{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T03:51:02Z","timestamp":1791258662728,"version":"4.1.0"},"reference-count":38,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T00:00:00Z","timestamp":1788393600000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Risk Analysis"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Hydrological risk is a growing challenge for renewable power systems, as droughts reduce generation, increase costs, and expose gaps in risk\u2010transfer mechanisms. We examine this problem in Brazil, home to the world's sixth\u2010largest electricity system and highly dependent on hydroelectricity, which accounted for 43% of installed generation capacity in 2026. We develop and evaluate a parametric insurance scheme for run\u2010of\u2010river hydroelectric generators indexed to the National System Operator's affluent flow measure. Using monthly energy and climate data from 151 powerplants between 2006 and 2022, we incorporate hydrological network dependence into insurance design. We model generation through a time\u2010varying upstream\u2013downstream spatial network and estimate it using a two\u2010way fixed\u2010effects SAR\u2010IV\u2010GMM\u2010HAC specification. We then use vine copulas to assess the dependence structure among climatic variables, hydrological conditions, and electricity generation, supporting the use of affluent flow as the insurance trigger. Results reveal significant hydrological propagation across connected plants and indicate that parametric insurance can mitigate drought\u2010related losses. However, feasibility depends on plant\u2010specific trigger design, diversification, reinsurance support, and payout magnitude. Water\u2010storage plants exhibit higher basis risk because of their operational flexibility.<\/jats:p>","DOI":"10.1111\/risa.70347","type":"journal-article","created":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T05:53:46Z","timestamp":1788501226000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["When There's No November Rain: Developing a Parametric Insurance for Hydroelectric Energy Generators in Brazil"],"prefix":"10.1111","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0178-4663","authenticated-orcid":false,"given":"Nathalia Costa","family":"Fonseca","sequence":"first","affiliation":[{"name":"Department of Accounting and Actuarial Science"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1076-662X","authenticated-orcid":false,"given":"Jo\u00e3o Vin\u00edcius Fran\u00e7a","family":"Carvalho","sequence":"additional","affiliation":[{"name":"Department of Accounting and Actuarial Science"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3006-1376","authenticated-orcid":false,"given":"Thiago Dutra","family":"Ara\u00fajo","sequence":"additional","affiliation":[{"name":"Department of Accounting and Actuarial Science"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7870-8736","authenticated-orcid":false,"given":"Andr\u00e9 Luis Squarize","family":"Chagas","sequence":"additional","affiliation":[{"name":"Department of Economics University of S\u00e3o Paulo \u2013 FEA\/USP  S\u00e3o Paulo Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,3]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijdrr.2021.102653"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-015-7799-1"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/RISA.70226"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1080\/02664763.2017.1420146"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2020.10.091"},{"key":"e_1_2_11_7_1","unstructured":"Cataia M.2019. \u201cMacrossistema el\u00e9trico brasileiro: Integra\u00e7\u00e3o Nacional e Centraliza\u00e7\u00e3o do Poder.\u201dV Simposio Internacional de La Historia de La Electrificaci\u00f3n: La Electricidad y La Transformaci\u00f3n de La Vida Urbana y Social581\u2013602."},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.5194\/nhess\u201021\u20102379\u20102021"},{"key":"e_1_2_11_9_1","doi-asserted-by":"crossref","unstructured":"Chagas A. L. S.2026.Decomposed Specification Tests for Asymmetric Network Panels.https:\/\/doi.org\/10.2139\/SSRN.6662238.","DOI":"10.2139\/ssrn.6662238"},{"key":"e_1_2_11_10_1","doi-asserted-by":"crossref","unstructured":"Corr\u00eaa C. S. andD. M. Y.Maya.2023. \u201cCompetitive Strategies for Renewable Energies: Brazilian Market.\u201dProceedings of the XV Ibero\u2010American Congress of Mechanical Engineering 230\u2013236.https:\/\/doi.org\/10.1007\/978\u20103\u2010031\u201038563\u20106_34.","DOI":"10.1007\/978-3-031-38563-6_34"},{"key":"e_1_2_11_11_1","volume-title":"Lecture Notes in Statistics","author":"Czado C.","year":"2019"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2024.108076"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rsase.2020.100301"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ribaf.2023.102065"},{"key":"e_1_2_11_15_1","unstructured":"Enr\u00edquez S. E.Hyman L.Ram\u00edrez\u2010Leiva E.Reyes L. M.Cardona andC.Gonz\u00e1lez\u2010Rivera.2020.Parametric Insurance for Renewable Electric Power Producers in Central America."},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1111\/risa.13122"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev\u2010financial\u2010111914\u2010041815"},{"key":"e_1_2_11_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.gloei.2020.01.008"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jup.2021.101267"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.21552\/cclr\/2018\/4\/4"},{"key":"e_1_2_11_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2018.02.030"},{"key":"e_1_2_11_22_1","unstructured":"IEA.2021.Hydropower Special Market Report.https:\/\/www.iea.org\/reports\/hydropower\u2010special\u2010market\u2010report."},{"key":"e_1_2_11_23_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007707430416"},{"key":"e_1_2_11_24_1","doi-asserted-by":"publisher","DOI":"10.1111\/1468\u20102354.00027"},{"key":"e_1_2_11_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2006.09.005"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2009.10.025"},{"key":"e_1_2_11_27_1","doi-asserted-by":"publisher","DOI":"10.1017\/S1446788700027312"},{"key":"e_1_2_11_28_1","doi-asserted-by":"publisher","DOI":"10.1057\/s10713\u2010018\u20100033\u2010z"},{"key":"e_1_2_11_29_1","doi-asserted-by":"publisher","DOI":"10.1111\/rmir.12146"},{"key":"e_1_2_11_30_1","unstructured":"McNeil A. 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