Jay R. Lund

The Economics of Water Infrastructure Investment Timing and Location under Climate Change

The Dong Nai Delta in Vietnam has been projected to face long-term changes in physical conditions stemming from climate change. Sea level rise combined with changes in the hydrologic cycle will result in increased salinity conditions, causing significant damage to the current style of agricultural production. Adapting to these changes in salinity will require not only adjusting the cropping patterns, but also new water infrastructure investments. Two important questions arise for planners and practitioners. First, a balance needs to be found with regards to the appropriate timing of the investment. An important amount of investment is needed for new water infrastructure while salinity will increase gradually over time. Second, considerable trade-offs exist with respect to the location of the investment arising from the morphological characteristics of the delta. Constructing water infrastructure closer to the sea implies a higher investment cost. However, the additional benefits will be reduced since regions closer to the sea already have lower agricultural productivity due to greater salinity. This paper develops an economic model to analyse the optimal timing and location of water infrastructure investments in the Dong Nai Delta of Vietnam. This paper develops a dynamic programming model to analyze the timing and location of water infrastructure investments to control salinity in the Dong Nai Delta. Investment costs are estimated using engineering parameters. The benefits of water infrastructure are parameterized from an agricultural production model that uses positive mathematical programming to estimate the value of agricultural production as a function of salinity levels for each of the agricultural districts of the Delta. Each district has a different response to salinity in economic terms, resulting from diverse endowments of land, technology and crops being grown. The first model formulation assumes that salinity increases over a planning horizon of 40 years and finds the optimal timing (year) for building water infrastructure such that the value of agricultural production profits is maximized. The problem is formulated as a dynamic programming problem with one state variable and one control variable. I use a deterministic, discrete space and discrete control specification where time t is measured in years. The state variable represents salinity level at year t. The control variable is binary and represents the decision at year t on whether or not to build a sluice gate. The model is solved numerically for the optimal policy rule, i.e., the timing profile of sluice gate construction, using both value function iteration and backwards recursion. Sensitivity analysis is conducted with respect to the specification of the agricultural profit function, the salinity trend, the value of sluice gate construction, and the choice of discount rate. The model is then extended to incorporate investment location choice in the decision variable. Again, the problem is formulated as a dynamic programming problem with one state variable and one control variable, except that the control variable represents both time and space. The spatial links between regions are also included both in the transition equation and the net benefit function of the water infrastructure investment decision. This paper demonstrates the importance of economic analysis for long-term investments in water infrastructure. Optimization methods can be used to study the appropriate design of investment plans integrating economic, engineering and hydrologic aspects. The framework of analysis can be extended to incorporate additional aspects relevant for decision-makers such as alternative salinity protection measures, equity considerations of investment plans, or infrastructure financing options. This paper developed a methodological framework to analyze the economics of water infrastructure investment timing and location. The first question addressed in the modeling framework is the appropriate timing to build water infrastructure. Simulation results suggest that the optimal timing for investment differs considerably if the possibility of adjusting cropping patterns is considered. The possibility of adapting the agricultural system by introducing new salt resistant varieties delays also the optimal timing for investment when compared to a situation of no crop substitution. Other parameters such as a higher water infrastructure investment cost or a higher rate of salinity growth shift the economic viability of construction to later or earlier periods respectively. The second question addressed in this chapter is the tradeoffs associated with the spatial characteristics of the delta and the location of the investment. Simulation results suggest that abandoning regions closer to the sea and concentrating salinity control in upstream regions improves the value of the investment. These results critically depend on the resolution of the model in terms of region size and variability in infrastructure construction costs. Improving the resolution of the model, introducing equity considerations and the interaction between different infrastructure investments are areas for further research in the subject.

Re-operation of major reservoirs for flood and environmental management

This paper summarizes the results of two similar studies of reservoir flood operations. The first study is a re-operation of Folsom Dam, California with outlet structure improvements and the potential of flood rules that are fixed or based on a combination of precipitation, snowpack, and ENSO conditions. Trade-offs between flood probabilities and water supply spill are estimated and analyzed using expected ranges of costs of levee failures downstream and the value of spilled water for water supply. The second study is a re-operation of Camanche Reservoir in central California to reallocate some flood storage for use in managing downstream environmental flows as well as urban water supply and hydropower purposes. Trade-offs between economic and environmental performance are estimated and discussed.