The Urban Watershed Continuum: Evolving Spatial and Temporal Dimensions
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The Hyporheic Handbook a Handbook on the Groundwater–Surface Water Interface and Hyporheic Zone for Environment Managers
The Hyporheic Handbook A handbook on the groundwater–surface water interface and hyporheic zone for environment managers Integrated catchment science programme Science report: SC050070 The Environment Agency is the leading public body protecting and improving the environment in England and Wales. It’s our job to make sure that air, land and water are looked after by everyone in today’s society, so that tomorrow’s generations inherit a cleaner, healthier world. Our work includes tackling flooding and pollution incidents, reducing industry’s impacts on the environment, cleaning up rivers, coastal waters and contaminated land, and improving wildlife habitats. This report is the result of research funded by NERC and supported by the Environment Agency’s Science Programme. Published by: Dissemination Status: Environment Agency, Rio House, Waterside Drive, Released to all regions Aztec West, Almondsbury, Bristol, BS32 4UD Publicly available Tel: 01454 624400 Fax: 01454 624409 www.environment-agency.gov.uk Keywords: hyporheic zone, groundwater-surface water ISBN: 978-1-84911-131-7 interactions © Environment Agency – October, 2009 Environment Agency’s Project Manager: Joanne Briddock, Yorkshire and North East Region All rights reserved. This document may be reproduced with prior permission of the Environment Agency. Science Project Number: SC050070 The views and statements expressed in this report are those of the author alone. The views or statements Product Code: expressed in this publication do not necessarily SCHO1009BRDX-E-P represent the views of the Environment Agency and the Environment Agency cannot accept any responsibility for such views or statements. This report is printed on Cyclus Print, a 100% recycled stock, which is 100% post consumer waste and is totally chlorine free. -
Managing Storm Water Runoff to Prevent Contamination of Drinking Water
United States Office of Water EPA 816-F-01-020 Environmental Protection (4606) July 2001 Agency Source Water Protection Practices Bulletin Managing Storm Water Runoff to Prevent Contamination of Drinking Water Storm water runoff is rain or snow melt that flows off the land, from streets, roof tops, and lawns. The runoff carries sediment and contaminants with it to a surface water body or infiltrates through the soil to ground water. This fact sheet focuses on the management of runoff in urban environments; other fact sheets address management measures for other specific sources, such as pesticides, animal feeding operations, and vehicle washing. SOURCES OF STORM WATER RUNOFF Urban and suburban areas are predominated by impervious cover including pavements on roads, sidewalks, and parking lots; rooftops of buildings and other structures; and impaired pervious surfaces (compacted soils) such as dirt parking lots, walking paths, baseball fields and suburban lawns. During storms, rainwater flows across these impervious surfaces, mobilizing contaminants, and transporting them to water bodies. All of the activities that take place in urban and suburban areas contribute to the pollutant load of storm water runoff. Oil, gasoline, and automotive fluids drip from vehicles onto roads and parking lots. Storm water runoff from shopping malls and retail centers also contains hydrocarbons from automobiles. Landscaping by homeowners, around businesses, and on public grounds contributes sediments, pesticides, fertilizers, and nutrients to runoff. Construction of roads and buildings is another large contributor of sediment loads to waterways. In addition, any uncovered materials such as improperly stored hazardous substances (e.g., household Parking lot runoff cleaners, pool chemicals, or lawn care products), pet and wildlife wastes, and litter can be carried in runoff to streams or ground water. -
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. -
Seasonal Flooding Affects Habitat and Landscape Dynamics of a Gravel
Seasonal flooding affects habitat and landscape dynamics of a gravel-bed river floodplain Katelyn P. Driscoll1,2,5 and F. Richard Hauer1,3,4,6 1Systems Ecology Graduate Program, University of Montana, Missoula, Montana 59812 USA 2Rocky Mountain Research Station, Albuquerque, New Mexico 87102 USA 3Flathead Lake Biological Station, University of Montana, Polson, Montana 59806 USA 4Montana Institute on Ecosystems, University of Montana, Missoula, Montana 59812 USA Abstract: Floodplains are comprised of aquatic and terrestrial habitats that are reshaped frequently by hydrologic processes that operate at multiple spatial and temporal scales. It is well established that hydrologic and geomorphic dynamics are the primary drivers of habitat change in river floodplains over extended time periods. However, the effect of fluctuating discharge on floodplain habitat structure during seasonal flooding is less well understood. We collected ultra-high resolution digital multispectral imagery of a gravel-bed river floodplain in western Montana on 6 dates during a typical seasonal flood pulse and used it to quantify changes in habitat abundance and diversity as- sociated with annual flooding. We observed significant changes in areal abundance of many habitat types, such as riffles, runs, shallow shorelines, and overbank flow. However, the relative abundance of some habitats, such as back- waters, springbrooks, pools, and ponds, changed very little. We also examined habitat transition patterns through- out the flood pulse. Few habitat transitions occurred in the main channel, which was dominated by riffle and run habitat. In contrast, in the near-channel, scoured habitats of the floodplain were dominated by cobble bars at low flows but transitioned to isolated flood channels at moderate discharge. -
Modifying Wepp to Improve Streamflow Simulation in a Pacific Northwest Watershed
MODIFYING WEPP TO IMPROVE STREAMFLOW SIMULATION IN A PACIFIC NORTHWEST WATERSHED A. Srivastava, M. Dobre, J. Q. Wu, W. J. Elliot, E. A. Bruner, S. Dun, E. S. Brooks, I. S. Miller ABSTRACT. The assessment of water yield from hillslopes into streams is critical in managing water supply and aquatic habitat. Streamflow is typically composed of surface runoff, subsurface lateral flow, and groundwater baseflow; baseflow sustains the stream during the dry season. The Water Erosion Prediction Project (WEPP) model simulates surface runoff, subsurface lateral flow, soil water, and deep percolation. However, to adequately simulate hydrologic conditions with significant quantities of groundwater flow into streams, a baseflow component for WEPP is needed. The objectives of this study were (1) to simulate streamflow in the Priest River Experimental Forest in the U.S. Pacific Northwest using the WEPP model and a baseflow routine, and (2) to compare the performance of the WEPP model with and without including the baseflow using observed streamflow data. The baseflow was determined using a linear reservoir model. The WEPP- simulated and observed streamflows were in reasonable agreement when baseflow was considered, with an overall Nash- Sutcliffe efficiency (NSE) of 0.67 and deviation of runoff volume (Dv) of 7%. In contrast, the WEPP simulations without including baseflow resulted in an overall NSE of 0.57 and Dv of 47%. On average, the simulated baseflow accounted for 43% of the streamflow and 12% of precipitation annually. Integration of WEPP with a baseflow routine improved the model’s applicability to watersheds where groundwater contributes to streamflow. Keywords. Baseflow, Deep seepage, Forest watershed, Hydrologic modeling, Subsurface lateral flow, Surface runoff, WEPP. -
Influence of a Waterfall Over Richness and Similarity in Adjoining Pools Of
Acta Limnologica Brasiliensia, 2010, vol. 22, no. 4, p. 378-383 doi: 10.4322/actalb.2011.003 Influence of a waterfall over richness and similarity in adjoining pools of an Atlantic Rainforest stream Influência de uma queda d’água sobre a riqueza e a similaridade de dois remansos em um rio da Mata Atlântica Biological LimnologyBiological Célio Roberto Jönck¹ and José Marcelo Rocha Aranha² ¹Avaliação e Monitoramento Ambiental, Centro de Pesquisas Leopoldo Américo Miguez de Melo, CEP 21941-915, Rio de Janeiro, RJ, Brazil e-mail: [email protected] ²Laboratório de Ecologia de Rios, Universidade Federal do Paraná – UFPR, Campus Palotina, Rua 24 de Junho, 698, CEP 85950-000, Palotina, PR, Brazil e-mail: [email protected] Abstract: Aim: The main goal of the study was to determine the effect of the Morato Fall in the richness and composition of the aquatic animal community; Methods: We compared faunal richness and similarity in four substrate samples from two pools separated by a waterfall in the Morato River, southern Brazil; Results: The richness was not significantly different, although the upstream pool had 72 taxa and the downstream one just 65. On the other hand, composition was poorly similar, just a 36.5% similarity between the two sites; Conclusions: That indicates a strong influence of the waterfall, mainly on organisms which spent its entire life cycle on the water, such as fish and small crustaceans. That allow aquatic insects, a group with airborne adult phase and, therefore, able to disperse up to the upstream pool, to evolve with less predatory pressure, becoming the top group in the food web of this environment. -
Surface Water
Chapter 5 SURFACE WATER Surface water originates mostly from rainfall and is a mixture of surface run-off and ground water. It includes larges rivers, ponds and lakes, and the small upland streams which may originate from springs and collect the run-off from the watersheds. The quantity of run-off depends upon a large number of factors, the most important of which are the amount and intensity of rainfall, the climate and vegetation and, also, the geological, geographi- cal, and topographical features of the area under consideration. It varies widely, from about 20 % in arid and sandy areas where the rainfall is scarce to more than 50% in rocky regions in which the annual rainfall is heavy. Of the remaining portion of the rainfall. some of the water percolates into the ground (see "Ground water", page 57), and the rest is lost by evaporation, transpiration and absorption. The quality of surface water is governed by its content of living organisms and by the amounts of mineral and organic matter which it may have picked up in the course of its formation. As rain falls through the atmo- sphere, it collects dust and absorbs oxygen and carbon dioxide from the air. While flowing over the ground, surface water collects silt and particles of organic matter, some of which will ultimately go into solution. It also picks up more carbon dioxide from the vegetation and micro-organisms and bacteria from the topsoil and from decaying matter. On inhabited watersheds, pollution may include faecal material and pathogenic organisms, as well as other human and industrial wastes which have not been properly disposed of. -
Estimation of Surface Runoff Using NRCS Curve Number in Some Areas in Northwest Coast, Egypt
E3S Web of Conferences 167, 02002 (2020) https://doi.org/10.1051/e3sconf/202016702002 ICESD 2020 Estimation of surface runoff using NRCS curve number in some areas in northwest coast, Egypt Mohamed E.S1. Abdellatif M.A1. Sameh Kotb Abd-Elmabod2, Khalil M.M.N.3 1 National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt 2 Soil and Water Use Department, Agricultural and Biological Research Division, National Research Centre, Cairo 12622, Egyp 3 Soil Science Department, Faculty of Agriculture, Zagazig University, Zagazig, Egypt. Abstract. The sustainable agricultural development in the northwest coast of Egypt suffers constantly from the effects of surface runoff. Moreover, there is an urgent need by decision makers to know the effects of runoff. So the aim of this work is to integrate remote sensing and field data and the natural resource conservation service curve number model (NRCS-CN).using geographic information systems (GIS) for spatial evaluation of surface runoff .CN approach to assessment the effect of patio-temporal variations of different soil types as well as potential climate change impact on surface runoff. DEM was used to describe the effects of slope variables on water retention and surface runoff volumes. In addition the results reflects that the magnitude of surface runoff is associated with CN values using NRCS-CN model . The average of water retention ranging between 2.5 to 3.9m the results illustrated that the highest value of runoff is distinguished around the urban area and its surrounding where it ranged between 138 - 199 mm. The results show an increase in the amount of surface runoff to 199 mm when rainfall increases 200 mm / year. -
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 -
Biogeochemical and Metabolic Responses to the Flood Pulse in a Semi-Arid Floodplain
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by DigitalCommons@USU 1 Running Head: Semi-arid floodplain response to flood pulse 2 3 4 5 6 Biogeochemical and Metabolic Responses 7 to the Flood Pulse in a Semi-Arid Floodplain 8 9 10 11 with 7 Figures and 3 Tables 12 13 14 15 H. M. Valett1, M.A. Baker2, J.A. Morrice3, C.S. Crawford, 16 M.C. Molles, Jr., C.N. Dahm, D.L. Moyer4, J.R. Thibault, and Lisa M. Ellis 17 18 19 20 21 22 Department of Biology 23 University of New Mexico 24 Albuquerque, New Mexico 87131 USA 25 26 27 28 29 30 31 present addresses: 32 33 1Department of Biology 2Department of Biology 3U.S. EPA 34 Virginia Tech Utah State University Mid-Continent Ecology Division 35 Blacksburg, Virginia 24061 USA Logan, Utah 84322 USA Duluth, Minnesota 55804 USA 36 540-231-2065, 540-231-9307 fax 37 [email protected] 38 4Water Resources Division 39 United States Geological Survey 40 Richmond, Virginia 23228 USA 41 1 1 Abstract: Flood pulse inundation of riparian forests alters rates of nutrient retention and 2 organic matter processing in the aquatic ecosystems formed in the forest interior. Along the 3 Middle Rio Grande (New Mexico, USA), impoundment and levee construction have created 4 riparian forests that differ in their inter-flood intervals (IFIs) because some floodplains are 5 still regularly inundated by the flood pulse (i.e., connected), while other floodplains remain 6 isolated from flooding (i.e., disconnected). -
River Incision Into Bedrock: Mechanics and Relative Efficacy of Plucking, Abrasion and Cavitation
River incision into bedrock: Mechanics and relative efficacy of plucking, abrasion and cavitation Kelin X. Whipple* Department of Earth, Atmospheric, and Planetary Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 Gregory S. Hancock Department of Geology, College of William and Mary, Williamsburg, Virginia 23187 Robert S. Anderson Department of Earth Sciences, University of California, Santa Cruz, California 95064 ABSTRACT long term (Howard et al., 1994). These conditions are commonly met in Improved formulation of bedrock erosion laws requires knowledge mountainous and tectonically active landscapes, and bedrock channels are of the actual processes operative at the bed. We present qualitative field known to dominate steeplands drainage networks (e.g., Wohl, 1993; Mont- evidence from a wide range of settings that the relative efficacy of the gomery et al., 1996; Hovius et al., 1997). As the three-dimensional structure various processes of fluvial erosion (e.g., plucking, abrasion, cavitation, of drainage networks sets much of the form of terrestrial landscapes, it is solution) is a strong function of substrate lithology, and that joint spac- clear that a deep appreciation of mountainous landscapes requires knowl- ing, fractures, and bedding planes exert the most direct control. The edge of the controls on bedrock channel morphology. Moreover, bedrock relative importance of the various processes and the nature of the in- channels play a critical role in the dynamic evolution of mountainous land- terplay between them are inferred from detailed observations of the scapes (Anderson, 1994; Anderson et al., 1994; Howard et al., 1994; Tucker morphology of erosional forms on channel bed and banks, and their and Slingerland, 1996; Sklar and Dietrich, 1998; Whipple and Tucker, spatial distributions. -
Estimation of the Base Flow Recession Constant Under Human Interference Brian F
WATER RESOURCES RESEARCH, VOL. 49, 7366–7379, doi:10.1002/wrcr.20532, 2013 Estimation of the base flow recession constant under human interference Brian F. Thomas,1 Richard M. Vogel,2 Charles N. Kroll,3 and James S. Famiglietti1,4,5 Received 28 January 2013; revised 27 August 2013; accepted 13 September 2013; published 15 November 2013. [1] The base flow recession constant, Kb, is used to characterize the interaction of groundwater and surface water systems. Estimation of Kb is critical in many studies including rainfall-runoff modeling, estimation of low flow statistics at ungaged locations, and base flow separation methods. The performance of several estimators of Kb are compared, including several new approaches which account for the impact of human withdrawals. A traditional semilog estimation approach adapted to incorporate the influence of human withdrawals was preferred over other derivative-based estimators. Human withdrawals are shown to have a significant impact on the estimation of base flow recessions, even when withdrawals are relatively small. Regional regression models are developed to relate seasonal estimates of Kb to physical, climatic, and anthropogenic characteristics of stream-aquifer systems. Among the factors considered for explaining the behavior of Kb, both drainage density and human withdrawals have significant and similar explanatory power. We document the importance of incorporating human withdrawals into models of the base flow recession response of a watershed and the systemic downward bias associated with estimates of Kb obtained without consideration of human withdrawals. Citation: Thomas, B. F., R. M. Vogel, C. N. Kroll, and J. S. Famiglietti (2013), Estimation of the base flow recession constant under human interference, Water Resour.