Geology topics

Michael S. Kohn

Publications and source records attributed to Michael S. Kohn.

At least 19 recordsLinked to original sources

USGS2026

Sediment transport, terrace incision, and sediment chemistry in subbasins of differing land use, Stinking Water Creek Basin near Rangely, Colorado

In many areas of western Colorado, Late Cretaceous Mancos Shale is a source of sediment, salinity, and selenium to surface water. Natural weathering processes and human activity can expose and move sediments from the Mancos Shale, leading to increased salinity and selenium concentrations in surface water. The U.S. Geological Survey, in cooperation with the Bureau of Land Management, studied four subbasins of Stinking Water Creek near Rangely, Colorado, to provide information regarding landscapes on Mancos Shale that have undergone land-use change. Rangeland grazing is present in all four subbasins. Subbasins A1 and A2 have land use related to energy development and subbasins B1 and B2 do not. Aerial photographs, sediment chemistry, optically stimulated luminescence (OSL) ages, cross-section surveys, and Watershed Erosion Prediction Project (WEPP) modeling were used to characterize the history of land-use change by estimating stream channel incision rates and sediment, salinity, and selenium loads. All subbasins had upper and lower terraces and a modern streambed channel, and these surfaces were dated using OSL. In subbasins A1, A2, and B1, the streambed age was older than the terraces, indicating the channels are incising and widening into the older alluvium. In subbasin B2, however, the streambed age was much younger than the terraces, indicating aggradation is the main process. Differences in channel morphology were not always related to land use but to the subbasin position (upstream compared to downstream). Channels in subbasins A1 and A2 were generally wider and shallower than channels in subbasins B1 and B2. Landscape disturbances related to energy development in subbasins A1 and A2 could have caused channel evolution to progress from incision to widening processes.

Colorado↗

USGS2026

Peak-, mean-, and low-streamflow regional-regression equations for natural streamflow in central and western Colorado, 2019

The U.S. Geological Survey (USGS), in cooperation with the Colorado Department of Transportation, developed peak-, mean-, and low-streamflow regional-regression equations for estimating various statistics for natural streamflow in hydrologic regions of central and western Colorado. The peak-streamflow regression equations were developed using data from 418 streamgages, consisting of 15,202 years of record and a mean of approximately 36 years of record per streamgage. The mean- and low-streamflow regional-regression equations were developed using data from 323 streamgages where daily streamflow data were collected year-round. The annual exceedance-probability discharges for each streamgage were computed using the USGS software program PeakFQ. Mean monthly and 7-day minimum and maximum streamflows were computed using the USGS software program SWToolbox. Streamflow-duration values were computed using an R script. The regional-regression equations were determined using data for the period of record for a given streamgage through water year 2019. Geographic information systems datasets were used to develop 55 basin and 42 climatic characteristics, which were evaluated as candidate explanatory variables in the regression analysis. For the peak-streamflow regional-regression equations, the study area was divided into four hydrologic regions based on mean basin elevation, including the Plateau (less than 8,014 feet), Mid-Elevation (8,015 feet to 9,492 feet), Sub-Alpine (9,493 feet to 10,490 feet), and Alpine (greater than 10,490 feet) regions. For the peak-streamflow equations, the selection of basin and climatic characteristics was based on the 1-percent annual exceedance-probability discharge for each hydrologic region. For the mean streamflow, streamflow-duration values, and 7-day minimum and maximum streamflows, the study area was divided into four hydrologic regions based on river basin, including the (1) Colorado-East Slope Headwaters, (2) Green River, (3) Rio Grande, and (4) San Juan-Dolores. For mean streamflows, basin and climatic characteristics were evaluated separately for the annual period and each month for each hydrologic region. Regional regression equations published in this report are available for use in the USGS web-based program StreamStats.

Colorado↗

USGS2024

Post-wildfire curve number estimates for the southern Rocky Mountains in Colorado, USA

The curve number method first developed by the US Department of Agriculture Soil Conservation Service (now the Natural Resources Conservation Service) is often used for post-wildfire runoff assessments. These assessments are critical for land and emergency managers making decisions on life and property risks following a wildfire event. Three approaches (i.e., historical event observations, linear regression model, and regression tree model) were used to help estimate a post-wildfire curve number from watershed and wildfire parameters. For the first method, we used runoff events from 102 burned watersheds in Colorado, southern Wyoming, northern New Mexico, and eastern Utah to quantify changes in curve number values from pre- to post-wildfire conditions. The curve number changes from the measured runoff events vary substantially between positive and negative values. The measured curve number changes were then associated with watershed characteristics (e.g., slope, elevation, northness, and eastness) and land cover type to develop prediction models that provide estimates of post-wildfire curve number changes. Finally, we used a regression tree method to demonstrate that accurate predications can be developed using the measured curve number changes from our study domain. These models can be used for future post-wildfire assessments within the region.

Colorado, New Mexico, Utah, Wyoming↗

USGS2024

Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins

The magnitude and timing of extreme events such as debris and floodflows (collectively referred to as floodflows) in post-wildfire basins are difficult to measure and are even more difficult to predict. To address this challenge, a sensor ensemble consisting of noncontact, ground-based (near-field), Doppler velocity (velocity) and pulsed (stage or gage height) radars, rain gages, and a redundant radio communication network was leveraged to monitor flood wave velocities, to validate travel times, and to compliment observations from NEXRAD weather radar. The sensor ensemble (DEbris and Floodflow Early warNing System, DEFENS) was deployed in Waldo Canyon, Pike National Forest, Colorado, USA, which was burned entirely (100 percent burned) by the Waldo Canyon fire during the summer of 2012 ( MTBS, 2020 ). Surface velocity, stage, and precipitation time series collected during the DEFENS deployment on 10 August 2015 were used to monitor and predict flood wave velocities and travel times as a function of stream discharge (discharge; streamflow). The 10 August 2015 event exhibited spatial and temporal variations in rainfall intensity and duration that resulted in a discharge equal to 5.01 cubic meters per second (m 3 /s). Discharge was estimated post-event using a slope-conveyance indirect discharge method and was verified using velocity radars and the probability concept algorithm. Mean flood wave velocities – represented by the kinematic celerity ( c k = 2.619 m e t e r s p e r s e c o n d , m / s ± 0.556 p e r c e n t "> 𝑐 𝑘 = 2.619 𝑚𝑒𝑡𝑒𝑟𝑠 𝑝𝑒𝑟 𝑠𝑒𝑐𝑜𝑛𝑑, m/s ± 0.556 𝑝𝑒𝑟𝑐𝑒𝑛𝑡) and dynamic celerity ( c d = 3.533 m / s ± 0.181 p e r c e n t a n d t h e i r u n c e r t a i n t i e s "> 𝑐 𝑑 = 3.533 m/s ± 0.181 𝑝𝑒𝑟𝑐𝑒𝑛𝑡) and their uncertainties were computed. L-moments were computed to establish probability density functions (PDFs) and associated statistics for each of the at-a-section hydraulic parameters to serve as a workflow for implementing alert networks in hydrologically similar basins that lack data. Measured flood wave velocities and travel times agreed well with predicted values. Absolute percent differences between predicted and measured flood wave velocities ranged from 1.6 percent to 49 percent and varied with water slope, hydraulic radius, and depth. The kinematic celerity was a better predictor for steep slopes and wide flood plains associated with the Upper Waldo and Middle Waldo radar streamgages; whereas, the dynamic celerity was a better surrogate for shallow slopes and incised channels such as the Lower Waldo radar streamgage. The method demonstrates the potential extensibility of a post-wildfire warning system by (1) leveraging multiple systems (i.e., weather radar, near-field velocity and stage radars, and rain gages) for accurate and timely warnings of debris and floodflows, (2) establishing an order of operations to site, install, and operate near-field radars and conventional rain gages to record floodflows, forecast travel times, and document geomorphic change in this basin and hydrologically similar basins that lack data, and (3) communicating data operationally with the Colorado Department of Transportation engineering staff, National Weather Service forecasters, and emergency managers.

Colorado↗

USGS2021

Characterization of water-resource threats and needs for U.S. Fish and Wildlife Service National Wildlife Refuges in the Legacy Mountain-Prairie Region, 2020

The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service (FWS), began a study in 2019 to complete the compilation and quality assurance of water-resource threats and needs data for the 117 National Wildlife Refuges (NWRs) in the FWS Legacy Mountain-Prairie Region (LMPR) and to characterize the water-resource threats and needs of each refuge and of the LMPR itself. The LMPR encompasses the states of Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, and Wyoming. This report includes the compilation and quality assurance of current (April 2020) water-resource threats and needs data for the refuges in the LMPR and a statistical, graphical, and spatial characterization, including the ranking and prioritization of threat types, threat causes, and needs by the number of occurrences in the LMPR as a whole and by refuges, states, and select U.S. Environmental Protection Agency Level III Ecoregions. A total of 540 unique threat occurrences were identified for 109 refuges in the LMPR. No threats were identified for eight refuges. About 43 percent of the threat occurrences, for 59 refuges, had a high-severity threat rating. Of the 10 most common threat types, 8 were also among the most common high-severity threat types. Water-resource threats had 72 different causes. About 83 percent of the overall common causes for threats and for high-severity threats were the same. The most common threat types overall and the most common high-severity threat types were compromised water management capability, habitat shifting/alteration, and altered flow regimes. The 20 water-resource threat types for Long Lake NWR were the most for refuges in the LMPR. Other refuges with the greatest number of threat types included Marais des Cygnes NWR (18) and Arapaho and Lee Metcalf NWRs (16 each). About 54 percent of refuges with threats had high-severity threats. Arapaho and Quivira NWRs each had 10 high-severity threat types, the maximum number of high-severity threat types for LMPR refuges. A total of 637 unique need occurrences were identified for 114 refuges. No needs were reported for three refuges. The most common need type, a Water Resource Inventory and Assessment, was reported for 78 refuges. Two of the most common need types, repair and replace water management infrastructure and water supply/quantity monitoring, were the most common high-priority need types. Bear River Migratory Bird Refuge had the most (39) unique water-resource need types for refuges in the LMPR. Other refuges with the greatest number of need types were Baca (38), Alamosa (36), and Monte Vista (36) NWRs. The most high-priority need types for a refuge was 23, at Monte Vista NWR. Alamosa (22), Baca (22), and Lake Andes (19) NWRs were also among the top 4 refuges with the greatest number of high-priority need types. An overall ranking scheme was developed to identify refuges that have the highest-ranking priority for conservation efforts to fulfill refuges’ statutory purposes. The count of occurrences of high-severity threats and high-priority needs were summed to determine the overall ranking value for a refuge. The 10 refuges with the highest overall ranking values, in order of ranking from higher to lower, were Alamosa, Baca, and Monte Vista NWRs (tied for highest); Lake Andes NWR, Ouray and Quivira NWRs, Bear River Migratory Bird Refuge and Flint Hills NWR, Cokeville Meadows NWR, and Arapaho NWR. About 33 percent of overall threat occurrences were reported as under the control of the FWS to mitigate, as were 37 percent of all threat occurrences with a high-severity rating. The most common overall threat types and high-severity threat types under FWS control were compromised water management capability; habitat shifting/alteration; altered flow regimes; loss/alteration of wetland habitat; and legal challenges or fines for non-compliance with water policy, law, or regulation. A total of 68 percent of overall need occurrences and 67 percent of all high-priority need occurrences were under the control of the FWS. The most common overall need types and high-priority needs types under control were repair or replace water management infrastructure, water supply/quantity monitoring, water quality baseline monitoring, and protect habitat from invasive species. A Water Resource Inventory and Assessment was also a common overall need under FWS control, as was the high-priority need of water level monitoring.

Colorado, Kansas, Montana, Nebraska, North Dakota,↗

USGS2020

QCam: sUAS-based doppler radar for measuring river discharge

The U.S. Geological Survey is actively investigating remote sensing of surface velocity and river discharge (discharge) from satellite-, high altitude-, small, unmanned aircraft systems- (sUAS or drone), and permanent (fixed) deployments. This initiative is important in ungaged basins and river reaches that lack the infrastructure to deploy conventional streamgaging equipment. By coupling alternative discharge algorithms with sensors capable of measuring surface velocity, streamgage networks can be established in regions where data collection was previously impractical or impossible. To differentiate from satellite or high-altitude platforms, near-field remote sensing is conducted from sUAS or fixed platforms. QCam is a Doppler (velocity) radar mounted and integrated on a 3DR © Solo sUAS. It measures the along-track surface velocity by spot dwelling in a river cross section at a vertical where the maximum surface velocity is recorded. The surface velocity is translated to a mean-channel (mean) velocity using the probability concept (PC), and discharge is computed using the PC-derived mean velocity and cross-sectional area. Factors including surface-scatterer quality, flight altitude, propwash, wind drift, and sample duration may affect the radar-returns and the subsequent computation of mean velocity and river discharge. To evaluate the extensibility of the method, five science flights were conducted on four rivers of varying size and dynamics and included the Arkansas River, Colorado (CO), USA (two events); Salcha River near Salchaket, Alaska (AK), USA; South Platte River, CO, USA; and the Tanana River, AK, USA. QCam surface velocities and river discharges were compared to conventional streamgaging methods, which represented truth. QCam surface velocities for the Arkansas River, Salcha River, South Platte River, and Tanana River were 1.02 meters per second (m/s) and 1.43 m/s; 1.58 m/s; 0.90 m/s; and 2.17 m/s, respectively. QCam discharges (and percent differences) were 9.48 (0.3%) and 20.3 cubic meters per second (m 3 /s) (2.5%); 62.1 m 3 /s (−10.4%); 3.42 m 3 /s (7.3%), and 1579 m 3 /s (−18.8%). QCam results compare favorably with conventional streamgaging and are a viable near-field remote sensing technology that can be operationalized to deliver real-time surface velocity, mean velocity, and river discharge, if cross-sectional area is available.

Remote Sensing↗

USGS2020

Bathymetry of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1–3, and Non-Potable Reservoirs 1–4 at the U.S. Air Force Academy, Colorado, 2019

The U.S. Geological Survey, in cooperation with the U.S. Air Force Academy (USAFA), carried out bathymetric and topographic surveys to characterize the volume of Deadmans Lake, Golf Course Reservoir 9, Ice Lake, Kettle Lakes 1–3, and Non-Potable Reservoirs 1–4 at the U.S. Air Force Academy, Colorado. Bathymetric maps of each lake and reservoir are presented with figures of the elevation-volume curves. The bathymetric surveys were carried out from October 15, 2019, to December 12, 2019, using a manually operated, boat-mounted, single-beam echo sounder integrated with a Real-Time Kinematic Global Navigation Satellite Systems receiver. Topographic surveys were carried out during the same time period using Real-Time Kinematic Global Navigation Satellite System to collect elevation data at and above the water surface and up to the elevation of the dam or spillway at the time of the surveys. The topographic and bathymetric datasets were imported into Esri ArcMap 10.7.1. The combined survey points were then interpolated into digital elevation models, which were used to determine lake or reservoir volumes that correspond to water-surface elevations between the lakebed and the approximate top of the dam or spillway. This report provides an updated characterization of storage capacity and improved understanding of present (2019) water capacity in the lakes and reservoirs at the USAFA. In addition, these surveys serve as a baseline that could be compared with future surveys of the lakes and reservoirs. The differences in these and future surveys could then be used to determine sedimentation infill rates and provide estimates of the lifespan of the lakes and reservoirs.

Colorado↗

USGS2020

Incipient bed-movement and flood-frequency analysis using hydrophones to estimate flushing flows on the upper Colorado River, Colorado, 2019

In 2019, the U.S. Geological Survey, in cooperation with the Upper Colorado River Wild and Scenic Stakeholder Group, studied the magnitude and recurrence interval of streamflow (discharge) needed to initiate bed movement of gravel-sized and finer sediment in a segment of the Colorado River in Colorado to better understand sediment movement and its relation to flow regimes of the river. The study area extended from the confluence of the Blue and Colorado Rivers near Kremmling, Colorado, downstream to the confluence of the Eagle and Colorado Rivers near Dotsero, Colo. Bed movement occurred more frequently and at lower streamflows from State Bridge to Catamount Bridge compared to the study area upstream from State Bridge. As a result, the flushing flow was characterized in the study area using two definitions: the “upstream flushing flow” for locations above State Bridge and the “downstream flushing flow” for locations below State Bridge. Acoustic data from stationary hydrophones continuously deployed in the spring and summer of 2019 and longitudinal hydrophone acoustic profiles manually collected in summer 2019 were used to identify the streamflow needed for incipient gravel-bed movement and establish flushing flows defined for this study. The upstream flushing flow was defined as 3,000 cubic feet per second (ft 3 /s) at streamgage 09058000 Colorado River near Kremmling, Colo. (the Kremmling streamgage) based on the underwater acoustic data from the downstream location at the Radium stationary site (2,950 ft 3 /s at the Kremmling streamgage which was rounded to 3,000 ft 3 /s). The downstream flushing flow was defined as 2,400 ft 3 /s at the Kremmling streamgage or 3,100 ft 3 /s at streamgage 09060799 Colorado River at Catamount Bridge, Colo. (the Catamount Bridge streamgage) based on the more conservative streamflow associated with the flushing flow defined using underwater acoustic data from the downstream location at the above Catamount Bridge stationary site (2,310 ft 3 /s at the Kremmling streamgage which was rounded to 2,400 ft 3 /s and 3,040 ft 3 /s at the Catamount Bridge streamgage which was rounded to 3,100 ft 3 /s). The annual series of peak-streamflow data at the Kremmling streamgage were used to estimate annual exceedance probability (AEP) streamflows to compare to the flushing flow. Results from the Denver Water Platte and Colorado Simulation Model were used to generate daily peak-streamflows for a future conditions scenario provided for this report. The upstream flushing flow of approximately 3,000 ft 3 /s at the Kremmling streamgage has an AEP near 0.50 (2-year return period) depending on the period of historical record and an AEP near 0.43 (2.33-year return period) for the future period. The downstream flushing flow of approximately 2,400 ft 3 /s at the Kremmling streamgage has an AEP near 0.67 (1.5-year return period) depending on the period of historical record and an AEP near 0.67 (1.5-year return period) for the future period.

Colorado↗

USGS2019

Water-budget analysis of the Upper Big Sandy Designated Ground-water Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016

The U.S. Geological Survey in cooperation with the Colorado Water Conservation Board and the Upper Big Sandy Groundwater Management District carried out a study in 2016 to evaluate potential groundwater storage changes within the Upper Big Sandy Designated Groundwater Basin (UBSDGB) alluvial aquifer, including groundwater flow between the UBSDGB alluvial aquifer and the Denver Basin bedrock aquifers. The UBSDGB alluvial aquifer is located along the ephemeral Big Sandy Creek on the east-central edge of the Denver Basin aquifer system and covers an area of about 66,560 acres within the UBSDGB. The UBSDGB alluvial aquifer consists of unconsolidated Quaternary sand and gravel deposits that contain an unconfined (water table) groundwater system. The western three-fourths of the UBSDGB alluvial aquifer overlies the Tertiary and Cretaceous bedrock formations that compose the Denver Basin aquifer system. The updated water budget for the UBSDGB alluvial aquifer, including annual change in groundwater storage in 2016, was determined by combining water-budget information from an existing Denver Basin model for about three-fourths of the study area with best estimates for the major water-budget components for the area outside the Denver Basin aquifer system. The western part of the UBSDGB was included in the Denver Basin model (modeled area), whereas the eastern part of the UBSDGB was not included in the Denver Basin model (unmodeled area). The water-budget components were first estimated for the modeled area using outputs from the Denver Basin model, which uses the modular finite-difference groundwater flow computer model MODFLOW-2000 with 1-mile grid cells. For this study, the Denver Basin model was updated with additional data from 2004 through 2016 to generate current (2016) estimates of water consumption in the UBSDGB alluvial aquifer. A basin-specific water budget for the UBSDGB alluvial aquifer from the Denver Basin model was computed using a modeling tool called ZONEBUDGET. The modeled area groundwater budget, along with previous studies, was used to estimate a groundwater budget for the unmodeled area, and results for the modeled and unmodeled areas were combined for an overall water-budget estimate for the entire UBSDGB alluvial aquifer. The net groundwater flow into the basin from adjacent alluvial aquifers was positive with flow entering the UBSDGB alluvial aquifer. Combining the total inflow from adjacent alluvial and the total outflow to adjacent alluvial aquifers resulted in a net flow from adjacent alluvial aquifers to UBSDGB alluvial aquifer of 5,125 acre-feet (ac-ft) in 2016. The net flow between the underlying bedrock aquifers and the UBSDGB alluvial aquifer was positive with flow entering the UBSDGB alluvial aquifer from the bedrock aquifers. The net flow from the bedrock aquifers to the UBSDGB alluvial aquifer was 347 ac-ft in 2016. Net recharge (precipitation and irrigation return flows minus evaporation) into the UBSDGB alluvial aquifer was negative with groundwater being removed from the UBSDGB alluvial aquifer over the total area of the basin. Combining the total inflow from recharge to the UBSDGB alluvial aquifer of 11,153 ac-ft in 2016 and the total evapo-transpiration of −11,656 ac-ft from the UBSDGB alluvial aquifer in 2016 resulted in a net recharge from UBSDGB alluvial aquifer of −503 ac-ft in 2016. Combining the modeled and unmodeled well pumping resulted in a total well pumping volume of −3,735 ac-ft in 2016 from the UBSDGB alluvial aquifer. The net groundwater flow to the stream network in the basin was negative with flow discharging from the UBSDGB alluvial aquifer into streams. Combining the total inflow from streams and the total outflow to streams for the UBSDGB alluvial aquifer resulted in −1,032 ac-ft in 2016 that was lost to the stream network in the UBSDGB. The net groundwater flow out of the UBSDGB was negative with flow leaving the UBSDGB alluvial aquifer. Combining the total area inflow to the basin from upgradient areas and the total area outflow from the basin for the UBSDGB alluvial aquifer resulted in a net flow out of the basin of −2,300 ac-ft. In the annual groundwater budget for 2016, groundwater storage in the UBSDGB alluvial aquifer system was removed because annual groundwater outflows from storage exceeded groundwater inflows to storage; in other words, water was removed from storage to balance the annual water budget. Combining the net flow from storage for the modeled area of 73 ac-ft and the inflow from storage for the unmodeled area of 2,025 ac-ft resulted in a net positive flow from storage of the UBSDGB alluvial aquifer of 2,098 ac-ft. Increased pumping since 1958 in the Denver and upper Arapahoe aquifers, not necessarily in the UBSDGB, has caused a change in flow from bedrock units, which were minor or non-contributors of inflow to the UBSDGB alluvial aquifer, to receiving outflow from the UBSDGB alluvial aquifer. Since 2000, aquifer storage has been an inflow component of the water budget, which means that outflow from the modeled area exceeded inflow for the UBSDGB alluvial aquifer. Increased recharge from wetter than average years could replenish the UBSDGB alluvial aquifer. From 2003 through 2016, 13 of the 25 observation wells completed in the UBSDGB alluvial aquifer had a decline in the groundwater-level elevation with an average decline of −2.21 feet, and 12 of the 25 observation wells had an increase in the groundwater-level elevation with an average increase of 1.54 feet. In general, wells at the eastern and western edges of the UBSDGB showed an increase in groundwater-level elevation that appears related to areas of groundwater discharge from the lower Dawson and Laramie-Fox Hills bedrock aquifers to the UBSDGB alluvial aquifer. The remaining wells exhibited water-level declines. Future work could include the development of a basin-specific model to serve as a basin management tool for modeling changes in groundwater levels and storage under various future groundwater recharge and withdrawal scenarios.

Colorado↗

USGS2018

Flood-inundation maps for the South Platte River at Fort Morgan, Colorado, 2018

In 2017, the U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board (CWCB), studied floods in the historic record to produce a library of flood-inundation maps for the South Platte River at Fort Morgan, Colorado. Digital flood-inundation maps for a 4.5-mile (7.2-kilometers) reach of the South Platte River at Fort Morgan from Morgan County Road 16 to Morgan County Road 20.5, were created. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey streamgage on the South Platte River at Fort Morgan (streamgage number 06759500). Water-surface profiles were computed for the stream reach by means of a one-dimensional, step-backwater model. The September 15, 2013, and May 20, 2017, floods were used to calibrate the model, and the June 15, 2015, and May 29, 2017, floods were used to independently validate the model. Nine pressure transducers were deployed to record the stage at nine different locations along the reach and to document the floods of May 20 and 29, 2017, at the South Platte River at Fort Morgan streamgage. The hydraulic model was then used to compute 16 water-surface profiles for flood stages at 1-foot (ft; 0.3-meter [m]) intervals referenced to the streamgage datum and ranging from 12 ft (3.66 m) or below bankfull to 27 ft (8.23 m), which is 1 ft (0.3 m) greater than the highest recorded water level (25.73 ft [7.84 m] on September 15, 2013) at the South Platte River at Fort Morgan streamgage during its period of record; the 2013 flood exceeds the major flood stage of 21.5 ft (6.55 m) by more than 4 ft (1.2 m), as defined by the National Weather Service. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.37-ft [0.11-m] vertical accuracy and 3.28-ft [1.00-m] horizontal resolution) to delineate the area flooded for stages ranging from 12 to 27 ft (3.66 to 8.23 m). These flood-inundation maps, in conjunction with the real-time stage data from the USGS streamgage on the South Platte River at Fort Morgan, are intended to help guide the general public in taking individual safety precautions and provide emergency management personnel with a tool to efficiently manage emergency flood operations and post flood recovery efforts.

Colorado↗

USGS2018

Computing under-ice discharge: A proof-of-concept using hydroacoustics and the Probability Concept

Under-ice discharge is estimated using open-water reference hydrographs; however, the ratings for ice-affected sites are generally qualified as poor. The U.S. Geological Survey (USGS), in collaboration with the Colorado Water Conservation Board, conducted a proof-of-concept to develop an alternative method for computing under-ice discharge using hydroacoustics and the Probability Concept. The study site was located south of Minturn, Colorado (CO), USA, and was selected because of (1) its proximity to the existing USGS streamgage 09064600 Eagle River near Minturn, CO, and (2) its ease-of-access to verify discharge using a variety of conventional methods. From late September 2014 to early March 2015, hydraulic conditions varied from open water to under ice. These temporal changes led to variations in water depth and velocity. Hydroacoustics (tethered and uplooking acoustic Doppler current profilers and acoustic Doppler velocimeters) were deployed to measure the vertical-velocity profile at a singularly important vertical of the channel-cross section. Because the velocity profile was non-standard and cannot be characterized using a Power Law or Log Law, velocity data were analyzed using the Probability Concept, which is a probabilistic formulation of the velocity distribution. The Probability Concept-derived discharge was compared to conventional methods including stage-discharge and index-velocity ratings and concurrent field measurements; each is complicated by the dynamics of ice formation, pressure influences on stage measurements, and variations in cross-sectional area due to ice formation. No particular discharge method was assigned as truth. Rather one statistical metric (Kolmogorov-Smirnov; KS), agreement plots, and concurrent measurements provided a measure of comparability between various methods. Regardless of the method employed, comparisons between each method revealed encouraging results depending on the flow conditions and the absence or presence of ice cover. For example, during lower discharges dominated by under-ice and transition (intermittent open-water and under-ice) conditions, the KS metric suggests there is not sufficient information to reject the null hypothesis and implies that the Probability Concept and index-velocity rating represent similar distributions. During high-flow, open-water conditions, the comparisons are less definitive; therefore, it is important that the appropriate analytical method and instrumentation be selected. Six conventional discharge measurements were collected concurrently with Probability Concept-derived discharges with percent differences (%) of −9.0%, −21%, −8.6%, 17.8%, 3.6%, and −2.3%. This proof-of-concept demonstrates that riverine discharges can be computed using the Probability Concept for a range of hydraulic extremes (variations in discharge, open-water and under-ice conditions) immediately after the siting phase is complete, which typically requires one day. Computing real-time discharges is particularly important at sites, where (1) new streamgages are planned, (2) river hydraulics are complex, and (3) shifts in the stage-discharge rating are needed to correct the streamflow record. Use of the Probability Concept does not preclude the need to maintain a stage-area relation. Both the Probability Concept and index-velocity rating offer water-resource managers and decision makers alternatives for computing real-time discharge for open-water and under-ice conditions.

Colorado↗

USGS2017

Peak discharge, flood frequency, and peak stage of floods on Big Cottonwood Creek at U.S. Highway 50 near Coaldale, Colorado, and Fountain Creek below U.S. Highway 24 in Colorado Springs, Colorado, 2016

The U.S. Geological Survey (USGS), in cooperation with the Colorado Department of Transportation, determined the peak discharge, annual exceedance probability (flood frequency), and peak stage of two floods that took place on Big Cottonwood Creek at U.S. Highway 50 near Coaldale, Colorado (hereafter referred to as “Big Cottonwood Creek site”), on August 23, 2016, and on Fountain Creek below U.S. Highway 24 in Colorado Springs, Colorado (hereafter referred to as “Fountain Creek site”), on August 29, 2016. A one-dimensional hydraulic model was used to estimate the peak discharge. To define the flood frequency of each flood, peak-streamflow regional-regression equations or statistical analyses of USGS streamgage records were used to estimate annual exceedance probability of the peak discharge. A survey of the high-water mark profile was used to determine the peak stage, and the limitations and accuracy of each component also are presented in this report. Collection and computation of flood data, such as peak discharge, annual exceedance probability, and peak stage at structures critical to Colorado’s infrastructure are an important addition to the flood data collected annually by the USGS. The peak discharge of the August 23, 2016, flood at the Big Cottonwood Creek site was 917 cubic feet per second (ft 3/s ) with a measurement quality of poor (uncertainty plus or minus 25 percent or greater). The peak discharge of the August 29, 2016, flood at the Fountain Creek site was 5,970 ft 3/s with a measurement quality of poor (uncertainty plus or minus 25 percent or greater). The August 23, 2016, flood at the Big Cottonwood Creek site had an annual exceedance probability of less than 0.01 (return period greater than the 100-year flood) and had an annual exceedance probability of greater than 0.005 (return period less than the 200-year flood). The August 23, 2016, flood event was caused by a precipitation event having an annual exceedance probability of 1.0 (return period of 1 year, or the 1-year storm), which is a statistically common (high probability) storm. The Big Cottonwood Creek site is downstream from the Hayden Pass Fire burn area, which dramatically altered the hydrology of the watershed and caused this statistically rare (low probability) flood from a statistically common (high probability) storm. The peak flood stage at the cross section closest to the U.S. Highway 50 culvert was 6,438.32 feet (ft) above the North American Datum of 1988 (NAVD 88). The August 29, 2016, flood at the Fountain Creek site had an estimated annual exceedance probability of 0.5505 (return period equal to the 1.8-year flood). The August 29, 2016, flood event was caused by a precipitation event having an annual exceedance probability of 1.0 (return period of 1 year, or the 1-year storm). The peak stage during this flood at the cross section closest to the U.S. Highway 24 bridge was 5,832.89 ft (NAVD 88). Slope-area indirect discharge measurements were carried out at the Big Cottonwood Creek and Fountain Creek sites to estimate peak discharge of the August 23, 2016, flood and August 29, 2016, flood, respectively. The USGS computer program Slope-Area Computation Graphical User Interface was used to compute the peak discharge by adding the surveyed cross sections with Manning roughness coefficient assignments to the high-water marks. The Manning roughness coefficients for each cross section were estimated in the field using the Cowan method.

Colorado↗

USGS2017

Bathymetry of Clear Creek Reservoir, Chaffee County, Colorado, 2016

To better characterize the water supply capacity of Clear Creek Reservoir, Chaffee County, Colorado, the U.S. Geological Survey, in cooperation with the Pueblo Board of Water Works and Colorado Mountain College, carried out a bathymetry survey of Clear Creek Reservoir. A bathymetry map of the reservoir is presented here with the elevation-surface area and the elevation-volume relations. The bathymetry survey was carried out June 6–9, 2016, using a man-operated boat-mounted, multibeam echo sounder integrated with a Global Positioning System and a terrestrial survey using real-time kinematic Global Navigation Satellite Systems. The two collected datasets were merged and imported into geographic information system software. The equipment and methods used in this study allowed water-resource managers to maintain typical reservoir operations, eliminating the need to empty the reservoir to carry out the survey.

Colorado↗

USGS2016

Paleoflood investigations to improve peak-streamflow regional-regression equations for natural streamflow in eastern Colorado, 2015

The U.S. Geological Survey (USGS), in cooperation with the Colorado Department of Transportation, developed regional-regression equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, 0.2-percent annual exceedance-probability discharge (AEPD) for natural streamflow in eastern Colorado. A total of 188 streamgages, consisting of 6,536 years of record and a mean of approximately 35 years of record per streamgage, were used to develop the peak-streamflow regional-regression equations. The estimated AEPDs for each streamgage were computed using the USGS software program PeakFQ. The AEPDs were determined using systematic data through water year 2013. Based on previous studies conducted in Colorado and neighboring States and on the availability of data, 72 characteristics (57 basin and 15 climatic characteristics) were evaluated as candidate explanatory variables in the regression analysis. Paleoflood and non-exceedance bound ages were established based on reconnaissance-level methods. Multiple lines of evidence were used at each streamgage to arrive at a conclusion (age estimate) to add a higher degree of certainty to reconnaissance-level estimates. Paleoflood or nonexceedance bound evidence was documented at 41 streamgages, and 3 streamgages had previously collected paleoflood data.To determine the peak discharge of a paleoflood or non-exceedanc bound, two different hydraulic models were used. The mean standard error of prediction ( SEP ) for all 8 AEPDs was reduced approximately 25 percent compared to the previous flood-frequency study. For paleoflood data to be effective in reducing the SEP in eastern Colorado, a larger ratio than 44 of 188 (23 percent) streamgages would need paleoflood data and that paleoflood data would need to increase the record length by more than 25 years for the 1-percent AEPD. The greatest reduction in SEP for the peak-streamflow regional-regression equations was observed when additional new basin characteristics were included in the peak-streamflow regional-regression equations and when eastern Colorado was divided into two separate hydrologic regions. To make further reductions in the uncertainties of the peak-streamflow regional-regression equations in the Foothills and Plains hydrologic regions, additional streamgages or crest-stage gages are needed to collect peak-streamflow data on natural streams in eastern Colorado. Generalized-Least Squares regression was used to compute the final peak-streamflow regional-regression equations for peak-streamflow. Dividing eastern Colorado into two new individual regions at –104° longitude resulted in peak-streamflow regional-regression equations with the smallest SEP . The new hydrologic region located between –104° longitude and the Kansas-Nebraska State line will be designated the Plains hydrologic region and the hydrologic region comprising the rest of eastern Colorado located west of the –104° longitude and east of the Rocky Mountains and below 7,500 feet in the South Platte River Basin and below 9,000 feet in the Arkansas River Basin will be designated the Foothills hydrologic region.

Colorado↗

USGS2016

Identifying and preserving high-water mark data

High-water marks provide valuable data for understanding recent and historical flood events. The proper collection and recording of high-water mark data from perishable and preserved evidence informs flood assessments, research, and water resource management. Given the high cost of flooding in developed areas, experienced hydrographers, using the best available techniques, can contribute high-quality data toward efforts such as public education of flood risk, flood inundation mapping, flood frequency computations, indirect streamflow measurement, and hazard assessments. This manual presents guidance for skilled high-water mark identification, including marks left behind in natural and man-made environments by tranquil and rapid flowing water. This manual also presents pitfalls and challenges associated with various types of flood evidence that help hydrographers identify the best high-water marks and assess the uncertainty associated with a given mark. Proficient high-water mark data collection contributes to better understanding of the flooding process and reduces risk through greater ability to estimate flood probability. The U.S. Geological Survey, operating the Nation’s premier water data collection network, encourages readers of this manual to familiarize themselves with the art and science of high-water mark collection. The U.S. Geological survey maintains a national database at http://water.usgs.gov/floods/FEV/ that includes high-water mark information for many flood events, and local U.S. Geological Survey Water Science Centers can provide information to interested readers about participation in data collection and flood documentation efforts as volunteers or observers.

Techniques and Methods↗

USGS2015

Evaluation of mean-monthly streamflow-regression equations for Colorado, 2014

The U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, evaluated the predictive uncertainty of mean-monthly streamflow-regression equations representative of natural streamflow conditions in Colorado. This study evaluates the predictive uncertainty of mean-monthly streamflow-regression equations developed in a 2009 U.S. Geological Survey study using streamflow data collected over the entire period of record at each streamgage through calendar year 2013. The study area for this report is limited to the Mountain, Northwest, Rio Grande, and Southwest hydrologic regions of Colorado. Data collected from the beginning of the period of record through calendar year 2013 were used to evaluate the mean-monthly streamflow equations using the same basin characteristics as in the 2009 study. U.S. Geological Survey and Colorado Division of Water Resources streamgages with at least 10 years of streamflow record and identified as representative of natural streamflow conditions were selected for this study. During the streamgage selection process, a total of 432 streamgages, composed of 278 from the 2009 study and 154 new streamgages, were identified. The updated standard error of prediction and adjusted coefficient of determination values that correspond to the mean-monthly streamflow equations developed in the 2009 study are in close agreement with the results of this study. The old streamgages performed slightly better than the new streamgages, with approximately 88 and 85 percent of the data within the prediction intervals, respectively. This result was expected because the streamgages used to develop the regression equations should yield a better performance than the new streamgages. For all hydrologic regions, approximately 87 percent of the data are within the 95-percent prediction intervals. The explanation for why fewer than 95 percent of the data are within the prediction intervals is that the data do not conform perfectly to the regression assumptions required to accurately estimate performance metrics. The equations for the Rio Grande hydrologic region had the best fit with the parametric prediction-interval assumptions, with approximately 91.8 percent of the data within the prediction interval (average 12 months). The Mountain, Northwest, and Southwest hydrologic regions had 87.8, 84.9, and 83.5 percent of the data contained within the prediction interval, respectively. Monthly adjusted coefficient of determination values were computed and have the same general pattern for all four hydrologic regions. The largest values usually occur in March or April, and the lowest values usually occur in August or September. Only the Rio Grande hydrologic region deviates from this seasonal pattern, exhibiting a decrease in adjusted coefficient of determination values in August and September, with the lowest values occurring in the winter months (December, January, and February). Generally, the adjusted coefficient of determination values for this report are just slightly less (0.76 compared to 0.79) than the values computed in the 2009 study. The similarity of values, even when tested with data not used to originally develop the mean-monthly streamflow-regression equations, provides confidence that the predictive uncertainty of mean-monthly regression equations in the 2009 study are accurate. The fact that the results for the two datasets are very similar provides assurance that when these equations are applied to locations not used to develop the equations, the standard error of prediction and adjusted-coefficient of determination error metrics should be similar to those established in the 2009 study for locations with natural streamflow. The median absolute differences between the observed and computed mean-monthly streamflow for Mountain, Northwest, and Southwest hydrologic regions are fairly uniform throughout the year, with the exception of late summer and early fall (July, August, and September), when each hydrologic region exhibits a substantial increase in median absolute percent difference. The greatest difference occurs in the Northwest hydrologic region, and the smallest difference occurs in the Mountain hydrologic region. The Rio Grande hydrologic region shows seasonal variation in median absolute percent difference with March, April, August, and September having a median absolute difference near or below 40 percent, and the remaining months of the year having a median absolute difference near or above 50 percent. In the Mountain, Northwest, and Southwest hydrologic regions, the mean-monthly streamflow equations perform the best during spring (March, April, and May). However, in the Rio Grande hydrologic region, the mean-monthly streamflow equations perform the best during late summer and early fall (August and September).

Arizona, Colorado, New Mexico, Utah, Wyoming↗

USGS2014

Remediation scenarios for attenuating peak flows and reducing sediment transport in Fountain Creek, Colorado, 2013

The U.S. Geological Survey (USGS) in cooperation with the Fountain Creek Watershed, Flood Control and Greenway District assessed remediation scenarios to attenuate peak flows and reduce sediment loads in the Fountain Creek watershed. To evaluate these strategies, the U.S. Army Corps of Engineers Hydrologic Engineering Center (HEC) hydrologic and hydraulic models were employed. The U.S. Army Corps of Engineers modeling system HEC-HMS (Hydrologic Modeling System) version 3.5 was used to simulate runoff in the Fountain Creek watershed, Colorado, associated with storms of varying magnitude and duration. Rain-gage precipitation data and radar-based precipitation data from the April 28–30, 1999, and September 14–15, 2011, storm events were used in the calibration process for the HEC-HMS model. The curve number and lag time for each subwatershed and Manning's roughness coefficients for each channel reach were adjusted within an acceptable range so that the simulated and measured streamflow hydrographs for each of the 12 USGS streamgages approximated each other. The U.S. Army Corps of Engineers modeling system HEC-RAS (River Analysis System) versions 4.1 and 4.2 were used to simulate streamflow and sediment transport, respectively, for the Fountain Creek watershed generated by a particular storm event. Data from 15 USGS streamgages were used for model calibration and 7 of those USGS streamgages were used for model validation. The calibration process consisted of comparing the simulated water-surface elevations and the cross-section-averaged velocities from the model with those surveyed in the field at the cross section at the corresponding 15 and 7 streamgages, respectively. The final Manning’s roughness coefficients were adjusted between –30 and 30 percent at the 15 calibration streamgages from the original left, right, and channel-averaged Manning's roughness coefficients upon completion of calibration. The U.S. Army Corps of Engineers modeling system HEC-RAS version 4.2 was used to simulate streamflow and sediment transport for the Fountain Creek watershed generated by a design-storm event. The Laursen-Copeland sediment-transport function was used in conjunction with the Exner 5 sorting method and the Ruby fall-velocity method to predict sediment transport. Six USGS streamgages equipped with suspended-sediment samplers were used to develop sediment-flow rating curves for the sediment-transport-model calibration. The critical Shields number in the Laursen-Copeland sediment-transport function and the volume of sediment available at a given cross section were adjusted during the HEC-RAS sediment-model calibration process. HEC-RAS model simulations used to evaluate the 14 remediation scenarios were based on unsteady-state streamflows associated with a 24-hour, 1-percent annual exceedance probability (100-year) National Oceanic and Atmospheric Administration Type II precipitation event. Scenario 0 represents the baseline or current conditions in the watershed and was used to compare the remaining 13 scenarios. Scenarios 1–8 and 12 rely on side-detention facilities to reduce peak flows and sediment transport. Scenario 9 has a diversion channel, and scenario 10 has a reservoir. Scenarios 11 and 13 incorporate channel armoring and channel widening, respectively. Scenarios 8 and 10, the scenario with the most side-detention facilities, and the scenario with the reservoir, respectively, were the most effective at reducing sediment transport and peak flow at the Pueblo, Colorado, streamgage. Scenarios 8 and 10 altered the peak flow by –58.9 and –56.4 percent, respectively. In turn, scenarios 8 and 10 altered the sediment transport by –17.7 and –62.1 percent, respectively.

Colorado↗

USGS2013

Web-based flood database for Colorado, water years 1867 through 2011

In order to provide a centralized repository of flood information for the State of Colorado, the U.S. Geological Survey, in cooperation with the Colorado Department of Transportation, created a Web-based geodatabase for flood information from water years 1867 through 2011 and data for paleofloods occurring in the past 5,000 to 10,000 years. The geodatabase was created using the Environmental Systems Research Institute ArcGIS JavaScript Application Programing Interface 3.2. The database can be accessed at http://cwscpublic2.cr.usgs.gov/projects/coflood/COFloodMap.html. Data on 6,767 flood events at 1,597 individual sites throughout Colorado were compiled to generate the flood database. The data sources of flood information are indirect discharge measurements that were stored in U.S. Geological Survey offices (water years 1867–2011), flood data from indirect discharge measurements referenced in U.S. Geological Survey reports (water years 1884–2011), paleoflood studies from six peer-reviewed journal articles (data on events occurring in the past 5,000 to 10,000 years), and the U.S. Geological Survey National Water Information System peak-discharge database (water years 1883–2010). A number of tests were performed on the flood database to ensure the quality of the data. The Web interface was programmed using the Environmental Systems Research Institute ArcGIS JavaScript Application Programing Interface 3.2, which allows for display, query, georeference, and export of the data in the flood database. The data fields in the flood database used to search and filter the database include hydrologic unit code, U.S. Geological Survey station number, site name, county, drainage area, elevation, data source, date of flood, peak discharge, and field method used to determine discharge. Additional data fields can be viewed and exported, but the data fields described above are the only ones that can be used for queries.

Colorado↗