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The role of size in the sustainability of irrigation systems

Periodic Reporting for period 1 - SIZE (The role of size in the sustainability of irrigation systems)

Reporting period: 2019-09-01 to 2021-08-31

The project SIZE studies how the size of irrigation systems (e.g. their physical extension) influences their sustainability. It has two objectives: 1) To discern which attributes of irrigation systems scale with size, and 2) to study how a change in size conditions the behavior of irrigation systems against disturbances. The project draws from a long tradition of studies in Biology, Ecology and Complexity that attested size to be a master variable defining the properties of animals, cities or social-ecological systems and their capacity to manage risks. While some studies suggested that size might also influence some features of irrigation systems (e.g. their production output per unit of terrain, the volume of water withdrawn), the knowledge available was fragmentary and focused on case studies. SIZE aims at unfolding scaling relationships of wide application and on formalizing the relationship between size and irrigation-related attributes through dynamic models, allometry and uncertainty and sensitivity analysis. Such knowledge is important given the social-environmental relevance of irrigated agriculture: it currently provides c. 40% of the worldwide food production and consume c. 70% of all freshwater resources. With the insights provided by SIZE, we will have better tools to assess the social-ecological risks and benefits derived from enlarging or reducing the extension of irrigation.
These first two years have focused on 1) retrieving data on irrigation attributes (e.g. volume of water withdrawn for irrigation, irrigation efficiency, production) from several large-scale datasets, 2) collecting data on the global extension of irrigation from the four irrigated area maps available (FAO-GMIA, GRIPC, IWMI-GIAM, Meier map), 3) mining the data to identify scaling relationships, 4) model the relation between irrigated areas and these attributes, and 5) identify and appraise uncertainties and sensitivities. The work has led to 9 papers (6 as lead author), including one in Nature and one in Nature Communications. The main results achieved so far can be summarized as follows:
- Irrigated areas increase disproportionally for every increase in population.
- Current models severely underestimate the future extension of irrigation in 2050, in the most extreme cases by one order of magnitude.
- Irrigation water withdrawals scale with irrigated areas, and this scaling relationship might be scale-independent.
- Global irrigation water withdrawal estimates produced by large-scale models are spuriously accurate.
- More detailed models tend to produce more uncertain estimates due to the increase in the models' effective dimensions.
The project has made several contributions that have gone beyond the state-of-the-art. Firstly, it has shown that the latent environmental impact of irrigated areas on freshwater resources is much more important than previously thought. This is because existing models do not take into account uncertainties in population growth rates and on the model structure in projecting future irrigated areas to 2050. Secondly, it suggests that we might not need complex algorithms to simulate irrigation water withdrawals, as the latter is tightly coupled with irrigated areas. We can produce almost identical global or country-level irrigation water withdrawal estimates with a simple linear regression against the extension of irrigation, thus saving financial and computational resources. Thirdly, it has observed that the addition of detail in models tends to increase (and not decrease) the uncertainty in the model output due to the increase in the model's effective dimensions. This means that the drive towards ever-complex models characterizing many disciplines (including hydrology) should be reconsidered as a means to constrain uncertainties in our understanding of the world. Fourthly, it has discovered that irrigation water withdrawal estimates produced by Global Models are unreliable as they disregard several key uncertainties. These models might therefore be misguiding our policies on irrigation by conveying unwarranted accuracy. In the upcoming months I expect to produce more results on scaling relationships (e.g. on the relation between irrigated areas and irrigation efficiency) and on the change in properties of irrigation systems as a function of size (e.g. on the dynamics of collaboration in "small" and "large" irrigation systems).
Uncertainty analysis of the projection of global irrigated areas to 2050