scholarly journals Rapid changes in snow cover at low elevations in the Sierra Nevada, California, U.S.A.

1997 ◽  
Vol 25 ◽  
pp. 367-370 ◽  
Author(s):  
Richard Kattelmann
Keyword(s):  
Snow Cover ◽  
Sierra Nevada ◽  
Mountain Range ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Distributed Models ◽  
Rapid Changes ◽  
Spatially Distributed ◽  
Precipitation Type ◽  
River Forecasting

Snow cover in the intermittent snow zone of the Sierra Nevada can occupy more than 10 000 km2of the mountain range, but it has received relatively little attention in river forecasting. Snow is deposited at lower elevations only during the cold storms of winter, and remains there only for a few days or weeks. When cold storms have created a thin snow cover at low elevations, a subsequent warm storm can melt this snow in just a few hours and increase the runoff response dramatically. Operational hydrological models and river-forecasting procedures have tended to overlook contributions from the intermittent-snow zone, focusing instead on rainfall-runoff or melt from the snowpack zone at higher elevations. Data-collection efforts are minimal in this zone, too. Ideally, spatially distributed models of snowmelt and runoff generation are needed to account for the typically large differences in snow cover on different aspects in the intermittent snow zone. Although aircraft and satellite imagery would be most desirable to monitor the distribution of snow cover in the intermittent-snow zone, even a few climate stations that report precipitation type and snow presence would be a major improvement over the present situation in the Sierra Nevada.

scholarly journals Rapid changes in snow cover at low elevations in the Sierra Nevada, California, U.S.A.

1997 ◽  
Vol 25 ◽  
pp. 367-370 ◽  
Author(s):  
Richard Kattelmann
Keyword(s):  
Snow Cover ◽  
Sierra Nevada ◽  
Mountain Range ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Distributed Models ◽  
Rapid Changes ◽  
Spatially Distributed ◽  
Precipitation Type ◽  
River Forecasting

Snow cover in the intermittent snow zone of the Sierra Nevada can occupy more than 10 000 km2 of the mountain range, but it has received relatively little attention in river forecasting. Snow is deposited at lower elevations only during the cold storms of winter, and remains there only for a few days or weeks. When cold storms have created a thin snow cover at low elevations, a subsequent warm storm can melt this snow in just a few hours and increase the runoff response dramatically. Operational hydrological models and river-forecasting procedures have tended to overlook contributions from the intermittent-snow zone, focusing instead on rainfall-runoff or melt from the snowpack zone at higher elevations. Data-collection efforts are minimal in this zone, too. Ideally, spatially distributed models of snowmelt and runoff generation are needed to account for the typically large differences in snow cover on different aspects in the intermittent snow zone. Although aircraft and satellite imagery would be most desirable to monitor the distribution of snow cover in the intermittent-snow zone, even a few climate stations that report precipitation type and snow presence would be a major improvement over the present situation in the Sierra Nevada.

scholarly journals Changes in plant diversity in a water-limited and isolated high-mountain range (Sierra Nevada, Spain)

Alpine Botany ◽  
2021 ◽  
Author(s):  
Andrea Lamprecht ◽  
Harald Pauli ◽  
Maria Rosa Fernández Calzado ◽  
Juan Lorite ◽  
Joaquín Molero Mesa ◽  
...  
Keyword(s):  
Species Richness ◽  
Snow Cover ◽  
Sierra Nevada ◽  
Plant Diversity ◽  
Endemic Species ◽  
Vascular Plant ◽  
Climate Change Impacts ◽  
Permanent Plots ◽  
High Mountain ◽  
Mountain Range

AbstractClimate change impacts are of a particular concern in small mountain ranges, where cold-adapted plant species have their optimum zone in the upper bioclimatic belts. This is commonly the case in Mediterranean mountains, which often harbour high numbers of endemic species, enhancing the risk of biodiversity losses. This study deals with shifts in vascular plant diversity in the upper zones of the Sierra Nevada, Spain, in relation with climatic parameters during the past two decades. We used vegetation data from permanent plots of three surveys of two GLORIA study regions, spanning a period of 18 years (2001–2019); ERA5 temperature and precipitation data; and snow cover durations, derived from on-site soil temperature data. Relationships between diversity patterns and climate factors were analysed using GLMMs. Species richness showed a decline between 2001 and 2008, and increased thereafter. Species cover increased slightly but significantly, although not for endemic species. While endemics underwent cover losses proportional to non-endemics, more widespread shrub species increased. Precipitation tended to increase during the last decade, after a downward trend since 1960. Precipitation was positively related to species richness, colonisation events, and cover, and negatively to disappearance events. Longer snow cover duration and rising temperatures were also related to increasing species numbers, but not to cover changes. The rapid biotic responses of Mediterranean alpine plants indicate a tight synchronisation with climate fluctuations, especially with water availability. Thus, it rather confirms concerns about biodiversity losses, if projections of increasing temperature in combination with decreasing precipitation hold true.

Ingredients of German flood events

2020 ◽  
Author(s):  
Ralf Merz ◽  
Larisa Tarasova ◽  
Stefano Basso
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Rainfall Intensity ◽  
Machine Learning Techniques ◽  
Rainfall Runoff ◽  
Flood Events ◽  
Runoff Generation ◽  
Regional Variability ◽  
Large Variability ◽  
Runoff Events

<p>Floods can be caused by a large variety of different processes, such as short, but intense rainfall bursts, long rainfall events, which are wetting up substantial parts of the catchment, or rain on snow cover or frozen soils. Although there is a plethora on studies analysing or modelling rainfall-runoff processes, it is still not well understood, what rainfall and runoff generation conditions are needed to generate flood runoff and how these characteristics vary between catchments. In this databased approach we decipher the ingredients of flood events occurred in 161 catchments across Germany. For each catchment rainfall-runoff events are separated from observed time series for the period 1950-2013, resulting in about 170,000 single events. A peak-over-threshold approach is used to select flood events out of these runoff events. For each event, spatially and temporally distributed rainfall and runoff generation characteristics, such as snow cover and soil moisture, as well as their interaction are derived. Then we decipher those event characteristics controlling flood event occurrence by using machine learning techniques.</p><p>On average, the most important event characteristic controlling flood occurrence in Germany is, as expected, event rainfall volume, followed by the overlap of rainfall and soil moisture and the extent of wet areas in the catchment (area with high soil moisture content). Rainfall intensity is another important characteristic. However, a large variability in its importance is noticeable between dryer catchments where short rainfall floods occur regularly and wetter catchments, where rainfall intensity might be less important for flood generation. To analyse the regional variability of flood ingredients, we cluster the catchments according to similarity in their flood controlling event characteristics and test how good the flood occurrence can be predicted from regionalised event characteristics. Finally, we analyse the regional variability of the flood ingredients in the light of climate and landscape catchment characteristics.</p>

scholarly journals The Canadian Hydrological Model (CHM): A multi-scale, multi-extent, variable-complexity hydrological model – Design and overview

2019 ◽  
Author(s):  
Christopher B. Marsh ◽  
John W. Pomeroy ◽  
Howard S. Wheater
Keyword(s):  
High Resolution ◽  
Hydrological Model ◽  
Model Design ◽  
Rainfall Runoff ◽  
Predictive Capacity ◽  
Cold Regions ◽  
Distributed Models ◽  
Multi Scale ◽  
Spatially Distributed

Abstract. Despite debate in the rainfall-runoff hydrology literature about the merits of physics-based and spatially distributed models, substantial work in cold regions hydrology has shown improved predictive capacity by including physics-based process representations, relatively high-resolution semi- and fully-distributed discretizations, and use of physically identifiable parameters with limited calibration. While there is increasing motivation for modelling at hyper-resolution (

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 Using isotopes to constrain water flux and age estimates in snow-influenced catchments using the STARR (Spatially distributed Tracer-Aided Rainfall–Runoff) model

2017 ◽  
Vol 21 (10) ◽  
pp. 5089-5110 ◽  
Author(s):  
Pertti Ala-aho ◽  
Doerthe Tetzlaff ◽  
James P. McNamara ◽  
Hjalmar Laudon ◽  
Chris Soulsby
Keyword(s):  
Water Flux ◽  
Water Isotopes ◽  
Major Influence ◽  
Variable Degree ◽  
Rainfall Runoff ◽  
Stable Water Isotopes ◽  
Runoff Generation ◽  
Water Age ◽  
Landscape Characteristics ◽  
Spatially Distributed

Abstract. Tracer-aided hydrological models are increasingly used to reveal fundamentals of runoff generation processes and water travel times in catchments. Modelling studies integrating stable water isotopes as tracers are mostly based in temperate and warm climates, leaving catchments with strong snow influences underrepresented in the literature. Such catchments are challenging, as the isotopic tracer signals in water entering the catchments as snowmelt are typically distorted from incoming precipitation due to fractionation processes in seasonal snowpack. We used the Spatially distributed Tracer-Aided Rainfall–Runoff (STARR) model to simulate fluxes, storage, and mixing of water and tracers, as well as estimating water ages in three long-term experimental catchments with varying degrees of snow influence and contrasting landscape characteristics. In the context of northern catchments the sites have exceptionally long and rich data sets of hydrometric data and – most importantly – stable water isotopes for both rain and snow conditions. To adapt the STARR model for sites with strong snow influence, we used a novel parsimonious calculation scheme that takes into account the isotopic fractionation through snow sublimation and snowmelt. The modified STARR setup simulated the streamflows, isotope ratios, and snow pack dynamics quite well in all three catchments. From this, our simulations indicated contrasting median water ages and water age distributions between catchments brought about mainly by differences in topography and soil characteristics. However, the variable degree of snow influence in catchments also had a major influence on the stream hydrograph, storage dynamics, and water age distributions, which was captured by the model. Our study suggested that snow sublimation fractionation processes can be important to include in tracer-aided modelling for catchments with seasonal snowpack, while the influence of fractionation during snowmelt could not be unequivocally shown. Our work showed the utility of isotopes to provide a proof of concept for our modelling framework in snow-influenced catchments.

scholarly journals Incorporating Snow Albedo Feedback into Downscaled Temperature and Snow Cover Projections for California’s Sierra Nevada

2017 ◽  
Vol 30 (4) ◽  
pp. 1417-1438 ◽  
Author(s):  
Daniel B. Walton ◽  
Alex Hall ◽  
Neil Berg ◽  
Marla Schwartz ◽  
Fengpeng Sun
Keyword(s):  
Climate Change ◽  
Statistical Model ◽  
Snow Cover ◽  
Sierra Nevada ◽  
Statistical Downscaling ◽  
Dynamical Downscaling ◽  
Global Climate Models ◽  
Mountain Range ◽  
Albedo Feedback ◽  
Snow Albedo

Abstract California’s Sierra Nevada is a high-elevation mountain range with significant seasonal snow cover. Under anthropogenic climate change, amplification of the warming is expected to occur at elevations near snow margins due to snow albedo feedback. However, climate change projections for the Sierra Nevada made by global climate models (GCMs) and statistical downscaling methods miss this key process. Dynamical downscaling simulates the additional warming due to snow albedo feedback. Ideally, dynamical downscaling would be applied to a large ensemble of 30 or more GCMs to project ensemble-mean outcomes and intermodel spread, but this is far too computationally expensive. To approximate the results that would occur if the entire GCM ensemble were dynamically downscaled, a hybrid dynamical–statistical downscaling approach is used. First, dynamical downscaling is used to reconstruct the historical climate of the 1981–2000 period and then to project the future climate of the 2081–2100 period based on climate changes from five GCMs. Next, a statistical model is built to emulate the dynamically downscaled warming and snow cover changes for any GCM. This statistical model is used to produce warming and snow cover loss projections for all available CMIP5 GCMs. These projections incorporate snow albedo feedback, so they capture the local warming enhancement (up to 3°C) from snow cover loss that other statistical methods miss. Capturing these details may be important for accurately projecting impacts on surface hydrology, water resources, and ecosystems.

scholarly journals Modelling monthly runoff generation processes following land use changes: groundwater–surface runoff interactions

2004 ◽  
Vol 8 (5) ◽  
pp. 903-922 ◽  
Author(s):  
M. Bari ◽  
K. R. J. Smettem
Keyword(s):  
Land Use ◽  
Water Balance ◽  
Surface Runoff ◽  
Land Use Changes ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Mean Annual Rainfall ◽  
Monthly Runoff ◽  
Stream Bed

Abstract. A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall–runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, "Ernies" (control, fully forested) and "Lemon" (54% cleared) are in a zone of mean annual rainfall of 725 mm, while "Salmon" (control, fully forested) and "Wights" (100% cleared) are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall–runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i) an upper zone unsaturated store, (ii) a transient stream zone store, (ii) a lower zone unsaturated store and (iv) a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and predicted monthly hydrographs. The observed and predicted monthly runoff for all catchments matched well with coefficients of determination (R2) ranging from 0.68 to 0.87. Predictions were relatively poor for: (i) the Ernies catchment (lowest rainfall, forested), and (ii) months with very high flows. Overall, the predicted mean annual streamflow was within ±8% of the observed values. Keywords: monthly streamflow, land use change, conceptual model, data-based approach, groundwater

Sign in / Sign up

Export Citation Format

Share Document