نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
Soil erodibility is one of the key indicators of soil quality and is directly influenced by soil physical properties. This study aimed to Assessment soil physical quality indices and identify the most sensitive indicators across different soil erodibility classes in the semi-arid region of Zanjan Province, Iran. For this purpose, 20 soil physical properties were measured at 68 sampling points, including rangeland (45 points), cropland (13 points), orchard (8 points), and forest (2 points) land uses. Soils were classified into three erodibility classes based on the Williams erodibility factor. Differences among physical properties across erodibility classes were assessed using one-way ANOVA. Soil physical quality indices (SQI) were calculated using linear and nonlinear scoring functions with both simple and weighted approaches for the total dataset (TDS) and minimum dataset (MDS), and were compared using discriminant analysis. Principal Component Analysis (PCA) identified three main components explaining 83% of the total variance. In the TDS, sand content, mean weight diameter of primary particles (MWDp), and mean weight diameter of dry aggregates (MWDdry) had the highest weights (W = 0.12, p < 0.01). In the MDS, sand content was the most important factor (W = 0.57, p < 0.01), followed by wet mean geometric diameter of aggregates (GMDwet) and MWDdry (W = 0.32 and 0.10, respectively). These findings indicate that, in the TDS, primary particle-size distribution, particularly sand content, together with aggregate size, especially MWDdry, were the main determinants of soil physical quality based on the soil erodibility index, whereas in the MDS, sand content was the dominant indicator. Discriminant analysis indicated that the best soil physical quality index for erodibility assessment was the weighted linear scoring method based on the TDS (SQI-2). Overall, soil structure stability and PSD were identified as effective tools for monitoring soil physical quality.
کلیدواژهها English
Soil physical quality is a key component of soil quality and plays an important role in ecosystem sustainability and land productivity. Soil erodibility is one of the most important indicators of physical soil quality, reflecting soil susceptibility to erosion processes. However, comprehensive assessments of soil physical quality indices in relation to soil erodibility have received limited attention in semi-arid regions of Iran. Accordingly, the overall objectives of this study were to: (1) quantitatively and comprehensively evaluate soil physical quality indices using discriminant analysis based on the Total Data Set (TDS) and the Minimum Data Set (MDS), employing both linear and non-linear scoring methods across different soil erodibility classes defined by the Williams erodibility factor; and (2) identify the most sensitive soil quality indicators under both datasets in selected soils of the semi-arid region of Zanjan Province, Iran.
This research was conducted in the semi-arid region of Zanjan. In order to quantitatively evaluate the physical quality indicators of soil in different erodibility classes, the sampling operation was designed to be a comprehensive representation of the soil conditions in the studied semi-arid region. Sampling points were determined by considering criteria such as land use type, vegetation cover, soil texture, and information obtained from soil maps and field surveys. In total, disturbed soil samples (depth 0 to 60 cm) and undisturbed soil samples (depth 0 to 30 cm) were collected from 68 selected points. A total of 20 physical properties were measured for this research. To measure soil permeability in the field, experiments were conducted using the double-ring infiltrometer method. The cumulative water infiltration was measured at time intervals of 0, 0.5, 1, 2, 3, 5, 10, 15, 20, 30, 45, 60, 80, and 90 minutes until steady-state infiltration was reached. Based on the obtained data, water infiltration indices including Cumulative Infiltration (CI), Final Infiltration Rate (FIR), and Mean Infiltration Rate (MIR) were calculated. The particle size distribution of particles larger than 0.05 mm was obtained using the dry sieving method according to the standard guidelines of Gee & Bauder (1986). Particles smaller than 0.05 mm were measured by the hydrometer method based on the method of Yavari et al. (2021). Furthermore, the standard methods presented by Gee & Bauder (1986) were used to measure particles larger than 2 mm. Bulk density was measured using a metal cylinder (Culley, 1993). Electrical conductivity and soil reaction were measured in the saturated paste extract (Thomas, 1996), along with organic matter (Walkley & Black, 1934) and calcium carbonate equivalent (Page et al., 1982). The weighted mean diameter (MWDp) and geometric mean diameter (dg) of primary soil particles were calculated using the results of the primary particle size distribution. The wet sieving method was used to determine aggregate stability, and dry sieving was used for the mean weight diameter of aggregates. For this purpose, the weighted mean diameter (MWDwet and dry) and geometric mean diameter (GMDwet and dry) of aggregates were measured in both wet and dry conditions. Soil Structure Stability Index (SSI), Degree of Compactness (DC), Relative Aggregate Stability Index (SI), Overall Aggregate Stability (OAS), and Effective Infiltration Depth (EID) were also calculated.
Soil erodibility (K) was determined using the method of Williams (1990). In order to reduce data dimensions and identify suitable properties for developing a soil quality index, Principal Component Analysis (PCA) was performed on the Total Data Set (TDS) to derive the Minimum Data Set (MDS). For this purpose, the number of selectable components was determined based on the scree plot and the break point of the eigenvalue curve (Askari & Holden, 2015; Brejda et al., 2000). The SQI index was calculated using two methods Simple and Weighted and with two scoring approaches Linear and Non-linear for both data sets: the TDS and the MDS. To examine the correlation between soil physical properties, the Pearson correlation matrix was calculated. To better understand the internal structure of the data and reduce the dimensions of correlated variables, Principal Component Analysis (PCA) was utilized. Finally, the comparison and significance of differences in the obtained SQI index values were evaluated using discriminant analysis. Data analysis, graphing, and comparison of means were performed using Excel (2016) and SPSS (2022) software.
Among the 20 measured properties, 10 showed significant differences among soil erodibility classes (P < 0.05), including sand and silt contents, MWDp, dg, MWDdry, MWDwet, GMDwet, SSI, SI, and EID. Principal Component Analysis identified three principal components explaining 83% of the total variance. Sand content, GMDwet, and MWDdry were selected as the most representative indicators of soil physical quality in the MDS. Sand content showed the highest contribution (weight = 0.57), followed by GMDwet (0.32) and MWDdry (0.10). Discriminant analysis demonstrated a strong capability of SQI for differentiating soil erodibility classes, with the first discriminant function explaining 92.48% of the total variance. Among the evaluated methods, the weighted SQI based on the TDS with linear scoring exhibited the highest discrimination coefficient (33.04).
The studied soils were predominantly classified as moderately to highly erodible. Soil physical quality decreased with increasing erodibility, highlighting the close relationship between soil degradation and erosion susceptibility. Indicators related to particle-size distribution and aggregate stability were identified as the most influential factors controlling soil erodibility and soil physical quality. The results demonstrate that soil quality indices, particularly those based on weighted approaches, can serve as effective tools for monitoring soil degradation and supporting sustainable soil management in semi-arid regions.
This study was conducted with the equipment support of the Department of Soil Science and Engineering and with the financial and moral support of the Vice Chancellor for Research of the University of Zanjan. Financial support for this research was provided by the Faculty of Agriculture, University of Zanjan, in the form of a graduate thesis grant for the first author and research grants for the co-authors.
All authors contributed substantially to the study. They participated in the design and implementation of the research, data collection, statistical analyses, interpretation of results, manuscript preparation, revision, and final approval of the manuscript. The contributions of the authors in this thesis-derived manuscript were approximately as follows:
- First Author (Graduate Student): Sample preparation, conducting experiments, data collection, performing calculations, statistical analyses, interpretation of results, and preparation of the manuscript draft.
- Second Author (Supervisor): Research design, supervision of the research process, evaluation of results, manuscript revision, and finalization of the manuscript.
- Third Author (Advisor): Research supervision, manuscript review, and revision
This manuscript is the result of field research and direct writing by the authors. No generative artificial intelligence or AI-assisted technologies were used at any stage of the research or manuscript preparation. The authors take full responsibility for the content of the manuscript.
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.
The authors would like to express their sincere gratitude to the Vice Chancellor for Research of the University of Zanjan for the financial support provided for this study.
This research was approved by the Department of Soil Science and the Faculty of Agriculture Council of the University of Zanjan in accordance with the relevant regulations. The authors confirm that all ethical principles related to conducting and publishing scientific research have been fully observed.
The authors declare that there is no conflict of interest regarding the publication of this manuscript.
