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Guillaume S. Mauger

Publications and source records attributed to Guillaume S. Mauger.

4 recordsLinked to original sources

How does precipitation variability control bedload response across a mountainous channel network in a maritime climate?

Modeled stream discharge is often used to drive sediment transport models across channel networks. Because sediment transport varies non-linearly with flow rates, discharge modeled from daily total precipitation distributed evenly over 24-hrs may significantly underestimate actual bedload transport capacity. In this study, we assume bedload transport capacity determined from a hydrograph resulting from the use of hourly (1-h) precipitation is a close approximation of actual transport capacity and quantify the error introduced into a network-scale bedload transport model driven by daily precipitation at channel network locations varying from lowland pool-riffle channels to upland colluvial channels in a watershed where snow accumulation and melt can affect runoff processes. Transport capacity is determined using effective stresses and the Wilcock and Crowe (2003) equations and expressed in terms of transport capacity normalized by the bankfull value. We find that, depending on channel network location, cumulative error can range from 10 - 20% to more than two orders of magnitude. Surprisingly, variation in flow rates due to differences in hillslope and channel runoff do not seem to dictate the network locations where the largest errors in predicted bedload transport capacity occur. Rather, spatial variability of the magnitude of the effective-bankfull-excess shear stress and changes in runoff due to snow accumulation and melt exert the greatest influence. These findings have implications for flood-hazard and aquatic habitat models that rely on modeled sediment transport driven by coarse-temporal-resolution climate data.

Washington

An assessment of vertical land movement to support coastal hazards planning in Washington state

The sea and land change elevation spatially and temporally from a multitude of processes, so it is necessary to constrain the movement of both to evaluate how coastlines will evolve and how those evolving coastlines will impact the natural and built environment over time. We combine land movement observations from global navigation satellite systems (GNSSs), leveling of geodetic monuments, and tide gauge records with a tectonic model of the Cascadia subduction zone to constrain absolute rates of vertical land movement in coastal Washington. We infer rates of vertical land movement in areas lacking direct observations by interpolating high-quality land movement observations and a discretely sampled interseismic locking model. Here we present a model of absolute vertical land movement that is combined with sea level rise estimates to inform local relative sea level projections on a community-scale. The most rapid vertical uplift (~3.5 mm/year) of the land is found across the northwest Olympic Peninsula, which currently outpaces sea level rise. Conversely, some areas, including a stretch of the northern Pacific Ocean coast from La Push to Kalaloch and the southern Puget Sound, are found to be subsiding at 0.5–1.0 mm/year, exacerbating the rate of relative sea level rise and thereby increasing the vulnerability of coastal communities.

Washington

Uncertainty and extreme events in future climate and hydrologic projections for the Pacific Northwest: providing a basis for vulnerability and core/corridor assessments

The purpose of this project was to (1) provide an internally-consistent set of downscaled projections across the Western U.S., (2) include information about projection uncertainty, and (3) assess projected changes of hydrologic extremes. These objectives were designed to address decision support needs for climate adaptation and resource management actions. Specifically, understanding of uncertainty in climate projections – in particular for extreme events – is currently a key scientific and management barrier to adaptation planning and vulnerability assessment. The new dataset fills in the Northwest domain to cover a key gap in the previous dataset, adds additional projections (both from other global climate models and a comparison with dynamical downscaling) and includes an assessment of changes to flow and soil moisture extremes. This new information can be used to assess variations in impacts across the landscape, uncertainty in projections, and how these differ as a function of region, variable, and time period. In this project, existing University of Washington Climate Impacts Group (UW CIG) products were extended to develop a comprehensive data archive that accounts (in a reigorous and physically based way) for climate model uncertainty in future climate and hydrologic scenarios. These products can be used to determine likely impacts on vegetation and aquatic habitat in the Pacific Northwest (PNW) region, including WA, OR, ID, northwest MT to the continental divide, northern CA, NV, UT, and the Columbia Basin portion of western WY New data series and summaries produced for this project include: 1) extreme statistics for surface hydrology (e.g. frequency of soil moisture and summer water deficit) and streamflow (e.g. the 100-year flood, extreme 7-day low flows with a 10-year recurrence interval); 2) snowpack vulnerability as indicated by the ratio of April 1 snow water to cool-season precipitation; and, 3) uncertainty analyses for multiple climate scenarios.

Arizona, California, Colorado, Idaho, Montana, Nev

Mount Rainier National Park

Natural Resource Condition Assessments (NRCAs) evaluate current conditions for a subset of natural resources and resource indicators in national parks. NRCAs also report on trends in resource condition (when possible), identify critical data gaps, and characterize a general level of confidence for study findings. The resources and indicators emphasized in a given project depend on the park’s resource setting, status of resource stewardship planning and science in identifying high-priority indicators, and availability of data and expertise to assess current conditions for a variety of potential study resources and indicators. Although the primary objective of NRCAs is to report on current conditions relative to logical forms of reference conditions and values, NRCAs also report on trends, when appropriate (i.e., when the underlying data and methods support such reporting), as well as influences on resource conditions. These influences may include past activities or conditions that provide a helpful context for understanding current conditions and present-day threats and stressors that are best interpreted at park, watershed, or landscape scales (though NRCAs do not report on condition status for land areas and natural resources beyond park boundaries). Intensive cause-andeffect analyses of threats and stressors, and development of detailed treatment options, are outside the scope of NRCAs. It is also important to note that NRCAs do not address resources that lack sufficient data for assessment. For Mount Rainier National Park, this includes most invertebrate species and many other animal species that are subject to significant stressors from climate change and other anthropogenic sources such as air pollutants and recreational use. In addition, we did not include an analysis of the physical hydrology associated with streams (such as riverine landforms, erosion and aggradation which is significant in MORA streams), due to a loss of staff expertise from the USGS-BRD staff conducting the work, and human disturbance landcover issues such as the effects of roads, trails, and other anthropogenic developments due to lack of funds.

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