Incorporating probabilistic seasonal climate forecasts into river management using a risk-based framework

被引:12
|
作者
Towler, Erin [1 ]
Roberts, Mike [2 ]
Rajagopalan, Balaji [3 ,4 ]
Sojda, Richard S. [5 ]
机构
[1] Natl Ctr Atmospher Res, Boulder, CO 80307 USA
[2] Montana Dept Nat Resources & Conservat, Helena, MT USA
[3] Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA
[4] Univ Colorado, Dept Civil Architectural & Environm Engn, Boulder, CO 80309 USA
[5] US Geol Survey, Northern Rocky Mt Sci Ctr, Bozeman, MT USA
基金
美国国家科学基金会;
关键词
water management; risk; fisheries; generalized linear model; seasonal forecasting; drought; ENSEMBLE STREAMFLOW FORECASTS; WATER MANAGEMENT; FLOW; BASIN;
D O I
10.1002/wrcr.20378
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Despite the influence of hydroclimate on river ecosystems, most efforts to date have focused on using climate information to predict streamflow for water supply. However, as water demands intensify and river systems are increasingly stressed, research is needed to explicitly integrate climate into streamflow forecasts that are relevant to river ecosystem management. To this end, we present a five step risk-based framework: (1) define risk tolerance, (2) develop a streamflow forecast model, (3) generate climate forecast ensembles, (4) estimate streamflow ensembles and associated risk, and (5) manage for climate risk. The framework is successfully demonstrated for an unregulated watershed in southwest Montana, where the combination of recent drought and water withdrawals has made it challenging to maintain flows needed for healthy fisheries. We put forth a generalized linear modeling (GLM) approach to develop a suite of tools that skillfully model decision-relevant low flow characteristics in terms of climate predictors. Probabilistic precipitation forecasts are used in conjunction with the GLMs, resulting in season-ahead prediction ensembles that provide the full risk profile. These tools are embedded in an end-to-end risk management framework that directly supports proactive fish conservation efforts. Results show that the use of forecasts can be beneficial to planning, especially in wet years, but historical precipitation forecasts are quite conservative (i.e., not very sharp). Synthetic forecasts show that a modest sharpening can strongly impact risk and improve skill. We emphasize that use in management depends on defining relevant environmental flows and risk tolerance, requiring local stakeholder involvement. Key Points <list list-type="bulleted"> Connects climate forecasts with sustainable ecosystem management General Linear Models used to predict decision-relevant streamflow attributes Presents end-to-end risk-based framework to support proactive planning
引用
收藏
页码:4997 / 5008
页数:12
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