Climate Informatics for the Water-Energy-Food Nexus in the Indus Basin:
A Scoping Study in Modeling Dairy Farms
Abstract
Climate patterns in the agricultural zones of the Indus basin are
predicted to undergo undesirable changes in the hydrological cycle.
These changes are a threat to the widespread agricultural activity and
associated livelihoods of the underlying population. Livestock, an
essential sector for human sustenance in the basin, is also a major
source of greenhouse gas emissions thereby contributing towards climate
change. However, it is also a recipient of climate impacts, thus
introducing feedbacks and uncertainties that are further accentuated by
the Water-Energy-Food Nexus. Here we model and simulate the farm-level
dairy operations of a single dairy farm by introducing
informatics-driven precision measurements of water, energy, food, and
carbon emissions in a system dynamics framework. We analyze the
simulated trajectories for energy, water, and waste fluxes to under
different interventive scenarios to identify actions that enhance
productivity and minimize environmental impact. The model is constructed
based on data gathered from two dairy farms located in rural Punjab,
Pakistan. The farms have a livestock capacity of 300 and 134 animals
respectively, with data related to water, energy, food, and climate
gathered over a duration of two years. The simulated results may be used
to uncover structural changes in dairy-farm operations which improve the
economic structure of the farm while remining within the thresholds
defined by Sustainable Development Goals (SDG) 3, 7 and 13 set by the
United Nations. The model itself also helps in unravelling the complex
interactions among water-energy-food flows along with their coupling to
land-climate interactions in context of the dairy farm operations.
Beyond the climate change adaptation measures extracted from this study,
the system dynamics model that we construct in the process, can help
develop economic tools that leverage the advantages of water/climate
informatics driven data services and decisions under large variabilities
to devise sound agricultural policy.