Understanding Spatial Distribution Variability of Top Soil Organic Carbon in Cultivated Soils of India as Influenced by Rainfall, Elevation and Temperature

ABSTRACT Assessment and mapping of the spatial pattern of soil organic carbon (SOC) distribution in cultivated areas is vital for degradation monitoring, land use classes, carbon credits, crop production, agricultural management practices, and climate action. The distribution of SOC is influenced by several factors including elevation (E), rainfall, and temperature. We, in this study, assessed the spatial pattern of SOC distribution in cultivated areas and evaluated the relationship of SOC with average annual rainfall (AAR), elevation, and average annual maximum temperature (AAMT) of India. Altogether, 254,236 georeferenced and representative top soil (0 to 15 cm depth) samples were collected from the study area, processed, and analyzed to estimate SOC content. The SOC varied from 0.01% to 5.25% (mean ± SD 0.64 ± 0.42) with the coefficient of variation value of 65.6%. SOC had an exponential best‐fitted model with moderate (nugget/sill ratio of 0.52) spatial dependence. The ordinary kriging‐based interpolation map had varied patterns of SOC distribution in different states, agro‐ecological regions, and crop‐growing areas of India. Around 7.50%, 25.5%, and 43.5% of the area had SOC content of ≤ 0.25%, > 0.25% to ≤ 0.50%, and > 0.50% to ≤ 0.75%, respectively. The content of SOC in 10.8% and 12.7% of the area was > 0.75% to ≤ 1.00%, and > 1.0%, respectively. The SOC was significantly and positively correlated with E ( r = 0.535 p ≤ 0.01). It was significantly and negatively correlated with AAR ( r = −0.070 p ≤ 0.01) and with AAMT ( r = −0.620 p ≤ 0.01). The % variance explained by E toward SOC content was found to be 29% ( R 2 = 0.2864). However, the % variance explained by AAMT toward SOC was 38% ( R 2 = 0.3844). The generated SOC thematic maps may be used as references for local and regional scale policymaking and adoption of suitable soil‐crop management strategies for effective SOC management and to achieve improved soil health, land degradation neutrality, sustainable crop production and food security, carbon credits, and climate change mitigation.

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Publication Details

Journal
Land Degradation and Development
Published
2025-11-06
DOI
https://doi.org/10.1002/ldr.70252
Citations
1
Primary Topic
Soil Carbon and Nitrogen Dynamics
Type
article
Field-Weighted Citation Impact
1.19
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article

Understanding Spatial Distribution Variability of Top Soil Organic Carbon in Cultivated Soils of India as Influenced by Rainfall, Elevation and Temperature

S. S. Dhaliwal, Sanjib Kumar Behera, A. K. Nayak, Arvind Kumar Shukla et al.
1 citations
Land Degradation and Development
Soil Carbon and Nitrogen Dynamics
1.19
article

Understanding Spatial Distribution Variability of Top Soil Organic Carbon in Cultivated Soils of India as Influenced by Rainfall, Elevation and Temperature

S. S. Dhaliwal, Sanjib Kumar Behera, A. K. Nayak, Arvind Kumar Shukla, Vimal Shukla, M.L. Jat, Rahul Mishra, Ch. Srinivasarao
article en
1 citations

Abstract

ABSTRACT Assessment and mapping of the spatial pattern of soil organic carbon (SOC) distribution in cultivated areas is vital for degradation monitoring, land use classes, carbon credits, crop production, agricultural management practices, and climate action. The distribution of SOC is influenced by several factors including elevation (E), rainfall, and temperature. We, in this study, assessed the spatial pattern of SOC distribution in cultivated areas and evaluated the relationship of SOC with average annual rainfall (AAR), elevation, and average annual maximum temperature (AAMT) of India. Altogether, 254,236 georeferenced and representative top soil (0 to 15 cm depth) samples were collected from the study area, processed, and analyzed to estimate SOC content. The SOC varied from 0.01% to 5.25% (mean ± SD 0.64 ± 0.42) with the coefficient of variation value of 65.6%. SOC had an exponential best‐fitted model with moderate (nugget/sill ratio of 0.52) spatial dependence. The ordinary kriging‐based interpolation map had varied patterns of SOC distribution in different states, agro‐ecological regions, and crop‐growing areas of India. Around 7.50%, 25.5%, and 43.5% of the area had SOC content of ≤ 0.25%, > 0.25% to ≤ 0.50%, and > 0.50% to ≤ 0.75%, respectively. The content of SOC in 10.8% and 12.7% of the area was > 0.75% to ≤ 1.00%, and > 1.0%, respectively. The SOC was significantly and positively correlated with E ( r = 0.535 p ≤ 0.01). It was significantly and negatively correlated with AAR ( r = −0.070 p ≤ 0.01) and with AAMT ( r = −0.620 p ≤ 0.01). The % variance explained by E toward SOC content was found to be 29% ( R 2 = 0.2864). However, the % variance explained by AAMT toward SOC was 38% ( R 2 = 0.3844). The generated SOC thematic maps may be used as references for local and regional scale policymaking and adoption of suitable soil‐crop management strategies for effective SOC management and to achieve improved soil health, land degradation neutrality, sustainable crop production and food security, carbon credits, and climate change mitigation.

Land Degradation and Development
Indian Institute of Soil Science (IN), Indian Council of Agricultural Research (IN), Jawaharlal Nehru Krishi Vishwa Vidyalaya (IN), Indian Agricultural Research Institute (IN), Punjab Agricultural University (IN)
Openalex Percentile: Top 16%
Soil Carbon and Nitrogen Dynamics
1.19
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