2006 /program/hydrosciences/ en INVITED FACULTY TALK - The “Teflon Basin” Myth Debunked: Most Snowmelt Runoff Is “Old” Water And Not “New” Water /program/hydrosciences/2018/08/23/invited-faculty-talk-teflon-basin-myth-debunked-most-snowmelt-runoff-old-water-and-not <span>INVITED FACULTY TALK - The “Teflon Basin” Myth Debunked: Most Snowmelt Runoff Is “Old” Water And Not “New” Water</span> <span><span>Anonymous (not verified)</span></span> <span><time datetime="2018-08-23T12:19:54-06:00" title="Thursday, August 23, 2018 - 12:19">Thu, 08/23/2018 - 12:19</time> </span> <div role="contentinfo" class="container ucb-article-categories" itemprop="about"> <span class="visually-hidden">Categories:</span> <div class="ucb-article-category-icon" aria-hidden="true"> <i class="fa-solid fa-folder-open"></i> </div> <a href="/program/hydrosciences/taxonomy/term/58"> 2006 </a> <a href="/program/hydrosciences/taxonomy/term/6"> Abstract </a> </div> <div role="contentinfo" class="container ucb-article-tags" itemprop="keywords"> <span class="visually-hidden">Tags:</span> <div class="ucb-article-tag-icon" aria-hidden="true"> <i class="fa-solid fa-tags"></i> </div> <a href="/program/hydrosciences/taxonomy/term/84" hreflang="en">Talk</a> </div> <span>Mark W Williams</span> <div class="ucb-article-content ucb-striped-content"> <div class="container"> <div class="paragraph paragraph--type--article-content paragraph--view-mode--default 3"> <div class="ucb-article-row-subrow row"> <div class="ucb-article-text col-lg d-flex align-items-center" itemprop="articleBody"> <div><p><strong>Williams</strong>, Mark W&nbsp;<sup>1</sup></p><p><sup>1</sup>&nbsp;INSTAAR and Geography</p><p>New research shows high-altitude aquifers honeycomb parts of the Colorado Rockies, trapping snowmelt and debunking the myth that high mountain valleys act as “Teflon basins” to rush water downstream. In much of western North America, snow and snow melt provides the primary means for storage of winter precipitation, effectively transferring water from the relatively wet winter season to the typically dry summers. A common assumption is that high-elevation catchments in the western United States behave like "Teflon basins" and that water released from seasonal storage in snow packs flows directly into streams with little or no interaction with geologic or biologic materials.</p><p>We determined source waters and flowpaths in the Green Lakes valley of the Front Range using isotopic, geochemical, and hydrometric data in 2- and 3- component hydrograph separations along with end-member mixing analysis (EMMA). EMMA results showed that much of the water released from the seasonal snowpack infiltrated into subsurface reservoirs and that old groundwater contributed almost 50% of flow on the rising limb of the hydrograph and 80% on the recession limb. Thus most of the water sampled from North «Ƶ Creek during the runoff months was “old groundwater” that had been stored in subterranean mountain catchments.</p><p>The common perception that water stored in mountain snow packs runs immediately into streams and rivers is probably wrong, and the Teflon basin myth is incorrect.</p></div> </div> <div class="ucb-article-content-media ucb-article-content-media-right col-lg"> <div> <div class="paragraph paragraph--type--media paragraph--view-mode--default"> </div> </div> </div> </div> </div> </div> </div> <h2> <div class="paragraph paragraph--type--ucb-related-articles-block paragraph--view-mode--default"> <div>Off</div> </div> </h2> <div>Traditional</div> <div>0</div> <div>On</div> <div>White</div> Thu, 23 Aug 2018 18:19:54 +0000 Anonymous 1245 at /program/hydrosciences Retreat Rates And Controls On The Form Of Hard-Capped Cliffs In Plateau Country /program/hydrosciences/2018/08/23/retreat-rates-and-controls-form-hard-capped-cliffs-plateau-country <span>Retreat Rates And Controls On The Form Of Hard-Capped Cliffs In Plateau Country</span> <span><span>Anonymous (not verified)</span></span> <span><time datetime="2018-08-23T12:18:03-06:00" title="Thursday, August 23, 2018 - 12:18">Thu, 08/23/2018 - 12:18</time> </span> <div role="contentinfo" class="container ucb-article-categories" itemprop="about"> <span class="visually-hidden">Categories:</span> <div class="ucb-article-category-icon" aria-hidden="true"> <i class="fa-solid fa-folder-open"></i> </div> <a href="/program/hydrosciences/taxonomy/term/58"> 2006 </a> <a href="/program/hydrosciences/taxonomy/term/6"> Abstract </a> </div> <div role="contentinfo" class="container ucb-article-tags" itemprop="keywords"> <span class="visually-hidden">Tags:</span> <div class="ucb-article-tag-icon" aria-hidden="true"> <i class="fa-solid fa-tags"></i> </div> <a href="/program/hydrosciences/taxonomy/term/86" hreflang="en">Poster</a> </div> <span>Dylan J Ward</span> <div class="ucb-article-content ucb-striped-content"> <div class="container"> <div class="paragraph paragraph--type--article-content paragraph--view-mode--default 3"> <div class="ucb-article-row-subrow row"> <div class="ucb-article-text col-lg d-flex align-items-center" itemprop="articleBody"> <div><p><strong>Ward</strong>, Dylan J&nbsp;<sup>1</sup>&nbsp;;&nbsp;<strong>Anderson</strong>, Robert S&nbsp;<sup>2</sup></p><p><sup>1</sup>&nbsp;University of Colorado Dept. of Geological Sciences and INSTAAR<br><sup>2</sup>&nbsp;University of Colorado Dept. of Geological Sciences and INSTAAR</p><p>The retreat of hard-capped cliffbands represents the erosional response of the Plateau landscape to changes in base level, i.e., incision of major rivers such as the Colorado River. Treatments of the mechanisms and morphologies of scarp retreat have lacked quantitative constraint on rates of backwearing of cliffbands and the dominant controls on those rates. We measure spatially and temporally averaged scarp retreat rates in areas such as the Book Cliffs of CO and UT and model the evolution of idealized scarps. Retreat rates are determined using a modification of the cosmogenic basin-averaged erosion rate method. Measured rates, along with field and GIS observations, constrain parameters in a 1D numerical model we use to assess the dominant controls on scarp morphology and retreat rate. The model simulates retreat of cliff profiles through time, driven by incision of channels on the soft rock plinth. Retreat proceeds by knickpoint migration and/or landsliding; debris-armoring of the channel is captured. Realistic morphologies are generated in the simplest case by spatially varying model fluvial erodibility depending on the substrate (hard rock, soft rock, or debris). Retreat rate and morphology vary as drainage area declines through time. Exploring feedbacks between morphology, mass wasting, and debris armoring of the channels will require further attention to the physics and rates of processes involved in scarp retreat.</p></div> </div> <div class="ucb-article-content-media ucb-article-content-media-right col-lg"> <div> <div class="paragraph paragraph--type--media paragraph--view-mode--default"> </div> </div> </div> </div> </div> </div> </div> <h2> <div class="paragraph paragraph--type--ucb-related-articles-block paragraph--view-mode--default"> <div>Off</div> </div> </h2> <div>Traditional</div> <div>0</div> <div>On</div> <div>White</div> Thu, 23 Aug 2018 18:18:03 +0000 Anonymous 1243 at /program/hydrosciences Morphology And Potential Retreat Processes Of East Fork Falls, Roan Plateau, Colorado /program/hydrosciences/2018/08/23/morphology-and-potential-retreat-processes-east-fork-falls-roan-plateau-colorado <span>Morphology And Potential Retreat Processes Of East Fork Falls, Roan Plateau, Colorado</span> <span><span>Anonymous (not verified)</span></span> <span><time datetime="2018-08-23T12:17:30-06:00" title="Thursday, August 23, 2018 - 12:17">Thu, 08/23/2018 - 12:17</time> </span> <div role="contentinfo" class="container ucb-article-categories" itemprop="about"> <span class="visually-hidden">Categories:</span> <div class="ucb-article-category-icon" aria-hidden="true"> <i class="fa-solid fa-folder-open"></i> </div> <a href="/program/hydrosciences/taxonomy/term/58"> 2006 </a> <a href="/program/hydrosciences/taxonomy/term/6"> Abstract </a> </div> <div role="contentinfo" class="container ucb-article-tags" itemprop="keywords"> <span class="visually-hidden">Tags:</span> <div class="ucb-article-tag-icon" aria-hidden="true"> <i class="fa-solid fa-tags"></i> </div> <a href="/program/hydrosciences/taxonomy/term/86" hreflang="en">Poster</a> </div> <span>David Thul</span> <div class="ucb-article-content ucb-striped-content"> <div class="container"> <div class="paragraph paragraph--type--article-content paragraph--view-mode--default 3"> <div class="ucb-article-row-subrow row"> <div class="ucb-article-text col-lg d-flex align-items-center" itemprop="articleBody"> <div><p><strong>Thul</strong>, David&nbsp;<sup>1</sup>&nbsp;;&nbsp;<strong>Berlin</strong>, Maureen&nbsp;<sup>2</sup>&nbsp;;&nbsp;<strong>Anderson</strong>, Robert S.&nbsp;<sup>3</sup></p><p><sup>1</sup>&nbsp;Geological Sciences, Univ. of Colorado at «Ƶ<br><sup>2</sup>&nbsp;Geological Sciences, Univ. of Colorado at «Ƶ<br><sup>3</sup>&nbsp;INSTAAR and Geological Sciences, Univ. of Colorado at «Ƶ</p><p>Colorado's Roan Plateau provides a natural laboratory for the study of bedrock river incision due to its predominantly horizontal stratigraphy and numerous waterfalls up to 50 m in height. The morphology of these waterfalls can provide an important constraint on processes of waterfall retreat. Using a laser range finder we documented the morphology of East Fork Falls by surveying stratigraphic markers along the waterfall face, cliff tops, and points around the plunge pool. East Fork Falls has areas of undercutting where the face is recessed 2-20 m beyond the waterfall lip. The north and south faces have markedly different morphology; the north face is overhanging and blocky while the south face is smooth and nearly vertical. Also, the plan form of the waterfall alcove is roughly parabolic with a slight northeast skew. At the time of surveying, the waterfall jet did not access the plunge pool and instead impacted a mottled surface on the waterfall face 5 m upstream of the pool. We calculated that an upstream horizontal velocity of 2.6 m/s was required for the jet to access the plunge pool. As this high velocity is typically not met by the upstream flow conditions, plunge pool erosion may not be the dominant waterfall retreat process here</p></div> </div> <div class="ucb-article-content-media ucb-article-content-media-right col-lg"> <div> <div class="paragraph paragraph--type--media paragraph--view-mode--default"> </div> </div> </div> </div> </div> </div> </div> <h2> <div class="paragraph paragraph--type--ucb-related-articles-block paragraph--view-mode--default"> <div>Off</div> </div> </h2> <div>Traditional</div> <div>0</div> <div>On</div> <div>White</div> Thu, 23 Aug 2018 18:17:30 +0000 Anonymous 1241 at /program/hydrosciences Numerical Simulation Of Tectonic Strain And Water Level At A Desert Fault System /program/hydrosciences/2018/08/23/numerical-simulation-tectonic-strain-and-water-level-desert-fault-system <span>Numerical Simulation Of Tectonic Strain And Water Level At A Desert Fault System</span> <span><span>Anonymous (not verified)</span></span> <span><time datetime="2018-08-23T12:16:53-06:00" title="Thursday, August 23, 2018 - 12:16">Thu, 08/23/2018 - 12:16</time> </span> <div role="contentinfo" class="container ucb-article-categories" itemprop="about"> <span class="visually-hidden">Categories:</span> <div class="ucb-article-category-icon" aria-hidden="true"> <i class="fa-solid fa-folder-open"></i> </div> <a href="/program/hydrosciences/taxonomy/term/58"> 2006 </a> <a href="/program/hydrosciences/taxonomy/term/6"> Abstract </a> </div> <div role="contentinfo" class="container ucb-article-tags" itemprop="keywords"> <span class="visually-hidden">Tags:</span> <div class="ucb-article-tag-icon" aria-hidden="true"> <i class="fa-solid fa-tags"></i> </div> <a href="/program/hydrosciences/taxonomy/term/86" hreflang="en">Poster</a> </div> <span>Gregory D Robertson</span> <div class="ucb-article-content ucb-striped-content"> <div class="container"> <div class="paragraph paragraph--type--article-content paragraph--view-mode--default 3"> <div class="ucb-article-row-subrow row"> <div class="ucb-article-text col-lg d-flex align-items-center" itemprop="articleBody"> <div><p><strong>Robertson</strong>, Gregory D&nbsp;<sup>1</sup>&nbsp;;&nbsp;<strong>Ge</strong>, Shemin&nbsp;<sup>2</sup>&nbsp;;&nbsp;<strong>Cutillo</strong>, Paula&nbsp;<sup>3</sup></p><p><sup>1</sup>&nbsp;University of Colorado at «Ƶ<br><sup>2</sup>&nbsp;University of Colorado at «Ƶ<br><sup>3</sup>&nbsp;National Park Service, Water Resource Division</p><p>Tectonic deformation in the Great Basin is speculated as one of the possible causes for water level fluctuations observed in Devils Hole, southwestern Nevada. Devils Hole is a large fault cavern located along a 10 mile spring discharge line in a carbonate aquifer, 150 miles west of Las Vegas, Nevada. It is an area of high attention as it provides habitat for an endangered species of fish, Cyprinodon diabolis. The survival of the fish is believed to be dependent upon the water level in Devils Hole.</p><p>Tectonic deformation is examined using the volumetric strain field present throughout the Great Basin. Extension in the Devils Hole area is N 65 W at a rate of 8 nanostrain/yr (Wernicke et al., 1998). The carbonate aquifer that provides water to Devils Hole is heterogeneous and anisotropic containing fractures and faults at multiple scales. This preliminary analysis indicates that rates of pressure head fluctuation may be on the order of millimeters per year due to tectonic strain. An external program is used to calculate head changes due to strain present in the Great Basin. Strain is incorporated into the groundwater flow model through imposing these head changes to the initial head at the beginning of each time step in transient MODFLOW simulations.</p><blockquote><p>Wernicke, B., Davis, J., Bennett, R., Elosegui, P., Abolins, M., Brady, R., House, M., Niemi, N., and Snow, J. 1998. Anomalous strain accumulation in the Yucca Mountain area, Nevada. Science, v. 279, p. 2096-2099.</p></blockquote></div> </div> <div class="ucb-article-content-media ucb-article-content-media-right col-lg"> <div> <div class="paragraph paragraph--type--media paragraph--view-mode--default"> </div> </div> </div> </div> </div> </div> </div> <h2> <div class="paragraph paragraph--type--ucb-related-articles-block paragraph--view-mode--default"> <div>Off</div> </div> </h2> <div>Traditional</div> <div>0</div> <div>On</div> <div>White</div> Thu, 23 Aug 2018 18:16:53 +0000 Anonymous 1239 at /program/hydrosciences Local Polynomial Method For Ensemble Forecast Of Time Series /program/hydrosciences/2018/08/23/local-polynomial-method-ensemble-forecast-time-series <span>Local Polynomial Method For Ensemble Forecast Of Time Series</span> <span><span>Anonymous (not verified)</span></span> <span><time datetime="2018-08-23T12:16:05-06:00" title="Thursday, August 23, 2018 - 12:16">Thu, 08/23/2018 - 12:16</time> </span> <div role="contentinfo" class="container ucb-article-categories" itemprop="about"> <span class="visually-hidden">Categories:</span> <div class="ucb-article-category-icon" aria-hidden="true"> <i class="fa-solid fa-folder-open"></i> </div> <a href="/program/hydrosciences/taxonomy/term/58"> 2006 </a> <a href="/program/hydrosciences/taxonomy/term/6"> Abstract </a> </div> <div role="contentinfo" class="container ucb-article-tags" itemprop="keywords"> <span class="visually-hidden">Tags:</span> <div class="ucb-article-tag-icon" aria-hidden="true"> <i class="fa-solid fa-tags"></i> </div> <a href="/program/hydrosciences/taxonomy/term/86" hreflang="en">Poster</a> </div> <span>Satish K Regonda</span> <div class="ucb-article-content ucb-striped-content"> <div class="container"> <div class="paragraph paragraph--type--article-content paragraph--view-mode--default 3"> <div class="ucb-article-row-subrow row"> <div class="ucb-article-text col-lg d-flex align-items-center" itemprop="articleBody"> <div><p><strong>Regonda</strong>, Satish K&nbsp;<sup>1</sup>&nbsp;;&nbsp;<strong>Rajagopalan</strong>, Balaji&nbsp;<sup>2</sup>&nbsp;;&nbsp;<strong>Lall</strong>, Upmanu&nbsp;<sup>3</sup>&nbsp;;&nbsp;<strong>Clark</strong>, Martyn&nbsp;<sup>4</sup>;&nbsp;<strong>Moon</strong>, Young-Il&nbsp;<sup>5</sup></p><p><sup>1</sup>&nbsp;Dept of Civil, Environmental &amp; Architectural Engineering, Cooperative Institute for Research in Environmental Sciences, University of Colorado at «Ƶ<br><sup>2</sup>&nbsp;Dept of Civil, Environmental &amp; Architectural Engineering, Cooperative Institute for Research in Environmental Sciences, University of Colorado at «Ƶ<br><sup>3</sup>&nbsp;Dept. of Earth and Env. Eng., Columbia University, New York, NY, USA<br><sup>4</sup>&nbsp;Cooperative Institute for Research in Environmental Sciences, University of Colorado at «Ƶ<br><sup>5</sup>&nbsp;Dept. of Civil Engg., University of Seoul, Seoul, Korea</p><p>We present a nonparametric approach based on local polynomial regression for ensemble forecast of time series. The state space is first reconstructed by embedding the univariate time series of the response variable in a space of dimension (D) with a delay time (τ). To obtain a forecast from a given time point t , three steps are involved: (i) the current state of the system is mapped on to the state space, known as the feature vector, (ii) a small number (K = α * n, α =fraction (0,1] of the data, n=data length) of neighbors (and their future evolution) to the feature vector are identified in the state space, and (iii) a polynomial of order p is fitted to the identified neighbors, which is then used for prediction. A suite of parameter combinations (D, τ, α, p) is selected based on an objective criterion, called the Generalized Cross Validation (GCV). All of the selected parameter combinations are then used to issue a T-step iterated forecast starting from the current time t , thus generating an ensemble forecast which can be used to obtain the forecast probability density function (PDF). The ensemble approach improves upon the traditional method of providing a single mean forecast by providing the forecast uncertainty. Further, for short noisy data it can provide better forecasts. We demonstrate the utility of this approach on synthetic (Lorenz attractors) and two real data sets (Great Salt Lake bi-weekly volume and NINO3 index).</p><blockquote><p>Regonda, S., B. Rajagopalan, U. Lall, M. Clark and Y. Moon, Local polynomial mehtod for ensemble forecast of time series, Nonlinear Processes in Geophysics, Special issue on "Nonlinear Deterministic Dynamics in Hydrologic Systems: Present Activities and Future Challenges", 12, 397-406, 2005.</p></blockquote></div> </div> <div class="ucb-article-content-media ucb-article-content-media-right col-lg"> <div> <div class="paragraph paragraph--type--media paragraph--view-mode--default"> </div> </div> </div> </div> </div> </div> </div> <h2> <div class="paragraph paragraph--type--ucb-related-articles-block paragraph--view-mode--default"> <div>Off</div> </div> </h2> <div>Traditional</div> <div>0</div> <div>On</div> <div>White</div> Thu, 23 Aug 2018 18:16:05 +0000 Anonymous 1237 at /program/hydrosciences A Multi-Model Ensemble Forecast Framework: Application To Spring Seasonal Flows In The Gunnison River Basin /program/hydrosciences/2018/08/23/multi-model-ensemble-forecast-framework-application-spring-seasonal-flows-gunnison-river <span>A Multi-Model Ensemble Forecast Framework: Application To Spring Seasonal Flows In The Gunnison River Basin</span> <span><span>Anonymous (not verified)</span></span> <span><time datetime="2018-08-23T12:15:09-06:00" title="Thursday, August 23, 2018 - 12:15">Thu, 08/23/2018 - 12:15</time> </span> <div role="contentinfo" class="container ucb-article-categories" itemprop="about"> <span class="visually-hidden">Categories:</span> <div class="ucb-article-category-icon" aria-hidden="true"> <i class="fa-solid fa-folder-open"></i> </div> <a href="/program/hydrosciences/taxonomy/term/58"> 2006 </a> <a href="/program/hydrosciences/taxonomy/term/6"> Abstract </a> </div> <div role="contentinfo" class="container ucb-article-tags" itemprop="keywords"> <span class="visually-hidden">Tags:</span> <div class="ucb-article-tag-icon" aria-hidden="true"> <i class="fa-solid fa-tags"></i> </div> <a href="/program/hydrosciences/taxonomy/term/84" hreflang="en">Talk</a> </div> <span>Satish K Regonda</span> <div class="ucb-article-content ucb-striped-content"> <div class="container"> <div class="paragraph paragraph--type--article-content paragraph--view-mode--default 3"> <div class="ucb-article-row-subrow row"> <div class="ucb-article-text col-lg d-flex align-items-center" itemprop="articleBody"> <div><p><strong>Regonda</strong>, Satish K&nbsp;<sup>1</sup>&nbsp;;&nbsp;<strong>Rajagopalan</strong>, Balaji&nbsp;<sup>2</sup>&nbsp;;&nbsp;<strong>Clark</strong>, Martyn&nbsp;<sup>3</sup>&nbsp;;&nbsp;<strong>Zagona</strong>, Edith&nbsp;<sup>4</sup></p><p><sup>1</sup>&nbsp;Dept of Civil, Environmental &amp; Architectural Engineering, Cooperative Institute for Research in Environmental Sciences, University of Colorado at «Ƶ<br><sup>2</sup>&nbsp;Dept of Civil, Environmental &amp; Architectural Engineering, Cooperative Institute for Research in Environmental Sciences, University of Colorado at «Ƶ<br><sup>3</sup>&nbsp;Cooperative Institute for Research in Environmental Sciences, University of Colorado at «Ƶ<br><sup>4</sup>&nbsp;Center for Advanced Decision Support for Water and Environmental Systems, University of Colorado at «Ƶ</p><p>We propose a multi-model ensemble forecast framework for streamflow forecasts at multiple locations that incorporates large-scale climate information. It has four broad steps - (i) Principal Component Analysis is performed on the spatial streamflows to identify the dominant modes of variability; (ii) Potential predictors of the dominant streamflow modes are identified from among large-scale climate features and snow water equivalent information; (iii) Objective criterion is used to select a suite of candidate nonlinear regression models each with different predictors and; (iv) Ensemble forecasts of the dominant streamflow modes are generated from the candidate models and are combined objectively to produce a multi-model ensemble – which are then back transformed to produce spatially coherent streamflow forecasts at all the locations. The utility of the framework is demonstrated in the skillful forecast of spring seasonal streamflows at six locations in the Gunnison River Basin at several lead times. The generated ensemble streamflow forecast provide valuable and useful information for optimal management and planning of water resources in the basin.</p><blockquote><p>Regonda, S., B. Rajagopalan, M. Clark, and E. Zagona, 2005,A Multi-model Ensemble Forecast Framework: Application to Spring Seasonal Flows in the Gunnison River Basin , Water Resources Research, (accepted, pending revisions).</p></blockquote></div> </div> <div class="ucb-article-content-media ucb-article-content-media-right col-lg"> <div> <div class="paragraph paragraph--type--media paragraph--view-mode--default"> </div> </div> </div> </div> </div> </div> </div> <h2> <div class="paragraph paragraph--type--ucb-related-articles-block paragraph--view-mode--default"> <div>Off</div> </div> </h2> <div>Traditional</div> <div>0</div> <div>On</div> <div>White</div> Thu, 23 Aug 2018 18:15:09 +0000 Anonymous 1235 at /program/hydrosciences Hydrologic Science Vs. Regulatory Policy: USEPA’s Watershed Control Requirements For Cryptosporidium /program/hydrosciences/2018/08/23/hydrologic-science-vs-regulatory-policy-usepas-watershed-control-requirements <span>Hydrologic Science Vs. Regulatory Policy: USEPA’s Watershed Control Requirements For Cryptosporidium</span> <span><span>Anonymous (not verified)</span></span> <span><time datetime="2018-08-23T12:14:23-06:00" title="Thursday, August 23, 2018 - 12:14">Thu, 08/23/2018 - 12:14</time> </span> <div role="contentinfo" class="container ucb-article-categories" itemprop="about"> <span class="visually-hidden">Categories:</span> <div class="ucb-article-category-icon" aria-hidden="true"> <i class="fa-solid fa-folder-open"></i> </div> <a href="/program/hydrosciences/taxonomy/term/58"> 2006 </a> <a href="/program/hydrosciences/taxonomy/term/6"> Abstract </a> </div> <div role="contentinfo" class="container ucb-article-tags" itemprop="keywords"> <span class="visually-hidden">Tags:</span> <div class="ucb-article-tag-icon" aria-hidden="true"> <i class="fa-solid fa-tags"></i> </div> <a href="/program/hydrosciences/taxonomy/term/84" hreflang="en">Talk</a> </div> <span>Frederick W. Pontius</span> <div class="ucb-article-content ucb-striped-content"> <div class="container"> <div class="paragraph paragraph--type--article-content paragraph--view-mode--default 3"> <div class="ucb-article-row-subrow row"> <div class="ucb-article-text col-lg d-flex align-items-center" itemprop="articleBody"> <div><p><strong>Pontius</strong>, Frederick W.&nbsp;<sup>1</sup></p><p><sup>1</sup>&nbsp;Dept. of Civil, Environmental, and Architectural Engineering, University of Colorado, «Ƶ, Colo.</p><p>Watershed control is one option within the US Environmental Protection Agency’s (USEPA’s) Long-Term 2 Enhanced Surface Water Treatment Rule (LT2ESWTR) microbial toolbox for public water systems to provide extra protection against Cryptosporidium. To receive credit for removal of Cryptosporidium, a watershed control program must meet certain requirements.</p><p>Watershed control programs must include an analysis of the system’s source water vulnerability to the different sources of Cryptosporidium. Assessments must include a characterization of watershed hydrology, identification of an “area of influence on source water quality,” sources of Cryptosporidium, seasonal variability, and the relative impact of the sources of Cryptosporidium on the system’s source water quality. An analysis of sustainable interventions and an evaluation of their relative effectiveness in reducing Cryptosporidium in source water is required.</p><p>Federal regulatory policy can have both a positive and negative affect on the advancement of science. This review of the state of knowledge regarding Cryptosporidium sources, fate, and transport within a surface watershed demonstrates that USEPA’s presumptive 0.5 log removal ‘credit’ has a weak scientific basis. The implications of this for researchers, regulators, and regulated water utilities will be discussed.</p><blockquote><p>USEPA. 2006, Final Long Term 2 Enhanced Surface Water Treatment Rule. Federal Register, v. 71, p. 653-702.</p><p>Davies, C., Kaucner, C., Altavilla, N., Ashbolt, N., Fuerguson, C., Krogh, M., Hijnen, W., Medema, G., and Deere, D. 2005, Fate and Transport of Surface Water Pathogens in Watersheds, AWWA Research Foundation, Denver, Colo.</p></blockquote></div> </div> <div class="ucb-article-content-media ucb-article-content-media-right col-lg"> <div> <div class="paragraph paragraph--type--media paragraph--view-mode--default"> </div> </div> </div> </div> </div> </div> </div> <h2> <div class="paragraph paragraph--type--ucb-related-articles-block paragraph--view-mode--default"> <div>Off</div> </div> </h2> <div>Traditional</div> <div>0</div> <div>On</div> <div>White</div> Thu, 23 Aug 2018 18:14:23 +0000 Anonymous 1233 at /program/hydrosciences INVITED TALK: From Research To Remediation: Some Applications Of Hydrogeochemical Research To Mine Site Remediation /program/hydrosciences/2018/08/23/invited-talk-research-remediation-some-applications-hydrogeochemical-research-mine-site <span>INVITED TALK: From Research To Remediation: Some Applications Of Hydrogeochemical Research To Mine Site Remediation</span> <span><span>Anonymous (not verified)</span></span> <span><time datetime="2018-08-23T12:13:36-06:00" title="Thursday, August 23, 2018 - 12:13">Thu, 08/23/2018 - 12:13</time> </span> <div role="contentinfo" class="container ucb-article-categories" itemprop="about"> <span class="visually-hidden">Categories:</span> <div class="ucb-article-category-icon" aria-hidden="true"> <i class="fa-solid fa-folder-open"></i> </div> <a href="/program/hydrosciences/taxonomy/term/58"> 2006 </a> <a href="/program/hydrosciences/taxonomy/term/6"> Abstract </a> </div> <div role="contentinfo" class="container ucb-article-tags" itemprop="keywords"> <span class="visually-hidden">Tags:</span> <div class="ucb-article-tag-icon" aria-hidden="true"> <i class="fa-solid fa-tags"></i> </div> <a href="/program/hydrosciences/taxonomy/term/84" hreflang="en">Talk</a> </div> <span>D. Kirk Nordstrom</span> <div class="ucb-article-content ucb-striped-content"> <div class="container"> <div class="paragraph paragraph--type--article-content paragraph--view-mode--default 3"> <div class="ucb-article-row-subrow row"> <div class="ucb-article-text col-lg d-flex align-items-center" itemprop="articleBody"> <div><p><strong>Nordstrom</strong>, D. Kirk&nbsp;<sup>1</sup></p><p><sup>1</sup>&nbsp;U.S. Geological Survey, «Ƶ, CO</p><p>Research in chemistry, geochemistry, and hydrogeochemistry has been applied successfully to identify the geochemical processes that produce acid rock drainage and determine its fate, and to understand remediation scenarios. When iron in acid drainage fully oxidizes, does the pH always decrease? No, it can increase and chemistry and microbiology are keys to understanding the answer (1). What conditions cause efflorescent salts to form at mine sites? Water, drawn by capillary forces, evaporates to dryness and the efflorescent salts are left. In acid sulfate environments these salts usually form from waters of negative pH and very high metal concentrations (2). Can pH be negative? Not only can it be theoretically, but such low pH waters actually exist at Iron Mountain (2,3). Is mine plugging a reasonable option for treating acid mine drainage flowing from a portal? Probably not, unless you wish to increase the cost and complexity of the problem. Iron Mountain, California and Summitville, Colorado are good examples to prove that point (2). If several alternative remedial options are available with estimates for each of the decrease in loading, can the resultant improvement in stream water quality be predicted? Yes, by applying carefully controlled steady-injection tracer tests combined with synoptic sampling (4). Can ground-water quality before mining be estimated after mining has begun? The Questa project, New Mexico, is one of the first successful examples of this analysis.</p><blockquote><p>(1) Nordstrom, D.K. Modeling low-temperature geochemical processes: in Drever, J.I., vol. ed., Vol. 5, Surface and Ground Water, Weathering and Soils, Treatise on Geochemistry, Holland, H.D. and Turekian, K.K., ex. eds., Elsevier, Amsterdam, 37-72, 2004.</p><p>(2) Nordstrom, D.K. and Alpers, C. N. Proc. Nat’l. Acad. Sci. 96, (1999), 3455.</p><p>(3) Nordstrom, D.K., Alpers, C.N., Ptacek, C.J. and Blowes, D.W. Envir. Sci. Tech. 34, (2000) 254.</p><p>(4) Ball, J.W., Runkel, R.L., and Nordstrom, D.K. Chap. 3, In Environmental Sciences and Environmental Computing. Vol. II, P. Zanetti (ed.), the EnviroComp Institute, 2004, (http://www.envirocomp.org).</p></blockquote></div> </div> <div class="ucb-article-content-media ucb-article-content-media-right col-lg"> <div> <div class="paragraph paragraph--type--media paragraph--view-mode--default"> </div> </div> </div> </div> </div> </div> </div> <h2> <div class="paragraph paragraph--type--ucb-related-articles-block paragraph--view-mode--default"> <div>Off</div> </div> </h2> <div>Traditional</div> <div>0</div> <div>On</div> <div>White</div> Thu, 23 Aug 2018 18:13:36 +0000 Anonymous 1231 at /program/hydrosciences INVITED FACULTY TALK - Applications Of Wavelet Analysis In Hydrology /program/hydrosciences/2018/08/23/invited-faculty-talk-applications-wavelet-analysis-hydrology <span>INVITED FACULTY TALK - Applications Of Wavelet Analysis In Hydrology</span> <span><span>Anonymous (not verified)</span></span> <span><time datetime="2018-08-23T12:12:58-06:00" title="Thursday, August 23, 2018 - 12:12">Thu, 08/23/2018 - 12:12</time> </span> <div role="contentinfo" class="container ucb-article-categories" itemprop="about"> <span class="visually-hidden">Categories:</span> <div class="ucb-article-category-icon" aria-hidden="true"> <i class="fa-solid fa-folder-open"></i> </div> <a href="/program/hydrosciences/taxonomy/term/58"> 2006 </a> <a href="/program/hydrosciences/taxonomy/term/6"> Abstract </a> </div> <div role="contentinfo" class="container ucb-article-tags" itemprop="keywords"> <span class="visually-hidden">Tags:</span> <div class="ucb-article-tag-icon" aria-hidden="true"> <i class="fa-solid fa-tags"></i> </div> <a href="/program/hydrosciences/taxonomy/term/84" hreflang="en">Talk</a> </div> <span>Roseanna M. Neupauer</span> <div class="ucb-article-content ucb-striped-content"> <div class="container"> <div class="paragraph paragraph--type--article-content paragraph--view-mode--default 3"> <div class="ucb-article-row-subrow row"> <div class="ucb-article-text col-lg d-flex align-items-center" itemprop="articleBody"> <div><p><strong>Neupauer</strong>, Roseanna M&nbsp;<sup>1</sup></p><p><sup>1</sup>&nbsp;Univ. of Colorado</p><p>Wavelet analysis is a relatively new tool for data analysis and signal processing. Similar to Fourier analysis, wavelet analysis identifies dominant periods or scales in one-dimensional and multi-dimensional data sets. The key difference between Fourier analysis and wavelet analysis is in the global vs. local nature of the analysis. In Fourier analysis, the dominant scales or periods are assumed to be global (i.e., they do not change with time or position), while wavelet analysis can extract different dominant periods or scales at different times or positions. In this talk, we will present an overview of wavelet analysis, and we will demonstrate its usefulness in analysis of hydrologic data.</p></div> </div> <div class="ucb-article-content-media ucb-article-content-media-right col-lg"> <div> <div class="paragraph paragraph--type--media paragraph--view-mode--default"> </div> </div> </div> </div> </div> </div> </div> <h2> <div class="paragraph paragraph--type--ucb-related-articles-block paragraph--view-mode--default"> <div>Off</div> </div> </h2> <div>Traditional</div> <div>0</div> <div>On</div> <div>White</div> Thu, 23 Aug 2018 18:12:58 +0000 Anonymous 1229 at /program/hydrosciences Regional Assessment Of Lake Sensitivity To Acidification From Atmospheric Deposition Of Pollutants In Five National Parks Of The Rocky Mountains /program/hydrosciences/2018/08/23/regional-assessment-lake-sensitivity-acidification-atmospheric-deposition-pollutants-five <span>Regional Assessment Of Lake Sensitivity To Acidification From Atmospheric Deposition Of Pollutants In Five National Parks Of The Rocky Mountains</span> <span><span>Anonymous (not verified)</span></span> <span><time datetime="2018-08-23T12:12:22-06:00" title="Thursday, August 23, 2018 - 12:12">Thu, 08/23/2018 - 12:12</time> </span> <div role="contentinfo" class="container ucb-article-categories" itemprop="about"> <span class="visually-hidden">Categories:</span> <div class="ucb-article-category-icon" aria-hidden="true"> <i class="fa-solid fa-folder-open"></i> </div> <a href="/program/hydrosciences/taxonomy/term/58"> 2006 </a> <a href="/program/hydrosciences/taxonomy/term/6"> Abstract </a> </div> <div role="contentinfo" class="container ucb-article-tags" itemprop="keywords"> <span class="visually-hidden">Tags:</span> <div class="ucb-article-tag-icon" aria-hidden="true"> <i class="fa-solid fa-tags"></i> </div> <a href="/program/hydrosciences/taxonomy/term/86" hreflang="en">Poster</a> </div> <span>Leora Nanus</span> <div class="ucb-article-content ucb-striped-content"> <div class="container"> <div class="paragraph paragraph--type--article-content paragraph--view-mode--default 3"> <div class="ucb-article-row-subrow row"> <div class="ucb-article-text col-lg d-flex align-items-center" itemprop="articleBody"> <div><p><strong>Nanus</strong>, Leora&nbsp;<sup>1</sup>&nbsp;;&nbsp;<strong>Williams</strong>, Mark W.&nbsp;<sup>2</sup>&nbsp;;&nbsp;<strong>Campbell</strong>, Donald H.&nbsp;<sup>3</sup></p><p><sup>1</sup>&nbsp;«Ƶ<br><sup>2</sup>&nbsp;«Ƶ<br><sup>3</sup>&nbsp;United States Geological Survey</p><p>Acidification of high-elevation lakes in the Western United States is of concern because of the storage and release of pollutants in snowmelt runoff combined with steep topography, granitic bedrock, and limited soils and biota. The sensitivity of 850 lakes to acidification from atmospheric deposition of nitrogen (N) and sulfur was estimated by relating water-quality and landscape attributes in Glacier National Park, Yellowstone National Park, Grand Teton National Park, Rocky Mountain National Park and Great Sand Dunes National Park and Preserve. Water-quality data measured during synoptic surveys (n=151) were used to calibrate statistical models of lake sensitivity. Landscape attributes for the lake basins were derived from GIS including topography, bedrock type, soil type, and vegetation type. Using multivariate logistic regression analysis, probability estimates were developed for acid-neutralizing capacity (ANC), and sensitive lakes were identified. In the case of N deposition, water-quality data included dual isotopes of d15N and d18O of nitrate. Water-quality data collected at 60 lakes during fall 2004 were used for cross-validation and 85% of lakes sampled were accurately identified by the model. Lakes exceeding 60% probability of having an ANC concentration less than 100 microequivalents per liter are located in Rocky Mountain and Grand Teton National Parks, at elevations above 2800m, and greater than 83% of the basin with low buffering capacity bedrock.</p></div> </div> <div class="ucb-article-content-media ucb-article-content-media-right col-lg"> <div> <div class="paragraph paragraph--type--media paragraph--view-mode--default"> </div> </div> </div> </div> </div> </div> </div> <h2> <div class="paragraph paragraph--type--ucb-related-articles-block paragraph--view-mode--default"> <div>Off</div> </div> </h2> <div>Traditional</div> <div>0</div> <div>On</div> <div>White</div> Thu, 23 Aug 2018 18:12:22 +0000 Anonymous 1227 at /program/hydrosciences