Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.5194/hess-18-2773-2014 |
| Title (Primary) | How to identify groundwater-caused thermal anomalies in lakes based on multi-temporal satellite data in semi-arid regions |
| Author | Mallast, U.; Gloaguen, R.; Friesen, J.
; Rödiger, T.; Geyer, S.
; Merz, R.; Siebert, C.
|
| Source Titel | Hydrology and Earth System Sciences |
| Year | 2014 |
| Department | CATHYD; CIWAS |
| Volume | 18 |
| Issue | 7 |
| Page From | 2773 |
| Page To | 2787 |
| Language | englisch |
| UFZ wide themes | RU2; |
| Abstract | Information on groundwater discharge over large spatial scales are essential
for groundwater management particularly in (semi-) arid regions. If
discharge areas are known, direct measurements over larger spatial scales
are complicated to obtain by conventional means, why thermal remote sensing
is increasingly applied to localize and quantify groundwater discharge. In
this context, mostly unconsidered is (i) the influence of surface-runoff
that can negatively affect groundwater focused studies and (ii) the
representativeness of remotely sensed groundwater discharge based on single
thermal images, against the background of discharge intermittency.
Addressing these issues we apply a multi-temporal SST data approach based on
19 Landsat ETM+ band 6.2 (high gain) data from the year 2000 until 2002 at
the example of the (semi-)arid vicinity of Dead Sea. To be independent of
auxiliary rain data we develop a novel approach to identify surface-runoff
influenced images solely using image statistics. Compared to foregoing rain
events the result reveals a general influence-time of at least two days, but
also that a simple time-difference criterion to exclude possible
surface-runoff is not advisable. In the second part of the study we evaluate
the significance of six statistical measures calculated on a per-pixel basis
on the remaining 12 surface-runoff uninfluenced sea-surface-temperature
(SST) data using in situ discharge measurements of the Israel Hydrological
Service (IHS). We found that the spatial patterns of the standard deviation
and range on the SST data series best fit to the IHS observed discharge
locations and hence are suitable for detecting groundwater discharge areas. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=13875 |
| Mallast, U., Gloaguen, R., Friesen, J., Rödiger, T., Geyer, S., Merz, R., Siebert, C. (2014): How to identify groundwater-caused thermal anomalies in lakes based on multi-temporal satellite data in semi-arid regions Hydrol. Earth Syst. Sci. 18 (7), 2773 - 2787 10.5194/hess-18-2773-2014 |
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