Urbanization impacts on the hydrometeorology in the Upper Great

Lakes Region

Some brief results for the overview paper

General picture

• Study the relative impact of infiltration changes (urban land cover increase) and weather change (convective precipitation) on hydrologic response in the Upper Great Lakes Region.

• Three Land Use/ Land Cover maps used:

projected year 2010 map from LTM, projected year 2030 map from LTM, and no urban map, created by removing urban and rescaling other veg fractions in 2010 map.

• The RAMS model simulates the meteorological conditions (precipitation and temperature) corresponding to the three land cover maps during the storm event (6/21/2006 ~ 6/23/2006)

• The VIC model simulates the runoff (discharge) production from different land cover and weather scenarios

Impervious surface area (ISA) percentage at 12 km grid scale for two land cover maps and their difference

RAMS precipitation (prec) spatial map

2010 -> 2030 changes are opposite to no urban -> 2010.

FP_NOURB

0. 4

0. 6

0. 8

1. 0

1. 2

1. 4

1. 6

FRAC_2010

0 10 20 30 40 50 60 70

Prec ratio vs. ISA

FP_2030

0. 4

0. 6

0. 8

1. 0

1. 2

1. 4

1. 6

I SA_Df adj

0 10 20 30 40

fp_nourb vs. 2010 ISA percentage fp_2030 vs. (2030-2010) ISA percentage

No relationship between prec ratio and ISA fraction for all grids;

Largest precipitation changes do not necessarily occur in cells with

higher impervious area or highest change in impervious area

RAMS temperature (temp) spatial map

RAMS temperature (temp) spatial map

2010 -> 2030 changes are opposite to no urban -> 2010,

but not as pronounced as precipitation

FT_NOURB

0. 980

0. 985

0. 990

0. 995

1. 000

1. 005

1. 010

1. 015

1. 020

FRAC_2010

0 10 20 30 40 50 60 70

FT_2030

0. 980

0. 985

0. 990

0. 995

1. 000

1. 005

1. 010

1. 015

1. 020

I SA_Df adj

0 10 20 30 40

Temp ratio vs. ISA

ft_nourb vs. 2010 ISA percentage ft_2030 vs. (2030-2010) ISA percentage

No relationship between temp ratio and ISA fraction for all grids;

Largest temperature changes do not necessarily occur in cells with

higher impervious area or highest change in impervious area

ISA fraction for LC 2010 RAMS prec for LC 2010

Similar spatial plots but in the HUC8 watershed scale in the four states domain

prec ratio for 2030/2010prec ratio for 2010/no-urban

Bias correction for prec and temp

Bias correction for 2010 scenario:Tcorr2010 = Trams2010 + [Tvic(ave) – Trams2010(ave)]Pcorr2010 = Prams2010 * [Pvic(total) / Prams2010(total)]

Bias correction for 2030 scenario:Tcorr2030 = Trams2030 + [Tvic(ave) - Trams2010(ave)]Pcorr2030 = Prams2030 * [Pvic(total) / Prams2010(total)]

Bias correction for no-urban (nou) scenario:Tcorr_nou = Tnou + [Tvic(ave) - Trams2010(ave)]Pcorr_nou = Pnou * [Pvic(total) / Prams2010(total)]

RAMS prec before/after correction, and observed prec

RAMS temp before/after correction, and observed prec

Five different scenarios for the VIC model simulation

Meteorology (bias corrected)

Nourb 2010 2030

LC maps

Nourb nourbanall ①2010 2010nourb ② 2010 ③ 2030 ④

2030 2030all ⑤

Test the impact of different factors on runoff

•Vertical difference: impervious impact only (with same weather: prec and temp)

e.g. 2010nourb – nourbanall, 2030all - 2030

•Horizontal difference: weather impact only (with same LC)

e.g. 2010 - 2010nourb, 2030 - 2010nourb, 2030 - 2010

•Diagonal difference: both urban and weather impact

e.g. 2010 - nourbanall, 2030all - 2010

prec changesinfiltration

restriction

Runoff spatial maps at grid scale (urban impact)

• A. (2010nourb – nourball) vs. (ISA2010): R2 = 0.59

• 2010nourb - nourball: runoff difference was only caused by urban representation in 2010 LC (with same nourb weather)

• B. (2030all - 2030) vs. ΔISA(2030LC-2010LC); R2 = 0.74

• 2030all - 2030: runoff difference was caused by urban representation in 2030 and 2010 LC maps (with same 2030 urban weather)

Runoff vs. ISATest the relationship between ISA fraction and increased runoff

working on grids with ISA fraction >= 0.05 (less than 600 grids)

f r o_nou

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

ext _ I SA10

0. 0 0. 1 0. 2 0. 3 0. 4 0. 5 0. 6 0. 7

f r o_2030

0

1

2

3

4

5

6

7

8

di _ ext i sa

0. 0 0. 1 0. 2 0. 3 0. 4 0. 5 0. 6

A B

Runoff ratio vs. ISARunoff ratio: runoff/ precipitation

working on grids with ISA fraction >= 0.05, and precipitation > 0

A. RO2010/P2010 vs. ISA2010: R2 = 0.98RO2010: runoff from 2010 scenario (with 2010 urban and weather)

B. RO2030all/P2030 vs. ISA2030: R2 = 0.99RO2030all: runoff from 2030all scenario (with 2030 urban and weather)

RO2010r at i o

0. 0

0. 1

0. 2

0. 3

0. 4

0. 5

0. 6

0. 7

0. 8

ext _ I SA10

0. 0 0. 1 0. 2 0. 3 0. 4 0. 5 0. 6 0. 7

RO2030r at i o

0. 0

0. 1

0. 2

0. 3

0. 4

0. 5

0. 6

0. 7

0. 8

ext _ I SA30

0. 0 0. 1 0. 2 0. 3 0. 4 0. 5 0. 6 0. 7

BA

Runoff spatial maps at grid scale (prec impact)

All three figures are based on same 2010 LC map

2030urb impact 2010 urb and prec impact 2030 urb and prec impact

Runoff spatial maps (both urban and prec impact)

Runoff (RO) spatial ratio maps at HUC8 scale

(RO2010nou - ROnourb)/ (RO2010 - ROnourb)

(RO2010nou - ROnourb)/ (RO2030 - ROnourb)

Relative impact of urban (weather) on runoff

ISA fraction for LC 2010 (RO2030 - ROnourb)/ (RO2010 - ROnourb)

2030 weather vs. 2010 weather

White

Muskegon

Hydrograph for four delineated watershedsFor the storm event during 6/21/2006 ~ 6/23/2006

Hydrograph for White and Muskegon River

• Overall, the bias corrected 2010nourban, 2010 and 2030 weather scenarios yield very similar discharge during the storm event (with same 2010 LC map).

• The hydrograph shows a great increased discharge from no urban, 2010, to 2030 LC maps (with increasing urban fraction).

• Means restricting infiltration rate has a dominating contribution to the increased discharge in the storm event, and the modified precipitation from different LC maps do not have much impact on the discharge.

Grand

Kankakee

Hydrograph for four delineated watersheds

Wind direction impact on prec (downwind vs. upwind)

Four urban regions: Milwaukee, Muskegon + Grand, Chicago, White

Wilcoxon rank-sum test: fp_nourb (prec ratio 2010/nourban),

then fp_2030 (prec ratio 2030/2010)

1. White Riverfp_nou (P2010/ P2010nou): downwind fp_nou is significantly larger than upwind at 0.01 significance levelfp_2030 (P2030/P2010): opposite 2. Chicagofp_nou (P2010/ P2010nou): downwind fp_nou > upwind at 0.01 significance levelfp_2030 (P2030/P2010): not significant3. Milwafp_nou (P2010/ P2010nou): downwind fp_nou > upwind at 0.05 significance levelfp_2030 (P2030/P2010): opposite 4. Muskegon (+ Grand Rapids)All grids can be considered as the downwind group because of the two cities and the W (SW) wind direction from the lake.fp_nou > 1 at 0.01 significance levelfp_2030 < 1 at 0.01 significance level

Wind direction impact on prec (downwind vs. upwind)

VIC model calibration/validation

Table 3. Monthly NSE for calibration and evaluation periods.

Watersheds Calibration (1986 ~ 1996)

Evaluation (1996 ~ 2006)

CHIPP 0.40

MUSKE 0.49

GRAND 0.56

KANKA 0.75

WHITE 0.79

LWABA 0.69

Need other LC map or use short time period to do calibration/ evaluation?

Thank you!

Suggestions?