An Economic Valuation Of The Water Footprint: A Case Study Of The Citrus Sector In The Lower Sundays River Valley, Eastern Cape, South Africa.

Thursday, 18 December 2014: 8:30 AM
Samantha Alanna Munro, Gavin C.G Fraser and Jen D Snowball, Rhodes University, Grahamstown, South Africa
With the implementation of the South African National Water Act (NWA) currently underway, water intensive sectors, such as the irrigated agriculture sector, can expect reduced water allocations and an increase in water prices. Water footprints (WFs) are increasingly being recognised as a meaningful way by which to represent human appropriation of water resources.

This study examines the green and blue WFs of a variety of citrus cultivars in the lower Sundays River Valley, Eastern Cape, South Africa. WFs were calculated across dry, humid and long-term average climates and comparisons were made to available global average benchmark WFs. An number of indicators were also explored including; water productivity (ton/m3), economic land productivity (R/ha) and economic water productivity (R/m3) across all three climatic years. Most applications of WF sustainability assessments have focused on examining physical water scarcity as a measure for determining environmental hotspots. This study, therefore, also calculates the marginal product value for the irrigation water using a non-parametric linear programming approach. Marginal product value of irrigation water is not only useful in assisting with water-allocation decision making, but also useful in demonstrating the effects of resource depletion and degradation, and is therefore a useful measure for determining economic water scarcity.

The study highlights that both farmers and governments could reduce blue WF’s through adopting measures to increase water efficiency and considering economic water and land productivity. It also demonstrates the importance of including both environmental and economic scarcity indicators into water management and planning strategies, and the importance of conducting WF assessments using more accurate, site specific data.