Evaluation de la ressource en eau associée au manteau neigeux sur le Mont Liban à partir d'observations et de la modélisation

Les ressources en eau du Liban sont soumises à une pression croissante due au développement économique, à la croissance démographique, à la gestion non-durable des ressources en eau et au changement climatique. Les montagnes du Mont et Anti-Liban sont des châteaux d'eau naturels pour le Liban car elles augmentent les précipitations par le soulèvement orographique des masses d'air. En raison de l'influence du climat méditerranéen, la plupart des précipitations au-dessus de 1200 m a.s.l. tombe sous la forme de neige en hiver. Par conséquent, la fonte des neiges contribue de façon importante au bilan hydrique national. En particulier, la fonte des neiges du Mont-Liban alimente les réseaux d'eau souterraine karstiques, qui fournissent des ressources en eau essentielle pour la région côtière. Malgré l'importance du manteau neigeux au Liban, sa variabilité spatiale et temporelle est insuffisament observée si bien que sa contribution au débit des fleuve et des sources reste méconnue. L'objectif de ce travail est de réduire ce manque de connaissance en utilisant des mesures in situ, des observations satellite et de la modélisation du manteau neigeux. 1. Nous présentons d'abord une revue de la littérature sur les processus nivo- hydrologiques dans les régions montagneuses méditerranéennes. De nombreuses études - principalement aux Etats-Unis de l'Ouest et dans les montagnes au sud de l'Europe - soulignent l'impact fort de la variabilité interannuelle du climat méditerranéen sur la dynamique du manteau neigeux. Le rayonnement solaire élevé est un facteur important du bilan énergétique du manteau neigeux, mais la contribution des flux de chaleur est plus forte à la fin de la saison nivale. La sublimation de la neige et la densification rapide sont des processus importants dans ce contexte. Les approches hybrides combinant des données de stations météorologiques et la télédétection optique de la surface enneigée à travers la modélisation sont recommandées pour compenser l'absence d'observations spatialisées du forçage météorologique. 2. Ensuite, nous présentons un ensemble original de données sur le manteau neigeux au Mont-Liban pour la période 2013-2016. Nous avons recueilli des observations sur le terrain de la hauteur de neige (HS), de l'équivalent en eau de neige (SWE) et de la densité de neige entre 1300 et 2900 m d'altitude sur le flanc occidental du Mont-Liban. De plus, des données météorologiques continues ont été acquises par trois stations météorologiques automatiques situées dans la partie enneigée du Mont-Liban. Le produit MODIS a été utilisé pour calculer la superficie couverte par la neige dans trois bassins hydrographiques couverts par les observations in situ. Nous remarquons la grande variabilité de HS et SWE et une densité élevée du manteau neigeux. Nous trouvons une corrélation significative entre HS et SWE qui peut être utile pour réduire la quantité de travail de terrain en vue d'un suivi opérationnel futur. 3. Grâce à ces données, nous avons mis en place un modèle distribué du manteau neigeux sur le Mont-Liban à une résolution de 100 m. Le modèle est validé à différentes échelles en utilisant les observations de SWE, densité, HS et SCA. Une simulation avec des modifications très limitées du paramétrage par défaut permet de capturer correctement la plupart des observations. Cette simulation permet donc d'estimer l'évolution du SWE et la fonte dans les trois bassins étudiés entre 2013 et 2016. Cette recherche a mis en évidence l'importance de réaliser simultanément des mesures sur le terrain et des observations météorologiques continues pour mieux appréhender les processus physiques qui contrôlent l'évolution du manteau neigeux sur le Mont-Liban. Enfin, l'influence du transport de la neige par le vent et des dépôts de poussière sur la fonte des neiges reste à évaluer en perspective de ce travail.Lebanon's water resources are under increasing pressure due to economic development, demographic growth, unsustainable water resource management, and climate change. The Mount- and Anti-Lebanon Mountains are natural water towers for Lebanon as they play an important role in enhancing orographic precipitation. Due to the influence of the Mediterranean climate, most precipitation above 1200 m a.s.l. falls as snow during winter season. As a result, snowmelt is an important contributor to the national water balance. In particular, snowmelt from Mount-Lebanon feeds the karst groundwater systems, which provide key water resources to the coastal region. Despite the importance of the snow cover in the Lebanese mountains, the actual snowpack spatial and temporal variability and its contribution to the spring and river discharges in Lebanon remains poorly constrained. The objective of this work is to reduce this lack of knowledge using a combination of in situ measurements, remote sensing observations and modelling of the snowpack in Mount-Lebanon. 1. We first present an extensive review of the literature about the snow hydrological processes in Mediterranean-like mountain regions. Many studies - mainly from Western USA and Southern Europe mountains - emphasize the strong impact of the interannual Mediterranean climate variability on the snowpack dynamics. The high incoming solar radiation is an important driver of the snowpack energy balance, but the contribution of heat fluxes is stronger at the end of the snow season. Snow sublimation and rapid densification are important processes to consider. Hybrid approaches combining weather station data with optical remote sensing of the snow extent through modelling are recommended to tackle the lack of spatially-distributed observations of the meteorological forcing. 2. Then, we introduce an original dataset on the snow cover in Mount-Lebanon for the period 2013-2016. We collected field observations of the snow height (HS), snow water equivalent (SWE), and snow density between 1300 and 2900 m a.s.l. in the western slope of Mount-Lebanon. In addition, continuous meteorological data were acquired by three automatic weather stations located in the snow dominated region of Mount-Lebanon. The MODIS snow product was used to compute the daily snow cover area in three snow dominated basins. We find that HS and SWE have large variances and that snow density is high. The strong correlation between HS and SWE may be useful to reduce the amount of field work for future operational monitoring. 3. Using these data we set up a distributed snowpack energy balance in the Mount- Lebanon at 100 m resolution. The model is validated at different scales using the observed SWE, snow density, HS and SCA. A simulation with very limited adjustments to the default parameterization is found to correctly capture most of the observations. This simulation allows the estimation of the SWE evolution and snow melt in the three study basins between 2013 and 2016. This research highlighted the importance of conducting simultaneous field surveys and meteorological observations to gain insights into the physical processes driving snowpack evolution in Mount-Lebanon. Finally, the influence of snow erosion by wind and the influence of dust deposits on snowmelt, remains less known, and are warrant for future research

Developing A Hydrologic Information System: Towards Promoting Sustainable Standardization

Water quantity and quality monitoring plays a key role towards the development of a sustainable water sector. The required infrastructure needed to monitor and manage surface and groundwater systems are often lacking particularly in developing countries. When available, water quantity and quality data are invariably fragmented, intermittent, not shared, with deficient metadata, and stored in formats that hinder establishing seamless coupling with hydrological models. Most data are saved locally with little attention placed on defining and maintaining metadata on the collection protocols, geographic referencing, measurement accuracy, resolution, detection limits, and data censorship. These limitations present serious challenges in reaching sound water management strategies. To alleviate these shortcomings, a Hydrologic Information System (HIS) based on the ArcHydro data model was developed using the country of Lebanon as a prototype. The HIS centralized available hydrological and water resources information; coupled spatial coverage with respective time series data on flow, water demand, meteorology, and water quality; and standardized metadata. Additionally, the system was structured to support hydrologic modeling and water resources analysis. A loose coupling was also integrated between the system and the Water Evaluation And Planning (WEAP) hydrological model and tested on the Upper Litani River Basin. The framework encompassed the ability to export back model simulation results and incorporate them within the HIS as time series records. The developed HIS system has since been adopted as a data repository for other water related projects in Lebanon and has helped identify key gaps in existing data and set monitoring priorities

Development of a composite drought indicator for operational drought monitoring in the MENA region

This paper presents the composite drought indicator (CDI) that Jordanian, Lebanese, Moroccan, and Tunisian government agencies now produce monthly to support operational drought management decision making, and it describes their iterative co-development processes. The CDI is primarily intended to monitor agricultural and ecological drought on a seasonal time scale. It uses remote sensing and modelled data inputs, and it reflects anomalies in precipitation, vegetation, soil moisture, and evapotranspiration. Following quantitative and qualitative validation assessments, engagements with policymakers, and consideration of agencies’ technical and institutional capabilities and constraints, we made changes to CDI input data, modelling procedures, and integration to tailor the system for each national context. We summarize validation results, drought modelling challenges and how we overcame them through CDI improvements, and we describe the monthly CDI production process and outputs. Finally, we synthesize procedural and technical aspects of CDI development and reflect on the constraints we faced as well as trade-offs made to optimize the CDI for operational monitoring to support policy decision-making—including aspects of salience, credibility, and legitimacy—within each national context

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Evaluation of the snow water resources in mount lebanon using observations and modelling

Les ressources en eau du Liban sont soumises à une pression croissante due au développement économique, à la croissance démographique, à la gestion non-durable des ressources en eau et au changement climatique. Les montagnes du Mont et Anti-Liban sont des châteaux d'eau naturels pour le Liban car elles augmentent les précipitations par le soulèvement orographique des masses d'air. En raison de l'influence du climat méditerranéen, la plupart des précipitations au-dessus de 1200 m a.s.l. tombe sous la forme de neige en hiver. Par conséquent, la fonte des neiges contribue de façon importante au bilan hydrique national. En particulier, la fonte des neiges du Mont-Liban alimente les réseaux d'eau souterraine karstiques, qui fournissent des ressources en eau essentielle pour la région côtière. Malgré l'importance du manteau neigeux au Liban, sa variabilité spatiale et temporelle est insuffisament observée si bien que sa contribution au débit des fleuve et des sources reste méconnue. L'objectif de ce travail est de réduire ce manque de connaissance en utilisant des mesures in situ, des observations satellite et de la modélisation du manteau neigeux. 1. Nous présentons d'abord une revue de la littérature sur les processus nivo- hydrologiques dans les régions montagneuses méditerranéennes. De nombreuses études - principalement aux Etats-Unis de l'Ouest et dans les montagnes au sud de l'Europe - soulignent l'impact fort de la variabilité interannuelle du climat méditerranéen sur la dynamique du manteau neigeux. Le rayonnement solaire élevé est un facteur important du bilan énergétique du manteau neigeux, mais la contribution des flux de chaleur est plus forte à la fin de la saison nivale. La sublimation de la neige et la densification rapide sont des processus importants dans ce contexte. Les approches hybrides combinant des données de stations météorologiques et la télédétection optique de la surface enneigée à travers la modélisation sont recommandées pour compenser l'absence d'observations spatialisées du forçage météorologique. 2. Ensuite, nous présentons un ensemble original de données sur le manteau neigeux au Mont-Liban pour la période 2013-2016. Nous avons recueilli des observations sur le terrain de la hauteur de neige (HS), de l'équivalent en eau de neige (SWE) et de la densité de neige entre 1300 et 2900 m d'altitude sur le flanc occidental du Mont-Liban. De plus, des données météorologiques continues ont été acquises par trois stations météorologiques automatiques situées dans la partie enneigée du Mont-Liban. Le produit MODIS a été utilisé pour calculer la superficie couverte par la neige dans trois bassins hydrographiques couverts par les observations in situ. Nous remarquons la grande variabilité de HS et SWE et une densité élevée du manteau neigeux. Nous trouvons une corrélation significative entre HS et SWE qui peut être utile pour réduire la quantité de travail de terrain en vue d'un suivi opérationnel futur. 3. Grâce à ces données, nous avons mis en place un modèle distribué du manteau neigeux sur le Mont-Liban à une résolution de 100 m. Le modèle est validé à différentes échelles en utilisant les observations de SWE, densité, HS et SCA. Une simulation avec des modifications très limitées du paramétrage par défaut permet de capturer correctement la plupart des observations. Cette simulation permet donc d'estimer l'évolution du SWE et la fonte dans les trois bassins étudiés entre 2013 et 2016. Cette recherche a mis en évidence l'importance de réaliser simultanément des mesures sur le terrain et des observations météorologiques continues pour mieux appréhender les processus physiques qui contrôlent l'évolution du manteau neigeux sur le Mont-Liban. Enfin, l'influence du transport de la neige par le vent et des dépôts de poussière sur la fonte des neiges reste à évaluer en perspective de ce travail.Lebanon's water resources are under increasing pressure due to economic development, demographic growth, unsustainable water resource management, and climate change. The Mount- and Anti-Lebanon Mountains are natural water towers for Lebanon as they play an important role in enhancing orographic precipitation. Due to the influence of the Mediterranean climate, most precipitation above 1200 m a.s.l. falls as snow during winter season. As a result, snowmelt is an important contributor to the national water balance. In particular, snowmelt from Mount-Lebanon feeds the karst groundwater systems, which provide key water resources to the coastal region. Despite the importance of the snow cover in the Lebanese mountains, the actual snowpack spatial and temporal variability and its contribution to the spring and river discharges in Lebanon remains poorly constrained. The objective of this work is to reduce this lack of knowledge using a combination of in situ measurements, remote sensing observations and modelling of the snowpack in Mount-Lebanon. 1. We first present an extensive review of the literature about the snow hydrological processes in Mediterranean-like mountain regions. Many studies - mainly from Western USA and Southern Europe mountains - emphasize the strong impact of the interannual Mediterranean climate variability on the snowpack dynamics. The high incoming solar radiation is an important driver of the snowpack energy balance, but the contribution of heat fluxes is stronger at the end of the snow season. Snow sublimation and rapid densification are important processes to consider. Hybrid approaches combining weather station data with optical remote sensing of the snow extent through modelling are recommended to tackle the lack of spatially-distributed observations of the meteorological forcing. 2. Then, we introduce an original dataset on the snow cover in Mount-Lebanon for the period 2013-2016. We collected field observations of the snow height (HS), snow water equivalent (SWE), and snow density between 1300 and 2900 m a.s.l. in the western slope of Mount-Lebanon. In addition, continuous meteorological data were acquired by three automatic weather stations located in the snow dominated region of Mount-Lebanon. The MODIS snow product was used to compute the daily snow cover area in three snow dominated basins. We find that HS and SWE have large variances and that snow density is high. The strong correlation between HS and SWE may be useful to reduce the amount of field work for future operational monitoring. 3. Using these data we set up a distributed snowpack energy balance in the Mount- Lebanon at 100 m resolution. The model is validated at different scales using the observed SWE, snow density, HS and SCA. A simulation with very limited adjustments to the default parameterization is found to correctly capture most of the observations. This simulation allows the estimation of the SWE evolution and snow melt in the three study basins between 2013 and 2016. This research highlighted the importance of conducting simultaneous field surveys and meteorological observations to gain insights into the physical processes driving snowpack evolution in Mount-Lebanon. Finally, the influence of snow erosion by wind and the influence of dust deposits on snowmelt, remains less known, and are warrant for future research

The role of liquid water percolation representation in estimating snow water equivalent in a Mediterranean mountain region (Mount Lebanon)

International audienceIn many Mediterranean mountain regions, the seasonal snowpack is an essential yet poorly known water resource. Here, we examine, for the first time, the spatial distribution and evolution of the snow water equivalent (SWE) during three snow seasons (2013-2016) in the coastal mountains of Lebanon. We run SnowModel (Liston and Elder, 2006a), a spatially distributed, process-based snow model, at 100 m resolution forced by new automatic weather station (AWS) data in three snow-dominated basins of Mount Lebanon. We evaluate a recent upgrade of the liquid water percolation scheme in SnowModel, which was introduced to improve the simulation of the SWE and runoff in warm maritime regions. The model is evaluated against continuous snow depth and snow albedo observations at the AWS, manual SWE measurements, and MODIS snow cover area between 1200 and 3000 m a.s.l. The results show that the new percolation scheme yields better performance, especially in terms of SWE but also in snow depth and snow cover area. Over the simulation period between 2013 and 2016, the maximum snow mass was reached between December and March. Peak mean SWE (above 1200 m a.s.l.) changed significantly from year to year in the three study catchments, with values ranging between 73 and 286 mm w.e. (RMSE between 160 and 260 mm w.e.). We suggest that the major sources of uncertainty in simulating the SWE, in this warm Mediterranean climate, can be attributed to forcing error but also to our limited understanding of the separation between rain and snow at lower-elevations, the transient snowmelt events during the accumulation season, and the high variability of snow depth patterns at the subpixel scale due to the wind-driven blown-snow redistribution into karstic features and sinkholes. Yet, the use of a process-based snow model with minimal requirements for parameter estimation provides a basis to simulate snow mass SWE in nonmonitored catchments and characterize the contribution of snowmelt to the karstic groundwater recharge in Lebanon. While this research focused on three basins in the Mount Lebanon, it serves as a case study to highlight the importance of wet snow processes to estimate SWE in Mediterranean mountain regions

Detecting Changes in Vegetation Trends in the Middle East and North Africa (MENA) Region Using SPOT Vegetation

The Middle East and North Africa (MENA) can be considered as the most water-scarce regions of the world and thus affecting the status of vegetation in this zone. Normalized Difference Vegetation Index (NDVI) datasets are used worldwide for large-area mapping and monitoring. Time series analysis techniques are used to define, evaluate, and monitor vegetation dynamics and variability using up-to-date remote sensing datasets. This study assesses vegetation degradation in the Arab countries using the SPOT Vegetation derived NDVI time series data of remotely sensed imageries for the time period between 1999 and 2012. Five classes were identified: Hot spot, negative change, no change, positive change and bright spot areas. Results indicate a severe decrease in the vegetation cover in almost 553 000 km2 of the total Arab region surface. On the other hand, only less than 1% of the region witnessed positive ‎changes in the vegetation cover. The positive and bright spot areas are mainly located in Algeria and Egypt, as well as in the southern part of Somalia and Iraq. Negative change and hot spot areas were found to be wide spreading all over the Arab countries, irrespective of the location, climate and topography. In addition, it is found that the vegetation changes in these regions are mainly related to human activities and decisions; climate change plays only a secondary role in the MENA region

Snow dataset for Mount-Lebanon (2011-2016)

We present a comprehensive snow dataset for Mont-Lebanon. The dataset includes continuous meteorological observations from three high elevation automatic weather stations (AWS), snowpack field measurements collected at 30 different snow courses (elevation range 1300-2900 m a.s.l.), and post-processed MODIS snow products. Meteorological and snow observations are presented for the snow seasons (November-June) between 2011 and 2016 for Mzar (MZA, 2294 m a.s.l.), 2014-2016 for the Cedars (CED, 2834 m a.s.l.), and 2015-2016 for Laqlouq (LAQ, 1830 m a.s.l.). Meteorological and snow data includes snow depth, temperature, relative humidity, incoming and reflected solar radiation, wind speed and direction, and atmospheric pressure measured at 30-min interval. Snow depth, snow density, and snow water equivalent were measured at the 30 different snow courses during snow season 2015 and 2016 with an average revisit time of 11.4 days. Post-processed daily MODIS snow cover area (SCA) and snow cover duration (SCD) products are presented for the three snow dominated basins (Abou Ali, Ibrahim, and El Kelb) and cover the time period from 01 September 2011 to 31 August 2016

Snowpack dynamics in the Lebanese mountains from quasi-dynamically downscaled ERA5 reanalysis updated by assimilating remotely sensed fractional snow-covered area

The snowpack over the Mediterranean mountains constitutes a key water resource for the downstream populations. However, its dynamics have not been studied in detail yet in many areas, mostly because of the scarcity of snowpack observations. In this work, we present a characterization of the snowpack over the two mountain ranges of Lebanon. To obtain the necessary snowpack information, we have developed a 1 km regional-scale snow reanalysis (ICAR_assim) covering the period 2010–2017. ICAR_assim was developed by means of an ensemble-based data assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) fractional snow-covered area (fSCA) through an energy and mass snow balance model, the Flexible Snow Model (FSM2), using the particle batch smoother (PBS). The meteorological forcing data were obtained by a regional atmospheric simulation from the Intermediate Complexity Atmospheric Research model (ICAR) nested inside a coarser regional simulation from the Weather Research and Forecasting model (WRF). The boundary and initial conditions of WRF were provided by the ERA5 atmospheric reanalysis. ICAR_assim showed very good agreement with MODIS gap-filled snow products, with a spatial correlation of R=0.98 in the snow probability (P(snow)) and a temporal correlation of R=0.88 on the day of peak snow water equivalent (SWE). Similarly, ICAR_assim has shown a correlation with the seasonal mean SWE of R=0.75 compared with in situ observations from automatic weather stations (AWSs). The results highlight the high temporal variability in the snowpack in the Lebanese mountain ranges, with the differences between Mount Lebanon and the Anti-Lebanon Mountains that cannot only be explained by hypsography as the Anti-Lebanon Mountains are in the rain shadow of Mount Lebanon. The maximum fresh water stored in the snowpack is in the middle elevations, approximately between 2200 and 2500 m a.s.l. (above sea level). Thus, the resilience to further warming is low for the snow water resources of Lebanon due to the proximity of the snowpack to the zero isotherm