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University of Adelaide (2011)

Modelling organic carbon turnover in salt-affected soils

Setia, Raj Kumar

Titre : Modelling organic carbon turnover in salt-affected soils

Auteur : Setia, Raj Kumar

Grade : Doctor of Philosophy (PhD) 2011

Université de soutenance : University of Adelaide

Résumé
Salinity and sodicity are major constraints for crop production in arid and semi-arid regions of the world. Salt-affected soils cover 6.5% of the total land area of the world. Since the global soil carbon (C) pool is greater than the atmospheric and biotic pool combined, changes in soil organic matter content will affect atmospheric carbon dioxide (CO₂) concentration. Therefore it is important to understand soil organic carbon (SOC) dynamics. Soil organic carbon models, which have been successfully validated for non-saline soils, are important for estimation of past and future SOC contents and for evaluating management effects on SOC. However, it was unclear if they accurately predict CO₂ emission/​SOC stocks in salt-affected soils. In this work, an integrated approach using remote sensing, incubation experiments, modelling and geographical information system was used to simulate SOC dynamics in salt-affected soils at field and regional scale in the past, present and the future. Satellite imagery was used to map soil salinity and select soil sampling sites in two climatically distinct regions which also differ in cause of salinity : Kadina, South Australia and Muktsar district (Punjab), India. High resolution multispectral satellite imagery (Quick bird, spatial resolution 0.6 m) was used to map salinity ( 1:10000 scale) in an agricultural area around Kadina, South Australia where salinity associated with ground water or an impermeable subsoil is wide-spread. Resourcesat-I (spatial resolution 23.5 m) was used for mapping salinity on a 1:50000 scale in Muktsar (Punjab), India where salinity is induced by irrigation. Unsupervised classification of the Quick bird imagery (September, 2008) covering the study area in South Australia (hereafter called Australia) allowed differentiation of severity levels of salt-affected soils, but these levels did not match those based on electrical conductivity (EC) and sodium adsorption ratio (SAR) measurements of the soil samples, primarily because the expression of salinity was strongly influenced by paddock-level variations in crop type, growth and prior land management. Segmentation of the whole image into 450 paddocks and unsupervised classification using a paddock-by-paddock-approach resulted in a more accurate discrimination of salinity with image derived salinity classes correlated with EC but not with SAR. For the Indian site (hereafter called India), Resourcesat-I LISS-III data of April 2005, October 2005 and February 2006 was visually interpreted for variation in spectral properties. The map of salt-affected soils was generated after integration of ground and laboratory data with delineated land use units from the satellite data. On the basis of land use and soil types, 120 (59 saltaffected and 61 non-salt-affected) and 160 (70-salt-affected and 90-non-salt-affected) soils were collected from 0-0.30 m depth from the Indian and Australian sites, respectively. Salt-affected soils occur in dry climates and often contain calcium carbonate (CaCO₃) particularly at pH > 7.5. Therefore, using CO₂ emission as a measure of microbial activity and SOC decomposition in these soils is problematic, but an experiment involving addition of 2% wheat residues and varying the rate of calcium carbonate added to a non-calcareous soil showed that CO₂ emission from salt-affected soils was not affected by CaCO₃ addition in the presence of residues.

Subjects : carbon ; decomposition rate ; modifier ; rothC ; salinity ; unsupervised classification

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