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Jeremy K. Newson

Publications and source records attributed to Jeremy K. Newson.

6 recordsLinked to original sources
USGS2017

StreamStats, version 4

Introduction StreamStats version 4, available at https://streamstats.usgs.gov , is a map-based web application that provides an assortment of analytical tools that are useful for water-resources planning and management, and engineering purposes. Developed by the U.S. Geological Survey (USGS), the primary purpose of StreamStats is to provide estimates of streamflow statistics for user-selected ungaged sites on streams and for USGS streamgages, which are locations where streamflow data are collected. Streamflow statistics, such as the 1-percent flood, the mean flow, and the 7-day 10-year low flow, are used by engineers, land managers, biologists, and many others to help guide decisions in their everyday work. For example, estimates of the 1-percent flood (which is exceeded, on average, once in 100 years and has a 1-percent chance of exceedance in any year) are used to create flood-plain maps that form the basis for setting insurance rates and land-use zoning. This and other streamflow statistics also are used for dam, bridge, and culvert design; water-supply planning and management; permitting of water withdrawals and wastewater and industrial discharges; hydropower facility design and regulation; and setting of minimum allowed streamflows to protect freshwater ecosystems. Streamflow statistics can be computed from available data at USGS streamgages depending on the type of data collected at the stations. Most often, however, streamflow statistics are needed at ungaged sites, where no streamflow data are available to determine the statistics.

Fact Sheet↗
USGS2013

Significance of exchanging SSURGO and STATSGO data when modeling hydrology in diverse physiographic terranes

The Water Availability Tool for Environmental Resources (WATER) is a TOPMODEL-based hydrologic model that depends on spatially accurate soils data to function in diverse terranes. In Kentucky, this includes mountainous regions, karstic plateau, and alluvial plains. Soils data are critical because they quantify the space to store water, as well as how water moves through the soil to the stream during storm events. We compared how the model performs using two different sources of soils data--Soil Survey Geographic Database (SSURGO) and State Soil Geographic Database laboratory data (STATSGO)--for 21 basins ranging in size from 17 to 1564 km 2 . Model results were consistently better when SSURGO data were used, likely due to the higher field capacity, porosity, and available-water holding capacity, which cause the model to store more soil-water in the landscape and improve streamflow estimates for both low- and high-flow conditions. In addition, there were significant differences in the conductivity multiplier and scaling parameter values that describe how water moves vertically and laterally, respectively, as quantified by TOPMODEL. We also evaluated whether partitioning areas that drain to streams via sinkholes in karstic basins as separate hydrologic modeling units (HMUs) improved model performance. There were significant differences between HMUs in properties that control soil-water storage in the model, although the effect of partitioning these HMUs on streamflow simulation was inconclusive.

Kentucky↗
USGS2012

Phase II modification of the W ater A vailability T ool for E nvironmental R esources (WATER) for Kentucky: The sinkhole-drainage process, point-and-click basin delineation, and results of karst test-basin simulations

This report describes Phase II modifications made to the Water Availability Tool for Environmental Resources (WATER), which applies the process-based TOPMODEL approach to simulate or predict stream discharge in surface basins in the Commonwealth of Kentucky. The previous (Phase I) version of WATER did not provide a means of identifying sinkhole catchments or accounting for the effects of karst (internal) drainage in a TOPMODEL-simulated basin. In the Phase II version of WATER, sinkhole catchments are automatically identified and delineated as internally drained subbasins, and a modified TOPMODEL approach (called the sinkhole drainage process, or SDP-TOPMODEL) is applied that calculates mean daily discharges for the basin based on summed area-weighted contributions from sinkhole drain-age (SD) areas and non-karstic topographically drained (TD) areas. Results obtained using the SDP-TOPMODEL approach were evaluated for 12 karst test basins located in each of the major karst terrains in Kentucky. Visual comparison of simulated hydrographs and flow-duration curves, along with statistical measures applied to the simulated discharge data (bias, correlation, root mean square error, and Nash-Sutcliffe efficiency coefficients), indicate that the SDPOPMODEL approach provides acceptably accurate estimates of discharge for most flow conditions and typically provides more accurate simulation of stream discharge in karstic basins compared to the standard TOPMODEL approach. Additional programming modifications made to the Phase II version of WATER included implementation of a point-and-click graphical user interface (GUI), which fully automates the delineation of simulation-basin boundaries and improves the speed of input-data processing. The Phase II version of WATER enables the user to select a pour point anywhere on a stream reach of interest, and the program will automatically delineate all upstream areas that contribute drainage to that point. This capability enables automatic delineation of a simulation basin of any size (area) and having any level of stream-network complexity. WATER then automatically identifies the presence of sinkholes catchments within the simulation basin boundaries; extracts and compiles the necessary climatic, topographic, and basin characteristics datasets; and runs the SDP-TOPMODEL approach to estimate daily mean discharges (streamflow).

Kentucky↗
USGS2012

Construction of estimated flow- and load-duration curves for Kentucky using the W ater A vailability T ool for E nvironmental R esources (WATER)

Flow- and load-duration curves were constructed from the model outputs of the U.S. Geological Survey's Water Availability Tool for Environmental Resources (WATER) application for streams in Kentucky. The WATER application was designed to access multiple geospatial datasets to generate more than 60 years of statistically based streamflow data for Kentucky. The WATER application enables a user to graphically select a site on a stream and generate an estimated hydrograph and flow-duration curve for the watershed upstream of that point. The flow-duration curves are constructed by calculating the exceedance probability of the modeled daily streamflows. User-defined water-quality criteria and (or) sampling results can be loaded into the WATER application to construct load-duration curves that are based on the modeled streamflow results. Estimates of flow and streamflow statistics were derived from TOPographically Based Hydrological MODEL (TOPMODEL) simulations in the WATER application. A modified TOPMODEL code, SDP-TOPMODEL (Sinkhole Drainage Process-TOPMODEL) was used to simulate daily mean discharges over the period of record for 5 karst and 5 non-karst watersheds in Kentucky in order to verify the calibrated model. A statistical evaluation of the model's verification simulations show that calibration criteria, established by previous WATER application reports, were met thus insuring the model's ability to provide acceptably accurate estimates of discharge at gaged and ungaged sites throughout Kentucky. Flow-duration curves are constructed in the WATER application by calculating the exceedence probability of the modeled daily flow values. The flow-duration intervals are expressed as a percentage, with zero corresponding to the highest stream discharge in the streamflow record. Load-duration curves are constructed by applying the loading equation (Load = Flow*Water-quality criterion) at each flow interval.

Kentucky↗
USGS2011

Source-water susceptibility assessment in Texas—Approach and methodology

Public water systems provide potable water for the public's use. The Safe Drinking Water Act amendments of 1996 required States to prepare a source-water susceptibility assessment (SWSA) for each public water system (PWS). States were required to determine the source of water for each PWS, the origin of any contaminant of concern (COC) monitored or to be monitored, and the susceptibility of the public water system to COC exposure, to protect public water supplies from contamination. In Texas, the Texas Commission on Environmental Quality (TCEQ) was responsible for preparing SWSAs for the more than 6,000 public water systems, representing more than 18,000 surface-water intakes or groundwater wells. The U.S. Geological Survey (USGS) worked in cooperation with TCEQ to develop the Source Water Assessment Program (SWAP) approach and methodology. Texas' SWAP meets all requirements of the Safe Drinking Water Act and ultimately provides the TCEQ with a comprehensive tool for protection of public water systems from contamination by up to 247 individual COCs. TCEQ staff identified both the list of contaminants to be assessed and contaminant threshold values (THR) to be applied. COCs were chosen because they were regulated contaminants, were expected to become regulated contaminants in the near future, or were unregulated but thought to represent long-term health concerns. THRs were based on maximum contaminant levels from U.S. Environmental Protection Agency (EPA)'s National Primary Drinking Water Regulations. For reporting purposes, COCs were grouped into seven contaminant groups: inorganic compounds, volatile organic compounds, synthetic organic compounds, radiochemicals, disinfection byproducts, microbial organisms, and physical properties. Expanding on the TCEQ's definition of susceptibility, subject-matter expert working groups formulated the SWSA approach based on assumptions that natural processes and human activities contribute COCs in quantities that vary in space and time; that increased levels of COC-producing activities within a source area may increase susceptibility to COC exposure; and that natural and manmade conditions within the source area may increase, decrease, or have no observable effect on susceptibility to COC exposure. Incorporating these assumptions, eight SWSA components were defined: identification, delineation, intrinsic susceptibility, point- and nonpoint-source susceptibility, contaminant occurrence, area-of-primary influence, and summary components. Spatial datasets were prepared to represent approximately 170 attributes or indicators used in the assessment process. These primarily were static datasets (approximately 46 gigabytes (GB) in size). Selected datasets such as PWS surface-water-intake or groundwater-well locations and potential source of contamination (PSOC) locations were updated weekly. Completed assessments were archived, and that database is approximately 10 GB in size. SWSA components currently (2011) are implemented in the Source Water Assessment Program-Decision Support System (SWAP-DSS) computer software, specifically developed to produce SWSAs. On execution of the software, the components work to identify the source of water for the well or intake, assess intrinsic susceptibility of the water- supply source, assess susceptibility to contamination with COCs from point and nonpoint sources, identify any previous detections of COCs from existing water-quality databases, and summarize the results. Each water-supply source's susceptibility is assessed, source results are weighted by source capacity (when a PWS has multiple sources), and results are combined into a single SWSA for the PWS.'SWSA reports are generated using the software; during 2003, more than 6,000 reports were provided to PWS operators and the public. The ability to produce detailed or summary reports for individual sources, and detailed or summary reports for a PWS, by COC or COC group was a unique capability of SWAP-DSS. In 2004, the TCEQ began a rotating schedule for SWSA wherein one-third of PWSs statewide would be assessed annually, or sooner if protection-program activities deemed it necessary, and that schedule has continued to the present. Cooperative efforts by the TCEQ and the USGS for SWAP software maintenance and enhancements ended in 2011 with the TCEQ assuming responsibility for all tasks.

Texas↗
USGS2009

The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion

The Water Availability Tool for Environmental Resources (WATER) was developed in cooperation with the Kentucky Division of Water to provide a consistent and defensible method of estimating streamflow and water availability in ungaged basins. WATER is process oriented; it is based on the TOPMODEL code and incorporates historical water-use data together with physiographic data that quantitatively describe topography and soil-water storage. The result is a user-friendly decision tool that can estimate water availability in non-karst areas of Kentucky without additional data or processing. The model runs on a daily time step, and critical source data include a historical record of daily temperature and precipitation, digital elevation models (DEMs), the Soil Survey Geographic Database (SSURGO), and historical records of water discharges and withdrawals. The model was calibrated and statistically evaluated for 12 basins by comparing the estimated discharge to that observed at U.S. Geological Survey streamflow-gaging stations. When statistically evaluated over a 2,119-day time period, the discharge estimates showed a bias of -0.29 to 0.42, a root mean square error of 1.66 to 5.06, a correlation of 0.54 to 0.85, and a Nash-Sutcliffe Efficiency of 0.26 to 0.72. The parameter and input modifications that most significantly improved the accuracy and precision of streamflow-discharge estimates were the addition of Next Generation radar (NEXRAD) precipitation data, a rooting depth of 30 centimeters, and a TOPMODEL scaling parameter (m) derived directly from SSURGO data that was multiplied by an adjustment factor of 0.10. No site-specific optimization was used.

Kentucky↗