India’s falling aquifer levels, erratic monsoons, arable land constraints, stagnating crop yields, growing food demand, and rising greenhouse gas (GHG) emissions necessitate that strategic interventions be planned and implemented to maintain food security in the country. In this paper, we present two novel system dynamics simulation models—termed ‘Sustainable Alternative Futures for India’ (SAFARI) and SAFARI-R (a regionally disaggregated version of SAFARI)—that can be used to develop and analyse specific interventions required at the national and regional levels to sustainably maintain food security. Our simulation results show that increasing micro-irrigation coverage, limiting sugarcane cultivation, and improving water recycling in domestic and industrial sectors can help achieve food production sufficiency within the limitations posed by the availability of natural resources. Alternatively, a behavioural shift towards eating (and cultivating) coarse cereals instead of rice (which is water intensive) is another effective intervention, especially when combined with micro-irrigation or crop yield improvements, and reduced sugarcane cultivation. When compared to a scenario where current practices continue, these alternative pathways to food security can reduce annual water consumption for irrigation by 18%–24%, electricity demand for irrigation by 60%–65%, and the agriculture sector’s total (direct + indirect) GHG emissions by 17%–25%, by 2050. Further, simulations on SAFARI-R indicate that the north, centre, and west zones of the country are considerably pressed for water, while the south and east zones could run out of land. As a way to meet the food demand in these zones in future, the possibility of crop redistribution is explored along with other strategies such as reducing groundwater dependence.
This paper presents findings from a process aimed at identifying the climate linkages of non-climate focused environment and development projects in India. Findings from four case studies based on workshops using participatory systems thinking are summarized. These climate adjacencies are documented as systems stories using the tools of systems thinking—behavior over time graphs and causal loop diagrams. These place-based stories highlight how the environment and development projects have linkages with climate change mitigation and adaptation. An attempt has been made to convert one of the systems stories into a computable simulation model using system dynamics modelling. A small concept model has been created thus and used to perform simulation runs. Four scenarios have been generated and the results discussed. Our learning from converting feedback maps into stock-flow models is presented. The insights generated from interpreting the feedback maps and simulation results are also presented. These insights are then compared and the benefits of simulation evaluated. The paper highlights the need to document climate linkages of non-climate-focused development projects and the benefit of converting systems stories into simulation models for developing operational insights. The important role such methods can play in developing capacities for enhancing climate action is also discussed.
This is a study of the interactions between the ecology and economy of the Banni grassland, located in the district of Kutch, Gujarat, India. The study focuses on modelling the economic impact of grassland degradation in the Banni from 1992–2015 and simulates future scenarios up to 2030 using system dynamics. The specific sectors being modelled are the area spread of the invasive species Prosopis juliflora, palatable grass, the populations of livestock as well as the livestock and charcoal incomes of Banni. An economic valuation is done by discounting the future earnings of the pastoral (milk, livestock sale, dung manure) and charcoal economy under two scenarios 1) Base case (Business as Usual), i.e. keeping current policies constant and 2) P. juliflora removal policy (PRP) i.e. where a decision is implemented to remove P. juliflora from Banni. Under the BAU scenario, modelling results indicate that the Banni grassland is headed for severe fodder scarcity due to the shrinking area under grassland. Under the PRP scenario, Banni is able to revive its grasslands and increase the present value of future earnings (up till 2030) by 62 per cent. A delay of five years in the decision to remove P. juliflora results in a 28 per cent reduction in earnings indicating the policy’s time sensitivity. The model serves as a test bed for generating what-if scenarios of the Banni grassland.
In this response, we will first address the general statements made by C.P. Geevan, A. Dixit S. Silori (this issue of EES; henceforth GDS) in the context of our paper published earlier in EES (M&S), and then move to addressing the specific points raised. The model presented in (M&S) indeed follows a highly coupled approach, refer Figure 1 (Higher Order Causal Loop Diagram of the Simulation Model) (M&S, 37), as is what GDS suggest should be the case for such an ecological-economic system, and unlike what they claim the model actually is. The sectors of livestock, economy and land area are interdependent through multiple feedbacks, some of which are described in the section 'Key Cross-sectorial Feedbacks' (M&S, 44). As is asserted incorrectly by GDS, the computation of livestock numbers as well as P. juliflora (PJ) area-referred to as MCA by GDS-is not done using a 'stand alone' approach, and both the sectors are interdependent on each other. PJ area is influenced by livestock numbers through an increased spread rate due to livestock acting as vectors in Banni; and, livestock numbers depend on PJ area as with increased PJ invasion, area available for grass growth comes down, thereby reducing biomass production, which leads to fodder deficit-named as such in our modelimpacting livestock numbers. These impacts manifest themselves through three feedbacks: 1) by increasing migration of buffalo and cattle from Banni, 2) by increasing fodder and feed input cost, thereby reducing livestock profitability, and increasing the stress sale of livestock and 3)
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