Comparisons of Simulation Results Using the NWS Hydrology Laboratory's Research Modeling System (HL-RMS) Hydrology Laboratory Office of Hydrologic Development.

Slides:

Advertisements

Similar presentations

COMPARISON OF MEAN AREAL PRECIPITATION ESTIMATES FROM WSR-88D AND HISTORICAL GAGE NETWORKS OVER CHEAT RIVER BASIN, WV David Wang, Michael Smith, D.J. Seo.

Advertisements

Modelling the rainfall-runoff process

NWS Calibration Workshop, LMRFC March, 2009 Slide 1 Sacramento Model Derivation of Initial Parameters.

Rainfall-Runoff Modeling

Hydrological Modeling for Upper Chao Phraya Basin Using HEC-HMS UNDP/ADAPT Asia-Pacific First Regional Training Workshop Assessing Costs and Benefits of.

Lucinda Mileham, Dr Richard Taylor, Dr Martin Todd

International Centre for Integrated Mountain Development Kathmandu, Nepal Mandira Singh Shrestha Satellite rainfall application in the Narayani basin CORDEX.

Kinematic Routing Model and its Parameters Definition.

Distributed Hydrologic Model-Threshold Frequency (DHM-TF) Reggina Cabrera NOAA/National Weather Service Eastern Region

A Distributed Flash Flood Forecasting Rainfall- Runoff Model Applied to Watersheds in the Northeast United States Michael Schaffner NOAA National Weather.

Colorado Basin River Forecast Center Water Supply Forecasting Method Michelle Stokes Hydrologist in Charge Colorado Basin River Forecast Center April 28,

Calibration Mike Smith, Victor Koren, Zhengtao Cui, Seann Reed, Fekadu Moreda DOH Science Conference July 17, 2008.

1 Calibration of HL-RDHM Lecture 4b. 2 Calibration of SAC Parameters with Scalar Multipliers Use of scalar multipliers (assumed to be uniform over a basin)

6/3/2010 ER FFG Conference An Overview of Gridded Flash Flood Guidance; A Spatially Distributed Runoff and Threshold-Runoff Based Approach Erick Boehmler.

ABSTRACT One of the large challenges in data assimilation (DA) into distributed hydrologic models is how to reduce the degrees of freedom in the inverse.

A Statistical-Distributed Hydrologic Model for Flash Flood Forecasting International Workshop on Flash Flood Forecasting March 13, 2006 Seann Reed 1, John.

Patrick Broxton (University of Arizona) Michael Schaffner (National Weather Service) Peter Troch (University of Arizona) Dave Goodrich (USDA–ARS–SWRC)

Discussion and Future Work With an explicit representation of river network, CHARMS is capable of capturing the seasonal variability of streamflow, although.

Hydrologic Modeling: Verification, Validation, Calibration, and Sensitivity Analysis Fritz R. Fiedler, P.E., Ph.D.

ELDAS Case Study 5100: UK Flooding

August 20th, CONTENT 1. Introduction 2. Data and Characteristics 3. Flood analysis 1. MOUSE 2. SOBEK 3. ARC-SWAT 4. Conclusions and suggestions.

Streamflow Predictability Tom Hopson. Conduct Idealized Predictability Experiments Document relative importance of uncertainties in basin initial conditions.

1 Mike Smith, Victor Koren, Ziya Zhang, Brian Cosgrove, Zhengtao Cui, Naoki Mizukami OHD/HL Hydrologic Science and Modeling Branch Introduction Lecture.

Hydrology Laboratory Research Modeling System (HL-RMS) Introduction: Office of Hydrologic Development National Weather Service National Oceanic and Atmospheric.

Preliminary Applications of the HL-RDHM within the Colorado Basin River Forecast Center Ed Clark, Hydrologist Presented July 26 th, 2007 as part of the.

1 Brian Cosgrove Collaborators: Seann Reed, Michael Smith, Feng Ding, Yu Zhang, Zhengtao Cui, Ziya Zhang NOAA/NWS/OHD Brian Cosgrove Collaborators: Seann.

1 OHD/HL Distributed Hydrologic Modeling Pedro Restrepo Hydrology Group HIC Conference Jan , 2006.

Applications of the NWS Research Distributed Hydrologic Model in Operational Hydrology The Colorado Basin River Forecast Center (CBRFC), an office of NOAA’s.

Gridded Rainfall Estimation for Distributed Modeling in Western Mountainous Areas 1. Introduction Estimation of precipitation in mountainous areas continues.

Overview of the Colorado Basin River Forecast Center Lisa Holts.

Variational Assimilation (VAR) Presented by: Jerry Nunn Hydrologist In Charge West Gulf River Forecast Center October 28, 2003.

Eric Jones Senior Hydrologist Lower Mississippi River Forecast Center 89 th AMS Meeting.

Team 10 Presentation Vol. II 18th February 2011 Sophia Antipolis, France Improvement by calibration or with geometry?

A Soil-water Balance and Continuous Streamflow Simulation Model that Uses Spatial Data from a Geographic Information System (GIS) Advisor: Dr. David Maidment.

1 Integrating Water Resources Engineering and Geographic Information Systems (GIS) National Weather Service NWSRFS International Workshop October 21-23,

Hydrologic Modeling on a 4km Grid over the Conterminous United States (CONUS) 1. INTRODUCTION The Hydrology Laboratory (HL) of the NOAA/National Weather.

Introduction to the TOPMODEL

Arkansas Red Basin River Forecast Center An Operational Forecast Office Perspective of the National Weather Service Hydrologic Distributed Modeling System.

Preliminary Applications of the HL-RDHM within the Colorado Basin River Forecast Center Ed Clark, Hydrologist Presented July 26 th, 2007 as part of the.

Application of DHSVM to Hydrologically Complex Regions as Part of Phase 2 of the Distributed Model Intercomparison Project Erin Rogers Dennis Lettenmaier.

Parameterisation by combination of different levels of process-based model physical complexity John Pomeroy 1, Olga Semenova 2,3, Lyudmila Lebedeva 2,4.

LMRFC March, 2009 Calibration at Finer Time and Space Scales.

Introduction to Urban Hydrology

FY07 Hydro Group Proposals to AHPS SLF Theme Team Mike Smith October 12, 2006.

Hydrologic Objects for Modeling: One Viewpoint Thomas A. Evans US Army Corps of Engineers Hydrologic Engineering Center.

1 DHM: Operational Distributed Hydrologic Model Lecture 5 DHM/HL-RDHM Workshop ABRFC June 5 -7, 2007 Lee Cajina OHD/HL Hydrologic Software Engineering.

Performance Comparison of an Energy- Budget and the Temperature Index-Based (Snow-17) Snow Models at SNOTEL Stations Fan Lei, Victor Koren 2, Fekadu Moreda.

TEAM 1 st Topic Presentation, Friday 18 th February 2011 Polytech’Nice - Sophia I NTEREST OF DISTRIBUTED HYDROLOGICAL MODELS ( Mike SHE & HEC-HMS.

MRC-MDBC STRATEGIC LIAISON PROGRAM BASIN DEVELOPMENT PLANNING TRAINING MODULE 3 SCENARIO-BASED PLANNING for the MEKONG BASIN Napakuang, Lao PDR 8-11 December.

TRANSITION FROM LUMPED TO DISTRIBUTED SYSTEMS Victor Koren, Michael Smith, Seann Reed, Ziya Zhang NOAA/NWS/OHD/HL, Silver Spring, MD.

Automatic Calibration of HSPF model with NEXRAD rainfall data for DMIP Jae Ryu Hydrologist, National Drought Mitigation Center University of Nebraska Lincoln,

Overview of CBRFC Flood Operations Arizona WFOs – May 19, 2011 Kevin Werner, SCH.

Modeling of a Watershed Basic Calibration Workshop LMRFC March 10-13, 2009 slide 1.

Basic Hydrology: Rainfall-runoff based methods – III

BUILDING AND RUNNING THE HYDROLOGICAL MODEL

EF5: A hydrologic model for prediction, reanalysis and capacity building Zachary Flamig Postdoctoral Scholar.

Digital model for estimation of flash floods using GIS

Application of soil erosion models in the Gumara-Maksegnit watershed

Change in Flood Risk across Canada under Changing Climate

Approaches to Continental Scale River Flow Routing

Looking for universality...

Rainfall-Runoff Modeling

Utah Water Research Laboratory

Introduction to Urban Hydrology

Hydrologic River Routing

USING NUMERICAL PREDICTED RAINFALL DATA FOR A DISTRIBUTED HYDROLOGICAL MODEL TO ENHANCE FLOOD FORECAST: A CASE STUDY IN CENTRAL VIETNAM Nguyen Thanh.

Elaine B. Darby GIS – Fall 2005

Overview of Models & Modeling Concepts

HEC-HMS Runoff Computation Modeling Direct Runoff with HEC-HMS Empirical models Empirical models - traditional UH models - traditional UH models - a.

Hydrologic modeling of Waller Creek

Presentation transcript:

Comparisons of Simulation Results Using the NWS Hydrology Laboratory's Research Modeling System (HL-RMS) Hydrology Laboratory Office of Hydrologic Development National Weather Service/NOAA Ziya Zhang, Victor Koren, Seann Reed, Michael Smith, and David Wang HYDROLOGY LABORATORY, OHD/NWS/NOAA

What is HL-RMS? A Research Modeling System being developed by researchers in the Hydrology Laboratory, Office of Hydrologic Development, NWS/NOAA. Modeling framework for testing lumped, semi- distributed, and fully-distributed hydrologic modeling approaches.  

HYDROLOGY LABORATORY, OHD/NWS/NOAA HL-RMS Components Pre-simulation: Determines connectivity matrix Derives SAC parameters Derives routing parameters Simulation: Simulates rainfall/runoff for each grid (SAC,...) Conducts hillslope and channel routing Computes hydrographs  

HYDROLOGY LABORATORY, OHD/NWS/NOAA HL-RMS Capabilities Ingests NEXRAD Stage III xmrg data Uses lumped or distributed model parameters Uses lumped or distributed precipitation Computes hydrographs at any interior points Selection between lumped, semi-distributed, and fully distributed modes     

HYDROLOGY LABORATORY, OHD/NWS/NOAA HL-RMS Capabilities cont. Output Arc/Info grids for selected variables Flexible to modify gridded parameters Modular design to test other models Computational element: NEXRAD 4km HRAP grid    

HYDROLOGY LABORATORY, OHD/NWS/NOAA Test Basin Blue River Basin Oklahoma Missouri Kansas Arkansas Texas Area: 1233 km 2 Blue River Basin, OK

HYDROLOGY LABORATORY, OHD/NWS/NOAA Test Runs   Lumped parameters from manual calibration, lumped forcing Distributed parameters, distributed forcing Scaled distributed parameters, distributed forcing  Continuous Simulation from 1993 to 2000 Scale factor was based on comparing a calibrated value of a basin to an averaged value of gridded values of that basin

HYDROLOGY LABORATORY, OHD/NWS/NOAA Samples of Gridded Parameters

HYDROLOGY LABORATORY, OHD/NWS/NOAA Test Results Distributed Channel Runoff Channel Runoff (cms) November 7, :00 outlet

HYDROLOGY LABORATORY, OHD/NWS/NOAA November 7, :00 - 8:00 Test Results Rainfall & Surface Runoff

HYDROLOGY LABORATORY, OHD/NWS/NOAA Test Results Interior Points Basin Outlet A B C

HYDROLOGY LABORATORY, OHD/NWS/NOAA Basin Outlet A B C Test Results Interior Points

HYDROLOGY LABORATORY, OHD/NWS/NOAA outlet Total Precipitation (mm) An Event in 1994 Test Results Hydrograph Comparison

HYDROLOGY LABORATORY, OHD/NWS/NOAA outlet Total Precipitation (mm) An Event in 1995 Test Results Hydrograph Comparison

HYDROLOGY LABORATORY, OHD/NWS/NOAA outlet Total Precipitation (mm) An Event in 1996 Test Results Hydrograph Comparison

HYDROLOGY LABORATORY, OHD/NWS/NOAA An Event in 1997 outlet Total Precipitation (mm) Test Results Hydrograph Comparison

HYDROLOGY LABORATORY, OHD/NWS/NOAA outlet Total Precipitation (mm) An Event in 1998 Test Results Hydrograph Comparison

HYDROLOGY LABORATORY, OHD/NWS/NOAA outlet Total Precipitation (mm) An Event in 1999 Test Results Hydrograph Comparison

HYDROLOGY LABORATORY, OHD/NWS/NOAA Observations Simulations using HL-RMS in distributed mode without any calibration effort yields better results than calibrated lumped simulations at most times Distributed modeling yields much better results for events where rainfall has big variation across a basin Distributed simulation results are better when the SAC parameters are scaled based on calibrated parameters   

HYDROLOGY LABORATORY, OHD/NWS/NOAA Rainfall distribution has the biggest effect on differences between lumped and distributed simulations Derived gridded rainfall-runoff and routing parameters are reasonably good Use of only gridded parameters yields higher peaks in hydrographs Recession part of simulated hydrographs is off the most compared to observed discharges Observations cont.    

HYDROLOGY LABORATORY, OHD/NWS/NOAA Observations cont.  HL-RMS is a workable and a flexible research tool to study hydrologic processes, and to test the sensitivity of model parameters and input forcing on simulations