Repository logo

Browsing by Author "Ross, Matt, committee member"

Now showing 1 - 5 of 5
  • Thumbnail Image
    ItemOpen Access
    Evaluating post-fire woody mulch effects on soil and stream nitrogen
    (Colorado State University. Libraries, 2024) Richardson, Mikaela, author; Kampf, Stephanie, advisor; Rhoades, Chuck, advisor; Ross, Matt, committee member; Wilkins, Mike, committee member
    Severe wildfires often increase nitrogen (N) loss from burned watersheds, impacting downstream water quality, water treatability, and aquatic habitat. Woody mulch is commonly applied to mitigate soil erosion and enhance revegetation post-fire, but it also provides a source of labile carbon (C) that may stimulate microbial immobilization and limit N release from soils. The objective of our study was to evaluate whether mulch application influenced turnover and loss of soil C and N in laboratory leaching trials and hillslope field settings, and then compared post-fire C and N in streams draining mulched and unmulched catchments. In the laboratory, we quantified C and N inputs and leaching outputs from mulched and unmulched soil columns. Within the Cameron Peak fire burn scar in northern Colorado, we compared soil N availability and potential leaching losses between mulched and unmulched hillslope plots. We also measured C, N, and other chemical constituents in streams draining three mulched and three unmulched catchments. In the laboratory leaching studies, mulch added high concentrations of dissolved organic carbon (> 500 mg L-1) and decreased nitrate leaching from soil columns by 27% during repeated simulated rainfall events. In hillslope plots, mulching also reduced soil nitrate, with greater impacts following spring snowmelt when N losses from soils to streams was highest. However, the effect of mulching was not measurable at the catchment scale due to low application rates and mulch extent, paired with high topographic and geomorphic variability amongst the catchments. Our findings show that C inputs from woody mulch can influence soil N retention in burned watersheds when applied at a minimum rate of 5 Mg ha-1; however practical constraints on aerial application may make it challenging to apply enough mulch for any downstream response to be detectable. Coupled with physical erosion protection, the biogeochemical impacts of mulching may facilitate soil and vegetation recovery following severe wildfire and reduce post-fire N losses to streams if sufficiently applied. Therefore, further post-fire rehabilitation efforts should optimize mulch operations by prioritizing sensitive watersheds and treating them with adequate mulch.
  • Thumbnail Image
    ItemOpen Access
    Intra and inter-annual patterns in Lake Yojoa, Honduras: disentangling biogeochemical drivers of a tropical monomictic lake ecosystem
    (Colorado State University. Libraries, 2022) Fadum, Jemma Mazuri, author; Hall, Ed, advisor; Wrighton, Kelly, committee member; Ross, Matt, committee member; Burgin, Amy, committee member
    To view the abstract, please see the full text of the document.
  • Thumbnail Image
    ItemOpen Access
    Predicting flow duration and assessing its drivers in north-central Colorado using crowdsourced data
    (Colorado State University. Libraries, 2022) Peterson, David, author; Kampf, Stephanie K., advisor; Ross, Matt, committee member; Gallen, Sean, committee member
    Headwater streams are globally important both ecologically and for human resource needs. These streams represent the majority of stream network length, but their flow regimes are often unknown. Streams can be classified by flow regime as perennial, intermittent, or ephemeral. These classifications are used in forest land management decisions and may affect Clean Water Act jurisdiction; however, the National Hydrography Dataset (NHD) often misclassifies headwater streams. The goal of this study is to model flow duration across the stream networks of eight subbasins in north-central Colorado. We used crowdsourced flow presence/absence data from 82 sites in the Stream Tracker program and eight flow sensors to train random forest regression models; these models predicted the fraction of time a stream flows from April-September for both the average from 2016-2020 (dubbed mean annual) and yearly averages (annual). Model predictor variables included climatic, physiographic, and land cover attributes of the study area. Models were developed using a sample of the sites for training and leaving the remaining sites for model testing. The resulting mean annual model's Nash-Sutcliffe efficiency (NSE) was 0.88 for test data, and the annual model's test data had an NSE value of 0.81. We found climate variables such as snow persistence, precipitation, and potential evapotranspiration most influential in predicting flow fraction based on the random forest-ranked variable importance. Forested and herbaceous land cover as well as depth to bedrock, available water storage, hydraulic conductivity, hydrologic soil group, drainage area, and watershed curvature were also identified as important drivers. We developed maps of predicted flow fractions and compared them to NHD flow classifications. In the Cache La Poudre subbasin, the mean annual model predicted perennial flow in 10% of streams and intermittent or ephemeral flow in 90% of streams. Our model predicted nonperennial flow for 76% of the streams that were mapped as perennial in the medium-resolution NHD. Based on these findings, the NHD over-represented perennial streams, classifying them three times more than our model, and under-represented intermittent and ephemeral streams by 32% in our study area. The annual model captured interannual variability in flow fraction and highlighted isolated areas of high variability in flow fraction between years in mid-to-low elevations. The models we developed using crowdsourced data can improve flow classifications of headwater streams and inform resource management decisions in northern Colorado. Crowdsourced streamflow data can be used in streamflow predictions anywhere that nonperennial flow is common.
  • Thumbnail Image
    ItemOpen Access
    Snow depth measurement via automated image recognition
    (Colorado State University. Libraries, 2019) Brown, Kevin S. J., author; Fassnacht, Steven, advisor; Ham, Jay, committee member; McGrath, Dan, committee member; Ross, Matt, committee member
    Seasonal snow is a significant contributor to the water supply of nearly 2 billion people in semi-arid regions around the world. Quantification of this resource is critical to planning sustainable water and food supplies in these regions. While Snow Water Equivalent (SWE) is the most common parameter used to estimate snow water storage, snow depth has often been used as a proxy since it is much simpler to measure and can be converted to SWE if density can be estimated. Depth of snow varies greatly at the regional, watershed, and plot scales and better quantification of this variability can improve water storage estimates. Installation and maintenance of new snow measurement sites is typically expensive and time consuming, so a technology that could produce high temporal resolution snow depth data for a low cost would be useful. Manual reading of snow depth from graduated staffs driven into the ground has been used by the Natural Resources Conservation Service (NRCS) for operational and research purposes. The amount of data available from this method has traditionally been limited by the time-consuming step of manually reading snow depths in images. The central objective of this research was to automate this process in order to reduce the time requirement and allow this technology to be deployed more widely. Five sites were established with time lapse cameras and a set of snow depth staffs around the state of Colorado. Several image recognition methods were considered, and the Aggregate Channel Features technique was used to detect snow depths based on images of the depth staffs. At the most successful sites, absolute error was close to 20 cm, while at less successful sites consistent errors as high as 100 cm made the data unusable. The variety of site configurations examined allowed factors which increased error such as forested backgrounds, close staff placement, and poor camera mounting, to be identified. Additional studies could take advantage of new, cloud-based image recognition technologies in order to allow anyone with a camera and an internet connection to measure snow depth automatically from pictures taken at specific locations.
  • Thumbnail Image
    ItemOpen Access
    The topology and ecohydrology of river corridors in mountain river networks
    (Colorado State University. Libraries, 2022) Brooks, Alexander C., author; Covino, Tim, advisor; Morrison, Ryan, committee member; Rhoades, Chuck, committee member; Ross, Matt, committee member; Wohl, Ellen, committee member
    River corridors are comprised of the river, the surrounding valley and riparian areas, and subsurface hyporheic zones. River corridors have the potential to regulate hydrological, biogeochemical, and ecological processes and patterns from reach to watershed scales. Within mountainous landscapes, narrow sections of the river corridor are often interspersed within wider, yet less frequent, river corridor sections. Reach-scale studies (i.e., 1 km) suggest that wide river corridors, also referred to as river-floodplain systems and river beads in this dissertation, have disproportionate impacts on river network behavior. In chapter one, I introduce the concept of river corridors, briefly review the history of the concept's development, the hydrologic and eco-geomorphic factors that drive functioning in these systems, and alterations driven by anthropogenic activities. In chapter two, as a first step to deepening understanding of the influence of river network valley morphology on watershed process, I quantify the spatial distribution of wide and narrow river corridor segments in twenty river networks in the Southern Rockies Ecoregion. I then characterize the spatial configuration of river beads including their frequency, abundance, and spacing. These results reveal variable network topology of river beads in the region and illustrate the need to consider network position when investigating functioning in these systems. I conclude that characterizing river bead configurations can improve river network understanding and aid decision making in prioritizing conservation and restoration efforts. In chapter three, I explore water-mediated linkages, termed hydrologic connectivity, that connect landscape components within an intact beaver mediated river-floodplain system in Rocky Mountain National Park. I evaluate surface water hydrologic connectivity using field indicators and develop a continuous connectivity metric that represents a vector strength between a source along the North St Vrain River to ten surface water target sites within the river-floodplain system. To measure this connectivity strength, I analyzed hydrometric, injected conservative tracers, and natural occurring geochemical and microbial tracers across streamflows in 2018. I developed empirical models of surface water hydrologic connectivity as a function of river stage to predict daily connectivity strength across multiple floodplain sites for 2018 and assessed the sensitivity of surface connectivity to inter-annual streamflow variability between 2016-2020. At the river-floodplain system scale, I found hydrologic connectivity always increased with streamflow while across-system variance in connectivity peaked at intermediate streamflow. At sites with intermittent connections to the river, river stage disconnection thresholds were variable and their connectivity dynamics were sensitive to inter-annual variation in streamflows, suggesting that future connectivity behavior under climate change will depend on how flow durations change across a range of flow states. These results suggest that the intermediate flows are critical periods for understanding seasonal connectivity within river-floodplain systems. Accordingly, our results suggest that alteration to connectivity regimes as dictated by future hydrologic change will be in part a function of the speed at which streamflow moves from peak to low flow states. In chapter four, I examine the spatial patterns in land cover within the Southern Rockies Ecoregion and assess the implications of wetland cover on river corridor productivity and the sensitivity of productivity to inter-annual climate variability across geographic and climatic gradients in the region. We found that wetlands, which comprise today only around a third of river corridor area, maintain high productivity even in river corridor segments within water limited landscapes. However, degradation in wetlands and the loss of woody cover create river corridors with high sensitivity to climate variability, particularly in areas with lower climatic water availability. Wetlands with woody cover were clustered in proximity to rivers and maintain relatively low climate sensitivity even in more water limited landscapes. Vegetation productivity and sensitivity patterns in river corridors without wetlands were largely driven by climatic water availability. Areas with high water availability generally contained forested cover with high productivity and low climate sensitivity while water limited areas generally contained shrub lands and grasslands cover with low productivity and high climate sensitivity. These results suggest that wetland loss and/or degradation have resulted in losses in productivity and climate resilience, particularly within more water limited portions of the region.