Research Impact Statement: Prioritizing stream barrier removal using dual-objective optimization quantifies tradeoffs between quality-weighted, connected fish habitat and water scarcity costs of reduced water deliveries.ABSTRACT: Instream barriers, such as dams, culverts, and diversions, alter hydrologic processes and aquatic habitat. Removing uneconomical and aging instream barriers is increasingly used for river restoration. Historically, selection of barrier removal projects used score-and-rank techniques, ignoring cumulative change and the spatial structure of stream networks. Likewise, most water supply models prioritize either human water uses or aquatic habitat, failing to incorporate both human and environmental water use benefits. Here, a dual-objective optimization model identifies barriers to remove that maximize connected aquatic habitat and minimize water scarcity. Aquatic habitat is measured using monthly average streamflow, temperature, channel gradient, and geomorphic condition as indicators of aquatic habitat suitability. Water scarcity costs are minimized using economic penalty functions while a budget constraint specifies the money available to remove barriers. We demonstrate the approach using a case study in Utah's Weber Basin to prioritize removal of instream barriers for Bonneville cutthroat trout, while maintaining human water uses. Removing 54 instream barriers reconnects about 160 km of quality-weighted habitat and costs approximately US$10 M. After this point, the cost-effectiveness of removing barriers to connect river habitat decreases. The modeling approach expands barrier removal optimization methods by explicitly including both economic and environmental water uses.(
BackgroundTo improve estimates of net primary production for terrestrial ecosystems of the continental United States, we evaluated a new image fusion technique to incorporate high resolution Landsat land cover data into a modified version of the CASA ecosystem model. The proportion of each Landsat land cover type within each 0.004 degree resolution CASA pixel was used to influence the ecosystem model result by a pure-pixel interpolation method.ResultsSeventeen Ameriflux tower flux records spread across the country were combined to evaluate monthly NPP estimates from the modified CASA model. Monthly measured NPP data values plotted against the revised CASA model outputs resulted in an overall R2 of 0.72, mainly due to cropland locations where irrigation and crop rotation were not accounted for by the CASA model. When managed and disturbed locations are removed from the validation, the R2 increases to 0.82.ConclusionsThe revised CASA model with pure-pixel interpolated vegetation index performed well at tower sites where vegetation was not manipulated or managed and had not been recently disturbed. Tower locations that showed relatively low correlations with CASA-estimated NPP were regularly disturbed by either human or natural forces.
The snowpack regime influences the timing of soil water available for transpiration and synchrony with the evapotranspiration (ET) energy demand (air temperature, VPD, and shortwave radiation). Variability of snowmelt timing, soil water availability, and the energy demand results in heterogeneous ET rates throughout a watershed. In this study, we assessed how ET and growing season length vary across five sites on an elevational gradient in the Dry Creek Watershed, ID, USA. We compared trends of daily and annual ET between 2012 and 2017 to environmental parameters of soil moisture, air temperature, vapour pressure deficit, snow cover, and precipitation. Trends between parameters and ET were evaluated at each site and compared between sites. We observed three trends in ET across the watershed. The first trend is at the low elevation site where the snow cover is not continuous throughout the winter and rain is the dominant precipitation form. The first day of the growing season and ET occurs early in the season when the energy demand is low and soil water is available. Annual ET at the low elevation site is a balance between spring precipitation providing soil water into the summer season and limiting the ET energy demand. The second trend occurs at the middle elevation site located in the rain–snow transition. At this site, ET increases with snow depth and spring precipitation extending the soil water availability into the summer season. At the higher elevation sites, ET is aligned with the energy demand and limited by growing season length. At the high elevation sites, decreasing snow depth and spring precipitation and increasing spring air temperatures result in greater annual ET rates. The observations from this study highlight the influence of environmental parameters and the potential sensitivity of ET to climate change.
Snowmelt is complex under heterogeneous forest cover due to spatially variable snow surface energy and mass balances and snow accumulation. Forest canopies influence the under-canopy snowpack net total radiation energy balance by enhancing longwave radiation, shading the surface from shortwave radiation, in addition to intercepting snow, and protecting the snow surface from the wind. Despite the importance of predicting snowmelt timing for water resources, there are limited observations of snowmelt timing in heterogeneous forest cover across the Intermountain West. This research seeks to evaluate the processes that control snowmelt timing and magnitude at two paired forested and open sites in semi-arid southern Idaho, USA. Snow accumulation, snowmelt, and snow energy balance components were measured at a marginal snowpack and seasonal snowpack location in the forest, sparse vegetation, forest edge, and open environments. At both locations, the snow disappeared either later in the forest or relatively uniformly in the open and forest. At the upper elevation location, a later peak in maximum snow depth resulted in more variable snow disappearance timing between the open and forest sites with later snow disappearance in the forest. Snow disappearance timing at the marginal snowpack location was controlled by the magnitude and duration of a late season storm increasing snow depth variability and reducing the shortwave radiation energy input. Here, a shorter duration spring storm resulted in more uniform snowmelt in the forest and open. At both locations, the low-density forests shaded the snow surface into the melt period slowing the melt rate in the forest. However, the forest site had less cold content to overcome before melting started, partially canceling out the forest shading effect. Our results highlight the regional similarities and differences of snow surface energy balance controls on the timing and duration of snowmelt.
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