D. Partington, M. Thyer, M. Shanafield, D. McInerney, S. Westra, H. Maier, C. Simmons, B. Croke, A. Jakeman, H. Gupta, D. Kavetski
{"title":"预测野火引起的径流变化:建模方法的回顾和综合","authors":"D. Partington, M. Thyer, M. Shanafield, D. McInerney, S. Westra, H. Maier, C. Simmons, B. Croke, A. Jakeman, H. Gupta, D. Kavetski","doi":"10.1002/wat2.1599","DOIUrl":null,"url":null,"abstract":"Wildfires elicit a diversity of hydrological changes, impacting processes that drive both water quantity and quality. As wildfires increase in frequency and severity, there is a need to assess the implications for the hydrological response. Wildfire‐related hydrological changes operate at three distinct timescales: the immediate fire aftermath, the recovery phase, and long‐term across multiple cycles of wildfire and regrowth. Different dominant processes operate at each timescale. Consequentially, models used to predict wildfire impacts need an explicit representation of different processes, depending on modeling objectives and wildfire impact timescale. We summarize existing data‐driven, conceptual, and physically based models used to assess wildfire impacts on runoff, identifying the dominant assumptions, process representations, timescales, and key limitations of each model type. Given the substantial observed and projected changes to wildfire regimes and associated hydrological impacts, it is likely that physically based models will become increasingly important. This is due to their capacity both to simulate simultaneous changes to multiple processes, and their use of physical and biological principles to support extrapolation beyond the historical record. Yet benefits of physically based models are moderated by their higher data requirements and lower computational speed. We argue that advances in predicting hydrological impacts from wildfire will come through combining these physically based models with new computationally faster conceptual and reduced‐order models. The aim is to combine the strengths and overcome weaknesses of the different model types, enabling simulations of critical water resources scenarios representing wildfire‐induced changes to runoff.","PeriodicalId":23774,"journal":{"name":"Wiley Interdisciplinary Reviews: Water","volume":null,"pages":null},"PeriodicalIF":6.8000,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Predicting wildfire induced changes to runoff: A review and synthesis of modeling approaches\",\"authors\":\"D. Partington, M. Thyer, M. Shanafield, D. McInerney, S. Westra, H. Maier, C. Simmons, B. Croke, A. Jakeman, H. Gupta, D. Kavetski\",\"doi\":\"10.1002/wat2.1599\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wildfires elicit a diversity of hydrological changes, impacting processes that drive both water quantity and quality. As wildfires increase in frequency and severity, there is a need to assess the implications for the hydrological response. Wildfire‐related hydrological changes operate at three distinct timescales: the immediate fire aftermath, the recovery phase, and long‐term across multiple cycles of wildfire and regrowth. Different dominant processes operate at each timescale. Consequentially, models used to predict wildfire impacts need an explicit representation of different processes, depending on modeling objectives and wildfire impact timescale. We summarize existing data‐driven, conceptual, and physically based models used to assess wildfire impacts on runoff, identifying the dominant assumptions, process representations, timescales, and key limitations of each model type. Given the substantial observed and projected changes to wildfire regimes and associated hydrological impacts, it is likely that physically based models will become increasingly important. This is due to their capacity both to simulate simultaneous changes to multiple processes, and their use of physical and biological principles to support extrapolation beyond the historical record. Yet benefits of physically based models are moderated by their higher data requirements and lower computational speed. We argue that advances in predicting hydrological impacts from wildfire will come through combining these physically based models with new computationally faster conceptual and reduced‐order models. The aim is to combine the strengths and overcome weaknesses of the different model types, enabling simulations of critical water resources scenarios representing wildfire‐induced changes to runoff.\",\"PeriodicalId\":23774,\"journal\":{\"name\":\"Wiley Interdisciplinary Reviews: Water\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2022-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Wiley Interdisciplinary Reviews: Water\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1002/wat2.1599\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wiley Interdisciplinary Reviews: Water","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1002/wat2.1599","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Predicting wildfire induced changes to runoff: A review and synthesis of modeling approaches
Wildfires elicit a diversity of hydrological changes, impacting processes that drive both water quantity and quality. As wildfires increase in frequency and severity, there is a need to assess the implications for the hydrological response. Wildfire‐related hydrological changes operate at three distinct timescales: the immediate fire aftermath, the recovery phase, and long‐term across multiple cycles of wildfire and regrowth. Different dominant processes operate at each timescale. Consequentially, models used to predict wildfire impacts need an explicit representation of different processes, depending on modeling objectives and wildfire impact timescale. We summarize existing data‐driven, conceptual, and physically based models used to assess wildfire impacts on runoff, identifying the dominant assumptions, process representations, timescales, and key limitations of each model type. Given the substantial observed and projected changes to wildfire regimes and associated hydrological impacts, it is likely that physically based models will become increasingly important. This is due to their capacity both to simulate simultaneous changes to multiple processes, and their use of physical and biological principles to support extrapolation beyond the historical record. Yet benefits of physically based models are moderated by their higher data requirements and lower computational speed. We argue that advances in predicting hydrological impacts from wildfire will come through combining these physically based models with new computationally faster conceptual and reduced‐order models. The aim is to combine the strengths and overcome weaknesses of the different model types, enabling simulations of critical water resources scenarios representing wildfire‐induced changes to runoff.
期刊介绍:
The WIREs series is truly unique, blending the best aspects of encyclopedic reference works and review journals into a dynamic online format. These remarkable resources foster a research culture that transcends disciplinary boundaries, all while upholding the utmost scientific and presentation excellence. However, they go beyond traditional publications and are, in essence, ever-evolving databases of the latest cutting-edge reviews.