Modifying Wepp to Improve Streamflow Simulation in a Pacific Northwest Watershed
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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. -
Adapting the Water Erosion Prediction Project (WEPP) Model for Forest Applications
Journal of Hydrology 366 (2009) 46–54 Contents lists available at ScienceDirect Journal of Hydrology journal homepage: www.elsevier.com/locate/jhydrol Adapting the Water Erosion Prediction Project (WEPP) model for forest applications Shuhui Dun a,*, Joan Q. Wu a, William J. Elliot b, Peter R. Robichaud b, Dennis C. Flanagan c, James R. Frankenberger c, Robert E. Brown b, Arthur C. Xu d a Washington State University, Department of Biological Systems Engineering, P.O. Box 646120, Pullman, WA 99164, USA b US Department of Agriculture, Forest Service, Rocky Mountain Research Station, Moscow, ID 83843, USA c US Department of Agriculture, Agricultural Research Service (USDA-ARS), National Soil Erosion Research Laboratory, West Lafayette, IN 47907, USA d Tongji University, Department of Geotechnical Engineering, Shanghai 200092, China article info summary Article history: There has been an increasing public concern over forest stream pollution by excessive sedimentation due Received 11 July 2008 to natural or human disturbances. Adequate erosion simulation tools are needed for sound management Received in revised form 6 December 2008 of forest resources. The Water Erosion Prediction Project (WEPP) watershed model has proved useful in Accepted 12 December 2008 forest applications where Hortonian flow is the major form of runoff, such as modeling erosion from roads, harvested units, and burned areas by wildfire or prescribed fire. Nevertheless, when used for mod- eling water flow and sediment discharge from natural forest watersheds where subsurface flow is dom- Keywords: inant, WEPP (v2004.7) underestimates these quantities, in particular, the water flow at the watershed Forest watershed outlet. Surface runoff Subsurface lateral flow The main goal of this study was to improve the WEPP v2004.7 so that it can be applied to adequately Soil erosion simulate forest watershed hydrology and erosion. -
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). -
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. -
Geothermal Solute Flux Monitoring Using Electrical Conductivity in Major Rivers of Yellowstone National Park by R
Geothermal solute flux monitoring using electrical conductivity in major rivers of Yellowstone National Park By R. Blaine McCleskey, Dan Mahoney, Jacob B. Lowenstern, Henry Heasler Yellowstone National Park Yellowstone National Park is well-known for its numerous geysers, hot springs, mud pots, and steam vents Yellowstone hosts close to 4 million visits each year The Yellowstone Supervolcano is located in YNP Monitoring the Geothermal System: 1. Management tool 2. Hazard assessment 3. Long-term changes Monitoring Geothermal Systems YNP – difficult to continuously monitor 10,000 thermal features YNP area = 9,000 km2 long cold winters Thermal output from Yellowstone can be estimated by monitoring the chloride flux downstream of thermal sources in major rivers draining the park River Chloride Flux The chloride flux (chloride concentration multiplied by discharge) in the major rivers has been used as a surrogate for estimating the heat flow in geothermal systems (Ellis and Wilson, 1955; Fournier, 1989) “Integrated flux” Convective heat discharge: 5300 to 6100 MW Monitoring changes over time Chloride concentrations in most YNP geothermal waters are elevated (100 - 900 mg/L Cl) Most of the water discharged from YNP geothermal features eventually enters a major river Madison R., Yellowstone R., Snake R., Falls River Firehole R., Gibbon R., Gardner R. Background Cl concentrations in rivers low < 1 mg/L Dilute Stream water -snowmelt -non-thermal baseflow -low EC (40 - 200 μS/cm) -Cl < 1 mg/L Geothermal Water -high EC (>~1000 μS/cm) -high Cl, SiO2, Na, B, As,… -Most solutes behave conservatively Mixture of dilute stream water with geothermal water Historical Cl Flux Monitoring • The U.S. -
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. -
Using the Wepp Model to Predict Sediment Yield in a Sample Watershed in Kahramanmaras Region
USING THE WEPP MODEL TO PREDICT SEDIMENT YIELD IN A SAMPLE WATERSHED IN KAHRAMANMARAS REGION Alaaddin YÜKSEL Abdullah E. AKAY Mahmut REİS KSÜ, Orman Fakültesi, Orman Mühendisliği Bölümü, 46060, Kahramanmaraş Recep GÜNDOĞAN KSÜ, Ziraat Fakültesi, Toprak Bölümü, 46060, Kahramanmaraş E-mail: [email protected], [email protected], [email protected], [email protected] ABSTRACT Considerable amount of sediment yield reaches into streams, lakes, and dam reservoirs from 26 major watersheds in Turkey. Several models have been developed to estimate the sediment yield from watersheds. WEPP (Water Erosion Prediction Project) model is one of the most common model which not only predicts the amount of sediment yield but also determines where and when the sediment produc- tion occurs and locates possible deposition places. Besides, the geo-spatial interface for WEPP model (GeoWEPP) can use digital geo-referenced information by integrat- ing with the most common GIS tools ( i.e. ArcView, ArcGIS) . Therefore, watershed managers can decide the most appropriate soil erosion conservation and sediment prevention techniques for a specific watershed based on the WEPP outputs in text or graphical format. The sediment yield from a watershed in Kahramanmaraş region (Ayvalı Dam Watershed) was estimated by using GeoWEPP model. In this study, process of estimating sediment yield from a specific sub watershed located in a for- ested area was presented to indicate the performance of GeoWEPP. This study indi- cated that using GeoWEPP can provide watershed managers with quick estimation of sediment yield from large watersheds in high accuracy. Keywords: WEPP, GeoWEPP, Sedimentation, Dam Watershed, Kahramanmaraş, 12 INTERNATIONAL CONGRESS ON RIVER BASIN MANAGEMENT 1. -
Springs and Springs-Dependent Taxa of the Colorado River Basin, Southwestern North America: Geography, Ecology and Human Impacts
water Article Springs and Springs-Dependent Taxa of the Colorado River Basin, Southwestern North America: Geography, Ecology and Human Impacts Lawrence E. Stevens * , Jeffrey Jenness and Jeri D. Ledbetter Springs Stewardship Institute, Museum of Northern Arizona, 3101 N. Ft. Valley Rd., Flagstaff, AZ 86001, USA; Jeff@SpringStewardship.org (J.J.); [email protected] (J.D.L.) * Correspondence: [email protected] Received: 27 April 2020; Accepted: 12 May 2020; Published: 24 May 2020 Abstract: The Colorado River basin (CRB), the primary water source for southwestern North America, is divided into the 283,384 km2, water-exporting Upper CRB (UCRB) in the Colorado Plateau geologic province, and the 344,440 km2, water-receiving Lower CRB (LCRB) in the Basin and Range geologic province. Long-regarded as a snowmelt-fed river system, approximately half of the river’s baseflow is derived from groundwater, much of it through springs. CRB springs are important for biota, culture, and the economy, but are highly threatened by a wide array of anthropogenic factors. We used existing literature, available databases, and field data to synthesize information on the distribution, ecohydrology, biodiversity, status, and potential socio-economic impacts of 20,872 reported CRB springs in relation to permanent stream distribution, human population growth, and climate change. CRB springs are patchily distributed, with highest density in montane and cliff-dominated landscapes. Mapping data quality is highly variable and many springs remain undocumented. Most CRB springs-influenced habitats are small, with a highly variable mean area of 2200 m2, generating an estimated total springs habitat area of 45.4 km2 (0.007% of the total CRB land area). -
Application of the WEPP Model to Surface Mine Reclamation• By
Application of the WEPP Model to Surface Mine Reclamation• by W. J. Elliot Wu Qiong Annette V. Elliot2 Abstract. Sediment from mining sources contributes to the pollution of surface waters. Restoration of mined sites can reduce the problems associated with erosion, and one of the most important objectives of surface mine reclamation is the control of surface runoff and erosion from reclaimed areas. Current methods for predicting sediment yield do not suit surface mine sites because non- agricultural soils and vegetation are involved. There is a need for a computer model to aid in identifying improved management systems and reclamation practices with suitable input data files and appropriate hydrologic modeling routines. The USDA Water Erosion Prediction Project (WEPP) resulted in the development of a computer model based on fundamental erosion mechanics. The WEPP model will be in widespread use by the mid 1990s by the Soil Conservation Service (SCSI, and will be the erosion prediction model of choice well into the next century. This paper gives an overview of the WEPP erosion prediction technology and its implications to surface mine reclamation, and reports on a research project that identifies critical watershed parameters unique to surface mining and reclamation through a sensitivity analysis of the WEPP Watershed Model. The study contributes to the validation of the WEPP Watershed Version by comparing estimates generated by the model with observed data from watersheds after surface mining. Additional Key Words: Erosion simulation INTRODUCTION control of surface runoff and erosion from reclaimed areas (Mitchell et al., 1983; Hartley As renewable fossil fuel energy reserves are and Schuman, 1984). -
Modeling Phosphorus Transport Using the WEPP Model Mario Perez-Bidegain Iowa State University
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Digital Repository @ Iowa State University Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 2007 Modeling phosphorus transport using the WEPP model Mario Perez-Bidegain Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Agriculture Commons, Agronomy and Crop Sciences Commons, Bioresource and Agricultural Engineering Commons, Environmental Sciences Commons, and the Soil Science Commons Recommended Citation Perez-Bidegain, Mario, "Modeling phosphorus transport using the WEPP model" (2007). Retrospective Theses and Dissertations. 15497. https://lib.dr.iastate.edu/rtd/15497 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Modeling phosphorus transport using the WEPP model by Mario Perez-Bidegain A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Co-majors: Soil Science (Soil Management); Environmental Science Program of Study Committee: Richard M. Cruse, Co-major Professor Matthew J. Helmers, Co-major Professor Brian K. Hornbuckle Robert Horton John M. Laflen Iowa State University Ames, Iowa 2007 Copyright © Mario Perez-Bidegain, 2007. All rights reserved. UMI Number: 3259439 UMI Microform 3259439 Copyright 2007 by ProQuest Information and Learning Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. -
Wepp Model Applications for Evaluations of Best Management Practices
WEPP MODEL APPLICATIONS FOR EVALUATIONS OF BEST MANAGEMENT PRACTICES D.C. FLANAGAN 1, W.J. ELLIOT 2, J.R. FRANKENBERGER 3, C. HUANG 4 1USDA-Agricultural Research Service, National Soil Erosion Research Laboratory, 275 S. Russell Street, West Lafayette, Indiana, USA, 47907. Phone: +01 765-494- 8673, FAX: +01 765-494-5948, email: [email protected] 2USDA-Forest Service, Rocky Mountain Research Station, 1221 S. Main St., Moscow, ID, USA. 83843. Phone: +01 208-883-2338, FAX: +01 208-883-2318, email: [email protected] 3USDA-Agricultural Research Service, National Soil Erosion Research Laboratory, 275 S. Russell Street, West Lafayette, Indiana, USA, 47907. Phone: +01 765-494- 8673, FAX: +01 765-494-5948, email: [email protected] 4USDA-Agricultural Research Service, National Soil Erosion Research Laboratory, 275 S. Russell Street, West Lafayette, Indiana, USA, 47907. Phone: +01 765-494- 8673, FAX: +01 765-494-5948, email: [email protected] Summary The Water Erosion Prediction Project (WEPP) model is a process-based erosion prediction technology for application to small watersheds and hillslope profiles, under agricultural, forested, rangeland, and other land management conditions. Developed by the United States Department of Agriculture (USDA) over the past 25 years, WEPP simulates many of the physical processes that are important when estimating runoff, soil erosion, and sediment delivery at a location having unique climate, topography, soils, and plants/tillage/management. A variety of user interfaces and databases make the model very easy to apply and use, particularly within the United States. The USDA Agricultural Research Service (ARS) has developed a stand-alone Windows WEPP system, as well as internet web-based hillslope and GIS watershed interfaces. -
WEPP Model Be Improved to Allow Access to Sub-Daily Time Scale Results So That It Can Be Better Integrated with Other Watershed Models
A COUPLED UPLAND-EROSION AND INSTREAM HYDRODYNAMIC-SEDIMENT TRANSPORT MODEL FOR EVALUATING SEDIMENT TRANSPORT IN FORESTED WATERSHEDS W. J. Conroy, R. H. Hotchkiss, W. J. Elliot ABSTRACT. This article describes a prototype modeling system for assessing forest management-related erosion at its source and predicting sediment transport from hillslopes to stream channels and through channel networks to a watershed outlet. We demonstrate that it is possible to develop a land management tool capable of accurately assessing the primary impacts of spatiotemporally varied forest management practices on sediment yield and delivery at hillslope to watershed scales in a single simulation. The modeling system consists of four components: (1) the TOpographic ParameteriZation (TOPAZ) model for discretizing hillslope and channel elements, (2) the Water Erosion Prediction Project (WEPP) model for evaluating hillslope-scale surface erosion processes, (3) the National Center for Computational Hydrodynamics and Engineering’s one-dimensional (CCHE1D) hydrodynamic-sediment transport model, and (4) an interface program to manage relational databases and data transfer between modules. The coupled models were calibrated and validated with observed flow and sediment load data from the North Fork Caspar Creek Experimental Watershed in coastal northern California. The coupled models’ predictions of peak flow rate and total flow volume were not significantly different from observed values. Predicted sediment concentrations were significantly different from observed values, but within typical ranges for sediment transport equations. We recommend that the WEPP model be improved to allow access to sub-daily time scale results so that it can be better integrated with other watershed models. Keywords. Erosion modeling, Hydrodynamic modeling, Watershed models, TMDLs, CCHE1D, WEPP.