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Hydrology of Walnut Gulch, Arizona Unearthing a First-Order Approximate Correlation Between Regional Hydrology and Extent of Vegetative Land Cover
Hydrology of Walnut Gulch, Arizona
Unearthing a First-Order Approximate Correlation Between Regional Hydrology and
Extent of Vegetative Land Cover
Why Relate Hydrology and Vegetation?
• Energy Transfer in an Ecosystem begins with Primary Producers
• Plants need Water…• Hydrologic Cycle dictates the sustainability of
an Ecosystem
Methodology
• Select model ecosystem• Select easily quantifiable hydrologic variables• Construct an “Average Hydrologic Year” model• Quantify Vegetative Land Cover• Correlate the average hydrologic year with the
vegetative land cover
Model Ecosystem
• Desert– RELATIVELY simple ecosystem– Most vegetation low shrub
• Walnut Gulch is VERY well documented
http://www.tucson.ars.ag.gov/dap/DAPveg/default.htm
Hydrologic Variables
• Precipitation– Easy to Measure– Easy to Average over watershed area
• Atmospheric Moisture– Easy to Measure and Average over watershed
• Soil Moisture– Difficult to Measure over any extent– Highly Heterogeneous over watershed area
Annual Rainfall Data in 20-min Intervals11
/25/
2003
0:0
0
1/14
/200
4 0:
00
3/4/
2004
0:0
0
4/23
/200
4 0:
00
6/12
/200
4 0:
00
8/1/
2004
0:0
0
9/20
/200
4 0:
00
11/9
/200
4 0:
00
12/2
9/20
04 0
:00
2/17
/200
5 0:
00
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.82004 Rainfall Data - 20 min intervals
Rain
fall
(in)
Annual Daily Cumulative Rainfall11
/25/
2003
1/14
/200
4
3/4/
2004
4/23
/200
4
6/12
/200
4
8/1/
2004
9/20
/200
4
11/9
/200
4
12/2
9/20
04
2/17
/200
5
0
0.2
0.4
0.6
0.8
1
1.22004 Daily Cumulative Rainfall
Rain
fall
(in)
10-yr Average Rainfall Year
3-Dec 22-Jan 13-Mar 2-May 21-Jun 10-Aug 29-Sep 18-Nov 7-Jan 26-Feb0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
10-yr Average Daily Cummulative Rainfall
Same Process for Atmospheric Moisture25
-Nov
14-Ja
n
4-M
ar
23-A
pr
12-Ju
n
1-Au
g
20-S
ep
9-No
v
29-D
ec
17-F
eb
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1.4%
10-yr Daily Average Atmospheric Moisture ContentOverlayed on 2004 Daily Data
Atm
osph
eric
Moi
stur
e Co
nten
t (kg
/kg)
Quantifying Vegetative Cover
• Fractional Absorbed Photosynthetically Active Radiation– faPAR = (PAR-rPAR)/PAR– rPAR = Reflected PAR
PAR PARrPAR rPAR
10-yr Average Daily Maximum faPAR
3-Dec 22-Jan 13-Mar 2-May 21-Jun 10-Aug 29-Sep 18-Nov 7-Jan 26-Feb0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
10-yr Average Daily Maximum faPAR
Correlation with Precipitation
3-Dec 22-Jan 13-Mar 2-May 21-Jun 10-Aug 29-Sep 18-Nov 7-Jan 26-Feb0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
faPAR and Precipitation
Phase Shift
3-Dec 22-Jan 13-Mar 2-May 21-Jun 10-Aug 29-Sep 18-Nov 7-Jan 26-Feb0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
faPAR and Precipitation
Conclusions and Future Work
• For desert environments, Vegetative Land Cover seems to be predicted by Precipitation
• Is this true for other, more hydrologically complex ecosystems?
• What causes the phase shift?– Deeper exploration of Soil Moisture and
Watershed Storage
