتع »

One of the main factors of the reducing agricultural production is the irrigation water salinity. Mazandaran province is one of the most important citrus-producing area in Iran, where the groundwater used for supplying the irrigation water in citrus orchards of the province. The main objective of this paper was to determine map spatial and temporal variations of groundwater salinity (EC) in the coastal strip of Mazandaran province with an area of 8252 km2. The collected data of 300 wells of the study area were measured by Mazandaran Regional Water Authority for 9 consecutive years and defined for ArcGIS 10.7.1 software as the average ECs for each 6 months.

EC maps were obtained by ordinary kriging (OK) for each 6-month periods from and the beginning of 2012 to the end of 2020, by using ArcGIS 10.7.1 software. According to the derived empirical function of the effect of EC on the citrus yield (Y=100-13(EC-1.4)). According to this function, ECs of 1.40, 2.17, 2.94 and 3.71 dS/m, corresponding to relative yields of 100, 90, 80 and 70% were selected, respectively. Thereby, areas belonging to the classes of 100%, 90-100%, 80-90% and <70% were outlined. In addition, the Mann–Kendall test and Sen’s slope were used to project future changes.

The result of EC maps indicated that the salinity of groundwater increases from west to east of the province. The Mann-Kendall test result showed a significant temporal trend of the size of the area below the <70% yield (EC >3.71 dS/m) and 100% (EC <1.40 dS/m), presenting that the salinity of groundwater can be a concern for citrus orchards in the coastal strip of Mazandaran province. The equation given by Sen’s slope estimator denoted that if this trend is continuing, the area under 100% yield will reach to zero in 2021 and the yield of citrus in the coastal strip will reach below 70% at the latest by 2047.

This study has shown that the salinity of groundwater was increasing in the eastern part over the time and it covered a wider area around the Miankaleh lagoon, which may be due to the leakage of the lagoon to the groundwater aquifer in that area. The reduction of groundwater quality over the time can be attributed to two factors: reduced rainfall in recent years and digging illegal wells and subsequently consumed extraction of wells in the region. Taken together, it is suggested that the wells in the area will be exploited completely controlled to prevent the reduction trend of its quality.

One of the important problems of water resources studies is estimating the spatial distribution of rainfall based on point rainfall observations. In the present study, interpolation methods including definitive mathematical methods including Inverse Distance Weighting(IDW)  and Radial Basis Functions (RBF), Global polynomials, and local polynomials, and Kriging and Cokriging geostatistical methods using Geographic Information System (GIS) to estimate monthly and annual rainfall in the Namak lake watershed were evaluated. Spatial distribution analysis was carried out in the period 1988-1999 to 2006-2007 water year. In this study, in order to compare interpolation methods in iso-rainfall of the Namak lake watershed, 110 meteorological stations into the mentioned watershed with the statistical period of 30 years were used. The results showed that overall in annual rainfall according to Root Mean Square (RMSE) index, Cokriging and Kriging geostatistical methods in rank one and two, respectively have the best rainfall estimation. Therefore, Cokriging method with RMSE of 63.68mm had the best estimation. RBF, Cokriging and Kriging methods had also in the best estimation for   monthly rainfall data. In general, geostatistical methods have been overestimated in monthly and annual rainfall estimation in the Namak lake watershed.

Regional analysis is the stability method to improve estimates of flood frequency, which has become one of the dynamic sectors in hydrology and the new theories are testing, constantly. Application of geostatistical method is an innovation in this field for regional flood analysis.This technique is based on the interpolation of hydrological variables in the physiographical space instead of using common geographical space. However, the hydrological, climatological and physiographical information of 38 river basin information of watersheds inside of Mazandaran province were obtained and Canonical Kriging method was used for regional flood analysis whit return periods of 10, 20, 50 and 100 years. The Canonical Correlation Analysis was used to design physiographic space by the geomorphoclimatical variables affecting the flood. The Gaussian model had the best fit to semi-variogram model in all return periods and the geostatistical method of Ordinary Kriging was used for regionalization. Results evaluated using Jack Knife mutual procedure and the five statistical indexes. The performance of NASH was obtained over than 0.9 in all of return periods, which implies the accurate and acceptable predictions of flood in ungauged basins. The other indicators led to satisfying results, too. According to the results of relative statistical indicators accuracy regional estimates improves as long as return periods increase. These results showed that application of Canonical Kriging method is effective and practical approach for regional flood analysis.

One of the most important parameter of soil erosion is soil erodiblity. Soil erodiblity (K-USLE) plays the main role in mathematical function of erosion models as well as Universal Soil Loss Equation (USLE). In recent paper, the objectives are including determination the spatial pattern of soil erodibility of USLE in part of Yazd Ardakan plain as a typical arid plain of center of Iran and comparison and evaluation the kinds of kriging interpolation procedure consist simple, ordinary and universal. Soil was sampled in 37 points from 0-10 cm soil depth in almost uniform distribution by random classification sampling pattern. Infiltration was determined by double ring method. Soil samples were analyzed in laboratory with standard methods consist grain size distribution and organic matter. Soil erodiblity was calculated by method of Wischmeier and Smith. Normality test was carried out. ArcGIS 9.3 was applied to determine the spatial pattern of K-USLE and the effective parameters using simple, ordinary, universal and Inverse Distance Weighting (IDW) interpolation methods. MAE (Mean Absolute Error), MBE (Mean Bias Error), RMSE (Root Mean Square Error) and RI (Relative Improvement) were calculated for evaluation the interpolation procedures. K-USLE were varied at about 0.0055±0.0072, 0.005±0.0037 and 0.0173±0.0133 ton.hr/MJ.mm in fine, medium and coarse gravely plains, respectively. The result shows Gaussian model was fitted on ordinary kriging as well as spherical was applied for simple and universal kriging. In addition, the result shows the ordinary kiriging have the minimum bias in compare to the else interpolating procedures. Finally, the kriging procedures are more accurate and precision than IDW.

The Soil erodibility Factor is one of the important and effective factor that is used for estimating water erosion by USLE model and its different versions. The main topic of this paper is the spatial distribution of K factor and knowing its effective factors. One of the factors which is usually ignored for K stimation,is the desert pavement density as the natural factor of soil conservation. The other purpose of this paper is the estimating of the variations of K factor due to landuse change, land plowging and combination with sub-layers soil. For doing that in cross-section of Yazd-Ardakan plain (including Coarse grain plain, Medium grain plain and fine grain plain) with different pavement density, by random classification sampling method, the soil samples were collected in 37 points from 0-10 cm of surface soil in each parts of plain. The rate of infiltration was measured by using double ring method. Desert pavement cover in to conditions (natural and disturbed) was measured using the exist scales in Munsell’s notebook. Grain size distribution by hydrometry method and organic matter by standard methods were analyzed. Then the spatial pattern of variations by ArcGIS9.3 and Surfer9.0 softwares and zonation by kriging method for K factor and its effective parameters were determined. To evaluate the obtained semivariogram, some statistical indices like MAE(Mean Absolute Error), MBE(Mean Bias Error), MSE(Mean Square Error), RMSE(Root Mean Square Error) and determination coefficient were applied. The results show that in fine grain plains due to decreasing the desert pavement until less than %20, it can not be considerd as the conservation factor and the relation between pavement desert and K factor is not sufficient. On the other hand, in Coarse grain and Medium grain plains (that desert pavement is more than %50), the K factor lies in the low until very low. The conservative role of desert pavement in Coarse grain and Medium grain plains that by combining pavement, the K factor is increased 10 times more than natural conditions. The results of model fitting on spatial changes show that Gaussian model is the best. Totally, ordinary kriging is suitable method for spatial variability description of K and its effective factors.