Hydro-economic modeling of water scarcity: An application to an Ebro sub-catchment

October 21st, 2014

Dr. Nina Graveline, Bureau de Recherches Geologiques et Minieres, France

This communication based on the work of Graveline et al.1 highlights the importance of adopting integrated hydro-economic models2 to investigate the climate-water nexus and to assess the effects of global changes in terms of water scarcity, salinity and agricultural economics at a regional scale. We develop a hydro-economic model for a sub-catchment of the Ebro basin ­- the Gállego catchment – that combines hydrological processes, regulation and operation of water reservoirs, and economic processes that drive agricultural water demands.

The Gallego catchment covers a 4,009 km2 area and is located in the northern part of the Ebro basin (Figure 1). At the confluence with the Ebro river near the city of Zaragoza, the Gallego river has an average annual discharge of 1090 hm3. Several reservoirs have been constructed in the Gallego catchment since the 1960s for hydropower production and irrigation purposes. Reservoirs mostly supply irrigation water demand, which represents 94% of the water demand in the Gallego catchment.

The hydrological modelling system implements suitable modules for snow accumulation and melting, infiltration, evapotranspiration, subsurface flow generation and channel routing and it is specifically designed to model climate change impacts on this catchment3. The management of the 5 reservoirs present in the catchment is simulated as a trade-off between maximizing water availability for agricultural uses, satisfying the minimum ecological flow conditions in the river and satisfying the reservoir security margins for flood control.

The economic model is a linear programming model4. Irrigation water demands are simulated based on the water availability in the system, which influences the farmers’ choices with respect to cropping patterns and irrigation practices. This means that in dry years, farmers may choose crops that are less water intensive, leading to lower irrigation demands.

The integration of the different models is performed with a “compartment approach” which consists of an exchange of input/output data done at specific locations in the systems. This allows for the adoption of sophisticated models for each “compartment”, as opposed to holistic models that integrate in one unique model (which often includes oversimplified hydrological and economic modelling) the representation of all processes.

The technical implementation of the coupled modeling system can be summarized in five steps.

Step 1: Based on different levels of water availability for agriculture, economic model runs have been performed in order to create a library of responses able to provide the input data for the hydrological model and the reservoir operation compartment (i.e. monthly water demand based on selected cropping pattern). The optimization time-horizon was fixed at one year, with each month being simulated separately.

Based on different levels of water availability for agriculture, economic model runs have been performed in order to create a library of responses able to provide the input data for the hydrological model and the reservoir operation compartment (i.e. monthly water demand based on selected cropping pattern). The optimization time-horizon was fixed at one year, with each month being simulated separately. Step 2: Based on the monthly water demands derived in Step 1 and on the reservoir management rules, expected withdrawals from reservoirs and water supplies to rivers and irrigation districts are fixed at daily time scale by the reservoir operation compartment.

Based on the monthly water demands derived in Step 1 and on the reservoir management rules, expected withdrawals from reservoirs and water supplies to rivers and irrigation districts are fixed at daily time scale by the reservoir operation compartment. Step 3: Based on output from Step 2, hydrological model runs are performed with a daily time-step, which provides data of water fluxes and water storage in selected nodes.

Based on output from Step 2, hydrological model runs are performed with a daily time-step, which provides data of water fluxes and water storage in selected nodes. Step 4: Based on aggregated yearly values of water supplied as output from Steps 2 and 3, the economic model provides irrigated area, crop yields, regional agricultural income and salt emissions.

Based on aggregated yearly values of water supplied as output from Steps 2 and 3, the economic model provides irrigated area, crop yields, regional agricultural income and salt emissions. Step 5: Coupling of the models is achieved by iterating Steps 2, 3 and 4 over the simulation period in which the hydrological model updates yearly values of water availability together with the input data provided by the agro-economic library and the reservoir management compartment.

The hydro-economic model is then used to simulate different scenarios and their impact on water and agricultural economics (Figure 2). The impacts of three main changes are explored: (i) projected changes in climate as characterized by previous work conducted in the catchment;5 (ii) an expansion of water storage capacity by reservoir enlargement; and (iii) the modernization of irrigation technology (from gravity irrigation to sprinkler irrigation for 50% of irrigated land) resulting in a decrease in per hectare-water demand by the improvement of water application efficiency.

Furthermore, two global change scenarios are also considered. They are both characterized by the modernization of irrigation technology and climatic change. The first, GC1, includes the enlargement of water storage capacity while the second, GC2, doesn’t. In particular, the effect of reservoir expansion in the GC1 scenario is negligible if compared to the GC2 scenario. As a result, the outcomes of both global change scenarios are almost identical.

The results suggest that, in this part of the Ebro basin, reservoir expansion appears not to be an effective solution for adapting to the impacts of climate change and for meeting water demands for extra irrigated land. The results also suggest that investments in modernization of irrigation technology would mitigate the negative impacts of climate change on the agricultural sector. However, irrigation technology modernization has high implementation costs, which would slightly outweigh the extra regional agricultural income, and would result in negative enviromental impacts through increased salinity. Furthermore, we show that adoption of more efficient water-saving irrigation technologies does not result in an increased water-availability at the basin scale in dry years.

Our integrated hydro-economic model is practically relevant to decision-makers in the Ebro basin because it enables for the simultaneous assessment of different factors of change, both natural and socio-economic, and for the simulation of their impacts on future water availability. Different water management policies can be simulated in our model and results can be used to assist water planning decisions in the Ebro basin.

References:

Graveline, N., Majone, B., Van Duinen, R., and Ansink, E. (2014). Hydro-economic modeling of water scarcity under global change: an application to the Gállego river basin (Spain). Regional Environmental Change, 14(1), 119-132. Harou, J.J., Pulido-Velazquez, M., Rosenberg, D.E., Medellín-Azuara, J., Lund, J.R., Howitt, R.E., 2009. Hydro-economic models: concepts, design, applications, and future prospects. Journal of Hydrology. 375(3-4), 627-643. Majone, B., Bovolo, C. I., Bellin, A., Blenkinsop, S., & Fowler, H. J. (2012). Modeling the impacts of future climate change on water resources for the Gállego river basin (Spain). Water Resources Research, 48(1). Hazell, P.B.R., Norton, R.D., 1986. Mathematical Programming for Economic Analysis in Agriculture. Macmillan, New York. Bürger, C. M., O. Kolditz, H. J. Fowler, and S. Blenkinsop (2007), Learning machines for rainfall-runoff modelling in the Upper Gallego catchment (Spain), Environemental Pollution, 148, 842-854.

Nina Graveline is a researcher in agricultural and water economics at BRGM since 2004 where she is involved and/or leads research and science support to policy projects dealing with water management. As an economist she is concerned with the analysis and evaluation of water uses and contaminations’ regulation. After a stay at the University of California, Davis in 2011 she defended a PhD on agricultures’ adaptation to global change and to water policies, and the interest of economic mathematic programming approaches, which has been her main research focus until now. She has worked in several parts of France, La Réunion, Germany, North Africa and Spain on topics dealing with water quality or quantity management.

The views expressed in this article belong to the individual authors and do not represent the views of the Global Water Forum, the UNESCO Chair in Water Economics and Transboundary Water Governance, UNESCO, the Australian National University, or any of the institutions to which the authors are associated. Please see the Global Water Forum terms and conditions here.