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The groundwater shortage for agriculture in upland villages in southern India has revealed the inter-relationship between the farmers' income, crop, and water with social, economic, and climatic variables. System Dynamics models such complex problems and leads to more effective solutions if done with stakeholder participation. In this work, participatory System Dynamics modeling of crop-waterincome dynamics has been carried out in a village with the last ve decades' data to develop an action plan for ecologically and economically sustainable agriculture. Causal loop diagrams and Stocks-and-ows diagrams were developed and validated through stakeholders' focused group discussions and individual meetings. Multiple 'what-if' scenarios suggested by stakeholders are simulated and analyzed. The bene ts of less water-intensive, chemical-free, climate-resilient 'Zero Budget Natural Farming (ZBNF)' are clear compared to other scenarios. A post-project survey indicated that 90% of stakeholders agreed that the framework is unbiased, encourages new ideas, and promotes a better understanding of the issues.

A resource management system is likely to succeed if stakeholders get involved in analyzing and choosing from the alternatives. The present work deals with multi-criteria decision models to evaluate rain water harvesting (RWH) structures. Standard practice is to acquire the weights for criteria from stakeholders using analytic hierarchy process (AHP) to predict the RWH structures' performance and rank them. Challenges in this process are that the data collection is laborious and time-consuming, considers limited stakeholders' opinions, and suffers from lower confidence factors. This work proposes a probabilistic approach to AHP using Monte Carlo simulation (MCS) to model uncertainty. The proposal is to collect multiple assessments instead of a single judgment from knowledgeable stakeholders (KSH) with customized questionnaires and to compute the relative importance of criteria using pairwise comparisons. Stochastically similar assessments within the range of these samples are then generated using different distribution functions to compute the performance of the RWH structures. The computed performance correlated well with common stakeholders' (CSH) opinions in the case study involving 10 existing RWH structures with seven different criteria, for all the distributions. The mean relative error with the proposed method is approximately 21% less than the existing point estimate method.