How can resource-level thresholds guide sustainable intensification of agriculture at farm level? A system dynamics study of farm-pond based intensification

Abstract

Sustainable intensification (SI) of agriculture combines the dual goals of increasing productivity while staying within safe limits of resource use. In practice, how can thresholds which operate at resource scale guide intensification driven by social, economic and biophysical factors at the farm scale? In this paper, we present the case of agricultural intensification in the shallow hard-rock aquifer region of western India to illustrate how cross-scale feedback effects are crucial determinants of not only the resource sustainability and farm productivity but also of social dimensions of SI such as equity and justice. Supported by private investment in plastic-lined farm-ponds, the increasing shift to horticulture in the study area raises questions about the sustainability of the practice. We use a socio-hydrological lens and develop a system dynamics model to analyze how the growing technology-mediated intensification may lead to SI. We find that from a static farm-level view, the plastic-lined farm-pond is beneficial in shielding farmers from droughts and in enhancing productivity. However, when within and across scale socio-hydrological dynamics are considered, the practice is found to instead aggravate the drought impact on the community. This happens when intensification level accelerates, driven by aspiration and vulnerability induced feedbacks, resulting in groundwater demand exceeding the system threshold. In practice, SI is complicated by the fact that this threshold for safe groundwater use is dynamic. In drought years the carrying capacity falls significantly, so that even a low level of intensification may tip the system resulting in a tragedy of the commons. Therefore, achieving SI requires seasonally agile intensification which retains the adaptive capacity of farmers instead of locking them into fixed annual irrigation requirement in a highly uncertain and resource-scarce environment. We thus conclude that the recognition and translation of resource level thresholds to an actionable level is key to practicing SI.