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E.E.R. 2022, 12(3): 147-164 |
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Seyed Hosseini Asl S A, Rezaei H, Shahbazi F, Oustan S. The Role of Sampling Pattern on the Efficiency of Soil Salinity Monitoring Map in Shamlou Region. E.E.R. 2022; 12 (3) :147-164
URL: http://magazine.hormozgan.ac.ir/article-1-690-en.html
URL: http://magazine.hormozgan.ac.ir/article-1-690-en.html
Department of Soil Science and Engineering, Faculty of Agriculture, University of Tabriz, Tabriz , hosseinrezaei@tabrizu.ac.ir
Abstract: (1743 Views)
1- Introduction
Sustainable management of soil and land resources requires the identification of factors affecting their development or degradation. Accurate and reliable determination of the distribution of soil and landscape properties is the basis of such identification. In this regard, it is necessary to prepare continuous location maps. In soil surveying, soils are generally collected by a point-by-point sampling method and soil properties between these points are estimated by interpolation methods. Soil salinity is one of the most common challenges in arid and semi-arid regions of Iran, which leads to land degradation by declining soil quality. Therefore, monitoring soil salinity is needed to overcome the aforementioned problem. The accuracy and precision of Kriging, as one of the major geostatistical methods, depend on the size, distribution as well as density of soil samples. Due to the use of these maps in soil planning and management for the future, their accuracy and precision are of great importance. This study aims to evaluate the role of grid sampling patterns on the quality and efficiency of final soil salinity maps.
2- Methodology
The study was conducted in Shamlou region with an area of about 155 ha. It is located in Heris County, East Azerbaijan Province comprising abandoned cultivated lands. The dominant soils across the study area were Inceptisols and Aridisols. Based on the main objective of this research, five sampling patterns were designed: I) uniform grids of 100 m; II) uniform grids of 200 m; III) offset grids of 200 m; IV) rectangular grids (100×200 m) with vertical direction; V) rectangular grids (100×200 m) with the horizontal direction. A total of 155 disturbed samples (0-20 cm) were taken in the study area. All the collected samples were transferred to the laboratory for analysis. After providing the soil extracts, ECe was measured. The Kriging method was also employed to predict the spatial distribution of soil salinity according to the above-mentioned patterns. The accuracy of prepared maps in a classified mode was also evaluated. Finally, the efficiency of each map was evaluated using the Average Size Delineation (ASD), Index of Maximum Reduction (IMR), and Delineation Density (DD) criteria.
3- Results
The maximum ECe in the study area was reported to be 36.5 dS.m-1. The provided maps based on the use of various sampling patterns showed that the salinity of the west part of the area was higher than the east one. Geostatistical analysis revealed that the spherical model can be identified as the best-fitted model for a 100×200 m rectangular grid with vertical direction, while the exponential model was the best one for the rest patterns. The results demonstrated that the least and the highest values of nugget and range were observed for 100 and 200 m uniform grids, respectively. Since the index of nugget/sill illustrates the spatial dependence of soil salinity, it was found that management has no role in the spatial distribution of salinity using all studied patterns except 100×200 m rectangular grid with the vertical direction. The t-test results indicated that there is no significant difference between the predicted and actual values. According to the R2 values, the best sampling pattern was found to be uniform grids of 100 m, followed by, rectangular grids with horizontal direction, offset grids, rectangular grids with vertical direction and uniform grids of 200 m. The next step was to assess the maps (with a scale of 1:13337) efficiency indices. It was found that the maximum location accuracy, minimum legible delineation (MLD), optimum legible delineation (OLD) and optimum legible area (OLA) were 1.33 m, 7115 m2, 1.6 cm2 and 2.84 ha, respectively. The lowest average size delineation (ASD) was found for uniform grids of 100 m while the highest one was for rectangular grids with vertical directions patterns. A similar trend was also observed in terms of index maximum of reduction (IMR). Furthermore, the optimum delineation density (DD) was found to be 4.59 for the offset grids of 200 m pattern.
4- Discussion & Conclusions
The results showed that sampling point distribution had a more important role than sampling point density in selection of the optimum model for interpolation. In terms of nugget and range, this role was demonstrated in an inverse manner. Since the nugget/sill index (taken by all studied sampling patterns in the same results) revealed that salinity has a strong spatial distribution, the density and distribution of sampling points did not play an important role. Although the distribution of sampling points had a role in the accuracy of interpolation, the sampling point density was more effective. The results showed that preparation of high resolution maps with many details does not always require a large density of sampling, but in patterns with the equal densities, the efficiency of maps depends on the distribution of sampling points. Also, there was no direct relation between optimum delineation density and specific density as well as distribution of sampling points. Therefore, prior to the selection of suitable distribution for soil sampling patterns, it is recommended to find the optimum sampling density for the project.
Sustainable management of soil and land resources requires the identification of factors affecting their development or degradation. Accurate and reliable determination of the distribution of soil and landscape properties is the basis of such identification. In this regard, it is necessary to prepare continuous location maps. In soil surveying, soils are generally collected by a point-by-point sampling method and soil properties between these points are estimated by interpolation methods. Soil salinity is one of the most common challenges in arid and semi-arid regions of Iran, which leads to land degradation by declining soil quality. Therefore, monitoring soil salinity is needed to overcome the aforementioned problem. The accuracy and precision of Kriging, as one of the major geostatistical methods, depend on the size, distribution as well as density of soil samples. Due to the use of these maps in soil planning and management for the future, their accuracy and precision are of great importance. This study aims to evaluate the role of grid sampling patterns on the quality and efficiency of final soil salinity maps.
2- Methodology
The study was conducted in Shamlou region with an area of about 155 ha. It is located in Heris County, East Azerbaijan Province comprising abandoned cultivated lands. The dominant soils across the study area were Inceptisols and Aridisols. Based on the main objective of this research, five sampling patterns were designed: I) uniform grids of 100 m; II) uniform grids of 200 m; III) offset grids of 200 m; IV) rectangular grids (100×200 m) with vertical direction; V) rectangular grids (100×200 m) with the horizontal direction. A total of 155 disturbed samples (0-20 cm) were taken in the study area. All the collected samples were transferred to the laboratory for analysis. After providing the soil extracts, ECe was measured. The Kriging method was also employed to predict the spatial distribution of soil salinity according to the above-mentioned patterns. The accuracy of prepared maps in a classified mode was also evaluated. Finally, the efficiency of each map was evaluated using the Average Size Delineation (ASD), Index of Maximum Reduction (IMR), and Delineation Density (DD) criteria.
3- Results
The maximum ECe in the study area was reported to be 36.5 dS.m-1. The provided maps based on the use of various sampling patterns showed that the salinity of the west part of the area was higher than the east one. Geostatistical analysis revealed that the spherical model can be identified as the best-fitted model for a 100×200 m rectangular grid with vertical direction, while the exponential model was the best one for the rest patterns. The results demonstrated that the least and the highest values of nugget and range were observed for 100 and 200 m uniform grids, respectively. Since the index of nugget/sill illustrates the spatial dependence of soil salinity, it was found that management has no role in the spatial distribution of salinity using all studied patterns except 100×200 m rectangular grid with the vertical direction. The t-test results indicated that there is no significant difference between the predicted and actual values. According to the R2 values, the best sampling pattern was found to be uniform grids of 100 m, followed by, rectangular grids with horizontal direction, offset grids, rectangular grids with vertical direction and uniform grids of 200 m. The next step was to assess the maps (with a scale of 1:13337) efficiency indices. It was found that the maximum location accuracy, minimum legible delineation (MLD), optimum legible delineation (OLD) and optimum legible area (OLA) were 1.33 m, 7115 m2, 1.6 cm2 and 2.84 ha, respectively. The lowest average size delineation (ASD) was found for uniform grids of 100 m while the highest one was for rectangular grids with vertical directions patterns. A similar trend was also observed in terms of index maximum of reduction (IMR). Furthermore, the optimum delineation density (DD) was found to be 4.59 for the offset grids of 200 m pattern.
4- Discussion & Conclusions
The results showed that sampling point distribution had a more important role than sampling point density in selection of the optimum model for interpolation. In terms of nugget and range, this role was demonstrated in an inverse manner. Since the nugget/sill index (taken by all studied sampling patterns in the same results) revealed that salinity has a strong spatial distribution, the density and distribution of sampling points did not play an important role. Although the distribution of sampling points had a role in the accuracy of interpolation, the sampling point density was more effective. The results showed that preparation of high resolution maps with many details does not always require a large density of sampling, but in patterns with the equal densities, the efficiency of maps depends on the distribution of sampling points. Also, there was no direct relation between optimum delineation density and specific density as well as distribution of sampling points. Therefore, prior to the selection of suitable distribution for soil sampling patterns, it is recommended to find the optimum sampling density for the project.
Received: 2021/11/7 | Published: 2022/09/21
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