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Despite the tremendous progress that has been achieved in water pollution, almost 40% of the U.S. waters that have been assessed by states do not meet water quality goals. About 20,000 water bodies are impacted by siltation, nutrients, bacteria, oxygen depletion substances, metals, habitat alterations, pesticides, and toxic organic chemicals. With pollution from point sources being dramatically reduced, nonpoint source pollution is the major cause of most water that does not meet water quality goals. About 50 to 70% of the assessed surface waters are adversely affected by agricultural nonpoint source pollution caused by soil erosion from cropland and overgrazing and from pesticide and fertilizer applica...

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  1. AGRICULTURAL NONPOINT SOURCE POLLUTION Watershed Management and Hydrology Edited by William F. Ritter Adel Shirmohammadi LEWIS PUBLISHERS Boca Raton London New York Washington, D.C. © 2001 by CRC Press LLC
  2. Library of Congress Cataloging-in-Publication Data Agricultural nonpoint source pollution : watershed management and hydrology / edited by William F. Ritter, Adel Shirmohammadi p. cm. Includes bibliographical references. ISBN 1-56670-222-4 (alk. paper) 1. Agricultural pollution--Environmental aspects--United States. 2. Nonpoint source pollution--United States. 3.Watershed management--United States. 4. Water quality management--United States. I. Ritter, William F. II. Shirmohammadi, Adel, 1952- TD428.A37 A362 2000 628.1′.684—dc21 00-046349 CIP This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the consequences of their use. Neither this book nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming, and recording, or by any information storage or retrieval system, without prior permission in writing from the publisher. All rights reserved. Authorization to photocopy items for internal or personal use, or the personal or internal use of specific clients, may be granted by CRC Press LLC, provided that $.50 per page photocopied is paid directly to Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923 USA. The fee code for users of the Transactional Reporting Service is ISBN 0-1-56670-222- 4/01/$0.00+$.50. The fee is subject to change without notice. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. The consent of CRC Press LLC does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific permission must be obtained in writing from CRC Press LLC for such copying. Direct all inquiries to CRC Press LLC, 2000 N.W. Corporate Blvd., Boca Raton, Florida 33431. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation, without intent to infringe. © 2001 by CRC Press LLC Lewis Publishers is an imprint of CRC Press LLC No claim to original U.S. Government works International Standard Book Number 1-56670-222-4 Library of Congress Card Number 0046349 Printed in the United States of America 1 2 3 4 5 6 7 8 9 0 Printed on acid-free paper © 2001 by CRC Press LLC
  3. Preface Despite the tremendous progress that has been achieved in water pollution, almost 40% of the U.S. waters that have been assessed by states do not meet water quality goals. About 20,000 water bodies are impacted by siltation, nutrients, bacteria, oxy- gen depletion substances, metals, habitat alterations, pesticides, and toxic organic chemicals. With pollution from point sources being dramatically reduced, nonpoint source pollution is the major cause of most water that does not meet water quality goals. About 50 to 70% of the assessed surface waters are adversely affected by agri- cultural nonpoint source pollution caused by soil erosion from cropland and over- grazing and from pesticide and fertilizer applications. States have identified almost 500,000 kilometers of rivers and streams and more than two million hectares of lakes that do not meet state water quality goals. In 1998, about one-third of the 1062 beaches reporting to the U.S. Environmental Protection Agency had at least one health advisory or closing. More than 2500 fish consumption advisories or bans were issued by states in areas where fish were too contaminated to eat. Clean water is important for the nation’s economy. A third of Americans visit coastal areas each year, generating new jobs and billions of dollars. Closed beaches and fish advisories result in lost revenue. Water used for irrigating crops and raising livestock helps American farmers produce and sell $197 billion worth of food and fiber each year. Manufacturers use thirty-five trillion liters of fresh water annually. This book is intended to give a comprehensive overview of agricultural nonpoint source pollution and its management on a watershed scale. The first chapter provides background information on watershed hydrology, with a discussion on each phase of the hydrologic cycle. The second chapter is on soil erosion and sedimentation. The basic processes of soil erosion as it occurs in upland areas are discussed, most of it focused on rill and interrill erosion. Process-based soil erosion models and cropping and management effects on erosion are treated and contrasted in some detail. Chapters 3, 4, and 5 take up the nonpoint source pollutants nitrogen, phospho- rus, and pesticides in detail. Both surface and subsurface processes are discussed in each chapter. Chapters 3 and 4 begin with nitrogen and phosphorus cycles, respec- tively. Management practices to control nonpoint source pollution from nitrogen, phosphorus, and pesticides are discussed. Chapter 6 discusses nonpoint source pollution from the livestock industry. Surface water and groundwater quality effects from feedlots, manure storage and treatment systems, and land application of manures are presented, along with non- point source pollution control practices for each of these sources. Chapter 7 addresses the impact of irrigated agriculture on water quality. The nonpoint source pollutants nitrates, pesticides, salts, trace elements, and sus- pended sediments are discussed, along with management practices for reducing non- point source pollution from irrigation. Chapter 8 is focused on the impact of iii © 2001 by CRC Press LLC
  4. agricultural drainage on water quality. Both conventional drainage and water-table management are discussed. Chapter 9 provides an overview of water quality models. Different types of water quality models are discussed along with model development, sensitivity analysis, model validation and verification, and the role of geographic information systems in water quality modeling. Chapter 10 provides a treatment of best management prac- tices (BMPs) to control nonpoint source pollution and the framework for the design of a monitoring system for BMP impact assessment. Fourteen BMPs are discussed in detail. The final chapter discusses monitoring, including monitoring system design, data needs and collection, and implementation strategies, along with methods to monitor edge-of-field overland flow, bottom of root zone, soil, groundwater, and sur- face water. The editors thank all authors for their valuable contribution to this book. We hope it will give people a better insight into the issues involved in agricultural non- point source pollution and its control. William F. Ritter Adel Shirmohammadi © 2001 by CRC Press LLC
  5. Editors William F. Ritter, Ph.D. is Professor of Bioresources and Civil and Environmental Engineering at the University of Delaware and a Senior Policy Fellow in the Center for Energy and Environment Policy. In 1965 Dr. Ritter received his B.S.A. in agricultural engineering from the University of Guelph, and in 1966 received a B.A.S. in civil engineering from the University of Toronto. He obtained his M.S. in 1968 in water resources and his Ph.D. in 1971 in sanitary and agricultural engineering from Iowa State University. He was a research associate at Iowa State University from 1966 to 1971 and joined the Agricultural Engineering Department at the University of Delaware as an assistant professor in 1971. He served as department chair of the Agricultural Engineering Department from 1992 to 1998. Dr. Ritter is a registered professional engineer in Delaware, Maryland, Pennsylvania, and New Jersey and is a fellow of the American Society of Agricultural Engineers and American Society of Civil Engineers. He is also a member of the American Water Works Association, Water Environment Federation, Canadian Society of Agricultural Engineers, and American Society of Engineering Education. He has taught courses on hydrology, soil erosion, irrigation, drainage, soil physics, solid waste management, wastewater treatment, and land application of wastes. He has conducted research on irrigation water management, livestock waste manage- ment, surface and groundwater quality, and land application of wastes. He has served as a consultant to government and industry on wastewater management, water qual- ity, land application of wastes, and livestock waste management. Dr. Ritter is the author of more than 270 papers, reports, and book contributions and has presented over 140 papers at regional, national, and international confer- ences. He has also received numerous awards that include the College of Agriculture Outstanding Research Award (1990), ASAE Gunlogson Countryside Engineering Award (1989), ASCE Outstanding News Correspondent (1997), and ASCE Delaware Section Civil Engineer of the Year (1999). Dr. Adel Shirmohammadi, Ph.D. is Professor of Biological Resources Engineering at the University of Maryland, College Park campus. In 1974, Dr. Shirmohammadi received his B.S. in agricultural engineering from the University of Rezaeiyeh in Iran. He obtained an M.S. in 1977 in agricultural engi- neering from the University of Nebraska and a Ph.D. in 1982 in biological and agri- cultural engineering from North Carolina State University. From 1982 to 1986 he was a post-doctoral agricultural research engineer and assistant research scientist in the Agricultural Engineering Department at the University of Georgia Coastal Plains Experiment Station at Tifton. In 1986, he joined the Agricultural Engineering Department at the University of Maryland as an assistant professor. Dr. Shirmohammadi is a member of the American Society of Agricultural Engineers, Soil and Water Conservation Society of America, and American v © 2001 by CRC Press LLC
  6. Geophysical Union. He has taught courses in hydrology, soil and water conservation engineering, water quality modeling, flow-through porous media, and nonpoint source pollution. He has conducted research in hydrologic and water quality mode- ling, drainage, and nonpoint source pollution. He has developed an international reputation in water quality modeling for his work with CREAMS, GLEAMS, DRAINMODE, and ANSWERS. Dr. Shirmohammadi has received numerous competitive grants and has served as a consultant to industry and government. He is the author of more than 100 refereed publications, conference proceedings, papers, and book contributions. © 2001 by CRC Press LLC
  7. --, Contributors Lars Bergstrom, Ph.D. Theo A. Dillaha III, Ph.D. Professor Professor Swedish University of Agricultural Biological Systems Engineering Sciences Department Division of Water Quality Research Virginia Polytechnic and State Uppsala, Sweden University Blacksburg, VA Kevin M. Brannan, M.S. Research Associate Dwayne R. Edwards, Ph.D. Biological Systems Engineering Associate Professor Department Biosystems and Agricultural Virginia Polytechnic and State Engineering Department University University of Kentucky Blacksburg, VA Lexington, KY Blaine R. Hanson, Ph.D. Adriana C. Bruggeman, Ph.D. Irrigation and Drainage Specialist Research Associate Department of Land, Air and Water Biological Systems Engineering Resources Department University of California Virginia Polytechnic and State Davis, CA University Blacksburg, VA Walter G. Knisel, Jr., Ph.D. Kenneth L. Campbell, Ph.D. Retired Hydraulic Engineer of USDA- Professor ARS and Affiliate Professor Agricultural and Biological Engineering Biological and Agricultural Engineering Department Department University of Florida Coastal Plains Experiment Station Gainesville, FL University of Georgia Tifton, GA © 2001 by CRC Press LLC
  8. William L. Magette, Ph.D. Adel Shirmohammadi, Ph.D. Lecturer Biological Resources Engineering Agricultural and Food Engineering Department Department University of Maryland University College Dublin College Park, MD Dublin, Ireland William F. Ritter, Ph.D. Hubert J. Montas, Ph.D. Bioresources Engineering Assistant Professor Department Biological Resources Engineering University of Delaware Department Newark, DE University of Maryland College Park, MD Thomas J. Trout, Ph.D. Agricultural Engineer Saied Mostaghimi, Ph.D. USDA-ARS Water Management H. E. and Elizabeth Alphin Professor Research Laboratory Biological Systems Engineering Fresno, CA Department Virginia Polytechnic and State Mary Leigh Wolfe, Ph.D. University Associate Professor Blacksburg, VA Biological Systems Engineering Department Virginia Polytechnic and State Mark A. Nearing, Ph.D. University Scientist Blacksburg, VA USDA-ARS National Soil Erosion Research Laboratory West Lafayette, IN Xunchang Zhang, Ph.D. Scientist USDA-ARS Soil Erosion Research L. Darrell Norton, Ph.D. Laboratory Scientist West Lafayette, IN USDA-ARS National Soil Erosion Research Laboratory West Lafayette, IN © 2001 by CRC Press LLC
  9. Table of Contents Chapter 1 Hydrology Mary Leigh Wolfe Chapter 2 Soil Erosion and Sedimentation Mark A. Nearing, L. Darrell Norton, and Xunchang Zhang Chapter 3 Nitrogen and Water Quality William F. Ritter and Lars Bergstrom Chapter 4 Phosphorus and Water Quality Impacts Kenneth L. Campbell and Dwayne R. Edwards Chapter 5 Pesticides and Water Quality Impacts William F. Ritter Chapter 6 Nonpoint Source Pollution and Livestock Manure Management William F. Ritter Chapter 7 Irrigated Agriculture and Water Quality Impacts Blaine R. Hanson and Thomas J. Trout Chapter 8 Agricultural Drainage and Water Quality William F. Ritter and Adel Shirmohammadi Chapter 9 Water Quality Models Adel Shirmohammadi, Hubert J. Montas, Lars Bergstrom, and Walter J. Knisel, Jr. © 2001 by CRC Press LLC
  10. Chapter 10 Best Management Practices for Nonpoint Source Pollution Control: Selection and Assessment Saied Mostaghimi, Kevin M. Brannan, Theo A. Dillaha and Adriana C. Bruggeman Chapter 11 Monitoring William L. Magette © 2001 by CRC Press LLC
  11. 1 Hydrology M. L. Wolfe CONTENTS 1.1 Introduction 1.2 Hydrologic Cycle 1.2.1 Precipitation Description Rainfall estimation 1.2.2 Surface Runoff Description Estimating runoff Rainfall excess Runoff hydrographs 1.2.3 Soil Water Movement 1.2.4 Infiltration 1.2.5 Groundwater Groundwater flow estimation References 1.1 INTRODUCTION Sources of water pollution can be classified broadly into two categories: point sources and nonpoint sources. Point sources are most readily identified with indus- trial sources such as manufacturing, processing, power generation, and waste treat- ment facilities where pollutants are delivered through a pipe (discharge point). In contrast, nonpoint, or diffuse, sources include areas such as agricultural fields, park- ing lots, and golf courses. Nonpoint pollutants such as sediment, nutrients, pesticides, and pathogens are transported across the land surface by runoff and through the soil by percolating water. Nonpoint source (NPS) pollution is intermittent, associated very closely with rainfall runoff. Nonpoint source pollution is a function of climatic factors and site- specific land characteristics such as soil type, land management, and topography. This chapter focuses on the hydrologic processes that strongly influence NPS pollution. First, an overview of the hydrologic cycle is given, with emphasis on the interaction of the processes. Interaction of hydrologic processes is highlighted throughout the chapter because it is difficult, if not impossible, to describe one © 2001 by CRC Press LLC
  12. process without mentioning others. The sections that follow include qualitative descriptions of each process, presentations of estimation techniques, and discussions of the relationship of each process to NPS pollution. Information related to measure- ment of each process is included in Chapter 11. 1.2 HYDROLOGIC CYCLE Nonpoint source pollution is tied closely to the hydrologic cycle (Figure 1.1). Falling rain can be followed to several fates. Some rain evaporates as it falls and returns to the atmosphere. Some rainfall is intercepted by vegetation. Intercepted rainfall then either evaporates or drips to the soil surface. Some rainfall reaches the soil surface, where some of it infiltrates into the soil, some ponds on the soil surface, and some runs off. Ponded rainfall can evaporate, infiltrate into the soil, or run off. Rainfall that infiltrates can be used by plants, remain in the soil profile, or percolate to groundwater. The proportions of rainfall that reach the various fates depend on dynamic site-specific conditions such as vegetative cover, soil moisture content, soil texture, and slope. Similar to rainfall, snowmelt can run off or infiltrate. Nonpoint pollutants are transported by runoff to surface water and by leaching to groundwater. In addition, groundwater feeds streams, so pollutants can also reach surface water via groundwater. In the following sections, hydrologic processes that are particularly important with respect to NPS pollution are described. FIGURE 1.1 The hydrologic cycle. (From Shaw, E. M., Hydrology—a multidisciplinary subject, in Environment, Man and Economic Change, Phillips, A. D. M. and Turton, B. J., Eds., Longman, London and New York, 1975, 164. ©Longman Group Limited 1975. With permission.) © 2001 by CRC Press LLC
  13. 1.2.1 PRECIPITATION Description Precipitation occurs in a number of different forms, including drizzle, mist, rain, snow, sleet, hail, and dew (Brooks et al.1). Drizzle consists of drops less than 0.5 mm in diameter. Rain consists of drops 0.5 to 7 mm in diameter. Mist describes a rate of less than one mm/h. Snow is precipitation that changes directly from water vapor to ice. Sleet refers to frozen raindrops cooled to ice while falling through air at sub- freezing temperatures. Hail is formed by alternate freezing and melting as raindrops are carried up and down in a turbulent air current. Dew is caused by condensation of moisture in air on cooler surfaces. The relationship among atmospheric moisture, temperature, and vapor pres- sure determines the occurrence and amounts of precipitation. Precipitation occurs when three conditions are met (Eagleson2): (1) saturation conditions in the atmos- phere, (2) phase change of water content from vapor to liquid or solid state, and (3) growth of the small water droplets or ice crystals to precipitable size. Detailed 2 descriptions of these phenomena are presented in many sources (e.g., Eagleson, 1 Brooks et al. ). Rain is the precipitation of primary importance to NPS pollution. Rainfall varies both temporally (Figure 1.2) and spatially (Figure 1.3), which means that NPS pol- lution varies temporally and spatially. Characteristics of rainfall that are important to NPS pollution include rainfall intensity, duration, amount, drop size distribution, FIGURE 1.2 Distribution of mean (1961–1990) monthly precipitation (mm) for three loca- tions that receive about 1120 mm total annual precipitation. (Based on data from National Climatic Data Center, © 2001 by CRC Press LLC
  14. FIGURE 1.3 Mean (1961–1990) annual precipitation for selected locations in the United States. (Based on data from National Climatic Data Center, climate/online/nrmlprcp.html) raindrop energy, and frequency of occurrence. Intensity and duration determine the total amount of rainfall. Both total amount and intensity of rainfall are important influences on NPS pollution. For example, in general, a short-duration, high-inten- sity rainfall will cause more runoff than a long-duration, low-intensity rainfall of the same amount. Drop size and velocity determine raindrop energy (KE 1/2 mv,2 KE kinetic energy, m mass, v velocity), which influences infiltration and, therefore, runoff and erosion. Drop size distribution is related to rainfall intensity (Laws and Parsons3). As rainfall intensity increases, the range of drop sizes increases and there are more drops of large diameter. Higher energy has the potential to decrease infiltration through surface sealing and to increase soil erosion through increased soil detach- ment. Terminal velocity ranges from about 5 m/s for a 1-mm drop to about 9 m/s for a 5-mm drop (Laws4). Frequency of rainfall and other hydrologic events is typically described in terms of a return period, or recurrence interval. Return period is the average number of years within which a given event will be equaled or exceeded. A rainfall event is described fully in terms of its depth and duration. For example, a 25-year, 24-hour rainfall is the amount of rainfall during a 24-hour duration that is equaled or exceeded on the average once every 25 years. It does not mean that an exceedance occurs every 25 years, but that the average time between exceedances is 25 years. Depth-duration- frequency relationships have been developed for the United States for durations of © 2001 by CRC Press LLC
  15. 30 minutes to 24 hours and return periods of 1 to 100 years (Hershfield5). Frequency of rainfall events is important in designing some management practices and struc- tures for NPS pollution control. Rainfall Estimation Daily rainfall is a complex process and therefore difficult to model (Richardson6). The randomness of rainfall occurrence and characteristics must be represented. Stochastic modeling of rainfall has often used the approach of first estimating the occurrence of rainfall and then modeling the rainfall event characteristics of depth and duration. For example, Mills7 modeled occurrence of rainfall using a Poisson dis- tribution and then estimated duration using a Weibull marginal probability density function (PDF) and depth using a log-normal conditional PDF given duration. Monte 7 8 Carlo simulation (Mills ) and Markov type rainfall models (Jimoh and Webster ) are often used to describe the occurrence of daily rainfall occurrence (i.e., wet day/dry day sequences). Jimoh and Webster8 investigated the optimum order of Markov mod- els for simulating rainfall occurrence. A second approach to simulating rainfall combines occurrence and depth of rain- fall. Khaliq and Cunnane9 described cluster-based models and a three-state conti- nuous Markov process occurrence model (Hutchinson10). Cluster-based models represent rainfall events as clusters of rain cells. Each cell is considered to be a pulse with a random duration and random intensity that is constant throughout the cell duration. Cells are distributed in time according to the Neyman-Scott cluster process or the Bartlett-Lewis cluster process (Rodriguez-Iturbe et al.11). Efforts continue to improve estimation of rainfall occurrence and event charac- teristics. The increasing availability of space-time rainfall data from radar and satel- lite is contributing to the effort (Mellor12). Detailed information on estimating rainfall events can be found in a number of publications (e.g., Singh13 and O’Connell and Todini14). 1.2.2 SURFACE RUNOFF Description Surface runoff occurs when the infiltration capacity of the soil is exceeded by the rainfall rate. Excess rain (in excess of infiltration) accumulates on the soil surface and runs off when the depth of ponding and other surface conditions cause the water to flow. Runoff travels across the land surface, increasing and decreasing in flow velo- city and changing course depending on slope, vegetation, surface roughness, and other surface characteristics. Some runoff can infiltrate as it flows (transmission losses). Previously infiltrated water can reemerge (interflow or shallow subsurface flow) to join the surface flow. The amount of runoff depends on other components of the hydrologic cycle such as infiltration, interception, evapotranspiration (ET), and surface storage. If the rate of rainfall does not exceed the rate of infiltration, there is no runoff. The amount of interception is a function of the type and growth stage of vegetation and wind © 2001 by CRC Press LLC
  16. velocity. There is little information available about amount of interception by agri- cultural crops, but there has been considerable work done on interception by forests. Interception by a well-developed forest canopy is about 10 to 20% of the annual rain- fall (Linsley et al.15). Evapotranspiration affects soil moisture conditions, which in turn affect infiltration capacity of the soil. Rainfall that reaches the soil surface but does not immediately infiltrate becomes part of surface retention or surface detention. Surface retention is water retained on the land surface in micro-depressions. Retained water will eventually evaporate or infiltrate. Surface detention is water temporarily detained on the land surface prior to running off. Microtopography, or surface rough- ness, and surface macroslope affect both retention and detention. In addition, deten- tion is influenced by vegetation and rainfall excess distribution (Huggins and Burney16). Runoff transports NPS pollutants in dissolved forms and in forms adsorbed to sediment. The detachment and transport capacity of runoff are dependent on the velo- city and depth of flow. The velocity and depth of flow both change with time and space as runoff flows over a land surface. Sometimes the flow can be characterized as shallow sheet flow across the surface. Often the flow will be concentrated into small channels called rills on an agricultural field. The temporal distribution of runoff at a location is described graphically by a hydrograph (Figure 1.4) with runoff plot- ted on the y-axis and time on the x-axis. Runoff can be expressed in units of volume 3 per time (cfs or m /s) or stage (L) of flow. Hydrographs can show surface runoff, direct runoff or total runoff. The time of concentration refers to the time required for runoff to reach the watershed outlet from the farthest hydraulic distance from the out- let. The time of concentration is a function of topography, surface cover, and distance of flow. The amount and rate of runoff depend on rainfall and watershed characteristics. Important rainfall characteristics include duration, intensity, and areal distribution. FIGURE 1.4 Hydrograph for Watershed W-1, Moorefield, WV, May 23, 1962. (Based on data from Agricultural Research Service Water Database, ter.html) © 2001 by CRC Press LLC
  17. Watershed characteristics that influence runoff include soil properties, land use, vegetation cover, moisture condition, size, shape, topography, orientation, geology, cultural practices, and channel characteristics. Larger watersheds generally produce larger volumes and rates of runoff. Long, narrow watersheds have longer times of concentration compared with compact watersheds. Storms moving upstream cause lower runoff rates at the watershed outlet than storms moving downstream. In the upstream case, rain stops at the lower end of the watershed before the upper end of the watershed contributes to runoff at the outlet. In the downstream case, runoff from the upper parts of the watershed reach the outlet while runoff is being contributed by the lower part of the watershed as well. Steeper slopes generally have higher runoff rates. The geology of a watershed affects runoff through its effect on infiltration. Vegetation in general retards overland flow and increases infiltration. Different vege- tation types affect runoff differently. Close-growing plants such as sod retard flow more than woody plants that do not have much ground cover. Estimating Runoff Runoff is clearly a complex, variable process, influenced by many factors. Runoff calculations typically include estimating the amount of runoff, or rainfall excess, and then translating that amount of runoff into a hydrograph. Common approaches for estimating rainfall excess and runoff hydrographs are described in the following sections. Rainfall Excess Rainfall excess is determined as the total amount of rainfall minus infiltration and interception. Rainfall excess is typically estimated in two ways. In one approach, infiltration is estimated directly and then subtracted from rainfall. Methods of esti- mating infiltration are described later in this chapter. The second approach is the USDA Soil Conservation Service (SCS) (now Natural Resources Conservation Service, NRCS) method of estimating runoff vol- ume, commonly called the curve number approach. The SCS method correlates the difference between rainfall and runoff with antecedent soil moisture (ASM), or antecedent moisture condition (AMC), soil type, vegetative cover, and cultural prac- tices. Rainfall excess is computed using the following relationship (SCS17): 0.2S )2 (P Q (1.1) P 0.8S 25,400 S 254 (1.2) CN where Q is the direct storm runoff volume (mm), P is the storm rainfall depth (mm), S is the maximum potential difference between rainfall and runoff starting at the time the storm begins (mm), and CN is the runoff curve number (Table 1.1), which © 2001 by CRC Press LLC
  18. TABLE 1.1 Runoff Curve Numbers for Hydrologic Soil-Cover Complexes (Antecedent Moisture Condition II and Ia 0.2S) (From SCS, Hydrology, Section 4. National Engineering Handbook, U.S. Soil Conservation Service, GPO, Washington, DC, 1972) Land Use Description/Treatment/Hydrologic Condition Hydrologic Soil Group A B C D Residential:a Average % Imperviousb Average Lot Size 0.05 ha or less 65 77 85 90 92 0.10 ha 38 61 75 83 87 0.13 ha 30 57 72 81 86 0.20 ha 25 54 70 80 85 0.40 ha 20 51 68 79 84 Paved parking lots, 98 98 98 98 c roofs, driveways, etc. Street and roads: paved with curbs and storm sewersc 98 98 98 98 gravel 76 85 89 91 dirt 72 82 87 89 Commercial and business areas 89 92 94 95 (85% impervious) Industrial districts (72% impervious) 81 88 91 93 Open Spaces, lawns, parks, golf courses, cemeteries, etc. good condition: grass cover on 75% or more of the area 39 61 74 80 fair condition: grass cover on 50% to 75% of the area 49 69 79 84 Fallow Straight row — 77 86 91 94 Row crops Straight row Poor 72 81 88 91 Straight row Good 67 78 85 89 Contoured Poor 70 79 84 88 Contoured Good 65 75 82 86 Contoured & terraced Poor 66 74 80 82 Contoured & terraced Good 62 71 78 81 Small grain Straight row Poor 65 76 84 88 Good 63 75 83 87 Contoured Poor 63 74 82 85 Good 61 73 81 84 Contoured & terraced Poor 61 72 79 82 Good 59 70 78 81 Close–seeded Straight row Poor 66 77 85 89 legumesd Straight row Good 58 72 81 85 or Contoured Poor 64 75 83 85 rotation Contoured Good 55 69 78 83 meadow Contoured & terraced Poor 63 73 80 83 Contoured & terraced Good 51 67 76 80 © 2001 by CRC Press LLC
  19. TABLE 1.1 (cont’d.) Land Use Description/Treatment/Hydrologic Condition Hydrologic Soil Group Pasture Poor 68 79 86 89 or range Fair 49 69 79 84 Good 39 61 74 80 Contoured Poor 47 67 81 88 Contoured Fair 25 59 75 83 Contoured Good 6 35 70 79 Meadow Good 30 58 71 78 Woods or Poor 45 66 77 83 Forest land Fair 36 60 73 79 Good 25 55 70 77 Farmsteads — 59 74 82 86 a Curve numbers are computed assuming the runoff from the house and driveway is directed toward the street with a minimum of roof water directed to lawns where additional infiltration could occur. b The remaining pervious areas (lawn) are considered to be in good pasture condition for these curve numbers. c In some warmer climates of the country, a curve number of 95 may be used. d Close-drilled or broadcast. represents runoff potential of a surface. Rainfall depth, P, must be greater than 0.2 S for the equation to be applicable. The CN indicates the runoff potential of a surface based on soil characteristics and land use conditions and ranges from 1 to 100 (Table 1.1), increasing with increas- ing CN. Required information to use the table includes the hydrologic soil group (defined in Table 1.2), the vegetal and cultural practices of the site, and the AMC (defined in Table 1.2). The CN obtained from Table 1.1 for AMC II can be converted to AMC I or III using the values in Table 1.3. Curve numbers can be determined from rainfall runoff data for a particular site. Investigations have been conducted to determine CN values for conditions not included in Table 1.1 or similar tables. Examples include exposed fractured rock sur- faces (Rasmussen and Evans18), animal manure application sites (Edwards and 19 Daniel ), and dryland wheat-sorghum-fallow crop rotation in the semi-arid western Great Plains (Hauser and Jones20). The CN approach is widely used for estimating runoff volume. Because the CN is defined in terms of land use treatments, hydrologic condition, AMC, and soil type, the approach can be applied to ungaged watersheds. Errors in selecting CN values can result from misclassifying land cover, treatment, hydrologic conditions, or soil type (Bondelid et al.21). The magnitude of the error depends on the size of the area mis- classified and the type of misclassification. In a sensitivity analysis of runoff esti- 21 mates to errors in CN estimates, Bondelid et al. found that effects of variations in 22 CN decrease as design rainfall depth increases and confirmed Hawkins’ conclusion that errors in CN estimates are especially critical near the threshold of runoff. © 2001 by CRC Press LLC
  20. TABLE 1.2 Hydrologic Soil Group Descriptions and Antecedent Rainfall Conditions for Use with the SCS Curve Number Method (From SCS, Hydrology, Section 4. National Engineering Handbook, U.S. Soil Conservation Sservice, GPO, Washington, DC, 1972) Soil Group Description A Lowest Runoff Potential. Includes deep sands with very little silt and clay, also deep, rapidly permeable loess. B Moderately Low Runoff Potential. Mostly sandy soils less deep than A, and loess less deep or less aggregated than A, but the group as a whole has above-average infiltration after thor- ough wetting. C Moderately High Runoff Potential. Comprises shallow soils and soils containing consider- able clay and colloids, though less than those of group D. The group has below-average infiltration after presaturation. D Highest Runoff Potential. Includes mostly clays of high swelling percentage, but the group also includes some shallow soils with nearly impermeable subhorizons near the surface. 5-Day Antecedent Rainfall (mm) Condition General Description Dormant Season Growing Season I Optimum soil condition from about 6.4 35.6 lower plastic limit to wilting point II Average value for annual floods 6.4 27.9 35.6–53.3 III Heavy rainfall or light rainfall and 27.9 53.3 low temperatures within 5 days prior to the given storm The CN approach is used in a number of NPS pollution models. Bingner23 found that although most of the five models he evaluated use the CN approach, it is not implemented in the same way in each model. Bingner thus cautions that a user must understand the purpose for which a model was developed to avoid improper use of the model. Sensitivity analyses (e.g., Ma et al.,24 Chung et al.25) have demonstrated the sensitivity of runoff estimates to CN in those models. Additional concerns have been raised about the CN method. It is not clear whether the data from which the relationship was developed were ever presented. The method was developed only for estimating runoff volume from storms of long dura- tion medium to large watersheds (5–50 km2). Runoff Hydrographs Runoff, or overland flow, can be visualized as sheet-type flow (as opposed to chan- nel flow) with small depths of flow and slow velocities (less than 0.3 m/sec). Considerable volumes of water can move through overland flow. In routing overland © 2001 by CRC Press LLC
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