Models meet data: Challenges and opportunities inimplementing land management in Earth system models

As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land‐cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices—forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire—for (1) their importance on the Earth system, (2) the possibility of implementing them in state‐of‐the‐art ESMs, and (3) availability of required input data. Matching these criteria, we identify “low‐hanging fruits” for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs

Greenhouse gas implications of novel and conventional rice production technologies in the Eastern-Gangetic plains

Wetland rice (Oryza sativa L.) production contributes 55% of agricultural greenhouse gas (GHG) emissions in the world. Hence any new technology with the potential to reduce the GHG emissions of wetland rice could make a significant contribution to total global warming mitigation by agriculture. We applied a streamlined life cycle assessment to the effect of a novel unpuddled transplanting of rice and of increased crop residue retention on GHG emissions from rice fields in the Eastern Gangetic Plains. We compared them with the conventional puddling of soils and current residue retention for transplanting. The GHG emissions from one tonne of rice production for the following four cropping practices were studied: a) conventional puddled transplanting with low residue retention (CTLR); b) conventional puddled transplanting with high residue retention (CTHR); c) unpuddled transplanting following strip tillage with low residue retention (UTLR) and; d) unpuddled transplanting with high residue retention (UTHR). The emissions recorded on-farm and emissions related to pre-farm activities were converted to CO2-eq using Global Warming Potential (GWP) values of GHGs for 20-, 100- and 500-year time horizons. The GHG emissions of 1 tonne of rice varied from 1.11 to 1.57 tonne CO2-eq in the 100-year horizon. For all four treatments, soil methane (CH4) was the predominant GHG emitted (comprising 60–67% of the total) followed by emission from on-farm machinery use. The UTLR was the most effective GHG mitigation option (it avoided 29%, 16% and 6% of the total GHG emissions in comparison with CTHR, CTLR and UTHR, respectively) in wetland rice production. The novel minimum tillage establishment approach for rice involving strip tillage followed by UT has potential to increase global warming mitigation of wetland rice in the Eastern Gangetic Plains, but further research is needed to assess the role of increased residue retention