A current program of the Land-Use and Land-Cover Change (LUC) at the International Institute for Applied Systems Analysis is to determine the potential primary productivity of agricultural crops for parts of China, the former Soviet Union, and Mongolia. The work in this paper, supported by the Dynamic Systems group, is in collaboration with that LUC program. The main goal is to provide a methodology for investigating some of the indirect processes and pathways which affect primary productivity of crop production and to introduce a different modeling approach in estimating the potential productivity. The three main objectives of this research are the following: 1. Use network analysis to identify and quantify the indirect processes that affect the primary production of crop growth, 2. Develop a flow-storage compartment model to be used in the network analysis, 3. Quantify the flow-storage model using a dynamical simulation model. Although many factors control the primary productivity of a region, a main one is the availability of water, so the simulation model used here is based on the hydrologic budget of the study region. A four-compartment hydrologic model is developed which includes the within-system transfers between ground water, surface water, atmosphere, and vegetation, along with the external water transfers with the environment. When available, on-site climatic data are used to evaluate the model's parameters. The model is applied to a homogeneous region with a single cover type. Specifically, the model is calibrated using data from the Kursk region of Russia and the crop barley. This research shows that the atmosphere and soil moisture content both contribute important direct and indirect pathways for the water to reach the vegetation and subsequently affect primary production. Also, based on this model, the primary productivity is most sensitive to the vegetation growth rate and the rate of evapotranspiration. The model rationale and the results are discussed herein
