Abstract
Soil organic matter (SOM) plays an important role in maintaining soil quality, agriculture productivity, ecosystem functionality, as well as in environment moderation. Besides quantity, the composition of soil organic matter is vital for understanding the mechanism of carbon (C) sequestration in soils. A number of methods, with several variants, have been proposed to measure and characterize SOM. Conventional methods of soil organic carbon (SOC) measurement are not only laborious and time-consuming but also suffer from issues related to spatial variability. In the last few decades, several new methods including in situ techniques have been developed to minimize the uncertainties associated with the conventional procedures. Besides being more sensitive, the in situ techniques provide the possibility of repetitive and sequential measurements for spatial and temporal evaluation of soil C stock on a large scale. However, these methods are still evolving and pose some procedural limitations. Models have been used to overcome some of the problems associated with measurements and to upscale point measurements at different levels of spatial aggregation. Organic matter turnover models have been used to predict C sequestration potential of soils, assess and identify appropriate land-use and best management practices for C sequestration and to predict climate change effects on SOC. However, application of these models is constrained because of the lack of detailed spatial data, leading to the development of protocols for reducing input data requirements. In this chapter, we trace the developments in measurement and modelling organic matter dynamics in soils.
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Benbi, D.K., Nisar, S. (2020). Developments in Measurement and Modelling of Soil Organic Carbon. In: Ghosh, P., Mahanta, S., Mandal, D., Mandal, B., Ramakrishnan, S. (eds) Carbon Management in Tropical and Sub-Tropical Terrestrial Systems. Springer, Singapore. https://doi.org/10.1007/978-981-13-9628-1_23
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