Integrated Modeling of Regional Basins:

Thirteen Years of Hard Lesson Learned

Mark A. Ross, Patrick D. Tara, and Jeffrey S. Geurink

University of South Florida

Integrated Model: Coupled Comprehensive Surface-

Groundwater Model

(Specifically: Experience with coupled HSPF-MODFLOW model known as FHM, ISGW, or IHM)

PrecipitationTranspiration

Evaporation

Baseflow

Runoff

Water Table

Infiltration &Percolation

Interflow

Leakage

Interception

Impervious Lens

Surface water storages & stream

flowsGroundwater Flow

Aquitard (Confining Unit)Confined or Artesian Aquifer

Unconfined Aquifer

Evaporation

Bays, Gulf, and Oceans

Hydrologic Cycle Process Coupling

1. DTWT2. Hydr. heads (streams, wetlands & lakes)3. Base flow4. SW/GW ET5. Irrigation fluxes6. Variable SY(vadose moist.)

FHM (HSPF/MODFLOW) Integration Pathways

FHM Chronology 1989 FHM development 1993 FHM ver 1.2 used in mine reclamation 1995 ISGW proprietary version used for public water supply

investigations, FHM District-scale application 1995-1997 FHM peer-reviewed, adapted for USFWS water rights

investigations 1995-1998 period of W-C Fl water wars, numerous models 1997-2000 several FHM version updates for regional W-C Fl

regional investigations, ISGW peer reviewed 2001-2002 major re-write of FHM/ISGW->IHM (Interra,

Aquaterra, USF)

Early Problems(Limitations)

Computers (286s) Model components (HSPF & MODFLOW) Data utilities (GIS, database programs) Digital data (no digital quads) Client perspectives/interest (“recharge

generator”) User acceptance (“too much time & money”)

Consequence: Limited Discretization

R 18 W

R 18 W

R 17 W

R 17 W

R 16 W

R 16 W

T11N

Lake Havasu

River

95

N

Bill Williams National Wildlife Refuge

IMPERIALNATIONAL WILDLIFE

REFUGE

T

T

1

S

S

2

R 24 W R 23 WR 21 E

N

Cibola National Wildlife Refuge

T 16 N

T 15 N

R 16 E R 17 E

N

Las Vegas National

Wildlife Refuge

Rattlesnake Creek Study

Model Simulation Results Rattlesnake Creek

USFWS ApplicationsLessons Learned

Need does not justify model where there is no data Streamflow separation (runoff/baseflow) very

important to do but problematic Component pre-calibration very important Size and discretization barriers remained Need much better data utilities

Mid 90s “Water Wars”West-Central Florida

Many model applications, similar stream flow performance & gross ET, wildly varying resultant models (recharge), conclusions

Wide variability in model parameterization resulted from inadequate data, understanding and characterization of processes

Need for detailed basin-scale study, tie down internal fluxes and storages

Near Field Model

10 0 10 20 30 40 50 60 Miles

Hydrography

No Flow BoundaryGeneral Head Boundary

Saddle Creek Basin OutlineDistgen.shp

Saddle Creek Study

(Data Collection, Far-field and Near-

field Models)

N

EW

S

Saddle Creek Gauging Stations

Station 17 Calibration

0

20

40

60

80

100

120 F

lo

w (c

fs

)

Oct-96Apr-97Oct-97Apr-98Oct-98Apr-99Date

Obs. Streamflow

Sim. Streamflow

Station 17b Calibration

0

5

10

15

20

In

ch

es

Oct-96 Apr-97 Oct-97 Apr-98 Oct-98 Apr-99

Date

Obs. Streamflow

Obs. Baseflow

Sim. Streamflow

Sim. Baseflow

Saddle Creek StudyLessons Learned

Extensive basin-scale data collection helped refine model calibration and resultant internal fluxes

Real important to characterize time/space scale of rainfall

Needed to understand the mechanism of runoff, especially role of variable saturated areas (VSAs)

Variable specific yield (SY) very important process

30 0 30 60 Miles

Coastline

BasinsUngagedGaged

Stream/Lake

N

SWFWMD Southern

District Model

HSPF,MODFLOW pre-calibration,1st phase of integrated model

SWFWMD Southern District ModelLessons Learned

Importance of including all hydrography explicitly Strong parameterization and model performance

constraints by DTWT resulted in greatly improved calibration (streamflow and aquifer behavior)

Indicated much higher GW ET fraction in shallow watertable settings than previously considered – resulting in model concept changes

Importance of irrigation fluxes and deep aquifer discharges zones

Alafia Subbasins

N

EW

S

Statecounties_poly.shp

Land UseUrbanAg/Rec IrrigatedGrass/PastureForrestedOpen WaterWetlandsMining/Other

Subbasins

Alafia Subbasins and Land Use

9000 0 9000 18000 Meters

Alafia ModelLesson

Need to explicitly characterize connected and unconnected hydrography for each basin

Depart from basin calibration, move to land use calibration

Alafia Micro-Scale Field StudyPreliminary Results

Runoff dominated by saturation excess (VSAs) Air entrapment plays a strong role Water table fluctuations are very rapid Baseflow timescale may be controlled by ET timescale not

water table drainage SY is highly variable (.2 – 2 m) controlling water table

fluctuation Vadose zone moisture maintenance pronounced, thus

significant GW ET (watertable depths < 2 m)

New IHM Model Developments

New code integration structure, HSPF and MODFLOW run concurrently, greatly enhanced capability and enhanced run speed

Integration and all other timesteps completely user defined

Landforms explicitly modeled (more distributed parameterization)

Old Model Structure

New Model Structure

Legend

Land Use

Urban

Irrigated/Rec

Grassland/Pasture

Forested

Open Water

Wetlands

Mining/Other

0 1 20.5 Miles

TBW Connected &Unconnected Hydrography

DICRETIZATIONMODFLOW:20,000 grids (1/4 mi)150,000 river reaches3 aquifer layersHSPF:172 non-connected reaches172 storage attenuation73 routing reaches172 basins5 landform categories 320,000 landuse polygons

zo = 0

Zone 1: Upper ConstantMoisture Region

Zone 2: IntermediateCapillary Zone

Zone 3: LowerCapillary Fringe

DryProfile

WetProfile

EquilibriumProfile

zcz

zcf

zwt

Three Layer Soil Moisture Model

(z)

b)a) c)

D1

D2, icz

D3, cf

z

zrz

Three-Layer Soil Moisture Model

Important Spatial & Temporal Scales(Shallow Aquifer Coastal Plain Systems)

Rainfall

Runoff flow plain Infiltration

1 km2

102 m

102 m

5-15 min.

5-15 min.

5-15 min.

ET: Surface

Vadoze

Water table

102 m Horizontal

.1 – 3 m Vertical

3 m V

hourly

daily

Daily

Rchg: Vadose zone

Surficial

Confined

0.1-2 m

102 mH, 1 mV,

103 mH, 10-102 mV

1-24 hrs.

1-24 hrs.

Wkly

Other: Stream base flow

GW Pumping sens.

Landuse change sens.

103 m

Vars.

Vars.

daily – season

daily

1-5 years

Overall Conclusions & Recommendations

Understand the hydrologic processes and water budget magnitudes before beginning

Ensure adequate data to support model Commit to the data pre-analysis Understand the limitations and long-term

commitments Attention to internal fluxes and storages will

ensure fully constrained, unique solution

Integrated Model Commitments

Enormous data requirementsComplete surface water datasetComplete groundwater datasetData pertaining to the integration

Different timescales and space scales Considerable data analysis prior to calibration More difficulty in calibration Users must possess both SW and GW expertise

ZLS

ZRZZCFZWT

ZCZ

(c) Root zone capillary fringe (ZWT ZRZ < ZCF)

(a) Deep water table (ZWT < ZCF ZRZ)

ZLS

ZRZ

ZCFZWT

ZCZ

(b) Capillary interaction (ZWT < ZCF Zrz)

ZLS

ZRZZCFZWT

ZCZ

(d) Root zone water table ( ZRZ < ZWT; ZCZ ZLS)

ZLS

ZRZ

ZCFZWT

ZCZ

(e) Capillary zone at land surface (ZCF ZLS ZCZ)

ZLS

ZRZ

ZCF

ZWT

Figure 1 a-f: Six cases for vadose zone soil moisture condition.

ZLS

ZRZ

ZWT

(f) Capillary fringe at land surface (ZWT ZLS ZCF)

Root Capillary Zone