Comparative Review of Integrated Groundwater and Surface Water Models

June 21, 2011

Acknowledgements

Ontario Ministry of Natural Resources Mike Garraway Lynne Milford

DHI Water and Environment Patrick Delaney Ying Qiao Doug Graham

Alberta Innovates Dr. Jon Paul Jones

S.S. Papadopulos and Associates Chris Neville

AquaResource Inc. David Van Vliet Steven Murray Christian Gabriel

Comparative Review of Integrated Groundwater and Surface Water Models

Prepared by:AquaResource Inc.DHI Water and EnvironmentAlberta InnovatesS.S. Papadopulos and Associates

Prepared for: The Ontario Ministry of Natural Resources

Summary of Report• Compare available

codes based on theory, numerical methods, and user experience

• GSFLOW*• HydroGeoSphere*• MikeSHE**• ModHMS• Parflow

• Ontario case studies. * Subwatershed 19 (Credit River)** Mill Creek Subwatershed (Grand River)

• Recommended modelling methods and procedures

• Release Summer 2011

Conjunctive Modelling – Why? Conventional surface water or

groundwater models don’t always reflect natural systems Simplifying assumptions made for either

groundwater or surface water portions of model.

Interpretation and quantification of interaction between surface water and groundwater system difficult.

The value of conventional models is reflected by the hydrological processes represented by those models

Traditional methods are not well suited to cumulative impact assessment. Unless physical processes are not well represented, marginal and incremental change prediction is uncertain

Conjunctive Models Considered

Model Developer Hydrologic Processes

GSFLOW (MODFLOW + PRMS)

United States Geological Survey

Physical & Empirical,Semi-distributed

Hydrogeosphere (HGS)

University of Waterloo and

Laval University

Physical,Fully Distributed

MIKE SHE DHI Water & Environment

Physical and EmpiricalFully or semi-distributed

Model Evaluation GSFLOW (USGS) Based on well

established and accepted modelling codes (PRMS + MODFLOW)

Supported by USGS Open source, free No dynamic stream

routing, no overland flow routing

Soil water balance and runoff calculations highly empirical

Daily timesteps

Model Evaluation – HydroGeoSphere (HGS) (University of Waterloo)

Variable finite element mesh resolution, excellent mass balance

Sophisticated subsurface model: 3D Richards representation

of unsaturated zone. Variable saturated

groundwater flow as well as Limited hydrologic processes

(snowmelt, soil water balance, interflow)

long run times

Model Evaluation – MIKE SHE (DHI Water and Environment)

Highly flexible, full GUI interface

Empirical and physical representations of hydrologic processes

Sophisticated post processing

Reasonable run times DHI support Uniform finite difference

mesh

Examples of Model Comparison Criteria

Watershed

Processes

•Rainfall

•Snowmelt

•ET•Overland Flow

•Seasonal Parameters

Vadose Zone

•Soil Moisture•Infiltration, Percolation, Recharge

Groundwater

•Lumped vs numerical

•Boundary conditions

•Fractures

•Macropores

•Water takings

Surface Water

•Channel flow

•Pipe flow

•Lakes

•Flooding

•Dams and reservoirs

•Diversions

•Irrigation

•Erosion and Sediment

•Water takings

Other

•Numerical solution parameters•GIS support•GUI•Tech support•Training

Mill CreekGrand River Watershed

Subwatershed 19Credit River Watershed

Case Studies Objectives

Compare models Explore and demonstrate benefits of integrated models over

traditional approaches Develop recommended practices and methods

Case Study: Credit Valley Subcatchment 19

Case Study: Credit Valley Subcatchment 19 Headwaters of the Credit River - Approximately 60 km2 Land use: urban, agriculture, wetlands, aggregate. Issues:

Municipal drinking water supply (groundwater) Wastewater assimilation Streamflow quality and quantity

Existing studies: Subwatershed Study (CVC) Tier Three Water Quantity Risk Assessment (MNR, municipalities) Island Lake Water Budget Study

Existing Models HSPF, GAWSER (Surface Water) MODFLOW, FEFLOW (Groundwater)

Integrated Models Provide Realistic ET Predictions

Groundwater Recharge Predictions Influenced by Soils, Vegetation, Topography, Discharge

Groundwater Discharge Into Wetlands Simulated Without Boundary Conditions

Streamflow Impact Assessment

0.01

0.10

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Flow

(m3 /

s)

Month

Flow Distribution for Lower Monora Creek - MIKE-SHEBaseline vs Combined Impact Scenario

Pre-Impact Interquartile Range Post-Impact Interquartile Range Upper/Lower DecilePre-Impact Median Flow Post-Impact Median Flow

Mill Creek Subwatershed

Description of the Subwatershed Covers an area of roughly 100 km2 and is situated

between the Galt-Paris moraines. The headwaters of Mill Creek are located southeast of

Guelph, where Mill Creek flows southwest, joining the Grand River in downtown Cambridge (Galt).

Land cover within Mill Creek is predominantly agriculture, with forests and wetlands comprising the majority of the remaining land area.

Mill Creek supports cold-water fisheries, rich wetlands, and also has extensive aggregate production facilities within the watershed.

Mill Creek Subwatershed Land Cover

Calibration – Mike SHE Represents Low Flows Very Well. GW/SW Interactions Critical

01-Jan-04 01-Mar-04 01-May-04 01-Jul-04 01-Sep-04 01-Nov-040

1

2

3

4

5

6

7

Simulated Discharge Observed Discharge

Dis

charg

e (

m3/s

)

Variable ET Across Watershed, Influenced by Landuse, Wetlands, Aggregate Extraction

Groundwater Discharge Critical Along Streams, Wetlands and Hillslopes

Simulated Soil Moisture Reflects Delineated Wetlands

Seasonal Soil Moisture Variability in Wetlands

Conclusions Benefits of Integrated Models over Traditional Models

Integrating groundwater and surface water models removes traditional assumptions (recharge, boundary conditions)

Realistic water budgets (ET, Influence of Topography) Groundwater / surface water interactions (Wetlands, Hillslopes, Hummocky Areas)

better handled Physically-based continuous low flow predictions – needed for ecological flow

assessments Data requirements are similar to traditional approaches

Limitations Computational Time – It can be manageable Calibration Time – Reduced with experience Urban Systems – Manage technical expectations Learning Curve – Training requirements are significant

Success requires both surface water and groundwater modelling expertise Costs are marginally extra than traditional methods but the results are much

more meaningful