Increased water charges improve efficiency and equity in an irrigation system

Conventional wisdom in many agricultural systems across the world is that farmers cannot, will not, or should not pay the full costs associated with surface water delivery. Across Organisation for Economic Co-operation and Development (OECD) countries, only a handful can claim complete recovery of operation, maintenance, and capital costs; across Central and South Asia, fees are lower still, with farmers in Nepal, India, and Kazakhstan paying fractions of a U.S. penny for a cubic meter of water. In Pakistan, fees amount to roughly USD 1-2 per acre per season. However, farmers in Pakistan spend orders of magnitude more for diesel fuel to pump groundwater each season, suggesting a latent willingness to spend for water that, under the right conditions, could potentially be directed toward water-use fees for surface water supply. Although overall performance could be expected to improve with greater cost recovery, asymmetric access to water in canal irrigation systems leaves the question open as to whether those benefits would be equitably shared among all farmers in the system. We develop an agent-based model (ABM) of a small irrigation command to examine efficiency and equity outcomes across a range of different cost structures for the maintenance of the system, levels of market development, and assessed water charges. We find that, robust to a range of different cost and structural conditions, increased water charges lead to gains in both efficiency and concomitant improvements in equity as investments in canal infrastructure and system maintenance improve the conveyance of water resources further down watercourses. This suggests that, under conditions in which (1) farmers are currently spending money to pump groundwater to compensate for a failing surface water system, and (2) there is the possibility that through initial investment to provide perceptibly better water supply, genuine win-win solutions can be attained through higher water-use fees to beneficiary farmers.

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging because of reinforcing feedbacks between multiple drivers. We conducted semistructured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. The “Hands-off” scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production under drought conditions. The “Fire management” scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared with the “Fire suppression” scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decision-support tool and serve as a “boundary object” to facilitate collaboration and integration of different perceptions of fire in the region. This approach also has the potential to inform decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.