Managing Drought Related Financial Risks with Water Futures

Managing Drought Related Financial Risks with Water Futures | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 25 June 2025 V1 Latest version Share on Managing Drought Related Financial Risks with Water Futures Authors : Dan Li 0000-0002-6843-9250 [email protected] , Rohini S Gupta 0000-0003-3538-0675 , Harrison Zeff , and Gregory W. Characklis 0000-0001-9882-9068 Authors Info & Affiliations https://doi.org/10.22541/au.175087591.14639320/v1 378 views 211 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Water markets for short-term transfers exhibit high price volatility linked to hydrologic conditions, creating financial risk when prices are intermittently driven higher by drought. The California water price index (Nasdaq: NQH2O) alongside its associated water futures (CME: H2O) offer water users an opportunity to hedge against unfavorable price movements in California’s water market, particularly during extended drought periods. This research explores the potential of systems-based models to predict water index prices using ensemble forecasts of daily water deliveries, storage levels, and irrigation district demands in the Central Valley of California. Forecasting of the spot market price was conducted using a random forest model trained on modelled water supply and delivery data from 2013 to 2024, achieving an R² value of 0.98. These predictions are applied to a 9-month futures contract to manage the costs of supplemental short-term water purchases during drought for an industrial farm in California. By covering 50% of the water deficit with futures contracts, the strategy reduces variance by 25.6% across a 100-member synthetically generated ensemble, while maintaining relatively low estimated contract fees and initial margin requirements. The seasonal hydrologic forecasting model of water prices thus offers a cost-effective hedging tool to reduce water purchase cost volatility, providing an enhanced ability to manage the financial risk posed by constrained water resources and competing demands. Supplementary Material File (1035605_0_merged_1748279412.pdf) Download 1.75 MB File (agu_manuscript_final.docx) Download 4.52 MB File (supporting information.docx) Download 1.09 MB Information & Authors Information Version history V1 Version 1 25 June 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords agricultural environmental sciences financial risk analysis hydrology risk mitigation Authors Affiliations Dan Li 0000-0002-6843-9250 [email protected] The University of North Carolina at Chapel Hill View all articles by this author Rohini S Gupta 0000-0003-3538-0675 Cornell University View all articles by this author Harrison Zeff The University of North Carolina at Chapel Hill View all articles by this author Gregory W. Characklis 0000-0001-9882-9068 University of North Carolina - Chapel Hill View all articles by this author Metrics & Citations Metrics Article Usage 378 views 211 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Dan Li, Rohini S Gupta, Harrison Zeff, et al. Managing Drought Related Financial Risks with Water Futures. Authorea . 25 June 2025. DOI: https://doi.org/10.22541/au.175087591.14639320/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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