scholarly journals Learning about precipitation lapse rates from snow course data improves water balance modeling

2021 ◽  
Vol 25 (4) ◽  
pp. 2109-2131
Author(s):  
Francesco Avanzi ◽  
Giulia Ercolani ◽  
Simone Gabellani ◽  
Edoardo Cremonese ◽  
Paolo Pogliotti ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Water Security ◽  
High Elevation ◽  
Annual Runoff ◽  
Data Sets ◽  
European Alps ◽  
Significant Step ◽  
Orographic Enhancement ◽  
Precipitation Gauge ◽  
Lapse Rates

Abstract. Precipitation orographic enhancement is the result of both synoptic circulation and topography. Since high-elevation headwaters are often sparsely instrumented, the magnitude and distribution of this enhancement, as well as how they affect precipitation lapse rates, remain poorly understood. Filling this knowledge gap would allow a significant step ahead for hydrologic forecasting procedures and water management in general. Here, we hypothesized that spatially distributed, manual measurements of snow depth (courses) could provide new insights into this process. We leveraged over 11 000 snow course data upstream of two reservoirs in the western European Alps (Aosta Valley, Italy) to estimate precipitation orographic enhancement in the form of lapse rates and, consequently, improve predictions of a snow hydrologic modeling chain (Flood-PROOFS). We found that snow water equivalent (SWE) above 3000 m a.s.l. (above sea level) was between 2 and 8.5 times higher than recorded cumulative seasonal precipitation below 1000 m a.s.l., with gradients up to 1000 mm w.e. km−1. Enhancement factors, estimated by blending precipitation gauge and snow course data, were consistent between the two hydropower headwaters (median values above 3000 m a.s.l. between 4.1 and 4.8). Including blended gauge course lapse rates in an iterative precipitation spatialization procedure allowed Flood-PROOFS to remedy underestimations both of SWE above 3000 m a.s.l. (up to 50 %) and – importantly – of precipitation vs. observed streamflow. Annual runoff coefficients based on blended lapse rates were also more consistent from year to year than those based on precipitation gauges alone (standard deviation of 0.06 and 0.19, respectively). Thus, snow courses bear a characteristic signature of orographic precipitation, which opens a window of opportunity for leveraging these data sets to improve our understanding of the mountain water budget. This is all the more important due to the essential role of high-elevation headwaters in supporting water security and ecosystem services worldwide.

scholarly journals Learning about precipitation orographic enhancement from snow-course data improves water-balance modeling

2020 ◽  
Author(s):  
Francesco Avanzi ◽  
Giulia Ercolani ◽  
Simone Gabellani ◽  
Edoardo Cremonese ◽  
Paolo Pogliotti ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Water Security ◽  
High Elevation ◽  
Data Sets ◽  
European Alps ◽  
Spatially Distributed ◽  
Significant Step ◽  
Orographic Enhancement ◽  
Precipitation Gauge ◽  
Lapse Rates

Abstract. Precipitation orographic enhancement depends on both synoptic circulation and topography. Since high-elevation headwaters are often sparsely instrumented, the magnitude and distribution of this enhancement remain poorly understood. Filling this knowledge gap would allow a significant step ahead for hydrologic-forecasting procedures and water management in general. Here, we hypothesized that spatially distributed, manual measurements of snow depth (courses) could provide new insights into this process. We leveraged 11,000+ snow-course data upstream two reservoirs in the Western European Alps (Aosta Valley, Italy) to estimate precipitation orographic enhancement in the form of lapse rates and consequently improve predictions of a snow-hydrologic modeling chain (Flood-PROOFS). We found that Snow Water Equivalent (SWE) above 3000 m ASL was between 2 and 8.5 times higher than recorded cumulative seasonal precipitation below 1000 m ASL, with gradients up to 1000 mm w.e. km−1. Enhancement factors estimated by blending precipitation-gauge and snow-course data were quite consistent between the two hydropower headwaters (median values above 3000 m ASL between 4.1 and 4.8). Including blended gauge-course lapse rates in an iterative precipitation-spatialization procedure allowed Flood-PROOFS to remedy underestimations of both SWE above 3000 m ASL (up to 50 %) and importantly precipitation vs. observed streamflow. Runoff coefficients based on blended lapse rates were also more consistent from year to year that those based on precipitation gauges alone (standard deviation of 0.06 and 0.19, respectively). Thus, snow courses bear a characteristic signature of orographic precipitation, which opens a window of opportunity for leveraging these data sets to improve our understanding of the mountain water budget. This is all the more important due to their essential role in supporting water security and ecosystem services worldwide.

Insights into precipitation orographic enhancement from snow-course data and their value for improved hydrologic predictions

2020 ◽  
Author(s):  
Francesco Avanzi ◽  
Giulia Ercolani ◽  
Simone Gabellani ◽  
Edoardo Cremonese ◽  
Umberto Morra di Cella ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
High Elevation ◽  
Elevation Gradients ◽  
Precipitation Distribution ◽  
Orographic Enhancement ◽  
Snow Water ◽  
Snow Model ◽  
Precipitation Gauge ◽  
Lapse Rates ◽  
High Elevations

<p>Precipitation enhancement along elevation gradients is the result of complex interactions between synoptic-circulation patterns and local topography. Since precipitation measurements at high elevation are often biased and sparse, predicting precipitation distribution in mountain regions is challenging, despite this being a key step of hydrologic-forecasting procedures and of water management in general. By acting as a natural precipitation gauge, the snowpack can provide useful information about precipitation orographic enhancement, but the information content of snow-course measurements in this regard has been generally underappreciated. We leveraged 70,000+ measurements upstream five reservoirs in Valle d’Aosta, Italy, to show how manual and radar snow courses can be used to estimate precipitation lapse rates and consequently improve predictions of hydrologic models. Snow Water Equivalent above 3000 m ASL can be more than 4-5 times cumulative seasonal precipitation below 1000 m ASL, with elevational gradients up to 1000 mm w.e. / km ASL. Enhancement factors estimated by blending precipitation-gauge and snow-course data are highly seasonal and spatially variable, with exponential or linear profiles with elevation depending on the year. Blended gauge - snow-course precipitation lapse rates can be used to infer precipitation in ungauged areas and compensate for elevation gradients in an iterative, two-step distribution procedure of precipitation based on modified Kriging. Coupling this precipitation-distribution procedure with a snow model (S3M) shows promising improvements in Snow Water Equivalent estimates at high elevations.</p>

The altitudinal temperature lapse rates applied to high elevation rockfalls studies in the Western European Alps

2017 ◽  
Vol 131 (3-4) ◽  
pp. 1479-1491 ◽  
Author(s):  
Guido Nigrelli ◽  
Simona Fratianni ◽  
Arianna Zampollo ◽  
Laura Turconi ◽  
Marta Chiarle
Keyword(s):  
High Elevation ◽  
European Alps ◽  
Western European ◽  
Lapse Rates

scholarly journals Investigating the Variability of High-Elevation Seasonal Orographic Snowfall Enhancement and Its Drivers across Sierra Nevada, California

2018 ◽  
Vol 19 (1) ◽  
pp. 47-67 ◽  
Author(s):  
Laurie S. Huning ◽  
Steven A. Margulis
Keyword(s):  
Sierra Nevada ◽  
Snow Water Equivalent ◽  
High Elevation ◽  
Mountain Range ◽  
Distributed Data ◽  
Mountainous Regions ◽  
Average Maximum ◽  
Spatially Distributed ◽  
Orographic Enhancement ◽  
Snow Water

Abstract While orographically driven snowfall is known to be important in mountainous regions, a complete understanding of orographic enhancement from the basin to the mountain range scale is often inhibited by limited distributed data and spatial and/or temporal resolutions. A novel, 90-m spatially distributed snow water equivalent (SWE) reanalysis was used to overcome these limitations. Leveraging this SWE information, the interannual variability of orographic gradients in cumulative snowfall (CS) was investigated over 14 windward (western) basins in the Sierra Nevada in California from water years 1985 to 2015. Previous studies have not provided a detailed multidecadal climatology of orographic CS gradients or compared wet-year and dry-year orographic CS patterns, distributions, and gradients across an entire mountain range. The magnitude of seasonal CS gradients range from over 15 cm SWE per 100-m elevation to under 1 cm per 100 m with a 31-yr average of 6.1 cm per 100 m below ~2500 m in the western basins. The 31-yr average CS gradients generally decrease in higher elevation zones across the western basins and become negative at the highest elevations. On average, integrated vapor transport and zonal winds at 700 hPa are larger during wet years, leading to higher orographically driven CS gradients across the Sierra Nevada than in dry years. Below ~2500 m, wet years yield greater enhancement (relative to dry years) by factors of approximately 2 and 3 in the northwestern and southwestern basins, respectively. Overall, the western Sierra Nevada experiences about twice as much orographic enhancement during wet years as in dry years below the elevation corresponding to the 31-yr average maximum CS.

scholarly journals Assessment of MERRA-2 and ERA5 to Model the Snow Water Equivalent in the High Atlas (1981–2019)

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 890
Author(s):  
Mohamed Wassim Baba ◽  
Abdelghani Boudhar ◽  
Simon Gascoin ◽  
Lahoucine Hanich ◽  
Ahmed Marchane ◽  
...  
Keyword(s):  
River Discharge ◽  
Snow Water Equivalent ◽  
High Elevation ◽  
Water Runoff ◽  
High Atlas ◽  
Seasonal Snow ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Melt water runoff from seasonal snow in the High Atlas range is an essential water resource in Morocco. However, there are only few meteorological stations in the high elevation areas and therefore it is challenging to estimate the distribution of snow water equivalent (SWE) based only on in situ measurements. In this work we assessed the performance of ERA5 and MERRA-2 climate reanalysis to compute the spatial distribution of SWE in the High Atlas. We forced a distributed snowpack evolution model (SnowModel) with downscaled ERA5 and MERRA-2 data at 200 m spatial resolution. The model was run over the period 1981 to 2019 (37 water years). Model outputs were assessed using observations of river discharge, snow height and MODIS snow-covered area. The results show a good performance for both MERRA-2 and ERA5 in terms of reproducing the snowpack state for the majority of water years, with a lower bias using ERA5 forcing.

Multicomponent microseismic data denoising by 3D shearlet transform

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. A45-A51 ◽  
Author(s):  
Chao Zhang ◽  
Mirko van der Baan
Keyword(s):  
Noise Suppression ◽  
Random Noise ◽  
Real Data ◽  
Fracture Initiation ◽  
Multidimensional Data ◽  
Data Sets ◽  
Denoising Method ◽  
Shearlet Transform ◽  
Microseismic Data ◽  
Significant Step

The low-magnitude microseismic signals generated by fracture initiation are generally buried in strong background noise, which complicates their interpretation. Thus, noise suppression is a significant step. We have developed an effective multicomponent, multidimensional microseismic-data denoising method by conducting a simplified polarization analysis in the 3D shearlet transform domain. The 3D shearlet transform is very competitive in dealing with multidimensional data because it captures details of signals at different scales and orientations, which benefits signal and noise separation. We have developed a novel processing strategy based on a signal-detection operator that can effectively identify signal coefficients in the shearlet domain by taking the correlation and energy distribution of 3C microseismic signals into account. We perform tests on synthetic and real data sets and determine that the proposed method can effectively remove random noise and preserve weak signals.

scholarly journals New data towards the development of a comprehensive taphonomic framework for the Late Jurassic Cleveland-Lloyd Dinosaur Quarry, Central Utah

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3368 ◽  
Author(s):  
Joseph E. Peterson ◽  
Jonathan P. Warnock ◽  
Shawn L. Eberhart ◽  
Steven R. Clawson ◽  
Christopher R. Noto
Keyword(s):  
Late Jurassic ◽  
Data Sets ◽  
Morrison Formation ◽  
Multiple Sources ◽  
Theropod Dinosaurs ◽  
The Matrix ◽  
Significant Step ◽  
Primary Driver ◽  
History Of ◽  
Bone Fragments

The Cleveland-Lloyd Dinosaur Quarry (CLDQ) is the densest deposit of Jurassic theropod dinosaurs discovered to date. Unlike typical Jurassic bone deposits, it is dominated by the presence ofAllosaurus fragilis. Since excavation began in the 1920s, numerous hypotheses have been put forward to explain the taphonomy of CLDQ, including a predator trap, a drought assemblage, and a poison spring. In an effort to reconcile the various interpretations of the quarry and reach a consensus on the depositional history of CLDQ, new data is required to develop a robust taphonomic framework congruent with all available data. Here we present two new data sets that aid in the development of such a robust taphonomic framework for CLDQ. First, x-ray fluorescence of CLDQ sediments indicate elevated barite and sulfide minerals relative to other sediments from the Morrison Formation in the region, suggesting an ephemeral environment dominated by periods of hypereutrophic conditions during bone accumulation. Second, the degree of abrasion and hydraulic equivalency of small bone fragments dispersed throughout the matrix were analyzed from CLDQ. Results of these analyses suggest that bone fragments are autochthonous or parautochthonous and are derived from bones deposited in the assemblage rather than transported. The variability in abrasion exhibited by the fragments is most parsimoniously explained by local periodic re-working and re-deposition during seasonal fluctuations throughout the duration of the quarry assemblage. Collectively, these data support previous interpretations that the CLDQ represents an attritional assemblage in a poorly-drained overbank deposit where vertebrate remains were introduced post-mortem to an ephemeral pond during flood conditions. Furthermore, while the elevated heavy metals detected at the Cleveland-Lloyd Dinosaur Quarry are not likely the primary driver for the accumulation of carcasses, they are likely the result of multiple sources; some metals may be derived from post-depositional and diagenetic processes, and others are potentially produced from an abundance of decomposing vertebrate carcasses. These new data help to support the inferred depositional environment of the quarry as an ephemeral pond, and represent a significant step in understanding the taphonomy of the bonebed and Late Jurassic paleoecology in this region.

scholarly journals Canadian historical Snow Water Equivalent dataset (CanSWE, 1928–2020)

2021 ◽  
Author(s):  
Vincent Vionnet ◽  
Colleen Mortimer ◽  
Mike Brady ◽  
Louise Arnal ◽  
Ross Brown
Keyword(s):  
Newfoundland And Labrador ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Water Security ◽  
Monitoring And Evaluation ◽  
Surface Models ◽  
Snow Water ◽  
The Government ◽  
Different Sources

Abstract. In situ measurements of snow water equivalent (SWE) – the depth of water that would be produced if all the snow melted – are used in many applications including water management, flood forecasting, climate monitoring, and evaluation of hydrological and land surface models. The Canadian historical SWE dataset (CanSWE) combines manual and automated pan-Canadian SWE observations collected by national, provincial and territorial agencies as well as hydropower companies. Snow depth and derived bulk snow density are also included when available. This new dataset supersedes the previous Canadian Historical Snow Survey (CHSSD) dataset published by Brown et al. (2019), and this paper describes the efforts made to correct metadata, remove duplicate observations, and quality control records. The CanSWE dataset was compiled from 15 different sources and includes SWE information for all provinces and territories that measure SWE. Data were updated to July 2020 and new historical data from the Government of Northwest Territories, Government of Newfoundland and Labrador, Saskatchewan Water Security Agency, and Hydro Quebec were included. CanSWE includes over one million SWE measurements from 2607 different locations across Canada over the period 1928–2020. It is publicly available at https://doi.org/10.5281/zenodo.4734372 (Vionnet et al., 2021).

scholarly journals Shannon Entropy for Measuring Spatial Complexity Associated with Mean Annual Runoff of Tertiary Catchments of the Middle Vaal Basin in South Africa

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 366 ◽  
Author(s):  
Masengo Ilunga
Keyword(s):  
South Africa ◽  
Information Gain ◽  
Annual Runoff ◽  
Data Sets ◽  
Information Redundancy ◽  
Spatial Complexity ◽  
Surface Water Resources ◽  
Gain Loss ◽  
Relative Change ◽  
Hydrological Phases

This study evaluates essentially mean annual runoff (MAR) information gain/loss for tertiary catchments (TCs) in the Middle Vaal basin. Data sets from surface water resources (WR) of South Africa 1990 (WR90), 2005 (WR2005) and 2012 (WR2012) referred in this study as hydrological phases, are used in this evaluation. The spatial complexity level or information redundancy associated with MAR of TCs is derived as well as the relative change in entropy of TCs between hydrological phases. Redundancy and relative change in entropy are shown to coincide under specific conditions. Finally, the spatial distributions of MAR iso-information transmission (i.e., gain or loss) and MAR iso-information redundancy are established for the Middle Vaal basin.

scholarly journals Growth of a high-elevation large inland lake, associated with climate change and permafrost degradation in Tibet

2010 ◽  
Vol 14 (3) ◽  
pp. 481-489 ◽  
Author(s):  
J. Liu ◽  
S. Kang ◽  
T. Gong ◽  
A. Lu
Keyword(s):  
High Elevation ◽  
Annual Runoff ◽  
Annual Precipitation ◽  
The Tibetan Plateau ◽  
Permafrost Degradation ◽  
Lake Area ◽  
Pan Evaporation ◽  
Precipitation Increase ◽  
Nam Co Lake

Abstract. This study analyzed satellite images and long term climate variables from a high-elevation meteorological station (4730 m) and streamflow records to examine hydrological response of Nam Co Lake (4718 m), the largest lake on the Tibetan Plateau, over the last 50 years. The results show the lake area extended by 51.8 km2 (2.7% of the total area) when compared with the area in 1976. This change is associated with an annual precipitation increase of 65 mm (18.6%), annual and winter mean temperature increases of 0.9 °C and 2.1 °C respectively, an annual runoff increase of 20% and an annual pan evaporation decrease of about 2%, during the past 20 years. The year of the change point in annual precipitation, air temperature, annual pan evaporation and runoff occurred in 1971, 1983, 1997 and 1997, respectively. The timing of the lake growth corresponds with the abrupt increase in annual precipitation and runoff since the mid-1990s.

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