Nearby Gauges Research Articles

Optimizing parameter learning and calibration in an integrated hydrological model: Impact of observation length and information

Integrated hydrological modeling is gaining popularity due to its mechanistic representation of the surface and subsurface processes. However, estimating the parameters of such process-based models can be computationally expensive if careful consideration is not given to the length of streamflow observations used during model calibration. Here we evaluate the influence of the calibration period, the role of streamflow information content, and the gage location in parameter learning and calibration of a fully integrated hydrological model, the Advanced Terrestrial Simulator (ATS). We conducted the study at the Upper Neversink River Watershed within the Delaware River Basin, where streamflow observations are available at 11 gages with varying record lengths. We leveraged a recently proposed knowledge-informed deep learning technique for parameter estimation. To assess the impact of observation period and gage location, model parameters were learned on scenarios using different chunks of streamflow observations, including (1) using only one year or consecutive multiple years of streamflow observations at the watershed outlet and (2) using one shared year of observations at each of the sub-catchment gages, with the period from 1991-10-01 through 1999-09-30 as the overall calibration period. Using the estimated parameters, ATS was rerun for each scenario and evaluated on a subsequent period from 1999-10-01 through 2002-09-30. Results show that the basin outlet discharge prediction is mostly improved when using at least four years of observations for parameter estimation. Further, the performance of the calibrated ATS run correlates with the information content of the observed streamflows, suggesting that the information-theoretic metrics could be indicators for selecting the observation period for parameter estimation. Finally, we find that observations from an informative gage can be used in learning parameters to predict the streamflow at a nearby gage, which would potentially lower the computational expense by reducing the watershed domain used in calibration. Our success underscores the potential of using information theory to achieve robust model parameter estimation on a reduced computational budget.

Effects of bigheaded carp on larval Freshwater Drum diets

AbstractObjectiveWe investigated foraging success, diet composition, and the abundances of various prey taxa in the diets of larval Freshwater Drum Aplodinotus grunniens across a gradient of bigheaded carp (Bighead Carp Hypophthalmichthys nobilis and Silver Carp H. molitrix) relative abundance and in relation to zooplankton density, temperature, discharge, and larval fish densities in the upper Mississippi River (UMR).MethodsWe sampled fish larvae and zooplankton every 10 days (May–August 2017 and 2018) from UMR Pools 14, 16, and 18–20; collected environmental data from nearby gauging stations; and assessed bigheaded carp relative abundance.ResultCrustacean zooplankton abundance was positively related to larval foraging success. Copepods were the dominant prey, but larvae also consumed large proportions of rotifer eggs and benthic insect larvae. Bigheaded carp presence and catch per unit effort were positively associated with increased larval consumption of atypical prey (rotifer eggs and aquatic insect larvae) and cyclopoid copepods. Cladocerans were the rarest prey consumed by larvae in pools where bigheaded carp were present, but they were more frequently consumed in pools where bigheaded carp were absent. In addition to bigheaded carp abundance, river discharge was negatively associated with larval consumption of cladocerans, aquatic insect larvae, and rotifers; water temperature was negatively associated with the consumption of copepods and cladocerans; and rotifer abundance was positively associated with their consumption.ConclusionWe suggest that bigheaded carp alter larval fish diets to prey that may be less energetically beneficial, which can have implications for larval growth and survival.

Neural Network Analysis as a Base of the Future System of Water–Environmental Regulation

The article considers neural-network methods and technologies, which are relatively new even for many researchers and experts, as applied to water–environmental regulation. The efficiency of neural networks in this line of studies is due to their self-training, and the ensuing ability to reveal complex nonlinear relationships between the characteristics under control by data processing instruments, consisting of interrelated neurons. The methodology of artificial neural networks and the features of their functioning are described. Training and methodological examples are given to illustrate their potential use. A practical problem, considered as an example of ANN application, is the potential for improving the efficiency of identification of large enterprises polluting natural water among many water users in an industrial region. This is made with the use of data on the concentrations of some priority water-polluting metals at the hydrochemical gages in the Iset river near Ekaterinburg City. The neural-network analysis is shown to detect relationships between individual water quality characteristics at nearby gages. This allowed the conclusion that there exist close logistic economic relationships between water users, which help revealing water pollutants by the water footprint produced by plants working in the same branch. It is also shown that the use of ANN opens new ways for determining the contribution of industrial waste discharges to the level of water pollution by substances of dual genesis (natural and technogenic). The reliability of the conclusions is confirmed by the possibility to use the data on a given hydrochemical gage to satisfactorily predict water quality at a gage further downstream.

Neural Network Analysis as a Base of the Future System of Water–Environmental Regulation

The article considers neural-network methods and technologies, which are relatively new even for many researchers and experts, as applied to water–environmental regulation. The efficiency of neural networks in this line of studies is due to their self-training, and the ensuing ability to reveal complex nonlinear relationships between the characteristics under control by data processing instruments, consisting of interrelated neurons. The methodology of artificial neural networks and the features of their functioning are described. Training and methodological examples are given to illustrate their potential use. A practical problem, considered as an example of ANN application, is the potential for improving the efficiency of identification of large enterprises polluting natural water among many water users in an industrial region. This is made with the use of data on the concentrations of some priority water-polluting metals at the hydrochemical gages in the Iset river near Ekaterinburg City. The neural-network analysis is shown to detect relationships between individual water quality characteristics at nearby gages. This allowed the conclusion that there exist close logistic economic relationships between water users, which help revealing water pollutants by the water footprint produced by plants working in the same branch. It is also shown that the use of ANN opens new ways for determining the contribution of industrial waste discharges to the level of water pollution by substances of dual genesis (natural and technogenic). The reliability of the conclusions is confirmed by the possibility to use the data on a given hydrochemical gage to satisfactorily predict water quality at a gage further downstream.

Assessment of compound flooding through seamless linkage of coastal hydrodynamic and inland catchment models

Compound flooding refers to the complex interactions among oceanographic, inland (catchment) hydrological, and meteorological processes with anthropogenic factors such as land use changes due to urbanization. To-wit, the impact of higher tide levels, storm surge, and high intensity rainfall events over the inland catchment collectively may result in more extensive flooding than the individual processes acting separately. In the context of climate change and more frequent extreme weather events, coastal cities, particularly those in the ASEAN region, are increasingly vulnerable to compound flooding, yet there is no convenient and user-friendly modelling approach available that would enable the planning community and decision-makers to envision compound flooding as part of resiliency-oriented urban plan development. We addressed this gap by developing the3D Resiliency Visualisation Platform (3DRVP), within which linked features are established using Python scripts to seamless integrate a 2D mixed land use fluvial/pluvial catchment model (PCSWMM) with a 2D/3Dcoastal hydrodynamic model (Delft3D) to simulate the dynamics ofcompound floods for the assessment of coastal inundation. This platform aims to assist planners, urban design professionals, and engineers with a realistic visualization tool to picture the urban infrastructure planning alternatives as well as to facilitate the real-time operational decision-making and evacuation activation with flood control strategies. The integrated platform theory is developed first and the platform then is trialled for a developing coastal area in south Bangkok, Thailand. Similar to many cities of the global south, data availability to calibrate models is limited and as such we used a mixed methods approach to explore model accuracy. The Delft3D model was calibrated successfully using water level data from a nearby gauge in the Gulf of Thailand for Typhoon Linda. The catchment model (PCSWMM) was validated using observed flood areas as reported by the local municipality. A 100-year design rainstorm was subsequently modelled and linked with the Typhoon Linda surge levels with results indicating the combination of rainfall flooding and storm surge would increase the flooded area by 25.6% over the system components modelled individually.

A dip-corrected discharge estimation method for a river system

This work proposes a novel dip corrected velocity distribution model in combination with the entropy theory for discharge estimation in a braided river. A modified form of the dip correction factor is derived by considering the topographical complexities and applied for assessing velocity profiles in river cross-sections. The velocity profiles at different verticals are computed by employing Shanon's entropy theory. The depth-averaged velocities at different cross-sections are estimated from the computed vertical velocity profiles and substituted in the area-velocity method for the discharge calculation. The model is applied to two study areas, Majuli and Umananda of the Brahmaputra River, having both simple and braided sections. The validation of the model is performed using the observed discharge data available at the nearby gauge site for low flow condition. Results indicate that the integration of bed rugosity factor in dip corrected velocity distributions improves the accuracy of discharge estimations.

Four Years of Sediment and Phosphorus Monitoring in the Kraichbach River Using Large-Volume Samplers

Various sampling strategies come into operation to monitor water quality in rivers. Most frequently, grab samples are taken, but they are not suitable for recording the highly dynamic transport of solids and solid-bound pollutants. Composite samples reduce the influence of input and transport dynamics and are better suited to determine the annual river loads. Large-volume samplers (LVSs) produce both a composite sample over a long period of time and an amount of solids which allows for further analyses. In the small sub-catchment area of the Kraichbach river in Baden-Wuerttemberg (Germany) two LVSs have been installed to sample the river flow. The concentration of solids and phosphorus in the supernatant water and the settled sediment in the sampler have been determined and mean concentrations have been derived. Annual river loads were calculated in combination with discharge data from the nearby gauging station. Two sampling strategies of the LVS were tested and compared. For the first strategy, the LVS was used to collect quasi-continuous composite samples throughout the year, whereas, with the second strategy, samples were taken specifically for different flow conditions (low, mean and high flow). This study compares the advantages and constraints of both strategies. Results indicate that the first strategy is better suited to determine annual river loads. Quasi-continuous large-volume composite sampling is recommended for further monitoring campaigns.

Contextualizing Inflow and Infiltration Within the Streamflow Regime of Urban Watersheds

AbstractDefects in sanitary‐sewer infrastructure enable exchange of large volumes of fluids to and from the environment. The intrusion of rainfall and groundwater into sanitary sewers is called inflow and infiltration (I&I). Though long recognized in the assessment of sewers, the impacts of I&I on streamflow within urban watersheds are unknown. We quantified rainfall‐derived I&I (RDI&I), groundwater infiltration (GI), and total I&I using measured flows within sanitary‐sewer pipes serving four watersheds near Atlanta, Georgia, USA. Flows were monitored in pipes that parallel local stream channels and compared with streamflow measured at nearby gauging sites. Freshwater diverted into the sewer system due to I&I ranged from 24% to 36% of the flow measured within individual pipes. The RDI&I was the smaller component of I&I, ranging from 4.2 to 9.8 mm per year among watersheds. The GI was typically an order of magnitude greater than RDI&I, ranging from 24 to 41 mm per year among watersheds with annual stream discharge of approximately 500 mm. The I&I occurring at specific moments in time commonly represented 0%–20% of the flow measured in the adjacent stream. The enhancement of low flows in streams that could be achievable if I&I were abated ranges from as much as 6%–36% across watersheds. Our discussion presents explanations for the seasonality of I&I and associated impacts on streamflow in urban watersheds, while identifying important sources of remaining uncertainty. Our results support the conclusion that I&I substantially reduces flows in urban streams, especially low flows during dry weather.

Beach Deployment of a Low-Cost GNSS Buoy for Determining Sea-Level and Wave Characteristics

Spatially explicit data on tidal and waves are required as part of coastal monitoring applications (e.g., radar monitoring of coastal change) for the design of interventions to mitigate the impacts of climate change. A deployment over two tidal cycles of a low-cost Global Navigation Satellite System (GNSS) buoy at Rossall (near Fleetwood), UK demonstrated the potential to record good quality sea level and wave data within the intertidal zone. During each slack water and the following ebb tide, the sea level data were of good quality and comparable with data from nearby tide gauges on the national tide gauge network. Moreover, the GNSS receiver was able to capture wave information and these compared well with data from a commercial wave buoy situated 9.5 km offshore. Discontinuities were observed in the elevation data during flood tide, coincident with high accelerations and losing satellite signal lock. These were probably due to strong tidal currents, which, combined with spilling waves, would put the mooring line under tension and allow white water to spill over the antenna resulting in the periodic loss of GNSS signals, hence degrading the vertical solutions.

Climate Change Effects on Fish Passability across a Rock Weir in a Mediterranean River

Climate change represents a major challenge for the management of native fish communities in Mediterranean rivers, as reductions in discharge may lead to a decrease in passability through small barriers such as weirs, both in temporary and perennial rivers. Through hydraulic modelling, we investigated how discharges from a large hydropower plant in the Tagus River are expected to affect the passability of native freshwater fish species through a rock weir (Pego, Portugal), equipped with a nature-like fish ramp. We considered not only mean daily discharge values retrieved from nearby gauging stations (1991–2005) for our flow datasets, but also predicted discharge values based on climatic projections (RCP) until the end of the century (2071–2100) for the Tagus River. Results showed that a minimum flow of 3 m3 s−1 may be required to ensure the passability of all species through the ramp and that passability was significantly lower in the RCP scenarios than in the historical scenario. This study suggests that climate change may reduce the passability of native fish species in weirs, meaning that the construction of small barriers in rivers should consider the decreases in discharge predicted from global change scenarios for the suitable management of fish populations.

Waveform Decontamination for Improving Satellite Radar Altimeter Data Over Nearshore Area: Upgraded Algorithm and Validation

One of the thorniest problems in altimetry community is retrieving accurate coastal sea surface height, especially in the last several kilometers offshore. It is confirmed in previous studies that decontaminating waveforms is beneficial to improve the quality of coastal SSHs. In this article, we proposed an upgraded strategy for waveform decontamination, including a novel realignment algorithm and gate-wise outlier detector. We validated the new strategy in four test regions using Jason-2 altimeter data. In the validation process, we compared retracked SSHs by 16 retrackers, which include retrackers provided in SGDR (Sensor Geophysical Data Record), ALES (Adaptive Leading Edge Subwaveform), and PISTACH (Prototype Innovant de Système de Traitement pour les Applications Côtières et l’Hydrologie) products. Comparison results verified that retracking the waveforms decontaminated using our new method can greatly improve the SSHs in the coastal region. The 20% threshold retracker (DW-TR20) and the ICE1 retracker (DW-ICE1) based on the decontaminated waveforms outperform other retrackers, especially in 0–4 km zone offshore. DW-TR20 and DW-ICE1 can provide robust SSHs with a consistent accuracy in 0–20 km coastal band and a high correlation (>0.9) with nearby gauge data. To conclude, the upgraded waveform decontamination strategy provides a promising solution for coastal altimetry, which makes it possible to extend reliable observations to the last several kilometers offshore.

Inundation characteristics of mangrove and saltmarsh in micro-tidal estuaries

Tidal inundation is a principal driver in intertidal wetland functioning. A combination of surface elevation and its relation to tidal range creates inundation regimes that influence a range of abiotic factors that affect wetland species distribution. Hydroperiod is a term frequently used to describe inundation regimes; however, the term has been vaguely defined in the past and typically quantified using tide gauge data rather than empirical field observations. This study explores relationships between various characteristics, such as frequency, total duration, average duration, average depth, non-tidal exposure, and mangrove/saltmarsh distribution in micro-tidal estuarine settings of southeast Australia. Inundation was measured directly using 35 pressure transducers embedded into mangrove and saltmarsh substrates over a period of two lunar tidal cycles along six transects located at Clyde and Minnamurra River estuaries, New South Wales, Australia. Results indicated differences in wetland inundation characteristics between mangrove and saltmarsh that are a function of wetland microtopography and site-specific tidal regime (e.g. local tidal range). For example, mangroves were inundated approximately 15–70% of the time, and 0.9–2 times a day, whereas saltmarshes were submerged only <15% of the time and less than 0.9 times per day. Comparison of direct field measurements and tide gauge-derived estimates of wetland inundation regime revealed that nearby gauge data may provide an acceptable estimate; however, distant tide gauge data provided poor estimates due to the effect of tidal dampening and amplification, respectively. Detailed analysis of wetland inundation characteristics as presented in this study demonstrates a method for describing inundation regimes at local scale. Improved understanding of contemporary tidal inundation dynamics in mangrove and saltmarsh can support modelling of wetland response to sea-level rise, as well as restoration practises by providing estimates of inundation tolerances.

Determination of sea level variations in Turkish Mediterranean coast using GNSS reflectometry

Global Navigation Satellite System Reflectometry (GNSS-R) can be used to measure sea level heights based on reflected signals recorded as oscillations in signal-to-noise ratio (SNR) data. This study utilizes the SNR data from an existing MERS, located in Erdemli, Mersin on the Mediterranean coast of Turkey over a one-year time period. The dominant multipath frequency in the SNR data is derived with two methods presented in this study: the Lomb-Scargle periodogram (LSP) and the LSP with the Moving Average (MA) filtering. The results of both methods are compared in terms of the accuracy and correlation with respect to sea level records from the nearby Erdemli tide gauge. The correlations between the GNSS-R and tide gauge by using the LSP are 0.88 and 0.84 for GPS L1 and L5 signals, respectively. With the LSP with MA method, the correlations are increased by 0.91 and 0.88 for GPS L1 and L5 signals, respectively.

Study of the Sheyuegou dam breach – Experience with the post-failure investigation and back analysis

Documenting dam burst cases is of prime importance to improve understanding of dam failure mechanisms and the ability to predict dam breach floods during emergencies. However, the relevant dam burst information has rarely been reported because of the sudden occurrence of the failure and the lack of nearby gauging stations for many small-scale dams. This paper advocates a comprehensive study of the available field information that could be obtained during and after dam failure, which may be incomplete and include uncertainties but still is useful. On July 31, 2018, the Sheyuegou Dam in Hami City, Xinjiang, China broke because of rainfall-induced flooding that had considerably exceeded the specified standard for small dams. The disaster resulted in 20 deaths and 8 people missing. This study presents the authors’ field work after the dam failure that includes: (1) collection of the meteorological and hydrologic information, (2) interpretation of a witness’s video that records the breach process, (3) aerial scan of the residual body of the dam, and (4) a survey of the flood high water marks. In combination with laboratory hydraulic and geotechnical property tests and the analysis using a physically-based dam breach model (DB-IWHR), this case history is analyzed with comparisons to the information obtained in the field. The review confirmed, in general, the usefulness of the existing dam failure analysis method and helped calibrate the various input parameters involved in these models. It is suggested that more dam breach cases be documented by on-site drone or mobile phone video and post-failure investigations from which a database or inventory on dam breaches can be established although some of them may be information-incomplete and fault-tolerant.

Streamflow Variability Indicated by False Rings in Bald Cypress (Taxodium distichum (L.) Rich.)

Despite growing in wet lowland and riparian settings, Taxodium distichum (L.) Rich. (bald cypress) has a strong response to hydroclimate variability, and tree ring chronologies derived from bald cypress have been used extensively to reconstruct drought, precipitation and streamflow. Previous studies have also demonstrated that false rings in bald cypress appear to be the result of variations in water availability during the growing season. In this study 28 trees from two sites located adjacent to the Choctawhatchee River in Northwestern Florida, USA were used to develop a false ring record extending from 1881 to 2014. Twenty false ring events were recorded during the available instrumental era (1931–2014). This record was compared with daily and monthly streamflow data from a nearby gage. All 20 of the false-ring events recorded during the instrumental period occurred during years in which greatly increased streamflow occurred late in the growing season. Many of these wet events appear to be the result of rainfall resulting from landfalling tropical cyclones. We also found that the intra-annual position of false rings within growth rings reflects streamflow variability and combining the false-ring record with tree ring width chronologies improves the estimation of overall summer streamflow by 14%. Future work using these and other quantitative approaches for the identification and measurement of false ring variables in tree rings may improve tree-ring reconstructions of streamflow and potentially the record of tropical cyclone rainfall events.

Quality and timing of crowd‐based water level class observations

AbstractCrowd‐based hydrological observations can supplement existing monitoring networks and allow data collection in regions where otherwise no data would be available. In the citizen science project CrowdWater, repeated water level observations using a virtual staff gauge approach result in time series of water level classes (WL‐classes). To investigate the quality of these observations, we compared the WL‐class data with “real” (i.e., measured) water levels from the same stream at a nearby gauging station. We did this for nine locations where citizen scientists reported multiple observations using a smartphone app and at 12 locations where signposts were set up to ask citizens to record observations on a paper form that could be left in a letterbox. The results indicate that the quality of the data collected with the app was better than for the forms. A possible explanation is that for each app location, a single person submitted the vast majority of the observations, whereas at the locations of the forms almost every observation was made by a different person. On average, there were more contributions between May and September than during the other months. Observations were submitted for a range of flow conditions, with a higher fraction of high flow observations for the locations were data were collected with the app. Overall, the results are encouraging for citizen science approaches in hydrology and demonstrate that the smartphone application and the virtual staff gauge are a promising approach for crowd‐based water level class observations.

Chronic and episodic acidification of streams along the Appalachian Trail corridor, eastern United States

AbstractAcidic atmospheric deposition has adversely affected aquatic ecosystems globally. As emissions and deposition of sulfur (S) and nitrogen (N) have declined in recent decades across North America and Europe, ecosystem recovery is evident in many surface waters. However, persistent chronic and episodic acidification remain important concerns in vulnerable regions. We evaluated acidification in 269 headwater streams during 2010–2012 along the Appalachian Trail (AT) that transits several ecoregions and is located downwind of high levels of S and N emission sources. Discharge was estimated by matching sampled streams to those of a nearby gaged stream and assuming equivalent daily mean flow percentiles. Charge balance acid‐neutralizing capacity (ANC) values were adjusted to the 15th (Q15) and 85th flow percentiles (Q85) by applying the ANC/discharge slope among sample pairs collected at each stream. A site‐based approach was applied to streams sampled twice or more and a second regression‐based approach to streams sampled once to estimate episodic acidification magnitudes as the ANC difference from Q15 to Q85. Streams with ANC &lt;0 μeq/L doubled from 16% to 32% as discharge increased from Q15 to Q85 according to the site‐based approach. The proportion of streams with ANC &lt;0 μeq/L at low flow and high flow decreased from north to south. Base cation dilution explained the greatest amount of episodic acidification among streams and variation in sulfate (SO42−) concentrations was a secondary explanatory variable. Episodic SO42− patterns varied geographically with dilution dominant in northern streams underlain by soils developed in glacial sediment and increased concentrations dominant in southern streams with older, highly weathered soils. Episodic acidification increased as low‐flow ANC increased, exceeding 90 μeq/L in 25% of streams. Episodic increases in ANC were the dominant pattern in streams with low‐flow ANC values &lt;30 μeq/L. Chronic and episodic acidification remain an ecological concern among AT streams. The approach developed here could be applied to estimate the magnitude and extent of chronic and episodic acidification in other regions recovering from decreasing levels of atmospheric S and N deposition.

Analysis of the Spatial Patterns of Rainfall across the Agro-Climatic Zones of Jema Watershed in the Northwestern Highlands of Ethiopia

The association between elevation (agro-climatic zones, ACZs) and the mean annual total rainfall (MATRF) is not straightforward in different parts of the world. This study sought to estimate the amount of MATRF across four elevation zones of Jema watershed, which is situated in the northwestern highlands of Ethiopia, by employing an appropriate interpolation method. The elevation of the watershed ranges from 1895 to 3518 m a.s.l. For the sake of this study, 34 sample MATRF data were extracted from satellite and nearby gauge stations that were recorded from 1983 to 2010. These data sources were reconstructed by International Research Institute for Climate and Society at Columbia University, USA, at a scale of 10 km by 10 km. An elevation data set generated from a digital elevation model with 30-m resolution (DEM 30 m) was considered as a covariable to estimate the MATRF. To identify the optimal interpolation model, mean errors were computed using cross-validation statistics. The root-mean-square error (RMSE) analysis showed that ordinary cokriging (OCK) was the most accurate model with a predictive power of 87.3%. The root-mean-square standardized (RMSSE) analysis showed that the best precision value (0.72) occurred in OCK. Stable and Gaussian trend lines together with local polynomial types of trend removal, and an elliptical neighborhood search function could perform best to maximize the accuracy and the precision of estimating MATRF. Elevation, as a covariable, enhanced the degree of accuracy and precision of estimation. The value of the trend line function (least square) between the MATRF and elevation was very weak (R2 = 0.07), whereas the value of trend line function (least square) between the MATRF and the longitude coordinates (east–west direction) was medium (R2 = 0.34). The estimated MATRF for the entire watershed under study ranged from 1228 to 1640 mm. To conclude, elevation could contribute to the estimation of the MATRF. The value of the MATRF showed a declining pattern from the lower to higher elevation areas of the watershed.

Streambed scour of salmon spawning habitat in a regulated river influenced by management of peak discharge

Abstract In the Pacific Northwest of the United States, salmon eggs incubating within streambed gravels are susceptible to scour during floods. The threat to egg‐to‐fry survival by streambed scour is mitigated, in part, by the adaptation of salmon to bury their eggs below the typical depth of scour. In regulated rivers globally, we suggest that water managers consider the effect of dam operations on scour and its impacts on species dependent on benthic habitats. We instrumented salmon‐spawning habitat with accelerometer scour monitors (ASMs) at 73 locations in 11 reaches of the Cedar River in western Washington State of the United States from Autumn 2013 through the Spring of 2014. The timing of scour was related to the discharge measured at a nearby gage and compared to previously published ASM data at 26 locations in two reaches of the Cedar River collected between Autumn 2010 and Spring 2011. Thirteen percent of the recovered ASMs recorded scour during a peak‐discharge event in March 2014 (2‐to 3‐year recurrence interval) compared to 71% of the recovered ASMs during a higher peak‐discharge event in January 2011 (10‐year recurrence interval). Of the 23 locations where ASMs recorded scour during the 2011 and 2014 deployments, 35% had scour when the discharge was ≤87.3 m3/s (3,082 ft3/s) (2‐year recurrence interval discharge) with 13% recording scour at or below the 62.3 m3/s (2,200 ft3/s) operational threshold for peak‐discharge management during the incubation of salmon eggs. Scour to the depth of salmon egg pockets was limited during peak discharges with frequent (1.25‐year or less) recurrence intervals, which managers can regulate through dam operations on the Cedar River. Pairing novel measurements of the timing of streambed scour with discharge data allows the development of peak‐discharge management strategies that protect salmon eggs incubating within streambed gravels during floods.

Daily Reservoir Sedimentation Model: Case Study from the Fena Valley Reservoir, Guam

AbstractA model to compute reservoir sedimentation rates at daily timescales is presented. The model uses streamflow and sediment load data from nearby stream gauges to obtain an initial estimate o...