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).

Hydrogeology Steps for the 'recipes' Package
c(
person("Jonathan", "Kennel", email="jkennel@uoguelph.ca", role = c("aut", "cre")),
person("Beth", "Parker", role="ths")
)
Additional steps to be used with the 'recipes' package. New steps
were designed for regression deconvolution on datasets with millions of rows
with applications to signal decomposition and response
characterization. The methods in this package were developed as part of
PhD thesis titled High Frequency Water Level Responses to Natural
Signals <http://hdl.handle.net/10214/17890> by Jonathan Kennel in 2020.
Rcpp (>= 1.0.7), earthtide, generics, splines, tibble, dplyr,
rlang, tidyr, fftw
knitr, rmarkdown, ggplot2, scales, broom, glmnet, testthat
(>= 3.0.0), covr, splines2
Jonathan Kennel [aut, cre],
Beth Parker [ths]

Implements an empirical approach referred to as PeakTrace which uses multiple hydrographs 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. The method is based on the identification of associated events and uses (linear) regression models to describe translation and retention processes between neighboring hydrographs. Several regression model results are combined to arrive at a power plant-specific model. The approach is proposed and validated in Greimel et al. (2022, accepted with minor revisions). The identification of associated events is based on the event detection implemented in 'hydropeak'.
dplyr, ggpmisc, ggplot2, gridExtra, hydropeak, lubridate,
parallel, reshape2, stats, utils, scales