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A geospatial approach to assess climate change impact on soil organic carbon in a semi-arid region

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Abstract

The changes in the atmosphere and climate influence soils by disturbing the functioning of hydrologic and biogeochemical cycles, specifically that of Carbon (C). The impact of the climatic change on soil organic carbon (SOC) stocks over a semi-arid region of India (Medak district, Telangana) was assessed using remote sensing-based indices and geostatistical modeling. The global soil organic carbon (GSOC) stocks (0–30 cm depth) at 1 km spatial resolution and a set of environmental variables like Normalized difference vegetation index (NDVI), Net primary productivity (NPP), slope, elevation and various climate parameters such as rainfall, temperature, etc., were used to estimate the SOC stocks in current and future (2050 and 2070) climate change projections using regression kriging (RK) technique. The results of the study indicate that among the environmental covariates rainfall was the predominant factor that controls the SOC stocks in the study region. The current SOC stock in the study area was estimated as 25.4 Tg in top 0–30 cm depth. The future (2050 and 2070) SOC stocks were predicted using climate parameters of three Global Circulation Models (GCMs); namely CCSM4, HadGEM2-AO, and HadGEM2-ES. Results show a reduction in SOC stocks in 2050 and 2070 due to the projected climate change in the study region. The projected decrease in total SOC stocks varies from 1.12 to 4.93 and 0.45 to 4.49 Tg by 2050 and 2070 respectively. The uncertainty associated with the prediction of the current stock of SOC was 8.44%. The uncertainties associated with the SOC prediction in various future climate change scenarios for the year 2050 and 2070 were in the range of 8.83–10.48% and 8.15–10.26% respectively.

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Abbreviations

C:

Carbon

CI:

Confidence interval

DEM:

Digital elevation model

DSM:

Digital soil mapping

FAO:

Food and agriculture organization

GCM:

Global circulation model

GEFSOC:

Global environment facility soil organic carbon

GHG:

Greenhouse gases

GIS:

Geographical information system

GSOC:

Global soil organic carbon

GWRK:

Geographically weighted regression kriging

IPCC:

Intergovernmental panel for climate change

MAE:

Mean absolute error

ME:

Mean error

MLR:

Multiple linear regression

MODIS:

Moderate resolution imaging spectroradiometer

NDVI:

Normalized difference vegetation index

NPP:

Net primary productivity

OK:

Ordinary kriging

R2 :

Coefficient of determination

RCPs:

Representative concentration pathways

RK:

Regression kriging

RMSE:

Root mean square error

RS:

Remote sensing

SD:

Standard deviation

SOC:

Soil organic carbon

SPSS:

Statistical package for the social sciences

SRTM:

Shuttle radar topography mission

WGS 1984:

World Geodetic System 1984

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Acknowledgements

The first author is grateful to Outreach Facility, National Remote Sensing Centre, Jeedimetla, Hyderabad for providing necessary help and support to carry out the research work.

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Authors and Affiliations

  1. Alternate Hydro Energy Center, Indian Institute of Technology, Roorkee, Uttarakhand, 247667, India

    Jagriti Jain

  2. Soil and Land Resources Assessment Division, National Remote Sensing Centre, Indian Space Research Organization, Balanagar, Hyderabad, 500037, India

    Tarik Mitran

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  1. Jagriti Jain
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Jain, J., Mitran, T. A geospatial approach to assess climate change impact on soil organic carbon in a semi-arid region. Trop Ecol 61, 412–428 (2020). https://doi.org/10.1007/s42965-020-00100-x

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