Soil science
Z. Mosleh Ghahfarokhi; A. Azadi
Abstract
Introduction
Soil properties play a crucial role as they determine the soil's suitability for different types of plant growth, ecosystems, and biota functioning. They have a significant impact on nutrient cycling, carbon sequestration, and soil management. Digital Soil Mapping (DSM) is a process aimed ...
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Introduction
Soil properties play a crucial role as they determine the soil's suitability for different types of plant growth, ecosystems, and biota functioning. They have a significant impact on nutrient cycling, carbon sequestration, and soil management. Digital Soil Mapping (DSM) is a process aimed at delineating soil properties. Soil sampling for DSM serves as a fundamental step in improving prediction accuracy and is crucial for incorporating variability in terms of environmental covariates. Conditioned Latin Hypercube (CLH) sampling is a technique utilized to generate a sample of points from a multivariate distribution conditioned on one or more covariates. Numerous researchers (Ramirez-Lopez et al., 2014; Adhikari et al., 2017; Zhang et al., 2022) have endorsed this approach in their studies, following its inception by Minasny and McBratney in 2006. However, there has been limited research to date on the impact of the Latin hypercube method's random sample selection process on the accuracy of resulting maps. Hence, the central question remains: Is the Latin hypercube sampling method, which is currently widely adopted, always a dependable approach in this field?
Materials and Methods
The study area covers longitudes 50°35'47'' to 51°29'' east and latitudes 31°36''31'' to 32°15'48'' north in Borujen city, Chaharmahal, and Bakhtiari Province. The region, with an average elevation of 2338 meters above sea level, receives an annual rainfall of 250 millimeters and maintains an average temperature of 11.5 degrees centigrade. In this investigation, inherited data from soil studies were utilized, consisting of 250 samples distributed across the study area. In this research, the studied characteristics included percentage of equivalent calcium carbonate, clay, and soil organic carbon at a depth of 0 to 30 cm. Land component variables were extracted using the Alus Palsar digital elevation model with a spatial resolution of 12.5 meters. In the initial stage, digital maps of equivalent calcium carbonate, clay, and soil organic carbon were generated using the support vector machine method. The modeling process proceeded until a highly accurate model was achieved, with the root mean square error percentage (RMSE%) being less than 40. The Latin hypercube approach was utilized for sample design, with 500 repetitions in this study. After selecting sampling points for each run using the Latin hypercube method, these points were mapped onto a detailed map, and the corresponding feature values were retrieved. The final map was created based on the extracted points. Subsequently, the latin hypercube approach was employed to generate soil property maps for each selected dataset. Validation was conducted using criteria such as the coefficient of explanation, root mean square error, and root mean square error in multiple iterations to ensure the accuracy of the generated maps.
Results and Discussion
The results distinctly illustrates the varied selection of sampling positions with each implementation of the Latin hypercube method. It is important to note that there may be some overlaps in different implementations. Consequently, the primary question arises: Is a one-time execution of the Latin hypercube sufficient for selecting study points? The findings indicate that the support vector machine model achieves satisfactory accuracy for all the examined characteristics. In the studied area, the environmental factors such as slope and elevation were identified as a significant predictors for estimating percentage of equivalent calcium carbonate.
Conclusion
In the present study, the accuracy of the latin hypercube method was assessed for selecting sampling location for digital soil mapping endeavors in Chaharmahal and Bakhtiari Province. Given the impracticality of collecting numerous field samples to evaluate the soil sampling method, this research aimed to employ simulation methods based on highly accurate maps for this purpose. The results indicate that the different outputs of the Latin hypercube method influence the accuracy of modeling, although this effect is also influenced by the specific feature under investigation and the extent of its variability within the study area. Considering that the Latin hypercube method is based on the principle that samples are randomly selected in each class of environmental parameters, it is suggested that future studies using this method should account for this principle. Adequate consideration should be given, and the selection of sampling locations should rely on multiple implementations of the Bhattacharya distance method to ensure robustness and reliability.
abolfazl azadi; M. Baghernejad; N. A. Karimian; S. A. Abtahi
Abstract
Introduction: Phosphorus (P) is the second limiting nutrient in soils for crop production after nitrogen. Phosphorus is an essential nutrient in crop production. Determination of forms of soil phosphorus is important in the evaluation of soil phosphorus status. Various sequential P fractionation procedures ...
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Introduction: Phosphorus (P) is the second limiting nutrient in soils for crop production after nitrogen. Phosphorus is an essential nutrient in crop production. Determination of forms of soil phosphorus is important in the evaluation of soil phosphorus status. Various sequential P fractionation procedures have been used to identify the forms of P and to determine the distribution of P fractions in soils (Chang and Jackson, 1957, Williams et al., 1967; Hedley et al., 1982), but are not particularly sensitive to the various P compounds that may exist in calcareous soils. A Sequential fractionation scheme has been suggested for calcareous soils by which three types of Ca-phosphates i.e. dicalcium phosphate, octacalcium phosphate, and apatite could be identified (Jiang and Gu, 1989). These types of Ca-phosphates were described as Ca2-P (NaHCO3-extractable P), Ca8-P (NH4AC-extractable P) and Ca10-P (apatite type), respectively. In this study, the amount and distribution of soil inorganic phosphorus fractions were examined in 49 soil samples of Fars province according to the method described by Jiang and Gu (1989).
Materials and Methods: Based on the previous soil survey maps of Fars province and According to Soil Moisture and Temperature Regime Map of Iran (Banaei, 1998), three regions (abadeh, eghlid and noorabad) with different Soil Moisture and Temperature Regimes were selected. The soils were comprised Aridic, xeric, and ustic moisture regimes along with mesic, and hyperthemic temperature regimes. 49 representative samples were selected. The soil samples were air-dried and were passed through a 2-mm sieve before analysis. Particle size distribution was determined by hydrometer method (Gee and Bauder 1996). Also, Cation exchange capacity (CEC; Sumner and Miller 1996), calcium carbonate equivalent (Loeppert and Suarez 1996), organic matter content (Nelson and Sommers 1996), and pH by saturated paste method (Thomas 1996) were determined . Inorganic phosphorus sequential fractionation scheme was preformed according to the method described by Jiang and Gu (1989). Olsen-P fraction that was extracted by NaHCO3 (Olsen and Sommers 1982) was regarded as P-availability index. Also, Total-P by perchloric acid (HClO4) digestion (Sparks; 1996) and organic P were determined.. All of the extraction procedures were performed in duplicate and the amounts of P were colorimetrically measured in the supernatants by the ascorbic acid method of Murphy and Riley (1962).The relationships between forms of P and some of the soil properties were established using correlation method.
Results and Discussion: The chemical data of the soils showed that soils were calcareous with CCE range between 9.94 to 74.27 % ( average 51.10%) and pH range between 7.02 to 8.36 (average 7.85). Also, the amounts of CEC were between 5.35 to 29.39 cmol (+) kg-1(average 16.68 cmol (+) kg-1). The results showed a wide range in content of Phosphorus fractions. The amount of total Phosphate ranged from 301.87 to 1458.68 mg kg-1 with an average of 626.63 mg kg-1 . Calcium Phosphate ranged from 147.83 to 666.90 mg kg-1 with an average of 324.79 mg kg-1, that comprised 85 and 52 percent of inorganic and total Phosphorus, respectively. The amount of Fe-P ranged from 0.38 to 59.18 mg kg-1 with an average of 7.56 mg kg-1 that comprised 13.64 and 8.34 percent of inorganic and total Phosphorus, respectively. Also, the amount of Al-P ranged from 20.49 to 123.09 mg kg-1 with an average of 52.28 mg kg-1that comprised 1.97 and 1.21 percent of inorganic and total Phosphorus, respectively. The results of correlation study showed that available Phosphorus was significantly correlated with Ca2-P, Ca8-P, Al-P, Ca10-P, and Pt (total phosphorus). So, in calcareous soils, awareness of soil properties and phosphorus fractions and their relationships are important for evaluation of phosphorous status in soil and understanding of soil chemistry that influence soil fertility.
Conclusion: The relative abundance of inorganic P forms were in order of Ca10 – P > Ca8- P > Al –P> Ca2-P> Fe-P. Among the inorganic P fractions, Ca-P had the highest value and varied from 147.83 to 666.90 mg kg-1, which accounted for 53 percent of the sum of P fractions, occurred in H2SO4 extractable P fraction, which is attributed to primary Ca–P minerals, indicating their weak weathering nature. Also, correlation study showed that available Phosphorus was significantly correlated with Ca2-P, Ca8-P, Al-P, Ca10-P, and Pt. This result indicate that these fractions probably can be used by plant.
