Abstract. The knowledge of water storage volumes in catchments and in river networks
leading to river discharge is essential for the description of river
ecology, the prediction of floods and specifically for a sustainable
management of water resources in the context of climate change. Measurements
of mass variations by the GRACE gravity satellite or by ground-based
observations of river or groundwater level variations do not permit the
determination of the respective storage volumes, which could be considerably
bigger than the mass variations themselves. For fully humid tropical conditions like the Amazon the relationship between
GRACE and river discharge is linear with a phase shift. This permits the hydraulic time constant to be determined and thus the total
drainable storage directly from observed runoff can be quantified, if the phase shift can be
interpreted as the river time lag. As a time lag can be described by a
storage cascade, a lumped conceptual model with cascaded storages for the
catchment and river network is set up here with individual hydraulic time
constants and mathematically solved by piecewise analytical solutions. Tests of the scheme with synthetic recharge time series show that a
parameter optimization either versus mass anomalies or runoff reproduces the
time constants for both the catchment and the river network τC and τR in a unique way, and this then permits an individual
quantification of the respective storage volumes. The application to the
full Amazon basin leads to a very good fitting performance for total mass,
river runoff and their phasing (Nash–Sutcliffe for signals 0.96, for monthly
residuals 0.72). The calculated river network mass highly correlates (0.96
for signals, 0.76 for monthly residuals) with the observed flood area from
GIEMS and corresponds to observed flood volumes. The fitting performance versus GRACE permits river runoff and
drainable storage volumes to be determined from recharge and GRACE exclusively, i.e. even for
ungauged catchments. An adjustment of the hydraulic time constants (τC, τR) on a training period facilitates a simple
determination of drainable storage volumes for other times directly from
measured river discharge and/or GRACE and thus a closure of data gaps
without the necessity of further model runs.
Efficient and accurate determination of 13C T1 and T1ρ relaxation time constants of high-mobility polymers from limited-resolution spectra with optimized pulse sequences and data fitting