Project Details
Description
Worldwide, water management decisions are taken usually depending on the in-situ observation networks,
which decline in coverage of late. The decision-makers need information about the groundwater resources for
optimum management. Due to the incompleteness of ground-based observations, space-based observation of
global freshwater resources is critical. GRACE (GRAVITY RECOVERY AND CLIMATE EXPERIMENT)
satellite mission has become a very important water management tool since its initiation many years ago.
GRACE detects lateral variations in the gravitational potential in the earth, which is mostly caused by changes
in terrestrial water storage or TWS (Terrestrial Water Storage variation).
The excessive groundwater extraction would threat the limited fresh water resources in Saudi Arabia. Most
studies were conducted at local scale and the in-situ data are often limited and unmonitored. So that, utilization
of Remote Sensing (such as GRACE) would overcome these challenges and bring better water resource
management at regional scale.
The main objective of this study is to analyse the spatiotemporal groundwater variations using GRACE in the
Saudi Arabia and to compare the GRACE result with the in-situ observations. We plan to study in detail the
groundwater depletion in the Eastern Province, North-West and Central Saudi Arabia. The major challenge
during the course of the earlier study was the coarse scale GRACE data. Therefore, downscale GRACE data
by integrating in-situ data and gravity measurement using spatial correlation through variograms analysis will
be applied. Sequential Gaussian Simulation (SGS) will be used and multi realizations will be applied for
uncertainty quantification for different scenarios.
In Saudi Arabia, freshwater over-exploitation for irrigation purpose is attributed to groundwater depletion
instead of climate variability. It is worth to say that the use of GRACE and other satellite data for monitoring
the groundwater charge and discharge regionally could enhance management by integrating them with the land
surface models.
| Status | Finished |
|---|---|
| Effective start/end date | 1/07/21 → 1/01/23 |
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