Since the Green Revolution of the 1960s, rice-wheat cropping has been the major cropping system in the Indo-Gangetic Plains (IGP), where annual cycles of wet (puddling) and dry tillage conditions exert specific pressure on soil organic matter (SOM) dynamics. Puddling under flooded conditions destroys soil aggregates and disperses clay and SOM particles. Drainage following the rice harvest causes the clay particles to settle, creating a hardpan that makes it necessary to till before sowing the wheat. Tillage destroys soil aggregates, increases aeration and exposes SOM, making it more accessible to decomposing micro-organisms. Conservation agriculture (CA) based management practices (zero-tillage, residue retention and appropriate rotations, etc.) have been widely promoted as an alternative to intensive tillage based management practices for rice and wheat, that can result in more efficient use of water, fertilizer and fuel, maintain or increase land productivity, reduce greenhouse gases (GHGs) and also to help to cope with some weather extremes. Conservation agriculture management practices involve retaining residues on the soil surface, which has impact on the long-term buildup of SOM at different landscape levels. However, how this translates into improvements in soil health is still unclear. A holistic systems approach that combines experimentation tools and mathematical modeling is needed to evaluate the long-term effect of CA practices on multiple scales of SOM dynamics.
To explore the long-term effects of CA practices on SOM dynamics, resource use efficiency and crop yields and at a landscape scale using the Roth-Landscape model (Coleman et al., in prep). The Roth-Landscape model is a two-dimensional model that simulates the vertical and horizontal interactions of C, N, P and water between the atmosphere, plants and soil. The model has been tested for soil organic carbon (SOC), nitrogen (SON), soil moisture and crop yield in several long-term experiments (LTEs) under different crop rotations available from Rothamsted Research in the UK but has yet to be calibrated and tested for tropical conditions.
Previous experience in modeling (desirable but not essential).