Analyse en ondelettes de fluctuations de débit en réseau de distribution d’eau potable

Ce travail évalue la pertinence d’une analyse en ondelettes appliquée à la consommation en eau potable, afin d’établir les habitudes de consommation des usagers et de détecter des changements. Cette démonstration exploite une série d’observations de débit au pas de temps horaire, couvrant une période de dix semaines dont le congé des Fêtes de fin d’année, tirée du réseau de distribution d’eau potable de la ville de Québec, Canada. Les résultats confirment la non-stationnarité du débit pour la gamme de périodes à l’étude, soit de 2 à 256 heures. Le principal cycle, qui explique la moitié de la variance naturelle de la série, possède une période de 24 heures dont l’intensité non stationnaire décrit un cycle de sept jours avec des pointes le dimanche matin et des creux au coeur de la semaine de travail. Le second cycle, responsable de plus du tiers de la variance, possède une période de 12 heures dont l’intensité suit également (mais un peu moins clairement) un cycle de sept jours avec des pointes la semaine et des creux le week-end. Ce comportement diffère pendant le congé des Fêtes de fin d’année, lorsque presque toute la variance naturelle est expliquée par la composante 24 heures de la série.This study evaluates the relevance of wavelet analysis applied to water consumption in order to detect habits and changes in these habits. The demonstration is based on a series of one-hour flow observations from Quebec City’s water distribution flowmeter network for a 10-week period, which includes Christmas and the New Year holidays. Results confirm the non-stationarity of the flow data for all studied periods, which range from 2 to 256 h. The main cycle, which accounts for half of the natural variance of the series, has a period of 24 h, with a non-stationary intensity varying over 7 d, peaking on Sunday mornings and with lows during the work week. The second cycle, responsible for a third of the variance, has a period of 12 h, with an intensity which follows (although not as strongly as the previous cycle) a 7-d cycle, peaking during the week and with lows during the weekend. This behaviour differs during the Holidays, when most of the natural variance is explained by the 24-h component of the series

Accounting for three sources of uncertainty in ensemble hydrological forecasting

Seeking more accuracy and reliability, the hydrometeorological community has developed several tools to decipher the different sources of uncertainty in relevant modeling processes. Among them, the ensemble Kalman filter (EnKF), multimodel approaches and meteorological ensemble forecasting proved to have the capability to improve upon deterministic hydrological forecast. This study aims to untangle the sources of uncertainty by studying the combination of these tools and assessing their respective contribution to the overall forecast quality. Each of these components is able to capture a certain aspect of the total uncertainty and improve the forecast at different stages in the forecasting process by using different means. Their combination outperforms any of the tools used solely. The EnKF is shown to contribute largely to the ensemble accuracy and dispersion, indicating that the initial conditions uncertainty is dominant. However, it fails to maintain the required dispersion throughout the entire forecast horizon and needs to be supported by a multimodel approach to take into account structural uncertainty. Moreover, the multimodel approach contributes to improving the general forecasting performance and prevents this performance from falling into the model selection pitfall since models differ strongly in their ability. Finally, the use of probabilistic meteorological forcing was found to contribute mostly to long lead time reliability. Particular attention needs to be paid to the combination of the tools, especially in the EnKF tuning to avoid overlapping in error decipherin

Impacts of high precipitation on the energy and water budgets of a humid boreal forest

The boreal forest will be strongly affected by climate change and in turn, these vast ecosystems may significantly impact global climatology and hydrology due to their exchanges of carbon and water with the atmosphere. It is now crucial to understand the intricate relationships between precipitation and evapotranspiration in these environments, particularly in less-studied locations characterized by a cold and humid climate. This study presents state-of-the-art measurements of energy and water budgets components over three years (2016–2018) at the Montmorency Forest, Québec, Canada: a balsam fir boreal forest that receives ∼1600 mm of precipitation annually (continental subarctic climate; Köppen classification subtype Dfc). Precipitation, evapotranspiration and potential evapotranspiration at the site are compared with observations from thirteen experimental sites around the world. These intercomparison sites (89 study-years) encompass various types of climate and vegetation (black spruces, jack pines, etc.) encountered in boreal forests worldwide. The Montmorency Forest stands out by receiving the largest amount of precipitation. Across all sites, water availability seems to be the principal evapotranspiration constraint, as precipitation tends to be more influential than potential evapotranspiration and other factors. This leads to the Montmorency Forest generating the largest amount of evapotranspiration, on average ∼550 mm y−1. This value appears to be an ecosystem maximum for evapotranspiration, which may be explained either by a physiological limit or a limited energy availability due to the presence of cloud cover. The Montmorency Forest water budget evacuates the precipitation excess mostly by watershed discharges, at an average rate of ∼1050 mm y−1, with peaks during the spring freshet. This behaviour, typical of mountainous headwater basins, necessarily influence downstream hydrological regimes to a large extent. This study provides a much needed insight in the hydrological regimes of a humid boreal-forested mountainous watershed, a type of basin rarely studied with precise energy and water budgets before

Efficient treatment of climate data uncertainty in ensemble Kalman filter (EnKF) based on an existing historical climate ensemble dataset

The final publication is available at Elsevier via https://doi.org/10.1016/j.jhydrol.2018.11.047. © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Successful data assimilation depends on the accurate estimation of forcing data uncertainty. Forcing data uncertainty is typically estimated based on statistical error models. In practice, the hyper-parameters of statistical error models are often estimated by a trial-and-error tuning process, requiring significant analyst and computational time. To improve the efficiency of forcing data uncertainty estimation, this study proposes the direct use of existing ensemble climate products to represent climate data uncertainty in the ensemble Kalman filter (EnKF) of flow forecasting. Specifically, the Newman et al. (2015) dataset (N15 for short), covering the contiguous United States, northern Mexico, and southern Canada, is used here to generate the precipitation and temperature ensemble in the EnKF application. This study for the first time compares the N15 generated climate ensemble with the carefully tuned hyper-parameters generated climate ensemble in a real flow forecasting framework. The forecast performance comparison of 20 Québec catchments shows that the N15 generated climate ensemble yields improved or similar deterministic and probabilistic flow forecasts relative to the carefully tuned hyper-parameters generated climate ensemble. Improvements are most evident for short lead times (i.e., 1–3 days) when the influence of data assimilation dominates. However, the analysis and computational time required to use N15 is much less compared to the typical trial-and-error hyper-parameter tuning process.Natural Sciences and Engineering Research Council [NETGP 451456

Stimulating a Canadian narrative for climate

ABSTRACT: This perspective documents current thinking around climate actions in Canada by synthesizing scholarly proposals made by Sustainable Canada Dialogues (SCD), an informal network of scholars from all 10 provinces, and by reviewing responses from civil society representatives to the scholars' proposals. Motivated by Canada's recent history of repeatedly missing its emissions reduction targets and failing to produce a coherent plan to address climate change, SCD mobilized more than 60 scholars to identify possible pathways towards a low-carbon economy and sustainable society and invited civil society to comment on the proposed solutions. This perspective illustrates a range of Canadian ideas coming from many sectors of society and a wealth of existing inspiring initiatives. Solutions discussed include climate change governance, low-carbon transition, energy production, and consumption. This process of knowledge synthesis/creation is novel and important because it provides a working model for making connections across academic fields as well as between academia and civil society. The process produces a holistic set of insights and recommendations for climate change actions and a unique model of engagement. The different voices reported here enrich the scope of possible solutions, showing that Canada is brimming with ideas, possibilities, and the will to act

Forcing the Penman-Montheith Formulation with Humidity, Radiation, and Wind Speed Taken from Reanalyses, for Hydrologic Modeling

The Penman-Monteith reference evapotranspiration (ET0) formulation was forced with humidity, radiation, and wind speed (HRW) fields simulated by four reanalyses in order to simulate hydrologic processes over six mid-sized nivo-pluvial watersheds in southern Quebec, Canada. The resulting simulated hydrologic response is comparable to an empirical ET0 formulation based exclusively on air temperature. However, Penman-Montheith provides a sounder representation of the existing relations between evapotranspiration fluctuations and climate drivers. Correcting HRW fields significantly improves the hydrologic bias over the pluvial period (June to November). The latter did not translate into an increase of the hydrologic performance according to the Kling-Gupta Efficiency (KGE) metric. The suggested approach allows for the implementation of physically-based ET0 formulations where HRW observations are insufficient for the calibration and validation of hydrologic models and a potential reinforcement of the confidence affecting the projection of low flow regimes and water availability

On the difficulty to optimally implement the Ensemble Kalman Filter : an experiment based on many hydrological models and catchments

Forecast reliability and accuracy is a prerequisite for successful hydrological applications. This aim may be attained by using data assimilation techniques such as the popular Ensemble Kalman filter (EnKF). Despite its recognized capacity to enhance forecasting by creating a new set of initial conditions, implementation tests have been mostly carried out with a single model and few catchments leading to case specific conclusions. This paper performs an extensive testing to assess ensemble bias and reliability on 20 conceptual lumped models and 38 catchments in the Province of Québec with perfect meteorological forecast forcing. The study confirms that EnKF is a powerful tool for short range forecasting but also that it requires a more subtle setting than it is frequently recommended. The success of the updating procedure depends to a great extent on the specification of the hyper-parameters. In the implementation of the EnKF, the identification of the hyper-parameters is very unintuitive if the model error is not explicitly accounted for and best estimates of forcing and observation error lead to overconfident forecasts. It is shown that performance are also related to the choice of updated state variables and that all states variables should not systematically be updated. Additionally, the improvement over the open loop scheme depends on the watershed and hydrological model structure, as some models exhibit a poor compatibility with EnKF updating. Thus, it is not possible to conclude in detail on a single ideal manner to identify an optimal implementation; conclusions drawn from a unique event, catchment, or model are likely to be misleading since transferring hyper-parameters from a case to another may be hazardous. Finally, achieving reliability and bias jointly is a daunting challenge as the optimization of one score is done at the cost of the othe