DOCSLIB.ORG

Effects of Curve Number Modification on Runoff Estimation Using WSR

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Effects of Curve Number Modification on Runoff Estimation Using WSR ing, and has been incorporated into various computer models worldwide (Woodward et al., 2002; Hawkins et al., 2002). Although this is an accepted method for runoff estima- tion, studies have indicated that it should be Effects of curve number modification on evaluated and adapted to regional agro- climatic conditions. Hawkins (1998) states that curve number runoff estimation using WSR-88D rainfall tables should be used as guidelines and that actual curve numbers and their empirical data in Texas watersheds relationships should be determined based on local and regional data. This is supported by J.H. Jacobs and R. Srinivasan Van Mullem et al. (2002). They state that the direct runoff calculated by the curve ABSTRACT: The purpose of this study was to evaluate variations of the Natural Resources number method is more sensitive to the Conservation Service (NRCS) curve number method for estimating near real-time runoff for curve number variable than rainfall inputs. naturalized flow, using high resolution radar rainfall data in Texas watersheds. This study was This would suggest an increased need for undertaken in an attempt to provide more accurate runoff estimates to watershed and water field verification of land cover type and con- resource managers for planning purposes. Stage III Weather Surveillance Radar 1988 Doppler dition before curve number assignment. The accuracy of hydrologic models (WSR-88D) precipitation data, obtained from the West Gulf River Forecast Center, was used as depends on the accuracy of input data and, in the precipitation input for runoff estimates in this study. The study areas consisted of dominant the case of the NRCS curve number or homogenous land use and were characterized by naturalized flow. Findings indicate that the method, the variable inputs. The purpose of use of a dry antecedent soil moisture condition curve number value and a reduced initial this study was to evaluate several variations of abstraction coefficient (Ia) in the NRCS curve number equation produced the most statistically the NRCS curve number method for esti- significant comparison between observed and estimated runoff in nine out of ten watersheds. mating near real-time runoff for naturalized The combined comparison for all events in these nine watersheds produced a coefficient of flow, using WSR-88D rainfall data for water- efficiency (COE) of 0.70, with a slope of 0.78 and an r2 of 0.77. Overall, the results of this sheds in various agro-climatic regions of research suggest that, although further improvements can be made for improved runoff Texas in an attempt to represent the spatial estimation, the use of modified inputs to the NRCS curve number equation in conjunction with variability of rainfall. WSR-88D radar rainfall data could be useful in producing runoff estimates for Texas in real-time. Methods and Materials Study area selection and description. Te n Keywords: Hydrologic modeling watersheds of varying size (355 to 2,940 km2), in four river basins, throughout differ- ent agro-climatic regions of Texas were used Water availability has become a major in arid and semi-arid regions, such as west in this study to account for a variety of issue in Texas in recent years. Adding to Texas, where most rainfall occurs in short, hydrologic conditions throughout the state this issue is the expected doubling of the pop- heavy, localized thunderstorms. Dense net- (Figure 1). Watersheds were chosen based on ulation within the next 50 years, mainly in works necessary to provide such data are gen- dominant land use, soil hydrologic group, and areas presently without abundant water sup- erally available only for experimental or streamgauge location (Table 1). Land cover plies. To combat problems that Texas will research watersheds. Also, few rain gauge data was obtained from the 1992 U.S. face in the future, there has been a move networks are currently able to provide real- Geological Survey (USGS) National Land toward active planning and management of time data. The use of weather radar systems Cover Dataset at a 1:24,000 scale (30 m water resources. Real-time weather data could help alleviate these problems. One resolution). Only watersheds with homoge- processing and hydrologic modeling can pro- such system is the Weather Surveillance nous/dominant cover or similar curve num- vide information for this planning in addition Radar 1998 Doppler (WSR-88D) of the ber values were used. Soils data were derived to flood and drought mitigation, reservoir National Weather Service (NWS). This data from the U.S. Department of Agriculture operation, and watershed and water resource could be used in conjunction with runoff Natural Resources Conservation Service management practices (Texas Water Develop- models, such as the Natural Resources (USDA-NRCS) State Soil Geographic ment Board, 2000). However, in order to Conservation Service (NRCS) curve number (STATSGO) database, at a 1:250,000 scale provide this information to managers, it is method to deliver data to managers in a near (250 m resolution). Streamflow data was necessary to first obtain reliable and readily- real-time fashion. available weather data. In the 1950’s, the curve number method Jennifer H. Jacobs is a research associate and Rain gauge networks are generally sparse was developed to estimate runoff in Raghavan Srinivasan is the professor and director and insufficient to capture the spatial variabil- ungauged watersheds (SCS, 1972). This at the Spatial Sciences Laboratory at Texas A&M ity of rainfall across large watersheds, especially method is widely used for watershed model- University in College Station, Texas. Reprinted from the Journal of Soil and Water Conservation 274 JOURNAL OF SOIL AND WATER CONSERVATION S|O 2005 Volume 60, Number 5 Copyright © 2005 Soil and Water Conservation Society Figure 1 Study area locations. Red-1 (3) For the actual runoff calculation, initial abstractions (Ia) are generally approximated as Red-2 0.2 retention parameter, and the basic equa- Trinity-1 tion becomes (Equation 4): (4) where, LCR-1 Qsurf = surface runoff in mm, Trinity-2 Trinity-3 Rday = rainfall depth for the day,also in mm. LCR-2 Runoff will occur only when Rday greater LCR-3 than Ia (Neitsch et al., 2001). However, Ponce and Hawkins (1996) suggest that 0.2 SA-1 SA-2 retention parameter may not be the most N W E appropriate number for initial abstractions, 0 50 100 200 S and that it should be interpreted as a regional Kilometers parameter. Stage III WSR-88D data was obtained downloaded from the USGS website for each defined as (Equation 1): through a Memorandum of Agreement with watershed outlet. the West Gulf River Forecast Center Total streamflow is composed of baseflow (WGRFC) of the National Weather Service (lateral flow and shallow ground water dis- (1) (NWS). Data for the 1999 - 2001 time period charge to streams) and surface runoff. To was used as the rainfall input in this study, compare measured flow and estimated runoff based on findings by Jayakrishnan (2004) (NRCS curve number method provides only Curve number varies based on one of citing improved data quality and accuracy in direct runoff after a rainfall event), it was nec- three antecedent soil moisture conditions, recent years. This, in addition to the fact that essary to determine the portion of streamflow curve number I-dry (wilting point), curve the WSR-88D data is complete and available that could be attributed to surface runoff. number II-average, and curve number III-wet daily, makes it a more useful dataset for this Therefore, flow data was processed through a (field capacity) (Neitsch et al., 2001). Runoff type of modeling research. More informa- filter program. The filter program developed estimates increase with increasing antecedent tion concerning weather radar products and by Arnold et al. (1995) was used in this study, soil moisture condition, and with increasing processing algorithms can be found in Crum and is comparable to other automated separa- curve number. and Alberty (1993), Klazura and Imy (1993), tion techniques, with 74 percent efficiency Curve number II was assigned based on Smith et al. (1996), and Fulton et al. (1998). when compared to manual separation the dominant land use from National Land Comparing runoff results. For this analysis, (Arnold and Allen, 1999). Also, because the Cover Dataset and soil hydrologic group from curve number I and curve number II were runoff algorithms used in this study do not STATSGO according to the Soil Conserva- first used as curve number variables in the account for reservoirs or other diversions, tion Service’s (SCS) Texas Engineering runoff equation with an initial abstraction only sites with natural, or unregulated, flow Technical Note No. 210-18-TX5 (1990). ratio of 0.2, 0.1, and 0.05 to determine the were used. This allowed for a direct compar- Curve number I and curve number III are most appropriate constant for initial abstrac- ison of runoff estimates to measured stream- calculated from curve number II and are tions in the selected study sites. WSR-88D flow data. defined by Equations (2) and (3) respectively data was used as the rainfall input. Results of Curve number calculations. Daily runoff (Neitsch et al., 2001). A geographic informa- each alternative (a combination of curve calculations were generated using the NRCS tion system (GIS) layer in grid format was number variable and initial abstraction coeffi- curve number method. This calculation is created for each watershed based on curve cient) were then evaluated based on observed based on the retention parameter, S, initial number II values at a 4 km resolution, from runoff to determine which produced the abstractions, Ia (surface storage, interception, which curve number I was calculated. most statistically significant results (Hadley, and infiltration prior to runoff), and daily 2003). rainfall, Rday, (all in mm H20).
Load more

Recommended publications
  • Geomorphic Classification of Rivers
    9.36 Geomorphic Classification of Rivers JM Buffington, U.S. Forest Service, Boise, ID, USA DR Montgomery, University of Washington, Seattle, WA, USA Published by Elsevier Inc. 9.36.1 Introduction 730 9.36.2 Purpose of Classification 730 9.36.3 Types of Channel Classification 731 9.36.3.1 Stream Order 731 9.36.3.2 Process Domains 732 9.36.3.3 Channel Pattern 732 9.36.3.4 Channel–Floodplain Interactions 735 9.36.3.5 Bed Material and Mobility 737 9.36.3.6 Channel Units 739 9.36.3.7 Hierarchical Classifications 739 9.36.3.8 Statistical Classifications 745 9.36.4 Use and Compatibility of Channel Classifications 745 9.36.5 The Rise and Fall of Classifications: Why Are Some Channel Classifications More Used Than Others? 747 9.36.6 Future Needs and Directions 753 9.36.6.1 Standardization and Sample Size 753 9.36.6.2 Remote Sensing 754 9.36.7 Conclusion 755 Acknowledgements 756 References 756 Appendix 762 9.36.1 Introduction 9.36.2 Purpose of Classification Over the last several decades, environmental legislation and a A basic tenet in geomorphology is that ‘form implies process.’As growing awareness of historical human disturbance to rivers such, numerous geomorphic classifications have been de- worldwide (Schumm, 1977; Collins et al., 2003; Surian and veloped for landscapes (Davis, 1899), hillslopes (Varnes, 1958), Rinaldi, 2003; Nilsson et al., 2005; Chin, 2006; Walter and and rivers (Section 9.36.3). The form–process paradigm is a Merritts, 2008) have fostered unprecedented collaboration potentially powerful tool for conducting quantitative geo- among scientists, land managers, and stakeholders to better morphic investigations.
    [Show full text]
  • Flood Hazard of Dunedin's Urban Streams
    Flood hazard of Dunedin’s urban streams Review of Dunedin City District Plan: Natural Hazards Otago Regional Council Private Bag 1954, Dunedin 9054 70 Stafford Street, Dunedin 9016 Phone 03 474 0827 Fax 03 479 0015 Freephone 0800 474 082 www.orc.govt.nz © Copyright for this publication is held by the Otago Regional Council. This publication may be reproduced in whole or in part, provided the source is fully and clearly acknowledged. ISBN: 978-0-478-37680-7 Published June 2014 Prepared by: Michael Goldsmith, Manager Natural Hazards Jacob Williams, Natural Hazards Analyst Jean-Luc Payan, Investigations Engineer Hank Stocker (GeoSolve Ltd) Cover image: Lower reaches of the Water of Leith, May 1923 Flood hazard of Dunedin’s urban streams i Contents 1. Introduction ..................................................................................................................... 1 1.1 Overview ............................................................................................................... 1 1.2 Scope .................................................................................................................... 1 2. Describing the flood hazard of Dunedin’s urban streams .................................................. 4 2.1 Characteristics of flood events ............................................................................... 4 2.2 Floodplain mapping ............................................................................................... 4 2.3 Other hazards ......................................................................................................
    [Show full text]
  • Determination of Curve Number and Estimation of Runoff Using Indian Experimental Rainfall and Runoff Data
    Journal of Spatial Hydrology Volume 13 Number 1 Article 2 2017 Determination of curve number and estimation of runoff using Indian experimental rainfall and runoff data Follow this and additional works at: https://scholarsarchive.byu.edu/josh BYU ScholarsArchive Citation (2017) "Determination of curve number and estimation of runoff using Indian experimental rainfall and runoff data," Journal of Spatial Hydrology: Vol. 13 : No. 1 , Article 2. Available at: https://scholarsarchive.byu.edu/josh/vol13/iss1/2 This Article is brought to you for free and open access by the Journals at BYU ScholarsArchive. It has been accepted for inclusion in Journal of Spatial Hydrology by an authorized editor of BYU ScholarsArchive. For more information, please contact [email protected], [email protected]. Journal of Spatial Hydrology Vol.13, No.1 Fall 2017 Determination of curve number and estimation of runoff using Indian experimental rainfall and runoff data Pushpendra Singh*, National Institute of Hydrology, Roorkee, Uttarakhand, India; email: [email protected] S. K. Mishra, Dept. of Water Resources Development & Management, IIT Roorkee, Uttarakhand; email: [email protected] *Corresponding author Abstract The Curve Number (CN) method has been widely used to estimate runoff from rainfall runoff events. In this study, experimental plots in Roorkee, India have been used to measure natural rainfall-driven rates of runoff under the main crops found in the region and derive associated CN values from the measured data using five different statistical methods. CNs obtained from the standard United States Department of Agriculture - Natural Resources Conservation Service (USDA-NRCS) table were suitable to estimate runoff for bare soil, soybeans and sugarcane.
    [Show full text]
  • Classifying Rivers - Three Stages of River Development
    Classifying Rivers - Three Stages of River Development River Characteristics - Sediment Transport - River Velocity - Terminology The illustrations below represent the 3 general classifications into which rivers are placed according to specific characteristics. These categories are: Youthful, Mature and Old Age. A Rejuvenated River, one with a gradient that is raised by the earth's movement, can be an old age river that returns to a Youthful State, and which repeats the cycle of stages once again. A brief overview of each stage of river development begins after the images. A list of pertinent vocabulary appears at the bottom of this document. You may wish to consult it so that you will be aware of terminology used in the descriptive text that follows. Characteristics found in the 3 Stages of River Development: L. Immoor 2006 Geoteach.com 1 Youthful River: Perhaps the most dynamic of all rivers is a Youthful River. Rafters seeking an exciting ride will surely gravitate towards a young river for their recreational thrills. Characteristically youthful rivers are found at higher elevations, in mountainous areas, where the slope of the land is steeper. Water that flows over such a landscape will flow very fast. Youthful rivers can be a tributary of a larger and older river, hundreds of miles away and, in fact, they may be close to the headwaters (the beginning) of that larger river. Upon observation of a Youthful River, here is what one might see: 1. The river flowing down a steep gradient (slope). 2. The channel is deeper than it is wide and V-shaped due to downcutting rather than lateral (side-to-side) erosion.
    [Show full text]
  • Mitchell Creek Watershed Hydrologic Study 12/18/2007 Page 1
    Mitchell Creek Watershed Hydrologic Study Dave Fongers Hydrologic Studies Unit Land and Water Management Division Michigan Department of Environmental Quality September 19, 2007 Table of Contents Summary......................................................................................................................... 1 Watershed Description .................................................................................................... 2 Hydrologic Analysis......................................................................................................... 8 General ........................................................................................................................ 8 Mitchell Creek Results.................................................................................................. 9 Tributary 1 Results ..................................................................................................... 11 Tributary 2 Results ..................................................................................................... 15 Recommendations ..................................................................................................... 18 Stormwater Management .............................................................................................. 19 Water Quality ............................................................................................................. 20 Stream Channel Protection .......................................................................................
    [Show full text]
  • Drainage Patterns
    Drainage Patterns Over time, a stream system achieves a particular drainage pattern to its network of stream channels and tributaries as determined by local geologic factors. Drainage patterns or nets are classified on the basis of their form and texture. Their shape or pattern develops in response to the local topography and Figure 1 Aerial photo illustrating subsurface geology. Drainage channels develop where surface dendritic pattern in Gila County, AZ. runoff is enhanced and earth materials provide the least Courtesy USGS resistance to erosion. The texture is governed by soil infiltration, and the volume of water available in a given period of time to enter the surface. If the soil has only a moderate infiltration capacity and a small amount of precipitation strikes the surface over a given period of time, the water will likely soak in rather than evaporate away. If a large amount of water strikes the surface then more water will evaporate, soaks into the surface, or ponds on level ground. On sloping surfaces this excess water will runoff. Fewer drainage channels will develop where the surface is flat and the soil infiltration is high because the water will soak into the surface. The fewer number of channels, the coarser will be the drainage pattern. Dendritic drainage pattern A dendritic drainage pattern is the most common form and looks like the branching pattern of tree roots. It develops in regions underlain by homogeneous material. That is, the subsurface geology has a similar resistance to weathering so there is no apparent control over the direction the tributaries take.
    [Show full text]
  • Stream Visual Assessment Manual
    U.S. Fish & Wildlife Service Stream Visual Assessment Manual Cane River, credit USFWS/Gary Peeples U.S. Fish & Wildlife Service Conasauga River, credit USFWS Table of Contents Introduction ..............................................................................................................................1 What is a Stream? .............................................................................................................1 What Makes a Stream “Healthy”? .................................................................................1 Pollution Types and How Pollutants are Harmful ........................................................1 What is a “Reach”? ...........................................................................................................1 Using This Protocol..................................................................................................................2 Reach Identification ..........................................................................................................2 Context for Use of this Guide .................................................................................................2 Assessment ........................................................................................................................3 Scoring Details ..................................................................................................................4 Channel Conditions ...........................................................................................................4
    [Show full text]
  • Stream Visual Assessment Protocol (SVAP)
    National Water and Climate Center Technical Note 99–1 United States Department of Agriculture Natural Resources Conservation Service Stream Visual Assessment Protocol Issued December 1998 Cover photo: Stream in Clayton County, Iowa, exhibiting an impaired riparian zone. The U. S. Department of Agriculture (USDA) prohibits discrimination in its programs on the basis of race, color, national origin, gender, religion, age, disability, political beliefs, sexual orientation, and marital or family status. (Not all prohibited bases apply to all programs.) Persons with disabilities who require alternative means for communication of program information (Braille, large print, audiotape, etc.) should contact USDA’s TARGET Cen- ter at (202) 720-2600 (voice and TDD). To file a complaint of discrimination, write USDA, Director, Office of Civil Rights, Room 326W, Whitten Building, 14th and Independence Avenue, SW, Washington, DC 20250-9410 or call (202) 720-5964 (voice or TDD). USDA is an equal opportunity provider and employer. (NWCC Technical Note 99–1, Stream Visual Assessment Protocol, December 1998) Preface This document presents an easy-to-use assessment protocol to evaluate the condition of aquatic ecosystems associated with streams. The protocol does not require expertise in aquatic biology or extensive training. Least-im- pacted reference sites are used to provide a standard of comparison. The use of reference sites is variable depending on how the state chooses to implement the protocol. The state may modify the protocol based on a system of stream classification and a series of reference sites. Instructions for modifying the protocol are provided in the technical information sec- tion. Aternatively, a user may use reference sites in a less structured man- ner as a point of reference when applying the protocol.
    [Show full text]
  • North Branch of the Chicago River SCS Curve Number Generation
    North Branch of the Chicago River SCS Curve Number Generation This technical memorandum describes HDR’s approach for generating SCS Curve Number data for the watersheds comprising the North Branch of the Chicago River (herein referred to as the “North Branch”). 1. Approach Previous approaches for Detailed Watershed Plan (DWP) SCS curve number generation are the “Calumet-Sag Watershed SCS Curve Number Generation” technical memorandum a authored by CH2M Hill (dated August 14, 2007 and herein referred to as the “CH2M Hill Memo”) and “Comments on CH2MHill Curve Numbers” b email authored by CTE (dated September 14, 2007 and herein referred to as the “CTE email”). HDR will incorporate these approaches, with the following changes or refinements: o The use of an additional Natural Resources Conservation Service (NRCS) soil survey for the City of Chicago; o Analysis of the affects of minor soil types; o Review and revisions of land use information; o Use of existing remote sensing datasets to estimate impervious areas; o GIS dataset preparation. 2. NRCS Soil Survey The CH2M Hill Memo noted that NRCS soils datasets covered portions of the watersheds but did not include the City of Chicago. In place of this, the CH2M Hill Memo recommended assuming a uniform hydrologic soil group (HSG) of “C”, representing moderately high runoff potential soils. The NRCS provides two types of soil datasets for the area. One type is the Soil Survey Geographic, or SSURGO, dataset c. The SSURGO dataset is available for select areas and is a detailed soil survey. The City of Chicago is not included in the SSURGO dataset, although portions of the North Branch upper basin are included.
    [Show full text]
  • River Blackwater – Manor Farm
    River Blackwater – Manor Farm An advisory visit carried out by the Wild Trout Trust – January 2012 1 1. Introduction This report is the output of a Wild Trout Trust advisory visit undertaken on a reach of the River Blackwater adjacent to Manor Farm near Plaitford in Hampshire. The request for the visit was made by the landowner, Hillary Harper. Comments in this report are based on observations on the day of the site visit and discussions with Ms. Harper and Ms. Penny Scott, the owner of a section of the right (southern) bank. Throughout the report, normal convention is followed with respect to bank identification i.e. banks are designated Left Bank (LB) or Right Bank (RB) whilst looking downstream. 2. Catchment overview The River Blackwater rises just to the east of Red Lynch on the northern fringes of the New Forest. From here it flows south easterly for approximately 16km before joining the River Test at the upstream end of its tidal range. The Test has an international reputation as one of the finest chalk stream fisheries in the world. The Blackwater, by contrast, is not a chalk stream but rises from a network of small surface fed streams and gutters running over mainly tertiary clays and gravels. The Blackwater has long been recognised as a crucially important spawning tributary to the main River Test and is thought to be the destination of choice for the bulk of the migratory sea trout (Salmo trutta) that enter the system. Unlike the River Test, the Blackwater does not enjoy any high level statutory protection as a Site of Special Scientific Interest (SSSI).
    [Show full text]
  • Assessment of Debris Flow Potential Alice Claim
    Assessment of Debris Flow Potential Alice Claim Park City, Utah Date: July, 2017 Project No. 17014 Prepared By: Canyon Engineering Park City, Utah CANYON ENGINEERING SOLUTIONS FOR LAND August 7, 2017 Mr. Matt Cassel, PE, City Engineer Park City Municipal Corp. PO Box 1480 Park City, UT 84060 Subject: Woodside Gulch at Alice Claim Debris Flow Potential Dear Matt: Pursuant to your request, following is our professional opinion as to debris flow potential in Woodside Gulch, and its potential effect on the Alice Claim development. Also included herein is a 100-year floodplain analysis. EXECUTIVE SUMMARY Based on watershed recon, research, mapping, and computations, it is our professional opinion that the potential for hazardous debris flow at the Alice Claim development is quite limited. Is a debris flow event up valley possible? Yes, but in all likelihood, it would cover very little ground, with the potential for property damage at the Alice Claim development being exceedingly low. WATERSHED For the purposes of hydrologic analysis, our point of interest is the gulch thalweg at the north end of the Alice Claim project (King Road) at lat,long 40.6376,-111.4969. Tributary drainage area at this point is mapped at 290 acres (0.453 square miles). See Watershed Map in the Appendix. Ground elevation ranges from approximately 7,300 to 9,250 feet, with thalweg slope for the entire watershed length averaging almost 17%. For the most part, natural mountainsides slope at less than 45%, with a few steeper areas approaching 60%. The watershed is for the most part covered with mature vegetation, including oak and sagebrush, and aspen and fir forest.
    [Show full text]
  • SCS-CN Parameter Determination Using Rainfall-Runoff Data in Heterogeneous Watersheds – the Two-CN System Approach
    Hydrol. Earth Syst. Sci., 16, 1001–1015, 2012 www.hydrol-earth-syst-sci.net/16/1001/2012/ Hydrology and doi:10.5194/hess-16-1001-2012 Earth System © Author(s) 2012. CC Attribution 3.0 License. Sciences SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach K. X. Soulis and J. D. Valiantzas Agricultural University of Athens, Department of Natural Resources Management and Agricultural Engineering, Division of Water Resources Management, Athens, Greece Correspondence to: K. X. Soulis ([email protected]) Received: 5 September 2011 – Published in Hydrol. Earth Syst. Sci. Discuss.: 5 October 2011 Revised: 1 February 2012 – Accepted: 16 March 2012 – Published: 28 March 2012 Abstract. The Soil Conservation Service Curve Number 1 Introduction (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. Simple methods for predicting runoff from watersheds are The CN parameter values corresponding to various soil, land particularly important in hydrologic engineering and hydro- cover, and land management conditions can be selected from logical modelling and they are used in many hydrologic ap- tables, but it is preferable to estimate the CN value from mea- plications, such as flood design and water balance calcula- sured rainfall-runoff data if available. However, previous re- tion models (Abon et al., 2011; Steenhuis et al., 1995; van searchers indicated that the CN values calculated from mea- Dijk, 2010). The Soil Conservation Service Curve Num- sured rainfall-runoff data vary systematically with the rain- ber (SCS-CN) method was originally developed by the SCS fall depth.
    [Show full text]