دانلود رایگان مقاله انگلیسی کاربرد سناریو های مصنوعی در اشاره به نگرانی های منابع آبی: مطالعه حوزه رودخانه کلرادو - الزویر 2017

ABSTRACT

Water managers are increasingly interested in better understanding and planning for projected resource impacts from climate change. In this management-guided study, we use a very large suite of synthetic climate scenarios in a statistical modeling framework to simultaneously evaluate how (1) average temperature and precipitation changes, (2) initial basin conditions, and (3) temporal characteristics of the input climate data influence wateryear flow in the Upper Colorado River. The results here suggest that existing studies may underestimate the degree of uncertainty in future streamflow, particularly under moderate temperature and precipitation changes. However, we also find that the relative severity of future flow projections within a given climate scenario can be estimated with simple metrics that characterize the input climate data and basin conditions. These results suggest that simple testing, like the analyses presented in this paper, may be helpful in understanding differences between existing studies or in identifying specific conditions for physically based mechanistic modeling. Both options could reduce overall cost and improve the efficiency of conducting climate change impacts studies.

5. Conclusions

Numerous studies have addressed the question of how changing climate will influence streamflow, yet water resource managers tasked with providing sufficient water for irrigation, power generation, and household needs, still have concerns about responding to changing climate and about the large uncertainty in climate change projections. Will a new set of climate projections associated with CMIP6 require reevaluating streamflow projections? Could there be surprises where relatively modest changes in climate produce significant drought?

Water managers were integral in defining key elements of the research, and many provided useful and critical feedback on which results were particularly valuable and how they could be most effectively displayed. For example, managers’ interest in the role of temperature drove the need to include temperature as a forcing variable. We have presented these results to managers through a webinar and project meeting and are continuing our collaboration on additional questions. For greater dissemination of the results, we plan to translate the peerreviewed paper into a shorter publically accessible fact sheet and host a question-and-answer period with managers working in the Colorado basin and across the western U.S.

The approach we have taken here, driving a simple statistical model with synthetic climate data, provides critical context for evaluating existing streamflow projections made with more traditional “top-down” approaches. For example, such studies could be used to identify metrics that are associated with particularly modest or severe consequences relative to the projected climate change. Existing studies could be assessed in the context of those metrics. The approach taken here provides an example for exploring the concerns raised by water managers regarding future hydroclimatic conditions, and targeting particular timescales of significance to management, in a quick and economical way. Moreover, these large ensemble studies can assist managers in prioritizing which climate scenarios, initial conditions, and ecohydrological changes should be chosen for more detailed analysis, potentially reducing the costs and effort associated with climate change impacts analyses and planning.