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).

Statistical functions used in the French 'HydroPortail' <https://hydro.eaufrance.fr/>.
    This includes functions to estimate distributions, quantile curves and uncertainties, along with various other utilities.
    Technical details are available (in French) in Renard (2016) <https://hal.inrae.fr/hal-02605318>.

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) <doi:10.1002/rra.3978>. The identification of associated events is based on the event detection implemented in 'hydropeak'.