Showing 9 results for Interpolation
M. H. Mahdian, N. Ghiasi, S. M. Mousavy Nejad,
Volume 7, Issue 1 (4-2003)
Abstract
Point data of weather stations are not important in and by themselves. Therefore, it is necessary to change these point data into regional information. Undesirable distribution of weather stations and their data deficiency hinder the direct determination of the regional information, unless sufficient data in the study area could be provided. Providing extra data using the geostatistical methods is practical, scientific, simple and quick, but adopting a suitable method is the basic question. The objective of the present study is to find a suitable method to estimate monthly rainfall in the central region of Iran. In this regard, the methods of kriging (ordinary kriging, log-kriging, co-kriging), weighted moving average (WMA, with the power of 1 to 5), thin plate smoothing splines (TPSS, with the power of 2 and 3 and with covariable) were used. Cross validation technique was used to compare these methods.
Based on the variography analysis, the range of influence of monthly rainfall in the central region is about 450 km. The results show that TPSS, with the power of 2 and with elevation as a covariable, was the most accurate method to estimate monthly rainfall. In addition, it is preferable to use the selected interpolation method in the sub-basins with homogeneous climates instead of considering the whole region.
G Golmohamadi, S Maroufi, K Mohamadi,
Volume 12, Issue 46 (1-2009)
Abstract
In this research, using geographic information system (GIS) and different geostatistical methods including the kriging and co-kriging (ordinary, simple and universal) as well as the radial basis functions, the spatial distributions of runoff coefficient were evaluated in Hamedan province. To this end, the annual runoff were calculated in 18 existing hydrometery stations and another 11 auxiliary points, using digital elevation model (DEM) and 11 years available data of the stations. The performance criteria for evaluating the methods were mean absolute error (MAE), mean bias error (MBE), root mean square error (RMSE), and general standard deviation (GSD) along with the cross validation examination. A high regression between the runoff coefficient and watershed average slope was selected as auxiliary variable. The results showed that the runoff coefficient of the region changes between 3.5 and 85%. The findings also indicated that the universal co-krigings with spherical semi-variogram model had better performance with the values of MBE (-0.0014), MAE (0.036), RMSE (0.054) and GSD (20.152). The universal and simple kriging with spherical model were equal in runoff estimation of the region and were ranked as the second methods to this propose.
S.h. Tabatabaei, M. Ghazali ,
Volume 15, Issue 57 (10-2011)
Abstract
The accuracy and precision of the input data in decision making is important. Error originates from data collection, data entry, storage, retrieval and analysis of the data which consequently result in model error. One of the errors in spatial analysis is interpolation error. The main objective of this research was the suitability assessment of some interpolation methods for estimation of groundwater level in Farsan-Joneghan and Sefiddasht aquifers, located in Beheshtabad catchment, Chaharmahl-Va-Bakhtiyari province, Iran. Cross-validation technique was employed for the determination of each method's error. The RMSE and MAE indices were used for the error comparison. The results show that the modified Shapard's method with an MAE=6 and RMSE=7 was the most accurate for interpolation of groundwtaer level in the Sefiddasht aquifer. The inverse distance power method with MAE=6 and RMSE=9 was the best interpolation method for Farsan-Jonaghan aquifer. The Kriging with MAE=7 and RMSE=12 is the second best method in these aquifers. The moving average, minimum curvature and polynomial regression procedures produce the maximum error in the aquifers (17
M. Amini, A. Forghani,
Volume 19, Issue 71 (6-2015)
Abstract
Any change in the characteristics of air, soil, water and food that adversely affect the health of the ecosystem, activities of human and other organismsis called contamination. Heavy metal uptake by plants depends on the type and concentration of metalin soil, its bioavailability, and plant species. The use of new sciences such as geostatistics is useful for fast and simple determination of soil and leaf contamination risk. This study studied the amount of soil and leaves of Platanus orientalis contamination in order to map the lead (Pb) and cadmium (Cd) concentration in Rasht city using a geostatistic method. To achieve the goal, 126 samples of surface soil (0-30 cm) and 76 leaf samples (Platanus orientalis) were collected from city streets. Total concentrations of lead and cadmium in the soils and leaves were determined, and clay, silt and sand particle percentage, organic matters, and soil pH were measured. Average concentrations of elements in terms of mg/kg were as follows: soil’s Lead: 86.62, soil’s Cadmium: 0.6, leaf’s Lead: 8.99. For soil Pb and Cd and leaf Pb, spherical model yielded a better fit in the experimental variogram in GS+ program by using trial and error method. According to the spatial structure, Kriging and IDW estimators were used for interpolation. Kriging estimation was mapped using Arc GIS 9.2 software.
R. Mirzaei, K. Rahimi, H. Ghorbani, N. Hafezimoghades,
Volume 19, Issue 73 (11-2015)
Abstract
Determining the spatial distribution of different contaminants in soil is essential for the pollution assessment and risk control. Interpolation methods are widely used to estimate the concentrations of the heavy metals in the unstudied sites. In this study, the performances of interpolation methods (inverse distance weighting, local polynomials and ordinary Kriging and radial basis functions) were evaluated to estimate the topsoil contamination with copper and nickel in Golestan Province. 216 surface soil samples were collected from Golestan province, and their Cu and Ni concentrations were measured. Soil contamination was determined using different interpolation methods. Cross validation was applied to compare the methods and estimate their accuracy. The results showed that all the tested interpolation methods have an acceptable prediction accuracy of the mean content for soil heavy metals. RBF-IMQ and IDW1 methods had the lowest RMSE, whereas RBF-TPS method with the largest RMSE estimated a larger size for the polluted area. The greater the weighting power, the larger the polluted area estimated by IDW. Compared with the ‘‘sample ratio over the pollution limits” method, the polluted areas of Cu and Ni were reduced by 8.38% and 6.14%, respectively.
M. A. Amini, G. Torkan, S. S. Eslamian, M. J. Zareian, A. A. Besalatpour,
Volume 23, Issue 1 (6-2019)
Abstract
In the present study, we used 27 precipitation average monthly data from synoptic, climatologic, rain-guage and evaporative stations located in Zayandeh-Rud river basin for the period of 1970-2014. Before interpolating, the missing data in the time series of each station was reconstructed by the normal ratio method. Also, for the data quality control, the Dickey-Fuller and Shapiro-Wilk tests were used to check the data stationarity and normality. Then, these data were interpolated by six interpolation methods including Inverse Distance Weighting,
Natural Neighbor, Tension Spline, Regularized Spline, Ordinary Kriging and Universal Kriging; then each method was evaluated using the cross-validation technique with MAE, MBE and RMSE indices. The results showed that among the spatial interpolation methods, Natural Neighbor method with MAE of 0.24 had the best performance for interpolating precipitation among all of the methods. Also, among Ordinary Kriging, Universal Kriging, Spline and
Inverse Distance Weighting methods, respectively, Exponential Kriging with MAE 0.54, Quadratic Drift Kriging with MAE of 0.5, Tension Spline with the MAE of 0.54 and Inverse Distance Weighting with the power of 4 with MAE of 0.57 had the least error compared to other IDW methods.
M. Ghandali, K. Shayesteh, M. Sadi Mesgari,
Volume 23, Issue 1 (6-2019)
Abstract
Determination of water quality is an essential issue in water resources management and its monitoring and zoning should be considered as an important principle in planning. In this study, in order to investigate the quality of groundwater resources (springs, wells and qanats) in Semnan watershed, first, the water quality index for drinking and agricultural purposes was obtained by means of measuring SO4, Cl, Na, Mg, PH, EC, SAR, TDS in 55 groundwater sources. For calculating the parameters weight in WQI, the fuzzy hierarchy analysis process was used with the Chang's development analysis. Due to the lack of sampling points for zoning of the entire area, regarding the existence of EC data for the majority of groundwater resources used in this catchment (354 sources), as well as the high correlation (Adjusted R2=0.99) between WQI with EC, the mentioned indexes of other resources were estimated based on the regression relationship with EC. To analyze the spatial distribution and monitor the zoning of the groundwater quality, the ArcGIS version 10.3 and Geostatistical method such as simple Kriging and ordinary Kriging were used; additionally certain methods including Inverse distance weighting and Radial Basis Function were utilized. The performance criteria for evaluating the used methods including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), %RMSE and R2 were used to select the appropriate method. Our results showed that the ordinary Kriging and Radial Basis Function were the best methods to estimate the groundwater quality.
E. Moradi, D. Namdar Khojasteh,
Volume 24, Issue 4 (2-2021)
Abstract
Wind erosion is one of the environmental problems worldwide, particularly in arid and semi-arid areas of Iran. Different methods and models have been proposed to measure and monitor wind erosion in the recent years. One of the accurate models for measuring f wind erosion is the USEPA model. The purpose of this study was to evaluate the quantification of wind erosion with the USEPA model and the comparison of different interpolation methods for drowsing high-precision soil erosion mapping. For this purpose, 50 samples from 0-30 depth were taken from the study area. Based on the analysis of the physical properties of the soil, including the distribution of the primary and secondary particle sizes, climatic parameters such as evaporation and transpiration, rainfall, wind speed and also, the vegetation and topography characteristics of the area, the erosion rates of Q, Q30 and Q50 were measured. Interpolation methods including general kriging, IDW, LPI and RBF were compared. The results showed that the highest erosion emission rate of Q50 was 39 ton ha-1. The highest and lowest erosion rates for the Q30 index were 0.060 and 2.694 ton ha-1, respectively; for the Q index, the highest and lowest erosion rates were 0.009 and 0.055 ton ha-1, respectively. The results also showed that the IDW method for the Q50 index with the minimum error rate (RMSE) values of 3.94 and the mean absolute error (MAE) with the valueof 1.89 had the best performance among the studied models. The LPI model Q had the best performance with the lowest error (0.0086) and absolute absolute error (0.0021).
K. Shirani, R. Arfania, Y. Fereydoni, R. Naderi Samani, M. Shariati, M. Faizi,
Volume 26, Issue 4 (3-2023)
Abstract
Groundwater is always considered one of the important water resources, especially in arid and semi-arid regions of the world, such as Iran. In recent decades, it has decreased drastically due to excessive use. The objective of this study was to determine the best interpolation method and evaluation of the spatiotemporal variations for the groundwater level in the Sahneh-Biston plain of Kermanshah province during three decades from 1991 to 2020. At first, four Gaussian, linear, spherical, and power semi-variograms were obtained for observations. Then, the best semi-variogram and interpolation methods were selected among the evaluated methods for zoning the groundwater level in the region. The lowest value of the sum of RMSE, MBE, and MAE error criteria and the highest coefficient of determination (R2) between observations and estimates in all three decades and the average of the entire period were calculated and considered to evaluate the most appropriate semi-variogram and interpolation methods for spatial distribution. The results showed that the ordinary kriging method with Gaussian semi-variogram is the best method to estimate the groundwater level in the Sahneh-Biston plain. The average difference between the minimum and maximum groundwater levels based on the observation wells of the study area and the zonation method is from 1279 to 1372 meters and 1289 to 1409 meters during the studied period time, respectively. The groundwater level is placed in more depth with the proximity to the central and southern regions. The maximum decrease and increase of groundwater level variations have been 12 and 19 meters during three decades, respectively. Also, the underground water level variations during these three decades showed that both the second and third decades compared to the first decade and the third decade compared to the second decade have increased in more than 50% of the region. This increase can be caused by the optimum management and water use in these years. Therefore, groundwater level monitoring provides effective help for experts and users in planning and optimal management of groundwater for the sustainable development of water resources.
