Browsing by Author "Godsey, Sarah E."
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Assessing placement bias of the global river gauge network(Nature Portfolio, 2022) Krabbenhoft, Corey A.; Allen, George H.; Lin, Peirong; Godsey, Sarah E.; Allen, Daniel C.; Burrows, Ryan M.; DelVecchia, Amanda G.; Fritz, Ken M.; Shanafield, Margaret; Burgin, Amy J.; Zimmer, Margaret A.; Datry, Thibault; Dodds, Walter K.; Jones, C. Nathan; Mims, Meryl C.; Franklin, Catherin; Hammond, John C.; Zipper, Sam; Ward, Adam S.; Costigan, Katie H.; Beck, Hylke E.; Olden, Julian D.; State University of New York (SUNY) Buffalo; Texas A&M University College Station; Peking University; Idaho; Idaho State University; Pennsylvania State University; Pennsylvania State University - University Park; University of Melbourne; Duke University; United States Environmental Protection Agency; Flinders University South Australia; University of Kansas; University of California Santa Cruz; INRAE; Kansas State University; University of Alabama Tuscaloosa; Virginia Polytechnic Institute & State University; United States Department of the Interior; United States Geological Survey; Indiana University Bloomington; European Commission Joint Research Centre; EC JRC ISPRA Site; University of Washington; University of Washington Seattle; Swedish University of Agricultural SciencesHydrologic data collected from river gauges inform critical decisions for allocating water resources, conserving ecosystems and predicting the occurrence of droughts and floods. The current global river gauge network is biased towards large, perennial rivers, and strategic adaptations are needed to capture the full scope of rivers on Earth. Knowing where and when rivers flow is paramount to managing freshwater ecosystems. Yet stream gauging stations are distributed sparsely across rivers globally and may not capture the diversity of fluvial network properties and anthropogenic influences. Here we evaluate the placement bias of a global stream gauge dataset on its representation of socioecological, hydrologic, climatic and physiographic diversity of rivers. We find that gauges are located disproportionally in large, perennial rivers draining more human-occupied watersheds. Gauges are sparsely distributed in protected areas and rivers characterized by non-perennial flow regimes, both of which are critical to freshwater conservation and water security concerns. Disparities between the geography of the global gauging network and the broad diversity of streams and rivers weakens our ability to understand critical hydrologic processes and make informed water-management and policy decisions. Our findings underscore the need to address current gauge placement biases by investing in and prioritizing the installation of new gauging stations, embracing alternative water-monitoring strategies, advancing innovation in hydrologic modelling, and increasing accessibility of local and regional gauging data to support human responses to water challenges, both today and in the future.Item Exploring the Drivers of Streamflow and Drying Across Physiographic Regions, Hydrogeomorphic Features, and Spatiotemporal Scales(University of Alabama Libraries, 2025) Peterson, Delaney; Jones, C. NathanStream networks are dynamic features on the landscape that integrate characteristics oftheir watersheds to modulate streamflow and network length across space and time. While it is well understood that conditions in the stream reflect both local and upstream controls, patterns at watershed outlets often do not align with patterns observed at smaller scales due to heterogeneity in watershed processes. Therefore, it is difficult to predict stream network dynamics across all landscapes, especially given most studies have focused on montane, temperate, natural systems. Here, I investigated the physical controls on streamflow and drying across spatiotemporal scales using a suite of hydrologic sensors and metrics across four watersheds in the southeastern United States (US). First, I developed an intermediate spatial scale (hydrogeomorphic features; approximately 500 m) to characterize within-watershed variability in river corridor structure and hydrologic connectivity, and leveraged a network of monitoring wells to quantify groundwater- surface water interactions in a Coastal Plain headwater stream. I observed that hydrogeomorphic features displayed distinct hydrologic signatures, and that subsurface characteristics resulted in heterogeneity in groundwater flowpaths. Next, I instrumented three watersheds spanning a physiographic gradient with a dense network of surface water and groundwater monitoring sensors. I used the surface water monitoring sensors to investigate the drivers of stream network expansion and contraction, and tested existing topographically-derived paradigms in a low-relief, understudied region with land-use legacies. I found that topography alone was not a good predictor of network dynamics in our watersheds, and including geologic and vegetative characteristics was more reflective of the patterns we observed. Finally, I used the groundwater and surface water monitoring wells to evaluate how river corridor structure influenced the storage and connectivity dynamics of these three watersheds, as well as to investigate how patterns observed at watershed outlets aligned with within-watershed heterogeneity. I observed that within-watershed hydrologic patterns were more complex and often contradictory to outlet patterns, and that within these watersheds, variability often contradicted existing conceptualizations of the hydrologic functions of geomorphic features like wetlands. Altogether, these results provide critical context for hydrologic processes in low-relief, managed systems, and highlight the importance of studying watersheds across scales.Item Zero or not? Causes and consequences of zero-flow stream gage readings(Wiley, 2020) Zimmer, Margaret A.; Kaiser, Kendra E.; Blaszczak, Joanna R.; Zipper, Samuel C.; Hammond, John C.; Fritz, Ken M.; Costigan, Katie H.; Hosen, Jacob; Godsey, Sarah E.; Allen, George H.; Kampf, Stephanie; Burrows, Ryan M.; Krabbenhoft, Corey A.; Dodds, Walter; Hale, Rebecca; Olden, Julian D.; Shanafield, Margaret; DelVecchia, Amanda G.; Ward, Adam S.; Mims, Meryl C.; Datry, Thibault; Bogan, Michael T.; Boersma, Kate S.; Busch, Michelle H.; Jones, C. Nathan; Burgin, Amy J.; Allen, Daniel C.; University of California Santa Cruz; Idaho; Boise State University; University of Nevada Reno; University of Kansas; United States Department of the Interior; United States Geological Survey; United States Environmental Protection Agency; University of Louisiana Lafayette; Purdue University West Lafayette Campus; Purdue University; Idaho State University; Texas A&M University College Station; Colorado State University; Griffith University; State University of New York (SUNY) Buffalo; Kansas State University; University of Washington; University of Washington Seattle; Flinders University South Australia; University of Montana; Indiana University Bloomington; Virginia Polytechnic Institute & State University; INRAE; University of Arizona; University of San Diego; University of Oklahoma - Norman; University of Alabama TuscaloosaStreamflow observations can be used to understand, predict, and contextualize hydrologic, ecological, and biogeochemical processes and conditions in streams. Stream gages are point measurements along rivers where streamflow is measured, and are often used to infer upstream watershed-scale processes. When stream gages read zero, this may indicate that the stream has dried at this location; however, zero-flow readings can also be caused by a wide range of other factors. Our ability to identify whether or not a zero-flow gage reading indicates a dry fluvial system has far reaching environmental implications. Incorrect identification and interpretation by the data user can lead to inaccurate hydrologic, ecological, and/or biogeochemical predictions from models and analyses. Here, we describe several causes of zero-flow gage readings: frozen surface water, flow reversals, instrument error, and natural or human-driven upstream source losses or bypass flow. For these examples, we discuss the implications of zero-flow interpretations. We also highlight additional methods for determining flow presence, including direct observations, statistical methods, and hydrologic models, which can be applied to interpret causes of zero-flow gage readings and implications for reach- and watershed-scale dynamics. Such efforts are necessary to improve our ability to understand and predict surface flow activation, cessation, and connectivity across river networks. Developing this integrated understanding of the wide range of possible meanings of zero-flows will only attain greater importance in a more variable and changing hydrologic climate. This article is categorized under: Science of Water > Methods Science of Water > Hydrological Processes Water and Life > Conservation, Management, and Awareness