The duration of an event is specified as the number of consecutive
 time steps with equal flow trend.

An important environmental impact on running water ecosystems
is caused by hydropeaking - the discontinuous release of turbine water
because of peaks of energy demand. An event-based algorithm is implemented
to detect flow fluctuations referring to increase events (IC) and decrease
events (DC). For each event, a set of parameters related to the fluctuation
intensity is calculated. The framework is introduced in Greimel et al. (2016)
"A method to detect and characterize sub-daily flow fluctuations"
<doi:10.1002/hyp.10773> and can be used to identify different fluctuation
types according to the potential source: e.g., sub-daily flow fluctuations
caused by hydropeaking, rainfall, or snow and glacier melt.
This is a companion to the package 'hydroroute', which is used to detect and
follow hydropower plant-specific hydropeaking waves at the sub-catchment
scale and to describe how hydropeaking flow parameters change along the
longitudinal flow path as proposed and validated in Greimel et al. (2022).

Bettina Gruen

hydropeak

Detect and Characterize Sub-Daily Flow Fluctuations

Bettina Grün

Julia Haider

Franz Greimel

dur function

<dl><dt>x</dt>
<dd>Data frame (time series) from an event with equal flow trend. The
data frame must contain a date-time column (<code>Time</code>) and a flow rate
column (<code>Q</code>) and must be in a compatible format.
(see <code>flow()</code>).</dd></dl>

Arguments

DUR - Duration (Metric 4) — dur

<dl>

<dt>x</dt>
<dd>Data frame (time series) from an event with equal flow trend. The
data frame must contain a date-time column (<code>Time</code>) and a flow rate
column (<code>Q</code>) and must be in a compatible format.
(see <code>flow()</code>).</dd>

</dl>

dur: DUR - Duration (Metric 4)

Description

Usage

Value

Arguments

Examples