干旱区生态环境知识资源中心(Arid): Spatial variability of soil variables using geostatistical approaches in the hot arid region of India

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DOI	10.1007/s12665-024-11737-5
	Spatial variability of soil variables using geostatistical approaches in the hot arid region of India
	Nogiya, Mahaveer; Moharana, Pravash Chandra; Meena, Roshanlal; Yadav, Brijesh; Jangir, Abhishek; Malav, Lal Chand; Sharma, Ram Prasad; Kumar, Sunil; Meena, Ram Swaroop; Sharma, Gulshan Kumar; Jena, Roomesh Kumar; Mina, Bansi Lal; Patil, Nitin Gorakh
通讯作者	Nogiya, M
来源期刊	ENVIRONMENTAL EARTH SCIENCES
ISSN	1866-6280
EISSN	1866-6299
出版年	2024
卷号	83 期号:14
英文摘要	Geostatistics tools like ordinary kriging was utilized to investigate the spatial variation in soil reaction (pH), electrical conductivity (EC), soil organic carbon (OC), calcium carbonate (CaCO3), available nitrogen (N), available phosphorus (P), available potassium (K), DTPA-extractable copper (Cu), zinc (Zn), manganese (Mn), and iron (Fe) in hot arid region of Western India. For this, total 132 surface soil samples (0-20 cm depth) were obtained with GPS coordinates from the study area. The study's finding showed that EC showed the highest variability (390%) whereas soil pH showed the least variability (3.72%). The best variogram fit model in ordinary kriging was selected on the basis of largest R2 values. For pH, EC CaCO3, N, K, Zn, and Fe, an exponential model imparted the best variogram fit, while a Gaussian model imparted the best variogram fit for OC, P, and Mn. Semi-variogram analysis (nugget/sill ratio) revealed that EC (0.25), CaCO3 (0.072) and N (0.027) were weakly spatial dependent, whereas pH (0.37), OC (0.456), P (0.598), K (0.70), Mn (0.57) and Fe (0.59) were moderately spatial dependent. However, Cu (1.0) and Zn (0.78) were strongly spatial dependent. The largest goodness-of-prediction criterion (G) values were found for the exponential model for soil pH, EC, CaCO3, N, K, Zn, and Fe while the largest G values were found for the Gaussian model for OC, P, and Mn. The exponential and Gaussian models of ordinary kriging, were able to map the spatial variations in investigated soil-variables.
英文关键词	Geostatistics Ordinary kriging Exponential model Gaussian model Goodness-of-prediction criterion(G)
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001263479400002
WOS关键词	ELECTRICAL-CONDUCTIVITY ; FERTILITY STATUS ; ALLUVIAL SOILS ; ORGANIC-CARBON ; MAP QUALITY ; MANGANESE ; ZINC ; IRON ; MICRONUTRIENTS ; PLANTATIONS
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/403561
推荐引用方式 GB/T 7714	Nogiya, Mahaveer,Moharana, Pravash Chandra,Meena, Roshanlal,et al. Spatial variability of soil variables using geostatistical approaches in the hot arid region of India[J],2024,83(14).
APA	Nogiya, Mahaveer.,Moharana, Pravash Chandra.,Meena, Roshanlal.,Yadav, Brijesh.,Jangir, Abhishek.,...&Patil, Nitin Gorakh.(2024).Spatial variability of soil variables using geostatistical approaches in the hot arid region of India.ENVIRONMENTAL EARTH SCIENCES,83(14).
MLA	Nogiya, Mahaveer,et al."Spatial variability of soil variables using geostatistical approaches in the hot arid region of India".ENVIRONMENTAL EARTH SCIENCES 83.14(2024).