These results point again to difficulties in interpreting climate- and weather-oriented extremes in a hydrologic context. The breakout discussions noted that major uncertainties have presented themselves but have yet to be reconciled. Why have continental U. Are there inconsistencies in observed precipitation extremes and streamflow extremes, and if so, why?
What are the causes of pervasive increases in occurrence of low flows, for example, in the upper Midwest? To what extent is land cover, as contrasted with climate change, the cause of observed streamflow changes?
Assumptions on the occurrence of major hydrologic events to analyze extremes are based on the notion of stationarity, yet observational evidence increasingly shows that this assumption is untenable. Stationarity represents the idea that hydrologic systems fluctuate in an unchanging envelope of variability i.
Water management systems have been traditionally designed based on this assumption. Therefore, it is critical to the protection of life and property to understand if and how these assumptions are being violated Milly et al. From a scientific standpoint, fluctuations in stage heights and flood flows over the historical past constitute a natural experiment, with particular realizations that have in some cases been unexpected and changing over time. In other words, this hydrologic system no longer operates within its expected unchanging envelope of variability.
The statistical distribution of flood volumes that represent this system has become non-stationary. This document is the current standard in the United States, but it has not been updated since the early s. The workshop participants broadly agreed that although Bulletin 17B was concerned about non-stationarity, a remedy is not well addressed in the document. Because the available evidence at that time indicated that major climate-induced changes occur on the scale of thousands of years, Bulletin 17B assumed that floods are unaffected by the shorter-term changes that have been documented in the context of anthropogenically induced climate change.
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Regular revision of the Bulletin 17B guidelines as modeling and understanding of relevant phenomena improves would also be valuable. Regardless, continuing to use the assumption of stationarity in designing water management systems is no longer practical or defensible. How hydrologic extremes are intertwined with other anthropogenic effects is poorly understood. The nature of climate-induced hydrologic extremes is currently confounded by other, engineering-based, anthropogenic effects.
Interacting anthropogenic factors such as land cover change and the operation of water engineering facilities including dams, irrigation works, wells drawing on and drawing down aquifers, and interbasin transfers define the 21st century landscape and hydrologic dynamics of the continents. Additional confounding arises from the changing nature of climate variability, including the trajectories and patterns of storm tracks. Consequently, exploration of the climate extremes issue requires a better understanding of all of these factors and how they interact.
Such an understanding would greatly benefit the applications community, which requires highly region-specific and, in many cases, site-specific information. This is precisely the scale at which the current state of the art in climate modeling is least robust and least certain—and would create opportunities to harmonize traditional hydrologic field research carried out on more local domains with next-generation, high-resolution atmospheric modeling. Management and mission-oriented agencies with public-sector responsibilities have been provided with marginally useful scientific information about the likely manifestations of future climate change.
Future increases in flood extremes have often been inferred by climate modelers from extreme rainfall projections generalized in many cases within a global context. Yet, according to workshop participants, floods of interest to the user community occur locally in a magnitude and frequency context that is not the same as that implied by global models. It was noted during breakout sessions that the long time horizons, substantial uncertainty bounds, and relatively coarse-scale spatial resolutions despite progress in downscaling limit the usefulness of global climate model output for most hydrologic applications e.
Although research from the climate modeling community enhances understanding of atmospheric dynamics, it generates outputs that are not directly comparable to hydrologic extremes and are even less applicable to operational needs e.
Furthermore, smaller-scale regional climate models are not yet sophisticated enough to add significant value to this endeavor. Higher resolution regional climate models are now available that better resolve the effects of topography and may provide better estimates of precipitation extremes in areas where floods are mostly associated with large-scale storms e. However, the ability of these models to reproduce observed extremes remains to be demonstrated, and their resolution is insufficient to resolve the processes that control extreme precipitation in warm seasons, which dominate most of the United States outside of the West.
In addition, distinguishing signal versus noise is a challenging issue in the prediction. This challenge is exacerbated for regional climate models because variability from daily to interannual timescales is greater for small regions. Therefore, articulating regional results at a long enough timescale to tease out signal versus noise is difficult.
Planning and operations for water management and design of new projects require high-quality information in a site-specific context that the current generation of climate models cannot yet deliver to respond to realities dictated by regulation, current public policy, and other factors.
There are insufficient interactions and knowledge exchange between climate scientists, water scientists, and engineers and practitioners to solve these challenges. This contention is well illustrated by the use of terminology in the different communities involved with climatic and hydrologic extremes. If the scientific and practitioner communities can communicate and plan for extreme events now, then the results of their work will provide for improved preparation for events in the future.
Close cooperation between these communities to better assist each other is critical. In the absence of a common language, the different uses of important terms should be clearly defined and accepted, and each community should be more flexible and adaptable with respect to how the other uses the terms. Risk is generally defined as the probability of hazard occurrence multiplied by some measure of hazard consequence or capacity to be harmed given a particular level of hazard i. In the past, considerable emphasis was placed on the probability estimates for a particular hazardous process.
This is illustrated by the traditional civil engineering approach that uses probabilistic entities e. Flood and drought vulnerabilities are a consequence of human planning and actions. Humans have a propensity to settle in hydrologically dangerous settings, such as floodplains or drought-prone arid and semi-arid regions. Less emphasis has generally been placed on developing well-defined measures of vulnerability, which in this context is the varying level of. Vulnerability depends, in part, on social factors, and it continually changes in response to factors that differ from those measured in probabilistic analyses.
Although one of the primary goals of research on extreme events such as floods and droughts is risk reduction, the current emphasis of global climate science using models and observations addresses the probabilistic hazard component of risk NRC, a. We can easily read books on the mobile, tablets and Kindle, etc.
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