  Single-mission altimetric water level observations of rivers are spatially
and temporally limited, and thus they are often unable to quantify the full
extent of extreme flood events. Moreover, only missions with a short-repeat
orbit, such as Envisat, Jason-2, or SARAL, could provide meaningful time series
of water level variations directly. However, long or non-repeat orbit missions
such as CryoSat-2 have a very dense spatial resolution under the trade-off of a
repeat time insufficient for time series extraction. Combining data from
multiple altimeter missions into a multi-mission product allows for increasing
the spatial and temporal resolution of the data. In this study, we combined
water level data from CryoSat-2 with various observations from other altimeter
missions in the Mekong River Basin between 2008 and 2016 into one multi-mission
water level time series using the approach of universal kriging. In contrast to
former multi-mission altimetry methods, this approach allows for the
incorporation of CryoSat-2 data as well as data from other long or non-repeat
orbit missions, such as Envisat-EM or SARAL-DP. Additionally, for the first
time, data from tributaries are incorporated. The multi-mission time series
including CryoSat-2 data adequately reflects the general inter-annual flood
behaviour and the extreme floodings in 2008 and 2011. It performs better than
single-mission time series or multi-mission time series based only on
short-repeat orbit data. The Probability of Detection of the floodings with the
multi-mission altimetry was around 80\% while Envisat and Jason-2
single-mission altimetry could only detect around 40% of the floodings
correctly. However, small flash floods still remain undetectable.
