Submitted by Manuela Girotto on
Climate driven changes in land water storage have been assumed too small to be included in IPCC sea level budgets, but recent studies using Gravity and Climate Recovery Experiment NASA mission (GRACE) suggest that land hydrology can delay sea level rise. Most land surface includes hydrologic response to climate driven processes (i.e., hydrology changes driven by precipitation, temperature, solar radiation), but anthropogenic processes (i.e., groundwater extraction, irrigation, impoundment in reservoir) are not yet modeled.
These human activities may play a major role in modulating rates of sea level change by altering the hydrology of the aquifers and floodplains. Thus, to improve estimates of sea level rise we need to 1) improve model estimates of land hydrology by including both human and natural driven processes; 2) characterize their magnitude and uncertainty; 3) quantify land hydrology contribution (and uncertainty) to changes in the sea level.
Satellite observations give us the opportunity to improve modeling capabilities and to monitor the hydrological contribution to sea level rise in its entirety, without differentiating whether natural or human driven processes cause its variability. The soil moisture dedicated missions such as the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP) missions have the potential to detect agriculture irrigation. Other satellite observations, such as the Gravity and Climate Recovery Experiment mission (GRACE) have also been exploited to improve the water storage capacity of models and to investigate droughts and worldwide human driven terrestrial water storage (TWS) depletion rates.
This project will investigate if an improved sea level change characterization can be achieved with improved model estimate of land hydrology. The improved model estimated will be achieved via data assimilation (i.e., data integration) of satellite based observations and model estimates.
The analysis of land-hydrology water balance with or without the above proposed data assimilation approach will allow us to characterize the magnitude and uncertainty of the changes in the land hydrology thus, allowing for quantification and assessment of the uncertainty in sea level change due to land hydrology, and in particular we may gain insight into the human versus climatological driven land hydrological contribution to sea level.
The primary responsibility of the undergraduate student will be to help collect satellite and insitu data for validation purposes. The student will also be expected to help with the preprocessing of the data and data analysis. An example, could be runnign statistical analysis to compare changes in the satellite and model estimates of land hydrology water storage with recorded sea level changes
This project is part of a larger interdisciplinary team that include glaciologists, oceanographers and geodesists. Thus, the student shoudl be open to read and learn about other disciplines too.
Currently pursuing undergraduate degree at UC Berkeley
Good programming skill (or willingness to learn)
Students with strong interests in satellite remote sensing, data analysis and hydrology will find the experience most rewarding.