Geology topics

Ken Eng

Publications and source records attributed to Ken Eng.

28 records · Page 2Linked to original sources

USGS2013

A national streamflow network gap analysis

The U.S. Geological Survey (USGS) conducted a gap analysis to evaluate how well the USGS streamgage network meets a variety of needs, focusing on the ability to calculate various statistics at locations that have streamgages (gaged) and that do not have streamgages (ungaged). This report presents the results of analysis to determine where there are gaps in the network of gaged locations, how accurately desired statistics can be calculated with a given length of record, and whether the current network allows for estimation of these statistics at ungaged locations. The analysis indicated that there is variability across the Nation’s streamflow data-collection network in terms of the spatial and temporal coverage of streamgages. In general, the Eastern United States has better coverage than the Western United States. The arid Southwestern United States, Alaska, and Hawaii were observed to have the poorest spatial coverage, using the dataset assembled for this study. Except in Hawaii, these areas also tended to have short streamflow records. Differences in hydrology lead to differences in the uncertainty of statistics calculated in different regions of the country. Arid and semiarid areas of the Central and Southwestern United States generally exhibited the highest levels of interannual variability in flow, leading to larger uncertainty in flow statistics. At ungaged locations, information can be transferred from nearby streamgages if there is sufficient similarity between the gaged watersheds and the ungaged watersheds of interest. Areas where streamgages exhibit high correlation are most likely to be suitable for this type of information transfer. The areas with the most highly correlated streamgages appear to coincide with mountainous areas of the United States. Lower correlations are found in the Central United States and coastal areas of the Southeastern United States. Information transfer from gaged basins to ungaged basins is also most likely to be successful when basin attributes show high similarity. At the scale of the analysis completed in this study, the attributes of basins upstream of USGS streamgages cover the full range of basin attributes observed at potential locations of interest fairly well. Some exceptions included very high or very low elevation areas and very arid areas.

Puerto Rico↗

USGS2012

Macroinvertebrate community change associated with the severity of streamflow alteration

Natural streamflows play a critical role in stream ecosystems, yet quantitative relations between streamflow alteration and stream health have been elusive. One reason for this difficulty is that neither streamflow alteration nor ecological responses are measured relative to their natural expectations. We assessed macroinvertebrate community condition in 25 mountain streams representing a large gradient of streamflow alteration, which we quantified as the departure of observed flows from natural expectations. Observed flows were obtained from US Geological Survey streamgaging stations and discharge records from dams and diversion structures. During low-flow conditions in September, samples of macroinvertebrate communities were collected at each site, in addition to measures of physical habitat, water chemistry and organic matter. In general, streamflows were artificially high during summer and artificially low throughout the rest of the year. Biological condition, as measured by richness of sensitive taxa (Ephemeroptera, Plecoptera and Trichoptera) and taxonomic completeness (O/E), was strongly and negatively related to the severity of depleted flows in winter. Analyses of macroinvertebrate traits suggest that taxa losses may have been caused by thermal modification associated with streamflow alteration. Our study yielded quantitative relations between the severity of streamflow alteration and the degree of biological impairment and suggests that water management that reduces streamflows during winter months is likely to have negative effects on downstream benthic communities in Utah mountain streams.

Utah, Wyoming↗

USGS2012

Predicting the likelihood of altered streamflows at ungauged rivers across the conterminous United States

An approach is presented in this study to aid water-resource managers in characterizing streamflow alteration at ungauged rivers. Such approaches can be used to take advantage of the substantial amounts of biological data collected at ungauged rivers to evaluate the potential ecological consequences of altered streamflows. National-scale random forest statistical models are developed to predict the likelihood that ungauged rivers have altered streamflows (relative to expected natural condition) for five hydrologic metrics (HMs) representing different aspects of the streamflow regime. The models use human disturbance variables, such as number of dams and road density, to predict the likelihood of streamflow alteration. For each HM, separate models are derived to predict the likelihood that the observed metric is greater than (‘inflated’) or less than (‘diminished’) natural conditions. The utility of these models is demonstrated by applying them to all river segments in the South Platte River in Colorado, USA, and for all 10-digit hydrologic units in the conterminous United States. In general, the models successfully predicted the likelihood of alteration to the five HMs at the national scale as well as in the South Platte River basin. However, the models predicting the likelihood of diminished HMs consistently outperformed models predicting inflated HMs, possibly because of fewer sites across the conterminous United States where HMs are inflated. The results of these analyses suggest that the primary predictors of altered streamflow regimes across the Nation are (i) the residence time of annual runoff held in storage in reservoirs, (ii) the degree of urbanization measured by road density and (iii) the extent of agricultural land cover in the river basin.

River Research and Applications↗

USGS2012

Analysis of low flows and selected methods for estimating low-flow characteristics at partial-record and ungaged stream sites in western Washington

A regional low-flow survey of small, perennial streams in western Washington was initiated by the Northwest Indian Fisheries Commission (NWIFC), NWIFC-member tribes, and Point-No-Point Treaty Council in cooperation with the U.S. Geological Survey in 2007 and repeated by the tribes during the low-flow seasons of 2008–09. Low-flow measurements at 63 partial-record and miscellaneous streamflow-measurement sites during surveys in 2007–09 are used with concurrent flows at continuous streamflow-gaging stations (index sites) within the U.S. Geological Survey network to estimate the low-flow metric Q 7,10 at each measurement site (Q 7,10 is defined as the lowest average streamflow for a consecutive 7-day period that recurs on average once every 10 years). Index-site correlation methods for estimating low-flow characteristics at partial-record sites are reviewed and an empirical Monte Carlo technique is used with the daily streamflow record at 43 index sites to determine the error and bias associated with estimating the Q 7,10 at synthetic partial-record sites using three methods: Q-ratio, MOVE.1, and Base-Flow Correlation. The Q-ratio method generally has the lowest error and least amount of bias for 170 scenarios, with each scenario defined by the number of concurrent flow measurements between the partial-record and index sites (ranging from 4 to 20) and the combination of basin attributes used to select the index site. The root-mean square error for the Q-ratio method ranged from 70 to 118 percent, depending on the scenario. The scenario with the smallest root-mean square error used four concurrent flow measurements and the basin attributes: basin area, mean annual precipitation, and base-flow recession time constant, also referred to as tau (τ). Regional low-flow regression models for estimating Q 7,10 at ungaged stream sites are developed from the records of daily discharge at 65 continuous gaging stations (including 22 discontinued gaging stations) for the purpose of evaluating explanatory variables. By incorporating the base-flow recession time constant τ as an explanatory variable in the regression model, the root-mean square error for estimating Q 7,10 at ungaged sites can be lowered to 72 percent (for known values of τ), which is 42 percent less than if only basin area and mean annual precipitation are used as explanatory variables. If partial-record sites are included in the regression data set, τ must be estimated from pairs of discharge measurements made during continuous periods of declining low flows. Eight measurement pairs are optimal for estimating τ at partial-record sites, and result in a lowering of the root-mean square error by 25 percent. A low-flow survey strategy that includes paired measurements at partial-record sites requires additional effort and planning beyond a standard strategy, but could be used to enhance regional estimates of τ and potentially reduce the error of regional regression models for estimating low-flow characteristics at ungaged sites.

Washington↗

USGS2010

Estimation of selected streamflow statistics for a network of low-flow partial-record stations in areas affected by Base Realignment and Closure (BRAC) in Maryland

The U.S. Geological Survey, in cooperation with the Maryland Department of the Environment, operated a network of 20 low-flow partial-record stations during 2008 in a region that extends from southwest of Baltimore to the northeastern corner of Maryland to obtain estimates of selected streamflow statistics at the station locations. The study area is expected to face a substantial influx of new residents and businesses as a result of military and civilian personnel transfers associated with the Federal Base Realignment and Closure Act of 2005. The estimated streamflow statistics, which include monthly 85-percent duration flows, the 10-year recurrence-interval minimum base flow, and the 7-day, 10-year low flow, are needed to provide a better understanding of the availability of water resources in the area to be affected by base-realignment activities. Streamflow measurements collected for this study at the low-flow partial-record stations and measurements collected previously for 8 of the 20 stations were related to concurrent daily flows at nearby index streamgages to estimate the streamflow statistics. Three methods were used to estimate the streamflow statistics and two methods were used to select the index streamgages. Of the three methods used to estimate the streamflow statistics, two of them--the Moments and MOVE1 methods--rely on correlating the streamflow measurements at the low-flow partial-record stations with concurrent streamflows at nearby, hydrologically similar index streamgages to determine the estimates. These methods, recommended for use by the U.S. Geological Survey, generally require about 10 streamflow measurements at the low-flow partial-record station. The third method transfers the streamflow statistics from the index streamgage to the partial-record station based on the average of the ratios of the measured streamflows at the partial-record station to the concurrent streamflows at the index streamgage. This method can be used with as few as one pair of streamflow measurements made on a single streamflow recession at the low-flow partial-record station, although additional pairs of measurements will increase the accuracy of the estimates. Errors associated with the two correlation methods generally were lower than the errors associated with the flow-ratio method, but the advantages of the flow-ratio method are that it can produce reasonably accurate estimates from streamflow measurements much faster and at lower cost than estimates obtained using the correlation methods. The two index-streamgage selection methods were (1) selection based on the highest correlation coefficient between the low-flow partial-record station and the index streamgages, and (2) selection based on Euclidean distance, where the Euclidean distance was computed as a function of geographic proximity and the basin characteristics: drainage area, percentage of forested area, percentage of impervious area, and the base-flow recession time constant, t. Method 1 generally selected index streamgages that were significantly closer to the low-flow partial-record stations than method 2. The errors associated with the estimated streamflow statistics generally were lower for method 1 than for method 2, but the differences were not statistically significant. The flow-ratio method for estimating streamflow statistics at low-flow partial-record stations was shown to be independent from the two correlation-based estimation methods. As a result, final estimates were determined for eight low-flow partial-record stations by weighting estimates from the flow-ratio method with estimates from one of the two correlation methods according to the respective variances of the estimates. Average standard errors of estimate for the final estimates ranged from 90.0 to 7.0 percent, with an average value of 26.5 percent. Average standard errors of estimate for the weighted estimates were, on average, 4.3 percent less than the best average standard errors of estima

Scientific Investigations Report↗

USGS2009

Floods of Selected Streams in Arkansas, Spring 2008

Floods can cause loss of life and extensive destruction to property. Monitoring floods and understanding the reasons for their occurrence are the responsibility of many Federal agencies. The National Weather Service, the U.S. Army Corps of Engineers, and the U.S. Geological Survey are among the most visible of these agencies. Together, these three agencies collect and analyze floodflow information to better understand the variety of mechanisms that cause floods, and how the characteristics and frequencies of floods vary with time and location. The U.S. Geological Survey (USGS) has monitored and assessed the quantity of streamflow in our Nation's streams since the agency's inception in 1879. Because of ongoing collection and assessment of streamflow data, the USGS can provide information about a range of surface-water issues including the suitability of water for public supply and irrigation and the effects of agriculture and urbanization on streamflow. As part of its streamflow-data collection activities, the USGS measured streamflow in multiple streams during extreme flood events in Arkansas in the spring of 2008. The analysis of streamflow information collected during flood events such as these provides a scientific basis for decision making related to resource management and restoration. Additionally, this information can be used by water-resource managers to better define flood-hazard areas and to design bridges, culverts, dams, levees, and other structures. Water levels (stage) and streamflow (discharge) currently are being monitored in near real-time at approximately 150 locations in Arkansas. The streamflow-gaging stations measure and record hydrologic data at 15-minute or hourly intervals; the data then are transmitted through satellites to the USGS database and displayed on the internet every 1 to 4 hours. Streamflow-gaging stations in Arkansas are part of a network of over 7,500 active streamflow-gaging stations operated by the USGS throughout the United States in cooperation with other Federal, State, and local government agencies. In Arkansas, the major supporters of the streamflow-gaging network are the U.S. Army Corps of Engineers, Arkansas Natural Resources Commission, Arkansas Department of Environmental Quality, and Arkansas Geological Survey. Many other Federal, State, and local government entities provide additional support for streamflow-gaging stations. It is the combined support of the USGS and all funding partners that make it possible to maintain an adequate streamflow-gaging network in Arkansas. Data collected over the years at streamflow-gaging stations can be used to characterize the relative magnitude of flood events and their statistical frequency of occurrence. These analyses provide water-resource managers with accurate and reliable hydrologic information based on present and historical flow conditions. Continued collection of streamflow data, with consideration of changes in land use, agricultural practices, and climate change, will help scientists to more accurately characterize the magnitude of extreme floods in the future.

Fact Sheet↗

USGS2009

User's Guide to the Weighted-Multiple-Linear Regression Program (WREG version 1.0)

Streamflow is not measured at every location in a stream network. Yet hydrologists, State and local agencies, and the general public still seek to know streamflow characteristics, such as mean annual flow or flood flows with different exceedance probabilities, at ungaged basins. The goals of this guide are to introduce and familiarize the user with the weighted multiple-linear regression (WREG) program, and to also provide the theoretical background for program features. The program is intended to be used to develop a regional estimation equation for streamflow characteristics that can be applied at an ungaged basin, or to improve the corresponding estimate at continuous-record streamflow gages with short records. The regional estimation equation results from a multiple-linear regression that relates the observable basin characteristics, such as drainage area, to streamflow characteristics.

Techniques and Methods↗

USGS2008

Low-flow characteristics and regionalization of low-flow characteristics for selected streams in Arkansas

Water use in Arkansas has increased dramatically in recent years. Since 1990, the use of water for all purposes except power generation has increased 53 percent (4,004 cubic feet per second in 1990 to 6,113 cubic feet per second in 2005). The biggest users are agriculture (90 percent), municipal water supply (4 percent) and industrial supply (2 percent). As the population of the State continues to grow, so does the demand for the State’s water resources. The low-flow characteristics of a stream ultimately affect its utilization by humans. Specific information on the low-flow characteristics of streams is essential to State water-management agencies such as the Arkansas Department of Environmental Quality, the Arkansas Natural Resources Commission, and the Arkansas Game and Fish Commission when dealing with problems related to irrigation, municipal and industrial water supplies, fish and wildlife conservation, and dilution of waste. Low-flow frequency data are of particular value to management agencies responsible for the development and management of the State’s water resources. This report contains the low-flow characteristics for 70 active continuous-streamflow record gaging stations, 59 inactive continuous-streamflow record stations, and 101 partial-record gaging stations. These characteristics are the annual 7-day, 10-year low flow and the annual 7-day, 2-year low flow, and the seasonal, bimonthly, and monthly 7-day, 10-year low flow for the 129 active and inactive continuous-streamflow record and 101 partial-record gaging stations. Low-flow characteristics were computed on the basis of streamflow data for the period of record through September 2005 for the continuous-streamflow record and partial-record streamflow gaging stations. The low-flow characteristics of these continuous- and partial-record streamflow gaging stations were utilized in a regional regression analysis to produce equations for estimating the annual, seasonal, bimonthly, and monthly (November through April) 7-day, 10-year low flows and the annual 7-day, 2-year low flow for ungaged streams in the western two-thirds of Arkansas.

Arkansas↗

USGS2007

Relating low‐flow characteristics to the base flow recession time constant at partial record stream gauges

Base flow recession information is helpful for regional estimation of low‐flow characteristics. However, analyses that exploit such information generally require a continuous record of streamflow at the estimation site to characterize base flow recession. Here we propose a simple method for characterizing base flow recession at low‐flow partial record stream gauges (i.e., sites with very few streamflow measurements under low‐streamflow conditions), and we use that characterization as the basis for a practical new approach to low‐flow regression. In a case study the introduction of a base flow recession time constant, estimated from a single pair of strategically timed streamflow measurements, approximately halves the root‐mean‐square estimation error relative to that of a conventional drainage area regression. Additional streamflow measurements can be used to reduce the error further.

Water Resources Research↗

USGS2005

An analysis of region-of-influence methods for flood regionalization in the Gulf-Atlantic Rolling Plains

Region-of-influence (RoI) approaches for estimating stream flow characteristics at ungaged sites were applied and evaluated in a case study of the 50-year peak discharge in the Gulf-Atlantic Rolling Plains of the southeastern United States. Linear regression against basin characteristics was performed for each ungaged site considered based on data from a region of influence containing the n closest gages in predictor variable (PRoI) or geographic (GRoI) space. Augmentation of this count based cutoff by a distance based cutoff also was considered. Prediction errors were evaluated for an independent (split-sampled) dataset. For the dataset and metrics considered here: (1) for either PRoI or GRoI, optimal results were found when the simpler count based cutoff, rather than the distance augmented cutoff, was used; (2) GRoI produced lower error than PRoI when applied indiscriminately over the entire study region; (3) PRoI performance improved considerably when Rol was restricted to predefined geographic subregions.

Journal of the American Water Resources Associatio↗