EGU2020-5802
https://doi.org/10.5194/egusphere-egu2020-5802
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

How uncertain is the hydrological contribution to global sea level based on hydrological modelling compared to observational data?

Christian Mielke1, Olga Engels1, Bernd Uebbing1, Helena Gerdener1, Lara Börger1, Kerstin Schulze1, Petra Döll2, and Jürgen Kusche1
Christian Mielke et al.
  • 1Institute of Geodesy and Geoinformation, Bonn University, Bonn, Germany (s7chmiel@uni-bonn.de)
  • 2Institute of Physical Geography, Goethe University Frankfurt, Frankfurt am Main, Germany

Quantifying individual contributors to global and regional mean sea level along with corresponding uncertainties is crucial for future projections. However, the contribution of terrestrial hydrology seems to be the least known, but is particularly important, since in addition to the climate-driven changes human activities (such as groundwater pumping, irrigation, deforestation) have a large impact on global sea level changes. Under the common assumption that atmospheric water storage change is negligible, (total) terrestrial water storage anomalies (TWSA) represents a proxy for the hydrologic contribution. Generally, TWSA can be derived using models, observations or a combination of both. Each of the methods has its pros and cons.

In this study, we estimate the contribution of terrestrial hydrological cycle changes to global mean sea level along with corresponding uncertainties for 2003 - 2016 based on land TWSA time series derived (i) from WaterGAP Global Hydrological Model WGHM that also simulates anthropogenic effects and provides a partitioning of TWSA into global river discharge and evapotranspiration minus precipitation, (ii) satellite gravimetry data from GRACE, and (iii) from a joint inversion using GRACE and altimetry data. To realistically describe uncertainties in forcing data, model parameters, initial water states, and errors in the model structure, an ensemble of 30 runs is generated and analyzed. Because of well-known large inter-annual and decadal hydrological variations, we estimate time-varying trends using a Kalman filter framework in addition to the usually estimated linear trends. This approach provides more reliable trend and corresponding uncertainty estimates. Moreover, it naturally enables detecting any changes in rates, which is acceleration.

How to cite: Mielke, C., Engels, O., Uebbing, B., Gerdener, H., Börger, L., Schulze, K., Döll, P., and Kusche, J.: How uncertain is the hydrological contribution to global sea level based on hydrological modelling compared to observational data?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5802, https://doi.org/10.5194/egusphere-egu2020-5802, 2020

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