Gemma L. Harvey, Adam T. Hartley, Alexander J. Henshaw, Zareena Khan, Stewart J. Clarke, Christopher J. Sandom, Judy England, Sara King, Orlando Venn
{"title":"The role of rewilding in mitigating hydrological extremes: State of the evidence","authors":"Gemma L. Harvey, Adam T. Hartley, Alexander J. Henshaw, Zareena Khan, Stewart J. Clarke, Christopher J. Sandom, Judy England, Sara King, Orlando Venn","doi":"10.1002/wat2.1710","DOIUrl":null,"url":null,"abstract":"Landscape rewilding has the potential to help mitigate hydrological extremes by allowing natural processes to function. Our systematic review assessed the evidence base for rewilding-driven mitigation of high and low flows. The review uncovers a lack of research directly addressing rewilding, but highlights research in analogue contexts which can, with caution, indicate the nature of change. There is a lack of before-after studies that enable deeper examination of temporal trajectories and legacy effects, and a lack of research on the scrub and shrubland habitats common in rewilding projects. Over twice as much evidence is available for high flows compared to low flows, and fewer than one third of studies address high and low flows simultaneously, limiting our understanding of co-benefits and contrasting effects. Flow magnitude variables are better represented within the literature than flow timing variables, and there is greater emphasis on modeling for high flows, and on direct measurement for low flows. Most high flow studies report a mitigating effect, but with variability in the magnitude of effect, and some exceptions. The nature of change for low flows is more complex and suggests a higher potential for increased low flow risks associated with certain trajectories but is based on a very narrow evidence base. We recommend that future research aims to: capture effects on both high and low flow extremes for a given type of change; analyze both magnitude and timing characteristics of flow extremes; and examine temporal trajectories (before and after data) ideally using a full before-after-control-impact design.","PeriodicalId":501223,"journal":{"name":"WIREs Water","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"WIREs Water","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/wat2.1710","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Landscape rewilding has the potential to help mitigate hydrological extremes by allowing natural processes to function. Our systematic review assessed the evidence base for rewilding-driven mitigation of high and low flows. The review uncovers a lack of research directly addressing rewilding, but highlights research in analogue contexts which can, with caution, indicate the nature of change. There is a lack of before-after studies that enable deeper examination of temporal trajectories and legacy effects, and a lack of research on the scrub and shrubland habitats common in rewilding projects. Over twice as much evidence is available for high flows compared to low flows, and fewer than one third of studies address high and low flows simultaneously, limiting our understanding of co-benefits and contrasting effects. Flow magnitude variables are better represented within the literature than flow timing variables, and there is greater emphasis on modeling for high flows, and on direct measurement for low flows. Most high flow studies report a mitigating effect, but with variability in the magnitude of effect, and some exceptions. The nature of change for low flows is more complex and suggests a higher potential for increased low flow risks associated with certain trajectories but is based on a very narrow evidence base. We recommend that future research aims to: capture effects on both high and low flow extremes for a given type of change; analyze both magnitude and timing characteristics of flow extremes; and examine temporal trajectories (before and after data) ideally using a full before-after-control-impact design.