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Chinese farmers have adopted multiple adaptation measures to mitigate the negative impact of, and to capture the opportunities brought by, the observed climate change in the last several decades. Such adaptations will continue in the coming decades given the foreseeing climate change. Scientifically assessing such dynamism of suitable agricultural adaptation requires unprecedented efforts of the research community to simulate and predict the interactions among crop growth dynamics, the environment and crop management, and cropping systems at and across various scales. This calls for efforts aiming to quantify the interactions of agro-ecological processes across different scales. This dissertation intends to make scientific contributions in this direction. The leading goal of this dissertation is to develop a cross-scale modeling framework that is capable of incorporating the field agricultural advances into the design and evaluation of regional cropping system adaptation strategies. It then applies this framework to identify feasible cropping system adaptation strategies under observed warmer climate and quantify their potential benefits to the grain production and water sustainability in the major cropping regions in north China. Three objectives of this study are: (1) Develop a cross-scale model-coupling framework between the site level DSSAT model and the regional level AEZ model to improve the AEZ performance in capturing the northern expansion of japonica rice under a warmer climate in the Northeast China Plain. (2) Construct a new wheat-maize cropping systems adaptation strategy to meet the double challenge of maintaining the regional grain production level and recovering local groundwater table in the semi-arid North China Plain, where the persistent overexploitation of groundwater has caused severe environmental damages. (3) Establish a dynamic adaptation strategy to identify the desired water sustainable cropping systems across different localities and to meet the challenge of recovery local groundwater table and minimize the output losses of wheat and then total grain production in the Hebei Plain, where the irrigation water shortage has threatened wheat production and thus potentially compromising China’s food security. This dissertation will improve our understanding of the interactions and interlinkage across multi-scale agro-ecosystems in mitigating the environmental risks associated with the irrigation-intensive farming and in adapting to climate change. The cropping systems adaptation strategies proposed by this dissertation provide scientific basis for future agricultural adaptation policy design compatible with local agro-climatic, land and soil conditions across China.

China is the largest rice producing and consuming country in the world, accounting for more than 25% of global production and consumption. Rice cultivation is also one of the main sources of anthropogenic methane (CH4) and nitrous oxide (N2O) emissions. The challenge of maintaining food security while reducing greenhouse gas emissions is an important tradeoff issue for both scientists and policy makers. A systematical evaluation of tradeoffs requires attention across spatial scales and over time in order to characterize the complex interactions across agricultural systems components. We couple three well-known models that capture different key agricultural processes in order to improve the tradeoff analysis. These models are the DNDC biogeochemical model of soil denitrification-decomposition processes, the DSSAT crop growth and development model for decision support and agro-technology analysis, and the regional AEZ crop productivity assessment tool based on agro-ecological analysis. The calibration of eco-physiological parameters and model evaluation used the phenology and management records of 1981-2010 at nine agro-meteorological stations spanning the major rice producing regions of China. The eco-physiological parameters were calibrated with the GLUE optimization algorithms of DSSAT and then converted to the counterparts of DNDC. The upscaling of DNDC was carried out within each cropping zone as classified by AEZ. The emissions of CH4 and N2O associated with rice production under different management scenarios were simulated with the DNDC at each site and also each 1010 km grid-cell across each cropping zone. Our results indicate that it is feasible to maintain rice yields while reducing CH4 and N2O emissions through careful management changes. Our simulations indicated that a reduction of fertilizer applications by 5-35% and the introduction of midseason drainage across the nine study sites resulted in reduced CH4 emission by 17-40% and N2O emission by 12-60%, without negative consequences on rice yield.