Integrated hydrological and economic modelling of a mining region Juan Sebastian Ossa-Moreno BEng (Honours), MSc A thesis submitted for the degree of Doctor of Philosophy at The University of Queensland in 2019 Sustainable Minerals Institute Centre for Water in the Minerals Industry Abstract Hydro-economic modelling is an established field of research that takes a multi-disciplinary approach to analysing water resources. This approach can be used to analyse water policies, assess impacts of changing climate conditions and explore synergies between water users, amongst other applications. Hydro-economic models have been applied mainly to agricultural and urban water uses. The mining industry, despite being a relevant user in several catchments worldwide, has rarely been included and the modelling challenges that arise in mining applications have not been investigated. The aim of this project was to develop a hydro-economic model in the upper Aconcagua River in central Chile, in order to understand how this approach may support catchment-scale water decision making in regions where mining is an important user. A literature review on the hydro-economics of mining highlighted several features that make the mining sector a special case. One of the most important was the large differences in both CAPEX and OPEX between this sector and alternative users of water. This means that the set of metrics used to compare the economic value of water between sectors is of particular importance, in order to avoid being biased toward the mining user. The literature review also highlighted the issues of developing water resources models with limited climate observations, as in the case of the many remote regions where mine projects are located. To address the problem of climate data, the project compared methods for interpolating point observations of precipitation and temperature in the upper Aconcagua River Basin, where precipitation and temperature spatial gradients are high and there is a lack of high elevation measurements. It was found that a relatively simple method that merges the WorldClim datasets (which are available worldwide) with available point observations worked well for the case study, and may support the development of similar models in comparable regions, even when there are few or no climate gauges available. A conceptual semi-distributed model in the WEAP software, was used as the water resources component of the upper Aconcagua River hydro-economic model (HEM). The calibration involved the comparison of flows, snow water equivalents and hydro-power energy generation, so as to minimise error compensation as much as possible. The economic analysis included four water users: mining, agriculture, hydro-power and urban users. The coupling was done using Python scripts that connected WEAP with the economic functions allowing automatic, constant feedback between components, without sacrificing a detailed representation of both components. i Three metrics were used to analyse water users in the HEM: total value of water (with and without mining), shadow value of water and water scarcity cost. These three metrics provide different viewpoints from the water users in the catchment, and thus all of them are important to take into account in decision making processes. Three sets of scenarios of potential applications of the HEM were analysed using the HEM. The first explored how changes in climate conditions may affect hydrology, coverage of user’s demand for water, and the economic metrics. This scenario helped understanding the added value of a detailed representation of hydrological processes in the catchment, as it showed how small increases in temperature would generate changes in snow melting periods that may not be harmful, and even beneficial in some cases, to all water users. The second scenario analysed the impacts of including minimum flow requirements in the catchment to improve the ecological condition of the river. Results showed that defining the magnitude of the restrictions and defining their location are equally important. It was highlighted that in this case study, the restrictions in the upper parts of the catchment had the largest economic impact, as they affected mining and hydro-power users mostly. Finally, the HEM was used to analyse the shared benefits of a mine tailings water recycling project in the catchment. It was found that the economic value of the project for agriculture, urban and hydro-power users may not be very large, because of the allocation rules for the additional water. However, the exercise illustrated how HEMs can be used to valuate the economic contributions that the mining industry can provide to other users by taking a catchment scale approach. This is of particular importance, as this sector tries to improve relations with communities and to demonstrate its contribution to sustainable development of regions. It is concluded that HEM can provide useful insight into water resources management in mining regions, although the set of metrics used have to be carefully selected as to properly take a catchment scale approach. It was also found that it is important to do a detailed representation of the water resources component, particularly when analysing areas where snow melt is a relevant hydrological process and when exploring the impacts of changing climate conditions. Finally, it was also shown that this tool may be used in the broader context of improving the mining water performance, an enhancing the relations with other water stakeholders in the catchment. ii Declaration by author This thesis is composed of my original work, and contains no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution by others to jointly-authored works that I have included in my thesis. I have clearly stated the contribution of others to my thesis as a whole, including statistical assistance, survey design, data analysis, significant technical procedures, professional editorial advice, financial support and any other original research work used or reported in my thesis. The content of my thesis is the result of work I have carried out since the commencement of my higher degree by research candidature and does not include a substantial part of work that has been submitted to qualify for the award of any other degree or diploma in any university or other tertiary institution. I have clearly stated which parts of my thesis, if any, have been submitted to qualify for another award. I acknowledge that an electronic copy of my thesis must be lodged with the University Library and, subject to the policy and procedures of The University of Queensland, the thesis be made available for research and study in accordance with the Copyright Act 1968 unless a period of embargo has been approved by the Dean of the Graduate School. I acknowledge that copyright of all material contained in my thesis resides with the copyright holder(s) of that material. Where appropriate I have obtained copyright permission from the copyright holder to reproduce material in this thesis and have sought permission from co- authors for any jointly authored works included in the thesis. iii Publications included in this thesis Peer-reviewed papers: Ossa-Moreno, J., McIntyre, N., Ali, S., Smart, J.C., Rivera, D., Lall, U. and Keir, G., 2018. The Hydro-economics of Mining. Ecological Economics, 145, pp.368-379. – Incorporated as Chapter 2. Submitted manuscripts included in this thesis Peer-reviewed papers: Ossa-Moreno, J., Keir, G., McIntyre, N., Cameletti, M. & Rivera, D. (2018) Comparison of approaches to interpolating climate observations in steep terrains with low-density gauging networks. Hydrology and Earth System Sciences - HESS (submitted). – Incorporated in Chapter 4. Other publications during candidature Peer-reviewed papers Ossa-Moreno, J., McIntyre, N., Ali, S., Smart, J.C., Rivera, D., Lall, U. and Keir, G., 2018. The Hydro-economics of Mining. Ecological Economics, 145, pp.368-379. – Incorporated as Chapter 2. McIntyre, N., Angarita, M., Fernandez, N., Camacho, L., Pearse, J., Huguet, C., Restrepo, O., Ossa-Moreno, J. (2018) A framework for assessing the impacts of mining development on regional water resources in Colombia. Water 10 (3), 268. AusIMM Bulletin article, co-authored: Pereira, L., Ossa-Moreno, J., Allen, M., Crosbie, J., 2018. Mining and Sustainable Development, Book review. The AusIMM Bulletin October 2018. https://www.ausimmbulletin.com/feature/book-review-mining-sustainable-development/ Conference papers: iv Ossa-Moreno, J., Keir, G. and McIntyre, N., 2016, April. Bayesian spatiotemporal interpolation of rainfall in the Central Chilean Andes. In EGU General Assembly Conference Abstracts (Vol. 18, p. 10533). Ossa-Moreno, J., Keir, G. and McIntyre, N., 2017, September. Hydro-economic modelling in mining regions: A case study in the Aconcagua Catchment. In 4th Water Research Conference Abstracts. Ossa-Moreno, J., Keir, G. and McIntyre, N., 2017, September. Hydro-economic modelling in mining regions: A case study in the Aconcagua Catchment. In International River Symposium Proceedings, Brisbane, Australia. Ossa Moreno, J.S., McIntyre, N., Rivera, D. and Smart, J.C.R., 2017, December. Hydro-economic modelling in mining catchments. In AGU Fall Meeting Abstracts. Ossa Moreno, J.S., McIntyre, N., Rivera, D. and Smart, J.C.R., 2018, May. A hydro- economic model of the Aconcagua basin: sensitivity of economic outcomes to climate and other uncertainties. Gecamin Water Congress 2018, Santiago, Chile. Ossa Moreno, J.S., McIntyre, N., Rivera, D. and Smart, J.C.R., 2018, September. Sensitivity of a hydro-economic model in a mining region to changes in hydrological and economic inputs. In Life of Mine Conference, Brisbane, Australia. Contributions by others to the thesis Dr Neil McIntyre (Principal PhD Supervisor) contributed to the design of the PhD, advised on the hydrological modelling methods used and provided advice on the content of all chapters of the PhD document. Dr Greg Keir contributed by suggesting the methods for the interpolation of climate variables and their implementation as scripts in R.