@article{segura_caldwell_sun_mcnulty_zhang_2015, title={A model to predict stream water temperature across the conterminous USA}, volume={29}, ISSN={["1099-1085"]}, DOI={10.1002/hyp.10357}, abstractNote={Abstract Stream water temperature ( t s ) is a critical water quality parameter for aquatic ecosystems. However, t s records are sparse or nonexistent in many river systems. In this work, we present an empirical model to predict t s at the site scale across the USA. The model, derived using data from 171 reference sites selected from the Geospatial Attributes of Gages for Evaluating Streamflow database, describes the linear relationship between monthly mean air temperature ( t a ) and t s . Multiple linear regression models are used to predict the slope ( m ) and intercept ( b ) of the t a –t s linear relation as a function of climatic, hydrologic and land cover characteristics. Model performance to predict t s resulted in a mean Nash–Sutcliffe efficiency coefficient of 0.78 across all sites. Application of the model to predict t s at additional 89 nonreference sites with a higher human alteration yielded a mean Nash–Sutcliffe value of 0.45. We also analysed seasonal thermal sensitivity ( m ) and found strong hysteresis in the t a –t s relation. Drainage area exerts a strong control on m in all seasons, whereas the cooling effect of groundwater was only evident for the spring and fall seasons. However, groundwater contributions are negatively related to mean t s in all seasons. Finally, we found that elevation and mean basin slope are negatively related to mean t s in all seasons, indicating that steep basins tend to stay cooler because of shorter residence times to gain heat from their surroundings. This model can potentially be used to predict climate change impacts on t s across the USA. Copyright © 2014 John Wiley & Sons, Ltd.}, number={9}, journal={HYDROLOGICAL PROCESSES}, author={Segura, Catalina and Caldwell, Peter and Sun, Ge and McNulty, Steve and Zhang, Yang}, year={2015}, month={Apr}, pages={2178–2195} }
 @article{caldwell_segura_laird_sun_mcnulty_sandercock_boggs_vose_2015, title={Short-term stream water temperature observations permit rapid assessment of potential climate change impacts}, volume={29}, ISSN={["1099-1085"]}, DOI={10.1002/hyp.10358}, abstractNote={Abstract Assessment of potential climate change impacts on stream water temperature ( T s ) across large scales remains challenging for resource managers because energy exchange processes between the atmosphere and the stream environment are complex and uncertain, and few long‐term datasets are available to evaluate changes over time. In this study, we demonstrate how simple monthly linear regression models based on short‐term historical T s observations and readily available interpolated air temperature ( T a ) estimates can be used for rapid assessment of historical and future changes in T s . Models were developed for 61 sites in the southeastern USA using ≥18 months of observations and were validated at sites with longer periods of record. The T s models were then used to estimate temporal changes in T s at each site using both historical estimates and future T a projections. Results suggested that the linear regression models adequately explained the variability in T s across sites, and the relationships between T s and T a remained consistent over 37 years. We estimated that most sites had increases in historical annual mean T s between 1961 and 2010 (mean of +0.11 °C decade −1 ). All 61 sites were projected to experience increases in T s from 2011 to 2060 under the three climate projections evaluated (mean of +0.41 °C decade −1 ). Several of the sites with the largest historical and future T s changes were located in ecoregions home to temperature‐sensitive fish species. This methodology can be used by resource managers for rapid assessment of potential climate change impacts on stream water temperature. Copyright © 2014 John Wiley & Sons, Ltd.}, number={9}, journal={HYDROLOGICAL PROCESSES}, author={Caldwell, Peter and Segura, Catalina and Laird, Shelby Gull and Sun, Ge and McNulty, Steven G. and Sandercock, Maria and Boggs, Johnny and Vose, James M.}, year={2015}, month={Apr}, pages={2196–2211} }
 @article{segura_lazzati_sankarasubramanian_2013, title={The use of broken power-laws to describe the distributions of daily flow above the mean annual flow across the conterminous U.S.}, volume={505}, ISSN={0022-1694}, url={http://dx.doi.org/10.1016/j.jhydrol.2013.09.016}, DOI={10.1016/j.jhydrol.2013.09.016}, abstractNote={A recent study employed a broken power-law (BPL) distribution for understanding the scaling frequency of bankfull discharge in snowmelt-dominated basins. This study, grounded from those findings, investigated the ability of a BPL function to describe the distribution of daily flows above the mean annual flow in 1217 sites across the conterminous U.S. (CONUS). The hydrologic regime in all the sites is unregulated and spans a wide range in drainage areas (2–120,000 km2) and elevation (0–3000 m). Available daily flow records in all sites varied between 15 and 108 years. Comparing the performance of BPL distribution and the traditionally used lognormal distribution, we found that BPL provides stronger fit in ∼80% of the sites. Thus the BPL function provides a suitable tool to model daily flows in most areas of the CONUS. The potential for developing a model for predicting the frequency distribution of daily flows in ungauged sites was analyzed. We found that such model is possible using drainage area, mean basin elevation, and mean annual precipitation as predicting variables for any site located above 600 m across the CONUS. We also found strong continental-wide correlations between 3 of the 4 parameters that describe the BPL and basin characteristics. Our results indicate that the BPL function provides a robust alternative to traditional functions such as the lognormal to model the statistical variation of daily flows above the mean annual in most basins of the CONUS.}, journal={Journal of Hydrology}, publisher={Elsevier BV}, author={Segura, Catalina and Lazzati, Davide and Sankarasubramanian, Arumugam}, year={2013}, month={Nov}, pages={35–46} }
 @article{segura_mccutchan_lewis_pitlick_2011, title={The influence of channel bed disturbance on algal biomass in a Colorado mountain stream}, volume={4}, ISSN={["1936-0592"]}, DOI={10.1002/eco.142}, abstractNote={Abstract The effects of channel bed disturbance on benthic chlorophyll a accrual were examined in three reaches of the Williams Fork River, CO, USA. A field calibrated multidimensional hydraulic model was used for estimation of shear‐stress distributions. Sediment grain size was used to determine the critical shear stress for bed movement. Disturbance at a given location is defined as the percentage of time during the growing season that the bed sediment is in motion. This metric was compared with periphyton biomass accrual. Growth control factors including temperature, grazing intensity, nutrient concentrations, and irradiance also were measured. Disturbance mapping showed that the common concept of bed disturbance as a byproduct of high‐flow events is overly simplistic. In the Williams Fork, bed movement occurs constantly over certain portions of the bed, even at low flows. There is a continuum of bed movement, expressed as percentage of the bed in motion, extending from low to high flows. Periphyton biomass accumulated exponentially in all study reaches but accumulation rates were inversely proportional to local disturbance. Periphyton biomass increased by approximately three orders of magnitude across the three reaches, but failed to reach a plateau. A combination of moderate grazing rates, low‐nutrient concentrations, moderately impaired solar irradiance, and, most importantly, low temperatures explains the failure of periphyton biomass to reach a plateau. This study shows that the control of periphyton biomass may be explained in streams by bed disturbance over the growing season plus the separate, superimposed on influence of population growth rate control factors. Copyright © 2010 John Wiley & Sons, Ltd.}, number={3}, journal={ECOHYDROLOGY}, author={Segura, Catalina and McCutchan, James H. and Lewis, William M., Jr. and Pitlick, John}, year={2011}, pages={411–421} }
 @article{segura_booth_2010, title={EFFECTS OF GEOMORPHIC SETTING AND URBANIZATION ON WOOD, POOLS, SEDIMENT STORAGE, AND BANK EROSION IN PUGET SOUND STREAMS}, volume={46}, ISSN={["1093-474X"]}, DOI={10.1111/j.1752-1688.2010.00470.x}, abstractNote={Segura, Catalina and Derek B. Booth, 2010. Effects of Geomorphic Setting and Urbanization on Wood, Pools, Sediment Storage, and Bank Erosion in Puget Sound Streams. Journal of the American Water Resources Association (JAWRA) 46(5):972-986. DOI: 10.1111/j.1752-1688.2010.00470.x Abstract: Interrelationships between urbanization, the near-riparian zone, and channel morphology were examined in 44 lowland stream reaches in the Puget Lowlands of western Washington, United States. Both the degree of urbanization and channel type control channel response to a range of instream and riparian conditions. Some of these relationships are not evident in lumped datasets (i.e., with all channel types and/or degrees of urbanization) and highlight the importance of fluvial geomorphology in determining channel response. We found that in low-urbanized watersheds dominated by forced pool-riffle and plane-bed morphologies, the frequency and distribution of large woody debris (LWD), pool spacing, sediment storage, and bank erosion have a strong relationship with channel confinement and characteristics of near-riparian vegetation. In contrast, high-urbanized reaches dominated by simplified morphologies are substantially less sensitive to the condition of the near-riparian zone (e.g., size of the near-riparian vegetation and the level of channel confinement), due to the common disconnection of stream and floodplain caused by the placement of stabilizing structures in the banks. These structures are typically placed to prevent erosion; however, they also result in fewer LWD and pools, less sediment storage, and higher potential for incision.}, number={5}, journal={JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION}, author={Segura, Catalina and Booth, Derek B.}, year={2010}, month={Oct}, pages={972–986} }
 @article{segura_pitlick_2010, title={Scaling frequency of channel-forming flows in snowmelt-dominated streams}, volume={46}, ISSN={["0043-1397"]}, DOI={10.1029/2009wr008336}, abstractNote={[1] The scaling properties of channel-forming flows are investigated using a regional flow frequency model developed for snowmelt-dominated streams in Colorado. The model is derived from analyses of daily flow records at 32 gauging stations where we have independent measurements of the bankfull discharge. The study sites are located in alpine/subalpine basins with drainage areas ranging from 4 to 3700 km2. The frequency distribution of daily flows at these locations can be reproduced with a broken power law (BPL) function described by two free parameters. Both parameters are strongly correlated with drainage area, and based on these correlations, a regional model capable of predicting the frequency of daily flows above the mean annual flow was formulated. The applicability of the model was tested using daily flow records from 32 similar-size basins in Idaho. The frequency distributions of daily flows in snowmelt-dominated streams in Colorado and Idaho with highly predictable hydrographs (i.e., 1 year autocorrelation above 0.7) are well fitted by the BPL function. According to the model, the frequency of flows greater than bankfull decreases downstream from about 15 d/yr in headwater reaches to about 6 d/yr in downstream reaches. These results imply that the basin response to precipitation and runoff is nonlinear. This multiscaling behavior can be physically interpreted as the result of scale-dependent variations in runoff and sediment supply, which influence downstream trends in the bankfull channel geometry and intensity of sediment transport.}, journal={WATER RESOURCES RESEARCH}, author={Segura, Catalina and Pitlick, John}, year={2010}, month={Jun} }