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On the use of spatially distributed, time‐lapse microgravity surveys to inform hydrological modeling
Author(s) -
Piccolroaz Sebastiano,
Majone Bruno,
Palmieri Francesco,
Cassiani Giorgio,
Bellin Alberto
Publication year - 2015
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2015wr016994
Subject(s) - streamflow , hydrological modelling , environmental science , state variable , inversion (geology) , drainage basin , hydrology (agriculture) , climatology , geology , structural basin , geography , geomorphology , geotechnical engineering , physics , cartography , thermodynamics
In the last decades significant technological advances together with improved modeling capabilities fostered a rapid development of geophysical monitoring techniques in support of hydrological modeling. Geophysical monitoring offers the attractive possibility to acquire spatially distributed information on state variables. These provide complementary information about the functioning of the hydrological system to that provided by standard hydrological measurements, which are either intrinsically local or the result of a complex spatial averaging process. Soil water content is an example of state variable, which is relatively simple to measure pointwise (locally) but with a vanishing constraining effect on catchment‐scale modeling, while streamflow data, the typical hydrological measurement, offer limited possibility to disentangle the controlling processes. The objective of this work is to analyze the advantages offered by coupling traditional hydrological data with unconventional geophysical information in inverse modeling of hydrological systems. In particular, we explored how the use of time‐lapse, spatially distributed microgravity measurements may improve the conceptual model identification of a topographically complex Alpine catchment (the Vermigliana catchment, South‐Eastern Alps, Italy). The inclusion of microgravity data resulted in a better constraint of the inversion procedure and an improved capability to identify limitations of concurring conceptual models to a level that would be impossible relying only on streamflow data. This allowed for a better identification of model parameters and a more reliable description of the controlling hydrological processes, with a significant reduction of uncertainty in water storage dynamics with respect to the case when only streamflow data are used.