Abstract
Abstract. Floods and flash floods are complex events, depending on
weather dynamics, basin physiographical characteristics, land use cover and
water management. For this reason, the prediction of such events usually deals
with very accurate model tuning and validation, which is usually
site-specific and based on climatological data, such as discharge time
series or flood databases. In this work, we developed and tested two
hydrological-stress indices for flood detection in the Italian Central
Apennine District: a heterogeneous geographical area, characterized by
complex topography and medium-to-small catchment extension. The proposed indices
are threshold-based and developed considering operational requirements of
National Civil Protection Department end-users. They are calibrated and tested through the
application of signal theory, in order to overcome data scarcity over
ungauged areas, as well as incomplete discharge time series. The validation
has been carried out on a case study basis, using flood reports from various
sources of information, as well as hydrometric-level time series, which
represent the actual hydrological quantity monitored by Civil Protection
operators. Obtained results show that the overall accuracy of flood
prediction is greater than 0.8, with false alarm rates below 0.5 and
the probability of detection ranging from 0.51 to 0.80. Moreover, the different
nature of the proposed indices suggests their application in a complementary
way, as the index based on drained precipitation appears to be more sensitive
to rapid flood propagation in small tributaries, while the discharge-based
index is particularly responsive to main-channel dynamics.
Subject
General Earth and Planetary Sciences,General Engineering,General Environmental Science
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