Multitemporal remote sensing analysis of a playa lake groundwater system in northern Chile
description
Transcript of Multitemporal remote sensing analysis of a playa lake groundwater system in northern Chile
Multitemporal remote sensing analysis of a playa lake groundwater system in northern Chile
GIS in Water Resources, Fall 2011Katherine Markovich
What is a playa lake or salar, and why do we care?Playa lake: an arid zone feature that is transitional between a playa, which is completely dry most of the year, and a lake (Briere, 2000).
In this study, a salar is an internally drained evaporative basin with surface water occurring mostly from spring discharge.
Image courtesy of Wikimedia Commons
Keller and Soto, 1998
1) Can we use remote sensing to quantify surface water extent on the salars?
2) Can we validate/refute Pastos Grandes as the recharge zone for Ascotán?
3) Can we determine if pumping has affected the northern springs and/or the springs at Carcote?
Research Questions
Proposed regional groundwater system:
Hypothesis: Yes, remote sensing is useful for monitoring of remote areas over large spatial and temporal scales. In situ field data can supplement the remote sensing analysis.
HydrologyΔV= (P+IGW+ISW) – (ET+OGW+OSW)
Background
( ) + assumptions =
Simple water budget for salars: ΔV= (IGW) – (E+OGW)
∆V=change in volume
P=precipitation (rain/snow)
ISW=surface water inputs
IGW=groundwater inputs
ET=evapotranspiration
OSW=surface water outputs
OSW=groundwater outputs
Remote sensing gives us ΔA, which can be related to the groundwater system!
Methods
Landsat Processing
Landsat 4-5 TM and 7 ETM+- 7-9 bands- 30m pixel resolution- Cloud-free- Orthorectified- Georeferenced
1) Download from USGS Landsat Archive
2) Stack, project, clip using ESRI ArcGIS 10
-WGS 1984 Datum-UTM Zone 19S Projection-Nearest Neighbor Resampling
3) Classify water pixels using ERDAS Imagine 2011
-Convert to water extent-Quality control-Perform analysis with respect to climate, chemical, and pumping data
Results
Optical Analysis• ‘False’ image• Qualitative only
UnsupervisedClassification
• Casteñeda et al., 2005• Depth/salinity
SupervisedClassification
• A priori knowledge• Possible Volume
1) Can we use remote sensing to quantify surface water extent as an analog to the regional groundwater system?
NDWI
• Xu, 2006• Overestimates
Results
Initial Multitemporal Analysis for 2009
January DecemberJulyMayMarch
Nov-08 Dec-08 Feb-09 Mar-09 May-09 Jul-09 Aug-09 Oct-09 Dec-09 Jan-100
2
4
6
8
10
12
0
20
40
60
80
100
120
140
160
180
200
2009
Avg. Precip.
Area
(km
2)
Prec
ipita
tion
(mm
)
Results
2 3 4 5 6 7 8 9 10 110
10
20
30
40
50
60
70
f(x) = 4.04073367075551 x − 3.87097007587574R² = 0.227565475064766
Salar Water Extent (km2)
Cald
era
Wat
er E
xten
t (km
2)
2 3 4 5 6 7 8 9 10 110
5
10
15
20
25
30
35
40
f(x) = 3.43872406035703 x − 4.67418784927699R² = 0.848797995379205
Salar Water Extent (km2)
Cald
era
Wat
er E
xten
t (km
2)
August, 1985 August, 1990
2) Can we validate/refute Pastos Grandes as a recharge zone for Ascotán?
Jan-85 Sep-87 Jun-90 Mar-93 Dec-95 Sep-98 Jun-01 Mar-04 Nov-06 Aug-090
2
4
6
8
10
12
f(x) = − 0.000431037530626917 x + 20.9791231775032R² = 0.40884261132233
TotalLinear (Total)North AscotanSouth AscotanCarcote
Sala
r Wat
er E
xten
t (km
2)Results
3) Can we determine if pumping has affected the northern springs and ultimately the water extent at Carcote?
CAR-1
V2
V7
V10
V11
¯
0 2.5 5 7.5 101.25Kilometers
LegendField Sites
Salars
North Ascotán
Carcote
South Ascotán
1) Developed a methodology to quantify surface water extent .
2) Found a positive correlation between the Pastos Grandes caldera and water extent on the salars.
3) Total surface water extent has decreased since 1985, but it is not certain whether the cause is predominantly anthropic or climatic.
4) Carcote shows a muted response to the changes at Ascotán, but the hydrologic relationship between North and South Ascotán remains a question.
Summary
Future Work:1. Continue remote sensing analysis by adding images, attempting to quantify volume,
and addressing uncertainty.
2. Further analysis of meteorological, hydrochemical, and pumping data from El Abra records and lab results.
3. Possible precipitation modeling using NASA TRMM data
Questions?