Quantifying the value of stakeholder elicited information in models of
coupled human-water systems
Abstract
Causal loop diagrams (CLDs) based on expert and/or stakeholder inputs
inform the quantitative structure of socio-hydrological models (SHMs).
However, a systematic exploration of the sensitivity of CLDs and SHMs to
different levels of stakeholder inputs is lacking. For a large
multi-purpose reservoir in southern India, we explore this sensitivity
by developing three CLDs that integrate reservoir water balance,
groundwater pumping, and consumer water use patterns. CLD1 is a
conventional water balance-based reservoir model, while CLD2
additionally incorporates the reservoir operatorâ\euro™s judgment and
groundwater pumping. CLD3 further incorporates the adaptive behavior of
water users by adjusting demands in response to long-term (5-year)
droughts. The correlation between observed and simulated monthly
reservoir storage (2000-2013) for SHM1, SHM2, and SHM3 is 0.57, 0.85,
and 0.87, respectively. SHM3 also outperforms SHM1 and SHM2 in
simulating the relative use of surface and groundwater for irrigation
purposes in the command area of the reservoir. Simulated demand
deficits, command area groundwater levels, and minimum environmental
flow satisfaction downstream of the reservoir for 1968-2013 using the
three models exhibit substantial differences. SHM1 and SHM2 simulate
deteriorating groundwater levels under the multi-year drought of
2001-2003 while SHM3 does not due to the consideration of adaptive
farmer behavior. Thus, our understanding of water and food security
during a multi-year drought can be significantly affected by the level
of stakeholder inputs incorporated in the models. We highlight the
importance of testing different SHMs structures to better understand
human-water interactions under extreme conditions.