[1] We present a conceptual synthesis of the impact that agricultural activity in India can have on land-atmosphere interactions through irrigation. We illustrate a ''bottom up'' approach to evaluate the effects of land use change on both physical processes and human vulnerability. We compared vapor fluxes (estimated evaporation and transpiration) from a pre-agricultural and a contemporary land cover and found that mean annual vapor fluxes have increased by 17% (340 km 3 ) with a 7% increase (117 km 3 ) in the wet season and a 55% increase (223 km 3 ) in the dry season. Two thirds of this increase was attributed to irrigation, with groundwater-based irrigation contributing 14% and 35% of the vapor fluxes in the wet and dry seasons, respectively. The area averaged change in latent heat flux across India was estimated to be 9 Wm
À2. The largest increases occurred where both cropland and irrigated lands were the predominant contemporary land uses. Citation: Douglas,
A B S T R A C TMathematical models, such as the DNDC (DeNitrification DeComposition) model, are powerful tools that are increasingly being used to examine the potential impacts of management and climate change in agriculture. DNDC can simulate the processes responsible for production, consumption and transport of nitrous oxide (N 2 O). During the last 20 years DNDC has been modified and adapted by various research groups around the world to suit specific purposes and circumstances. In this paper we review the different versions of the DNDC model including models developed for different ecosystems, e.g. Forest-DNDC, Forest-DNDC-Tropica, regionalised for different areas of the world, e.g. NZ-DNDC, UK-DNDC, modified to suit specific crops, e.g. DNDC-Rice, DNDC-CSW or modularised e.g. Mobile-DNDC, Landscape-DNDC. A 'family tree' and chronological history of the DNDC model is presented, outlining the main features of each version. A literature search was conducted and a survey sent out to c. 1500 model users worldwide to obtain information on the use and development of DNDC. Survey results highlight the many strengths of DNDC including the comparative ease with which the DNDC model can be used and the attractiveness of the graphical user interface. Identified weaknesses could be rectified by providing a more comprehensive user manual, version control and increasing model transparency in collaboration with the Global Research Alliance Modelling Platform (GRAMP), which has much to offer the DNDC user community in terms of promoting the use of DNDC and addressing the deficiencies in the present arrangements for the models' stewardship.
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