{"title":"开发和评估气候变化对洪水和干旱影响的决策支持指标(DSIs):挪威西部的案例研究","authors":"Shaochun Huang, Stephanie Eisner, S. Beldring","doi":"10.2166/wcc.2024.198","DOIUrl":null,"url":null,"abstract":"\n \n The decision support indicators (DSIs) are specifically designed to inform local and regional stakeholders on the characteristics of a predicted event to facilitate decision-making. They can be classified as conventional, impact-based and event-based DSIs. This study aims to develop methodologies for calculating event-based DSIs and to evaluate the usefulness of different classes of DSIs for climate impact assessment and climate actions by learning about users' perceptions. The DSIs are calculated based on an ensemble of hydrological projections in western Norway under two representative concentration pathway (RCP) scenarios. The definitions, methodologies and results of the indicators are summarized in questionnaires and evaluated by key stakeholders in terms of understandability, importance, plausibility and applicability. Based on the feedback, we conclude that the conventional DSIs are still preferred by stakeholders and an appropriate selection of conventional DSIs may overcome the understanding problems between the scientists and stakeholders. The DSIs based on well-known historical events are easy to understand and can be a useful tool to convey climate information to the public. However, they are not readily implemented by stakeholders in the decision-making process. The impact-based DSI is generally easy to understand and important but it can be restricted to specific impact sectors.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":"140 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Developing and evaluating decision support indicators (DSIs) of climate change impacts on flood and drought: a case study in Western Norway\",\"authors\":\"Shaochun Huang, Stephanie Eisner, S. Beldring\",\"doi\":\"10.2166/wcc.2024.198\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n The decision support indicators (DSIs) are specifically designed to inform local and regional stakeholders on the characteristics of a predicted event to facilitate decision-making. They can be classified as conventional, impact-based and event-based DSIs. This study aims to develop methodologies for calculating event-based DSIs and to evaluate the usefulness of different classes of DSIs for climate impact assessment and climate actions by learning about users' perceptions. The DSIs are calculated based on an ensemble of hydrological projections in western Norway under two representative concentration pathway (RCP) scenarios. The definitions, methodologies and results of the indicators are summarized in questionnaires and evaluated by key stakeholders in terms of understandability, importance, plausibility and applicability. Based on the feedback, we conclude that the conventional DSIs are still preferred by stakeholders and an appropriate selection of conventional DSIs may overcome the understanding problems between the scientists and stakeholders. The DSIs based on well-known historical events are easy to understand and can be a useful tool to convey climate information to the public. However, they are not readily implemented by stakeholders in the decision-making process. The impact-based DSI is generally easy to understand and important but it can be restricted to specific impact sectors.\",\"PeriodicalId\":506949,\"journal\":{\"name\":\"Journal of Water and Climate Change\",\"volume\":\"140 6\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Water and Climate Change\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/wcc.2024.198\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Water and Climate Change","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/wcc.2024.198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Developing and evaluating decision support indicators (DSIs) of climate change impacts on flood and drought: a case study in Western Norway
The decision support indicators (DSIs) are specifically designed to inform local and regional stakeholders on the characteristics of a predicted event to facilitate decision-making. They can be classified as conventional, impact-based and event-based DSIs. This study aims to develop methodologies for calculating event-based DSIs and to evaluate the usefulness of different classes of DSIs for climate impact assessment and climate actions by learning about users' perceptions. The DSIs are calculated based on an ensemble of hydrological projections in western Norway under two representative concentration pathway (RCP) scenarios. The definitions, methodologies and results of the indicators are summarized in questionnaires and evaluated by key stakeholders in terms of understandability, importance, plausibility and applicability. Based on the feedback, we conclude that the conventional DSIs are still preferred by stakeholders and an appropriate selection of conventional DSIs may overcome the understanding problems between the scientists and stakeholders. The DSIs based on well-known historical events are easy to understand and can be a useful tool to convey climate information to the public. However, they are not readily implemented by stakeholders in the decision-making process. The impact-based DSI is generally easy to understand and important but it can be restricted to specific impact sectors.