Runoff Risk Advisory Forecast (RRAF) for Wisconsin

Similar documents
Interest in a Community Model for Operational Delta Forecasting

Stanley J. Woodcock, Michael Thiemann, and Larry E. Brazil Riverside Technology, inc., Fort Collins, Colorado

Climate Change, Precipitation Trends and Water Quality David S. Liebl

Ithaca Area Intermunicipal Cooperation NYAWWA Conference. Chris Bordlemay Padilla Cornell University Water Manager 4/27/17

Edge-of-Field Monitoring

MMEA, WP5.2.7 Mining Deliverable D

The Impacts of Climate Change on Portland s Water Supply

Introduction. Welcome to the Belgium Study Abroad Program. Courses:

IPCC WG II Chapter 3 Freshwater Resources and Their Management

Trends in Illinois River Streamflow and Flooding

Spring Nutrient Flux to the Gulf of Mexico and Nutrient Balance in the Mississippi River Basin

Runoff Processes. Daene C. McKinney

The Performance of Satellite Precipitation Products for Water Resources Applications in the Upper Blue Nile Basin

2

Minnesota River Basin Interagency Study

Annual Stream Runoff and Climate in Minnesota s River Basins

Iowa Climate Change Adaptation and Resilience: Applying Climate Data to Plans & Ordinances

NREM 407/507 WATERSHED MANAGEMENT

Lecture 9A: Drainage Basins

Chehalis Basin Strategy Causes of Extreme Flooding. October 11, 2016 Policy Workshop

Salt Dynamics in prairie wetlands under changing climate

Error Analysis and Data Quality

NOAA S NATIONAL WATER CENTER

Modeling Nutrient and Sediment Losses from Cropland D. J. Mulla Dept. Soil, Water, & Climate University of Minnesota

Response Planning for Drought and Flood Events

SCOTT RIVER HYDROLOGY AND INTEGRATED SURFACE WATER / GROUNDWATER MODELING

Rock Creek Floodplain Analysis

Alabama Department of Agriculture & Industries. Commissioner John McMillan

Developing BMP s to Minimize the Water Quality Impacts of Winter Manure Spreading - Amendment

Vegetation Management and Water Yield: Silver Bullet or a Pipe Dream?

PRECIPITATION-RUNOFF MODELING USING ARTIFICIAL NEURAL NETWORKS AND CONCEPTUAL MODELS

Definitions 3/16/2010. GG22A: GEOSPHERE & HYDROSPHERE Hydrology

Simulation of Climate Change Impact on Runoff Using Rainfall Scenarios that Consider Daily Patterns of Change from GCMs

PROCEEDINGS 2017 Crop Pest Management Short Course & Minnesota Crop Production Retailers Association Trade Show

Effects of climate change and agricultural adaptation on nitrogen loading from Finnish watersheds simulated by VEMALA model

ADVANCED APPLICATIONS OF HEC-HMS

Addressing Groundwater Quality in Karst Regions

Uncertainty in Hydrologic Modelling for PMF Estimation

Influence of spatial and temporal resolutions in hydrologic models

Analysis & Comments. Livestock Marketing Information Center State Extension Services in Cooperation with USDA. National Hay Situation and Outlook

CLIMATE CHANGE EFFECTS ON THE WATER BALANCE IN THE FULDA CATCHMENT, GERMANY, DURING THE 21 ST CENTURY

Nutrient Management in. A presentation to the West Metro Water Alliance

SOIL P-INDEXES: MINIMIZING PHOSPHORUS LOSS. D. Beegle, J. Weld, P. Kleinman, A. Collick, T. Veith, Penn State & USDA-ARS

Model Diagnostics. How to evaluate and improve a model. CIVE 781: Principles of Hydrologic Modelling University of Waterloo Jun 19 24, 2017

Objective 1: Manage the demonstration site using common agricultural practices and monitor runoff quantity and quality.

MODELING SEDIMENT AND PHOSPHORUS YIELDS USING THE HSPF MODEL IN THE DEEP HOLLOW WATERSHED, MISSISSIPPI

Determining Soil Moisture and Temperature Condition Effects on Potential Run-Off for Cold Season Manure Application

Climate Change & Urbanization Have Changed River Flows in Ontario

Florida s Deranged Hydrology and the National Water Model Challenges and Opportunities

Climate Change Impact on Pastures and Livestock Systems in Kyrgyzstan

Inclusion of climate aspects in the implementation of the Water Framework Directive - Challenges and prospects from an increasingly wet Norway

Great Lakes Update. Volume 189: 2013 January through June Summary

NOAA National Water Model: Big Voluminous Data Challenges

OVERVIEW OF RESERVOIR OPERATIONS AND FLOOD RISK MANAGEMENT

Re-plumbing Roadside Ditch Networks

Environmental Flows: What, why, case studies and more

ESTIMATION OF CLIMATE CHANGE IMPACT ON WATER RESOURCES BY USING BILAN WATER BALANCE MODEL

Long-Term Agro-Ecosystem Research Network University of Wisconsin-Platteville Pioneer Farm Research

New Zealand Drought Index and Drought Monitor Framework

NRCS Progress in the Great Lakes Basin (Past, Present and Future)

M.L. Kavvas, Z. Q. Chen, M. Anderson, L. Liang, N. Ohara Hydrologic Research Laboratory, Civil and Environmental Engineering, UC Davis

Setting the Course for Improved Water Quality: Modeling for TMDL Studies

The Science Behind Quantifying Urban Forest Ecosystem Services. David J. Nowak USDA Forest Service Northern Research Station Syracuse, NY, USA

FLOW AND PRECIPITATION MONITORING

To 4R or Not to 4R Is There an Option?

fcgov.com/water-quality Water Quality Update Summer 2017 Monitoring and Protecting Our Water Sources

New York City s Operations Support Tool (OST) Delaware River Basin RFAC Meeting December 14, 2010

Topics Background Findings Recommendations

Nitrate Load Reduction Strategies for the Raccoon and Des Moines Rivers. Keith Schilling, Calvin Wolter Iowa DNR Geological and Water Survey

CEE3430 Engineering Hydrology

Preparing Stormwater Systems for Climate Change October 10 th, 2013 Monroe, MI. Leslie Yetka, Education Manager

Climate Change Impacts in Washington State

Event and Continuous Hydrological Modeling with HEC- HMS: A Review Study

Here is an overview of the material I will present over the next 20 minutes or so. We ll start with statistics, move on to physics, and look at

Pre/Post Assessment Rubric for Unit: Urban Storm Hydrograph Modeling with the Rational Method for the Urban Desert Southwest USA

History of Model Development at Temple, Texas. J. R. Williams and J. G. Arnold

ICF Propane Inventory Update and Winter 2014/15 Supply Assessment

The Fourth Assessment of the Intergovernmental

Flood risk management and land use planning in changing climate conditions Mikko Huokuna Finnish Environment Institute, SYKE

3.0 MANAGEMENT ISSUES AND RECOMMENDATIONS

Culvert Sizing procedures for the 100-Year Peak Flow

THE EFFECTS OF CLIMATE CHANGE ON THE HYDROLOGY AND WATER RESOURCES OF THE COLORADO RIVER BASIN

Climate change science, knowledge and impacts on water resources in South Asia

The national-level nutrient loading estimation tool for Finland: Watershed Simulation and Forecasting System WSFS-Vemala

Joint Research Centre (JRC)

USING ARCSWAT TO EVALUATE EFFECTS OF LAND USE CHANGE ON WATER QUALITY. Adam Gold Geog 591

WATER USES and AVAILABLE RESOURCES

Hydrology for Folsom Dam Water Control Manual Update

D C Le Maitre & D F Scott. Programme for Land-use and Hydrology Forestek CSIR Private Bag X5011 Stellenbosch.

Urbanization effects on the hydrology of the Atlanta area, Georgia (USA)

Lower Ohio and Middle Mississippi Rivers Flood Management

Keeping it Green and Growing: An Aerial Seeding Concept

Scientific Consensus Statement on the Likely Impacts of Climate Change on the Pacific Northwest. Executive Summary

Memorandum. To: From: Date: July 10, Cc: Re: Introduction. to control. This time. primarily. excavated

An Environmental Accounting System to Track Nonpoint Source Phosphorus Pollution in the Lake Champlain Basin. Year 2 Project Work Plan

City of Portsmouth Department of Public Works

Transcription:

Runoff Risk Advisory Forecast (RRAF) for Wisconsin Development & Production of a Real-Time Decision Support System for Wisconsin Manure Producers Dustin Goering North Central River Forecast Center (NCRFC) 2013 AWRA Spring Specialty Conference Agricultural Hydrology & Water Quality II St. Louis, MO

What is the NCRFC? and Water Quality? North Central River Forecast Center is 1 of 13 RFCs Covers 341,000 mi 2 over 9 states Staff of 19 responsible for 426 forecast points Real-time modeling of 1,173 sub-watersheds ranging from 6 3,061 mi 2 Primary focus is streamflow and river stage forecasts

What is the NCRFC? and Water Quality? North Central River Forecast Center is 1 of 13 RFCs Covers 341,000 mi 2 over 9 states Staff of 19 responsible for 426 forecast points Real-time modeling of 1,173 sub-watersheds ranging from 6 3,061 mi 2 Primary focus is streamflow and river stage forecasts NWS Strategic Plan Focus on helping decision makers where weather & water forecasts can have effect Address water quality not just quantity Leverage existing capabilities in new ways

RRAF Project Motivation Problem :: Excess contaminated field runoff can degrade water quality Well contamination, fish kills, Gulf of Mexico hypoxic zone, Great Lakes water/beach quality Important Issue 1.25 million Wisconsin dairy cows 34 million tons of waste annually Best Management Practices / Nutrient Management Plans focus on how & where Wisconsin Dept. Agriculture, Trade, and Consumer Protection (DATCP) Tasked to create advisory & notification system for state

RRAF Project Motivation Problem :: Excess contaminated field runoff can degrade water quality Well contamination, fish kills, Gulf of Mexico hypoxic zone, Great Lakes water/beach quality Important Issue 1.25 million Wisconsin dairy cows 34 million tons of waste annually Best Management Practices / Nutrient Management Plans focus on how & where Wisconsin Dept. Agriculture, Trade, and Consumer Protection (DATCP) Tasked to create advisory & notification system for state Goal :: Reduce nutrient loss in field runoff entering water bodies Utilize existing NWS weather & watershed modeling in water quality application Collaboration opportunity with federal, state, and university partners Complement BMPs/NMPs & producer knowledge Doesn t replace farmers responsibility

RRAF Project Motivation Problem :: Excess contaminated field runoff can degrade water quality Well contamination, fish kills, Gulf of Mexico hypoxic zone, Great Lakes water/beach quality Important Issue 1.25 million Wisconsin dairy cows 34 million tons of waste annually Best Management Practices / Nutrient Management Plans focus on how & where Wisconsin Dept. Agriculture, Trade, and Consumer Protection (DATCP) Tasked to create advisory & notification system for state Goal :: Reduce nutrient loss in field runoff entering water bodies Utilize existing NWS weather & watershed modeling in water quality application Collaboration opportunity with federal, state, and university partners Complement BMPs/NMPs & producer knowledge Doesn t replace farmers responsibility Action :: Focus on largest unknown When (when not) to Spread Warn when future runoff risk is high delay application reduce contaminated runoff Integrate land-atmosphere system for 10 day forecast more than is it going to rain tomorrow? Before this, no real-time guidance currently existed to aid decision process for producers

What is the RRAF? Derived from NCRFC operational models Lumped Snow-17 & Sacramento Soil Moisture Accounting Model (SAC-SMA) Incorporates 5 days future precip, 10 days future temps Issued 3x a day with forecast window out 10 days Event Based :: 3 conditions must be met SAC-SMA Interflow runoff > 0 SAC-SMA Upper Zone Tension Water Deficit = 0 Snow-17 Rain + snowmelt > 0 Forecast Precip & Temps NCRFC Soil & Snow Models Simulated Runoff Events DATCP Processing

What is the RRAF? Derived from NCRFC operational models Lumped Snow-17 & Sacramento Soil Moisture Accounting Model (SAC-SMA) Incorporates 5 days future precip, 10 days future temps Issued 3x a day with forecast window out 10 days Event Based :: 3 conditions must be met SAC-SMA Interflow runoff > 0 SAC-SMA Upper Zone Tension Water Deficit = 0 Snow-17 Rain + snowmelt > 0 Event list sent to DATCP They process events with thresholds Display risk on webpage they built and maintain Forecast Precip & Temps NCRFC Soil & Snow Models Simulated Runoff Events DATCP Processing

What is the RRAF? Derived from NCRFC operational models Lumped Snow-17 & Sacramento Soil Moisture Accounting Model (SAC-SMA) Incorporates 5 days future precip, 10 days future temps Issued 3x a day with forecast window out 10 days Event Based :: 3 conditions must be met SAC-SMA Interflow runoff > 0 SAC-SMA Upper Zone Tension Water Deficit = 0 Snow-17 Rain + snowmelt > 0 Event list sent to DATCP They process events with thresholds Display risk on webpage they built and maintain End Product Webpage indicating basin Low Med High runoff risk Available for 216 NWS watersheds in Wisconsin Forecast Precip & Temps NCRFC Soil & Snow Models Simulated Runoff Events DATCP Processing

What is the RRAF? Derived from NCRFC operational models Lumped Snow-17 & Sacramento Soil Moisture Accounting Model (SAC-SMA) Incorporates 5 days future precip, 10 days future temps Issued 3x a day with forecast window out 10 days Event Based :: 3 conditions must be met SAC-SMA Interflow runoff > 0 SAC-SMA Upper Zone Tension Water Deficit = 0 Snow-17 Rain + snowmelt > 0 Event list sent to DATCP They process events with thresholds Display risk on webpage they built and maintain End Product Webpage indicating basin Low Med High runoff risk Available for 216 NWS watersheds in Wisconsin Forecast Precip & Temps NCRFC Soil & Snow Models Simulated Runoff Events DATCP Processing Decision Support Regulatory Tool

Project Challenges Obvious Scale Difference Between Fields & NWS models Average NWS basin in Wisconsin = 301 mi 2 (9 1,800 mi 2 ) Using conceptual, lumped models calibrated for peak streamflow

Project Challenges Obvious Scale Difference Between Fields & NWS models Average NWS basin in Wisconsin = 301 mi 2 (9 1,800 mi 2 ) Using conceptual, lumped models calibrated for peak streamflow Communicate Assumptions to Users Not only information available for basing decisions This tool will never produce perfect prediction everywhere Combine local condition knowledge with forecast One farm may have runoff, the next one may not Rainfall and snowpack distribution, field aspect, etc.

Project Challenges Obvious Scale Difference Between Fields & NWS models Average NWS basin in Wisconsin = 301 mi 2 (9 1,800 mi 2 ) Using conceptual, lumped models calibrated for peak streamflow Communicate Assumptions to Users Not only information available for basing decisions This tool will never produce perfect prediction everywhere Combine local condition knowledge with forecast One farm may have runoff, the next one may not Rainfall and snowpack distribution, field aspect, etc. Long-term Success Dependent on: Will RRAF accurately predict average field scale conditions and runoff risk? Users build trust in the RRAF fewer contamination incidents?

RRAF Validation Compare observed & simulated historical runoff events 4 Edge-of-Field (EOF) sites 0.03 mi 2 vs. 230 mi 2 [0.01% NWS basin area] 7 Small USGS gauged Watersheds 15.9 mi 2 vs. 294 mi 2 [5.41% NWS basin area] Basin specific thresholds differentiate moderate and high risk

RRAF Validation Compare observed & simulated historical runoff events 4 Edge-of-Field (EOF) sites 0.03 mi 2 vs. 230 mi 2 [0.01% NWS basin area] 7 Small USGS gauged Watersheds 15.9 mi 2 vs. 294 mi 2 [5.41% NWS basin area] Basin specific thresholds differentiate moderate and high risk EOF Results Moderate & High Risk :: Hit = 80% Miss = 20% False Alarm = 71% High Risk :: Hit = 64% Miss = 36% False Alarm = 48%

RRAF Validation Compare observed & simulated historical runoff events 4 Edge-of-Field (EOF) sites 0.03 mi 2 vs. 230 mi 2 [0.01% NWS basin area] 7 Small USGS gauged Watersheds 15.9 mi 2 vs. 294 mi 2 [5.41% NWS basin area] Basin specific thresholds differentiate moderate and high risk EOF Results Moderate & High Risk :: Hit = 80% Miss = 20% False Alarm = 71% USGS Results Moderate & High Risk :: Hit = 62% Miss = 38% False Alarm = 45% High Risk :: High Risk :: Hit = 64% Hit = 41% Miss = 36% Miss = 59% False Alarm = 48% False Alarm = 19%

RRAF Validation Continued Average Both Scales Moderate & High Risk :: Hit = 71% Miss = 29% False Alarm = 58% High Risk :: Hit = 53% Miss = 47% False Alarm = 34%

RRAF Validation Continued Average Both Scales Moderate & High Risk :: Hit = 71% Miss = 29% False Alarm = 58% High Risk :: Hit = 53% Miss = 47% False Alarm = 34% Encouraging results overall However, for High Risk: hits and misses while false alarms What is being missed? Should increased misses cause concern? RRAF captures largest events while misses are much smaller in magnitude High Risk Hit/Miss Event Ratio = 9.6 Moderate & High Risk Hit/Miss Event Ratio = 7.7

RRAF Validation Continued Average Both Scales Moderate & High Risk :: Hit = 71% Miss = 29% False Alarm = 58% High Risk :: Hit = 53% Miss = 47% False Alarm = 34% Encouraging results overall However, for High Risk: hits and misses while false alarms What is being missed? Should increased misses cause concern? RRAF captures largest events while misses are much smaller in magnitude High Risk Hit/Miss Event Ratio = 9.6 Moderate & High Risk Hit/Miss Event Ratio = 7.7 Long-term behavior for all 216 basins over 50 year simulation :: Percent Time No Event simulated = 90% Percent Time Moderate Risk = 4% Percent Time High Risk = 6%

RRAF 2011 Verification Compare Edge-of-Field (EOF) runoff vs. Forecasts for 2011 9 Edge-of-Field sites in 4 NWS basins 0.03 mi 2 vs. 433 mi 2 [0.007% NWS basin area!] September December was unusually warm with much below snowpack in southern ⅔ of WI No observed runoff events past early September

RRAF 2011 Verification Compare Edge-of-Field (EOF) runoff vs. Forecasts for 2011 9 Edge-of-Field sites in 4 NWS basins 0.03 mi 2 vs. 433 mi 2 [0.007% NWS basin area!] September December was unusually warm with much below snowpack in southern ⅔ of WI No observed runoff events past early September Verification Results Moderate & High Risk :: Hit = 77% Miss = 23% False Alarm = 66% High Risk :: Hit = 74% Miss = 26% False Alarm = 54% Hit/Miss Ratio remains high = 10.2

RRAF Webpage Clickable basin interface overlaid on Google map Side bar with additional information How-to documentation, links to soil temps, state 590 maps Site News Working Group notes passed along to RRAF users

RRAF in Action Normal Mode = (3) 72-hour risk windows Only 1 event required in that time-frame to activate Highest risk wins (High > Moderate)

RRAF in Action Normal Mode = (3) 72-hour risk windows Only 1 event required in that time-frame to activate Highest risk wins (High > Moderate) Winter Mode uses entire 10-day forecast period Only uses High Risk or Winter Mode Snowmelt generated runoff indicated by hash-marks

RRAF in Action Normal Mode = (3) 72-hour risk windows Only 1 event required in that time-frame to activate Highest risk wins (High > Moderate) Winter Mode uses entire 10-day forecast period Only uses High Risk or Winter Mode Snowmelt generated runoff indicated by hash-marks Clickable Basins provide more forecast detail More forecast details to be provided to users in future

RRAF in Action Normal Mode = (3) 72-hour risk windows Only 1 event required in that time-frame to activate Highest risk wins (High > Moderate) Winter Mode uses entire 10-day forecast period Only uses High Risk or Winter Mode Snowmelt generated runoff indicated by hash-marks Clickable Basins provide more forecast detail More forecast details to be provided to users in future Positive reviews from surveys so far (0-10) Technical quality of product = 7.5 Ease of use = 7.9 Appropriate for NWS to provide this service = 100%

Next Steps Activating smaller secondary threshold to further reduce false alarms Analysis indicates between 6-20% decrease of smallest simulated events Minimal impact on percent of simulated hit events

Next Steps Activating smaller secondary threshold to further reduce false alarms Analysis indicates between 6-20% decrease of smallest simulated events Minimal impact on percent of simulated hit events Product Expansion Collaboration ongoing with Minnesota Department of Agriculture to replicate product in MN

Next Steps Activating smaller secondary threshold to further reduce false alarms Analysis indicates between 6-20% decrease of smallest simulated events Minimal impact on percent of simulated hit events Product Expansion Collaboration ongoing with Minnesota Department of Agriculture to replicate product in MN Continually briefing other agencies on the RRAF Very positive feedback from varied audiences on the product concept and application NCRFC eager to work with other states and universities in the future Open to have other partners expand and improve product different models?

Next Steps Activating smaller secondary threshold to further reduce false alarms Analysis indicates between 6-20% decrease of smallest simulated events Minimal impact on percent of simulated hit events Product Expansion Collaboration ongoing with Minnesota Department of Agriculture to replicate product in MN Continually briefing other agencies on the RRAF Very positive feedback from varied audiences on the product concept and application NCRFC eager to work with other states and universities in the future Open to have other partners expand and improve product different models? Summer 2013 Begin investigating capability of new model SAC-HTET (Heat Transfer & Evapotranspiration) Distributed model on 4-km grid

Questions? Dustin Goering dustin.goering@noaa.gov Brian Connelly Steve Buan brian.connelly@noaa.gov steve.buan@noaa.gov RRAF : http://www.manureadvisorysystem.wi.gov/app/runoffrisk NCRFC: http://www.crh.noaa.gov/ncrfc/