DOCSLIB.ORG

Appendix A: Streamflow Estimation Techniques

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Appendix A: Streamflow Estimation Techniques TMDLs for the White Oak Creek Watershed Appendix A: Streamflow Estimation Techniques Final Report TMDLs for the White Oak Creek Watershed Contents A-1 Introduction .................................................................................................................................. A-2 A-2 Drainage Area Weighting ............................................................................................................ A-3 A-2.1. Data ..................................................................................................................................... A-3 A-2.2. Analysis ............................................................................................................................... A-4 A-3 Linear Regression ........................................................................................................................ A-7 A-3.1. Data Preprocessing .............................................................................................................. A-7 A-3.2. Developing a Linear Regression ......................................................................................... A-7 A-3.3. Testing the Final Linear Regression .................................................................................. A-11 A-4 ILSAM ....................................................................................................................................... A-15 A-4.1. Little Wabash River .......................................................................................................... A-15 A-4.2. Equation Parameters for White Oak Creek ....................................................................... A-15 A-4.3. Analysis ............................................................................................................................. A-19 A-5 Summary .................................................................................................................................... A-26 A-6 References .................................................................................................................................. A-27 Figures Figure A-1. Station locations .................................................................................................................... A-4 Figure A-2. Predicted versus observed data at stations 300057 and X02W06 ......................................... A-6 Figure A-3. Linear regression of discharge data. ...................................................................................... A-8 Figure A-4. Linear regression of standardized discharge data. ................................................................. A-9 Figure A-5. Linear regression of standardized instantaneous discharge data. ........................................ A-11 Figure A-6. Accuracy testing of the linear regression. ........................................................................... A-13 Figure A-7. Linear regression estimation error. ...................................................................................... A-14 Figure A-8. SSURGO representative hydraulic conductivity at saturation at maximum depth. ............ A-17 Figure A-9. SSURGO maximum hydraulic conductivity at saturation at maximum depth.................... A-18 Figure A-10. ILSAM at USGS gage. ...................................................................................................... A-19 Figure A-11. ILSAM flow-duration curve for station 300057. .............................................................. A-21 Figure A-12. ILSAM flow-duration curve for station X02W06. ............................................................ A-22 Figure A-13. ILSAM flow-duration curve for station X02W05. ............................................................ A-23 Figure A-14. ILSAM flow-duration curve for station X02K17. ............................................................. A-24 Figure A-15. ILSAM flow-duration curve for station X02K15. ............................................................. A-25 Tables Table A-1. Ohio EPA sample stations with instantaneous discharge data. ............................................... A-3 Table A-2. Drainage area ratio method prediction for station 300057. .................................................... A-5 Table A-3. Drainage area ratio method prediction for station X02W06. .................................................. A-5 Table A-4. Standardized log data for the final linear regression. ........................................................... A-10 Table A-5. Estimating instantaneous discharge with the linear regression. ............................................ A-12 Table A-6. ILSAM estimation accuracy at gage 03238500. ................................................................... A-20 Table A-7. ILSAM estimation accuracy at station 300057. .................................................................... A-20 Table A-8. ILSAM estimation accuracy at station X02W06. ................................................................. A-21 Final Report A-1 TMDLs for the White Oak Creek Watershed A-1 Introduction Flow data are not available for the listed section 303(d) segments; although, there is one active USGS gage in the watershed. Thus, a streamflow estimation technique is necessary to create flow duration curves at the assessment points for each impaired waterbody. Additionally, streamflow estimates are also needed as part of the data assessment process using a duration curve framework. Three streamflow estimation techniques were analyzed for this report: drainage area weighting, linear regression, and ILSAM. The results showed that only the ILSAM method yielded acceptable results. Final Report A-2 TMDLs for the White Oak Creek Watershed A-2 Drainage Area Weighting Drainage area weighting is a widely used technique in many cases where limited streamflow monitoring data are available. This method is most valid in situations where watersheds are of similar size, land use, soil types, and experience similar precipitation patterns. Discharge is estimated by drainage area weighting using the following equation: Aungaged Qungaged Qgaged Agaged where Qungaged: Flow at the ungaged location Qgaged: Flow at surrogate USGS gage station Aungaged: Drainage area of the ungaged location Agaged: Drainage area at surrogate USGS gage station A-2.1. Data The accuracy of this method was tested using the instantaneous discharge data collected by Ohio EPA at stations X02W06 and 300057 (Figure A-1) during the summer of 2006. The drainage areas of the two stations are 29.7 and 53.6 square miles (mi2), respectively (Table A-1). Table A-1. Ohio EPA sample stations with instantaneous discharge data Number of River mile Drainage area discharge Station ID Station name Stream name (miles) (mile2) samples @ CR-24B North Fork 300057 1.48 53.6 10 (Tri-County Hwy) White Oak Creek @ Sterling Road at X02W06 Sterling Run 0.59 29.7 12 South Ford Final Report A-3 TMDLs for the White Oak Creek Watershed Figure A-1. Station locations. USGS operates a gage on White Oak Creek (03238500) near Georgetown (Figure A-1). The gage has a drainage area of 218 square miles and a period of record of October 1923 to November 1935 and October 1939 to present. Mean daily discharges were downloaded from the National Water Information System (USGS 2008b). Hourly data at this gage were downloaded from Instantaneous Discharge Archive (USGS 2008a). Hourly data for 03238500 were not available on August 7, 2006, August 9, 2006, and September 8, 2006, because the gage was not operating properly (Koltun, hydrologist, USGS, email correspondance, June 2008). Mean daily discharges for these dates are available and were used as surrogates for the instantaneous data to be paired with the Ohio EPA data. A-2.2. Analysis For rural, unregulated streams in Ohio, it is recommended that the drainage area ratio method be applied only if the drainage area of the ungaged site is between 50 and 150 percent of the gaged site (Koltun and Whitehead 2002; Koltun 2003). Both stations have a drainage area of less than 50 percent of USGS gage 03238500 (White Oak Creek near Georgetown OH). Final Report A-4 TMDLs for the White Oak Creek Watershed The observed discharges at station 300057 ranged from 0.164 to 26.606 cubic feet per second (cfs) with an average of 5.714 cfs. The predicted discharges at station 300057, using the drainage area ratio method, ranged from 0.8 to 34.4 cfs with an average of 7.6 cfs. The percent error (observed minus expected, quantity divided by observed) ranged from -859 percent to 8 percent with an average error of -262 percent. The largest percent errors are for low-flow predictions. The data are displayed in Table A-2. Table A-2. Drainage area ratio method prediction for station 300057 Observed Estimated Station Gage Station Station Station discharge Gage discharge discharge % date time (cfs) date and time (cfs) (cfs) Error 4/10/06 1:30 PM 26.606 4/10/06 13:00 140 34.42 29% 5/18/06 10:20 AM 8.69 5/18/06 10:00 46 11.31 30% 7/18/06 2:42 PM 1.3884 7/18/06 15:00 12 2.95 113% 7/27/06 10:20 AM 0.497 7/27/06 10:00 10 2.46 395% 8/3/06 9:45 AM 0.415 8/3/06 10:00 6.9 1.70 309% 8/7/06 1:05 PM 0.1639 8/7/06 0:00 3.4 0.84 410% 8/31/06 9:00 AM 0.282 8/31/06 9:00 11 2.70 859% 9/8/06 11:11 AM 0.1795 9/8/06 0:00 3.3 0.81 352% 9/20/06 2:45 PM 1.273 9/20/06 15:00 12 2.95 132% 12/14/06 1:30 PM 17.647 12/10/06 14:00 66 16.23 -8% The observed discharges at station X02W06 ranged from 0.218 to 14.094 cfs with an average of 3.175
Load more

Recommended publications
  • Analysis of Streamflow Variability and Trends in the Meta River, Colombia
    water Article Analysis of Streamflow Variability and Trends in the Meta River, Colombia Marco Arrieta-Castro 1, Adriana Donado-Rodríguez 1, Guillermo J. Acuña 2,3,* , Fausto A. Canales 1,* , Ramesh S. V. Teegavarapu 4 and Bartosz Ka´zmierczak 5 1 Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, Barranquilla 080002, Atlántico, Colombia; [email protected] (M.A.-C.); [email protected] (A.D.-R.) 2 Department of Civil and Environmental Engineering, Instituto de Estudios Hidráulicos y Ambientales, Universidad del Norte, Km.5 Vía Puerto Colombia, Barranquilla 081007, Colombia 3 Programa de Ingeniería Ambiental, Universidad Sergio Arboleda, Escuela de Ciencias Exactas e Ingeniería (ECEI), Calle 74 #14-14, Bogotá D.C. 110221, Colombia 4 Department of Civil, Environmental and Geomatics Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA; [email protected] 5 Department of Water Supply and Sewerage Systems, Faculty of Environmental Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland; [email protected] * Correspondence: [email protected] (F.A.C.); [email protected] (G.J.A.); Tel.: +57-5-3362252 (F.A.C.) Received: 29 March 2020; Accepted: 13 May 2020; Published: 20 May 2020 Abstract: The aim of this research is the detection and analysis of existing trends in the Meta River, Colombia, based on the streamflow records from seven gauging stations in its main course, for the period between June 1983 to July 2019. The Meta River is one of the principal branches of the Orinoco River, and it has a high environmental and economic value for this South American country.
    [Show full text]
  • Stream Discharge (Streamflow)
    The Importance of Streamflow in California’s Southern Sierra Nevada Mountains Kings River Experimental Watersheds Because 55 to 65 percent of California’s developed water comes from small streams in the Sierra Nevada, it is important to under- stand the role the snowpack has in the distribution and quantity of stream discharge (streamflow). In the southern Sierra, more than 80 percent of precipitation falls December through April. However, owing to the delay in snowmelt, there is a lag in runoff until the spring. At higher elevation sites, the spring melt does not peak until May or even June. This makes mountain water available to California during the summer months. The Kings River Experi- mental Watersheds (KREW) sites demonstrate that precipitation in the form of snow generates greater yearly discharge in a given watershed. The difference in discharge between the KREW Provi- dence site and Bull site is as much as 20 percent per year. C. Hunsaker Research Area Figure 1—KREW’s double flume system. The large flume KREW is a watershed-level, integrated ecosystem project for (background) accurately captures high flows, and the small flume headwater streams in the Sierra Nevada. Eight watersheds at two is successful at measuring lower base flows. study sites are fully instrumented to monitor ecosystem changes. Stream discharge data, just one component of the project, have been collected since 2002 from the Providence site and since 2003 from the Bull site. What is Stream Discharge? Discharge is the amount of water leaving each watershed within the stream channel. It is represented as a rate of flow such as cubic feet per second (cfs), gallons per minute (gpm), or acre-feet per year.
    [Show full text]
  • From the River to You: USGS Real-Time Streamflow Information …From the National Streamflow Information Program
    From the River to You: USGS Real-Time Streamflow Information …from the National Streamflow Information Program This Fact Sheet is one in a series that highlights information or recent research findings from the USGS National Streamflow Information Program (NSIP). The investigations and scientific results reported in this series require a nationally consistent streamgaging network with stable long-term monitoring sites and a rigorous program of data, quality assurance, management, archiving, and synthesis. NSIP produces multipurpose, unbiased surface-water information that is readily accessible to all. Introduction Collecting and Transmitting data are stored in a data logger in Streamflow Information the gagehouse. As part of the National Stream- On a preset schedule, typically flow Information Program, the U.S. The streamflow information every 1 to 4 hours, the streamgage Geological Survey (USGS) operates collected at most streamgages transmits all the stage information more than 7,400 streamgages nation- is stream stage (also called gage recorded since the last transmission to wide to provide streamflow informa- height). This is the height of the a Geostationary Operational Envi- tion for a wide variety of uses. These water surface above a reference level ronmental Satellite (GOES). Many uses include prediction of floods, or datum. Stream stage is measured streamgages have predetermined management and allocation of water by a variety of methods including stage thresholds. When these thresh- resources, design and operation of floats, pressure transducers, and olds are exceeded, the time between engineering structures, scientific acoustic or optical sensors (fig. 1). transmissions to the satellite will research, operation of locks and Stage data are measured at the decrease from 1 to 4 hours to every dams, and for recreational safety and time interval necessary to monitor the 15 minutes to provide more timely enjoyment.
    [Show full text]
  • Distributed Hydrologic Modeling for Streamflow Prediction at Ungauged Basins
    Utah State University DigitalCommons@USU All Graduate Theses and Dissertations Graduate Studies 5-2008 Distributed Hydrologic Modeling For Streamflow Prediction At Ungauged Basins Christina Bandaragoda Utah State University Follow this and additional works at: https://digitalcommons.usu.edu/etd Part of the Civil and Environmental Engineering Commons Recommended Citation Bandaragoda, Christina, "Distributed Hydrologic Modeling For Streamflow Prediction At Ungauged Basins" (2008). All Graduate Theses and Dissertations. 62. https://digitalcommons.usu.edu/etd/62 This Dissertation is brought to you for free and open access by the Graduate Studies at DigitalCommons@USU. It has been accepted for inclusion in All Graduate Theses and Dissertations by an authorized administrator of DigitalCommons@USU. For more information, please contact [email protected]. DISTRIBUTED HYDROLOGIC MODELING FOR STREAMFLOW PREDICTION AT UNGAUGED BASINS by Christina Bandaragoda A dissertation submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY in Civil and Environmental Engineering UTAH STATE UNIVERSITY Logan, UT 2007 ii ABSTRACT Distributed Hydrologic Modeling for Prediction of Streamflow at Ungauged Basins by Christina Bandaragoda, Doctor of Philosophy Utah State University, 2008 Major Professor: Dr. David G. Tarboton Department: Civil and Environmental Engineering Hydrologic modeling and streamflow prediction of ungauged basins is an unsolved scientific problem as well as a policy-relevant science theme emerging as a major
    [Show full text]
  • Introduction and Characteristics of Flow
    Introduction and Characteristics of Flow By James W. LaBaugh and Donald O. Rosenberry Chapter 1 of Field Techniques for Estimating Water Fluxes Between Surface Water and Ground Water Edited by Donald O. Rosenberry and James W. LaBaugh Techniques and Methods Chapter 4–D2 U.S. Department of the Interior U.S. Geological Survey Contents Introduction.....................................................................................................................................................5 Purpose and Scope .......................................................................................................................................6 Characteristics of Water Exchange Between Surface Water and Ground Water .............................7 Characteristics of Near-Shore Sediments .......................................................................................8 Temporal and Spatial Variability of Flow .........................................................................................10 Defining the Purpose for Measuring the Exchange of Water Between Surface Water and Ground Water ..........................................................................................................................12 Determining Locations of Water Exchange ....................................................................................12 Measuring Direction of Flow ............................................................................................................15 Measuring the Quantity of Flow .......................................................................................................15
    [Show full text]
  • Chapter 5 Streamflow Data
    Part 630 Hydrology National Engineering Handbook Chapter 5 Streamflow Data (210–VI–NEH, Amend. 76, November 2015) Chapter 5 Streamflow Data Part 630 National Engineering Handbook Issued November 2015 The U.S. Department of Agriculture (USDA) prohibits discrimination against its customers, em- ployees, and applicants for employment on the bases of race, color, national origin, age, disabil- ity, sex, gender identity, religion, reprisal, and where applicable, political beliefs, marital status, familial or parental status, sexual orientation, or all or part of an individual’s income is derived from any public assistance program, or protected genetic information in employment or in any program or activity conducted or funded by the Department. (Not all prohibited bases will apply to all programs and/or employment activities.) If you wish to file a Civil Rights program complaint of discrimination, complete the USDA Pro- gram Discrimination Complaint Form (PDF), found online at http://www.ascr.usda.gov/com- plaint_filing_cust.html, or at any USDA office, or call (866) 632-9992 to request the form. You may also write a letter containing all of the information requested in the form. Send your completed complaint form or letter to us by mail at U.S. Department of Agriculture, Director, Office of Adju- dication, 1400 Independence Avenue, S.W., Washington, D.C. 20250-9410, by fax (202) 690-7442 or email at [email protected] Individuals who are deaf, hard of hearing or have speech disabilities and you wish to file either an EEO or program complaint please contact USDA through the Federal Relay Service at (800) 877- 8339 or (800) 845-6136 (in Spanish).
    [Show full text]
  • Beyond Binary Baseflow Separation: a Delayed-Flow Index for Multiple Streamflow Contributions
    Hydrol. Earth Syst. Sci., 24, 849–867, 2020 https://doi.org/10.5194/hess-24-849-2020 © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. Beyond binary baseflow separation: a delayed-flow index for multiple streamflow contributions Michael Stoelzle1,*, Tobias Schuetz2, Markus Weiler1, Kerstin Stahl1, and Lena M. Tallaksen3 1Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany 2Department of Hydrology, Faculty VI Regional and Environmental Sciences, University of Trier, Trier, Germany 3Department of Geosciences, University of Oslo, Oslo, Norway *Invited contribution by Michael Stoelzle, recipient of the EGU Outstanding Student Poster Awards 2015. Correspondence: Michael Stoelzle ([email protected]) Received: 14 May 2019 – Discussion started: 28 May 2019 Revised: 18 November 2019 – Accepted: 20 January 2020 – Published: 25 February 2020 Abstract. Understanding components of the total streamflow the primary contribution, whereas below 800 m groundwa- is important to assess the ecological functioning of rivers. Bi- ter resources are most likely the major streamflow contri- nary or two-component separation of streamflow into a quick butions. Our analysis also indicates that dynamic storage in and a slow (often referred to as baseflow) component are of- high alpine catchments might be large and is overall not ten based on arbitrary choices of separation parameters and smaller than in lowland catchments. We conclude that the also merge different delayed components into one baseflow DFI can be used to assess the range of sources forming catch- component and one baseflow index (BFI). As streamflow ments’ storages and to judge the long-term sustainability of generation during dry weather often results from drainage streamflow.
    [Show full text]
  • What Is Flow Alteration?
    Flow Alteration What is Flow Alteration? Flow alteration is any change in the natural flow regime of a river or stream or water level of a lake or reservoir induced by human activities. As illustrated below, five components of the natural flow regime are now recognized as requiring protection to maintain healthy river and lake ecosystems (Figure 1). They are: Magnitude – the amount of water flowing in the stream at any given time; Frequency – how often a given flow occurs over time; Duration – the length of time that a given flow occurs; Timing – how predictable or regular a given flow can be expected to occur; Rate of change – how quickly flows rise or fall. Figure 1: Hydrographs of a river (A) and lake (B) that illustrate the general seasonal pattern and the variability seen in Vermont rivers and lakes, with increased streamflow and water level in the spring followed by receding levels in the summer and an increase in streamflow and water level in the fall. A natural flow regime refers to a range that each of these five components can be expected to fall within due to the variability of precipitation and other natural hydrologic processes. Significant flow alteration can push these components of flow outside the expected range, leading to environmental degradation. Climate change is another potential driver of shifting flow regimes, and must also be considered in a well- informed approach to addressing flow alteration. These same five components influence lake water level and changes from the natural condition in one or more of these components affect the health of lake ecosystems.
    [Show full text]
  • A Computer Program for Streamflow Hydrograph Separation and Analysis
    HYSEP: A COMPUTER PROGRAM FOR STREAMFLOW HYDROGRAPH SEPARATION AND ANALYSIS U.S. GEOLOGICAL SURVEY Water-Resources Investigations Report 96-4040 HYSEP: A COMPUTER PROGRAM FOR STREAMFLOW HYDROGRAPH SEPARATION AND ANALYSIS by Ronald A. Sloto and Michèle Y. Crouse U.S. GEOLOGICAL SURVEY Water-Resources Investigations Report 96-4040 Lemoyne, Pennsylvania 1996 U.S. DEPARTMENT OF THE INTERIOR BRUCE BABBITT, Secretary U.S. GEOLOGICAL SURVEY Gordon P. Eaton, Director The use of firm, trade, and brand names in this report is for identification purposes only and does not constitute endorsement by the U.S. Geological Survey. For additional information Copies of this report may be write to: purchased from: District Chief U.S. Geological Survey U.S. Geological Survey Branch of Information Services 840 Market Street Box 25286 Lemoyne, Pennsylvania 17043-1586 Denver, Colorado 80225-0286 ii CONTENTS Page Abstract . .1 Introduction . .1 Purpose and scope . .2 Limitations and cautions. .2 Hydrograph-separation methods . .3 Fixed-interval method . .5 Sliding-interval method . .6 Local-minimum method . .7 Program input requirements . .8 Program output . .9 Hydrograph separation. .9 Cumulative annual base-flow distribution . .9 Flow duration . 11 Seasonal flow distribution . 12 Daily-values files . 12 How HYSEP works. 13 User interface . 13 Commands . 13 Data panel . 15 Assistance panel. 16 Instruction panel . 16 Special files . 16 System defaults—TERM.DAT. 16 Session record—HYSEP.LOG . 17 Error and warning messages—ERROR.FIL . 17 Program options . 17 Default settings . 18 Specifying input files. 20 Selecting WDM file data sets. 20 Add . 20 Browse . 21 Find . 23 Selecting program output . 24 Tables. 24 Data files.
    [Show full text]
  • Hydrological Measurements
    Water Quality Monitoring - A Practical Guide to the Design and Implementation of Freshwater Quality Studies and Monitoring Programmes Edited by Jamie Bartram and Richard Ballance Published on behalf of United Nations Environment Programme and the World Health Organization © 1996 UNEP/WHO ISBN 0 419 22320 7 (Hbk) 0 419 21730 4 (Pbk) Chapter 12 - HYDROLOGICAL MEASUREMENTS This chapter was prepared by E. Kuusisto. Hydrological measurements are essential for the interpretation of water quality data and for water resource management. Variations in hydrological conditions have important effects on water quality. In rivers, such factors as the discharge (volume of water passing through a cross-section of the river in a unit of time), the velocity of flow, turbulence and depth will influence water quality. For example, the water in a stream that is in flood and experiencing extreme turbulence is likely to be of poorer quality than when the stream is flowing under quiescent conditions. This is clearly illustrated by the example of the hysteresis effect in river suspended sediments during storm events (see Figure 13.2). Discharge estimates are also essential when calculating pollutant fluxes, such as where rivers cross international boundaries or enter the sea. In lakes, the residence time (see section 2.1.1), depth and stratification are the main factors influencing water quality. A deep lake with a long residence time and a stratified water column is more likely to have anoxic conditions at the bottom than will a small lake with a short residence time and an unstratified water column. It is important that personnel engaged in hydrological or water quality measurements are familiar, in general terms, with the principles and techniques employed by each other.
    [Show full text]
  • Streamflow Measurement and Analysis
    BLBS113-c06 BLBS113-Brooks Trim: 244mm×172mm August 25, 2012 17:2 CHAPTER 6 Streamflow Measurement and Analysis INTRODUCTION Streamflow is the primary mechanism by which water moves from upland watersheds to ocean basins. Streamflow is the principal source of water for municipal water supplies, ir- rigated agricultural production, industrial operations, and recreation. Sediments, nutrients, heavy metals, and other pollutants are also transported downstream in streamflow. Flooding occurs when streamflow discharge exceeds the capacity of the channel. Therefore, stream- flow measurements or methods for predicting streamflow characteristics are needed for various purposes. This chapter discusses the measurement of streamflow, methods and mod- els used for estimating streamflow characteristics, and methods of streamflow-frequency analysis. MEASUREMENT OF STREAMFLOW Streamflow discharge, the quantity of flow per unit of time, is perhaps the most important hydrologic information needed by a hydrologist and watershed manager. Peak-flow data are needed in planning for flood control and designing engineering structures including bridges and road culverts. Streamflow data during low-flow periods are required to estimate the dependability of water supplies and for assessing water quality conditions for aquatic organisms (see Chapter 11). Total streamflow and its variation must be known for design purposes such as downstream reservoir storage. The stage or height of water in a stream channel can be measured with a staff gauge or water-level recorder at some location on a stream reach. The problem then becomes converting a measurement of the stage of a stream to discharge of the stream. This problem Hydrology and the Management of Watersheds, Fourth Edition. Kenneth N.
    [Show full text]
  • High Flow Management Objectives for New Jersey Non-Coastal Waters
    HIGH FLOW MANAGEMENT OBJECTIVES FOR NEW JERSEY NON-COASTAL WATERS A Study of the Delaware, Saddle, Whippany, and Musconetcong Rivers and Flat Brook Delaware River Basin Commission West Trenton, NJ August 2000 Cover Photo: Flat Brook in Delaware Water Gap National Recreation Area, NJ. Whippany River at Morristown Musconetcong at Riegelsville Musconetcong at Bloomsbury Saddle River at Fair Lawn Acknowledgements This report was developed by the Delaware River Basin Commission (DRBC) and the U.S. Geological Survey (USGS) under a grant from the New Jersey Department of Environmental Protection (NJDEP). This study was conceived by Richard Albert of DRBC and Eric Evenson of USGS, and nurtured by various NJDEP staff. This DRBC report and a companion report by USGS (Kariouk 2000) represent a collaborative effort. 2 Copies of this report are available from the Delaware River Basin Commission, PO Box 7360, West Trenton, NJ, 08628. Tel. 609-883-9500 ext. 205. An Adobe .pdf version is available via DRBC's web site at http://www.drbc.net Project Staff Project Managers: Mr. Albert and Kathryn Kariouk (USGS). Report Authors: Mr. Albert and Robert L. Limbeck, DRBC. Field Study Crew: Mr. Albert, supervisor; Mr. Limbeck, environmental scientist; Pamela V’Combe, DRBC watershed planner; Douglas Jerolmack, Drexel University student; Todd Kratzer and Paul Webber, DRBC water resources engineers; and Judith Strong, DRBC librarian/naturalist. Additional field assistance was provided by Alan Ambler and Sheryl Soborowski of the National Park Service. Office assistance was provided by Kirsten Conover, DRBC. Musconetcong River field workers (clockwise from top left): Doug Jerolmack surveys at a cross-section; Pamela V'Combe takes notes by a scoured stream bank; Judith Strong records measurements at a cross section; and Ms.
    [Show full text]