Unravelling the Unintended Consequences of Water Interventions
Challenges of Understanding Adoption within Human-Water Systems and a Way Forward
M.F. Alam (TU Delft - Water Resources, International Water Management Institute)
Daniel Sihombing (Universitas Gadjah Mada)
Soham Adla (TU Delft - Water Resources)
S. Pande (TU Delft - Water Resources)
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Abstract
Changes in the water cycle (availability/variability of water) influence and shape human society (e.g. floods and droughts have shaped human civilization), whereas decisions humans take (e.g. building dams, irrigation) influence the water cycle. The study of these coupled and co-evolving human–water systems is central to sociohydrology (Sivapalan et al., 2012). For example, irrigation efficiency measures can lead to increased water use, rather than the expected reduction (Perry and Steduto, 2017), or the unplanned proliferation of rainwater harvesting structures such as check dams in river streams can reduce downstream flows leading to upstream–downstream conflicts or even increased demand (Alam et al., 2022; Calder et al., 2008). While the motivation of such interventions has been to make regional agriculture climate resilient, they can have unintended negative impacts such as shifts toward more water-intensive crops, increased vulnerability to droughts and groundwater exploitation (Alam et al., 2022). While farmers of all income groups behave similarly, poorer farmers who cannot adapt to these negative consequences (e.g. by drilling deeper groundwater wells) bear most of the negative impacts (Bouma et al., 2011; Narayanamoorthy, 2015). Without accounting for the bidirectional feedback of human–water systems, investments in interventions to increase irrigation efficiency or harvest rainwater can lead to long-term unintended consequences, exacerbating existing vulnerabilities and social inequities, or impacting the sustainability of resources. We propose a way forward to disentangle such bidirectional feedback so that coupled human–water systems (e.g. human agricultural systems) can be realistically modeled and the effects of the intervention on human well-being are more accurately estimated.