Abstract
Abstract. Corporations, industries and non-governmental organizations have become increasingly concerned with growing water risks in many parts of the world. Most of the focus has been on water scarcity and competition for the resource between agriculture, urban users, ecology and industry. However, water risks are multi-dimensional. Water-related hazards include flooding due to extreme rainfall, persistent drought and pollution, either due to industrial operations themselves, or to the failure of infrastructure. Most companies have risk management plans at each operational location to address these risks to a certain design level. The residual risk may or may not be managed, and is typically not quantified at a portfolio scale, i.e. across many sites. Given that climate is the driver of many of these extreme events, and there is evidence of quasi-periodic climate regimes at inter-annual and decadal timescales, it is possible that a portfolio is subject to persistent, multi-year exceedances of the design level. In other words, for a multi-national corporation, it is possible that there is correlation in the climate-induced portfolio water risk across its operational sites as multiple sites may experience a hazard beyond the design level in a given year. Therefore, from an investor's perspective, a need exists for a water risk index that allows for an exploration of the possible space and/or time clustering in exposure across many sites contained in a portfolio. This paper represents a first attempt to develop an index for financial exposure of a geographically diversified, global portfolio to the time-varying risk of climatic extremes using long daily global rainfall datasets derived from climate re-analysis models. Focusing on extreme daily rainfall amounts and using examples from major mining companies, we illustrate how the index can be developed. We discuss how companies can use it to explore their corporate exposure, and what they may need to disclose to investors and regulators to promote transparency as to risk exposure and mitigation efforts. For the examples of mining companies provided, we note that the actual exposure is substantially higher than would be expected in the absence of space and time correlation of risk as is usually tacitly assumed. We also find evidence for the increasing exposure to climate-induced risk, and for decadal variability in exposure. The relative vulnerability of different portfolios to multiple extreme events in a given year is also demonstrated.
Highlights
Long-term investors, such as sovereign wealth funds, need to account for risks that may manifest themselves over several decades, and they may have a very different perspective on risk than short-term investors
Global water risk including scarcity, flooding, pollution and anthropogenic climate change is of increasing concern to investors, companies, regulators and governments worldwide
Despite the recognition that these factors exist, an approach towards portfolio risk assessment that accounts for the geographical distribution of assets in a portfolio, and the associated exposure to climate extremes has not emerged. Such an assessment is of growing interest in particular to long-term investors, who are the owners of these multi-national businesses and currently lack a concrete methodology to compare www.hydrol-earth-syst-sci.net/21/2075/2017/
Summary
Long-term investors, such as sovereign wealth funds, need to account for risks that may manifest themselves over several decades, and they may have a very different perspective on risk than short-term investors. The subsequent investigation of the disaster led to a reformulation of policies, design standards, and monitoring requirements for tailing dams These have had an impact on the subsequent cost structure for managing such risks, but to our knowledge have not triggered a significant evaluation of the methods used to manage the residual risk from extreme rainfall events in the industry, other than. While the procedures we develop here could readily use future climate projections, in this paper we choose to develop examples that use long historical datasets so that we can reveal how potential changes in portfolio risk associated with rainfall extremes may have manifested over the past century or longer, providing a changing baseline for the risk that needs to be understood before undertaking an extrapolation to the future. This web application is available upon request from the authors
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