WorldWideScience

Sample records for monitoring snow water

  1. ESA GlobSnow Snow Water Equivalent (SWE)

    Data.gov (United States)

    National Aeronautics and Space Administration — The European Space Agency (ESA) Global Snow Monitoring for Climate Research (GlobSnow) snow water equivalent (SWE) v2.0 data record contains snow information derived...

  2. Snow monitoring using microwave radars

    OpenAIRE

    Koskinen, Jarkko

    2001-01-01

    Remote sensing has proven its usefulness in various applications. For mapping, land-use classification and forest monitoring optical satellite and airborne images are used operationally. However, this is not the case with snow monitoring. Currently only ground-based in situ and weather measurements are used operationally for snow monitoring in Finland. Ground measurements are conducted once a month on special snow courses. These measurements are used to update the hydrological model that simu...

  3. Monitoring of the Liquid Water Content During Snowmelt Using C-Band SAR Data and the Snow Model CROCUS

    Science.gov (United States)

    Rondeau-Genesse, G.; Trudel, M.; Leconte, R.

    2014-12-01

    Coupling C-Band synthetic aperture radar (SAR) data to a multilayer snow model is a step in better understanding the temporal evolution of the radar backscattering coefficient during snowmelt. The watershed used for this study is the Nechako River Basin, located in the Rocky Mountains of British-Columbia (Canada). This basin has a snowpack of several meters in depth and part of its water is diverted to the Kemano hydropower system, managed by Rio-Tinto Alcan. Eighteen RADARSAT-2 ScanSAR Wide archive images were acquired in VV/VH polarization for the winter of 2011-2012, under different snow conditions. They are interpreted along with CROCUS, a multilayer physically-based snow model developed by Météo-France. This model discretizes the snowpack into 50 layers, which makes it possible to monitor various characteristics, such as liquid water content (LWC), throughout the season. CROCUS is used to model three specific locations of the Nechako River Basin. Results vary from one site to another, but in general there is a good agreement between the modeled LWC of the first layer of the snowpack and the backscattering coefficient of the RADARSAT-2 images, with a coefficient of determination (R²) of 0.80 and more. The radar images themselves were processed using an updated version of Nagler's methodology, which consists of subtracting an image in wet snow conditions to one in dry snow conditions, as wet snow can then be identified using a soft threshold centered around -3 dB. A second filter was used in order to differentiate dry snow and bare soil. That filter combines a VH/VV ratio threshold and an altitude criterion. The ensuing maps show a good agreement with the MODIS snow-covered area, which is already obtained daily over the Nechako River Basin, but with additional information on the location of wet snow and without sensibility to cloud cover. As a next step, the outputs of CROCUS will be used in Mätzler's Microwave Emission Model of Layered Snowpacks (MEMLS) to

  4. Snow water content estimation from measured snow temperature

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The vertical temperature profiles of snow and sea ice have been measured in the Arctic during the 2nd Chinese National Arctic Research Expedition in 2003 (CHINARE2003). The high-resolution temperature profile in snow is solved by one-dimensional heat transfer equation. The effective heat diffusivity, internal heat sources are identified. The internal heat source refers to the penetrated solar radiation which usually warms the lower part of the snow layer in summer. By temperature gradient analysis, the zero level can be clarified quantitatively as the boundary of the dry and wet snow. According to the in situ time series of vertical temperature profile, the time series of water content in snow is obtained based on an evaluation method of snow water content associated with the snow and ice physical parameters. The relationship of snow water content and snow temperature and temporal-spatial distribution of snow water content are presented

  5. Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.; Foster, James L.

    2009-01-01

    Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed

  6. Assessing the thermal dissipation sap flux density method for monitoring cold season water transport in seasonally snow-covered forests.

    Science.gov (United States)

    Chan, Allison M; Bowling, David R; Phillips, Nathan

    2017-07-01

    Productivity of conifers in seasonally snow-covered forests is high before and during snowmelt when environmental conditions are optimal for photosynthesis. Climate change is altering the timing of spring in many locations, and changes in the date of transition from winter dormancy can have large impacts on annual productivity. Sap flow methods provide a promising approach to monitor tree activity during the cold season and the winter-spring and fall-winter transitions. Although sap flow techniques have been widely used, cold season results are generally not reported. Here we examine the feasibility of using the Granier thermal dissipation (TD) sap flux density method to monitor transpiration and dormancy of evergreen conifers during the cold season. We conducted a laboratory experiment which demonstrated that the TD method reliably detects xylem water transport (when it occurs) both at near freezing temperature and at low flow rate, and that the sensors can withstand repeated freeze-thaw events. However, the dependence between sensor output and water transport rate in these experiments differed from the established TD relation. In field experiments, sensors installed in two Abies forests lasted through two winters and a summer with low failure. The baseline (no-flow) sensor output varied considerably with temperature during the cold season, and a new baseline algorithm was developed to accommodate this variation. The Abies forests differed in elevation (2070 and 2620 m), and there was a clear difference in timing of initiation and cessation of transpiration between them. We conclude that the TD method can be reliably used to examine water transport during cold periods with associated low flow conditions. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  7. Snow Monitoring Using Remote Sensing Data: Modification of Normalized Difference Snow Index

    Science.gov (United States)

    Kaplan, G.; Avdan, U.

    2016-12-01

    Snow cover is an important part of the Earth`s climate system so its continuous monitoring is necessary to map snow cover in high resolution. Satellite remote sensing can successfully fetch land cover and land cover changes. Although normalized difference snow index NDSI has quite good accuracy, topography shadow, water bodies and clouds can be easily misplaced as snow. Using Landsat TM, +ETM and TIRS/OLI satellite images, the NDSI was modified for more accurate snow mapping. In this paper, elimination of the misplaced water bodies was made using the high reflectance of the snow in the blue band. Afterwards, the modified NDSI (MNDSI) was used for estimating snow cover through the years on the highest mountains in Republic of Macedonia. The results from this study show that the MNDSI accuracy is bigger than the NDSI`s, totally eliminating the misplaced water bodies, and partly the one caused from topography and clouds. Also, it was noticed that the snow cover in the study area has been lowered through the years. For future studies, the MNDSI should be validated on different study areas with different characteristics.

  8. MONITORING OF SNOW COVER VARIATION USING MODIS SNOW PRODUCT

    Directory of Open Access Journals (Sweden)

    N. Fayaz

    2013-09-01

    Full Text Available Snow is one of the integral components of hydrological and climatic systems. Needless to say, snow cover areas (SCA are considered as indispensable input of hydrological and general circulation models. Studying the spatial and temporal variability of SCA is of the paramount importance for tremendous variety of research such as climate change, water supply and properly managing water resources. In this study by means of Moderate Resolution Imaging Spectroradiometer (MODIS snow cover product, the variation of snow cover extent (SCE in Karoun basin located in western part of Iran is evaluated for twelve years' duration; since 2000 to 2012. The results show that the paramount occurrence of SCE is observed during February months of 2003, 2010 and 2011 as well as during December months of 2006 and 2009.The utmost occurrence of SCE is considered during January months of the other remaining years. Annual average shows that SCE varies from 11% in 2011 to 22% in 2006. According to Mann-Kendal trend test, throughout twelve years; 2000 to 2012, a majority of the pixels in the study area have no considerable trend although there is a decreasing trend on a small portion of the pixels located in the eastern part the study domain.

  9. NASA Airborne Snow Observatory: Measuring Spatial Distribution of Snow Water Equivalent and Snow Albedo

    Science.gov (United States)

    Joyce, M.; Painter, T. H.; Mattmann, C. A.; Ramirez, P.; Laidlaw, R.; Bormann, K. J.; Skiles, M.; Richardson, M.; Berisford, D. F.

    2015-12-01

    The two most critical properties for understanding snowmelt runoff and timing are the spatial and temporal distributions of snow water equivalent (SWE) and snow albedo. Despite their importance in controlling volume and timing of runoff, snowpack albedo and SWE are still largely unquantified in the US and not at all in most of the globe, leaving runoff models poorly constrained. NASA Jet Propulsion Laboratory, in partnership with the California Department of Water Resources, has developed the Airborne Snow Observatory (ASO), an imaging spectrometer and scanning LiDAR system, to quantify SWE and snow albedo, generate unprecedented knowledge of snow properties for cutting edge cryospheric science, and provide complete, robust inputs to water management models and systems of the future. This poster will describe the NASA Airborne Snow Observatory, its outputs and their uses and applications, along with recent advancements to the system and plans for the project's future. Specifically, we will look at how ASO uses its imaging spectrometer to quantify spectral albedo, broadband albedo, and radiative forcing by dust and black carbon in snow. Additionally, we'll see how the scanning LiDAR is used to determine snow depth against snow-free acquisitions and to quantify snow water equivalent when combined with in-situ constrained modeling of snow density.

  10. Snow water equivalent mapping in Norway

    Science.gov (United States)

    Tveito, O. E.; Udnæs, H.-C.; Engeset, R.; Førland, E. J.; Isaksen, K.; Mengistu, Z.

    2003-04-01

    In high latitude area snow covers the ground large parts of the year. Information about the water volume as snow is of major importance in many respects. Flood forecasters at NVE need it in order to assess possible flood risks. Hydropower producers need it to plan the most efficient production of the water in their reservoirs, traders to estimate the potential energy available for the market. Meteorologists on their side use the information as boundary conditions in weather forecasting models. The Norwegian meteorological institute has provided snow accumulation maps for Norway for more than 50 years. These maps are now produced twice a month in the winter season. They show the accumulated precipitation in the winter season from the day the permanent snow cover is established. They do however not take melting into account, and do therefore not give a good description of the actual snow amounts during and after periods with snowmelt. Due to an increased need for a direct measure of water volumes as snow cover, met.no and NVE initialized a joint project in order to establish maps of the actual snow cover expressed in water equivalents. The project utilizes recent developments in the use of GIS in spatial modeling. Daily precipitation and temperature are distributed in space by using objective spatial interpolation methods. The interpolation considers topographical and other geographical parameters as well as weather type information. A degree-day model is used at each modeling point to calculate snow-accumulation and snowmelt. The maps represent a spatial scale of 1x1 km2. The modeled snow reservoir is validated by snow pillow values as well traditional snow depth observations. Preliminary results show that the new snow modeling approach reproduces the snow water equivalent well. The spatial approach also opens for a wide use in the terms of areal analysis.

  11. Monitoring and modelling snow avalanches in Svalbard

    Science.gov (United States)

    Humlum, O.; Christiansen, H.; Neumann, U.; Eckerstorfer, M.; Sjöblom, A.; Stalsberg, K.; Rubensdotter, L.

    2009-04-01

    Monitoring and modelling snow avalanches in Svalbard Ole Humlum 1,3, Hanne H. Christiansen 1, Ulrich Neumann 1, Markus Eckerstorfer 1, Anna Sjöblom 1, Knut Stalsberg 2 and Lena Rubensdotter 2. 1: The University Centre in Svalbard (UNIS). 2: Geological Survey of Norway (NGU) 3: University of Oslo Ground based transportation in Svalbard landscape all takes place across mountainous terrain affected by different geomorphological slope processes. Traffic in and around the Svalbard settlements is increasing, and at the same time global climate models project substantial increases in temperature and precipitation in northern high latitudes for coming century. Therefore improved knowledge on the effect of climatic changes on slope processes in such high arctic landscapes is becoming increasingly important. Motivated by this, the CRYOSLOPE Svalbard research project since 2007 has carried out field observations on snow avalanche frequency and associated meteorological conditions. Snow avalanches are important geomorphic agents of erosion and deposition, and have long been a source of natural disasters in many mid-latitude mountain areas. Avalanches as a natural hazard has thereby been familiar to inhabitants of the Alps and Scandinavia for centuries, while it is a more recent experience in high arctic Svalbard. In addition, overall climate, topography and especially high winter wind speeds makes it difficult to apply snow avalanche models (numerical or empirical) developed for use at lower latitudes, e.g. in central Europe. In the presentation we examplify results from the ongoing (since winter 2006-07) monitoring of snow avalanches in Svalbard along a 70 km long observational route in the mountains. In addition, we present observations on the geomorphological impact of avalanches, with special reference to the formation of rock glaciers. Finally, we also present some initial results from numerical attempts of snow avalanche risk modelling within the study area.

  12. Water losses during technical snow production

    Science.gov (United States)

    Grünewald, Thomas; Wolfsperger, Fabian

    2017-04-01

    These days, the production of technical snow can be seen as a prerequisite for winter tourism. Huge amounts of water are used for technical snow production by ski resorts, especially in the beginning of the winter season. The aim is to guarantee an appropriate amount of snow to reliably provide optimal ski runs until the date of season opening in early December. Technical snow is generated by pumping pressurized water through the nozzles of a snow machine and dispersing the resulting spray of small water droplets which freeze during their travel to the ground. Cooling and freezing of the droplets can only happen if energy is emitted to the air mass surrounding the droplets. This heat transfer is happening through convective cooling and though evaporation and sublimation of water droplets and ice particles. This means that also mass is lost from the droplets and added in form of vapor to the air. It is important to note that not all water that is pumped through the snow machine is converted to snow distributed on the ground. Significant amounts of water are lost due to wind drift, sublimation and evaporation while droplets are traveling through the air or to draining of water which is not fully frozen when arriving at the ground. Studies addressing this question are sparse and the quantity of the water losses is still unclear. In order to assess this question in more detail, we obtained several systematic field observations at a test site near Davos, Switzerland. About a dozen of snow making tests had been performed during the last winter seasons. We compare the amount of water measured at the intake of the snow machine with the amount of snow accumulating at the ground during a night of snow production. The snow mass was calculated from highly detailed repeated terrestrial laser scanning measurements in combination with manually gathered snow densities. In addition a meteorological station had been set up in the vicinity observing all relevant meteorological

  13. Use of Sentinels to aid the global monitoring of snow cover

    Science.gov (United States)

    Pulliainen, Jouni; Salminen, Miia; Luojus, Kari; Metsämäki, Sari; Lemmetyinen, Juha; Takala, Matias; Cohen, Juval; Böttcher, Kristine

    2014-05-01

    Earth observation instruments onboard Sentinel satellites provide a unique opportunity for the monitoring and investigation of global snow processes. The issue of the possible decay of seasonal snow cover is highly relevant for climate research. In addition to water cycle, the extent and amount of snow affects to surface albedo, and indirectly to carbon cycling. The latter issue includes snow-induced changes in permafrost regions (active layer characteristics), as well as the effect of snow (melt) to vegetation growth and soil respiration. Recent advances in ESA DUE GlobSnow project have shown that by combining data from optical satellite sensors and passive microwave instruments advanced Climate Data Records (CDR) on seasonal snow cover can be produced, extending to time periods of over 30 years. The combined snow cover products provide information both on Snow Extent (SE) and Snow Water Equivalent (SWE) on a daily basis. The applicable instruments providing historical data for CDR generation include such microwave radiometers as SMMR, AMSR and SSMI/I, and such optical sensors as AVHRR, AATSR and VIIRS. Sentinel 3, especially its SLSTR instrument, is a prominent tool for expanding the snow CDR for forthcoming years. The developed global snow cover monitoring methodology, demonstrated and discussed here, derives the SWE information from passive microwave data (accompanied with in situ observations of snow depth at synoptic weather stations). The snow extent and fractional snow cover (FSC) on ground is derived from optical satellite data, in order to accurately map the continental line of seasonal snow cover, and to map regions of ephemeral snow cover. An advanced feature in the developed methodology is the provision of uncertainty information on snow cover characteristics associated with each individual satellite data footprint on ground and moment of time. In addition to assisting the generation and extension of the global snow cover CDR, Sentinel missions provide

  14. Snow Cover Monitoring Using MODIS Data in Liaoning Province, Northeastern China

    Directory of Open Access Journals (Sweden)

    Yu Lu

    2010-03-01

    Full Text Available This paper presents the results of snow cover monitoring studies in Liaoning Province, northeastern China, using MODIS data. Snow cover plays an important role in both the regional water balance and soil moisture properties during the early spring in northeastern China. In addition, heavy snowfalls commonly trigger hazards such as flooding, caused by rapid snow melt, or crop failure, resulting from fluctuations in soil temperature associated with changes in the snow cover. The latter is a function of both regional, or global, climatic changes, as well as fluctuations in the albedo resulting from variations in the Snow Covered Area (SCA. These impacts are crucial to human activities, especially to those living in middle-latitude areas such as Liaoning Province. Thus, SCA monitoring is currently an important tool in studies of global climate change, particularly because satellite remote sensing data provide timely and efficient snow cover information for large areas. In this study, MODIS L1B data, MODIS Daily Snow Products (MOD10A1 and MODIS 8-day Snow Products (MOD10A2 were used to monitor the SCA of Liaoning Province over the winter months of November–April, 2006–2008. The effects of cloud masking and forest masking on the snow monitoring results were also assessed. The results show that the SCA percentage derived from MODIS L1B data is relatively consistent, but slightly higher than that obtained from MODIS Snow Products. In situ data from 25 snow stations were used to assess the accuracy of snow cover monitoring from the SCA compared to the results from MODIS Snow Products. The studies found that the SCA results were more reliable than MODIS Snow Products in the study area.

  15. Monitoring snow cover and its effect on runoff regime in the Jizera Mountains

    Science.gov (United States)

    Kulasova, Alena

    2015-04-01

    The Jizera Mountains in the northern Bohemia are known by its rich snow cover. Winter precipitation represents usually a half of the precipitation in the hydrological year. Gradual snow accumulation and melt depends on the course of the particular winter period, the topography of the catchments and the type of vegetation. During winter the snow depth, and especially the snow water equivalent, are affected by the changing character of the falling precipitation, air and soil temperatures and the wind. More rapid snowmelt occurs more on the slopes without forest oriented to the South, while a gradual snowmelt occurs on the locations turned to the North and in forest. Melting snow recharges groundwater and affects water quality in an important way. In case of extreme situation the snowmelt monitoring is important from the point of view of flood protection of communities and property. Therefore the immediate information on the amount of water in snow is necessary. The way to get this information is the continuous monitoring of the snow depth and snow water equivalent. In the Jizera Mountains a regular monitoring of snow cover has been going on since the end of the 19th century. In the 80s of the last century the Jizera Mountains were affected by the increased fallout of pollutants in the air. There followed a gradual dieback of the forest cover and cutting down the upper part of the ridges. In order to get data for the quantification of runoff regime changes in the changing natural environment, the Czech Hydrometeorological Institute (CHMI) founded in the upper part of the Mountains several experimental catchments. One of the activities of the employees of the experimental basis is the regular measurement of snow cover at selected sites from 1982 up to now. At the same time snow cover is being observed using snow pillows, where its mass is monitored with the help of pressure sensors. In order to improve the reliability of the continuous measurement of the snow water

  16. Combining low-cost GPS receivers with upGPR to derive continuously liquid water content, snow height and snow water equivalent in Alpine snow covers

    Science.gov (United States)

    Koch, Franziska; Schmid, Lino; Prasch, Monika; Heilig, Achim; Eisen, Olaf; Schweizer, Jürg; Mauser, Wolfram

    2015-04-01

    The temporal evolution of Alpine snowpacks is important for assessing water supply, hydropower generation, flood predictions and avalanche forecasts. Especially in high mountain regions with an extremely varying topography, it is until now often difficult to derive continuous and non-destructive information on snow parameters. Since autumn 2012, we are running a new low-cost GPS (Global Positioning System) snow measurement experiment at the high alpine study site Weissfluhjoch (2450 m a.s.l.) in Switzerland. The globally and freely broadcasted GPS L1-band (1.57542 GHz) was continuously recorded with GPS antennas, which are installed at the ground surface underneath the snowpack. GPS raw data, containing carrier-to-noise power density ratio (C/N0) as well as elevation and azimuth angle information for each time step of 1 s, was stored and analyzed for all 32 GPS satellites. Since the dielectric permittivity of an overlying wet snowpack influences microwave radiation, the bulk volumetric liquid water content as well as daily melt-freeze cycles can be derived non-destructively from GPS signal strength losses and external snow height information. This liquid water content information is qualitatively in good accordance with meteorological and snow-hydrological data and quantitatively highly agrees with continuous data derived from an upward-looking ground-penetrating radar (upGPR) working in a similar frequency range. As a promising novelty, we combined the GPS signal strength data with upGPR travel-time information of active impulse radar rays to the snow surface and back from underneath the snow cover. This combination allows determining liquid water content, snow height and snow water equivalent from beneath the snow cover without using any other external information. The snow parameters derived by combining upGPR and GPS data are in good agreement with conventional sensors as e.g. laser distance gauges or snow pillows. As the GPS sensors are cheap, they can easily

  17. [Snow cover pollution monitoring in Ufa].

    Science.gov (United States)

    Daukaev, R A; Suleĭmanov, R A

    2008-01-01

    The paper presents the results of examining the snow cover polluted with heavy metals in the large industrial town of Ufa. The level of man-caused burden on the snow cover of the conventional parts of the town was estimated and compared upon exposure to a wide range of snow cover pollutants. The priority snow cover pollutants were identified among the test heavy metals.

  18. Preparation for Snow Cover Monitoring Using Sentinel-1 and Sentinel-3 Data

    Science.gov (United States)

    Nagler, Thomas; Rott, Helmut; Bippus, Gabriele; Ripper, Elisabeth

    2013-04-01

    Seasonal snow is a key element of the water cycle in high and mid latitudes, characterized by high spatial and temporal variability. Melt water is an important water resource in many mountain areas and also in lowlands downstream. Accurate observations of snow extent and physical properties of snow are not only of interest for climate change research, but are of great socio-economic importance. The Sentinel satellite series, including SAR and multispectral optical satellite data enable to monitor the snow extent from regional to global scale with high temporal sampling. Automatic processing lines of multispectral optical satellite data including rectification, calibration, cloud masking and snow detection have been implemented for generation of snow information and tested with various satellite sensors. Ongoing work is related with adapting and optimizing the snow retrieval algorithm for Sentinel 3 SLSTR and OCLI, making use of the full spectral capabilities of these sensors for generating high quality snow maps. The algorithm for mapping snow makes use of the typical spectral signature of snow in the visible (VIS) and short wave infrared (SWIR) region of the spectrum, which enables a clear discrimination against other surfaces. The baseline products include binary snow extent maps derived from combinations of VIS and SWIR bands and maps of fractional snow extent. The preliminary version of the retrieval algorithm uses dual-sensor Sentinel-3 SLSTR and OCLI data for mapping the snow extent and applies the multi-spectral un-mixing method and cloud screening making use of the various spectral channels of the two sensors. Snow conditions (wet/dry) can be retrieved from SAR observations as provided by Sentinel-1. The algorithm builds on the multi-temporal change detection technique for mapping melting snow areas and improved to make use of the dual-polarisation acquisition capabilities of Sentinel-1. In the presentation we will show first examples of the improved

  19. Data sets for snow cover monitoring and modelling from the National Snow and Ice Data Center

    Science.gov (United States)

    Holm, M.; Daniels, K.; Scott, D.; McLean, B.; Weaver, R.

    2003-04-01

    A wide range of snow cover monitoring and modelling data sets are pending or are currently available from the National Snow and Ice Data Center (NSIDC). In-situ observations support validation experiments that enhance the accuracy of remote sensing data. In addition, remote sensing data are available in near-real time, providing coarse-resolution snow monitoring capability. Time series data beginning in 1966 are valuable for modelling efforts. NSIDC holdings include SMMR and SSM/I snow cover data, MODIS snow cover extent products, in-situ and satellite data collected for NASA's recent Cold Land Processes Experiment, and soon-to-be-released ASMR-E passive microwave products. The AMSR-E and MODIS sensors are part of NASA's Earth Observing System flying on the Terra and Aqua satellites Characteristics of these NSIDC-held data sets, appropriateness of products for specific applications, and data set access and availability will be presented.

  20. Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

    Science.gov (United States)

    Stigter, Emmy E.; Wanders, Niko; Saloranta, Tuomo M.; Shea, Joseph M.; Bierkens, Marc F. P.; Immerzeel, Walter W.

    2017-07-01

    Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water equivalent (SWE). Therefore, in this study remotely sensed snow cover was combined with in situ observations and a modified version of the seNorge snow model to estimate (climate sensitivity of) SWE and snowmelt runoff in the Langtang catchment in Nepal. Snow cover data from Landsat 8 and the MOD10A2 snow cover product were validated with in situ snow cover observations provided by surface temperature and snow depth measurements resulting in classification accuracies of 85.7 and 83.1 % respectively. Optimal model parameter values were obtained through data assimilation of MOD10A2 snow maps and snow depth measurements using an ensemble Kalman filter (EnKF). Independent validations of simulated snow depth and snow cover with observations show improvement after data assimilation compared to simulations without data assimilation. The approach of modeling snow depth in a Kalman filter framework allows for data-constrained estimation of snow depth rather than snow cover alone, and this has great potential for future studies in complex terrain, especially in the Himalayas. Climate sensitivity tests with the optimized snow model revealed that snowmelt runoff increases in winter and the early melt season (December to May) and decreases during the late melt season (June to September) as a result of the earlier onset of snowmelt due to increasing temperature. At high elevation a decrease in SWE due to higher air temperature is (partly) compensated by an increase in precipitation, which emphasizes the need for accurate predictions on the changes in the spatial distribution of precipitation along with changes in temperature.

  1. Distribution of Snow and Maximum Snow Water Equivalent Obtained by LANDSAT Data and Degree Day Method

    Science.gov (United States)

    Takeda, K.; Ochiai, H.; Takeuchi, S.

    1985-01-01

    Maximum snow water equivalence and snowcover distribution are estimated using several LANDSAT data taken in snowmelting season over a four year period. The test site is Okutadami-gawa Basin located in the central position of Tohoku-Kanto-Chubu District. The year to year normalization for snowmelt volume computation on the snow line is conducted by year to year correction of degree days using the snowcover percentage within the test basin obtained from LANDSAT data. The maximum snow water equivalent map in the test basin is generated based on the normalized snowmelt volume on the snow line extracted from four LANDSAT data taken in a different year. The snowcover distribution on an arbitrary day in snowmelting of 1982 is estimated from the maximum snow water equivalent map. The estimated snowcover is compared with the snowcover area extracted from NOAA-AVHRR data taken on the same day. The applicability of the snow estimation using LANDSAT data is discussed.

  2. Technical snow production in skiing areas: conditions, practice, monitoring and modelling. A case study in Mayrhofen/Austria

    Science.gov (United States)

    Strasser, Ulrich; Hanzer, Florian; Marke, Thomas; Rothleitner, Michael

    2017-04-01

    The production of technical snow today is a self-evident feature of modern alpine skiing resort management. Millions of Euros are invested every year for the technical infrastructure and its operation to produce a homogeneous and continuing snow cover on the skiing slopes for the winter season in almost every larger destination in the Alps. In Austria, skiing tourism is a significant factor of the national economic structure. We present the framing conditions of technical snow production in the mid-size skiing resort of Mayrhofen (Zillertal Alps/Austria, 136 km slopes, elevation range 630 - 2.500 m a.s.l.). Production conditions are defined by the availability of water, the planned date for the season opening, and the climatic conditions in the weeks before. By means of an adapted snow production strategy an attempt is made to ecologically and economically optimize the use of water and energy resources. Monitoring of the snow cover is supported by a network of low-cost sensors and mobile snow depth recordings. Finally, technical snow production is simulated with the spatially distributed, physically based hydroclimatological model AMUNDSEN. The model explicitly considers individual snow guns and distributes the produced snow along the slopes. The amount of simulated snow produced by each device is a function of its type, of actual wet-bulb temperature at the location, of ski area infrastructure (in terms of water supply and pumping capacity), and of snow demand.

  3. Snow water equivalent interpolation for the Colorado River Basin from snow telemetry (SNOTEL) data

    OpenAIRE

    Fassnacht, SR; Dressler, KA; Bales, RC

    2003-01-01

    Inverse weighted distance and regression nonexact techniques were evaluated for interpolating methods snow water equivalent (SWE) across the entire Colorado River Basin of the western United States. A 1-km spacing was used for the gridding of snow telemetry (SNOTEL) measurements for the years 1993, 1998, and 1999, which on average, represented higher than average, average, and lower than average snow years. Because of the terrain effects, the regression techniques (hypsometric elevation and m...

  4. Assimilation of AMSR-E snow water equivalent data in a spatially-lumped snow model

    Science.gov (United States)

    Dziubanski, David J.; Franz, Kristie J.

    2016-09-01

    Accurately initializing snow model states in hydrologic prediction models is important for estimating future snowmelt, water supplies, and flooding potential. While ground-based snow observations give the most reliable information about snowpack conditions, they are spatially limited. In the north-central USA, there are no continual observations of hydrologically critical snow variables. Satellites offer the most likely source of spatial snow data, such as the snow water equivalent (SWE), for this region. In this study, we test the impact of assimilating SWE data from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument into the US National Weather Service (NWS) SNOW17 model for seven watersheds in the Upper Mississippi River basin. The SNOW17 is coupled with the NWS Sacramento Soil Moisture Accounting (SACSMA) model, and both simulated SWE and discharge are evaluated. The ensemble Kalman filter (EnKF) assimilation framework is applied and updating occurs on a daily cycle for water years 2006-2011. Prior to assimilation, AMSR-E data is bias corrected using data from the National Operational Hydrologic Remote Sensing Center (NOHRSC) airborne snow survey program. An average AMSR-E SWE bias of -17.91 mm was found for the study basins. SNOW17 and SAC-SMA model parameters from the North Central River Forecast Center (NCRFC) are used. Compared to a baseline run without assimilation, the SWE assimilation improved discharge for five of the seven study sites, in particular for high discharge magnitudes associated with snow melt runoff. SWE and discharge simulations suggest that the SNOW17 is underestimating SWE and snowmelt rates in the study basins. Deep snow conditions and periods of snowmelt may have introduced error into the assimilation due to difficulty obtaining accurate brightness temperatures under these conditions. Overall results indicate that the AMSR-E data and EnKF are viable and effective solutions for improving simulations

  5. Water and life from snow: A trillion dollar science question

    Science.gov (United States)

    Sturm, Matthew; Goldstein, Michael A.; Parr, Charles

    2017-05-01

    Snow provides essential resources/services in the form of water for human use, and climate regulation in the form of enhanced cooling of the Earth. In addition, it supports a thriving winter outdoor recreation industry. To date, the financial evaluation of the importance of snow is incomplete and hence the need for accelerated snow research is not as clear as it could be. With snow cover changing worldwide in several worrisome ways, there is pressing need to determine global, regional, and local rates of snow cover change, and to link these to financial analyses that allow for rational decision making, as risks related to those decisions involve trillions of dollars.

  6. Using crowdsourced web content for informing water systems operations in snow-dominated catchments

    Science.gov (United States)

    Giuliani, Matteo; Castelletti, Andrea; Fedorov, Roman; Fraternali, Piero

    2016-12-01

    Snow is a key component of the hydrologic cycle in many regions of the world. Despite recent advances in environmental monitoring that are making a wide range of data available, continuous snow monitoring systems that can collect data at high spatial and temporal resolution are not well established yet, especially in inaccessible high-latitude or mountainous regions. The unprecedented availability of user-generated data on the web is opening new opportunities for enhancing real-time monitoring and modeling of environmental systems based on data that are public, low-cost, and spatiotemporally dense. In this paper, we contribute a novel crowdsourcing procedure for extracting snow-related information from public web images, either produced by users or generated by touristic webcams. A fully automated process fetches mountain images from multiple sources, identifies the peaks present therein, and estimates virtual snow indexes representing a proxy of the snow-covered area. Our procedure has the potential for complementing traditional snow-related information, minimizing costs and efforts for obtaining the virtual snow indexes and, at the same time, maximizing the portability of the procedure to several locations where such public images are available. The operational value of the obtained virtual snow indexes is assessed for a real-world water-management problem, the regulation of Lake Como, where we use these indexes for informing the daily operations of the lake. Numerical results show that such information is effective in extending the anticipation capacity of the lake operations, ultimately improving the system performance.

  7. Historical Snow Cover and Water Resources Change in central Asia

    Science.gov (United States)

    ZHOU, H.; Aizen, E.; Aizen, V. B.

    2012-12-01

    Seasonal snow cover is a vital source of river runoff in arid and semi-arid regions of central Asia. Decrease of seasonal snow cover is one of the major consequences of climate change in central Asia. To quantify the historical snow cover change, its relationship to global and regional atmospheric processes, and its impact on water resources, a new database for cryospheric research in central Asia has been created in Asiacryoweb.org. It serves a data portal for snow cover, glacier, meteorology, hydrology and ice core data in central Asia, as well as a platform for further research collaborations. We analyze the historical snow cover change using data derived from AVHRR and MODIS images in 1986 - 2008. The results suggest that the snow cover extent in central Asia has declined significantly in general. We found significant decrease of seasonal snow cover in alpine regions surrounding major mountains (Tienshan, Pamir and Altai-Sayan) in summer; while in winter, northern part of Kazakhstan Steppe, mountains in Altai-Sayan and peripheral regions of Tienshan and Pamir mountains have seen significant strong increase of snow cover. Analysis of the relationship between snow cover extent and climate pattern indices shows a significant negative relationship between snow cover in Pamir mountains and Altai-Sayan mountains with Eastern Atlantic Pattern, and a significant negative relationship between snow cover in northern Aral-Caspian desert, Tienshan and the East Atlantic / West Russia pattern. And the Polar / Euraisa Pattern has a positive relationship with snow in Kazakhstan Steppe, Pamir, and Tienshan. The changing snow cover regime will affect not only the amount but also the timing of available water melting from snow.

  8. Snow

    Institute of Scientific and Technical Information of China (English)

    小雅

    2011-01-01

    雪花,雪花,白又凉。雪花,雪花,来了又走。啊,雪花!你去哪儿?我不知道,我不知道,飘到哪儿。%Snow, snow, White and cold. Snow, snow, Come and go. Oh, snow! Where do you go? I don't know, I don't know. Where I go.

  9. Snow Water Equivalent Retrieval Using Multitemporal COSMO Skymed X-Band SAR Images To Inform Water Systems Operation

    Science.gov (United States)

    Denaro, S.; Del Gobbo, U.; Castelletti, A.; Tebaldini, S.; Monti Guarnieri, A.

    2015-12-01

    In this work, we explore the use of exogenous snow-related information for enhancing the operation of water facilities in snow dominated watersheds. Traditionally, such information is assimilated into short-to-medium term streamflow forecasts, which are then used to inform water systems operation. Here, we adopt an alternative model-free approach, where the policy is directly conditioned upon a small set of selected observational data able to surrogate the snow-pack dynamics. In snow-fed water systems, the Snow Water Equivalent (SWE) stored in the basin often represents the largest contribution to the future season streamflow. The SWE estimation process is challenged by the high temporal and spatial variability of snow-pack and snow properties. Traditional retrieval methods, based on few ground sensors and optical satellites, often fail at representing the spatial diversity of snow conditions over large basins and at producing continuous (gap-free) data at the high sample frequency (e.g. daily) required to optimally control water systems. Against this background, SWE estimates from remote sensed radar products stand out, being able to acquire spatial information with no dependence on cloud coverage. In this work, we propose a technique for retrieving SWE estimates from Synthetic Aperture Radar (SAR) Cosmo SkyMed X-band images: a regression model, calibrated on ground SWE measurements, is implemented on dry snow maps obtained through a multi-temporal approach. The unprecedented spatial scale of this application is novel w.r.t. state of the art radar analysis conducted on limited spatial domains. The operational value of the SAR retrieved SWE estimates is evaluated based on ISA, a recently developed information selection and assessment framework. The method is demonstrated on a snow-rain fed river basin in the Italian Alps. Preliminary results show SAR images have a good potential for monitoring snow conditions and for improving water management operations.

  10. Evaluation of SNODAS snow depth and snow water equivalent estimates for the Colorado Rocky Mountains, USA

    Science.gov (United States)

    Clow, David W.; Nanus, Leora; Verdin, Kristine L.; Schmidt, Jeffrey

    2012-01-01

    The National Weather Service's Snow Data Assimilation (SNODAS) program provides daily, gridded estimates of snow depth, snow water equivalent (SWE), and related snow parameters at a 1-km2 resolution for the conterminous USA. In this study, SNODAS snow depth and SWE estimates were compared with independent, ground-based snow survey data in the Colorado Rocky Mountains to assess SNODAS accuracy at the 1-km2 scale. Accuracy also was evaluated at the basin scale by comparing SNODAS model output to snowmelt runoff in 31 headwater basins with US Geological Survey stream gauges. Results from the snow surveys indicated that SNODAS performed well in forested areas, explaining 72% of the variance in snow depths and 77% of the variance in SWE. However, SNODAS showed poor agreement with measurements in alpine areas, explaining 16% of the variance in snow depth and 30% of the variance in SWE. At the basin scale, snowmelt runoff was moderately correlated (R2 = 0.52) with SNODAS model estimates. A simple method for adjusting SNODAS SWE estimates in alpine areas was developed that uses relations between prevailing wind direction, terrain, and vegetation to account for wind redistribution of snow in alpine terrain. The adjustments substantially improved agreement between measurements and SNODAS estimates, with the R2 of measured SWE values against SNODAS SWE estimates increasing from 0.42 to 0.63 and the root mean square error decreasing from 12 to 6 cm. Results from this study indicate that SNODAS can provide reliable data for input to moderate-scale to large-scale hydrologic models, which are essential for creating accurate runoff forecasts. Refinement of SNODAS SWE estimates for alpine areas to account for wind redistribution of snow could further improve model performance. Published 2011. This article is a US Government work and is in the public domain in the USA.

  11. Upward-looking L-band FMCW radar for snow cover monitoring.

    Science.gov (United States)

    Okorn, Robert; Brunnhofer, Georg; Platzer, Thomas; Heilig, Achim; Schmid, Lino; Mitterer, Christoph; Schweizer, Jürg; Eisen, Olaf

    2014-07-01

    Forecasting snow avalanche danger in mountainous regions is of major importance for the protection of infrastructure in avalanche run-out zones. Inexpensive measurement devices capable of measuring snow height and layer properties in avalanche starting zones may help to improve the quality of risk assessment. We present a low-cost L-band frequency modulated continuous wave radar system (FMCW) in upward-looking configuration. To monitor the snowpack evolution, the radar system was deployed in fall and subsequently was covered by snowfalls. During two winter seasons we recorded reflections from the overlying snowpack. The influence of reflection magnitude and phase to the measured frequency spectra, as well as the influence of signal processing were investigated. We present a method to extract the phase of the reflection coefficients from the phase response of the frequency spectra and their integration into the presentation of the measurement data. The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection. We developed an automated and a semi-automated snow surface tracking algorithm. Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR). The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor. The percolation of water was observable in the radargrams. Results suggest that the upward-looking FMCW system may be a valuable alternative to conventional snow-depth sensors for locations, where fixed installations above ground are not feasible.

  12. Putting humans in the loop: Using crowdsourced snow information to inform water management

    Science.gov (United States)

    Fedorov, Roman; Giuliani, Matteo; Castelletti, Andrea; Fraternali, Piero

    2016-04-01

    The unprecedented availability of user generated data on the Web due to the advent of online services, social networks, and crowdsourcing, is opening new opportunities for enhancing real-time monitoring and modeling of environmental systems based on data that are public, low-cost, and spatio-temporally dense, possibly contributing to our ability of making better decisions. In this work, we contribute a novel crowdsourcing procedure for computing virtual snow indexes from public web images, either produced by users or generated by touristic webcams, which is based on a complex architecture designed for automatically crawling content from multiple web data sources. The procedure retains only geo-tagged images containing a mountain skyline, identifies the visible peaks in each image using a public online digital terrain model, and classifies the mountain image pixels as snow or no-snow. This operation yields a snow mask per image, from which it is possible to extract time series of virtual snow indexes representing a proxy of the snow covered area. The value of the obtained virtual snow indexes is estimated in a real world water management problem. We consider the snow-dominated catchment of Lake Como, a regulated lake in Northern Italy, where snowmelt represents the most important contribution to seasonal lake storage, and we used the virtual snow indexes for informing the daily operation of the lake's dam. Numerical results show that such information is effective in extending the anticipation capacity of the lake operations, ultimately improving the system performance.

  13. Photographic Snow-cover Monitoring on St Sorlin Glacier, France.

    Science.gov (United States)

    Gerbaux, M.; Genthon, C.; Dedieu, J.; Balestrieri, J.

    2004-12-01

    Like most other glaciers in the Alps, the St Sorlin glacier (french Alps, 45.16°N, 6.16°E, 2900 m asl mean elevation and 3km2 of surface area) has been retreating fast in the last 20 years. To understand the meteorological factors responsible for this retreat, and to tentatively predict glaciers evolution in a changing (warming) climate, we use a distributed snow/ice mass and energy balance model derived from the CROCUS snow model (Météo-France). There is no direct meteorological observation on or near St Sorlin glacier yet, and hourly meteorology to force the snow/ice model is obtained from disaggregated meteorological analyses. The model is found to reproduce the St Sorlin mass balance of the last 20 years as obtained from field glaciological measurements and stereophotographic reconstructions. The model is also found to reproduce the interannual variations of the equilibrium line as determined from optical satellite imagery. Because of the albedo feedback involved, it is also important to verify that the summer snow/ice transition on the glacier is correctly simulated. Thus, an automated photographic system was set up facing St Sorlin glacier to monitor the evolution of the snow cover. The system was installed on the 13th of July 2004 and is still in operation at time of abstract writing. Digital photographies are taken every 4 hours, permitting so far at least one non-obstructed (rain, fog) picture per day. The first pictures in the series show an almost fully snow-covered glacier while the latest ones show bare ice up to the highest parts of the glacier. Snow is occasionally deposited during precipitation events but hardly last more than 3 days. Snow line position is deduced from pictures using a DEM with georeferenced points visible on pictures. It should then be compared with the modelled one. The automated photographic system provides not only snow cover to check snow/ice model results at seasonal time-scales, but also qualitative meteorological

  14. Snow cover data derived from MODIS for water balance applications

    Directory of Open Access Journals (Sweden)

    A. Gafurov

    2009-02-01

    Full Text Available Snow cover information is of central importance for the estimation of water storage in cold mountainous regions. It is difficult to assess distributed snow cover information in a catchment in order to estimate possible water resources. It is especially a challenge to obtain snow cover information for high mountainous areas. Usually, snow depth is measured at meteorological stations, and it is relatively difficult to extrapolate this spatially or temporally since it highly depends on available energy and topography. The snow coverage of a catchment gives detailed information about the catchment's potential source for water. Many regions lack meteorological stations that measure snow, and usually no stations are available at high elevations.

    Satellite information is a very valuable source for obtaining several environmental parameters. One of the advantages is that the data is mostly provided in a spatially distributed format. This study uses satellite data to estimate snow coverage on high mountainous areas. Moderate-resolution Imaging Spectroradiometer (MODIS snow cover data is used in the Kokcha Catchment located in the north-eastern part of Afghanistan. The main disadvantage of MODIS data that restricts its direct use in environmental applications is cloud coverage. This is why this study is focused on eliminating cloud covered cells and estimating cell information under cloud covered cells using six logical, spatial and temporal approaches. The results give total cloud removal and mapping of snow cover for the study areas.

  15. Snow cover data derived from MODIS for water balance applications

    Science.gov (United States)

    Gafurov, A.; Bárdossy, A.

    2009-02-01

    Snow cover information is of central importance for the estimation of water storage in cold mountainous regions. It is difficult to assess distributed snow cover information in a catchment in order to estimate possible water resources. It is especially a challenge to obtain snow cover information for high mountainous areas. Usually, snow depth is measured at meteorological stations, and it is relatively difficult to extrapolate this spatially or temporally since it highly depends on available energy and topography. The snow coverage of a catchment gives detailed information about the catchment's potential source for water. Many regions lack meteorological stations that measure snow, and usually no stations are available at high elevations. Satellite information is a very valuable source for obtaining several environmental parameters. One of the advantages is that the data is mostly provided in a spatially distributed format. This study uses satellite data to estimate snow coverage on high mountainous areas. Moderate-resolution Imaging Spectroradiometer (MODIS) snow cover data is used in the Kokcha Catchment located in the north-eastern part of Afghanistan. The main disadvantage of MODIS data that restricts its direct use in environmental applications is cloud coverage. This is why this study is focused on eliminating cloud covered cells and estimating cell information under cloud covered cells using six logical, spatial and temporal approaches. The results give total cloud removal and mapping of snow cover for the study areas.

  16. Assessment of Northern Hemisphere Snow Water Equivalent Datasets in ESA SnowPEx project

    Science.gov (United States)

    Luojus, Kari; Pulliainen, Jouni; Cohen, Juval; Ikonen, Jaakko; Derksen, Chris; Mudryk, Lawrence; Nagler, Thomas; Bojkov, Bojan

    2016-04-01

    Reliable information on snow cover across the Northern Hemisphere and Arctic and sub-Arctic regions is needed for climate monitoring, for understanding the Arctic climate system, and for the evaluation of the role of snow cover and its feedback in climate models. In addition to being of significant interest for climatological investigations, reliable information on snow cover is of high value for the purpose of hydrological forecasting and numerical weather prediction. Terrestrial snow covers up to 50 million km² of the Northern Hemisphere in winter and is characterized by high spatial and temporal variability. Therefore satellite observations provide the best means for timely and complete observations of the global snow cover. There are a number of independent SWE products available that describe the snow conditions on multi-decadal and global scales. Some products are derived using satellite-based information while others rely on meteorological observations and modelling. What is common to practically all the existing hemispheric SWE products, is that their retrieval performance on hemispherical and multi-decadal scales are not accurately known. The purpose of the ESA funded SnowPEx project is to obtain a quantitative understanding of the uncertainty in satellite- as well as model-based SWE products through an internationally coordinated and consistent evaluation exercise. The currently available Northern Hemisphere wide satellite-based SWE datasets which were assessed include 1) the GlobSnow SWE, 2) the NASA Standard SWE, 3) NASA prototype and 4) NSIDC-SSM/I SWE products. The model-based datasets include: 5) the Global Land Data Assimilation System Version 2 (GLDAS-2) product 6) the European Centre for Medium-Range Forecasts Interim Land Reanalysis (ERA-I-Land) which uses a simple snow scheme 7) the Modern Era Retrospective Analysis for Research and Applications (MERRA) which uses an intermediate complexity snow scheme; and 8) SWE from the Crocus snow scheme, a

  17. Monitoring Snow Using Geostationary Satellite Retrievals During the SAAWSO Project

    Science.gov (United States)

    Rabin, Robert M.; Gultepe, Ismail; Kuligowski, Robert J.; Heidinger, Andrew K.

    2016-09-01

    The SAAWSO (Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations) field programs were conducted by Environment Canada near St. Johns, NL and Goose Bay, NL in the winters of 2012-13 and 2013-14, respectively. The goals of these programs were to validate satellite-based nowcasting products, including snow amount, wind intensity, and cloud physical parameters (e.g., cloud cover), over northern latitudes with potential applications to Search And Rescue (SAR) operations. Ground-based in situ sensors and remote sensing platforms were used to measure microphysical properties of precipitation, clouds and fog, radiation, temperature, moisture and wind profiles. Multi-spectral infrared observations obtained from Geostationary Operational Environmental Satellite (GOES)-13 provided estimates of cloud top temperature and height, phase (water, ice), hydrometer size, extinction, optical depth, and horizontal wind patterns at 15 min intervals. In this work, a technique developed for identifying clouds capable of producing high snowfall rates and incorporating wind information from the satellite observations is described. The cloud top physical properties retrieved from operational satellite observations are validated using measurements obtained from the ground-based in situ and remote sensing platforms collected during two precipitation events: a blizzard heavy snow storm case and a moderate snow event. The retrieved snow precipitation rates are found to be comparable to those of ground-based platform measurements in the heavy snow event.

  18. SNOW COVER MONITORING BY REMOTE SENSING AND SNOWMELT RUNOFF CALCULATION IN THE UPPER HUANGHE RIVER BASIN

    Institute of Scientific and Technical Information of China (English)

    LANYong-chao; MAQua-jie; 等

    2002-01-01

    The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai-Xizang(Tibet)Plateau of China.The melt-water from the snow-cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring .So snowmelt runoff forecast has importance for hydropower,flood prevention and water resources utilize-tion.The application of remote sensing and Geographic Information System(GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper.The key parame-ter-snow cover area can be computed by satellite images from multi-platform,multi-templral and multi-spectral.A clus-ter of snow-cover data can be yielded by means of the classification filter method.Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning .According to the typical samples extracting snow covered moun-tained in detail also.The runoff snowmelt models based on the snow-cover data from NOAA images and observation data of runoff,precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reser-voir,which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June.The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin.With the develop-ment of remote sensing technique and the progress of the interpretation method,the forecast accuracy of snowmelt runoff will be improved in the near future .Large scale extent and few stations are two objective reality situations in Chian,so they should be considered in simulation and forecast.Apart from dividing ,the derivation of

  19. SNOW COVER MONITORING BY REMOTE SENSING AND SNOWMELT RUNOFF CALCULATION IN THE UPPER HUANGHE RIVER BASIN

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai-Xizang(Tibet)Plateau of China. The melt-water from the snow-cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring. So snowmelt runoff forecast has importance for hydropower, flood prevention and water resources utilization. The application of remote sensing and Geographic Information System (GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper. The key parameter- snow cover area can be computed by satellite images from multi-platform, multi-temporal and multi-spectral. A cluster of snow-cover data can be yielded by means of the classification filter method. Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning. According to the typical samples extracting snow covered mountainous region, the snowmelt runoff calculation models in the upper Huanghe River basin are presented and they are mentioned in detail also. The runoff snowmelt models based on the snow-cover data from NOAA images and observation data of runoff, precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reservoir , which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June. The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin. With the development of remote sensing technique and the progress of the interpretation method, the forecast accuracy of snowmelt runoff will be improved in the near future. Large scale extent and few stations are two

  20. Producing Snow Extent and Snow Water Equivalent Information for Climate Research Purposes - ESA DUE Globsnow Effort

    Science.gov (United States)

    Luojus, Kari; Pulliainen, Jouni; Rott, Helmut; Nagler, Thomas; Solberg, Rune; Wiesmann, Andreas; Derksen, Chris; Metsämäki, Sari; Malnes, Eirik; Bojkov, Bojan

    2010-05-01

    The European Space Agency (ESA) Data User Element (DUE) funded GlobSnow project aims at creating a global database of snow parameters for climate research purposes. The main objective is to create a long term dataset on two essential snow parameters. The project will provide information concerning the areal extent of snow (SE) on a global scale and snow water equivalent (SWE) for the Northern Hemisphere. Both products will include the end product derived from the satellite data along with accuracy information for each snow parameter. The temporal span of the SE product will be 15 years and the span for the SWE product will be 30 years. A key improvement of the snow products, when compared with the currently available data sets, will be the inclusion of a statistically derived accuracy estimate accompanying each SE or SWE estimate (on a pixel level). In addition to the SE and SWE time-series, an operational near-real time (NRT) snow information service will be implemented. The service will provide daily snow maps for hydrological, meteorological, and climate research purposes. The snow products will be based on data acquired from optical and passive microwave-based spaceborne sensors combined with ground-based weather station observations. The work was initiated in November 2008, and is being coordinated by the Finnish Meteorological Institute (FMI). Other project partners involved are NR (Norwegian Computing Centre), ENVEO IT GmbH, GAMMA Remote Sensing AG, Finnish Environment Institute (SYKE), Environment Canada (EC) and Northern Research Institute (Norut). Extensive algorithm evaluation efforts were carried out for the candidate SWE and SE algorithms during 2009 using ground truth data gathered from Canada, Scandinavia, Russia and the Alps. The acquired evaluation results have enabled the selection of the algorithms to be utilized for the GlobSnow SE and SWE products. The SWE product is derived using the FMI Algorithm and the SE product is a combination of NR and

  1. Modeling and monitoring avalanches caused by rain-on-snow events

    Science.gov (United States)

    Havens, S.; Marshall, H. P.; Trisca, G. O.; Johnson, J. B.; Nicholson, B.

    2014-12-01

    Direct-action avalanches occur during large storm cycles in mountainous regions, when stresses on the snowpack increase rapidly due to the load of new snow and outpace snow strengthening due to compaction. If temperatures rise above freezing during the storm and snowfall turns to rain, the near-surface snow undergoes rapid densification caused by the introduction of liquid water. This shock to the snowpack, if stability is near critical, can cause widespread immediate avalanching due to the large induced strain rates in the slab, followed by secondary delayed avalanches due to both the increased load as well as water percolation to the depth of a weak layer. We use the semi-empirical SNOow Slope Stability model (SNOSS) to estimate the evolution of stability prior to large avalanches during rain-on-snow events on Highway 21 north of Boise, Idaho. We have continuously monitored avalanche activity using arrays of infrasound sensors in the avalanche-prone section of HW21 near Stanley, in collaboration with the Idaho Transportation Department's avalanche forecasting program. The autonomous infrasound avalanche monitoring system provides accurate timing of avalanche events, in addition to capturing avalanche dynamics during some major releases adjacent to the array. Due to the remote location and low winter traffic volume, the highway is typically closed for multiple days during major avalanche cycles. Many major avalanches typically release naturally and reach the road, but due the complex terrain and poor visibility, manual observations are often not possible until several days later. Since most avalanche programs typically use explosives on a regular basis to control slope stability, the infrasound record of avalanche activity we have recorded on HW21 provides a unique opportunity to study large naturally triggered avalanches. We use a first-order physically based stability model to estimate the importance of precipitation phase, amount, and rate during major rain-on-snow

  2. Is snow sublimation important in the alpine water balance?

    Directory of Open Access Journals (Sweden)

    U. Strasser

    2007-09-01

    Full Text Available In alpine terrain, snow sublimation as a component of the winter moisture budget represents a proportion of precipitation which does not contribute to melt. To quantify its amount we analyze the spatial pattern of snow sublimation at the ground, from a canopy and from turbulent suspension during wind-induced snow transport for a high alpine area in the Berchtesgaden National Park (Germany, and we discuss the efficiency of these processes with respect to seasonal snowfall. Therefore, we utilized hourly meteorological recordings from a network of automatic stations, and a distributed simulation framework comprising validated, physically based models. Meteorological data records were spatially distributed over the simulation domain by means of a quasi-physically based interpolation scheme that accounts for topographic influences on the distributed fields. The applied simulation tools were: a detailed model for shortwave and longwave radiative fluxes, a mass and energy balance model for the ground snow cover, a model for the microclimatic conditions within a forest canopy and related snow-vegetation interactions including snow sublimation from the surface of the trees, and a model for the simulation of wind-induced snow transport and related sublimation from suspended snow particles. For each of the sublimation processes, mass rates were quantified and aggregated over an entire winter season. Sublimation from the ground and from most canopy types are spatially relatively homogeneous and sum up to about 100 mm of snow water equivalent (SWE over the winter period. Accumulated seasonal sublimation due to turbulent suspension is small in the valley areas, but can locally, at very wind-exposed mountain ridges, add up to more than 1000 mm of SWE. The fraction of these sublimation losses of winter snowfall is between 10 and 90%.

  3. The Airborne Snow Observatory: fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo

    Science.gov (United States)

    Snow cover and its melt dominate regional climate and water resources in many of the world’s mountainous regions. Snowmelt timing and magnitude in mountains tend to be controlled by absorption of solar radiation and snow water equivalent, respectively, and yet both of these are very poorly known ev...

  4. Spatial distribution of stable water isotopes in alpine snow cover

    Directory of Open Access Journals (Sweden)

    N. Dietermann

    2013-07-01

    Full Text Available The aim of this study was to analyse and predict the mean stable water isotopic composition of the snow cover at specific geographic locations and altitudes. In addition, the dependence of the isotopic composition of the entire snow cover on altitude was analysed. Snow in four Swiss catchments was sampled at the end of the accumulation period in April 2010 and a second time during snowmelt in May 2010 and analysed for stable isotope composition of 2H and 18O. The sampling was conducted at both south-facing and north-facing slopes at elevation differences of 100 m, for a total altitude difference of approximately 1000 m. The observed variability of isotopic composition of the snow cover was analysed with stepwise multiple linear regression models. The analysis indicated that there is only a limited altitude effect on the isotopic composition when considering all samples. This is due to the high variability of the isotopic composition of the precipitation during the winter months and, in particular in the case of south-facing slopes, an enrichment of heavy isotopes due to intermittent melting processes. This enrichment effect could clearly be observed in the samples which were taken later in the year. A small altitudinal gradient of the isotopic composition could only be observed at some north-facing slopes. However, the dependence of snow depth and the day of the year were significant predictor variables in all models. This study indicates the necessity to further study the variability of water isotopes in the snow cover to increase prediction for isotopic composition of snowmelt and hence increase model performance of residence time models for alpine areas in order to better understand the accumulation processes and the sources of water in the snow cover of high mountains.

  5. Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation

    Science.gov (United States)

    Forman, Bart; Reichle, Rofl; Rodell, Matt

    2011-01-01

    Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for example, suffers a loss of information in deep/wet snow packs. Similarly, MODIS suffers a loss of temporal correlation information beyond the initial accumulation and final ablation phases of the snow season. Gravimetric measurements, on the other hand, do not suffer from these limitations. In this study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation (DA) framework to better characterize SWE in the Mackenzie River basin located in northern Canada. Comparisons are made against independent, ground-based SWE observations, state-of-the-art modeled SWE estimates, and independent, ground-based river discharge observations. Preliminary results suggest improved SWE estimates, including improved timing of the subsequent ablation and runoff of the snow pack. Additionally, use of the DA procedure can add vertical and horizontal resolution to the coarse-scale GRACE measurements as well as effectively downscale the measurements in time. Such findings offer the potential for better understanding of the hydrologic cycle in snow-dominated basins located in remote regions of the globe where ground-based observation collection if difficult, if not impossible. This information could ultimately lead to improved freshwater resource management in communities dependent on snow melt as well as a reduction in the uncertainty of river discharge into the Arctic Ocean.

  6. Blocking of Snow/Water Slurry Flow in Pipeline Caused by Compression-Strengthening of Snow Column

    Directory of Open Access Journals (Sweden)

    Masataka Shirakashi

    2014-01-01

    Full Text Available In earlier works by the present authors, two systems for sustainable energy were proposed: (i a system for urban snow removal in winter and storage for air conditioning in summer, applied to Nagaoka City, which suffers heavy snow fall every winter, and (ii a district cooling system utilizing latent heat of ice to reduce the size of storage reservoir and transportation pipeline system. In these systems, the hydraulic conveying of snow or ice through pump-and-pipeline is the key technique to be developed, since characteristics of snow (ice/ water slurry is largely different from those of conventional non-cohesive solid particle slurries. In this study, the blocking of pipeline of snow/water slurry is investigated experimentally. While the blocking of conventional slurry occurs due to deposition of heavy particles at low flow velocity or arching of large rigid particles, that of snow/water slurry is caused by a compressed plug of snow formed due to cohesive nature of snow particles. This is because the strength of snow plug formed at a high resistance piping element, such as an orifice, becomes higher when the compression velocity is lower, resulting in a solid-like plug filling the whole channel upstream the element.

  7. Chemistry of snow and lake water in Antarctic region

    Indian Academy of Sciences (India)

    Kaushar Ali; Sunil Sonbawane; D M Chate; Devendraa Siingh; P S P Rao; P D Safai; K B Budhavant

    2010-12-01

    Surface snow and lake water samples were collected at different locations around Indian station at Antarctica, Maitri, during December 2004-March 2005 and December 2006-March 2007.Samples were analyzed for major chemical ions. It is found that average pH value of snow is 6.1. Average pH value of lake water with low chemical content is 6.2 and of lake water with high chemical content is 6.5.The Na+ and Cl− are the most abundantly occurring ions at Antarctica. Considerable amount of SO$^{2-}_{4}$ is also found in the surface snow and the lake water which is attributed to the oxidation of DMS produced by marine phytoplankton.Neutralization of acidic components of snow is mainly done by NH$^{+}_{4}$ and Mg2+. The Mg2+, Ca2+ and K+ are nearly equally effective in neutralizing the acidic components in lake water.The NH$^{+}_{4}$ and SO$^{2-}_{4}$ occur over the Antarctica region mostly in the form of (NH4)2SO4.

  8. Variation of snow water resources in northwestern China,1951—1997

    Institute of Scientific and Technical Information of China (English)

    李培基

    1999-01-01

    An observation study is carried out on snow mass amount estimate in northwestern China by using microwave derived snow depth charts employing data from SMMR in conjunction with daily snow depth, density and snow cover duration records for 46 ground climate stations. Spatial patterns, seasonal cycle, and interannual variation of snow cover are discussed. Results show that snow cover is the second largest water supply over the arid northwestern China,and unlike most other areas in the world, northwestern China did not experience any decrease in snow cover since 1987.Secular trends reveal systematic increase in snow mass and durations. Analysis of snow cover-climate relationship indicates that gradual increase in snow cover is primarily in response to increase in snow season precipitation.

  9. Spatial estimates of snow water equivalent from reconstruction

    Science.gov (United States)

    Rittger, Karl; Bair, Edward H.; Kahl, Annelen; Dozier, Jeff

    2016-08-01

    Operational ground-based measurements of snow water equivalent (SWE) do not adequately explain spatial variability in mountainous terrain. To address this problem, we combine satellite-based retrievals of fractional snow cover for the period 2000 to 2011 with spatially distributed energy balance calculations to reconstruct SWE values throughout each melt season in the Sierra Nevada of California. Modeled solar radiation, longwave radiation, and air temperature from NLDAS drive the snowmelt model. The modeled solar radiation compares well to ground observations, but modeled longwave radiation is slightly lower than observations. Validation of reconstructed SWE with snow courses and our own snow surveys shows that the model can accurately estimate SWE at the sampled locations in a variety of topographic settings for a range of wet to dry years. The relationships of SWE with elevation and latitude are significantly different for wet, mean and dry years as well as between drainages. In all the basins studied, the relationship between remaining SWE and snow-covered area (SCA) becomes increasingly correlated from March to July as expected because SCA is an important model input. Though the SWE is calculated retrospectively SCA observations are available in near-real time and combined with historical reconstructions may be sufficient for estimating SWE with more confidence as the melt season progresses.

  10. Integrated snow and avalanche monitoring syatem for Indian Himalaya using multi-temporal satellite imagery and ancillary data

    Science.gov (United States)

    Sharma, S. S.; Mani, Sneh; Mathur, P.

    The variations in the local climate, environment and altitude as well as fast snow cover build up and rapid changes in snow characteristics with passage of winter are major contributing factors to make snow avalanches as one of the threatening problems in the North West Himalaya. For sustainable development of these mountainous areas, a number of multi-purpose projects are being planned. In recent times, the danger of natural and man-made hazards is increasing and the availability of water is fluctuating; and thus, making the project implementation difficult. To overcome these difficulties to a great extent, an integrated monitoring system is required for short term as well as long term assessment of snowcover variation and avalanche hazard. In order to monitor the spatial extent of snow cover, satellite data can be employed on an operational basis. Spectral settings as well as the temporal and spatial resolution make time series NOAA-AVHHR and MODIS sensor data well suited for operational snow cover monitoring at regional or continental scale; Indian Remote Sensing Satellite (IRS) LISS, WiFS and AWiFS sensor data suitable for studies at larger scale; and microwave data for extraction of snow wetness information.. In the present paper, an attempt is made to study the trends of changes in snow characteristics and related avalanche phenomenon using time series multi-temporal, multi-resolution satellite data with respect to different ranges in Western Himalaya, namely Pir Panjal range, Great Himalaya range, Zanskar range, Ladakh range and Great Karakoram range. The operational processing of these data included geocoding, calibration, terrain normalization, classification, statistical post classification and derivation of snow cover statistics. The calibration and normalization of imageries allowed the application of physically based classification thresholds possible for albedo, brightness temperature and the Normalized Difference Snow Index (NDSI) parameters

  11. Integrated snow and avalanche monitoring system for Indian Himalaya using multi-temporal satellite imagery and ancillary data

    Science.gov (United States)

    Sharma, S. S.; Mani, Sneh; Mathur, P.

    The variations in the local climate, environment and altitude as well as fast snow cover build up and rapid changes in snow characteristics with passage of winter are major contributing factors to make snow avalanches as one of the threatening problems in the North West Himalaya. For sustainable development of these mountainous areas, a number of multi-purpose projects are being planned. In recent times, the danger of natural and man-made hazards is increasing and the availability of water is fluctuating; and thus, making the project implementation difficult. To overcome these difficulties to a great extent, an integrated monitoring system is required for short term as well as long term assessment of snowcover variation and avalanche hazard. In order to monitor the spatial extent of snow cover, satellite data can be employed on an operational basis. Spectral settings as well as the temporal and spatial resolution make time series NOAA-AVHHR and MODIS sensor data well suited for operational snow cover monitoring at regional or continental scale; Indian Remote Sensing Satellite (IRS) LISS, WiFS and AWiFS sensor data suitable for studies at larger scale; and microwave data for extraction of snow wetness information.. In the present paper, an attempt is made to study the trends of changes in snow characteristics and related avalanche phenomenon using time series multi-temporal, multi-resolution satellite data with respect to different ranges in Western Himalaya, namely Pir Panjal range, Great Himalaya range, Zanskar range, Ladakh range and Great Karakoram range. The operational processing of these data included geocoding, calibration, terrain normalization, classification, statistical post classification and derivation of snow cover statistics. The calibration and normalization of imageries allowed the application of physically based classification thresholds possible for albedo, brightness temperature and the Normalized Difference Snow Index (NDSI) parameters

  12. 7 CFR 612.2 - Snow survey and water supply forecast activities.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 6 2010-01-01 2010-01-01 false Snow survey and water supply forecast activities. 612... SUPPLY FORECASTS § 612.2 Snow survey and water supply forecast activities. To carry out the cooperative snow survey and water supply forecast program, NRCS: (a) Establishes, maintains, and operates...

  13. Imaging the water-snow line during a protostellar outburst

    CERN Document Server

    Cieza, Lucas A; Tobin, John; Bos, Steven P; Williams, Jonathan P; Perez, Sebastian; Zhu, Zhaohuan; Caceres, Claudio; Canovas, Hector; Dunham, Michael M; Hales, Antonio; Prieto, Jose L; Principe, David A; Schreiber, Matthias R; Ruiz-Rodriguez, Dary; Zurlo, Alice

    2016-01-01

    A snow-line is the region of a protoplanetary disk at which a major volatile, such as water or carbon monoxide, reaches its condensation temperature. Snow-lines play a crucial role in disk evolution by promoting the rapid growth of ice-covered grains. Signatures of the carbon monoxide snow-line (at temperatures of around 20 kelvin) have recently been imaged in the disks surrounding the pre-main-sequence stars TW Hydra and HD163296, at distances of about 30 astronomical units (au) from the star. But the water snow-line of a protoplanetary disk (at temperatures of more than 100 kelvin) has not hitherto been seen, as it generally lies very close to the star (less than 5 au away for solar-type stars). Water-ice is important because it regulates the efficiency of dust and planetesimal coagulation, and the formation of comets, ice giants and the cores of gas giants. Here we report images at 0.03-arcsec resolution (12 au) of the protoplanetary disk around V883 Ori, a protostar of 1.3 solar masses that is undergoing ...

  14. Snow Cover Monitoring Method by Using H J-1 Satellite Data%Snow Cover Monitoring Method by Using H J-1Satellite Data

    Institute of Scientific and Technical Information of China (English)

    WANG Li-tao; ZHOU Yi; ZHOU Qiang; WANG Shi-xin; YAN Fu-li

    2011-01-01

    Environment and Disasters Monitoring Microsatellite Constellation with high spatial resolution,high temporal resolution and high spectral resolution characteristics was put forward by China.HJ-1B satellite,one of the first two small optical satellites,had a CCD camera and an infrared camera,which would provide an important new data source for snow monitoring.In the present paper,through analyzing the sensor and data characteristics of HJ-1B,we proposed a new infrared normalized difference snow index (INDSI) referring to the traditional normalized difference snow index (NDSI).The accuracy of these two automatic snow recognition methods was estimated based on a supervised classification method.The accuracy of the traditional NDSI method was 97.761 9% while that of the new INDSI method was 98.617 1%.

  15. Estimation of snow water equivalent using a radiance assimilation scheme with a multi-layered snow physical model

    Science.gov (United States)

    Mounirou Toure, Ally

    The feasibility of a radiance assimilation using a multi-layered snow physical model to estimate snow physical parameters is studied. The work is divided in five parts. The first two chapters are dedicated to the literature review. In the third chapter, experimental work was conducted in the alpine snow to estimate snow correlation (for microwave emission modelling) using near-infrared digital photography. We made microwave radiometric and near-infrared reflectance measurements of snow slabs under different experimental conditions. We used an empirical relation to link near-infrared reflectance of snow to the specific surface area (SSA), and converted the SSA into the correlation length. From the measurements of snow radiances at 21 and 35 GHz, we derived the microwave scattering coefficient by inverting two coupled radiative transfer models (RTM) (the sandwich and six-flux model). The correlation lengths found are in the same range as those determined in the literature using cold laboratory work. The technique shows great potential in the determination of the snow correlation length under field conditions. In the fourth chapter, the performance of the ensemble Kalman filter (EnKF) for snow water equivalent (SWE) estimation is assessed by assimilating synthetic microwave observations at Ground Based Microwave Radiometer (GBMR-7) frequencies (18.7, 23.8, 36.5, 89 vertical and horizontal polarization) into a snow physics model, CROCUS. CROCUS has a realistic stratigraphic and ice layer modelling scheme. This work builds on previous methods that used snow physics model with limited number of layers. Data assimilation methods require accurate predictions of the brightness temperature (Tb) emitted by the snowpack. It has been shown that the accuracy of RTMs is sensitive to the stratigraphic representation of the snowpack. However, as the stratigraphic fidelity increases, the number of layers increases, as does the number of state variables estimated in the assimilation

  16. Monitoring the spatio-temporal evolution of the snow cover in the eastern Alps from MODIS data

    Science.gov (United States)

    Cianfarra, P.; Salvini, F.; Valt, M.

    2009-04-01

    Estimating the snow cover extent in mountain ranges is important for a wide variety purposes including of scientific studies, environmental and meteo-climatic applications, as well as predicting water availability for energy resource and agriculture. Moreover, the monitoring of the spatio-temporal variation of the snow cover thickness, coupled with ground data from weather stations, allows to identify avalanche risk areas after heavy snowfall. The aim of this study is to test an automatic procedure to identify and map the snow coverage for different altitude interval in the eastern part of the Alpine range. There has been much progress since 1966 when the first operational snow mapping was done by NOAA with spaceborne sensors that provide daily, global observations to monitor the variability in space and time in the extent of snow cover. MODIS sensors offer increased improvements relative to the AVHRR that has been operational for many years on the NOAA Polar Operational Environmental Satellite System. In this context the MODIS provides observations at a nominal spatial resolution of 500 m versus the 1.1 km spatial resolution of the AVHRR and continuously available (spatially and temporally), spectral band observation that span the visible and short-wave infrared wavelengths, including those useful for recognize snow cover. The other advantage of using MODIS data is its availability and cost by the NASA's server. In this work we used MOD02 (L1B) data providing calibrated radiance values at the sensor (without atmospheric correction). Snow cover map production included the following steps: selection of the images with clear sky conditions, geometric correction and georeferencing to UTM zone 32 ,WSG 84 ellipsoid, to eliminate the distortion of and the typical bow-tie effect that produces the observed not alignment of the scan lines in the row image; spatial sub setting to produce an image covering an area of about 200 x 120 km; identification of the snow cover was

  17. Validating reconstruction of snow water equivalent in California's Sierra Nevada using measurements from the NASA Airborne Snow Observatory

    Science.gov (United States)

    Bair, Edward H.; Rittger, Karl; Davis, Robert E.; Painter, Thomas H.; Dozier, Jeff

    2016-11-01

    Accurately estimating basin-wide snow water equivalent (SWE) is the most important unsolved problem in mountain hydrology. Models that rely on remotely sensed inputs are especially needed in ranges with few surface measurements. The NASA Airborne Snow Observatory (ASO) provides estimates of SWE at 50 m spatial resolution in several basins across the Western U.S. during the melt season. Primarily, water managers use this information to forecast snowmelt runoff into reservoirs; another impactful use of ASO measurements lies in validating and improving satellite-based snow estimates or models that can scale to whole mountain ranges, even those without ground-based measurements. We compare ASO measurements from 2013 to 2015 to four methods that estimate spatially distributed SWE: two versions of a SWE reconstruction method, spatial interpolation from snow pillows and courses, and NOAA's Snow Data Assimilation System (SNODAS). SWE reconstruction downscales energy forcings to compute potential melt, then multiplies those values by satellite-derived estimates of fractional snow-covered area to calculate snowmelt. The snowpack is then built in reverse from the date the snow is observed to disappear. The two SWE reconstruction models tested include one that employs an energy balance calculation of snowmelt, and one that combines net radiation and degree-day approaches to estimate melt. Our full energy balance model, without ground observations, performed slightly better than spatial interpolation from snow pillows, having no systematic bias and 26% mean absolute error when compared to SWE from ASO. Both reconstruction models and interpolation were more accurate than SNODAS.

  18. Modelling the snowmelt and the snow water equivalent by creating a simplified energy balance conceptual snow model

    Science.gov (United States)

    Riboust, Philippe; Thirel, Guillaume; Le Moine, Nicolas; Ribstein, Pierre

    2016-04-01

    A better knowledge of the accumulated snow on the watersheds will help flood forecasting centres and hydro-power companies to predict the amount of water released during spring snowmelt. Since precipitations gauges are sparse at high elevations and integrative measurements of the snow accumulated on watershed surface are hard to obtain, using snow models is an adequate way to estimate snow water equivalent (SWE) on watersheds. In addition to short term prediction, simulating accurately SWE with snow models should have many advantages. Validating the snow module on both SWE and snowmelt should give a more reliable model for climate change studies or regionalization for ungauged watersheds. The aim of this study is to create a new snow module, which has a structure that allows the use of measured snow data for calibration or assimilation. Energy balance modelling seems to be the logical choice for designing a model in which internal variables, such as SWE, could be compared to observations. Physical models are complex, needing high computational resources and many different types of inputs that are not widely measured at meteorological stations. At the opposite, simple conceptual degree-day models offer to simulate snowmelt using only temperature and precipitation as inputs with fast computing. Its major drawback is to be empirical, i.e. not taking into account all of the processes of the energy balance, which makes this kind of model more difficult to use when willing to compare SWE to observed measurements. In order to reach our objectives, we created a snow model structured by a simplified energy balance where each of the processes is empirically parameterized in order to be calculated using only temperature, precipitation and cloud cover variables. This model's structure is similar to the one created by M.T. Walter (2005), where parameterizations from the literature were used to compute all of the processes of the energy balance. The conductive fluxes into the

  19. Snow and Water Imaging Spectrometer (SWIS): development of a CubeSat-compatible instrument

    Science.gov (United States)

    Bender, Holly A.; Mouroulis, Pantazis; Gross, Johannes; Painter, Thomas; Smith, Christopher D.; Wilson, Daniel W.; Smith, Colin H.; Van Gorp, Byron E.; Eastwood, Michael L.

    2016-05-01

    The Snow and Water Imaging Spectrometer (SWIS) is a fast, high-uniformity, low-polarization sensitivity imaging spectrometer and telescope system designed for integration on a 6U CubeSat platform. Operating in the 350-1700 nm spectral region with 5.7 nm sampling, SWIS is capable of simultaneously addressing the demanding needs of coastal ocean science and snow and ice monitoring. New key technologies that facilitate the development of this instrument include a linear variable anti-reflection (LVAR) detector coating for stray light management, and a single drive on-board calibration mechanism utilizing a transmissive diffuser for solar calibration. We provide an overview of the SWIS instrument design, spacecraft configuration design, and potential science missions.

  20. C-Band SAR Imagery for Snow-Cover Monitoring at Treeline, Churchill, Manitoba, Canada

    Directory of Open Access Journals (Sweden)

    Frédérique C. Pivot

    2012-07-01

    Full Text Available RADARSAT and ERS-2 data collected at multiple incidence angles are used to characterize the seasonal variations in the backscatter of snow-covered landscapes in the northern Hudson Bay Lowlands during the winters of 1997/98 and 1998/99. The study evaluates the usefulness of C-band SAR systems for retrieving the snow water equivalent under dry snow conditions in the forest–tundra ecotone. The backscatter values are compared against ground measurements at six sampling sites, which are taken to be representative of the land-cover types found in the region. The contribution of dry snow to the radar return is evident when frost penetrates the first 20 cm of soil. Only then does the backscatter respond positively to changes in snow water equivalent, at least in the open and forested areas near the coast, where 1-dB increases in backscatter for each approximate 5–10 mm of accumulated water equivalent are observed at 20–31° incidence angles. Further inland, the backscatter shows either no change or a negative change with snow accumulation, which suggests that the radar signal there is dominated by ground surface scattering (e.g., fen when not attenuated by vegetation (e.g., forested and transition. With high-frequency ground-penetrating radar, we demonstrate the presence of a 10–20-cm layer of black ice underneath the snow cover, which causes the reduced radar returns (−15 dB and less observed in the inland fen. A correlation between the backscattering and the snow water equivalent cannot be determined due to insufficient observations at similar incidence angles. To establish a relationship between the snow water equivalent and the backscatter, only images acquired with similar incidence angles should be used, and they must be corrected for both vegetation and ground effects.

  1. Using continuous measurements of near-surface atmospheric water vapor isotopes to document snow-air interactions

    Science.gov (United States)

    Steen-Larsen, Hans Christian; Masson-Delmotte, Valerie; Hirabayashi, Motohiro; Winkler, Renato; Satow, Kazuhide; Prie, Frederic; Bayou, Nicolas; Brun, Eric; Cuffey, Kurt; Dahl-Jensen, Dorthe; Dumont, Marie; Guillevic, Myriam; Kipfstuhl, Sepp; Landais, Amaelle; Popp, Trevor; Risi, Camille; Steffen, Konrad; Stenni, Barbara; Sveinbjornsdottir, Arny

    2014-05-01

    Water stable isotope data from Greenland ice cores provide key paleoclimatic information. However, post-depositional processes linked with snow metamorphism remain poorly documented. For this purpose, a monitoring of the isotopic composition δ18O and δD at several height levels (up to 13 meter) of near-surface water vapor, precipitation and snow in the first 0.5 cm from the surface has been conducted during three summers (2010-2012) at NEEM, NW Greenland. We observe a clear diurnal cycle in both the value and gradient of the isotopic composition of the water vapor above the snow surface. The diurnal amplitude in δD is found to be ~15‰. The diurnal isotopic composition follows the absolute humidity cycle. This indicates a large flux of vapor from the snow surface to the atmosphere during the daily warming and reverse flux during the daily cooling. The isotopic measurements of the flux of water vapor above the snow give new insights into the post depositional processes of the isotopic composition of the snow. During nine 1-5 days periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and near-surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in-between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near-surface vapor isotopic composition. This is consistent with an estimated 60% mass turnover of surface snow per day driven by snow

  2. A new MODIS daily cloud free snow cover mapping algorithm on the Tibetan Plateau

    Institute of Scientific and Technical Information of China (English)

    XiaoDong Huang; XiaoHua Hao; QiSheng Feng; Wei Wang; TianGang Liang

    2014-01-01

    Because of similar reflective characteristics of snow and cloud, the weather status seriously affects snow monitoring using optical remote sensing data. Cloud amount analysis during 2010 to 2011 snow seasons shows that cloud cover is the major limitation for snow cover monitoring using MOD10A1 and MYD10A1. By use of MODIS daily snow cover products and AMSR-E snow wa-ter equivalent products (SWE), several cloud elimination methods were integrated to produce a new daily cloud free snow cover product, and information of snow depth from 85 climate stations in Tibetan Plateau area (TP) were used to validate the accuracy of the new composite snow cover product. The results indicate that snow classification accuracy of the new daily snow cover product reaches 91.7%when snow depth is over 3 cm. This suggests that the new daily snow cover mapping algorithm is suitable for monitoring snow cover dynamic changes in TP.

  3. Water Quality Monitoring Sites

    Data.gov (United States)

    Vermont Center for Geographic Information — Water Quality Monitoring Site identifies locations across the state of Vermont where water quality data has been collected, including habitat, chemistry, fish and/or...

  4. Using Snow Fences to Augument Fresh Water Supplies in Shallow Arctic Lakes

    Energy Technology Data Exchange (ETDEWEB)

    Stuefer, Svetlana

    2013-03-31

    , 2010, and 2011), we selected and monitored two lakes with similar hydrological regimes. Both lakes are located 30 miles south of Prudhoe Bay, Alaska, near Franklin Bluffs. One is an experimental lake, where we installed a snow fence; the other is a control lake, where the natural regime was preserved. The general approach was to compare the hydrologic response of the lake to the snowdrift during the summers of 2010 and 2011 against the baseline conditions in 2009. Highlights of the project included new data on snow transport rates on the Alaska North Slope, an evaluation of the experimental lake's hydrological response to snowdrift melt, and cost assessment of snowdrift‐generated water. High snow transport rates (0.49 kg/s/m) ensured that the snowdrift reached its equilibrium profile by winter's end. Generally, natural snowpack disappeared by the beginning of June in this area. In contrast, snow in the drift lasted through early July, supplying the experimental lake with snowmelt when water in other tundra lakes was decreasing. The experimental lake retained elevated water levels during the entire open‐water season. Comparison of lake water volumes during the experiment against the baseline year showed that, by the end of summer, the drift generated by the snow fence had increased lake water volume by at least 21-29%. We estimated water cost at 1.9 cents per gallon during the first year and 0.8 cents per gallon during the second year. This estimate depends on the cost of snow fence construction in remote arctic locations, which we assumed to be at $7.66 per square foot of snow fence frontal area. The snow fence technique was effective in augmenting the supply of lake water during summers 2010 and 2011 despite low rainfall during both summers. Snow fences are a simple, yet an effective, way to replenish tundra lakes with freshwater and increase water availability in winter. This research project was synergetic with the NETL project, "North Slope Decision

  5. Using Snow Fences to Augument Fresh Water Supplies in Shallow Arctic Lakes

    Energy Technology Data Exchange (ETDEWEB)

    Stuefer, Svetlana

    2013-03-31

    , 2010, and 2011), we selected and monitored two lakes with similar hydrological regimes. Both lakes are located 30 miles south of Prudhoe Bay, Alaska, near Franklin Bluffs. One is an experimental lake, where we installed a snow fence; the other is a control lake, where the natural regime was preserved. The general approach was to compare the hydrologic response of the lake to the snowdrift during the summers of 2010 and 2011 against the baseline conditions in 2009. Highlights of the project included new data on snow transport rates on the Alaska North Slope, an evaluation of the experimental lake's hydrological response to snowdrift melt, and cost assessment of snowdrift‐generated water. High snow transport rates (0.49 kg/s/m) ensured that the snowdrift reached its equilibrium profile by winter's end. Generally, natural snowpack disappeared by the beginning of June in this area. In contrast, snow in the drift lasted through early July, supplying the experimental lake with snowmelt when water in other tundra lakes was decreasing. The experimental lake retained elevated water levels during the entire open‐water season. Comparison of lake water volumes during the experiment against the baseline year showed that, by the end of summer, the drift generated by the snow fence had increased lake water volume by at least 21-29%. We estimated water cost at 1.9 cents per gallon during the first year and 0.8 cents per gallon during the second year. This estimate depends on the cost of snow fence construction in remote arctic locations, which we assumed to be at $7.66 per square foot of snow fence frontal area. The snow fence technique was effective in augmenting the supply of lake water during summers 2010 and 2011 despite low rainfall during both summers. Snow fences are a simple, yet an effective, way to replenish tundra lakes with freshwater and increase water availability in winter. This research project was synergetic with the NETL project, "North Slope Decision

  6. Upward-looking L-band FMCW radar for snow cover monitoring

    OpenAIRE

    2014-01-01

    Forecasting snow avalanche danger in mountainous regions is of major importance for the protection of infrastructure in avalanche run-out zones. Inexpensive measurement devices capable of measuring snow height and layer properties in avalanche starting zones may help to improve the quality of risk assessment. We present a low-cost L-band frequency modulated continuous wave radar system (FMCW) in upward-looking configuration. To monitor the snowpack evolution, the radar system was deployed in ...

  7. Automatic monitoring of the effective thermal conductivity of snow in a low Arctic shrub tundra

    Science.gov (United States)

    Domine, F.; Barrere, M.; Sarrazin, D.; Morin, S.

    2015-03-01

    The effective thermal conductivity of snow, keff, is a critical variable which determines the temperature gradient in the snowpack and heat exchanges between the ground and the atmosphere through the snow. Its accurate knowledge is therefore required to simulate snow metamorphism, the ground thermal regime, permafrost stability, nutrient recycling and vegetation growth. Yet, few data are available on the seasonal evolution of snow thermal conductivity in the Arctic. We have deployed heated needle probes on low Arctic shrub tundra near Umiujaq, Quebec, (56°34´ N; 76°29´ W) and monitored automatically the evolution of keff for two consecutive winters, 2012-2013 and 2013-2014, at 4 heights in the snowpack. Shrubs are 20 cm high dwarf birch. Here, we develop an algorithm for the automatic determination of keff from the heating curves and obtain 404 keff values. We evaluate possible errors and biases associated with the use of the heated needles. The time-evolution of keff is very different for both winters. This is explained by comparing the meteorological conditions in both winters, which induced different conditions for snow metamorphism. In particular, important melting events the second year increased snow hardness, impeding subsequent densification and increase in thermal conductivity. Shrubs are observed to have very important impacts on snow physical evolution: (1) shrubs absorb light and facilitate snow melt under intense radiation; (2) the dense twig network of dwarf birch prevents snow compaction and therefore keff increase; (3) the low density depth hoar that forms within shrubs collapsed in late winter, leaving a void that was not filled by snow.

  8. Automatic monitoring of the effective thermal conductivity of snow in a low-Arctic shrub tundra

    Science.gov (United States)

    Domine, F.; Barrere, M.; Sarrazin, D.; Morin, S.; Arnaud, L.

    2015-06-01

    The effective thermal conductivity of snow, keff, is a critical variable which determines the temperature gradient in the snowpack and heat exchanges between the ground and the atmosphere through the snow. Its accurate knowledge is therefore required to simulate snow metamorphism, the ground thermal regime, permafrost stability, nutrient recycling and vegetation growth. Yet, few data are available on the seasonal evolution of snow thermal conductivity in the Arctic. We have deployed heated needle probes on low-Arctic shrub tundra near Umiujaq, Quebec, (N56°34'; W76°29') and monitored automatically the evolution of keff for two consecutive winters, 2012-2013 and 2013-2014, at four heights in the snowpack. Shrubs are 20 cm high dwarf birch. Here, we develop an algorithm for the automatic determination of keff from the heating curves and obtain 404 keff values. We evaluate possible errors and biases associated with the use of the heated needles. The time evolution of keff is very different for both winters. This is explained by comparing the meteorological conditions in both winters, which induced different conditions for snow metamorphism. In particular, important melting events in the second year increased snow hardness, impeding subsequent densification and increase in thermal conductivity. We conclude that shrubs have very important impacts on snow physical evolution: (1) shrubs absorb light and facilitate snow melt under intense radiation; (2) the dense twig network of dwarf birch prevent snow compaction, and therefore keff increase; (3) the low density depth hoar that forms within shrubs collapsed in late winter, leaving a void that was not filled by snow.

  9. Water Quality Monitoring Manual.

    Science.gov (United States)

    Mason, Fred J.; Houdart, Joseph F.

    This manual is designed for students involved in environmental education programs dealing with water pollution problems. By establishing a network of Environmental Monitoring Stations within the educational system, four steps toward the prevention, control, and abatement of water pollution are proposed. (1) Train students to recognize, monitor,…

  10. Aerotechnogenic Monitoring of Urban Environment on Snow Cover Pollution (on the Example of Voronezh City

    Directory of Open Access Journals (Sweden)

    Prozhorina Tatyana Ivanovna

    2014-09-01

    Full Text Available Snow cover is characterized by high sorption ability and represents an informative object in the process of identifying the technogenic pollution of urban environment. The article contains the results of the research on the chemical composition of the snow which fell in Voronezh in the winter period of 2013–2014. The coefficients of chemical elements concentration were calculated to provide objective characteristics of snow cover pollution. The authors analyze the connection between the presence of pollutants in snow and the level of technogenic impact. The obtained ranges of anomaly coefficients among anions reflect the composition of technogenic emissions. The mineralization of snow water reliably characterizes the intensity of anthropogenic impact on the urban environment, and the value of mineralization snow samples ranges from 62,6 (background to 183,9 mg/l. Maximum values of mineralization (more than 150 mg/l are typical for samples taken in transport area. High values of salinity (more than 120 mg/l are observed in snow samples taken in the industrial area, which confirms the high “technogenic pressure” on the urban environment in zones of industrial and transport potential of the city. The investigated functional areas can be arranged in the following series by descending level of contamination: transport area > industrial zone > residential and recreational areas > background territory. The study of the chemical composition of snow cover in the various functional areas of Voronezh allows to conclude that the pH level, mineralization and the content of suspended solids in snow waters characterize the intensity of anthropogenic pressure on the urban environment, and the composition of melt waters indicates the nature of its pollution.

  11. Measurements of water surface snow lines in classical protoplanetary disks

    CERN Document Server

    Blevins, Sandra M; Banzatti, Andrea; Zhang, Ke; Najita, Joan R; Carr, John S; Salyk, Colette; Blake, Geoffrey A

    2015-01-01

    We present deep Herschel-PACS spectroscopy of far-infrared water lines from a sample of four protoplanetary disks around solar-mass stars, selected to have strong water emission at mid-infrared wavelengths. By combining the new Herschel spectra with archival Spitzer-IRS spectroscopy, we retrieve a parameterized radial surface water vapor distribution from 0.1-100 AU using two-dimensional dust and line radiative transfer modeling. The surface water distribution is modeled with a step model comprising of a constant inner and outer relative water abundance and a critical radius at which the surface water abundance is allowed to change. We find that the four disks have critical radii of $\\sim 3-11$ AU, at which the surface water abundance decreases by at least 5 orders of magnitude. The measured values for the critical radius are consistently smaller than the location of the surface snow line, as predicted by the observed spectral energy distribution. This suggests that the sharp drop-off of the surface water abu...

  12. Improved Marine Waters Monitoring

    Science.gov (United States)

    Palazov, Atanas; Yakushev, Evgeniy; Milkova, Tanya; Slabakova, Violeta; Hristova, Ognyana

    2017-04-01

    IMAMO - Improved Marine Waters Monitoring is a project under the Programme BG02: Improved monitoring of marine waters, managed by Bulgarian Ministry of environment and waters and co-financed by the Financial Mechanism of the European Economic Area (EEA FM) 2009 - 2014. Project Beneficiary is the Institute of oceanology - Bulgarian Academy of Sciences with two partners: Norwegian Institute for Water Research and Bulgarian Black Sea Basin Directorate. The Project aims to improve the monitoring capacity and expertise of the organizations responsible for marine waters monitoring in Bulgaria to meet the requirements of EU and national legislation. The main outcomes are to fill the gaps in information from the Initial assessment of the marine environment and to collect data to assess the current ecological status of marine waters including information as a base for revision of ecological targets established by the monitoring programme prepared in 2014 under Art. 11 of MSFD. Project activities are targeted to ensure data for Descriptors 5, 8 and 9. IMAMO aims to increase the institutional capacity of the Bulgarian partners related to the monitoring and assessment of the Black Sea environment. The main outputs are: establishment of real time monitoring and set up of accredited laboratory facilities for marine waters and sediments chemical analysis to ensure the ability of Bulgarian partners to monitor progress of subsequent measures undertaken.

  13. Snow season variability in a boreal-Arctic transition area monitored by MODIS data

    Science.gov (United States)

    Malnes, Eirik; Rune Karlsen, Stein; Johansen, Bernt; Bjerke, Jarle W.; Tømmervik, Hans

    2016-12-01

    The duration and extent of snow cover is expected to change rapidly with climate change. Therefore, there is a need for improved monitoring of snow for the benefit of forecasting, impact assessments and the population at large. Remotely sensed techniques prove useful for remote areas where there are few field-based monitoring stations. This paper reports on a study of snow season using snow cover area fraction data from the two northernmost counties in Norway, Troms and Finnmark. The data are derived from the daily 500 m standard snow product (MOD10A1) from the NASA Terra MODerate Resolution Imaging Spectroradiometer (MODIS) sensor for the 2000-2010 period. This dataset has been processed with multi-temporal interpolation to eliminate clouds. The resulting cloud-free daily time series of snow cover fraction maps, have subsequently been used to derive the first and last snow-free day for the entire study area. In spring, the correlation between the first snow-free day mapped by MODIS data and snow data from 40 meteorological stations was highly significant (p < 0.05) for 36 of the stations, and with a of bias of less than 10 days for 34 of the stations. In autumn, 31 of the stations show highly significant (p < 0.05) correlation with MODIS data, and the bias was less than 10 days for 27 of the stations. However, in some areas and some years, the start and end of the snow season could not be detected due to long overcast periods. In spring 2002 and 2004 the first snow-free day was early, but arrived late in 2000, 2005 and 2008. In autumn 2009 snowfall arrived more than 7 days earlier in 50% of the study area as compared to the 2000-2010 average. MODIS-based snow season products will be applicable for a wide range of sectors including hydrology, nature-based industries, climate change studies and ecology. Therefore refinement and further testing of this method should be encouraged.

  14. Infrasound monitoring of snow avalanches in the Italian Alps

    Science.gov (United States)

    Ripepe, Maurizio; Ulivieri, Giacomo; Marchetti, Emanuele; Chiambretti, Igor; Segor, Valerio; Pitet, Luca

    2010-05-01

    Risk assessment of snow avalanches is mostly related to weather conditions and snow cover. However a robust risk validation requires to identify all avalanches occurring, in order to compare predictions to real effects. For this purpose on December 2009 we installed a temporary 4-element, small aperture (100 m), infrasound array in the Alps. The array has been deployed south of Mt. Rosa, at an elevation of 2000 m a.s.l. in the valley of Gressoney, where natural avalanches are expected and triggered ones are regularly programmed. The array consists into 4 absolute pressure transducers with a sensitivity of 0.01 Pa in the 0.1-50 Hz frequency band and a 7 channel Guralp CMG-DM24 A/D converter, sampling at 100 Hz. Timing is achieved with a GPS receiver. The array is completely buried in snow. Gel cell batteries and 200 W solar panels provide the array power requirements (~3 W) and should allow a continuous operation during the winter season. A multi-channel semblance is carried out on the continuous data set as a function of slowness, back-azimuth and frequency of recorded infrasound in order to detect all avalanches occurring from the back-ground signal, strongly affected by microbarom and mountain induced gravity waves. This pilot experiment in Italy will allow to verify the efficiency of the system, and might represent an important validation to modeled avalanches activity during this winter season.

  15. Climate change impacts on snow water availability in the Euphrates-Tigris basin

    Directory of Open Access Journals (Sweden)

    M. Özdoğan

    2011-04-01

    Full Text Available This study investigates the effects of projected climate change on snow water availability in the Euphrates-Tigris basin using the Variable Infiltration Capacity (VIC macro scale hydrologic model and a set of regional climate-change outputs from 13 global circulation models (GCMs forced with two greenhouse gas emission scenarios for two time periods in the 21st century (2050 and 2090. The hydrologic model produces a reasonable simulation of seasonal and spatial variation in snow cover and associated snow water equivalent (SWE in the mountainous areas of the basin, although its performance is poorer at marginal snow cover sites. While there is great variation across GCM outputs influencing snow water availability, the majority of models and scenarios suggest a significant decline (between 10 and 60 percent in available snow water, particularly under the aggressive A2 climate change scenario and later in the 21st century. The changes in SWE are more stable when multi-model ensemble GCM outputs are used to minimize inter-model variability, suggesting a consistent and significant decrease in snow-covered areas and associated water availability in the headwaters of the Euphrates Tigris basin. Detailed analysis of future climatic conditions point to the combined effects of reduced precipitation and increased temperatures as primary drivers of reduced snowpack. Results also indicate a more rapid decline in snow cover in the lower elevation zones than the higher areas in a changing climate. The simulated changes in snow water availability have important implications for the future of water resources and associated hydropower generation and land-use management and planning in a region already ripe for interstate water conflict. While the changes in the frequency and intensity of snow-bearing circulation systems or the interannual variability related to climate were not considered, the simulated changes in snow water availability presented here are likely

  16. Modelling the spatial distribution of snow water equivalent at the catchment scale taking into account changes in snow covered area

    Directory of Open Access Journals (Sweden)

    T. Skaugen

    2011-12-01

    Full Text Available A successful modelling of the snow reservoir is necessary for water resources assessments and the mitigation of spring flood hazards. A good estimate of the spatial probability density function (PDF of snow water equivalent (SWE is important for obtaining estimates of the snow reservoir, but also for modelling the changes in snow covered area (SCA, which is crucial for the runoff dynamics in spring. In a previous paper the PDF of SWE was modelled as a sum of temporally correlated gamma distributed variables. This methodology was constrained to estimate the PDF of SWE for snow covered areas only. In order to model the PDF of SWE for a catchment, we need to take into account the change in snow coverage and provide the spatial moments of SWE for both snow covered areas and for the catchment as a whole. The spatial PDF of accumulated SWE is, also in this study, modelled as a sum of correlated gamma distributed variables. After accumulation and melting events the changes in the spatial moments are weighted by changes in SCA. The spatial variance of accumulated SWE is, after both accumulation- and melting events, evaluated by use of the covariance matrix. For accumulation events there are only positive elements in the covariance matrix, whereas for melting events, there are both positive and negative elements. The negative elements dictate that the correlation between melt and SWE is negative. The negative contributions become dominant only after some time into the melting season so at the onset of the melting season, the spatial variance thus continues to increase, for later to decrease. This behaviour is consistent with observations and called the "hysteretic" effect by some authors. The parameters for the snow distribution model can be estimated from observed historical precipitation data which reduces by one the number of parameters to be calibrated in a hydrological model. Results from the model are in good agreement with observed spatial moments

  17. Modelling the spatial distribution of snow water equivalent at the catchment scale taking into account changes in snow covered area

    Science.gov (United States)

    Skaugen, T.; Randen, F.

    2011-12-01

    A successful modelling of the snow reservoir is necessary for water resources assessments and the mitigation of spring flood hazards. A good estimate of the spatial probability density function (PDF) of snow water equivalent (SWE) is important for obtaining estimates of the snow reservoir, but also for modelling the changes in snow covered area (SCA), which is crucial for the runoff dynamics in spring. In a previous paper the PDF of SWE was modelled as a sum of temporally correlated gamma distributed variables. This methodology was constrained to estimate the PDF of SWE for snow covered areas only. In order to model the PDF of SWE for a catchment, we need to take into account the change in snow coverage and provide the spatial moments of SWE for both snow covered areas and for the catchment as a whole. The spatial PDF of accumulated SWE is, also in this study, modelled as a sum of correlated gamma distributed variables. After accumulation and melting events the changes in the spatial moments are weighted by changes in SCA. The spatial variance of accumulated SWE is, after both accumulation- and melting events, evaluated by use of the covariance matrix. For accumulation events there are only positive elements in the covariance matrix, whereas for melting events, there are both positive and negative elements. The negative elements dictate that the correlation between melt and SWE is negative. The negative contributions become dominant only after some time into the melting season so at the onset of the melting season, the spatial variance thus continues to increase, for later to decrease. This behaviour is consistent with observations and called the "hysteretic" effect by some authors. The parameters for the snow distribution model can be estimated from observed historical precipitation data which reduces by one the number of parameters to be calibrated in a hydrological model. Results from the model are in good agreement with observed spatial moments of SWE and SCA

  18. Automated Webcam Monitoring of Fractional Snow Cover in Northern Boreal Conditions

    Directory of Open Access Journals (Sweden)

    Ali Nadir Arslan

    2017-07-01

    Full Text Available Fractional snow cover (FSC is an important parameter to estimate snow water equivalent (SWE and surface albedo important to climatic and hydrological applications. The presence of forest creates challenges to retrieve FSC accurately from satellite data, as forest canopy can block the sensor’s view of snow cover. In addition to the challenge related to presence of forest, in situ data of FSC—necessary for algorithm development and validation—are very limited. This paper investigates the estimation of FSC using digital imagery to overcome the obstacle caused by forest canopy, and the possibility to use this imagery in the validation of FSC derived from satellite data. FSC is calculated here using an algorithm based on defining a threshold value according to the histogram of an image, to classify a pixel as snow-covered or snow-free. Images from the MONIMET camera network, producing a continuous image series in Finland, are used in the analysis of FSC. The results obtained from automated image analysis of snow cover are compared with reference data estimated by visual inspection of same images. The results show the applicability and usefulness of digital imagery in the estimation of fractional snow cover in forested areas, with a Root Mean Squared Error (RMSE in the range of 0.1–0.3 (with the full range of 0–1.

  19. Toward advanced daily cloud-free snow cover and snow water equivalent products from Terra-Aqua MODIS and Aqua AMSR-E measurements

    Science.gov (United States)

    Gao, Yang; Xie, Hongjie; Lu, Ning; Yao, Tandong; Liang, Tiangang

    2010-05-01

    SummaryBy taking advantage of the high spatial resolution of optical sensors and cloud penetration of a passive microwave sensor, a method is developed to generate new daily cloud-free snow cover (SC) and snow water equivalent (SWE) products, both in 500 m spatial resolution, utilizing daily Terra-Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Aqua Advanced Microwave Scanning Radiometer for NASA's Earth Observing System (AMSR-E) snow products. This method was tested in Fairbanks and Upper Susitna Valley, Alaska area for one hydrological year (October 2006-September 2007). The results confirm that daily MODIS products and Terra-Aqua MODIS combined products have similar and high classification accuracy (91-94%) in cloud-free conditions and that the daily combination can reduce cloud cover ˜10%. The results also show the snow accuracy of the new SC products is 86%, which is much higher than the 31%, 45%, and 49% of the Terra, Aqua, and Terra/Aqua combined snow cover products (in all weather conditions), respectively. The validation demonstrates that the accuracy of AMSR-E SWE products is 68.5% and they tend to overestimate SWE. Redistribution of SWE, based on sub-pixel analysis of AMSR-E pixels, not only generates the new product at higher spatial resolution, now more suitable for basin and regional monitoring and modeling, but also slightly increases the accuracy of the SWE estimations. This method can also be used in merging other optical data such as AVHRR, Landsat with passive microwave data such as SSMR, SSM/I, and for future NPP and NPOESS missions.

  20. Using hacked point and shoot cameras for time-lapse snow cover monitoring in an Alpine valley

    Science.gov (United States)

    Weijs, S. V.; Diebold, M.; Mutzner, R.; Golay, J. R.; Parlange, M. B.

    2012-04-01

    In Alpine environments, monitoring snow cover is essential get insight in the hydrological processes and water balance. Although measurement techniques based on LIDAR are available, their cost is often a restricting factor. In this research, an experiment was done using a distributed array of cheap consumer cameras to get insight in the spatio-temporal evolution of snowpack. Two experiments are planned. The first involves the measurement of eolic snow transport around a hill, to validate a snow saltation model. The second monitors the snowmelt during the melting season, which can then be combined with data from a wireless network of meteorological stations and discharge measurements at the outlet of the catchment. The poster describes the hardware and software setup, based on an external timer circuit and CHDK, the Canon Hack Development Kit. This latter is a flexible and developing software package, released under a GPL license. It was developed by hackers that reverse engineered the firmware of the camera and added extra functionality such as raw image output, more full control of the camera, external trigger and motion detection, and scripting. These features make it a great tool for geosciences. Possible other applications involve aerial stereo photography, monitoring vegetation response. We are interested in sharing experiences and brainstorming about new applications. Bring your camera!

  1. Infrasonic monitoring of snow avalanches in the Alps

    Science.gov (United States)

    Marchetti, E.; Ulivieri, G.; Ripepe, M.; Chiambretti, I.; Segor, V.

    2012-04-01

    Risk assessment of snow avalanches is mostly related to weather conditions and snow cover. However a robust risk validation requires to identify all avalanches occurring, in order to compare predictions to real effects. For this purpose on December 2010 we installed a permanent 4-element, small aperture (100 m), infrasound array in the Alps, after a pilot experiment carried out in Gressonay during the 2009-2010 winter season. The array has been deployed in the Ayas Valley, at an elevation of 2000 m a.s.l., where natural avalanches are expected and controlled events are regularly performed. The array consists into 4 Optimic 2180 infrasonic microphones, with a sensitivity of 10-3 Pa in the 0.5-50 Hz frequency band and a 4 channel Guralp CMG-DM24 A/D converter, sampling at 100 Hz. Timing is achieved with a GPS receiver. Data are transmitted to the Department of Earth Sciences of the University of Firenze, where data is recorded and processed in real-time. A multi-channel semblance is carried out on the continuous data set as a function of slowness, back-azimuth and frequency of recorded infrasound in order to detect all avalanches occurring from the back-ground signal, strongly affected by microbarom and mountain induced gravity waves. This permanent installation in Italy will allow to verify the efficiency of the system in short-to-medium range (2-8 km) avalanche detection, and might represent an important validation to model avalanches activity during this winter season. Moreover, the real-time processing of infrasonic array data, might strongly contribute to avalanche risk assessments providing an up-to-description of ongoing events.

  2. Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss

    Directory of Open Access Journals (Sweden)

    Yurong Cui

    2016-06-01

    Full Text Available Snow water equivalent (SWE is a key parameter in the Earth’s energy budget and water cycle. It has been demonstrated that SWE can be retrieved using active microwave remote sensing from space. This necessitates the development of forward models that are capable of simulating the interactions of microwaves and the snow medium. Several proposed models have described snow as a collection of sphere- or ellipsoid-shaped ice particles embedded in air, while the microstructure of snow is, in reality, more complex. Natural snow usually forms a sintered structure following mechanical and thermal metamorphism processes. In this research, the bi-continuous vector radiative transfer (bi-continuous-VRT model, which firstly constructs snow microstructure more similar to real snow and then simulates the snow backscattering signal, is used as the forward model for SWE estimation. Based on this forward model, a parameterization scheme of snow volume backscattering is proposed. A relationship between snow optical thickness and single scattering albedo at X and Ku bands is established by analyzing the database generated from the bi-continuous-VRT model. A cost function with constraints is used to solve effective albedo and optical thickness, while the absorption part of optical thickness is obtained from these two parameters. SWE is estimated after a correction for physical temperature. The estimated SWE is correlated with the measured SWE with an acceptable accuracy. Validation against two-year measurements, using the SnowScat instrument from the Nordic Snow Radar Experiment (NoSREx, shows that the estimated SWE using the presented algorithm has a root mean square error (RMSE of 16.59 mm for the winter of 2009–2010 and 19.70 mm for the winter of 2010–2011.

  3. The possibility of distance methods application for snow dump sites monitoring

    Directory of Open Access Journals (Sweden)

    Pasko Olga

    2016-01-01

    Full Text Available In this article the results of remote sensing of the Earth for monitoring of four snow dump sites in Tomsk are described. Their compliance with permitted type of the territory use was evaluated. Earlier unknown time of the operation start was identified. The spatial-temporal variability of areas was defined. The temperature profiles of snow dump and background sites were analyzed. Use of remote sensing data allowed easy identification of snow dump sites creation time. The fact that the sites are located out of zones of permitted type of the territory use was revealed, that is violation of the law. For the first time the cartographic material was collected and showed that in the recent years their areas increased in average in 18%. The fore-cast for the nearest years was made. The article contains satellite images indicting the degradation of soil-vegetative cover of snow dumps. The reasons are contamination and overcooling of the soil in the beginning of vegetation period. The research results became the initial material for perfection of snow dumps territories management and will be applied in the work of environmental protecting service. Approaches proposed by authors may be used in solving similar problems in any region.

  4. The interplay of snow, surface water, and groundwater reservoirs for integrated water resources management

    Science.gov (United States)

    Rajagopal, S.; Huntington, J.

    2015-12-01

    Changes in climate, growth in population and economy have increased the reliance on groundwater to augment supplies of surface water across the world, and especially the Western United States. Martis Valley, a high altitude, snow dominated watershed in the Sierra Nevada, California has both surface (river/reservoir) and groundwater resources that are utilized to meet demands within the valley. The recent drought and changing precipitation type (less snow, more rain) has stressed the regional surface water supply and has increased the reliance on groundwater pumping. The objective of this paper is to quantify how changes in climate and depletion of snow storage result in decreased groundwater recharge and increased groundwater use, and to assess if increased surface water storage can mitigate impacts to groundwater under historic and future climate conditions. These objectives require knowledge on the spatiotemporal distribution of groundwater recharge, discharge, and surface and groundwater interactions. We use a high resolution, physically-based integrated surface and groundwater model, GSFLOW, to identify key mechanisms that explain recent hydrologic changes in the region. The model was calibrated using a multi-criteria approach to various historical observed hydrologic fluxes (streamflow and groundwater pumping) and states (lake stage, groundwater head, snow cover area). Observations show that while groundwater use in the basin has increased significantly since the 1980's, it still remains a relatively minor component of annual consumptive water use. Model simulations suggest that changes from snow to rain will lead to increases in Hortonian and Dunnian runoff, and decreases in groundwater recharge and discharge to streams, which could have a greater impact on groundwater resources than increased pumping. These findings highlight the necessity of an integrated approach for evaluating natural and anthropogenic impacts on surface and groundwater resources.

  5. Water quality monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Conio, O. [Azienda Mediterranea Gas e Acqua spa, Genua (Italy)

    1998-12-31

    By involving institutions and rules, and technology as well, water resources management presents remarkable complexity. In institutions such a complexity is due to division of competence into monitoring activities, quality control, water utility supply and water treatment. As far as technology goes, complexity results from a wide range of physical, chemical and biological requisites, which define water quality according to specific water uses (for populations, farms, factories). Thus it`s necessary to have reliable and in-time environmental data, so to fulfil two complementary functions: 1) the control of any state of emergency, such as floods and accidental pollution, in order to take immediate measures by means of timely available information; 2) the mid- and long-term planning of water resources, so to achieve their reclamation, conservation and exploitation. An efficient and reliable way to attain these goals is to develop integrated continuous monitoring systems, which allow to control the quality of surface and underground water, the flow of bodies of water and those weather conditions that directly affect it. Such systems compose an environmental information network, which enables to collect and process data relative to the state of the body of water, its aquifer, and the weather conditions.

  6. Sodankylä manual snow survey program

    Directory of Open Access Journals (Sweden)

    L. Leppänen

    2015-12-01

    Full Text Available The manual snow survey program of the Arctic Research Centre of Finnish Meteorological Institute (FMI-ARC consists of numerous observations of natural seasonal taiga snowpack in Sodankylä, northern Finland. The easily accessible measurement areas represent the typical forest and soil types in the boreal forest zone. Systematic snow measurements began in 1909 with snow depth (SD and snow water equivalent (SWE; however some older records of the snow and ice cover exists. In 2006 the manual snow survey program expanded to cover snow macro- and microstructure from regular snow pits at several sites using both traditional and novel measurement techniques. Present-day measurements include observations of SD, SWE, temperature, density, horizontal layers of snow, grain size, specific surface area (SSA, and liquid water content (LWC. Regular snow pit measurements are performed weekly during the snow season. Extensive time series of manual snow measurements are important for the monitoring of temporal and spatial changes in seasonal snowpack. This snow survey program is an excellent base for the future research of snow properties.

  7. Using SnowScat to characterize the backscatter response of water stress in an agricultural canopy

    Science.gov (United States)

    Steele-Dunne, S. C.; Werner, C.; Wiesmann, A.; de Pater, J.; van Emmerik, T. H.; Schuettemeyer, D.; Rommen, B.; Van De Giesen, N.

    2013-12-01

    SnowScat is a ground-based, fully polarimetric, coherent stepped frequency continuous wave scatterometer operating in the range of 9-18GHz. Since 2009, it has been employed in several field campaigns in Switzerland and Finland to investigate the backscatter characteristics of snow. In this presentation, we will give an overview of its first deployment in an agricultural application. In July 2013, it was installed above a maize canopy in Flevoland in the Netherlands. The objective is to characterize the backscatter response of vegetation in response to natural variations in moisture availability. Backscatter is measured hourly at a range of incident and elevation angles. Meteorological data, soil moisture profiles and vegetation stage are combined to quantify water stress. Regular destructive vegetation sampling and dielectric property measurements are used to monitor variations in the canopy water content. Additional ancillary measurements include temperature profiles and NDVI measurements. Here, we will present a description of the installation, a summary of the data collected and some preliminary results.

  8. Using the SnowScat instrument to investigate the influence of canopy water dynamics on backscatter from maize.

    Science.gov (United States)

    Steele-Dunne, Susan; Werner, Charles; Wiesmann, Andreas; van Emmerik, Tim; de Pater, Job; Rommen, Bjorn; van de Giesen, Nick

    2014-05-01

    In this study, we investigate the potential to monitor canopy water dynamics using high (9-18GHz) frequency scatterometry. SnowScat was developed by Gamma RS (Switzerland), and is a ground-based fully polarimetric, coherent stepped-frequency, continuous wave scatterometer that operates in the range 9-18GHz. Every winter since 2009, it has been deployed in Sodankylä(Finland) to investigate the potential use of scatterometry to measure snow mass and structure, grain size and type, as well as snow pack morphology. The proposed study is its first deployment in an agricultural setting. From July to September 2013, SnowScat was installed on a tower above a maize canopy in Flevoland in the Netherlands. The objective of the field campaign was to characterize the backscatter response of vegetation in response to natural variations in moisture availability. The full frequency range was swept every hour and data were collected for all polarizations, for five azimuth and five elevation angles. The azimuth angle was varied from perpendicular to almost parallel to maize row direction. Elevation angle was varied from 30 to 70 degrees in increments of 10 degrees. A HOBO weather station was installed to measure precipitation, solar radiation, wind speed and direction, relative humidity and air temperature. Vegetation stage, structure and geometry were monitored weekly. Destructive vegetation sampling and dielectric property measurements were used to monitor canopy water content. The soil moisture profile was monitored at two locations, and a hand-held probe was used for regular surface soil moisture measurements. Ancillary data include soil and canopy temperature profiles as well as NDVI. Here we present a review of the meteorological and hydrological conditions during the experiment, and a description of their influence on soil and canopy geometry, water content and dielectric properties. Finally, we analyze the impact of soil and canopy characteristics on backscatter as a

  9. Changes in seasonal snow liquid water content during the snowmelt period in the Western Tianshan Mountains, China

    Directory of Open Access Journals (Sweden)

    H. Lu

    2012-09-01

    Full Text Available Snow liquid water content is a very important parameter for snow hydrological processes, avalanche research and snow cover mapping by remote sensing. Snow liquid water content was measured with a portable instrument (Snow Fork in the Tianshan Station for Snow Cover and Avalanche Research, Chinese Academy of Sciences during the snowmelt period in spring 2010. This study analyzed the temporal and spatial distribution of snow liquid water content in different weather conditions. The average liquid water content of snow in the whole layer exponentially increased and can be calculated using a regression function of prior moving average temperature. The proportion of net radiation, sensible heat flux and latent heat flux in total energy changed in different snowmelt period. During the pre-snowmelt period (0.3% ≤ Wvol < 1%, snow liquid water content and its temporal variation were relatively small, with liquid water accumulated in the coarse snow layer. During the mid-snowmelt period (1% ≤ Wvol < 2.5%, the variation was significant in the upper layer and decreased drastically during the snowfall and the following one to two days. Only the temporal variation decreased after rain or snow (ROS events. During the late-snowmelt period (Wvol ≥ 2.5%, the distribution and variation of every snow layer showed a~uniform trend, and the effect of ROS events on liquid water content only occurred during rainfall and snowfall.

  10. Climate change impacts on snow water availability in the Euphrates-Tigris basin

    Directory of Open Access Journals (Sweden)

    M. Özdoğan

    2011-09-01

    Full Text Available This study investigates the effects of projected climate change on snow water availability in the Euphrates-Tigris basin using the Variable Infiltration Capacity (VIC macro scale hydrologic model and a set of regional climate-change outputs from 13 global circulation models (GCMs forced with two greenhouse gas emission scenarios for two time periods in the 21st century (2050 and 2090. The hydrologic model produces a reasonable simulation of seasonal and spatial variation in snow cover and associated snow water equivalent (SWE in the mountainous areas of the basin, although its performance is poorer at marginal snow cover sites. While there is great variation across GCM outputs influencing snow water availability, the majority of models and scenarios suggest a significant decline (between 10 and 60 percent in available snow water, particularly under the high-impact A2 climate change scenario and later in the 21st century. The changes in SWE are more stable when multi-model ensemble GCM outputs are used to minimize inter-model variability, suggesting a consistent and significant decrease in snow-covered areas and associated water availability in the headwaters of the Euphrates-Tigris basin. Detailed analysis of future climatic conditions point to the combined effects of reduced precipitation and increased temperatures as primary drivers of reduced snowpack. Results also indicate a more rapid decline in snow cover in the lower elevation zones than the higher areas in a changing climate but these findings also contain a larger uncertainty. The simulated changes in snow water availability have important implications for the future of water resources and associated hydropower generation and land-use management and planning in a region already ripe for interstate water conflict. While the changes in the frequency and intensity of snow-bearing circulation systems or the interannual variability related to climate were not considered, the simulated

  11. The Potential for Snow to Supply Human Water Demand in the Present and Future

    Science.gov (United States)

    Mankin, Justin S.; Viviroli, Daniel; Singh, Deepti; Hoekstra, Arjen Y.; Diffenbaugh, Noah S.

    2015-01-01

    Runoff from snowmelt is regarded as a vital water source for people and ecosystems throughout the Northern Hemisphere (NH). Numerous studies point to the threat global warming poses to the timing and magnitude of snow accumulation and melt. But analyses focused on snow supply do not show where changes to snowmelt runoff are likely to present the most pressing adaptation challenges, given sub-annual patterns of human water consumption and water availability from rainfall. We identify the NH basins where present spring and summer snowmelt has the greatest potential to supply the human water demand that would otherwise be unmet by instantaneous rainfall runoff. Using a multi-model ensemble of climate change projections, we find that these basins - which together have a present population of approx. 2 billion people - are exposed to a 67% risk of decreased snow supply this coming century. Further, in the multi-model mean, 68 basins (with a present population of more than 300 million people) transition from having sufficient rainfall runoff to meet all present human water demand to having insufficient rainfall runoff. However, internal climate variability creates irreducible uncertainty in the projected future trends in snow resource potential, with about 90% of snow-sensitive basins showing potential for either increases or decreases over the near-term decades. Our results emphasize the importance of snow for fulfilling human water demand in many NH basins, and highlight the need to account for the full range of internal climate variability in developing robust climate risk management decisions.

  12. The potential for snow to supply human water demand in the present and future

    Science.gov (United States)

    Mankin, Justin S.; Viviroli, Daniel; Singh, Deepti; Hoekstra, Arjen Y.; Diffenbaugh, Noah S.

    2015-11-01

    Runoff from snowmelt is regarded as a vital water source for people and ecosystems throughout the Northern Hemisphere (NH). Numerous studies point to the threat global warming poses to the timing and magnitude of snow accumulation and melt. But analyses focused on snow supply do not show where changes to snowmelt runoff are likely to present the most pressing adaptation challenges, given sub-annual patterns of human water consumption and water availability from rainfall. We identify the NH basins where present spring and summer snowmelt has the greatest potential to supply the human water demand that would otherwise be unmet by instantaneous rainfall runoff. Using a multi-model ensemble of climate change projections, we find that these basins—which together have a present population of ∼2 billion people—are exposed to a 67% risk of decreased snow supply this coming century. Further, in the multi-model mean, 68 basins (with a present population of >300 million people) transition from having sufficient rainfall runoff to meet all present human water demand to having insufficient rainfall runoff. However, internal climate variability creates irreducible uncertainty in the projected future trends in snow resource potential, with about 90% of snow-sensitive basins showing potential for either increases or decreases over the near-term decades. Our results emphasize the importance of snow for fulfilling human water demand in many NH basins, and highlight the need to account for the full range of internal climate variability in developing robust climate risk management decisions.

  13. Sodankylä manual snow survey program

    Science.gov (United States)

    Leppänen, Leena; Kontu, Anna; Hannula, Henna-Reetta; Sjöblom, Heidi; Pulliainen, Jouni

    2016-05-01

    The manual snow survey program of the Arctic Research Centre of the Finnish Meteorological Institute (FMI-ARC) consists of numerous observations of natural seasonal taiga snowpack in Sodankylä, northern Finland. The easily accessible measurement areas represent the typical forest and soil types in the boreal forest zone. Systematic snow measurements began in 1909 with snow depth (HS) and snow water equivalent (SWE). In 2006 the manual snow survey program expanded to cover snow macro- and microstructure from regular snow pits at several sites using both traditional and novel measurement techniques. Present-day snow pit measurements include observations of HS, SWE, temperature, density, stratigraphy, grain size, specific surface area (SSA) and liquid water content (LWC). Regular snow pit measurements are performed weekly during the snow season. Extensive time series of manual snow measurements are important for the monitoring of temporal and spatial changes in seasonal snowpack. This snow survey program is an excellent base for the future research of snow properties.

  14. A GIS Software Toolkit for Monitoring Areal Snow Cover and Producing Daily Hydrologic Forecasts using NASA Satellite Imagery Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Aniuk Consulting, LLC, proposes to create a GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts. This toolkit will be...

  15. Point observations of liquid water content in natural snow – investigating methodical, spatial and temporal aspects

    Directory of Open Access Journals (Sweden)

    F. Techel

    2010-10-01

    Full Text Available Information on the amount and distribution of liquid water in the snowpack is important for forecasting wet snow avalanches and predicting melt-water run-off. Considerable spatial and temporal variations of snowpack wetness exist. Currently, available information relies mostly on point observations. Often, the snow wetness is estimated manually using a hand test. However, quantitative measures are also applied. We compare the hand test to quantitative measurements and investigate temporal and small-scale spatial aspects of the snowpack wetness. For this, the liquid water content was measured using dielectric methods, with the Snow Fork and Denoth wetness instrument in the Swiss Alps, mostly above tree-line. More than 12 000 water content measurements were observed on 30 days in 85 locations. The qualitative hand test provides an indication of snowpack wetness, although snowpack wetness is often over-estimated and quantitative water content measurements are more reliable. If the measured water content is very low, it is unclear if the snow is dry or contains small quantities of liquid water. In particular during the initial melt-phase, when the snowpack is only partially wet, it is important to consider spatial aspects when interpreting point observations. One measurement taken at a certain measurement depth may significantly deviate in 10–20% of the cases from snowpack wetness in the surrounding snow. Not surprisingly, diurnal changes in snowpack wetness are significant in layers close to the snow surface. At depth, changes were noted within the course of a day. From a single vertical profile, it was often unclear if these changes were due to the heterogeneous nature of water infiltration. Based on our observations, we propose to repeat three measurements at horizontal distances greater than 50 cm. This approach provides representative snow wetness information for horizontal distances up to 5 m. Further, we suggest a simplified classification

  16. Analysis and improvement of estimated snow water equivalent (SWE) using Artificial Neural Networks

    Science.gov (United States)

    E Azar, A.; Ghedira, H.; Khanbilvardi, R.

    2005-12-01

    The goal of this study is to improve the retrieval of SWE/Snow depth in Great lakes area, United States using passive microwave images along with Normalized Difference Vegetation Index NDVI and Artificial Neural Networks (ANNs). Passive microwave images have been successfully used to estimate snow characteristics such as Snow Water Equivalent (SWE) and snow depth. Despite considerable progress, challenges still exist with respect to accuracy and reliability. In this study, Special Sensor Microwave Imager (SSM/I) channels which are available in Equal-Area Scalable Earth Grid (EASE-GRID) format are used. The study area is covered by a 28 by 35 grid of EASE-Grid pixels, 25km by 25km each. To have a comprehensive data set of brightness temperatures (Tb) of SSM/I channels, an assortment of pixels were selected based on latitude and land cover. A time series analysis was conducted for three winter seasons to assess the SSM/I capability to estimates snow depth and SWE for various land covers. Ground truth data' were obtained from the National Climate Data Center (NCDC) and the National Operational Hydrological Remote Sensing Center (NOHRSC). The NCDC provided daily snow depth measurements reported from various stations located in the study area. Measurements were recorded and projected to match EASE-GRID formatting. The NOHRSC produces SNODAS dataset using airborne Gamma radiation and gauge measurements combined with a physical model. The data set consisted of different snow characteristics such as SWE and snow depth. Landcover characteristics are introduced by using Normalized Difference Vegetation Index (NDVI). An Artificial Neural Network (ANN) algorithm has been employed to evaluate the effect of landcover in estimating snow depth and Snow Water Equivalent (SWE). The model is trained using SSM/I channels (19v, 19h, 37v, 37h, 22v, 85v, 85h) and the mean and standard deviation of NDVI for the each pixel. The preliminary time series results showed various degrees of

  17. Machine Learning on Images: Combining Passive Microwave and Optical Data to Estimate Snow Water Equivalent

    Science.gov (United States)

    Dozier, J.; Tolle, K.; Bair, N.

    2014-12-01

    We have a problem that may be a specific example of a generic one. The task is to estimate spatiotemporally distributed estimates of snow water equivalent (SWE) in snow-dominated mountain environments, including those that lack on-the-ground measurements. Several independent methods exist, but all are problematic. The remotely sensed date of disappearance of snow from each pixel can be combined with a calculation of melt to reconstruct the accumulated SWE for each day back to the last significant snowfall. Comparison with streamflow measurements in mountain ranges where such data are available shows this method to be accurate, but the big disadvantage is that SWE can only be calculated retroactively after snow disappears, and even then only for areas with little accumulation during the melt season. Passive microwave sensors offer real-time global SWE estimates but suffer from several issues, notably signal loss in wet snow or in forests, saturation in deep snow, subpixel variability in the mountains owing to the large (~25 km) pixel size, and SWE overestimation in the presence of large grains such as depth and surface hoar. Throughout the winter and spring, snow-covered area can be measured at sub-km spatial resolution with optical sensors, with accuracy and timeliness improved by interpolating and smoothing across multiple days. So the question is, how can we establish the relationship between Reconstruction—available only after the snow goes away—and passive microwave and optical data to accurately estimate SWE during the snow season, when the information can help forecast spring runoff? Linear regression provides one answer, but can modern machine learning techniques (used to persuade people to click on web advertisements) adapt to improve forecasts of floods and droughts in areas where more than one billion people depend on snowmelt for their water resources?

  18. Climate change impacts on snow water availability in the Euphrates-Tigris basin

    OpenAIRE

    Özdoğan, M.

    2011-01-01

    This study investigates the effects of projected climate change on snow water availability in the Euphrates-Tigris basin using the Variable Infiltration Capacity (VIC) macro scale hydrologic model and a set of regional climate-change outputs from 13 global circulation models (GCMs) forced with two greenhouse gas emission scenarios for two time periods in the 21st century (2050 and 2090). The hydrologic model produces a reasonable simulation of seasonal and spatial variation in snow cover and ...

  19. Consequences of declining snow accumulation for water balance of mid-latitude dry regions

    Science.gov (United States)

    Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

    2012-01-01

    Widespread documentation of positive winter temperature anomalies, declining snowpack and earlier snow melt in the Northern Hemisphere have raised concerns about the consequences for regional water resources as well as wildfire. A topic that has not been addressed with respect to declining snowpack is effects on ecosystem water balance. Changes in water balance dynamics will be particularly pronounced at low elevations of mid-latitude dry regions because these areas will be the first to be affected by declining snow as a result of rising temperatures. As a model system, we used simulation experiments to investigate big sagebrush ecosystems that dominate a large fraction of the semiarid western United States. Our results suggest that effects on future ecosystem water balance will increase along a climatic gradient from dry, warm and snow-poor to wet, cold and snow-rich. Beyond a threshold within this climatic gradient, predicted consequences for vegetation switched from no change to increasing transpiration. Responses were sensitive to uncertainties in climatic prediction; particularly, a shift of precipitation to the colder season could reduce impacts of a warmer and snow-poorer future, depending on the degree to which ecosystem phenology tracks precipitation changes. Our results suggest that big sagebrush and other similar semiarid ecosystems could decrease in viability or disappear in dry to medium areas and likely increase only in the snow-richest areas, i.e. higher elevations and higher latitudes. Unlike cold locations at high elevations or in the arctic, ecosystems at low elevations respond in a different and complex way to future conditions because of opposing effects of increasing water-limitation and a longer snow-free season. Outcomes of such nonlinear interactions for future ecosystems will likely include changes in plant composition and productivity, dynamics of water balance, and availability of water resources.

  20. Measuring snow liquid water content with low-cost GPS receivers.

    Science.gov (United States)

    Koch, Franziska; Prasch, Monika; Schmid, Lino; Schweizer, Jürg; Mauser, Wolfram

    2014-11-06

    The amount of liquid water in snow characterizes the wetness of a snowpack. Its temporal evolution plays an important role for wet-snow avalanche prediction, as well as the onset of meltwater release and water availability estimations within a river basin. However, it is still a challenge and a not yet satisfyingly solved issue to measure the liquid water content (LWC) in snow with conventional in situ and remote sensing techniques. We propose a new approach based on the attenuation of microwave radiation in the L-band emitted by the satellites of the Global Positioning System (GPS). For this purpose, we performed a continuous low-cost GPS measurement experiment at the Weissfluhjoch test site in Switzerland, during the snow melt period in 2013. As a measure of signal strength, we analyzed the carrier-to-noise power density ratio (C/N0) and developed a procedure to normalize these data. The bulk volumetric LWC was determined based on assumptions for attenuation, reflection and refraction of radiation in wet snow. The onset of melt, as well as daily melt-freeze cycles were clearly detected. The temporal evolution of the LWC was closely related to the meteorological and snow-hydrological data. Due to its non-destructive setup, its cost-efficiency and global availability, this approach has the potential to be implemented in distributed sensor networks for avalanche prediction or basin-wide melt onset measurements.

  1. Measuring Snow Liquid Water Content with Low-Cost GPS Receivers

    Directory of Open Access Journals (Sweden)

    Franziska Koch

    2014-11-01

    Full Text Available The amount of liquid water in snow characterizes the wetness of a snowpack. Its temporal evolution plays an important role for wet-snow avalanche prediction, as well as the onset of meltwater release and water availability estimations within a river basin. However, it is still a challenge and a not yet satisfyingly solved issue to measure the liquid water content (LWC in snow with conventional in situ and remote sensing techniques. We propose a new approach based on the attenuation of microwave radiation in the L-band emitted by the satellites of the Global Positioning System (GPS. For this purpose, we performed a continuous low-cost GPS measurement experiment at the Weissfluhjoch test site in Switzerland, during the snow melt period in 2013. As a measure of signal strength, we analyzed the carrier-to-noise power density ratio (C/N0 and developed a procedure to normalize these data. The bulk volumetric LWC was determined based on assumptions for attenuation, reflection and refraction of radiation in wet snow. The onset of melt, as well as daily melt-freeze cycles were clearly detected. The temporal evolution of the LWC was closely related to the meteorological and snow-hydrological data. Due to its non-destructive setup, its cost-efficiency and global availability, this approach has the potential to be implemented in distributed sensor networks for avalanche prediction or basin-wide melt onset measurements.

  2. Regional change in snow water equivalent-surface air temperature relationship over Eurasia during boreal spring

    Science.gov (United States)

    Wu, Renguang; Chen, Shangfeng

    2016-10-01

    Present study investigates local relationship between surface air temperature and snow water equivalent (SWE) change over mid- and high-latitudes of Eurasia during boreal spring. Positive correlation is generally observed around the periphery of snow covered region, indicative of an effect of snow on surface temperature change. In contrast, negative correlation is usually found over large snow amount area, implying a response of snow change to wind-induced surface temperature anomalies. With the seasonal retreat of snow covered region, region of positive correlation between SWE and surface air temperature shifts northeastward from March to May. A diagnosis of surface heat flux anomalies in April suggests that the snow impact on surface air temperature is dominant in east Europe and west Siberia through modulating surface shortwave radiation. In contrast, atmospheric effect on SWE is important in Siberia and Russia Far East through wind-induced surface sensible heat flux change. Further analysis reveals that atmospheric circulation anomalies in association with snowmelt over east Siberia may be partly attributed to sea surface temperature anomalies in the North Atlantic and the atmospheric circulation anomaly pattern associated with snowmelt over Russia Far East has a close association with the Arctic Oscillation.

  3. Is Snow a sufficient Source of Water for Horses kept Outdoors in Winter? A Case Report

    Directory of Open Access Journals (Sweden)

    Bøe KE

    2005-03-01

    Full Text Available Due to extreme weather conditions, a flock of outwintered Icelandic horses had to manage for several days on snow as the source of free water. They were fed grass silage ad lib, and any change in feed consumption was not observed. After nine days, blood samples were taken and analysed for plasma osmolality, they were subjected to a simple clinical examination, and offered drinking water. Osmolality levels were within normal limits and mean value did not differ significantly from samples which previously were taken of the same individuals. The general condition of the horses was normal, with no signs of clinical dehydration or disease. The horses showed very little interest for the offered drinking water. This suggests that in cold winter weather, horses being fed grass silage and adjusted to eat snow, can manage for several days with snow substituting liquid water without their physiology and welfare being challenged.

  4. Impact of spatial variation in snow water equivalent and snow ablation on spring snowcover depletion over an alpine ridge

    Science.gov (United States)

    Schirmer, Michael; Harder, Phillip; Pomeroy, John

    2016-04-01

    The spatial and temporal dynamics of mountain snowmelt are controlled by the spatial distribution of snow accumulation and redistribution and the pattern of melt energy applied to this snowcover. In order to better quantify the spatial variations of accumulation and ablation, Structure-from-Motion techniques were applied to sequential aerial photographs of an alpine ridge in the Canadian Rocky Mountains taken from an Unmanned Aerial Vehicle (UAV). Seven spatial maps of snow depth and changes to depth during late melt (May-July) were generated at very high resolutions covering an area of 800 x 600 m. The accuracy was assessed with over 100 GPS measurements and RMSE were found to be less than 10 cm. Low resolution manual measurements of density permitted calculation of snow water equivalent (SWE) and change in SWE (ablation rate). The results indicate a highly variable initial SWE distribution, which was five times more variable than the spatial variation in ablation rate. Spatial variation in ablation rate was still substantial, with a factor of two difference between north and south aspects and small scale variations due to local dust deposition. However, the impact of spatial variations in ablation rate on the snowcover depletion curve could not be discerned. The reason for this is that only a weak spatial correlation developed between SWE and ablation rate. These findings suggest that despite substantial variations in ablation rate, snowcover depletion curve calculations should emphasize the spatial variation of initial SWE rather than the variation in ablation rate. While there is scientific evidence from other field studies that support this, there are also studies that suggest that spatial variations in ablation rate can influence snowcover depletion curves in complex terrain, particularly in early melt. The development of UAV photogrammetry has provided an opportunity for further detailed measurement of ablation rates, SWE and snowcover depletion over complex

  5. Macroscopic modeling for heat and water vapor transfer in dry snow by homogenization.

    Science.gov (United States)

    Calonne, Neige; Geindreau, Christian; Flin, Frédéric

    2014-11-26

    Dry snow metamorphism, involved in several topics related to cryospheric sciences, is mainly linked to heat and water vapor transfers through snow including sublimation and deposition at the ice-pore interface. In this paper, the macroscopic equivalent modeling of heat and water vapor transfers through a snow layer was derived from the physics at the pore scale using the homogenization of multiple scale expansions. The microscopic phenomena under consideration are heat conduction, vapor diffusion, sublimation, and deposition. The obtained macroscopic equivalent model is described by two coupled transient diffusion equations including a source term arising from phase change at the pore scale. By dimensional analysis, it was shown that the influence of such source terms on the overall transfers can generally not be neglected, except typically under small temperature gradients. The precision and the robustness of the proposed macroscopic modeling were illustrated through 2D numerical simulations. Finally, the effective vapor diffusion tensor arising in the macroscopic modeling was computed on 3D images of snow. The self-consistent formula offers a good estimate of the effective diffusion coefficient with respect to the snow density, within an average relative error of 10%. Our results confirm recent work that the effective vapor diffusion is not enhanced in snow.

  6. Monitoring and evaluation of seasonal snow cover in Kashmir valley using remote sensing, GIS and ancillary data

    Indian Academy of Sciences (India)

    H S Negi; N K Thakur; Rajeev Kumar; Manoj Kumar

    2009-12-01

    Seasonal snow cover is a vital natural resource in the Himalaya. Monitoring of the areal extent of seasonal snow cover is important for both climatological studies as well as hydrological applications. In the present paper, snow cover monitoring was carried out to evaluate the region-wise accumulation and ablation pattern of snow cover in Pir Panjal and Shamshawari ranges of Kashmir valley. The study was carried out for the winter period between November and April of 2004–05, 2005–06 and 2006–07, using multi-temporal WiFS sensor data of IRS-1C/1D satellites. The study shows reduction in the areal extent of seasonal snow cover and rising trend of maximum temperature in three winters for the entire Kashmir valley. This has been validated with 20 years (1988– 89 to 2007–08) climatic conditions prevailed in both ranges of Kashmir valley. Region-wise study shows the spatial and temporal variability in seasonal snow cover within Kashmir valley. Advance melting was observed in Banihal and Naugam/Tangdhar regions than Gurez and Machhal regions. Different geographical parameters of these regions were studied to evaluate the influence on snow cover and it was observed that altitude and position of region with respect to mountain range are the deciding factors for retaining the seasonal snow cover for longer duration. Such region-wise study of snow cover monitoring, can provide vital inputs for planning the hydropower projects, development in habitat areas, recreational and strategic planning in the region.

  7. Assessing Scale Effects on Snow Water Equivalent Retrievals Using Airborne and Spaceborne Passive Microwave Data

    Science.gov (United States)

    Derksen, C.; Walker, A.; Goodison, B.

    2003-12-01

    The Climate Research Branch (CRB) of the Meteorological Service of Canada (MSC) has a long-standing research program focused on the development of methods to retrieve snow cover information from passive microwave satellite data for Canadian regions. Algorithms that derive snow water equivalent (SWE) have been developed by CRB and are used to operationally generate SWE information over landscape regions including prairie, boreal forest, and taiga. New multi-scale research datasets were acquired in Saskatchewan, Canada during February 2003 to quantify the impact of spatially heterogeneous land cover and snowpack properties on passive microwave SWE retrievals. MSC microwave radiometers (6.9, 19, 37, and 85 GHz) were flown on the National Research Council (NRC) Twin Otter aircraft at two flying heights along a grid of flight lines, covering a 25 by 25 km study area centered on the Old Jack Pine Boreal Ecosystem Research and Monitoring Site (BERMS). Spaceborne Special Sensor Microwave/Imager (SSM/I) and Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperatures were also acquired for this region. SWE was derived for all passive microwave datasets using the CRB land cover sensitive algorithm suite. An intensive, coincident ground sampling program characterized in situ snow depth, density, water equivalent and pack structure using a land cover based sampling scheme to isolate the variability in snow cover parameters within and between forest stands and land cover types, and within a single spaceborne passive microwave grid cell. The passive microwave data sets that are the focus of this investigation cover a range of spatial resolutions from 100-150 m for the airborne data to 10 km (AMSR-E) and 25 km (SSM/I) for the satellite data, providing the opportunity to investigate and compare microwave emission characteristics, SWE retrievals and land cover effects at different spatial scales. Initial analysis shows that the small footprint airborne passive microwave

  8. Temporal inconsistencies in coarse-scale snow water equivalent patterns: Colorado River Basin snow telemetry-topography regressions

    Directory of Open Access Journals (Sweden)

    Fassnacht, S. R.

    2012-05-01

    Full Text Available The relation between snow water equivalent (SWE and 28 variables (27 topographically-based topographic variables and canopy density for the Colorado River Basin, USA was explored through a multi-variate regression. These variables include location, slope and aspect at different scales, derived variables to indicate the distance to sources of moisture and proximity to and characteristics of obstacles between these moisture sources and areas of snow accumulation, and canopy density. A weekly time step of snow telemetry (SNOTEL SWE data from 1990 through 1999 was used. The most important variables were elevation and regional scale (81 km² slope. Since the seasonal and inter-annual variability is high, a regression relationship should be formulated for each time step. The inter-annual variation in the relation between SWE and topographic variables partially corresponded with the amount of snow accumulated over the season and the El Niño Southern Oscillation cycle.Se analiza la relación entre el equivalente de agua en la nieve (SWE y 28 variables (27 variables topográficas y otra basada en la densidad del dosel para la Cuenca del Río Colorado, EE.UU. mediante regresión multivariante. Estas variables incluyen la localización, pendiente y orientación a diferentes escalas, además de variables derivadas para indicar la distancia a las fuentes de humedad y la proximidad a las barreras topográficas, además de las características de las barreras topográficas entre las fuentes de humedad, las áreas de acumulación de nieve y la densidad del dosel. Se utilizaron telemetrías semanales de nieve (SNOTEL desde 1990 hasta 1999. Las variables más importantes fueron la elevación y la pendiente a escala regional (81 km². Dada la alta variabilidad estacional e interanual, fue necesario establecer regresiones específicas para cada intervalo disponible de datos. La variación interanual en la relación entre variables topográficas y el SWE se

  9. Details and Consequences of Water Vapor Diffusion In The Pore Space of Snow

    Science.gov (United States)

    Sokratov, S. A.; Bartelt, P.; Schneebeli, M.; Lehning, M.

    Despite a long history of extensive experimental and theoretical studies on the process of water vapor diffusion in snow, no quantitative explanation for the observed diffu- sion characteristics such as mass-transfer rates and snow density change is available at present. Results of a detailed investigatation of the process are presented. The pro- posed description of water vapor flux in snow now includes thermal diffusion, grav- itation, convective air flow, and volumetric mass-production. The relative importance of the components in the overall mass-transfer is analyzed. Although experimental data of sufficient detail concerning the individual components are not available, the results of our analysis provide an improved understanding of the sources of discrepan- cies in published experimental results. The consequences of the water vapor transport description for heat transfer and metamorphism are also discussed.

  10. Using Airborne Snow Observatory distributed snow water equivalent to predict seasonal inflow volumes and inform management decisions at the Hetch Hetchy Reservoir

    Science.gov (United States)

    Graham, C. B.; Painter, T. H.; Mazurkiewicz, A.

    2015-12-01

    Traditionally, estimates of seasonal streamflow volumes have been determined using statistical relationships to precipitation and snow depth measurements taken at widely spaced while geographically clustered gauges. While strong statistical relationships have been identified in some locations, these relationships are susceptible to breaking down during extreme conditions such as droughts or extremely wet years. The Airborne Snow Observatory (ASO) is a program where airplane mounted lidar is used to create snow-on and snow-off DEMs, yielding distributed estimates of snow water equivalent at the catchment scale. These estimates allow us, for the first time, to compare basin wide snow water equivalent to seasonal streamflow volumes. At the Tuolumne River basin in Yosemite National Park, Sierra Nevada Mountains, California, the ASO estimates of basin wide SWE are shown to be tightly correlated to seasonal streamflow volumes. These estimates are further improved when combined with precipitation measurements. These estimates appear to be more robust than traditional statistical methods, and have been used to improve predictions of inflows at the Hetch Hetchy Reservoir, the primary water source for the City and County of San Francisco and surrounding areas.

  11. Multi-objective calibration of a spatially semi-distributed rainfall runoff model and its snow water equivalent module.

    Science.gov (United States)

    Valent, Peter; Výleta, Roman; Danáčová, Michaela; Sleziak, Patrik; Kotríková, Katarína

    2016-04-01

    The snow cover is an important environmental and water management factor in mid latitudes. From the water management point of view the impact of the water accumulated in the snow cover is significant mainly during the spring season when it's melting causes a significant flooding threat when melting is accompanied by precipitation (rain on snow floods). Modelling of spatial and temporal distribution of the snow water equivalent is therefore an important component of rainfall-runoff models. The main objective of this work was to study the possibility to include information on the spatial distribution of the snow cover into runoff modelling and evaluate the quality of the simulation of both of the snow water equivalent and catchment runoff. A conceptual semi-distributed rainfall-runoff model was used in order to model the snow water equivalent in a daily time step. In order to calibrate and validate the model a multi-calibration techniques were used taking into account both runoff from the catchment and the observed values of the snow water equivalents and snow heights in elevation and vegetation zones. The multi-objective calibration linearly combines two optimization functions and aggregates them into one. While the first optimization function compares observed and simulated flows, the second one is based on an indirect comparison of a snow water equivalent simulated by a rainfall-runoff model and the snow cover heights measured in rainfall gauges within the catchment. The aim of the paper is to optimize the ratio of the weights in the optimization. The methodology was tested on the Upper Hron River catchment, which could be considered as a mountainous catchment.

  12. Remote Sensing of Snow as a Tool to Forecast Water Shortage in the Argentinian Dry Andes

    Science.gov (United States)

    Delbart, Nicolas; Dunesme, Samuel; Lavie, Emilie; Madelin, Malika

    2016-08-01

    In the Argentinian Dry Andes the annual snow melt is the main source of superficial water and aquifer recharge, essential for the population of the oases. Interannual variability in the snow cover in the Andes mountains causes variability in the water volumes available. In this study we analyze the errors of a water discharge forecast method based on the MODIS MOD10A2 snow cover product, with regards to the mass anomalies estimated by GRACE satellite at the scale of four watersheds.Because the high-water period (September-April) discharge is directly related to the snow extent at the beginning of the snowmelt period, i.e. in September and October, we use MOD10A2 images to forecast the average high water season discharge. Despite an average uncertainty of 15%, uncertainty peaks to about 50% in several years. Comparison with mass anomalies retrieved GRACE satellite data suggests that overestimation of our forecast method comes from snowbed thickness interannual variations.

  13. Estimating time and spatial distribution of snow water equivalent in the Hakusan area

    Science.gov (United States)

    Tanaka, K.; Matsui, Y.; Touge, Y.

    2015-12-01

    In the Sousei program, on-going Japanese research program for risk information on climate change, assessing the impact of climate change on water resources is attempted using the integrated water resources model which consists of land surface model, irrigation model, river routing model, reservoir operation model, and crop growth model. Due to climate change, reduction of snowfall amount, reduction of snow cover and change in snowmelt timing, change in river discharge are of increasing concern. So, the evaluation of snow water amount is crucial for assessing the impact of climate change on water resources in Japan. To validate the snow simulation of the land surface model, time and spatial distribution of the snow water equivalent was estimated using the observed surface meteorological data and RAP (Radar Analysis Precipitation) data. Target area is Hakusan. Hakusan means 'white mountain' in Japanese. Water balance of the Tedori River Dam catchment was checked with daily inflow data. Analyzed runoff was generally well for the period from 2010 to 2012. From the result for 2010-2011 winter, maximum snow water equivalent in the headwater area of the Tedori River dam reached more than 2000mm in early April. On the other hand, due to the underestimation of RAP data, analyzed runoff was under estimated from 2006 to 2009. This underestimation is probably not from the lack of land surface model, but from the quality of input precipitation data. In the original RAP, only the rain gauge data of JMA (Japan Meteorological Agency) were used in the analysis. Recently, other rain gauge data of MLIT (Ministry of Land, Infrastructure, Transport and Tourism) and local government have been added in the analysis. So, the quality of the RAP data especially in the mountain region has been greatly improved. "Reanalysis" of the RAP precipitation is strongly recommended using all the available off-line rain gauges information. High quality precipitation data will contribute to validate

  14. Combined assimilation of streamflow and snow water equivalent for mid-term ensemble streamflow forecasts in snow-dominated regions

    Science.gov (United States)

    Bergeron, Jean M.; Trudel, Mélanie; Leconte, Robert

    2016-10-01

    The potential of data assimilation for hydrologic predictions has been demonstrated in many research studies. Watersheds over which multiple observation types are available can potentially further benefit from data assimilation by having multiple updated states from which hydrologic predictions can be generated. However, the magnitude and time span of the impact of the assimilation of an observation varies according not only to its type, but also to the variables included in the state vector. This study examines the impact of multivariate synthetic data assimilation using the ensemble Kalman filter (EnKF) into the spatially distributed hydrologic model CEQUEAU for the mountainous Nechako River located in British Columbia, Canada. Synthetic data include daily snow cover area (SCA), daily measurements of snow water equivalent (SWE) at three different locations and daily streamflow data at the watershed outlet. Results show a large variability of the continuous rank probability skill score over a wide range of prediction horizons (days to weeks) depending on the state vector configuration and the type of observations assimilated. Overall, the variables most closely linearly linked to the observations are the ones worth considering adding to the state vector due to the limitations imposed by the EnKF. The performance of the assimilation of basin-wide SCA, which does not have a decent proxy among potential state variables, does not surpass the open loop for any of the simulated variables. However, the assimilation of streamflow offers major improvements steadily throughout the year, but mainly over the short-term (up to 5 days) forecast horizons, while the impact of the assimilation of SWE gains more importance during the snowmelt period over the mid-term (up to 50 days) forecast horizon compared with open loop. The combined assimilation of streamflow and SWE performs better than their individual counterparts, offering improvements over all forecast horizons considered

  15. Constraining Annual Water Balance Estimates with Basin-Scale Observations from the Airborne Snow Observatory during the Current Californian Drought

    Science.gov (United States)

    Bormann, K.; Painter, T. H.; Marks, D. G.; Hedrick, A. R.; Deems, J. S.; Patterson, V.; McGurk, B. J.

    2015-12-01

    One of the great unknowns in mountain hydrology is how much water is stored within a seasonal snowpack at the basin scale. Quantifying mountain water resources is critical for assisting with water resource management, but has proven elusive due to high spatial and temporal variability of mountain snow cover, complex terrain, accessibility constraints and limited in-situ networks. The Airborne Snow Observatory (ASO, aso.jpl.nasa.gov) uses coupled airborne LiDAR and spectrometer instruments for high resolution snow depth retrievals which are used to derive unprecedented basin-wide estimates of snow water mass (snow water equivalent, SWE). ASO has been operational over key basins in the Sierra Nevada Mountains in California since 2013. Each operational year has been very dry, with precipitation in 2013 at 75% of average, 2014 at 50% of average and 2015 - the lowest snow year on record for the region. With vastly improved estimates of the snowpack water content from ASO, we can now for the first time conduct observation-based mass balance accounting of surface water in snow-dominated basins, and reconcile these estimates with observed reservoir inflows. In this study we use ASO SWE data to constrain mass balance accounting of basin annual water storages to quantify the water contained within the snowpack above the Hetch Hetchy water supply reservoir (Tuolumne River basin, California). The analysis compares and contrasts annual snow water volumes from observed reservoir inflows, snow water volume estimates from ASO, a physically based model that simulates the snowpack from meteorological inputs and a semi-distributed hydrological model. The study provides invaluable insight to the overall volume of water contained within a seasonal snowpack during a severe drought and how these quantities are simulated in our modelling systems. We envisage that this research will be of great interest to snowpack modellers, hydrologists, dam operators and water managers worldwide.

  16. A regional climate model hindcast for Siberia – assessing the added value of snow water equivalent using ESA GlobSnow and reanalyses

    Directory of Open Access Journals (Sweden)

    K. Klehmet

    2012-11-01

    Full Text Available This study analyzes the added value of a regional climate model hindcast of CCLM compared to global reanalyses in providing a reconstruction of recent past snow water equivalent (SWE for Siberia. Consistent regional climate data in time and space is necessary due to lack of station data in that region. We focus on SWE since it represents an important snow cover parameter in a region where snow has the potential to feed back to the climate of the whole Northern Hemisphere. The simulation was performed in a 50 km grid spacing for the period 1948 to 2010 using NCEP Reanalysis 1 as boundary forcing. Daily observational reference data for the period of 1987–2010 was obtained by the satellite derived SWE product of ESA DUE GlobSnow that enables a large scale assessment. The analyses includes comparisons of the distribution of snow cover extent, example time series of monthly SWE for January and April, regional characteristics of long-term monthly mean, standard deviation and temporal correlation averaged over subregions. SWE of CCLM is compared against the SWE information of NCEP-R1 itself and three more reanalyses (NCEP-R2, NCEP-CFSR, ERA-Interim. We demonstrate a significant added value of the CCLM hindcast during snow accumulation period shown for January for many subregions compared to SWE of NCEP-R1. NCEP-R1 mostly underestimates SWE during whole snow season. CCLM overestimates SWE compared to the satellite-derived product during April – a month representing the beginning of snow melt in southern regions. We illustrate that SWE of the regional hindcast is more consistent in time than ERA-Interim and NCEP-R2 and thus add realistic detail.

  17. Aerial measurements of snow water equivalent in Norway using terrestrial gamma radiation

    Energy Technology Data Exchange (ETDEWEB)

    Tollan, O.; Dahl, J.B.; Qvenild, C.

    1979-01-01

    Airborne measurement of gamma radiation is used to determine the water equivalent of the snow magazines in 8000 km/sup 2/ of mountainous areas in Southern Norway. The terrain in the areas is exposed to the weather, causing considerable variation in the snow cover. This is regarded as a major source of error. As the terrain is inhomogeneous in most of the measurement areas careful selection of survey lines is important. The cost of surveying 1000 km of measurement routes was N.kr. 40,000 or US$ 8000 in 1978.

  18. Seasonal snow cover and glacier change impact on water and energy cycle of Central Asia Endorheic Basin

    Science.gov (United States)

    Eisen, Vladimir; Eisen, Elena

    2010-05-01

    High mountains of Central Asia Endorheic Basin (CAEB) hold one of the greatest in the World concentration of snow and glacier ice water resources at mid- latitudes thousands of miles from the oceans providing up to 80% of total river runoff. The total external atmospheric moisture flow over the CAEB comprises approximately 200 billion cubic meters per year. The glaciers of CAEB receive and retain annually up to 10% of moisture transferred over the mountains. However, the area of seasonal snow and glaciers has declining rapidly as result of recent climatic change causes by increase in air temperature and precipitation partitioning between snow and rain, and evaporation fluxes. Based on remote sensing data CAEB glaciers shrunk by 5% between the middle of 1940th and 1970th and 10% during the next 30 years. Evaluation of seasonal snow cover for the same period revealed 20% seasonal snow covered area reduction. During the last thirty years, the duration of snow melt reduced by 30 days from the date of maximum snow cover to the date of its disappearance. Further decrease in seasonal snow cover will be accelerated due to increase of rainfall instead of snowfall in early spring months at high elevations, and consequently a lesser heat expenditure for snowmelt. At high mountains, about 40% of snow ablated during the penultimate 10 days of snow cover. During ablation season, the amount of energy used to melt snow and glacier ice is in the same order as the combination of other components of the heat budget (e.g., heat associated with atmospheric advection, radiation balance and turbulent heat exchange). Heating of the air would have been 3 times higher if snow and glacier ice melt had not occurred. Analysis of shallow ice-cores from high elevation snow/ice fields of CAEB has helped determining the climatic processes controlling hydrological regimes via the changes in global and regional atmospheric circulation patterns and simulates impact of these changes on water and

  19. Water Quality Monitoring

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Our water quality sampling program is to determine the quality of Moosehorn's lakes and a limited number of streams. Water quality is a measure of the body of water,...

  20. Utilization of surface cover composition to improve the microwave determination of snow water equivalent in a mountain basin

    Science.gov (United States)

    Chang, A. T. C.; Foster, J. L.; Rango, A.

    1991-01-01

    Satellite microwave data have been used to derive areal snow water equivalent in flat homogeneous areas. Over heterogeneous mountainous areas different algorithms are needed to retrieve the water equivalent of the snow cover. A mixed pixel model based on the percentage of vegetation cover within a pixel has been developed to simulate the microwave brightness temperatures for the Rio Grande basin in southwestern Colorado. A relationship between the difference in microwave-brightness temperature at two different frequencies (37- and 18-GHz horizontal polarization), and the basin-wide average snow water equivalent was obtained. The areal snow-water equivalent values derived from the model were consistent with values generated by a reliable snowmelt run-off model using snow-cover extent data.

  1. Monitoring Continental Water Mass Variations by GRACE

    Science.gov (United States)

    Mercan, H.; Akyılmaz, O.

    2015-12-01

    The low-low satellite-to-satellite tracking mission GRACE (Gravity Recovery And Climate Experiment), launched in March 2002, aims to determine Earth's static gravity field and its temporal variations. Geophysical mass changes at regional and global scale, which are related with terrestrial water bodies, ocean and atmosphere masses, melting and displacements of ice sheets and tectonic movements can be determined from time-dependent changes of the Earth's gravity field. In this study, it is aimed to determine total water storage (TWS) (soil moisture, groundwater, snow and glaciers, lake and river waters, herbal waters) variations at different temporal and spatial resolution, monitoring the hydrologic effect causing time-dependent changes in the Earth's gravity field by two different methods. The region between 30°-40° northern latitudes and 36°-48° eastern longitudes has been selected as a study area covering the Euphrates - Tigris basin. TWS maps were produced with (i) monthly temporal and 400 km spatial resolution, based on monthly mean global spherical harmonic gravity field models of GRACE satellite mission (L2), and with (ii) monthly and semi-monthly temporal and spatial resolution as fine as 200 km based on GRACE in-situ observations (L1B). Decreasing trend of water mass anomalies from the year 2003 to 2013 is proved by aforesaid approaches. Monthly TWS variations are calculated using two different methods for the same region and time period. Time series of both solutions are generated and compared.

  2. Impulse waves generated by snow avalanches: Momentum and energy transfer to a water body

    Science.gov (United States)

    Zitti, Gianluca; Ancey, Christophe; Postacchini, Matteo; Brocchini, Maurizio

    2016-12-01

    When a snow avalanche enters a body of water, it creates an impulse wave whose effects may be catastrophic. Assessing the risk posed by such events requires estimates of the wave's features. Empirical equations have been developed for this purpose in the context of landslides and rock avalanches. Despite the density difference between snow and rock, these equations are also used in avalanche protection engineering. We developed a theoretical model which describes the momentum transfers between the particle and water phases of such events. Scaling analysis showed that these momentum transfers were controlled by a number of dimensionless parameters. Approximate solutions could be worked out by aggregating the dimensionless numbers into a single dimensionless group, which then made it possible to reduce the system's degree of freedom. We carried out experiments that mimicked a snow avalanche striking a reservoir. A lightweight granular material was used as a substitute for snow. The setup was devised so as to satisfy the Froude similarity criterion between the real-world and laboratory scenarios. Our experiments in a water channel showed that the numerical solutions underestimated wave amplitude by a factor of 2 on average. We also compared our experimental data with those obtained by Heller and Hager (2010), who used the same relative particle density as in our runs, but at higher slide Froude numbers.

  3. Use of positive reinforcement conditioning to monitor pregnancy in an unanesthetized snow leopard (Uncia uncia) via transabdominal ultrasound.

    Science.gov (United States)

    Broder, Jacqueline M; Macfadden, Annabell J; Cosens, Lindsay M; Rosenstein, Diana S; Harrison, Tara M

    2008-01-01

    Closely monitoring snow leopard (Uncia uncia) fetal developments via transabdominal ultrasound, with minimal stress to the animal, was the goal of this project. The staff at Potter Park Zoo has used the principles of habituation, desensitization, and positive reinforcement to train a female snow leopard (U. uncia). Ultrasound examinations were preformed on an unanesthetized feline at 63 and 84 days. The animal remained calm and compliant throughout both procedures. Fetuses were observed and measured on both occasions. The absence of anesthesia eliminated components of psychologic and physiologic stress associated with sedation. This was the first recorded instance of transabdominal ultrasound being carried out on an unanesthetized snow leopard. It documents the feasibility of detecting pregnancy and monitoring fetal development via ultrasound. Zoo Biol 27:78-85, 2008. (c) 2007 Wiley-Liss, Inc.

  4. Seeing the Snow through the Trees: Towards a Validated Canopy Adjustment for Fractional Snow Covered Area

    Science.gov (United States)

    Coons, L.; Nolin, A. W.; Painter, T.

    2012-12-01

    Satellite remote sensing is an important tool for monitoring the spatial distribution of snow cover, which acts as a vital reservoir of water for human and ecosystem needs. Current methods exist mapping the fraction of snow in each image pixel from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper (TM). Although these methods can effectively detect this fractional snow-covered area (fSCA) in open areas, snow cover is underestimated in forested areas where canopy cover obscures the snow. Accounting for obscured snow cover will significantly improve estimates of fSCA for hydrologic forecasting and monitoring. This study will address how individual trees and the overall forest canopy affect snow distributions on the ground with the goal of determining metrics that can parameterize the spatial patterns of sub-canopy snow cover. Snow cover measurements were made during winter 2011-2012 at multiple sites representing a range of canopy densities. In the snow-free season, we used terrestrial laser scanning (TLS) and manual field methods to fully characterize the forest canopy height, canopy gap fraction, crown width, tree diameter at breast height (DBH), and stand density. We also use multi-angle satellite imagery from MISR and airborne photos to map canopy characteristics over larger areas. Certain canopy structure characteristics can be represented with remote sensing data. These data serve as a key first step in developing canopy adjustment factors for fSCA from MODIS, TM, and other snow mapping sensors.

  5. Use of satellite images in snow water equivalent (SWE) estimation in the Upper Vistula drainage basin in southern Poland

    Science.gov (United States)

    Kasina, M.; Chamerlinska, A.; Lasek, J.; Przeniczny, P.

    2013-12-01

    Snow-water equivalent (SWE) and snow depth are the two most important parameters used in hydrological forecasting offices to estimate the amount of water stored in the form of snow. These two parameters are essential during snowmelt periods when rapid snowmelt (often combined with rainfall) causes slow-onset floods. In this case, the water equivalent can be used as an indicator of the amount of water expected in runoff. So far the Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB) produces this estimate based only on SWE and snow depth data obtained from meteorological stations at five day intervals. The two measurements are performed at shorter intervals either when heavy snowfall occurs or when the mean daily air temperature exceeds 0οC. The main aim of this project is to improve the existing method of snow water equivalent estimation by using satellite-derived data. Snow-water equivalent data and the extent of snow cover were derived from satellite products prepared within the H-SAF Project, which is the EUMETSAT Network of Satellite Application Facility dedicated to support Operational Hydrology and Water Management. Both H10 - Snow mask by VIS/IR radiometry and H11 - Snow water equivalent by MW radiometry products are derived in a daily time step. It then becomes possible to compare and further assimilate ground-truth data. Other analyses included Bayesian Kriging spatial interpolation, which is suitable for non-stationary data. The method described in this paper - same as other methods based on satellite derived data - is weather dependent and it is limited to cloud-free periods. A comparison of results obtained using this method and results obtained using ground-based data calculations proved its applicability in lowland areas. In mountainous regions, where differences in SWE values strongly depend on elevation, the obtained SWE values were underestimated.

  6. Commodifying snow, taming the waters. Socio-ecological niche construction in an Alpine village.

    Science.gov (United States)

    Gross, Robert; Winiwarter, Verena

    White belts of snow clad mountains all over the world each winter. Even if there is no snow, the tourism industry is able to produce the white finery at the push of the button, thereby consuming large amounts of water. Studying Damüls, a well-known ski resort in Austria's westernmost province Vorarlberg, we can show that the development of a service sector within agro-pastoral landscapes was connected with novel water uses and massive interventions into Alpine landscapes. Human niche construction theory offers a unique avenue for studying the development of Alpine communities, but also highlights side effects accompanying the change from agrarian to tourism livelihoods. One aim of this paper is to broaden the scope of human niche construction theory. Inceptive, counteractive and relocational niche construction activities were coupled to the differentiation of actor groups. To incorporate social dynamics, indispensable for studies in environmental history, we propose the concept of socio-ecological niche construction. The paper investigates how villagers balanced resource limitations typical for an agrarian society with the differentiation of sub-niches, mediating selective forces on the population. When the valleys were industrialized, Damüls was almost given up as a permanent settlement. Then, tourists entered the stage, by and by turning the wheel of local development into a different direction. A tourism niche based on natural snow evolved from the 1930s onwards. While the socio-ecological niches of agriculture and tourism coexisted in the interwar years, this changed when ski lifts were built, embedded into a debt-based economy that made the tourism niche vulnerable to snow availability. Snow-dependency became a powerful selective force. It was mediated by the ski lift companies through a range of niche construction activities that turned water into an important resource of snowmaking systems.

  7. Tomography-based monitoring of isothermal snow metamorphism under advective conditions

    Directory of Open Access Journals (Sweden)

    P. P. Ebner

    2015-02-01

    Full Text Available Time-lapse X-ray micro-tomography was used to investigate the structural dynamics of isothermal snow metamorphism exposed to an advective airflow. Diffusion and advection across the snow pores were analysed in controlled laboratory experiments. The 3-D digital geometry obtained by tomographic scans was used in direct pore-level numerical simulations to determine the effective transport properties. The results showed that isothermal advection with saturated air have no influence on the coarsening rate that is typical for isothermal snow metamorphism. Diffusion originating in the Kelvin effect between snow structures dominates and is the main transport process in isothermal snow packs.

  8. Estimating the distribution of snow water equivalent using remotely sensed snow cover data and a spatially distributed snowmelt model: A multi-resolution, multi-sensor comparison

    Science.gov (United States)

    Molotch, Noah P.; Margulis, Steven A.

    2008-11-01

    Time series of fractional snow covered area (SCA) estimates from Landsat Enhanced Thematic Mapper (ETM+), Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) data were combined with a spatially distributed snowmelt model to reconstruct snow water equivalent (SWE) in the Rio Grande headwaters (3419 km 2). In this reconstruction approach, modeled snowmelt over each pixel is integrated during the period of satellite-observed snow cover to estimate SWE. Due to underestimates in snow cover detection, maximum basin-wide mean SWE using MODIS and AVHRR were, respectively, 45% and 68% lower than SWE estimates obtained using ETM+ data. The mean absolute error (MAE) of SWE estimated at 100-m resolution using ETM+ data was 23% relative to observed SWE from intensive field campaigns. Model performance deteriorated when MODIS (MAE = 50%) and AVHRR (MAE = 89%) SCA data were used. Relative to differences in the SCA products, model output was less sensitive to spatial resolution (MAE = 39% and 73% for ETM+ and MODIS simulations run at 1 km resolution, respectively), indicating that SWE reconstructions at the scale of MODIS acquisitions may be tractable provided the SCA product is improved. When considering tradeoffs between spatial and temporal resolution of different sensors, our results indicate that higher spatial resolution products such as ETM+ remain more accurate despite the lower frequency of acquisition. This motivates continued efforts to improve MODIS snow cover products.

  9. Using MODIS snow cover and precipitation data to model water runoff for the Mokelumne River Basin in the Sierra Nevada, California (2000-2009)

    Science.gov (United States)

    Powell, Cynthia; Blesius, Leonhard; Davis, Jerry; Schuetzenmeister, Falk

    2011-05-01

    Climate change will affect snowpack and water supply systems in California, and methods for predicting daily stream flow help prepare for these changes. This research provides a daily model to predict stream flow based on snow cover and precipitation in the Mokelumne River Basin in the Sierra Nevada in California. The snow cover of the Mokelumne River Basin is monitored using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. Using data from these images as well as precipitation data from 2000 to 2009, we produced a predictive statistical model. The final results show that with an R2 of 0.71, the true natural flow (TNF) of the Mokelumne River is based on the daily area of snow cover in each of seven equal area elevation zones according to the time lag of that zone as well as the accumulated precipitation functioning as a proxy for snow depth. The capability of this model to predict water supply suggests the potential for developing new spatial hydrologic informational products based on MODIS and the probability of improving the accuracy of the prediction of hydrologic processes for water resource managers.

  10. Assimilation of Airborne Snow Observatory Snow Water Equivalent to Improve Runoff Forecasting Model Performance and Reservoir Management During Warm and Dry Winters

    Science.gov (United States)

    McGurk, B. J.; Painter, T. H.

    2015-12-01

    The Airborne Snow Observatory (ASO) NASA-JPL demonstration mission has collected detailed snow information for portions of the Tuolumne Basin in California for three years, 2013 - 2015. Both 2014 and 2015 were low snow years, and 2015 was exceptionally warm and analogous to future years after climate change. The ASO uses an imaging spectrometer and LiDAR sensors mounted in an aircraft to collect snow depth and extent data, and snow albedo. By combining ground and modeled density fields, the ~weekly flights over the Tuolumne produced both basin-wide and detailed sub-basin snow water equivalent (SWE) estimates that were provided to Hetch Hetchy Reservoir operators. The data were also assimilated into an hydrologic simulation model in an attempt to improve the accuracy and timing of a runoff forecasting tool that can be used to improve the management of Hetch Hetchy Reservoir, the source of 85% of the water supply for 2.6 million people on the San Francisco Peninsula. The USGS Precipitation Runoff Modeling System was calibrated to the 1181 square kilometer basin and simulation results compared to observed runoff with and without assimilation of ASO data. Simulated and observed were also compared with observed with both single updates associated with each flight, and with sequential updates from each flight. Sequential updating was found to improve correlation between observed and simulated reservoir inflows, and there by improve the ability of reservoir operators to more efficiently allocate the last half of the recession limb of snowmelt inflow and be assured of filling the reservoir and minimizing ecologically-damaging late season spills.

  11. Influence of snow pack and soil water dynamics on river flows in un-glaciarized Himalayan catchments.

    Science.gov (United States)

    Eeckman, Judith; Neppel, Luc; Chevalier, Pierre; Delclaux, François; Boone, Aaron

    2016-04-01

    In the Central Himalayas, it is generally accepted that 80 % of the annual precipitation occurs during the monsoon months (June - September). However, surveys with local populations show that surface water is available throughout the year. The main question then is to identify the origin of these surface flows. One hypothesis proposes that they are provided by glacial melt during the dry season. However, on the one hand, this historically "permanent" supply is also observed in catchments with little or no glacial contribution, and on the other hand, annual volumes cannot be totally explained by the glacial mass balances currently monitored. Therefore, a better understanding of the hydrological processes is needed for quantifying the influence of the inter-seasonal surface (snow) and sub-surface storage on surface flows outside of the monsoon season. One solution consists in the application of modelling tools. However, simulations for Himalayan catchments are limited due to a lack of knowledge regarding their hydrological behaviour. The main source of uncertainty in poorly monitored environments is the scarcity of observations, which can be used for model calibration and evaluation. In this study, physically-based modelling with the ISBA Soil-Vegetation-Atmosphere transfer scheme is applied to small catchments whose physical characteristics are well studied, therefore this approach could constitute an interesting way for understanding hydrological systems. For that purpose, two small slope catchments selected in the Dudh Koshi River basin (Eastern Nepal), which represent high and mid-mountain environments, are studied in order to evaluate the spatial variability of the studied processes. They are equipped with 6 stations for air temperature and precipitation observations. A distributed approach allows a better representation of the spatial variation of hydro-climatic processes. Moreover, the descriptions of surfaces currently available at global scales are enhanced

  12. Spatial and temporal variability of snow water equivalent in relations to the physiographic characteristics of the Kern watershed in the Sierra Nevada, CA

    Science.gov (United States)

    Girotto, M.; Cortes, G.; Margulis, S. A.; Durand, M. T.

    2012-12-01

    The spatial heterogeneity of the mountainous snowpack and a continuously changing climate affects a variety of processes including surface water discharge. An apparent shifting in ablation time and loss of SWE in the Sierra Nevada Mountains has been reported from several past studies based on downstream flow and/or point scale in-situ observations records. Understanding the geophysical controls and interannual variability of the spatial patterns of snow accumulation and ablation are critical for predicting the effects of climate variability on the snowpack water storage. Therefore, a continuous space-time characterization of snow distribution that uses spatially and temporally extensive remotely sensed information is necessary to improve our ability to predict and monitor this vital resource over complex mountainous terrain. Toward this end, this research estimates continuous spatial and temporal Snow Water Equivalent (SWE) estimates over the Kern watershed, a ~5300 km2 watershed characterized by a wide variety of physiographic characteristics, such as elevation, vegetation cover, and vegetation type. Kern extends 142 km north to south and 59 km east to west and it discharges its runoff to Lake Isabella (~0.57 million acre-feet), which is the largest open water reservoir of Southern California. We use a Bayesian reanalysis data assimilation approach, similar to an Ensemble Kalman Smoother, capable of merging remotely sensed Fractional Snow Covered Area (FSCA) data into snow prediction models, and at the same time accounting for the limitations of each. FSCA derived from the approximately three decade record of Landsat-5 thematic mapper are assimilated. The assimilation of FSCA into the land surface-snow depletion model, predicts seasonal, continuous (in space and time) SWE and FSCA at a nominal 90 m spatial resolution. The resulting SWE dataset from the assimilation framework, and its relation to different physiographic properties, is studied to explore specific

  13. Ion Mobility Spectrometry for Water Monitoring Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Current water quality monitors aboard the International Space Station (ISS) are specialized and provide limited data. The Colorimetric Water Quality Monitor Kit...

  14. Climate change impacts on snow water availability in the Euphrates-Tigris basin

    OpenAIRE

    Özdoğan, M.

    2011-01-01

    This study investigates the effects of projected climate change on snow water availability in the Euphrates-Tigris basin using the Variable Infiltration Capacity (VIC) macro scale hydrologic model and a set of regional climate-change outputs from 13 global circulation models (GCMs) forced with two greenhouse gas emission scenarios for two time periods in the 21st century (2050 and 2090). The hydrologic model produces a reasonable simulation of seasonal and spatial variation ...

  15. Studies of Aquatic Fungi. XXIV. Aquatic Fungi in the Water of Melting Snow

    Directory of Open Access Journals (Sweden)

    Bazyli Czeczuga

    2014-08-01

    Full Text Available The work was undertaken to investigate the mycoflora in the water of melting snow. Samples of water were collected in March 1987-1988 for hydrochemical analysis (3 sites and studies of the fungus content (9 sites. Forty-nine species of fungi were found in this waters. The following fungi unknown from Poland were found: Skirgiella septigena, Monoblepharis macraodra, M. polymorpha, M. fascicutlta, M. insignis, Achlya apiculata, Apodachlya punctata, Pythium dissotocum, Hansenula holstii, H. saturnus, Actiaospora megalospora and Heliscus lugdunensis.

  16. Tomography-based monitoring of isothermal snow metamorphism under advective conditions

    OpenAIRE

    P. P. Ebner; M. Schneebeli; A. Steinfeld

    2015-01-01

    Time-lapse X-ray microtomography was used to investigate the structural dynamics of isothermal snow metamorphism exposed to an advective airflow. The effect of diffusion and advection across the snow pores on the snow microstructure were analysed in controlled laboratory experiments and possible effects on natural snowpacks discussed. The 3-D digital geometry obtained by tomographic scans was used in direct pore-level numerical simulations to determine the effective permeabi...

  17. Comparing the impacts of mature spruce forests and grasslands on snow melt, water resource recharge, and run-off in the northern boreal environment

    Directory of Open Access Journals (Sweden)

    Jiří Kremsa

    2015-03-01

    Full Text Available Snow-melt runoff is an important factor in control of flooding and soil erosion in higher and cold regions of the world. In 1992–2008–2008, processes of snow accumulation and melting were monitored at two adjacent sites of the Paljakka environmental research centre (Finland. The forest stand of mature spruce (Picea abies has been compared with adjacent, local, and open grassland. In the forest, snowpack duration fluctuated for 180–245 days, with a maximum depth of 78–152 cm and snow–water content of 167–406 mm, while in the open grassland this occurred for some 20 days less, with maximum depth 65–122 cm, and snow–water content 143–288 mm. The snow–water captured in the canopy reached a maximum 27% of that registered on the ground; the loss of intercepted snow by sublimation was approximately 26% of the annual snowfall. During the high melt period (April–May, the degree-day factor in the forest stand achieved 60% of values observed in the grassland (2.3–3.5 against 3.8–6.0 mm °C−1 day−1. The hydrological model BROOK 90 was employed to analyse potential water resources recharge, and flood risk at Paljakka. Considering the normal climate season, snow-melt runoff from the forest exceeded the grassland by 22% (225 against 185 mm. In extreme situations, the maximum daily runoff from snow-melt in the grasslands (57 mm day−1 exceeded 2.6 times the values in spruce forest (22 mm day−1.

  18. A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation

    Science.gov (United States)

    Skaugen, Thomas; Weltzien, Ingunn H.

    2016-09-01

    Snow is an important and complicated element in hydrological modelling. The traditional catchment hydrological model with its many free calibration parameters, also in snow sub-models, is not a well-suited tool for predicting conditions for which it has not been calibrated. Such conditions include prediction in ungauged basins and assessing hydrological effects of climate change. In this study, a new model for the spatial distribution of snow water equivalent (SWE), parameterized solely from observed spatial variability of precipitation, is compared with the current snow distribution model used in the operational flood forecasting models in Norway. The former model uses a dynamic gamma distribution and is called Snow Distribution_Gamma, (SD_G), whereas the latter model has a fixed, calibrated coefficient of variation, which parameterizes a log-normal model for snow distribution and is called Snow Distribution_Log-Normal (SD_LN). The two models are implemented in the parameter parsimonious rainfall-runoff model Distance Distribution Dynamics (DDD), and their capability for predicting runoff, SWE and snow-covered area (SCA) is tested and compared for 71 Norwegian catchments. The calibration period is 1985-2000 and validation period is 2000-2014. Results show that SDG better simulates SCA when compared with MODIS satellite-derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" and giving spurious positive trends in SWE, typical for SD_LN, is prevented. The precision of runoff simulations using SDG is slightly inferior, with a reduction in Nash-Sutcliffe and Kling-Gupta efficiency criterion of 0.01, but it is shown that the high precision in runoff prediction using SD_LN is accompanied with erroneous simulations of SWE.

  19. Ballast Water Self Monitoring

    Science.gov (United States)

    2011-11-01

    water treatment systems for disinfection including:  Chlorination  Electrochlorination  Ozonation  Chlorine dioxide  Peracetic acid ...presents a challenge since the reagents used are themselves chemically hazardous. Peracetic acid and hydrogen peroxide (provided as a blend of the two...dosage and usage -Hydrogen peroxide readings from both on-line sensor and sample analysis -Hydrogen peroxide dosage and usage Peracetic acid On

  20. Snow physics as relevant to snow photochemistry

    Directory of Open Access Journals (Sweden)

    F. Domine

    2007-05-01

    Full Text Available Snow on the ground is a complex multiphase photochemical reactor that dramatically modifies the chemical composition of the overlying atmosphere. A quantitative description of the emissions of reactive gases by snow requires the knowledge of snow physical properties. This overview details our current understanding of how those physical properties relevant to snow photochemistry vary during snow metamorphism. Properties discussed are density, specific surface area, optical properties, thermal conductivity, permeability and gas diffusivity. Inasmuch as possible, equations to parameterize these properties as a function of climatic variables are proposed, based on field measurements, laboratory experiments and theory. The potential of remote sensing methods to obtain information on some snow physical variables such as grain size, liquid water content and snow depth are discussed. The possibilities for and difficulties of building a snow photochemistry model by adapting current snow physics models are explored. Elaborate snow physics models already exist, and including variables of particular interest to snow photochemistry such as light fluxes and specific surface area appears possible. On the other hand, understanding the nature and location of reactive molecules in snow seems to be the greatest difficulty modelers will have to face for lack of experimental data, and progress on this aspect will require the detailed study of natural snow samples.

  1. Simulations of a Canadian snowpack brightness temperatures using SURFEX-Crocus for Snow Water Equivalent (SWE) retrievals

    Science.gov (United States)

    Larue, Fanny; Royer, Alain; De Sève, Danielle; Langlois, Alexandre; Roy, Alexandre; Saint-Jean-Rondeau, Olivier

    2016-04-01

    In Quebec, the water associated to snowmelt represents 30% of the annual electricity production so that the snow cover evaluation in real time is of primary interest. The key variable is snow water equivalent (SWE) which describes the evolution of a global seasonal snow cover. However, the sparse distribution of meteorological stations in northern Québec generates great uncertainty in the extrapolation of SWE. On the contrary, the spatial and temporal coverage of satellite data offer a source of information with a high potential when considered as an alternative to the poor spatial distribution of in-situ information. Thus, this project aims to improve the prediction of SWE by assimilation of satellite passive microwave brightness temperatures (Tb) observations, independently of any ground observations. The snowpack evolution is simulated by the French snow model SURFEX-Crocus, driven by the Canadian atmospheric model GEM with a spatial resolution of 10 km. The bias of the atmospheric model and the impact of initialization errors on the simulated SWE were quantified from our ground measurements. To assimilate satellite observations, the multi-layered snow model is first coupled with a radiative transfer model using the Dense Media Radiative transfer theory (the DMRT-ML model) to estimate the microwave snow emission of the simulated snowpack. In order to retrieve simulated Tb in frequencies of interest (i.e. sensitive to snow dielectric properties), the snow microstructure needs to be well parameterized. It was shown in previous studies that the specific surface area (SSA) of snow grains is a well-defined parameter to describe the size and the shape of snow grains and which allows reproducible field measurements. SURFEX-Crocus estimates a SSA for each simulated snow layer, however, the snow microstructure in DMRT-ML is defined per layer by monodisperse optical radius of grain (~ 1/SSA) and by the stickiness which is not known. It thus becomes necessary to introduce

  2. Sublimation of Exposed Snow Queen Surface Water Ice as Observed by the Phoenix Mars Lander

    Science.gov (United States)

    Markiewicz, W. J.; Keller, H. U.; Kossacki, K. J.; Mellon, M. T.; Stubbe, H. F.; Bos, B. J.; Woida, R.; Drube, L.; Leer, K.; Madsen, M. B.; Goetz, W.; El Maarry, M. R.; Smith, P.

    2008-12-01

    One of the first images obtained by the Robotic Arm Camera on the Mars Phoenix Lander was that of the surface beneath the spacecraft. This image, taken on sol 4 (Martian day) of the mission, was intended to check the stability of the footpads of the lander and to document the effect the retro-rockets had on the Martian surface. Not completely unexpected the image revealed an oval shaped, relatively bright and apparently smooth object, later named Snow Queen, surrounded by the regolith similar to that already seen throughout the landscape of the landing site. The object was suspected to be the surface of the ice table uncovered by the blast of the retro-rockets during touchdown. High resolution HiRISE images of the landing site from orbit, show a roughly circular dark region of about 40 m diameter with the lander in the center. A plausible explanation for this region being darker than the rest of the visible Martian Northern Planes (here polygonal patterns) is that a thin layer of the material ejected by the retro-rockets covered the original surface. Alternatively the thrusters may have removed the fine surface dust during the last stages of the descent. A simple estimate requires that about 10 cm of the surface material underneath the lander is needed to be ejected and redistributed to create the observed dark circular region. 10 cm is comparable to 4-5 cm predicted depth at which the ice table was expected to be found at the latitude of the Phoenix landing site. The models also predicted that exposed water ice should sublimate at a rate not faster but probably close to 1 mm per sol. Snow Queen was further documented on sols 5, 6 and 21 with no obvious changes detected. The following time it was imaged was on sol 45, 24 sols after the previous observation. This time some clear changes were obvious. Several small cracks, most likely due to thermal cycling and sublimation of water ice appeared. Nevertheless, the bulk of Snow Queen surface remained smooth. The next

  3. Satellite Image-based Estimates of Snow Water Equivalence in Restored Ponderosa Pine Forests in Northern Arizona

    Science.gov (United States)

    Sankey, T.; Springer, A. E.; O'Donnell, F. C.; Donald, J.; McVay, J.; Masek Lopez, S.

    2014-12-01

    The U.S. Forest Service plans to conduct forest restoration treatments through the Four Forest Restoration Initiative (4FRI) on hundreds of thousands of acres of ponderosa pine forest in northern Arizona over the next 20 years with the goals of reducing wildfire hazard and improving forest health. The 4FRI's key objective is to thin and burn the forests to create within-stand openings that "promote snowpack accumulation and retention which benefit groundwater recharge and watershed processes at the fine (1 to 10 acres) scale". However, little is known about how these openings created by restoration treatments affect snow water equivalence (SWE) and soil moisture, which are key parts of the water balance that greatly influence water availability for healthy trees and for downstream water users in the Sonoran Desert. We have examined forest canopy cover by calculating a Normalized Difference Vegetation Index (NDVI), a key indicator of green vegetation cover, using Landsat satellite data. We have then compared NDVI between treatments at our study sites in northern Arizona and have found statistically significant differences in tree canopy cover between treatments. The control units have significantly greater forest canopy cover than the treated units. The thinned units also have significantly greater tree canopy cover than the thin-and-burn units. Winter season Landsat images have also been analyzed to calculate Normalized Difference Snow Index (NDSI), a key indicator of snow water equivalence and snow accumulation at the treated and untreated forests. The NDSI values from these dates are examined to determine if snow accumulation and snow water equivalence vary between treatments at our study sites. NDSI is significantly greater at the treated units than the control units. In particular, the thinned forest units have significantly greater snow cover than the control units. Our results indicate that forest restoration treatments result in increased snow pack

  4. Three-year study on feasibility of Snow Water Equivalent retrieval using X- to Ku band SAR

    Science.gov (United States)

    Lemmetyinen, Juha; Pulliainen, Jouni; Kontu, Anna; Wiesmann, Andreas; Mätzler, Christian; Rott, Helmut; Nagler, Thomas; Meta, Adriano; Schneebeli, Martin; Proksch, Martin; Davidson, Malcolm; Schüttemeyer, Dirk; Kern, Michael

    2013-04-01

    The possibility of high-resolution SAR imagery to derive information on the Snow Water Equivalent (SWE) of seasonal snow cover is one of the main goals of the proposed CoReH2O (Cold Regions Hydrology High-Resolution Observatory) mission. CoReH2O is a candidate 7th Earth Explorer Core mission by the European Space Agency (ESA), currently in Phase A. The NoSREx (Nordic Snow Radar Experiment) campaign was initiated in 2009 to provide data for development of the CoReH2O geophysical retrieval algorithm. The campaign provides a time-series of backscatter observations at X to Ku bands, the dual frequency bands proposed for CoReH2O, from snow covered terrain in the boreal forest/taiga region. The campaign was designed to cover entire winter periods from snow free conditions to eventual snow melt-off. Backscatter measurements of snow cover are complemented by microwave emission (radiometer) observations and numerous in situ observations of snow, soil and atmospheric properties. The campaign thus provides a unique, near-continuous dataset of coinciding microwave observations of snow cover and diverse measurements of snow characteristics over several winter seasons. The main instrument of the campaign is the ESA SnowScat scatterometer, installed for the entire campaign at a fixed location. The instrument provides a consistent time series of observations, allowing relating the backscatter signature to small scale changes in the snowpack at a high temporal resolution. During the second and third seasons of the campaign, SnowScat measurements were complemented by extensive airborne data acquisitions using the ESA X/Ku band SnowSAR instrument. The airborne data provide additional information on spatial variability of the backscattering signal, and allow demonstration of the CoReH2O SWE retrieval concept. As a reference to backscatter observations, the campaign provides routinely both manual and automated measurements of snow properties throughout the season. In addition, several

  5. Building a Cloud-based Global Snow Observatory

    Science.gov (United States)

    Li, X.; Coll, J. M.

    2016-12-01

    Snow covers some 40 percent of Earth's land masses year in and year out and constitutes a vitally important variable for the planet's climate, hydrology, and biosphere due to its high albedo and insulation. It affects atmospheric circulation patterns, permafrost, glacier mass balance, river discharge, and groundwater recharge (Dietz et al. 2015). Snow is also nature's igloo where species from microscopic fungi to 800-pound moose survive the winter each in its own way (Pauli et al. 2013; Petty et al. 2015). Many studies have found that snow in high elevation regions is particularly sensitive to global climate change and is considered as sentinel of change. For human beings, about one-sixth of the world's population depends on seasonal snow and glaciers for their water supply (Barnett et al. 2005) and more than 50% of mountainous areas have an essential or supportive role for downstream regions (Viviroli et al. 2007). Large snowstorms also have a major impact on society in terms of human life, economic loss, and disruption (Squires et al. 2014). Remote sensing provides a practical approach of monitoring global snow and ice cover change. Based on our comprehensive validation and assessment on MODIS snow products, we build a cloud-based Global Snow Observatory (GSO) using Google Earth Engine (GEE) to serve as a platform for global researchers and the general public to access, visualize, and analyze snow data and to build snowmelt runoff models for mountain watersheds. Specifically, we build the GSO to serve global MODIS daily snow cover data and their analyses through GEE on Google App Engine. The GSO provides users the functions of accessing and extracting cloud-gap-filled snow data and interactive snow cover change exploration. In addition to snow cover frequency (SCF), we also plan to develop several other snow cover parameters, including snow cover duration/days, snow cover onset dates, and snow cover melting dates, and to study the shift and trend of global snow

  6. Weekly LiDAR snow depth mapping for operational snow hydrology - the NASA JPL Airborne Snow Observatory (Invited)

    Science.gov (United States)

    Deems, J. S.; Painter, T. H.; McGurk, B. J.

    2013-12-01

    Operational hydrologic simulation and forecasting in snowmelt-dominated watersheds currently relies on indices of snow accumulation and melt from measurements at a small number of point locations or geographically-limited manual surveys. These data sources cannot adequately characterize the spatial distribution of snow depth/water equivalent, which is the primary determinant of snowpack volume and runoff rates. The NASA JPL Airborne Snow Observatory's airborne laser scanning system maps snow depth at high spatial and temporal resolutions, providing an unprecedented snowpack monitoring capability and enabling a new operational paradigm. In the Spring of 2013, the ASO mapped snow depth in the Tuolumne River Basin in California's Yosemite National Park on a nominally weekly basis, and provided fast-turnaround spatial snow depth and water equivalent maps to the operators of Hetch Hetchy Reservoir, the water supply for 2.5 million people on the San Francisco peninsula. These products enabled more accurate runoff simulation and optimal reservoir management in a year of very low snow accumulation. We present the initial results from this new application of multi-temporal LiDAR mapping in operational snow hydrology.

  7. Heavy snow: IR spectroscopy of isotope mixed crystalline water ice.

    Science.gov (United States)

    Wong, Andy; Shi, Liang; Auchettl, Rebecca; McNaughton, Don; Appadoo, Dominique R T; Robertson, Evan G

    2016-02-14

    Mid-infrared spectra have been measured for crystalline water ice aerosols of widely varied H/D isotopic composition. Particles with diameters ranging from 10-200 nm were generated via rapid collisional cooling with a cold buffer gas over a range of temperatures from 7-200 K. In near isotopically pure ices, the νL band position is slightly red-shifted with increasing temperature whilst in the ν2 region apparently anomalous shifts in peak maxima are explained by the contribution of a broad 2νL band of H2O and a 3νL band of D2O together with ν2 intensity that is particularly weak in low temperature crystalline ice. The hydrogen bonded OH (or OD) oscillator bands of near pure H2O (or D2O) ices are blue-shifted with temperature, with a gradient very similar to that of the corresponding band in isotope diluted samples, HOD in D2O (or H2O). It implies that this observed temperature trend is predominantly due to the intrinsic change in local hydride stretch potential energy, rather than to changes in intermolecular coupling. However, it is also observed that the narrow hydride stretch bands of an isotope diluted sample rapidly develop sub-band structure as the oscillator concentration increases, evidence of strong intermolecular coupling and a high degree of delocalisation. Anomalous blue-shifts in the OD stretch profile as D2O concentration grows is attributable to Fermi resonance with 2ν2 of D2O, in much closer proximity than the corresponding H2O levels. Theoretical results from a mixed quantum/classical approach are used to validate these findings in the hydride stretching region. Theory qualitatively reproduces the experimental trends as a function of temperature and isotopic variance.

  8. Permafrost and snow monitoring at Rothera Point (Adelaide Island, Maritime Antarctica): Implications for rock weathering in cryotic conditions

    Science.gov (United States)

    Guglielmin, Mauro; Worland, M. Roger; Baio, Fabio; Convey, Peter

    2014-11-01

    In February 2009 a new permafrost borehole was installed close to the British Antarctic Survey Station at Rothera Point, Adelaide Island (67.57195°S 68.12068°W). The borehole is situated at 31 m asl on a granodiorite knob with scattered lichen cover. The spatial variability of snow cover and of ground surface temperature (GST) is characterised through the monitoring of snow depth on 5 stakes positioned around the borehole and with thermistors placed at three different rock surfaces (A, B and C). The borehole temperature is measured by 18 thermistors placed at different depths between 0.3 and 30 m. Snow persistence is very variable both spatially and temporally with snow free days per year ranging from 13 and more than 300, and maximum snow depths varying between 0.03 and 1.42 m. This variability is the main cause of high variability in GST, that ranged between - 3.7 and - 1.5 °C. The net effect of the snow cover is a cooling of the surface. Mean annual GST, mean summer GST, and the degree days of thawing and the n-factor of thawing were always much lower at sensor A where snow persistence and depth were greater than in the other sensor locations. At sensor A the potential freeze-thaw events were negligible (0-3) and the thermal stress was at least 40% less than in the other sensor locations. The zero curtain effect at the rock surface occurred only at surface A, favouring chemical weathering over mechanical action. The active layer thickness (ALT) ranged between 0.76 and 1.40 m. ALT was directly proportional to the mean air temperature in summer, and inversely proportional to the maximum snow depth in autumn. ALT temporal variability was greater than reported at other sites at similar latitude in the Northern Hemisphere, or with the similar mean annual air temperature in Maritime Antarctica, because vegetation and a soil organic horizon are absent at the study site. Zero annual amplitude in temperature was observed at about 16 m depth, where the mean annual

  9. The effect of model scale in reconstructing snow water equivalent over complex terrain

    Science.gov (United States)

    Molotch, N. P.; Durand, M.; Margulis, S. A.

    2007-05-01

    Improving estimates of water and energy fluxes in the rugged landscapes of the American Cordillera is particularly challenging given the considerable topographic heterogeneity and paucity of observations within the region. In these complex systems, parameterizations of sub-grid variability in energy and mass transformations are highly sensitive to relationships between model spatial resolution and the correlation-length scale of the variable of interest - which is usually unknown. In the mountainous regions of the Western United States, the processes controlling the distribution of snow water equivalent are likely better known than any other hydrologic state. The observation record is relatively long (dating back to the early part of the 20th century) and snow cover is relatively easy to detect using remotely sensed observations in the visible and near infrared. Hence, distributed snowpack simulations provide an ideal case study for exploring relationships between process, model, and observation scales; potentially guiding efforts regarding other hydrologic states (e.g. soil moisture). To that end, this research uses a time series of fractional snow covered area (SCA) estimates from Landsat Enhanced Thematic Mapper (ETM+), Moderate Resolution Imaging Spectoradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) data, in combination with a spatially distributed snowmelt model, to reconstruct snow water equivalent (SWE) in the Rio Grande headwaters (3,419 km2) of Colorado, USA. In this reconstruction approach, modeled snowmelt over each pixel is integrated over the time of satellite observed snow cover to estimate SWE. Despite the considerable differences in the magnitude of SWE in 2001 versus 2002, model performance - using ETM+ data aggregated to 100-m resolution - was robust with a mean absolute error (MAE) of 23% relative to observed SWE from intensive field campaigns. Model performance deteriorated when MODIS (MAE = 57%) and AVHRR (MAE = 90

  10. Magnetic treatment of irrigation water and snow pea and chickpea seeds enhances early growth and nutrient contents of seedlings.

    Science.gov (United States)

    Grewal, Harsharn S; Maheshwari, Basant L

    2011-01-01

    The effects of magnetic treatment of irrigation water and snow pea (Pisum sativum L var. macrocarpon) and Kabuli chickpea (Cicer arietinum L) seeds on the emergence, early growth and nutrient contents of seedlings were investigated under glasshouse conditions. The treatments included (i) magnetic treatment of irrigation water (MTW), (ii) magnetic treatment of seeds (MTS), (iii) magnetic treatment of irrigation water and seeds (MTWS) and (iv) no magnetic treatment of irrigation water or seeds as control treatment. A magnetic treatment device with two permanent magnets (magnetic induction: 3.5-136 mT) was used for the above treatments. Seeds were sown in washed sand and seedlings were harvested at 20 days. The results showed that MTW led to a significant (P < 0.05) increase in emergence rate index (ERI; 42% for snow pea and 51% for chickpea), shoot dry weight (25% for snow pea and 20% for chickpea) and contents of N, K, Ca, Mg, S, Na, Zn, Fe and Mn in both seedling varieties compared to control seedlings. Likewise, there were significant increases in ERI (33% for snow peas and 37% for chickpea), shoot dry weight (11% for snow pea and 4% for chickpea) and some nutrients of snow pea and chickpea seedlings with MTS in comparison with the controls. The results of this study suggest that both MTW and MTS have the potential to improve the early seedling growth and nutrient contents of seedlings.

  11. Mapping of ice, snow and water using aircraft-mounted LiDAR

    Science.gov (United States)

    Church, Philip; Matheson, Justin; Owens, Brett

    2016-05-01

    Neptec Technologies Corp. has developed a family of obscurant-penetrating 3D laser scanners (OPAL 2.0) that are being adapted for airborne platforms for operations in Degraded Visual Environments (DVE). The OPAL uses a scanning mechanism based on the Risley prism pair. Data acquisition rates can go as high as 200kHz for ranges within 240m and 25kHz for ranges exceeding 240m. The scan patterns are created by rotating two prisms under independent motor control producing a conical Field-Of-View (FOV). An OPAL laser scanner with 90° FOV was installed on a Navajo aircraft, looking down through an aperture in the aircraft floor. The rotation speeds of the Risley prisms were selected to optimize a uniformity of the data samples distribution on the ground. Flight patterns simulating a landing approach over snow and ice in an unprepared Arctic environment were also performed to evaluate the capability of the OPAL LiDAR to map snow and ice elevation distribution in real-time and highlight potential obstacles. Data was also collected to evaluate the detection of wires when flying over water, snow and ice. Main results and conclusions obtained from the flight data analysis are presented.

  12. Islands erased by snow and ice: approaching the spatial philosophy of cold water island imaginaries

    Directory of Open Access Journals (Sweden)

    Johannes Riquet

    2016-05-01

    Full Text Available Representations of islands in Western fiction typically revolve around tropical islands. Critical discourse tends to reproduce this tendency and rarely addresses the specific spatial poetics of cold-water island fictions. This paper discusses three texts that poetically deploy the geographical inventory of northern snow- and icescapes to challenge essentialist assumptions about islands: D. H. Lawrence’s short story “The man who loved islands”, Georgina Harding’s novel The solitude of Thomas Cave, and Michel Serres’s treatise Le passage du Nord-Ouest. It is argued that these texts reflect on the importance of the horizontal and vertical components of material and textual topographies for the conception and experience of islands. In all three, the physical transformation of the islandscapes by snow and ice serves to put the island concept itself into question. Serres’s philosophical text geopoetically portrays the Arctic archipelago of the Northwest Passage to explore the reciprocal relations between language and the material world. In Lawrence and Harding, the snow-covered islands cease to function as economically productive spaces and turn into complex spatial figures offering a philosophical meditation on islandness as a contradictory and multifaceted condition.

  13. Fungal spores as potential ice nuclei in fog/cloud water and snow

    Science.gov (United States)

    Bauer, Heidi; Goncalves, Fabio L. T.; Schueller, Elisabeth; Puxbaum, Hans

    2010-05-01

    INTRODUCTION: In discussions about climate change and precipitation frequency biological ice nucleation has become an issue. While bacterial ice nucleation (IN) is already well characterized and even utilized in industrial processes such as the production of artificial snow or to improve freezing processes in food industry, less is known about the IN potential of fungal spores which are also ubiquitous in the atmosphere. A recent study performed at a mountain top in the Rocky Mountains suggests that fungal spores and/or pollen might play a role in increased IN abundance during periods of cloud cover (Bowers et al. 2009). In the present work concentrations of fungal spores in fog/cloud water and snow were determined. EXPERIMENTAL: Fog samples were taken with an active fog sampler in 2008 in a traffic dominated area and in a national park in São Paulo, Brazil. The number concentrations of fungal spores were determined by microscopic by direct enumeration by epifluorescence microscopy after staining with SYBR Gold nucleic acid gel stain (Bauer et al. 2008). RESULTS: In the fog water collected in the polluted area at a junction of two highly frequented highways around 22,000 fungal spores mL-1 were counted. Fog in the national park contained 35,000 spores mL-1. These results were compared with cloud water and snow samples from Mt. Rax, situated at the eastern rim of the Austrian Alps. Clouds contained on average 5,900 fungal spores mL-1 cloud water (1,300 - 11,000) or 2,200 spores m-3 (304 - 5,000). In freshly fallen snow spore concentrations were lower than in cloud water, around 1,000 fungal spores mL-1 were counted (Bauer et al. 2002). In both sets of samples representatives of the ice nucleating genus Fusarium could be observed. REFERENCES: Bauer, H., Kasper-Giebl, A., Löflund, M., Giebl, H., Hitzenberger, R., Zibuschka, F., Puxbaum, H. (2002). The contribution of bacteria and fungal spores to the organic carbon content of cloud water, precipitation and aerosols

  14. Unsaturated Flow Modeling in the Seasonally Snow-Covered Roselend Granite (French Alps) Using High Resolution and Long Term Meteorological and Water Flux Time Series

    Science.gov (United States)

    Patriarche, D.; Pili, E.; Richon, P.; Willemet, J.; Bureau, S.

    2006-12-01

    Quantifying water flow in an unsaturated and fractured medium is a challenging task which is often performed in media where water is scarce, in the context of studies related to waste disposals. The Roselend research program intends to clarify and to develop adapted methodologies to quantify unsaturated flow in fractured media undergoing strong external solicitations. Among them, the influence of drought and snowmelt recharge alternations is investigated. To do so, the 128 meter long Roselend tunnel that has been drilled in the sixties, in the granite (overburden of 55 meters at the closed end of the tunnel) at the vicinity of an artificial lake, is equipped with sensors recording dripwater fluxes at one hour time step, and water chemistry (major and trace elements) with sampling time varying from 36 hours to 4 days. Water level is also monitored by two boreholes located between the tunnel entrance and the lake. A meteorological station installed nearby the tunnel entrance provides hourly records of meteorological parameters. Additionally, an artificial tracer was injected in the ground surface, above the tunnel closed end. The high-range and steep mountainous environment in which the Roselend site is located is characterized by contrasted precipitation regimes with alternating snow, rain, and drought periods. Seasonal flow dynamics arise from dominant rain and melted snow infiltrations from late summer to mid-spring, increasing water content in the medium, and modulating flow rates of percolating waters. Over four years, infiltration in the medium is assessed considering separately the winter (snow on the ground) and summer (no snow on the ground) seasons. For the summer seasons, hourly potential evapotranspiration is calculated using the Penman-Monteith method, and is summed over each day. The real evapotranspiration is systematically calculated using the Thornthwaite-Mather budget, for various available soil water capacities at a daily time step. For the winter

  15. Assimilation of satellite information in a snowpack model to improve characterization of snow cover for runoff simulation and forecasting

    OpenAIRE

    2009-01-01

    A new technique for constructing spatial fields of snow characteristics for runoff simulation and forecasting is presented. The technique incorporates satellite land surface monitoring data and available ground-based hydrometeorological measurements in a physical based snowpack model. The snowpack model provides simulation of temporal changes of the snow depth, density and water equivalent (SWE), accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with...

  16. Objective Characterization of Snow Microstructure for Microwave Emission Modeling

    Science.gov (United States)

    Durand, Michael; Kim, Edward J.; Molotch, Noah P.; Margulis, Steven A.; Courville, Zoe; Malzler, Christian

    2012-01-01

    Passive microwave (PM) measurements are sensitive to the presence and quantity of snow, a fact that has long been used to monitor snowcover from space. In order to estimate total snow water equivalent (SWE) within PM footprints (on the order of approx 100 sq km), it is prerequisite to understand snow microwave emission at the point scale and how microwave radiation integrates spatially; the former is the topic of this paper. Snow microstructure is one of the fundamental controls on the propagation of microwave radiation through snow. Our goal in this study is to evaluate the prospects for driving the Microwave Emission Model of Layered Snowpacks with objective measurements of snow specific surface area to reproduce measured brightness temperatures when forced with objective measurements of snow specific surface area (S). This eliminates the need to treat the grain size as a free-fit parameter.

  17. Modelled seasonal forecasts of snow water equivalent and runoff in alpine catchments

    Science.gov (United States)

    Förster, Kristian; Hanzer, Florian; Schöber, Johannes; Huttenlau, Matthias; Achleitner, Stefan; Strasser, Ulrich

    2016-04-01

    Seasonal forecasts of water balance components are becoming increasingly important for hydrological applications. These forecasts are typically derived from coupled atmosphere-ocean climate models, which enable physically based seasonal forecasts. In mountainous regions, however, topography is complex whilst typical spatial resolutions of the climate models are still comparably coarse, i.e in the data, ridges and valleys are not represented with sufficient accuracy. Therefore, seasonal predictions of atmospheric variables require consideration of representative gradients. We present first results of seasonal forecasts and re-forecasts processed by the NCEP (National Centers for Environmental Prediction) Climate Forecast System version 2 (CFSv2). These are prepared for monthly time steps in order to be used for ensemble runs of water balance simulation using the Alpine Water balance And Runoff Estimation model (AWARE). This model has been designed for monthly seasonal predictions in ice- and snowmelt dominated catchments. The study area is the Inn catchment in Tyrol/Austria, including its headwaters in Switzerland. Results are evaluated for both anomalies of meteorological input data (temperature and precipitation), as well as balance components including snow water equivalent and runoff, both simulated with AWARE. Based on model skill evaluations derived from forecasts and observations, the model chain CFSv2 - AWARE proves helpful to analyse possible future hydrological system states of mountainous catchments with emphasis on spatio-temporal snow cover evolution.

  18. Quantifying the Effects of Wildfire Severity on Snow Water Equivalent in the Sierra Nevada

    Science.gov (United States)

    Nguyen, A.; Cunningham, S.; Sodergren, C.; Anzelc, J.; Cate, N.; Arya, V.

    2015-12-01

    Snowpack in the Sierra Nevada is a crucial component of the California water supply. Climate change effects on forest ecosystems in this region have reduced snowpack and resulted in earlier snowmelt. Wildfire frequency and severity in the Sierra Nevada have also increased, due to higher temperatures, drought, and a legacy of fire suppression policies leading to fuel loads augmented beyond the historic range of variability. These combined factors have the potential to severely impact California water supply. Using 2014 California Basin Characterization Model (BCM) climate data and automated classification of various Landsat imagery, this study geospatially quantified the effects of low, moderate, and high- severity wildfire on snowpack and snow water equivalent (SWE) in the Sierra Nevada. An assessment of modeled SWE data were also conducted to examine its usefulness in better understanding areas effected by wildfire. Results indicate little to no significant change in post-fire SWE for high and moderate severity wildfire, however, delineated a significant decrease in post-fire SWE in the low severity wildfire. Additionally, tests show little no significant change in fractional snow cover post-fire. This use of remote sensing and modeled data will assist in decision and policy making related to management of forest ecosystems and water resources within the Sierra Nevada.

  19. Monitoring snow cover variability (2000-2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method

    Science.gov (United States)

    Li, Xinghua; Fu, Wenxuan; Shen, Huanfeng; Huang, Chunlin; Zhang, Liangpei

    2017-08-01

    Monitoring the variability of snow cover is necessary and meaningful because snow cover is closely connected with climate and ecological change. In this work, 500 m resolution MODIS daily snow cover products from 2000 to 2014 were adopted to analyze the status in Hengduan Mountains. In order to solve the spatial discontinuity caused by clouds in the products, we propose an adaptive spatio-temporal weighted method (ASTWM), which is based on the initial result of a Terra and Aqua combination. This novel method simultaneously considers the temporal and spatial correlations of the snow cover. The simulated experiments indicate that ASTWM removes clouds completely, with a robust overall accuracy (OA) of above 93% under different cloud fractions. The spatio-temporal variability of snow cover in the Hengduan Mountains was investigated with two indices: snow cover days (SCD) and snow fraction. The results reveal that the annual SCD gradually increases and the coefficient of variation (CV) decreases with elevation. The pixel-wise trends of SCD first rise and then drop in most areas. Moreover, intense intra-annual variability of the snow fraction occurs from October to March, during which time there is abundant snow cover. The inter-annual variability, which mainly occurs in high elevation areas, shows an increasing trend before 2004/2005 and a decreasing trend after 2004/2005. In addition, the snow fraction responds to the two climate factors of air temperature and precipitation. For the intra-annual variability, when the air temperature and precipitation decrease, the snow cover increases. Besides, precipitation plays a more important role in the inter-annual variability of snow cover than temperature.

  20. Proof of Concept: Development of Snow Liquid Water Content Profiler Using CS650 Reflectometers at Caribou, ME, USA

    Science.gov (United States)

    Pérez Díaz, Carlos L.; Muñoz, Jonathan; Lakhankar, Tarendra; Khanbilvardi, Reza; Romanov, Peter

    2017-01-01

    The quantity of liquid water in the snowpack defines its wetness. The temporal evolution of snow wetness’s plays a significant role in wet-snow avalanche prediction, meltwater release, and water availability estimations and assessments within a river basin. However, it remains a difficult task and a demanding issue to measure the snowpack’s liquid water content (LWC) and its temporal evolution with conventional in situ techniques. We propose an approach based on the use of time-domain reflectometry (TDR) and CS650 soil water content reflectometers to measure the snowpack’s LWC and temperature profiles. For this purpose, we created an easily-applicable, low-cost, automated, and continuous LWC profiling instrument using reflectometers at the Cooperative Remote Sensing Science and Technology Center-Snow Analysis and Field Experiment (CREST-SAFE) in Caribou, ME, USA, and tested it during the snow melt period (February–April) immediately after installation in 2014. Snow Thermal Model (SNTHERM) LWC simulations forced with CREST-SAFE meteorological data were used to evaluate the accuracy of the instrument. Results showed overall good agreement, but clearly indicated inaccuracy under wet snow conditions. For this reason, we present two (for dry and wet snow) statistical relationships between snow LWC and dielectric permittivity similar to Topp’s equation for the LWC of mineral soils. These equations were validated using CREST-SAFE in situ data from winter 2015. Results displayed high agreement when compared to LWC estimates obtained using empirical formulas developed in previous studies, and minor improvement over wet snow LWC estimates. Additionally, the equations seemed to be able to capture the snowpack state (i.e., onset of melt, medium, and maximum saturation). Lastly, field test results show advantages, such as: automated, continuous measurements, the temperature profiling of the snowpack, and the possible categorization of its state. However, future work

  1. Tomography-based monitoring of isothermal snow metamorphism under advective conditions

    OpenAIRE

    P. P. Ebner; M. Schneebeli; A. Steinfeld

    2015-01-01

    Time-lapse X-ray micro-tomography was used to investigate the structural dynamics of isothermal snow metamorphism exposed to an advective airflow. Diffusion and advection across the snow pores were analysed in controlled laboratory experiments. The 3-D digital geometry obtained by tomographic scans was used in direct pore-level numerical simulations to determine the effective transport properties. The results showed that isothermal advection with saturated air have no influence...

  2. Monitoring snow-cover area change in Antarctic coastline region using MODIS product data

    Institute of Scientific and Technical Information of China (English)

    Chen Jing; Li Rendong; Ye Ming; Lu Yang

    2009-01-01

    Based on MODIS snow products, this article studied the changes of snow cover area during 2003-2006 along the coastline of the Antarctic, and 18 typical regions were chosen for further analysis. The result showed that the change of snow cover area was in a fluctuant downward trend as a whole, and more fluctuated obviously in warm season than in cold season. In temporal scale: for the season cycle, the snow cover extent increased rapidly in cold season (Apr-Oct), while the performance in warm season (Nov-Mar) was not exactly the same during the four years, the snow cover extent decreased in the first and then increased in 2004 and 2006, however, increased firstly and then decreased but reduced as a whole in 2005, for the inter-annual cycle, snow cover extent was the largest in 2003, but reached to the lowest level in 2004, and then increased gradually in 2005 and 2006, whereas, it declined with fluctuant as a whole. In spatial scale, changes mainly centralized along the coastline, moreover, it was more remarkable in the West Antarctic than in the East Antarctic, especially in the Antarctic Peninsula region.

  3. Catchment-scale evaluation of pollution potential of urban snow at two residential catchments in southern Finland.

    Science.gov (United States)

    Sillanpää, Nora; Koivusalo, Harri

    2013-01-01

    Despite the crucial role of snow in the hydrological cycle in cold climate conditions, monitoring studies of urban snow quality often lack discussions about the relevance of snow in the catchment-scale runoff management. In this study, measurements of snow quality were conducted at two residential catchments in Espoo, Finland, simultaneously with continuous runoff measurements. The results of the snow quality were used to produce catchment-scale estimates of areal snow mass loads (SML). Based on the results, urbanization reduced areal snow water equivalent but increased pollutant accumulation in snow: SMLs in a medium-density residential catchment were two- to four-fold higher in comparison with a low-density residential catchment. The main sources of pollutants were related to vehicular traffic and road maintenance, but also pet excrement increased concentrations to a high level. Ploughed snow can contain 50% of the areal pollutant mass stored in snow despite its small surface area within a catchment.

  4. Developing Snow Model Forcing Data From WRF Model Output to Aid in Water Resource Forecasting

    Science.gov (United States)

    Havens, S.; Marks, D. G.; Watson, K. A.; Masarik, M.; Flores, A. N.; Kormos, P.; Hedrick, A. R.

    2015-12-01

    Traditional operational modeling tools used by water managers in the west are challenged by more frequently occurring uncharacteristic stream flow patterns caused by climate change. Water managers are now turning to new models based on the physical processes within a watershed to combat the increasing number of events that do not follow the historical patterns. The USDA-ARS has provided near real time snow water equivalent (SWE) maps using iSnobal since WY2012 for the Boise River Basin in southwest Idaho and since WY2013 for the Tuolumne Basin in California that feeds the Hetch Hetchy reservoir. The goal of these projects is to not only provide current snowpack estimates but to use the Weather Research and Forecasting (WRF) model to drive iSnobal in order to produce a forecasted stream flow when coupled to a hydrology model. The first step is to develop methods on how to create snow model forcing data from WRF outputs. Using a reanalysis 1km WRF dataset from WY2009 over the Boise River Basin, WRF model results like surface air temperature, relative humidity, wind, precipitation, cloud cover, and incoming long wave radiation must be downscaled for use in iSnobal. iSnobal results forced with WRF output are validated at point locations throughout the basin, as well as compared with iSnobal results forced with traditional weather station data. The presentation will explore the differences in forcing data derived from WRF outputs and weather stations and how this affects the snowpack distribution.

  5. Informing Water Management by Direct Use of Snow Information as Surrogate of Medium-to-Long Range Streamflow Forecast

    Science.gov (United States)

    Denaro, S.; Giuliani, M.; Castelletti, A.

    2014-12-01

    Medium-to-long range streamflow forecast provide a key assistance in anticipating hydro- climatic adverse events and prompting effective adaptation measures. For instance, accurate medium-long range streamflow forecasts have a great potential to improve water reservoir operation by enabling more efficient allocation of water volumes in time (e.g. via hedging). Unfortunately, these forecasts often lacks reliability and accuracy, especially when low-frequency climate forcing (e.g. ENSO) is not intense enough to improve the forecast lead time (e.g. in Europe), and might be computationally very demanding, In this work, we explore the direct use of both rough snow data (e.g. snow depth) and snow water equivalent estimates as surrogate of medium-to-long range streamflow forecast to inform the operation of a regulated lake. The underlying idea is that snow data contains key information on current and future water availability throughout the snow melting season that might significantly improve the operation's anticipation potential. We adopt a three step methodology: First, we compute the upper bound of the system performance by assuming perfect foresight and we assess the value of additional information as the difference between this ideal solution and current operation. Using input variable selection, we then select the most relevant snow information to explain the release trajectory associated to the upper bound operating policy. Finally, we derive the optimal policy conditioned upon the selected variables by Multi-Objecting Evolutionary Direct Policy Search. The methodology is demonstrated on the snow-dominated Lake Como river basin, in the Italian Alps. Lake Como is a regulated lake primarily used to supply water to a large cultivated area and snowmelt from May-July is the most important contribution to the creation of the seasonal storage. Results show that using raw data or simple SWE estimates can largely improve anticipation capability in the daily operation of

  6. Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models

    Science.gov (United States)

    Terzago, Silvia; von Hardenberg, Jost; Palazzi, Elisa; Provenzale, Antonello

    2017-07-01

    The estimate of the current and future conditions of snow resources in mountain areas would require reliable, kilometre-resolution, regional-observation-based gridded data sets and climate models capable of properly representing snow processes and snow-climate interactions. At the moment, the development of such tools is hampered by the sparseness of station-based reference observations. In past decades passive microwave remote sensing and reanalysis products have mainly been used to infer information on the snow water equivalent distribution. However, the investigation has usually been limited to flat terrains as the reliability of these products in mountain areas is poorly characterized.This work considers the available snow water equivalent data sets from remote sensing and from reanalyses for the greater Alpine region (GAR), and explores their ability to provide a coherent view of the snow water equivalent distribution and climatology in this area. Further we analyse the simulations from the latest-generation regional and global climate models (RCMs, GCMs), participating in the Coordinated Regional Climate Downscaling Experiment over the European domain (EURO-CORDEX) and in the Fifth Coupled Model Intercomparison Project (CMIP5) respectively. We evaluate their reliability in reproducing the main drivers of snow processes - near-surface air temperature and precipitation - against the observational data set EOBS, and compare the snow water equivalent climatology with the remote sensing and reanalysis data sets previously considered. We critically discuss the model limitations in the historical period and we explore their potential in providing reliable future projections.The results of the analysis show that the time-averaged spatial distribution of snow water equivalent and the amplitude of its annual cycle are reproduced quite differently by the different remote sensing and reanalysis data sets, which in fact exhibit a large spread around the ensemble mean. We

  7. Gridded Snow Water Equivalent Reconstruction for Utah Using Forest Inventory and Analysis Tree-Ring Data

    Directory of Open Access Journals (Sweden)

    Daniel Barandiaran

    2017-06-01

    Full Text Available Snowpack observations in the Intermountain West are sparse and short, making them difficult for use in depicting past variability and extremes. This study presents a reconstruction of April 1 snow water equivalent (SWE for the period of 1850–1989 using increment cores collected by the U.S. Forest Service, Interior West Forest Inventory and Analysis program (FIA. In the state of Utah, SWE was reconstructed for 38 snow course locations using a combination of standardized tree-ring indices derived from both FIA increment cores and publicly available tree-ring chronologies. These individual reconstructions were then interpolated to a 4-km grid using an objective analysis with elevation correction to create an SWE product. The results showed a significant correlation with observed SWE as well as good correspondence to regional tree-ring-based drought reconstructions. Diagnostic analysis showed statewide coherent climate variability on inter-annual and inter-decadal time-scales, with added geographical details that would not be possible using courser pre-instrumental proxy datasets. This SWE reconstruction provides water resource managers and forecasters with better spatial resolution to examine past variability in snowpack, which will be important as future hydroclimatic variability is amplified by climate change.

  8. Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models

    Directory of Open Access Journals (Sweden)

    S. Terzago

    2017-07-01

    Full Text Available The estimate of the current and future conditions of snow resources in mountain areas would require reliable, kilometre-resolution, regional-observation-based gridded data sets and climate models capable of properly representing snow processes and snow–climate interactions. At the moment, the development of such tools is hampered by the sparseness of station-based reference observations. In past decades passive microwave remote sensing and reanalysis products have mainly been used to infer information on the snow water equivalent distribution. However, the investigation has usually been limited to flat terrains as the reliability of these products in mountain areas is poorly characterized.This work considers the available snow water equivalent data sets from remote sensing and from reanalyses for the greater Alpine region (GAR, and explores their ability to provide a coherent view of the snow water equivalent distribution and climatology in this area. Further we analyse the simulations from the latest-generation regional and global climate models (RCMs, GCMs, participating in the Coordinated Regional Climate Downscaling Experiment over the European domain (EURO-CORDEX and in the Fifth Coupled Model Intercomparison Project (CMIP5 respectively. We evaluate their reliability in reproducing the main drivers of snow processes – near-surface air temperature and precipitation – against the observational data set EOBS, and compare the snow water equivalent climatology with the remote sensing and reanalysis data sets previously considered. We critically discuss the model limitations in the historical period and we explore their potential in providing reliable future projections.The results of the analysis show that the time-averaged spatial distribution of snow water equivalent and the amplitude of its annual cycle are reproduced quite differently by the different remote sensing and reanalysis data sets, which in fact exhibit a large spread around

  9. A drought index accounting for snow

    Science.gov (United States)

    Staudinger, Maria; Stahl, Kerstin; Seibert, Jan

    2015-04-01

    The Standardized Precipitation Index (SPI) is the most widely used index to characterize and monitor droughts that are related to precipitation deficiencies. However, the SPI does not always deliver the relevant information for hydrological drought management when precipitation deficiencies are not the only reason for droughts as it is the case for example in snow influenced catchments. If precipitation is temporarily stored as snow, then there is a significant difference between meteorological and hydrological drought because the delayed release of melt water from the snow accumulation to the stream. In this study we introduce an extension to the SPI, the Standardized Snow Melt and Rain Index (SMRI), that captures both rain and snow melt deficits, which in effect modify streamflow. The SMRI does not require any snow data instead observations of temperature and precipitation are used to model snow. The SMRI is evaluated for seven Swiss catchments with varying degrees of snow influence. In particular for catchments with a larger component of snowmelt in runoff generation, we found the SMRI to be a good complementary index to the SPI to describe streamflow droughts. In a further step, the SPI and the SMRI were compared for the summer drought of 2003 and the spring drought of 2011 for Switzerland, using gridded products of precipitation and temperature including the entire country.

  10. A new web-based system to improve the monitoring of snow avalanche hazard in France

    Science.gov (United States)

    Bourova, Ekaterina; Maldonado, Eric; Leroy, Jean-Baptiste; Alouani, Rachid; Eckert, Nicolas; Bonnefoy-Demongeot, Mylene; Deschatres, Michael

    2016-05-01

    Snow avalanche data in the French Alps and Pyrenees have been recorded for more than 100 years in several databases. The increasing amount of observed data required a more integrative and automated service. Here we report the comprehensive web-based Snow Avalanche Information System newly developed to this end for three important data sets: an avalanche chronicle (Enquête Permanente sur les Avalanches, EPA), an avalanche map (Carte de Localisation des Phénomènes d'Avalanche, CLPA) and a compilation of hazard and vulnerability data recorded on selected paths endangering human settlements (Sites Habités Sensibles aux Avalanches, SSA). These data sets are now integrated into a common database, enabling full interoperability between all different types of snow avalanche records: digitized geographic data, avalanche descriptive parameters, eyewitness reports, photographs, hazard and risk levels, etc. The new information system is implemented through modular components using Java-based web technologies with Spring and Hibernate frameworks. It automates the manual data entry and improves the process of information collection and sharing, enhancing user experience and data quality, and offering new outlooks to explore and exploit the huge amount of snow avalanche data available for fundamental research and more applied risk assessment.

  11. Impact of intra- versus inter-annual snow depth variation on water relations and photosynthesis for two Great Basin Desert shrubs.

    Science.gov (United States)

    Loik, Michael E; Griffith, Alden B; Alpert, Holly; Concilio, Amy L; Wade, Catherine E; Martinson, Sharon J

    2015-06-01

    Snowfall provides the majority of soil water in certain ecosystems of North America. We tested the hypothesis that snow depth variation affects soil water content, which in turn drives water potential (Ψ) and photosynthesis, over 10 years for two widespread shrubs of the western USA. Stem Ψ (Ψ stem) and photosynthetic gas exchange [stomatal conductance to water vapor (g s), and CO2 assimilation (A)] were measured in mid-June each year from 2004 to 2013 for Artemisia tridentata var. vaseyana (Asteraceae) and Purshia tridentata (Rosaceae). Snow fences were used to create increased or decreased snow depth plots. Snow depth on +snow plots was about twice that of ambient plots in most years, and 20 % lower on -snow plots, consistent with several down-scaled climate model projections. Maximal soil water content at 40- and 100-cm depths was correlated with February snow depth. For both species, multivariate ANOVA (MANOVA) showed that Ψ stem, g s, and A were significantly affected by intra-annual variation in snow depth. Within years, MANOVA showed that only A was significantly affected by spatial snow depth treatments for A. tridentata, and Ψ stem was significantly affected by snow depth for P. tridentata. Results show that stem water relations and photosynthetic gas exchange for these two cold desert shrub species in mid-June were more affected by inter-annual variation in snow depth by comparison to within-year spatial variation in snow depth. The results highlight the potential importance of changes in inter-annual variation in snowfall for future shrub photosynthesis in the western Great Basin Desert.

  12. Calibration of a non-invasive cosmic-ray probe for wide area snow water equivalent measurement

    Science.gov (United States)

    Sigouin, Mark J. P.; Si, Bing C.

    2016-06-01

    Measuring snow water equivalent (SWE) is important for many hydrological purposes such as modelling and flood forecasting. Measurements of SWE are also crucial for agricultural production in areas where snowmelt runoff dominates spring soil water recharge. Typical methods for measuring SWE include point measurements (snow tubes) and large-scale measurements (remote sensing). We explored the potential of using the cosmic-ray soil moisture probe (CRP) to measure average SWE at a spatial scale between those provided by snow tubes and remote sensing. The CRP measures above-ground moderated neutron intensity within a radius of approximately 300 m. Using snow tubes, surveys were performed over two winters (2013/2014 and 2014/2015) in an area surrounding a CRP in an agricultural field in Saskatoon, Saskatchewan, Canada. The raw moderated neutron intensity counts were corrected for atmospheric pressure, water vapour, and temporal variability of incoming cosmic-ray flux. The mean SWE from manually measured snow surveys was adjusted for differences in soil water storage before snowfall between both winters because the CRP reading appeared to be affected by soil water below the snowpack. The SWE from the snow surveys was negatively correlated with the CRP-measured moderated neutron intensity, giving Pearson correlation coefficients of -0.90 (2013/2014) and -0.87 (2014/2015). A linear regression performed on the manually measured SWE and moderated neutron intensity counts for 2013/2014 yielded an r2 of 0.81. Linear regression lines from the 2013/2014 and 2014/2015 manually measured SWE and moderated neutron counts were similar; thus differences in antecedent soil water storage did not appear to affect the slope of the SWE vs. neutron relationship. The regression equation obtained from 2013/2014 was used to model SWE using the moderated neutron intensity data for 2014/2015. The CRP-estimated SWE for 2014/2015 was similar to that of the snow survey, with an root

  13. DIRECT IMAGING OF THE WATER SNOW LINE AT THE TIME OF PLANET FORMATION USING TWO ALMA CONTINUUM BANDS

    Energy Technology Data Exchange (ETDEWEB)

    Banzatti, A.; Pontoppidan, K. M. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Pinilla, P. [Leiden Observatory, Leiden University, P.O. Box 9513, 2300RA Leiden (Netherlands); Ricci, L.; Birnstiel, T. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Ciesla, F., E-mail: banzatti@stsci.edu [Department of the Geophysical Sciences, The University of Chicago, 5734 South Ellis Avenue, Chicago, IL 60637 (United States)

    2015-12-10

    Molecular snow lines in protoplanetary disks have been studied theoretically for decades because of their importance in shaping planetary architectures and compositions. The water snow line lies in the planet formation region at ≲10 AU, and so far its location has been estimated only indirectly from spatially unresolved spectroscopy. This work presents a proof-of-concept method to directly image the water snow line in protoplanetary disks through its physical and chemical imprint on the local dust properties. We adopt a physical disk model that includes dust coagulation, fragmentation, drift, and a change in fragmentation velocities of a factor of 10 between dry silicates and icy grains as found by laboratory work. We find that the presence of a water snow line leads to a sharp discontinuity in the radial profile of the dust emission spectral index α{sub mm} due to replenishment of small grains through fragmentation. We use the ALMA simulator to demonstrate that this effect can be observed in protoplanetary disks using spatially resolved ALMA images in two continuum bands. We explore the model dependence on the disk viscosity and find that the spectral index reveals the water snow line for a wide range of conditions, with opposite trends when the emission is optically thin rather than thick. If the disk viscosity is low (α{sub visc} < 10{sup −3}), the snow line produces a ringlike structure with a minimum at α{sub mm} ∼ 2 in the optically thick regime, possibly similar to what has been measured with ALMA in the innermost region of the HL Tau disk.

  14. Direct Imaging of the Water Snow Line at the Time of Planet Formation using Two ALMA Continuum Bands

    Science.gov (United States)

    Banzatti, A.; Pinilla, P.; Ricci, L.; Pontoppidan, K. M.; Birnstiel, T.; Ciesla, F.

    2015-12-01

    Molecular snow lines in protoplanetary disks have been studied theoretically for decades because of their importance in shaping planetary architectures and compositions. The water snow line lies in the planet formation region at ≲10 AU, and so far its location has been estimated only indirectly from spatially unresolved spectroscopy. This work presents a proof-of-concept method to directly image the water snow line in protoplanetary disks through its physical and chemical imprint on the local dust properties. We adopt a physical disk model that includes dust coagulation, fragmentation, drift, and a change in fragmentation velocities of a factor of 10 between dry silicates and icy grains as found by laboratory work. We find that the presence of a water snow line leads to a sharp discontinuity in the radial profile of the dust emission spectral index αmm due to replenishment of small grains through fragmentation. We use the ALMA simulator to demonstrate that this effect can be observed in protoplanetary disks using spatially resolved ALMA images in two continuum bands. We explore the model dependence on the disk viscosity and find that the spectral index reveals the water snow line for a wide range of conditions, with opposite trends when the emission is optically thin rather than thick. If the disk viscosity is low (αvisc < 10-3), the snow line produces a ringlike structure with a minimum at αmm ˜ 2 in the optically thick regime, possibly similar to what has been measured with ALMA in the innermost region of the HL Tau disk.

  15. Optical Thickness and Effective Radius Retrievals of Liquid Water Clouds over Ice and Snow Surface

    Science.gov (United States)

    Platnick, S.; King, M. D.; Tsay, S.-C.; Arnold, G. T.; Gerber, H.; Hobbs, P. V.; Rangno, A.

    1999-01-01

    Cloud optical thickness and effective radius retrievals from solar reflectance measurements traditionally depend on a combination of spectral channels that are absorbing and non-absorbing for liquid water droplets. Reflectances in non-absorbing channels (e.g., 0.67, 0.86 micrometer bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2.1, and 3.7 micrometer window bands) provide cloud particle size information. Retrievals are complicated by the presence of an underlying ice/snow surface. At the shorter wavelengths, sea ice is both bright and highly variable, significantly increasing cloud retrieval uncertainty. However, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. Sea ice spectral albedos derived from Cloud Absorption Radiometer (CAR) measurements during April 1992 and June 1995 Arctic field deployments are used to illustrate these statements. A modification to the traditional retrieval technique is devised. The new algorithm uses a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, preliminary retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 during FIRE-ACE. Data from coordinated ER-2 and University of Washington CV-580 aircraft observations of liquid water stratus clouds on June 3 and June 6, 1998 have been examined. Size retrievals are compared with in situ cloud profile measurements of effective radius made with the CV-580 PMS FSSP probe, and optical thickness retrievals are compared with extinction profiles derived from the Gerber Scientific "g-meter" probe. MAS retrievals are shown to be in good agreement with the in situ measurements.

  16. An assessment of two automated snow water equivalent instruments during the WMO Solid Precipitation Intercomparison Experiment

    Science.gov (United States)

    Smith, Craig D.; Kontu, Anna; Laffin, Richard; Pomeroy, John W.

    2017-01-01

    During the World Meteorological Organization (WMO) Solid Precipitation Intercomparison Experiment (SPICE), automated measurements of snow water equivalent (SWE) were made at the Sodankylä (Finland), Weissfluhjoch (Switzerland) and Caribou Creek (Canada) SPICE sites during the northern hemispheric winters of 2013/14 and 2014/15. Supplementary intercomparison measurements were made at Fortress Mountain (Kananaskis, Canada) during the 2013/14 winter. The objectives of this analysis are to compare automated SWE measurements with a reference, comment on their performance and, where possible, to make recommendations on how to best use the instruments and interpret their measurements. Sodankylä, Caribou Creek and Fortress Mountain hosted a Campbell Scientific CS725 passive gamma radiation SWE sensor. Sodankylä and Weissfluhjoch hosted a Sommer Messtechnik SSG1000 snow scale. The CS725 operating principle is based on measuring the attenuation of soil emitted gamma radiation by the snowpack and relating the attenuation to SWE. The SSG1000 measures the mass of the overlying snowpack directly by using a weighing platform and load cell. Manual SWE measurements were obtained at the intercomparison sites on a bi-weekly basis over the accumulation-ablation periods using bulk density samplers. These manual measurements are considered to be the reference for the intercomparison. Results from Sodankylä and Caribou Creek showed that the CS725 generally overestimates SWE as compared to manual measurements by roughly 30-35 % with correlations (r2) as high as 0.99 for Sodankylä and 0.90 for Caribou Creek. The RMSE varied from 30 to 43 mm water equivalent (mm w.e.) and from 18 to 25 mm w.e. at Sodankylä and Caribou Creek, which had respective SWE maximums of approximately 200 and 120 mm w.e. The correlation at Fortress Mountain was 0.94 (RMSE of 48 mm w.e. with a maximum SWE of approximately 650 mm w.e.) with no systematic overestimation. The SSG1000 snow scale, having a different

  17. Observing snow cover using unmanned aerial vehicle

    Science.gov (United States)

    Spallek, Waldemar; Witek, Matylda; Niedzielski, Tomasz

    2016-04-01

    Snow cover is a key environmental variable that influences high flow events driven by snow-melt episodes. Estimates of snow extent (SE), snow depth (SD) and snow water equivalent (SWE) allow to approximate runoff caused by snow-melt episodes. These variables are purely spatial characteristics, and hence their pointwise measurements using terrestrial monitoring systems do not offer the comprehensive and fully-spatial information on water storage in snow. Existing satellite observations of snow reveal moderate spatial resolution which, not uncommonly, is not fine enough to estimate the above-mentioned snow-related variables for small catchments. High-resolution aerial photographs and the resulting orthophotomaps and digital surface models (DSMs), obtained using unmanned aerial vehicles (UAVs), may offer spatial resolution of 3 cm/px. The UAV-based observation of snow cover may be done using the near-infrared (NIR) cameras and visible-light cameras. Since the beginning of 2015, in frame of the research project no. LIDER/012/223/L-5/13/NCBR/2014 financed by the National Centre for Research and Development of Poland, we have performed a series of the UAV flights targeted at four sites in the Kwisa catchment in the Izerskie Mts. (part of the Sudetes, SW Poland). Observations are carried out with the ultralight UAV swinglet CAM (produced by senseFly, lightweight 0.5 kg, wingspan 80 cm) which enables on-demand sampling at low costs. The aim of the field work is to acquire aerial photographs taken using the visible-light and NIR cameras for a purpose of producing time series of DSMs and orthophotomaps with snow cover for all sites. The DSMs are used to calculate SD as difference between observational (with snow) and reference (without snow) models. In order to verify such an approach to compute SD we apply several procedures, one of which is the estimation of SE using the corresponding orthophotomaps generated on a basis of visual-light and NIR images. The objective of this

  18. Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

    Science.gov (United States)

    Ehrlich, André; Bierwirth, Eike; Istomina, Larysa; Wendisch, Manfred

    2017-09-01

    The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff

  19. Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

    Directory of Open Access Journals (Sweden)

    A. Ehrlich

    2017-09-01

    Full Text Available The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow. Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C.In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S, λ2 = 1650 nm (sensitive to τ, and λ3 = 2100 nm (sensitive to reff, C are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012 were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice

  20. Application of radar polarimetry techniques for retrieval snow and rain characteristics in remote sensing

    Science.gov (United States)

    Darvishi, M.; Ahmadi, Gh. R.

    2013-09-01

    The presence of snow cover has significant impacts on the both global and regional climate and water balance on earth. The accurate estimation of snow cover area can be used for forecasting runoff due to snow melt and output of hydroelectric power. With development of remote sensing techniques at different scopes in earth science, enormous algorithms for retrieval hydrometeor parameters have been developed. Some of these algorithms are used to provide snow cover map such as NLR with AVHRR/MODIS sensor for Norway, Finnish with AVHRR sensor for Finland and NASA with MODIS sensor for global maps. Monitoring snow cover at different parts of spectral electromagnetic is detectable (visible, near and thermal infrared, passive and active microwave). Recently, specific capabilities of active microwave remote sensing such as snow extent map, snow depth, snow water equivalent (SWE), snow state (wet/dry) and discrimination between rain and snow region were given a strong impetus for using this technology in snow monitoring, hydrology, climatology, avalanche research and etc. This paper evaluates the potentials and feasibility of polarimetric ground microwave measurements of snow in active remote sensing field. We will consider the behavior co- and cross-polarized backscattering coefficients of snowpack response with polarimetric scatterometer in Ku and L band at the different incident angles. Then we will show how to retrieve snow cover depth, snow permittivity and density parameters at the local scale with ground-based SAR (GB-SAR). Finally, for the sake of remarkable significant the transition region between rain and snow; the variables role of horizontal reflectivity (ZHH) and differential reflectivity (ZDR) in delineation boundary between snow and rain and some others important variables at polarimetric weather radar are presented.

  1. Application of radar polarimetry techniques for retrieval snow and rain characteristics in remote sensing

    Directory of Open Access Journals (Sweden)

    M. Darvishi

    2013-09-01

    Full Text Available The presence of snow cover has significant impacts on the both global and regional climate and water balance on earth. The accurate estimation of snow cover area can be used for forecasting runoff due to snow melt and output of hydroelectric power. With development of remote sensing techniques at different scopes in earth science, enormous algorithms for retrieval hydrometeor parameters have been developed. Some of these algorithms are used to provide snow cover map such as NLR with AVHRR/MODIS sensor for Norway, Finnish with AVHRR sensor for Finland and NASA with MODIS sensor for global maps. Monitoring snow cover at different parts of spectral electromagnetic is detectable (visible, near and thermal infrared, passive and active microwave. Recently, specific capabilities of active microwave remote sensing such as snow extent map, snow depth, snow water equivalent (SWE, snow state (wet/dry and discrimination between rain and snow region were given a strong impetus for using this technology in snow monitoring, hydrology, climatology, avalanche research and etc. This paper evaluates the potentials and feasibility of polarimetric ground microwave measurements of snow in active remote sensing field. We will consider the behavior co- and cross-polarized backscattering coefficients of snowpack response with polarimetric scatterometer in Ku and L band at the different incident angles. Then we will show how to retrieve snow cover depth, snow permittivity and density parameters at the local scale with ground-based SAR (GB-SAR. Finally, for the sake of remarkable significant the transition region between rain and snow; the variables role of horizontal reflectivity (ZHH and differential reflectivity (ZDR in delineation boundary between snow and rain and some others important variables at polarimetric weather radar are presented.

  2. Vertical distribution and diel vertical migration of krill beneath snow-covered ice and in ice-free waters

    KAUST Repository

    Vestheim, Hege

    2013-11-11

    A bottom mounted upward looking Simrad EK60 120-kHz echo sounder was used to study scattering layers (SLs) and individuals of the krill Meganyctiphanes norvegica. The mooring was situated at 150-m depth in the Oslofjord, connected with an onshore cable for power and transmission of digitized data. Records spanned 5 months from late autumn to spring. A current meter and CTD was associated with the acoustic mooring and a shore-based webcam monitored ice conditions in the fjord. The continuous measurements were supplemented with intermittent krill sampling campaigns and their physical and biological environment.The krill carried out diel vertical migration (DVM) throughout the winter, regardless of the distribution of potential prey. The fjord froze over in mid-winter and the daytime distribution of a mid-water SL of krill immediately became shallower associated with snow fall after freezing, likely related to reduction of light intensities. Still, a fraction of the population always descended all the way to the bottom, so that the krill population by day seemed to inhabit waters with light levels spanning up to six orders of magnitude. Deep-living krill ascended in synchrony with the rest of the population in the afternoon, but individuals consistently reappeared in near-bottom waters already? 1 h after the ascent. Thereafter, the krill appeared to undertake asynchronous migrations, with some krill always being present in near-bottom waters even though the entire population appeared to undertake DVM. The Author 2013. Published by Oxford University Press. All rights reserved.

  3. Direct imaging of the water snow line at the time of planet formation using two ALMA continuum bands

    CERN Document Server

    Banzatti, Andrea; Ricci, Luca; Pontoppidan, Klaus M; Birnstiel, Til; Ciesla, Fred

    2015-01-01

    Molecular snow lines in protoplanetary disks have been studied theoretically for decades because of their importance in shaping planetary architectures and compositions. The water snow line lies in the planet formation region at < 10 AU, and so far its location has been estimated only indirectly from spatially-unresolved spectroscopy. This work presents a proof-of-concept method to directly image the water snow line in protoplanetary disks through its physical and chemical imprint in the local dust properties. We adopt a physical disk model that includes dust coagulation, fragmentation, drift, and a change in fragmentation velocities of a factor 10 between dry silicates and icy grains as found by laboratory work. We find that the presence of a water snow line leads to a sharp discontinuity in the radial profile of the dust emission spectral index {\\alpha}_mm, due to replenishment of small grains through fragmentation. We use the ALMA simulator to demonstrate that this effect can be observed in protoplaneta...

  4. TLS monitoring of snowpack distribution in a mountain forested areas: Analysis of canopy disturbance on snow evolution.

    Science.gov (United States)

    Revuelto, Jesús; López-Moreno, Juan Ignacio; Azorin-Molina, Cesar; Alonso, Esteban; San Miguel, Alba

    2016-04-01

    Forested mountain areas at high elevations show important interaction with snowpack distribution and its evolution in time, and thus in many cases are the limit of the cryosphere in mountain zones. Such interactions have significant consequences in the hydrologic response of mountain rivers. Thereby observing the evolution of snowpack in forested areas has a big importance form a basic science perspective and also for water management. This work presents a detailed comparison of small scale effect of forest characteristics on snowpack distribution in Central Pyrenees, before and after a strong modification of canopies features. The snowpack distribution has been obtained using a novel remote sensing technology (Terrestrial Laser Scanner, TLS), with high spatial resolution (0.25m) over a 1000m2 study area for 27 survey dates along three snow seasons. Between the second and the third snow season a strong canopy pruning was performed in the study site, and thereby the snowpack evolution with both canopy configurations was compared. A Principal Component Analysis has been applied to analyze the snowpack distributions observed during the study period. Results obtained have shown that despite large differences in Canopy radius (1.2 m) and Canopy height (2.5m), not a different snowpack evolution was observed. For both Canopy configurations the variable with higher importance on snowpack distribution is the snow depth amount. The change in forest structure has important implications in the decrease of Canopy areas and the increase of Open areas (proportionally to Canopy change), but not a different interaction with forest structure was observed. The canopy pruning realized in the study site is typically accomplished for fire risk reduction and this shows the consequences that such action has in snowpack distribution and that hereby these may have in water management possibly delaying peak runoff.

  5. Snow measurement system for airborne snow surveys (GPR system from helicopter) in high mountian areas.

    Science.gov (United States)

    Sorteberg, Hilleborg K.

    2010-05-01

    In the hydropower industry, it is important to have precise information about snow deposits at all times, to allow for effective planning and optimal use of the water. In Norway, it is common to measure snow density using a manual method, i.e. the depth and weight of the snow is measured. In recent years, radar measurements have been taken from snowmobiles; however, few energy supply companies use this method operatively - it has mostly been used in connection with research projects. Agder Energi is the first Norwegian power producer in using radar tecnology from helicopter in monitoring mountain snow levels. Measurement accuracy is crucial when obtaining input data for snow reservoir estimates. Radar screening by helicopter makes remote areas more easily accessible and provides larger quantities of data than traditional ground level measurement methods. In order to draw up a snow survey system, it is assumed as a basis that the snow distribution is influenced by vegetation, climate and topography. In order to take these factors into consideration, a snow survey system for fields in high mountain areas has been designed in which the data collection is carried out by following the lines of a grid system. The lines of this grid system is placed in order to effectively capture the distribution of elevation, x-coordinates, y-coordinates, aspect, slope and curvature in the field. Variation in climatic conditions are also captured better when using a grid, and dominant weather patterns will largely be captured in this measurement system.

  6. Seasonal ERT monitoring of subsurface processes connected to freezing, thawing, snow accumulation and melt cycles

    Science.gov (United States)

    Krzeminska, Dominika; Starkloff, Torsten; Bloem, Esther; Stolte, Jannes

    2016-04-01

    For a better understanding of processes that influence snowmelt infiltration and runoff, and their consequences on soil erosion during spring periods, we established a long-term winter-spring ERT transect in the Gryteland catchment (Norway). The ERT transect is 71 m long, with 1 m spacing between the electrodes. It covers a depression with a north and south facing slope. The readings are collected once a week and, if needed, after a sudden change in weather conditions. Additionally, the soil transect is equipped with six TDR profiles, which register soil moisture and soil temperature every thirty minutes, at five depths (5, 10, 20, 30, 40 cm), for quantifying the ERT readings. The measurements performed during winter 2014/2015 gave promising results and showed the potential of ERT monitoring for understanding the soil thermal and hydraulic processes occurring during a winter and early spring. Moreover, there are visible differences in temporal trends and spatial variations in observed ERT patterns on the opposite facing slopes, which are of special interest. With the on-going experiment, we are aiming to understand the reoccurrence of the observed processes as well as to quantify soil moisture patterns. Herein, we would like to present the preliminary result of two ERT experiments (2014/2015 and 2015/2016) and discuss the advantages and limitations of our experiments. Moreover, we would like to stimulate the discussion about the potential of ERT for spatial and temporal monitoring of soil hydraulic and thermal processes and indirect measurements of soil water content.

  7. Seasonal and interannual variations in snow cover thickness, water equivalent, and gravity-induced dynamics in a high Arctic valley glacier watershed.

    Science.gov (United States)

    Tolle, F.; Prokop, A.; Bernard, É.; Friedt, J. M.; Griselin, M.

    2014-12-01

    For 3 consecutive years, terrestrial laser scanning surveys have been conducted in the glacier basin of Austre Lovénbreen (Svalbard, 79°N). Each year, high density point clouds were acquired on the glacier surface and on the surrounding slopes. Two yearly scanning sessions were required in order to spatialize and quantify snow cover. The first session was done late April at the expected annual snow maximum. The second session was done in August near the end of the melting season and before the first potential significant snow falls. On the glacier itself, laser scans were produced on the glacier snout, in the area close to the equilibrium line, and in the upper reaches of the glacier. Manual snow drilling measurements and glacier mass balance data were subsequently used to validate snow cover results. In the steep slopes surrounding the glacier, scans were acquired on slopes at various altitudes and orientations in order to get a representative view of different snow cover settings. Particular attention was granted to snowdrift and avalanche processes, and their consequences on remaining packed snow stored in perennial snow accumulation at the bottom of slopes. A good knowledge of the dynamics of the snow cover is of particular interest in a glacier undergoing a clear retreat. Snow is slowing the melting of the ice for part of the season, and snow is also providing what will constitute future glacier ice in the upper reaches of the basin. Snow on slopes is also of importance as avalanches reaching on the glacier can contribute to the overall mass balance. Snow cover, by keeping the slopes permafrost from thawing early in the season, or by providing liquid water affecting it later in the season, is also playing a key role in the glacier basin morphology and its interactions with the glacier body.

  8. A coupled melt-freeze temperature index approach in a one-layer model to predict bulk volumetric liquid water content dynamics in snow

    Science.gov (United States)

    Avanzi, Francesco; Yamaguchi, Satoru; Hirashima, Hiroyuki; De Michele, Carlo

    2016-04-01

    Liquid water in snow rules runoff dynamics and wet snow avalanches release. Moreover, it affects snow viscosity and snow albedo. As a result, measuring and modeling liquid water dynamics in snow have important implications for many scientific applications. However, measurements are usually challenging, while modeling is difficult due to an overlap of mechanical, thermal and hydraulic processes. Here, we evaluate the use of a simple one-layer one-dimensional model to predict hourly time-series of bulk volumetric liquid water content in seasonal snow. The model considers both a simple temperature-index approach (melt only) and a coupled melt-freeze temperature-index approach that is able to reconstruct melt-freeze dynamics. Performance of this approach is evaluated at three sites in Japan. These sites (Nagaoka, Shinjo and Sapporo) present multi-year time-series of snow and meteorological data, vertical profiles of snow physical properties and snow melt lysimeters data. These data-sets are an interesting opportunity to test this application in different climatic conditions, as sites span a wide latitudinal range and are subjected to different snow conditions during the season. When melt-freeze dynamics are included in the model, results show that median absolute differences between observations and predictions of bulk volumetric liquid water content are consistently lower than 1 vol%. Moreover, the model is able to predict an observed dry condition of the snowpack in 80% of observed cases at a non-calibration site, where parameters from calibration sites are transferred. Overall, the analysis show that a coupled melt-freeze temperature-index approach may be a valid solution to predict average wetness conditions of a snow cover at local scale.

  9. Temporal monitoring of the soil freeze-thaw cycles over snow-cover land by using off-ground GPR

    KAUST Repository

    Jadoon, Khan

    2013-07-01

    We performed off-ground ground-penetrating radar (GPR) measurements over a bare agricultural field to monitor the freeze-thaw cycles over snow-cover. The GPR system consisted of a vector network analyzer combined with an off-ground monostatic horn antenna, thereby setting up an ultra-wideband stepped-frequency continuous-wave radar. Measurements were performed during nine days and the surface of the bare soil was exposed to snow fall, evaporation and precipitation as the GPR antenna was mounted 110 cm above the ground. Soil surface dielectric permittivity was retrieved using an inversion of time-domain GPR data focused on the surface reflection. The GPR forward model used combines a full-waveform solution of Maxwell\\'s equations for three-dimensional wave propagation in planar layered media together with global reflection and transmission functions to account for the antenna and its interactions with the medium. Temperature and permittivity sensors were installed at six depths to monitor the soil dynamics in the top 8 cm depth. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and permittivity data and in particular freeze and thaw events were clearly visible. A good agreement of the trend was observed between the temperature, permittivity and GPR time-lapse data with respect to five freeze-thaw cycles. The GPR-derived permittivity was in good agreement with sensor observations. The proposed method appears to be promising for the real-time mapping and monitoring of the frozen layer at the field scale. © 2013 IEEE.

  10. A synthesis of atmospheric mercury depletion event chemistry linking atmosphere, snow and water

    Directory of Open Access Journals (Sweden)

    A. Steffen

    2007-07-01

    Full Text Available It was discovered in 1995 that, during the spring time, unexpectedly low concentrations of gaseous elemental mercury (GEM occurred in the Arctic air. This was surprising for a pollutant known to have a long residence time in the atmosphere; however conditions appeared to exist in the Arctic that promoted this depletion of mercury (Hg. This phenomenon is termed atmospheric mercury depletion events (AMDEs and its discovery has revolutionized our understanding of the cycling of Hg in Polar Regions while stimulating a significant amount of research to understand its impact to this fragile ecosystem. Shortly after the discovery was made in Canada, AMDEs were confirmed to occur throughout the Arctic, sub-Artic and Antarctic coasts. It is now known that, through a series of photochemically initiated reactions involving halogens, GEM is converted to a more reactive species and is subsequently associated to particles in the air and/or deposited to the polar environment. AMDEs are a means by which Hg is transferred from the atmosphere to the environment that was previously unknown. In this article we review the history of Hg in Polar Regions, the methods used to collect Hg in different environmental media, research results of the current understanding of AMDEs from field, laboratory and modeling work, how Hg cycles around the environment after AMDEs, gaps in our current knowledge and the future impacts that AMDEs may have on polar environments. The research presented has shown that while considerable improvements in methodology to measure Hg have been made the main limitation remains knowing the speciation of Hg in the various media. The processes that drive AMDEs and how they occur are discussed. As well, the roles that the snow pack, oceans, fresh water and the sea ice play in the cycling of Hg are presented. It has been found that deposition of Hg from AMDEs occurs at marine coasts and not far inland and that a fraction of the deposited Hg does not

  11. Climate change impact assessment on mountain snow hydrology by water and energy budget-based distributed hydrological model

    Science.gov (United States)

    Bhatti, Asif M.; Koike, Toshio; Shrestha, Maheswor

    2016-12-01

    A water and energy budget-based distributed hydrological model with improved snow physics (WEB-DHM-S) was applied to elucidate the impact of climate change on mountain snow hydrology in the Shubuto River basin, Hokkaido, Japan. The simulated spatial distribution of snow cover was evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day maximum snow-cover extent (MOD10A2) product, which revealed the model's capability for capturing the spatiotemporal variations in snow cover within the study area. Four Atmosphere Ocean General Circulation Models (AOGCMs) were selected and the SRESA1B emission scenario of the Intergovernmental Panel on Climate Change was used to describe climate predictions in the basin. All AOGCMs predict a future decrease in snowmelt contribution to total discharge 11-22% and an average decrease in SWE of 36%, with a shift in peak SWE by 4-14 days. The shift in runoff regime is broadly consistent between the AOGCMs with snowmelt-induced peak discharge expected to occur on average about two weeks earlier in the future hydrological year. The warming climate will drive a shift in runoff regime from a combined rainfall- and snowmelt-driven regime to one with a reduced contribution from snowmelt. The results of the study revealed that the model could be successfully applicable on the basin scale to simulate river discharge and snow processes and to investigate the effect of climate change on hydrological processes. This research contributes to improve the understanding of basin hydrological responses and the pace of change associated with climate variability.

  12. Evaluation of snow cover and snow depth on the Qinghai-Tibetan Plateau derived from passive microwave remote sensing

    Science.gov (United States)

    Dai, Liyun; Che, Tao; Ding, Yongjian; Hao, Xiaohua

    2017-08-01

    Snow cover on the Qinghai-Tibetan Plateau (QTP) plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW) remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow depth across the QTP, new algorithms

  13. Evaluation of snow cover and snow depth on the Qinghai–Tibetan Plateau derived from passive microwave remote sensing

    Directory of Open Access Journals (Sweden)

    L. Dai

    2017-08-01

    Full Text Available Snow cover on the Qinghai–Tibetan Plateau (QTP plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow

  14. Polymer microcantilevers for water quality monitoring

    CSIR Research Space (South Africa)

    Ojijo, Vincent O

    2012-10-01

    Full Text Available The microcantilever project aims to develop novel polymer based microcantilevers able to detect E.coli in water samples for use as a rapid diagnostic for on-site water quality monitoring....

  15. Assimilation of Terrestrial Water Storage from GRACE in a Snow-Dominated Basin

    Science.gov (United States)

    Forman, Barton A.; Reichle, R. H.; Rodell, M.

    2011-01-01

    Terrestrial water storage (TWS) information derived from Gravity Recovery and Climate Experiment (GRACE) measurements is assimilated into a land surface model over the Mackenzie River basin located in northwest Canada. Assimilation is conducted using an ensemble Kalman smoother (EnKS). Model estimates with and without assimilation are compared against independent observational data sets of snow water equivalent (SWE) and runoff. For SWE, modest improvements in mean difference (MD) and root mean squared difference (RMSD) are achieved as a result of the assimilation. No significant differences in temporal correlations of SWE resulted. Runoff statistics of MD remain relatively unchanged while RMSD statistics, in general, are improved in most of the sub-basins. Temporal correlations are degraded within the most upstream sub-basin, but are, in general, improved at the downstream locations, which are more representative of an integrated basin response. GRACE assimilation using an EnKS offers improvements in hydrologic state/flux estimation, though comparisons with observed runoff would be enhanced by the use of river routing and lake storage routines within the prognostic land surface model. Further, GRACE hydrology products would benefit from the inclusion of better constrained models of post-glacial rebound, which significantly affects GRACE estimates of interannual hydrologic variability in the Mackenzie River basin.

  16. Geophysical investigations of underplating at the Middle American Trench, weathering in the critical zone, and snow water equivalent in seasonal snow

    Science.gov (United States)

    St. Clair, James

    indicate that to a first order, the permeability structure of the CZ can be predicted with knowledge of the regional tectonic stress field and local topography. In landscapes characterized by strongly compressive tectonic stresses or closely space ridges and valleys, deep zones of permeable bedrock are found beneath ridges, while the depth to impermeable bedrock beneath drainages is comparatively shallow. In landscapes characterized by weakly compressive tectonic stresses or widely spaced ridges and valleys, the depth to impermeable bedrock is approximately uniform throughout the landscape. In Chapter 3, a semi-automated method of estimating snow water equivalent (SWE) in seasonal snow packs from common offset Ground Penetrating Radar (GPR) data is presented. Many mountainous regions of the world depend on seasonal snow for fresh water resources. Water forecasting relies principally on historical records that relate SWE observations at a limited number of locations to stream discharge. As climate change contributes to a wider range of variability in seasonal snow fall, water forecasts are likely to become less reliable, thus there is a need to find new methods of estimating how much water is stored in seasonal snow. GPR has been shown to be an effective tool for measuring SWE if the radar velocity can be measured. In this chapter, a method that was originally developed to measure seismic velocities from zero-offset seismic reflection data is applied to common-offset GPR data collected over seasonal snow. The method involves suppressing continuous reflections in the image so that the velocity information contained in diffracted energy can be exploited. The filtered images are migrated through a suite of velocities and the velocity that best focus the diffracted energy is chosen on the basis of the varimax norm, which measures how peaked the energy distribution is. GPR derived SWE estimates agree with manual measurements within the uncertainty bounds of both methods. In

  17. Environmental Monitoring, Water Quality - MO 2009 Stream Team Volunteer Water Quality Monitoring Sites (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set shows the monitoring locations of trained Volunteer Water Quality Monitors. A monitoring site is considered to be a 300 foot section of stream channel....

  18. Environmental Monitoring, Water Quality - MO 2009 Stream Team Volunteer Water Quality Monitoring Sites (SHP)

    Data.gov (United States)

    NSGIC State | GIS Inventory — This data set shows the monitoring locations of trained Volunteer Water Quality Monitors. A monitoring site is considered to be a 300 foot section of stream channel....

  19. Iowater Water Quality Monitoring Sites

    Data.gov (United States)

    Iowa State University GIS Support and Research Facility — This coverage contains points representing monitoring locations on streams, lakes and ponds that have been registered by IOWATER monitors. IOWATER, Iowa's volunteer...

  20. A snow cover climatology for the Pyrenees from MODIS snow products

    Science.gov (United States)

    Gascoin, S.; Hagolle, O.; Huc, M.; Jarlan, L.; Dejoux, J.-F.; Szczypta, C.; Marti, R.; Sanchez, R.

    2015-05-01

    The seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations, satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (w.e.) and 150 mm, respectively, for both MOD10A1 and MYD10A1. κ coefficients are within 0.74 and 0.92 depending on the product and the variable for these thresholds. However, we also find a seasonal trend in the optimal SWE and SD thresholds, reflecting the hysteresis in the relationship between the depth of the snowpack (or SWE) and its extent within a MODIS pixel. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97% (κ = 0.85) for MOD10A1 and 96% (κ = 0.81) for MYD10A1, which indicates a good agreement between both data sets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decrease over the forests but the agreement remains acceptable (MOD10A1: 96%, κ = 0.77; MYD10A1: 95%, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gap-filling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band and aspect classes. There is snow on the ground at least 50% of the

  1. Hydrochemistry of snow and glacier-fed surface waters in the Gokyo Valley, Nepal: A Pre and Post Earthquake Assessment

    Science.gov (United States)

    Khan, A. L.; McKnight, D. M.; Williams, M. W.; Armstrong, R. L.

    2016-12-01

    To investigate the impacts of the 2015 earthquakes on water quality and resources in the Gokyo Valley, drinking water samples were collected in the Khumbu region of Nepal in early 2016 and compared to baseline data from November 2012. This study was part of a larger USAID funded project housed at the National Snow and Ice Data Center to understand Contributions to High Asian Run-off from Ice and Snow (CHARIS) which has more than 10 local partners across 8 countries in High Asia. The Gokyo Valley is home to the Ngozumba Glacier and the Gokyo Lakes, which serve as the headwaters to the Dudh Koshi River. Samples were collected from tributary streams, which serve as the local drinking water sources and contribute to the Dudh Koshi watershed, along a transect from Lukla, 9181 ft, to Gokyo, 15, 557 ft. Water samples were analyzed in the field with the Aquagenx, Compartment Bag Test, a low cost method to detect E.coli, an indicator bacteria of fecal contamination. E.coli was present at the lowest elevations. Water samples were also shipped back to CU-Boulder for further chemical analysis including dissolved organic carbon (DOC), total dissolved nitrogen (TDN), arsenic, and oxygen isotopes to identify changes in hydrologic flow paths. These samples are being analyzed over the summer of 2016. Snow samples were also collected along a transect from Namche Bazaar at 11,657 ft to Gokyo Ri at 17,500 ft and have been analyzed for refractory black carbon (rBC). In general, rBC concentrations decreased with increasing elevation, except near local point-sources. Impurities like these reduce surface albedo and increase the amount of solar radiation absorbed by snow/ice, leading to enhanced melt.

  2. Per- and polyfluoroalkyl substances in snow, lake, surface runoff water and coastal seawater in Fildes Peninsula, King George Island, Antarctica.

    Science.gov (United States)

    Cai, Minghong; Yang, Haizhen; Xie, Zhiyong; Zhao, Zhen; Wang, Feng; Lu, Zhibo; Sturm, Renate; Ebinghaus, Ralf

    2012-03-30

    The multi-matrices samples from snow (n=4), lake water (n=4), surface runoff water (SRW) (n=1) and coastal seawater (n=10) were collected to investigate the spatial distribution and the composition profiles of per- and polyfluoroalkyl substances (PFASs) in Fildes Peninsula, King George Island, Antarctica in 2011. All samples were prepared by solid-phase extraction and analyzed by using high performance liquid chromatography/negative electrospray ionization-tandem mass spectrometry (HPLC/(-)ESI-MS/MS). 14 PFASs in snow, 12 PFASs in lake water, 9 PFASs in SRW and 13 PFASs in coastal seawater were quantified, including C(4), C(7), C(8), C(10) PFSAs, C(4)-C(9), C(11)-C(14), C(16) PFCAs, and FOSA. PFOA was detected in all samples with the highest concentration (15,096 pg/L) in coastal seawater indicating a possible influence of local sewage effluent. High concentration and mostly frequency of PFBA occurred in snow (up to 1112 pg/L), lake water (up to 2670 pg/L) and SRW (1431 pg/L) while detected in the range of method detection limited (MDL) in the coastal seawaters indicate that PFBA is mainly originated from atmospheric dust contamination and also affected by the degradation of their precursors. No geographical differences in PFOS concentrations (n=8, 18 ± 3 pg/L) were measured in all snow and lake water samples also suggests that PFOS could be originated from the degradation of their precursors which can transported by long-range atmospheric route, but in a very low level.

  3. Use of time series of optical and SAR images in the estimation of snow cover for the optimization of water use in the Andes of Argentina and Chile

    Science.gov (United States)

    Salinas de Salmuni, Graciela; Cabezas Cartes, Ricardo; Menicocci, Felix

    2014-05-01

    This paper describes the progress in the bilateral cooperation project between academic and water resources management institutions from the Andes region of Argentina and Chile. The study zone is located in fragile ecosystems and mountain areas of the Andes (limit zone between the Province of San Juan, Argentina, and the IV Region of Coquimbo, Chile), with arid climate, where snow precipitates in the headwaters of watershed feed the rivers of the region by melting, which are the only source of water for human use, productive and energetic activities, as well as the native flora and fauna. CONAE, the Argentine Space Agency, participates in the Project through the provision of satellite data to the users and by this it contributes to ensuring the continuity of the results of the project. Also, it provides training in digital image processing. The project also includes the participation of water resource management institutions like Secretaria de Recursos Hidricos of Argentina and the Centro de Información de Recursos Naturales de Chile (CIREN), and of academic institution like the University of San Juan (Argentina) and University of La Serena (Chile). These institutions benefit from the incorporation of new methodologies advanced digital image processing and training of staff (researcher, lecturers, PhD Students and technical). Objectives: 1-Improve water distribution incorporating space technology for application in the prediction models of the stream flow. 2- Conduct an inventory of glaciers as well as studies in selected watersheds in the Andean region, aiming to know the water resource, its availability and potential risks to communities in the region. 3. Contribute to vulnerability studies in biodiversity Andean watersheds. Results: For estimation Snow cover Area, the MODIS images are appropriate due their high temporal resolution and allows for monitoring large areas (greater than 10 km) The proposed methodology (Use of snow index, NSDI) is appropriate for

  4. Snow Extent Variability in Lesotho Derived from MODIS Data (2000–2014

    Directory of Open Access Journals (Sweden)

    Stefan Wunderle

    2016-05-01

    Full Text Available In Lesotho, snow cover is not only highly relevant to the climate system, but also affects socio-economic factors such as water storage for irrigation or hydro-electricity. However, while sound knowledge of annual and inter-annual snow dynamics is strongly required by local stakeholders, in-situ snow information remains limited. In this study, satellite data are used to generate a time series of snow cover and to provide the missing information on a national scale. A snow retrieval method, which is based on MODIS data and considers the concept of a normalized difference snow index (NDSI, has been implemented. Monitoring gaps due to cloud cover are filled by temporal and spatial post-processing. The comparison is based on the use of clear sky reference images from Landsat-TM and ENVISAT-MERIS. While the snow product is considered to be of good quality (mean accuracy: 68%, a slight bias towards snow underestimation is observed. Based on the daily product, a consistent time series of snow cover for Lesotho from 2000–2014 was generated for the first time. Analysis of the time series showed that the high annual variability of snow coverage and the short duration of single snow events require daily monitoring with a gap-filling procedure.

  5. Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model

    Science.gov (United States)

    De Lannoy, Gabrielle J.M.; Reichle, Rolf H.; Houser, Paul R.; Arsenault, Kristi R.; Verhoest, Niko E.C.; Paulwels, Valentijn R.N.

    2009-01-01

    An ensemble Kalman filter (EnKF) is used in a suite of synthetic experiments to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of satellite retrievals) into fine-scale (1 km) model simulations. Coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (re-gridding) to the fine-scale model resolution prior to data assimilation. In either case observations are assimilated either simultaneously or independently for each location. Results indicate that assimilating disaggregated fine-scale observations independently (method 1D-F1) is less efficient than assimilating a collection of neighboring disaggregated observations (method 3D-Fm). Direct assimilation of coarse-scale observations is superior to a priori disaggregation. Independent assimilation of individual coarse-scale observations (method 3D-C1) can bring the overall mean analyzed field close to the truth, but does not necessarily improve estimates of the fine-scale structure. There is a clear benefit to simultaneously assimilating multiple coarse-scale observations (method 3D-Cm) even as the entire domain is observed, indicating that underlying spatial error correlations can be exploited to improve SWE estimates. Method 3D-Cm avoids artificial transitions at the coarse observation pixel boundaries and can reduce the RMSE by 60% when compared to the open loop in this study.

  6. Artificial neural network coupled with wavelet transform for estimating snow water equivalent using passive microwave data

    Indian Academy of Sciences (India)

    A B Dariane; S Azimi; A Zakerinej

    2014-10-01

    Snow Water Equivalent (SWE) is an important parameter in hydrologic engineering involving the stream-flow forecasting of high-elevation watersheds. In this paper, the application of classic Artificial Neural Network model (ANN) and a hybrid model combining the wavelet and ANN (WANN) is investigated in estimating the value of SWE in a mountainous basin. In addition, k-fold cross validation method is used in order to achieve a more reliable and robust model. In this regard, microwave images acquired from Spectral Sensor Microwave Imager (SSM/I) are used to estimate the SWE of Tehran sub-basins during 1992–2008 period. Also for obtaining measured SWE within the corresponding Equal-Area Scalable Earth-Grid (EASE-Grid) cell of SSM/I image, approach of Cell-SWE extraction using height–SWE relations is applied in order to reach more precise estimations. The obtained results reveal that the wavelet-ANN model significantly increases the accuracy of estimations, mainly because of using multi-scale time series as the ANN inputs. The Nash–Sutcliffe Index (NSE) for ANN and WANN models is respectively 0.09 and 0.44 which shows a firm improvement of 0.35 in NSE parameter when WANN is applied. Similar trend is observed in other parameters including RMSE where the value is 0.3 for ANN and 0.07 for WANN.

  7. Integrated Modeling and Decision-Support System for Water Management in the Puget Sound Basin: Snow Caps to White Caps

    Energy Technology Data Exchange (ETDEWEB)

    Copping, Andrea E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Yang, Zhaoqing [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Voisin, Nathalie [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Richey, Jeff [Univ. of Washington, Seattle, WA (United States); Wang, Taiping [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Taira, Randal Y. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Constans, Michael [Univ. of Washington, Seattle, WA (United States); Wigmosta, Mark S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Van Cleve, Frances B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Tesfa, Teklu K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2013-12-01

    Final Report for the EPA-sponsored project Snow Caps to White Caps that provides data products and insight for water resource managers to support their predictions and management actions to address future changes in water resources (fresh and marine) in the Puget Sound basin. This report details the efforts of a team of scientists and engineers from Pacific Northwest National Laboratory (PNNL) and the University of Washington (UW) to examine the movement of water in the Snohomish Basin, within the watershed and the estuary, under present and future conditions, using a set of linked numerical models.

  8. Integrated Modeling and Decision-Support System for Water Management in the Puget Sound Basin: Snow Caps to White Caps

    Energy Technology Data Exchange (ETDEWEB)

    Copping, Andrea E.; Yang, Zhaoqing; Voisin, Nathalie; Richey, Jeff; Wang, Taiping; Taira, Randal Y.; Constans, Michael; Wigmosta, Mark S.; Van Cleve, Frances B.; Tesfa, Teklu K.

    2013-12-31

    Final Report for the EPA-sponsored project Snow Caps to White Caps that provides data products and insight for water resource managers to support their predictions and management actions to address future changes in water resources (fresh and marine) in the Puget Sound basin. This report details the efforts of a team of scientists and engineers from Pacific Northwest National Laboratory (PNNL) and the University of Washington (UW) to examine the movement of water in the Snohomish Basin, within the watershed and the estuary, under present and future conditions, using a set of linked numerical models.

  9. Long-term monitoring of fecal steroid hormones in female snow leopards (Panthera uncia during pregnancy or pseudopregnancy.

    Directory of Open Access Journals (Sweden)

    Kodzue Kinoshita

    Full Text Available Knowledge of the basic reproductive physiology of snow leopards is required urgently in order to develop a suitable management conditions under captivity. In this study, the long-term monitoring of concentrations of three steroid hormones in fecal matter of three female snow leopards was performed using enzyme immunoassays: (1 estradiol-17β, (2 progesterone and (3 cortisol metabolite. Two of the female animals were housed with a male during the winter breeding season, and copulated around the day the estradiol-17β metabolite peaked subsequently becoming pregnant. The other female was treated in two different ways: (1 first housed with a male in all year round and then (2 in the winter season only. She did not mate with him on the first occasion, but did so latter around when estradiol-17β metabolite peaked, and became pseudopregnant. During pregnancy, progesterone metabolite concentrations increased for 92 or 94 days, with this period being approximately twice as long as in the pseudopregnant case (31, 42, 49 and 53 days. The levels of cortisol metabolite in the pseudopregnant female (1.35 µg/g were significantly higher than in the pregnant females (0.33 and 0.24 µg/g (P<0.05. Similarly, during the breeding season, the levels of estradiol-17β metabolite in the pseudopregnant female (2.18 µg/g were significantly higher than those in the pregnant females (0.81 and 0.85 µg/g (P<0.05. Unlike cortisol the average levels of estradiol-17β during the breeding season were independent of reproductive success.The hormone levels may also be related to housing conditions and the resulting reproductive success in female leopards. The female housed with a male during the non-breeding season had high levels of cortisol metabolites and low levels of estradiol-17β in the breeding season, and failed to become pregnant. This indicates that housing conditions in snow leopards may be an important factor for normal endocrine secretion and resulting breeding

  10. Global Public Water Education: The World Water Monitoring Day Experience

    Science.gov (United States)

    Araya, Yoseph Negusse; Moyer, Edward H.

    2006-01-01

    Public awareness of the impending world water crisis is an important prerequisite to create a responsible citizenship capable of participating to improve world water management. In this context, the case of a unique global water education outreach exercise, World Water Monitoring Day of October 18, is presented. Started in 2002 in the United…

  11. Water Quality Monitoring by Satellite

    Science.gov (United States)

    Journal of Chemical Education, 2004

    2004-01-01

    The availability of abundant water resources in the Upper Midwest of the United States is nullified by their contamination through heavy commercial and industrial activities. Scientists have taken the responsibility of detecting the water quality of these resources through remote-sensing satellites to develop a wide-ranging water purification plan…

  12. Ground-Water Protection and Monitoring Program

    Energy Technology Data Exchange (ETDEWEB)

    Dresel, P.E.

    1995-06-01

    This section of the 1994 Hanford Site Environmental Report summarizes the ground-water protection and monitoring program strategy for the Hanford Site in 1994. Two of the key elements of this strategy are to (1) protect the unconfined aquifer from further contamination, and (2) conduct a monitoring program to provide early warning when contamination of ground water does occur. The monitoring program at Hanford is designed to document the distribution and movement of existing ground-water contamination and provides a historical baseline for evaluating current and future risk from exposure to the contamination and for deciding on remedial action options.

  13. The value of data availability versus model complexity to estimate snow, glacier and rain water in mountain streams

    Science.gov (United States)

    Finger, David; Vis, Marc; Seibert, Jan

    2014-05-01

    The contribution of snow, glacier and rainwater to runoff in mountain streams is of major importance for water resources managers as climate change is expected to impact on all three sources (e.g. Huss, 2012). While glaciers are retreating worldwide, the snow cover during winter becomes shorter and precipitations events become more intense (e.g. Finger et al., 2012). Besides field investigation such as chemical fingerprints in water samples and artificial tracer experiments (e.g. Finger et al., 2013), the contribution of snow, glacier and rain can also be estimated with hydrological models, given that the modeling accounts adequately for snow-, glacier and rainwater runoff (Finger et al., 2011). We present a multi-variable calibration technique to estimate runoff composition using the conceptual HBV-light model (Seibert and Vis, 2012). The model code was extended to allow calibration and validation of simulations against glacier mass balances and satellite derived snow cover area, in addition to the usual comparison against measured discharge. We tested the value of these additional data sets on three meso-scale catchments in Switzerland: i) Rhoneglacier (39km2; ~50% glaciation), ii) Hinterrhein (53km2; ~17% glaciation) and iii) Silvretta glacier (103km2; ~8% glaciation). We also compared the results to a similar study performed with a physically based, fully distributed hydrological model (Finger et al., 2011). Preliminary results indicate that all three observational datasets are reproduced adequately by the model, allowing an accurate estimation of the runoff composition in the three mountain streams. However, the use of runoff alone to calibrate the model leads to unrealistic snow- and glacier melt, expressed by a low overall model performance. These results are in line with previous studies carried out with a more complex, physically based fully distributed hydrological model (Finger et al. 2011). Based on these results we conclude that it is essential to use

  14. Environmental monitoring of Norwegian water resources

    Energy Technology Data Exchange (ETDEWEB)

    Tollan, A.

    1980-01-01

    A national environmental monitoring program was started in Norway in 1980, under the auspices of the Norwegian State Pollution Control Authority. Within this program The Norwegian Institute for Water Research is responsible for: (1) Chemical and biological monitoring of selected rivers and fjord areas. Typically, the monitoring of a particular river or fjord starts with a basic investigation of 1-3 years, comprising physiography, human impacts on the water quality and a broad description of the present water quality status. This stage is followed by a permanent monitoring of carefully selected variables at a limited number of stations. Special water quality problems may be studied separately. (2) Participation in a coordinated monitoring of long-range transported atmospheric pollution, and its effects on water chemistry, aquatic life and soil properties. (3) Methodological development, standardization of analytical procedures and evaluation techniques for water quality assessment, and assistance as a national reference laboratory for water analyses. (4) Depository for environmental data collected within the national monitoring program.

  15. Value of seasonal flow forecast to reservoir operation for water supply in snow-dominated catchments

    Science.gov (United States)

    Anghileri, Daniela; Voisin, Nathalie; Castelletti, Andrea; Pianosi, Francesca; Nijssen, Bart; Lettenmaier, Dennis

    2014-05-01

    The recursive application of forecasting and optimization can make management strategies more flexible and efficient by improving the potential for anticipating, and thus adapting, to adverse events. In the field of reservoir operation, this means enriching the information base on which release decisions are made. At a minimum, this includes the available reservoir storage, but reservoir management can greatly benefit from consideration of other pieces of information as, for instance, weather and flow forecasts. However, the utility or value of inflow forecasts is directly related to forecast quality. In this work, we focus on snow-dominated water resource systems, where the prediction of the volume and timing of snowmelt can greatly enhance the operational performance. We use the Oroville-Thermalito reservoir complex in the Feather River Basin, California, as a case study to explore the effect of forecast quality on optimal release strategies. We use Deterministic Dynamic Programming to optimize medium-range and seasonal reservoir operation based on different forecasts of reservoir inflows. We determine maximum reservoir operation performance by forcing the optimization with observed inflows, which is equivalent to a perfect forecast. The forecast quality is then progressively degraded to relate forecast skill to changes in release decisions and to determine the minimum forecast skill that is required to affect decision-making. We generate forecasted inflow sequences using the Variable Infiltration Capacity (VIC) hydrology model. Forecast initial conditions are created using observed meteorology, while inflow forecasts are based on seasonal climate forecasts. Although the forecast skill level is specific to the Feather River basin, the methodology should be transferable to other systems with strong seasonal runoff regimes. We assess the transferability of the case study results to other systems using alternative reservoir characteristics of the Oroville

  16. ESCIMO.spread – a spreadsheet-based point snow surface energy balance model to calculate hourly snow water equivalent and melt rates for historical and changing climate conditions

    Directory of Open Access Journals (Sweden)

    T. Marke

    2010-05-01

    Full Text Available This paper describes the spreadsheet-based point energy balance model ESCIMO.spread which simulates the energy and mass balance as well as melt rates of a snow surface. The model makes use of hourly recordings of temperature, precipitation, wind speed, relative humidity, global and longwave radiation. The effect of potential climate change on the seasonal evolution of the snow cover can be estimated by modifying the time series of observed temperature and precipitation by means of adjustable parameters. Model output is graphically visualized in hourly and daily diagrams. The results compare well with weekly measured snow water equivalent (SWE. The model is easily portable and adjustable, and runs particularly fast: hourly calculation of a one winter season is instantaneous on a standard computer. ESICMO.spread can be obtained from the authors on request (contact: ulrich.strasser@uni-graz.at.

  17. R2 Water Quality Portal Monitoring Stations

    Science.gov (United States)

    The Water Quality Data Portal (WQP) provides an easy way to access data stored in various large water quality databases. The WQP provides various input parameters on the form including location, site, sampling, and date parameters to filter and customize the returned results. The The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA) and the National Water Quality Monitoring Council (NWQMC) that integrates publicly available water quality data from the USGS National Water Information System (NWIS) the EPA STOrage and RETrieval (STORET) Data Warehouse, and the USDA ARS Sustaining The Earth??s Watersheds - Agricultural Research Database System (STEWARDS).

  18. Water Pollution: Monitoring the Source.

    Science.gov (United States)

    Wilkes, James W.

    1980-01-01

    Described is an advanced biology class project involving study of the effects of organic pollution on an aquatic ecosystem from an sewage treatment plant overflow to evaluate the chemical quality and biological activity of the river water. (DS)

  19. Surface Water Quality Monitoring Sites

    Data.gov (United States)

    Minnesota Department of Natural Resources — The MN Department of Agriculture (MDA) is charged with periodically collecting and analyzing water samples from selected locations throughout the state to determine...

  20. ASAR analysis of the snow cover in Livingston and Deception Islands.

    Science.gov (United States)

    Mora, C.; Vieira, G.; Ramos, M.

    2009-04-01

    ASAR images from Envisat are analyzed to study the snow cover regime of Deception and Livingston Islands (South Sthetlands, Antarctic Peninsula). Data is provided by the European Space Agency in the framework of the Proposal Category-1: Snow cover characteristics and regime in the South Shetlands (Maritime Antarctic) - SnowAntar. Medium resolution images (WSW, APM and IMM) are analyzed since December 2008, and are prepared using the processing chains from BEST (Basic Envisat SAR Toolbox). The process includes the transformation of DN into power values, geometric and radiometric correction, image filtering and computation of the backscattering coefficient for each pixel. Thereafter, the imagery is analyzed in image analysis software for the classification of backscattering. A multitemporal imagery analysis is conducted in order to set a threshold on the differential backscatter between scenes under wet snow and snow free-conditions. These algorithms allow for the study of snow surface wetness and snow water equivalent. The study of snow cover regime is linked to the permafrost monitoring and modeling effort conducted in the region in the framework of the PERMANTAR-PERMAMODEL projects. The proprieties of snow are of major significance for the ground energy balance and therefore to the ground thermal regime, since thick snow provides excellent insulation. Permafrost is therefore influenced by snow cover properties, spatial distribution and regime. Snow cover maps will be produced for integration in permafrost modeling and also for comparison with re-analysis data from ERA-Interim. The poster presents the first results of the imagery analysis of the snow cover regime since December 2008. The satellite data is validated in the field with several areas of interest (AOI) with snow thickness monitoring devices based on thermal regimes at different heights.

  1. Design of a scanning laser meter for monitoring the spatio-temporal evolution of snow depth and its application in the Alps and in Antarctica

    Science.gov (United States)

    Picard, Ghislain; Arnaud, Laurent; Panel, Jean-Michel; Morin, Samuel

    2016-07-01

    Although both the temporal and spatial variations of the snow depth are usually of interest for numerous applications, available measurement techniques are either space-oriented (e.g. terrestrial laser scans) or time-oriented (e.g. ultrasonic ranging probe). Because of snow heterogeneity, measuring depth in a single point is insufficient to provide accurate and representative estimates. We present a cost-effective automatic instrument to acquire spatio-temporal variations of snow depth. The device comprises a laser meter mounted on a 2-axis stage and can scan ≈ 200 000 points over an area of 100-200 m2 in 4 h. Two instruments, installed in Antarctica (Dome C) and the French Alps (Col de Porte), have been operating continuously and unattended over 2015 with a success rate of 65 and 90 % respectively. The precision of single point measurements and long-term stability were evaluated to be about 1 cm and the accuracy to be 5 cm or better. The spatial variability in the scanned area reached 7-10 cm (root mean square) at both sites, which means that the number of measurements is sufficient to average out the spatial variability and yield precise mean snow depth. With such high precision, it was possible for the first time at Dome C to (1) observe a 3-month period of regular and slow increase of snow depth without apparent link to snowfalls and (2) highlight that most of the annual accumulation stems from a single event although several snowfall and strong wind events were predicted by the ERA-Interim reanalysis. Finally the paper discusses the benefit of laser scanning compared to multiplying single-point sensors in the context of monitoring snow depth.

  2. 40 CFR 141.701 - Source water monitoring.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Source water monitoring. 141.701... Monitoring Requirements § 141.701 Source water monitoring. (a) Initial round of source water monitoring... sampling frequency is evenly spaced throughout the monitoring period. (b) Second round of source water...

  3. Impact of Snow Melt Water on Aalfalfa Sseedlings%雪水对苜蓿幼苗的影响

    Institute of Scientific and Technical Information of China (English)

    曲善民; 刘艾; 杜广明; 李建英; 李国良; 杨智明; 鞠晓峰

    2012-01-01

    采用盆钵垂直板法,研究了清水和雪水对紫花苜蓿在幼苗生长过程中的影响,对两组苜蓿幼苗的株高、根长、茎粗、物质积累等指标进行了对比分析。结果表明:雪水处理组的苜蓿幼苗生长状态明显优于清水处理组,发芽率较对照平均高出28.26%,株高、茎粗、干物质积累均显著高于对照(P〈5%),根长与对照相比较无显著差异(P〉5%),雪水对苜蓿幼苗生长具有显著促进效应。建议:在农业生产中,广泛应用雪水促进牧草饲料作物增产丰收,尤其雪水浸种对改善作物苗期的生长势效果明显。%The paper have Separately studied the influnce of running water and snow melt water on alfalfa in seedling growth process, adopting the basin-port vertical slab method,and carries out a comparative analysis of two groups of alfalfa seedlings height, root length,stem diameter,matter accumulation of such indicators.To alfalfa seedlings growth state,results show that snow water treatment group obviously superior water treatment groups,high 28.26% than the average.Stem diameter,dry matter accumulation were significantly higher than controls(p5%),compared with controls for root no significant difference(p5%),snow melt water to alfalfa seedlings significantly promote effect.Suggestion: the wide applications on pasture feed will promote increasing harvest in the agricultural production,especially with snow smelt water soaked seeds,to improve crop seedling growth vigour influnce is obvious.

  4. High Impedance Comparator for Monitoring Water Resistivity.

    Science.gov (United States)

    Holewinski, Paul K.

    1984-01-01

    A high-impedance comparator suitable for monitoring the resistivity of a deionized or distilled water line supplying water in the 50 Kohm/cm-2 Mohm/cm range is described. Includes information on required circuits (with diagrams), sensor probe assembly, and calibration techniques. (JN)

  5. MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.

    2010-01-01

    Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

  6. Design of an optimal snow observation network to estimate snowpack

    Science.gov (United States)

    Juan Collados Lara, Antonio; Pardo-Iguzquiza, Eulogio; Pulido-Velazquez, David

    2016-04-01

    Snow is an important water resource in many river basins that must be taken into account in hydrological modeling. Although the snow cover area may be nowadays estimated from satellite data, the snow pack thickness must be estimated from experimental data by using some interpolation procedure or hydrological models that approximates snow accumulation and fusion processes. The experimental data consist of hand probes and snow samples collected in a given number of locations that constitute the monitoring network. Assuming that there is an existing monitoring network, its optimization may imply the selection of an optimal network as a subset of the existing network (decrease of the existing network in the case that there are no funds for maintaining the full existing network) or to increase the existing network by one or more stations (optimal augmentation problem). In this work we propose a multicriterion approach for the optimal design of a snow network. These criteria include the estimation variance from a regression kriging approach for estimating thickness of the snowpack (using ground and satellite data), to minimize the total snow volume and accessibility criteria. We have also proposed a procedure to analyze the sensitivity of the results to the non-snow data deduced from the satellite information. We intent to minimize the uncertities in snowpack estimation. The methodology has been applied to estimation of the snow cover area and the design of the optimal snow observation network in Sierra Nevada mountain range in the Southern of Spain. Acknowledgments: This research has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank ERHIN program and NASA DAAC for the data provided for this study.

  7. Water isotope variations in the snow pack and summer precipitation at July 1 Glacier, Qilian Mountains in northwest China

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper presents the stable isotope data of the snow pack and summer precipitation collected at the July 1 Glacier, Qilian Mountains in northwest China and analyses their relationships with meteorological factors. On an event scale, there is no temperature effect on the δ18O values in the summer precipitation, whereas the amount effect is shown to be clear. By tracing the moisture transport history and comparing the precipitation with its isotopic composition, it is shown that this amount effect not only reflects the change in moisture trajectory, which is related to the monsoon activities, but is also associated with the cooling degree of vapor in the cloud, the evaporation of falling raindrops and the isotopic exchange between the falling drops and the atmospheric vapor. As very little precipitation occurs in winter, the snow pack profile mainly represents the precipitation in the other three seasons. There are low precipitation δ18O ratios in summer and high ratios in spring and autumn. The Meteoric Water Line (MLW) for the summer precipitation is δD = 7.6 δ18O + 13.3, which is similar to that at Delingha, located in the south rim of the Qilian Mountains. The MWL for the snow pack is δD = 10.4 δ18O + 41.4, showing a large slope and intercept. The deuterium excess (d) of the snow pack is positively correlated with δ18O, indicating that both d and δ18O decrease from spring to summer and increase from early autumn to early spring. This then results in the high slope and intercept of the MWL. Seasonal fluctuations of d in the snow pack indicate the change of moisture source and trajectory. During spring and autumn, the moisture originates from continental recycling or rapid evaporation over relatively warm water bodies like Black, Caspian and Aral Seas when the dry westerly air masses pass over them, hence very high d values in precipitation are formed. During summer, the monsoon is responsible for the low d values. This indicates that the monsoon can

  8. 40 CFR 265.91 - Ground-water monitoring system.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 25 2010-07-01 2010-07-01 false Ground-water monitoring system. 265.91... DISPOSAL FACILITIES Ground-Water Monitoring § 265.91 Ground-water monitoring system. (a) A ground-water monitoring system must be capable of yielding ground-water samples for analysis and must consist of: (1...

  9. Monitoring Telluric Water Absorption with CAMAL

    Science.gov (United States)

    Baker, Ashley; Blake, Cullen; Sliski, David

    2017-01-01

    Ground-based observations are severely limited by telluric water vapor absorption features, which are highly variable in time and significantly complicate both spectroscopy and photometry in the near-infrared (NIR). To achieve the stability required to study Earth-sized exoplanets, monitoring the precipitable water vapor (PWV) becomes necessary to mitigate the impact of telluric lines on radial velocity measurements and transit light curves. To address this issue, we present the Camera for the Automatic Monitoring of Atmospheric Lines (CAMAL), a stand-alone, inexpensive 6-inch aperture telescope dedicated to measuring PWV at the Whipple Observatory. CAMAL utilizes three NIR narrowband filters to trace the amount of atmospheric water vapor affecting simultaneous observations with the MINiature Exoplanet Radial Velocity Array (MINERVA) and MINERVA-Red telescopes. We present the current design of CAMAL, discuss our calibration methods, and show PWV measurements taken with CAMAL compared to those of a nearby GPS water vapor monitor.

  10. What controls the isotopic composition of Greenland surface snow?

    Directory of Open Access Journals (Sweden)

    H. C. Steen-Larsen

    2013-10-01

    Full Text Available Water stable isotopes in Greenland ice core data provide key paleoclimatic information, and have been compared with precipitation isotopic composition simulated by isotopically-enabled atmospheric models. However, post-deposition processes linked with snow metamorphism remain poorly documented. For this purpose, a monitoring of the isotopic composition (δ18O, δD of surface water vapor, precipitation and samples of top (0.5 cm snow surface has been conducted during two summers (2011–2012 at NEEM, NW Greenland. The measurements also include a subset of 17O-excess measurements over 4 days, and the measurements span the 2012 Greenland heat wave. Our observations are consistent with calculations assuming isotopic equilibrium between surface snow and water vapor. We observe a strong correlation between surface vapor δ18O and air temperature (0.85 ± 0.11 ‰ °C−1 (R = 0.76 for 2012. The correlation with air temperature is not observed in precipitation data or surface snow data. Deuterium excess (d-excess is strongly anti-correlated with δ18O with a stronger slope for vapor than for precipitation and snow surface data. During nine 1–5 days periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated that 6 to 20% of the surface snow mass is exchanged with the atmosphere using the CROCUS snow model. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or condensation. Comparisons with atmospheric models show that day-to-day variations in surface vapor isotopic composition are driven by synoptic weather and changes in air mass trajectories and distillation histories. We suggest that, in-between precipitation events, changes in the surface snow isotopic composition are driven by these changes in surface vapor isotopic

  11. What controls the isotopic composition of Greenland surface snow?

    Directory of Open Access Journals (Sweden)

    H. C. Steen-Larsen

    2014-02-01

    Full Text Available Water stable isotopes in Greenland ice core data provide key paleoclimatic information, and have been compared with precipitation isotopic composition simulated by isotopically enabled atmospheric models. However, post-depositional processes linked with snow metamorphism remain poorly documented. For this purpose, monitoring of the isotopic composition (δ18O, δD of near-surface water vapor, precipitation and samples of the top (0.5 cm snow surface has been conducted during two summers (2011–2012 at NEEM, NW Greenland. The samples also include a subset of 17O-excess measurements over 4 days, and the measurements span the 2012 Greenland heat wave. Our observations are consistent with calculations assuming isotopic equilibrium between surface snow and water vapor. We observe a strong correlation between near-surface vapor δ18O and air temperature (0.85 ± 0.11‰ °C−1 (R = 0.76 for 2012. The correlation with air temperature is not observed in precipitation data or surface snow data. Deuterium excess (d-excess is strongly anti-correlated with δ18O with a stronger slope for vapor than for precipitation and snow surface data. During nine 1–5-day periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and near-surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near

  12. What controls the isotopic composition of Greenland surface snow?

    Science.gov (United States)

    Steen-Larsen, H. C.; Masson-Delmotte, V.; Hirabayashi, M.; Winkler, R.; Satow, K.; Prié, F.; Bayou, N.; Brun, E.; Cuffey, K. M.; Dahl-Jensen, D.; Dumont, M.; Guillevic, M.; Kipfstuhl, S.; Landais, A.; Popp, T.; Risi, C.; Steffen, K.; Stenni, B.; Sveinbjörnsdottír, A. E.

    2014-02-01

    Water stable isotopes in Greenland ice core data provide key paleoclimatic information, and have been compared with precipitation isotopic composition simulated by isotopically enabled atmospheric models. However, post-depositional processes linked with snow metamorphism remain poorly documented. For this purpose, monitoring of the isotopic composition (δ18O, δD) of near-surface water vapor, precipitation and samples of the top (0.5 cm) snow surface has been conducted during two summers (2011-2012) at NEEM, NW Greenland. The samples also include a subset of 17O-excess measurements over 4 days, and the measurements span the 2012 Greenland heat wave. Our observations are consistent with calculations assuming isotopic equilibrium between surface snow and water vapor. We observe a strong correlation between near-surface vapor δ18O and air temperature (0.85 ± 0.11‰ °C-1 (R = 0.76) for 2012). The correlation with air temperature is not observed in precipitation data or surface snow data. Deuterium excess (d-excess) is strongly anti-correlated with δ18O with a stronger slope for vapor than for precipitation and snow surface data. During nine 1-5-day periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and near-surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near-surface vapor

  13. Snow Web 2.0: The Next Generation of Antarctic Meteorological Monitoring Systems?

    Science.gov (United States)

    Coggins, J.; McDonald, A.; Plank, G.; Pannell, M.; Ward, R.; Parsons, S.

    2012-04-01

    Adequate in-situ observation of the Antarctic lower atmosphere has proved problematic, due to a combination of the inhospitable nature and extent of the continent. Traditional weather stations are expensive, subject to extreme weather for long periods and are often isolated, and as such are prone to failure and logistically difficult to repair. We have developed the first generation of an extended system of atmospheric sensors, each costing a fraction of the price of a traditional weather station. The system is capable of performing all of the monitoring tasks of a traditional station, but has built-in redundancy over the traditional approach because many units can be deployed in a relatively small area for similar expenditure as one large weather station. Furthermore, each unit is equipped with wireless networking capabilities and so is able to share information with those units in its direct vicinity. This allows for the ferrying of collected information to a manned observation station and hence the ability to monitor data in real-time. The distributed nature of the data collected can then be used as a stand-alone product to investigate small-scale weather and climate phenomena or integrated into larger studies and be used to monitor wide regions. GPS hardware installed on each unit also allows for high-resolution glacier or ice-shelf tracking. As a testing and data gathering study, eighteen such weather stations were deployed in the vicinity of Scott Base, Ross Island, Antarctica over the 2011/12 summer season. This presentation reports on findings from this field study, and discusses possibilities for the future.

  14. Modelling Water Flow, Heat Transport, Soil Freezing and Thawing, and Snow Processes in a Clayey, Subsurface Drained Agricultural Field

    Science.gov (United States)

    Warsta, L.; Turunen, M.; Koivusalo, H. J.; Paasonen-Kivekäs, M.; Karvonen, T.; Taskinen, A.

    2012-12-01

    Simulation of hydrological processes for the purposes of agricultural water management and protection in boreal environment requires description of winter time processes, including heat transport, soil freezing and thawing, and snow accumulation and melt. Finland is located north of the latitude of 60 degrees and has one third to one fourth of the total agricultural land area (2.3 milj. ha) on clay soils (> 30% of clay). Most of the clayey fields are subsurface drained to provide efficient drainage and to enable heavy machines to operate on the fields as soon as possible after the spring snowmelt. Generation of drainflow and surface runoff in cultivated fields leads to nutrient and sediment load, which forms the major share of the total load reaching surface waters at the national level. Water, suspended sediment, and soluble nutrients on clayey field surface are conveyed through the soil profile to the subsurface drains via macropore pathways as the clayey soil matrix is almost impermeable. The objective of the study was to develop the missing winter related processes into the FLUSH model, including soil heat transport, snow pack simulation and the effects of soil freezing and thawing on the soil hydraulic conductivity. FLUSH is an open source (MIT license), distributed, process-based model designed to simulate surface runoff and drainflow in clayey, subsurface drained agricultural fields. 2-D overland flow is described with the diffuse wave approximation of the Saint Venant equations and 3-D subsurface flow with a dual-permeability model. Both macropores and soil matrix are simulated with the Richards equation. Soil heat transport is described with a modified 3-D convection-diffusion equation. Runoff and groundwater data was available from different periods from January 1994 to April 1999 measured in a clayey, subsurface drained field section (3.6 ha) in southern Finland. Soil temperature data was collected in two locations (to a depth of 0.8 m) next to the

  15. Attributing the changes in seasonal runoff to dominated water sources in a snow and glacier melt-dominated catchment

    Science.gov (United States)

    He, Zhihua

    2016-04-01

    Attributing the changes in seasonal runoff to dominated water sources in a snow and glacier melt-dominated catchment Trend analysis indicates significant changes in the magnitude and timing of seasonal runoff from 1960 to 2010 in the Ala_archa catchment in Central Asia, which is dominated by snow and glacier meltwater. This study modeled the dominated water sources, including snowmelt water, glacier melt water and rainfall water, for daily discharge events in this basin. Hydrological parameters were estimated in a stepwise method. First, parameters were divided into the melting group and non-melting group based on sensitive analysis. The parameters belonged to the melting group effect the estimation of snow and glacier melting, while it is the opposite for the parameters belonged to the non-melting group. Second, the melting parameters were calibrated on the observed annual glacier mass balance data. Third, the non-melting parameters were calibrated on the observed daily discharge series using the calibrated melting parameters. Fourth, the melting parameters were recalibrated on both the observed glacier mass balance data and the daily discharge series. The calibration steps were repeated until the relative difference of all the melting parameter values between two calibration procedures were lower than 5%. The dominated water sources for each discharge event were identified by the fraction of water inputs in the whole basin during a 7-day period preceded the discharge event. The fraction of various water inputs were calculated in 300m-elevation bands. In cases the fraction of snowmelt water is higher than 0.6, the corresponding discharge events were identified as snowmelt dominated events, and it is the same for the rainfall and glacier melt dominated events. Results show that the increasing in winter runoff is caused by the increased rainfall, the increased spring runoff is driven by the increasing of snowmelt, while the increased glacier meltwater dominated the

  16. Real-time water quality monitoring and providing water quality ...

    Science.gov (United States)

    EPA and the U.S. Geological Survey (USGS) have initiated the “Village Blue” research project to provide real-time water quality monitoring data to the Baltimore community and increase public awareness about local water quality in Baltimore Harbor and the Chesapeake Bay. The Village Blue demonstration project complements work that a number of state and local organizations are doing to make Baltimore Harbor “swimmable and fishable” 2 by 2020. Village Blue is designed to build upon EPA’s “Village Green” project which provides real-time air quality information to communities in six locations across the country. The presentation, “Real-time water quality monitoring and providing water quality information to the Baltimore Community”, summarizes the Village Blue real-time water quality monitoring project being developed for the Baltimore Harbor.

  17. Densification and grain coarsening of melting snow

    Institute of Scientific and Technical Information of China (English)

    周石硚; 中尾正义; 桥本重将; 坂井亚规子; 成田英器; 石川信敬

    2003-01-01

    A field work was conducted at Moshiri in Japan.The work included intensive snow pit work, taking snow grain photos, recording snow and air temperatures, as well as measuring snow water content.By treating the snow as a viscous fluid, it is found that the snow compactive viscosity decreases as the density increases, which is opposite to the relation for dry snow.Based on the measurements of snow grain size, it is shown that, similar to the water-saturated snow, the frequency distributions of grain size at different times almost have the same shape.This reveals that the water-unsaturated melting snow holds the same grain-coarsening behavior as the water-saturated snow does.It is also shown that the water-unsaturated melting snow coarsens much more slowly than the water-saturated snow.The C value, which is the viscosity when the snow density is zero, is related to the mean grain size and found to decrease with increasing grain size.The decreasing rate of C value increases with decreasing grain-coarsening rate.

  18. Monitoring the waste water of LEP

    CERN Document Server

    Rühl, I

    1999-01-01

    Along the LEP sites CERN is discharging water of differing quality and varying amounts into the local rivers. This wastewater is not only process water from different cooling circuits but also water that infiltrates into the LEP tunnel. The quality of the discharged wastewater has to conform to the local environmental legislation of our Host States and therefore has to be monitored constantly. The most difficult aspect regarding the wastewater concerns LEP Point 8 owing to an infiltration of crude oil (petroleum), which is naturally contained in the soil along octant 7-8 of the LEP tunnel. This paper will give a short summary of the modifications made to the oil/water separation unit at LEP Point 8. The aim was to obtain a satisfactory oil/water separation and to install a monitoring system for a permanent measurement of the amount of hydrocarbons in the wastewater.

  19. John Snow and research.

    Science.gov (United States)

    Shephard, D A

    1989-03-01

    John Snow's leadership in epidemiology as well as anaesthesia resulted from his research as much as his clinical practice. In anaesthesia, Snow's research concerned the regulation of concentrations of volatile agents and the development of efficient inhalers; the uptake and elimination of volatile agents; stages of anaesthesia; carbon dioxide metabolism and rebreathing; and metabolism in anaesthesia and the theory of anaesthesia. In epidemiology, Snow investigated the relationship of water supplies to mortality in cholera during the London epidemic in 1854, which led him to formulate an original and valid theory of the transmission of cholera. Snow's research, which has received less attention than anecdotes concerning his career (e.g., his anaesthetizing Queen Victoria and urging removal of the handle of a contaminated water pump), was always directed towards solving specific problems. The significance of his research is evident in its leading not only to improvements in health care but also to the evolution of anaesthesia and epidemiology as professional disciplines.

  20. The snow line in viscous disks around low-mass stars: implications for water delivery to terrestrial planets in the habitable zone

    CERN Document Server

    Mulders, Gijs D; Min, Michiel; Pascucci, Ilaria

    2015-01-01

    The water ice or snow line is one of the key properties of protoplanetary disks that determines the water content of terrestrial planets in the habitable zone. Its location is determined by the properties of the star, the mass accretion rate through the disk, and the size distribution of dust suspended in the disk. We calculate the snow line location from recent observations of mass accretion rates and as a function of stellar mass. By taking the observed dispersion in mass accretion rates as a measure of the dispersion in initial disk mass, we find that stars of a given mass will exhibit a range of snow line locations. At a given age and stellar mass, the observed dispersion in mass accretion rates of 0.4 dex naturally leads to a dispersion in snow line locations of 0.2 dex. For ISM-like dust sizes, the one-sigma snow line location among solar mass stars of the same age ranges from 2 to 5 au. For more realistic dust opacities that include larger grains, the snow line is located up to two times closer to the ...

  1. Groundwater, Soil Moisture, Snow Water Equivalent, and River Water in the Seasonal Variation of Total Terrestrial Water Storage in Major River Basins

    Science.gov (United States)

    Oki, T.; Yoshimura, K.; Kim, H.; Shen, Y.; Thanh, N. D.; Seto, S.; Kanae, S.

    2006-12-01

    Both the combined atmospheric-river basin water balance and the remote sensing by GRACE can estimate the variation of the total terrestrial water storage which consist the changes in ground water, soil moisture, snow water equivalent, and water in rivers, lakes, ponds, etc. What are the major components in the change of the total terrestrial water storage? One hand, the seasonal variation of the total water storage in major continental-scale river basins are estimated by the atmospheric-river basin water balance (AWB) method The global distribution of water vapor flux convergence was estimated using the ECMWF global analysis data for the period from 1986 through 1995. The 10 year mean value of the atmospheric water vapor convergence was adjusted to match with the climatological mean value of river runoff for 1961-1990. Then the seasonal changes of the total terrestrial water storage were estimated by AWB method combining the atmospheric water vapor convergence for major river basins and the runoff from the area. On the other hand, the components in the change of the total terrestrial water storage were investigated using the multi-model products forced by observed surface meteorology. Under the Global Land/Atmosphere Study (GLASS), the Phase 2 of the Global Soil Wetness Project (GSWP-2) produced the first global (excluding Antarctica) 1x1 degree Multi-Model Analysis (MMA) of land-surface variables and fluxes for the 10-year period of 1986 1995 at the daily time scale. Thirteen land-surface models (LSMs) were driven by the best possible forcing data of the atmospheric conditions, such as precipitation, downward radiation, wind speed, air humidity and air temperature with temporal resolution of 3-hourly or higher. Water balance in major continental scale river basins were post-processed and the seasonal changes in ground water, soil moisture, snow water equivalent, and the water in river channel were analyzed using the Total Runoff Integrating Pathways (TRIP) and a

  2. Effect of clear cutting on snow accumulation and water outflow at Fraser, Colorado

    Directory of Open Access Journals (Sweden)

    C. A. Troendle

    1997-01-01

    Full Text Available This paper compares of snowpack accumulation and ablation, evapotranspiration, and water outflow from clearcut and forested plots within a high elevation (2900 m mixed conifer forest at the Fraser Experimental Forest near Fraser, Colorado, USA. Also presented is a method for defining contributing area where outflow is measured from unbounded plots. Plots were monitored from 1980 to 1990 and again in 1993. The clearcut plot was harvested in late 1984. Evapotranspiration (ET of the forested plot at zero discharge (ETo was estimated at 426 mm while the ET was 500 mm at the mean precipitation of 596 mm. ET was dependent on precipitation with about 28% of precipitation input in excess of 426 mm contributing to increased ET, while the remainder contributed to increased outflow. During the six monitored post-harvest years, Peak Water Equivalent of the snowpack averaged 36% higher on the cut plot than on the control, and the mean discharge increased from 85 mm to 356 mm. Area estimates were obtained from the slopes of the regression of outflow on precipitation inputs. Hydrologic parameters corresponded closely to those previously determined at Fraser Experimental Forest using other methods, lending credence to the validity of the area estimates.

  3. 21 CFR 868.2450 - Lung water monitor.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Lung water monitor. 868.2450 Section 868.2450 Food... DEVICES ANESTHESIOLOGY DEVICES Monitoring Devices § 868.2450 Lung water monitor. (a) Identification. A lung water monitor is a device used to monitor the trend of fluid volume changes in a patient's lung...

  4. 40 CFR 141.706 - Reporting source water monitoring results.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Reporting source water monitoring... Cryptosporidium Source Water Monitoring Requirements § 141.706 Reporting source water monitoring results. (a) Systems must report results from the source water monitoring required under § 141.701 no later than 10...

  5. Determination of total arsenic and arsenic species in drinking water, surface water, wastewater, and snow from Wielkopolska, Kujawy-Pomerania, and Lower Silesia provinces, Poland.

    Science.gov (United States)

    Komorowicz, Izabela; Barałkiewicz, Danuta

    2016-09-01

    Arsenic is a ubiquitous element which may be found in surface water, groundwater, and drinking water. In higher concentrations, this element is considered genotoxic and carcinogenic; thus, its level must be strictly controlled. We investigated the concentration of total arsenic and arsenic species: As(III), As(V), MMA, DMA, and AsB in drinking water, surface water, wastewater, and snow collected from the provinces of Wielkopolska, Kujawy-Pomerania, and Lower Silesia (Poland). The total arsenic was analyzed by inductively coupled plasma mass spectrometry (ICP-MS), and arsenic species were analyzed with use of high-performance liquid chromatography inductively coupled plasma mass spectrometry (HPLC/ICP-MS). Obtained results revealed that maximum total arsenic concentration determined in drinking water samples was equal to 1.01 μg L(-1). The highest concentration of total arsenic in surface water, equal to 3778 μg L(-1) was determined in Trująca Stream situated in the area affected by geogenic arsenic contamination. Total arsenic concentration in wastewater samples was comparable to those determined in drinking water samples. However, significantly higher arsenic concentration, equal to 83.1 ± 5.9 μg L(-1), was found in a snow sample collected in Legnica. As(V) was present in all of the investigated samples, and in most of them, it was the sole species observed. However, in snow sample collected in Legnica, more than 97 % of the determined concentration, amounting to 81 ± 11 μg L(-1), was in the form of As(III), the most toxic arsenic species.

  6. Characterization of organic composition in snow and surface waters in the Athabasca Oil Sands Region, using ultrahigh resolution Fourier transform mass spectrometry.

    Science.gov (United States)

    Yi, Y; Birks, S J; Cho, S; Gibson, J J

    2015-06-15

    This study was conducted to characterize the composition of dissolved organic compounds present in snow and surface waters in the Athabasca Oil Sands Region (AOSR) with the goal of identifying whether atmospherically-derived organic compounds present in snow are a significant contributor to the compounds detected in surface waters (i.e., rivers and lakes). We used electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FTICR MS) to characterize the dissolved organic compound compositions of snow and surface water samples. The organic profiles obtained for the snow samples show compositional differences between samples from near-field sites (surface water samples in the AOSR. The composition of dissolved organic compounds at the upstream Athabasca River site (i.e., Athabasca River at Athabasca) is found to be different from samples obtained from downstream sites in the vicinity of oil sands operations (i.e., Athabasca River at Fort McMurray and Athabasca River at Firebag confluence). The upstream Athabasca River sites tended to share some compositional similarities with far-field snow deposition, while the downstream Athabasca River sites are more similar to local lakes and tributaries. This contrast likely indicates the relative role of regional snowmelt contributions to the Athabasca River vs inputs from local catchments in the reach downstream of Fort McMurray.

  7. The Snow Line in Viscous Disks around Low-mass Stars: Implications for Water Delivery to Terrestrial Planets in the Habitable Zone

    NARCIS (Netherlands)

    Mulders, G.D.; Ciesla, F.J.; Min, M.; Pascucci, I.

    2015-01-01

    The water-ice or snow line is one of the key properties of protoplanetary disks that determines the water content of terrestrial planets in the habitable zone. Its location is determined by the properties of the star, the mass accretion rate through the disk, and the size distribution of dust suspen

  8. Using DNA damage to monitor water environment

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    DNA damage of aquatic organisms living in polluted environments can be used as a biomarker of the genotoxicity of toxic agents to organisms. This technique has been playing an important role in ecotoxicological study and environmental risk assessment. In this article, main types of DNA damage caused by pollutants in water environments were reviewed; methods of detecting DNA damage were also documented for water environmental monitoring.

  9. Measuring Snow Precipitation in New Zealand- Challenges and Opportunities.

    Science.gov (United States)

    Renwick, J. A.; Zammit, C.

    2015-12-01

    Monitoring plays a pivotal role in determining sustainable strategy for efficient overall management of the water resource. Though periodic monitoring provides some information, only long-term monitoring can provide data sufficient in quantity and quality to determine trends and develop predictive models. These can support informed decisions about sustainable and efficient use of water resources in New Zealand. However the development of such strategies is underpinned by our understanding and our ability to measure all inputs in headwaters catchments, where most of the precipitation is falling. Historically due to the harsh environment New Zealand has had little to no formal high elevation monitoring stations for all climate and snow related parameters outside of ski field climate and snow stations. This leads to sparse and incomplete archived datasets. Due to the importance of these catchments to the New Zealand economy (eg irrigation, hydro-electricity generation, tourism) NIWA has developed a climate-snow and ice monitoring network (SIN) since 2006. This network extends existing monitoring by electricity generator and ski stations and it is used by a number of stakeholders. In 2014 the network comprises 13 stations located at elevation above 700masl. As part of the WMO Solid Precipitation Intercomparison Experiment (SPICE), NIWA is carrying out an intercomparison of precipitation data over the period 2013-2015 at Mueller Hut. The site was commissioned on 11 July 2013, set up on the 17th September 2013 and comprises two Geonor weighing bucket raingauges, one shielded and the other un-shielded, in association with a conventional tipping bucket raingauge and conventional climate and snow measurements (temperature, wind, solar radiation, relative humidity, snow depth and snow pillow). The presentation aims to outline the state of the current monitoring network in New Zealand, as well as the challenge and opportunities for measurement of precipitation in alpine

  10. The assessment of EUMETSAT HSAF Snow Products for mountainuos areas in the eastern part of Turkey

    Science.gov (United States)

    Akyurek, Z.; Surer, S.; Beser, O.; Bolat, K.; Erturk, A. G.

    2012-04-01

    Monitoring the snow parameters (e.g. snow cover area, snow water equivalent) is a challenging work. Because of its natural physical properties, snow highly affects the evolution of weather from daily basis to climate on a longer time scale. The derivation of snow products over mountainous regions has been considered very challenging. This can be done by periodic and precise mapping of the snow cover. However inaccessibility and scarcity of the ground observations limit the snow cover mapping in the mountainous areas. Today, it is carried out operationally by means of optical satellite imagery and microwave radiometry. In retrieving the snow cover area from satellite images bring the problem of topographical variations within the footprint of satellite sensors and spatial and temporal variation of snow characteristics in the mountainous areas. Most of the global and regional operational snow products use generic algorithms for flat and mountainous areas. However the non-uniformity of the snow characteristics can only be modeled with different algorithms for mountain and flat areas. In this study the early findings of Satellite Application Facilities on Hydrology (H-SAF) project, which is financially supported by EUMETSAT, will be presented. Turkey is a part of the H-SAF project, both in product generation (eg. snow recognition, fractional snow cover and snow water equivalent) for mountainous regions for whole Europe, cal/val of satellite-derived snow products with ground observations and cal/val studies with hydrological modeling in the mountainous terrain of Europe. All the snow products are operational on a daily basis. For the snow recognition product (H10) for mountainous areas, spectral thresholding methods were applied on sub pixel scale of MSG-SEVIRI images. The different spectral characteristics of cloud, snow and land determined the structure of the algorithm and these characteristics were obtained from subjective classification of known snow cover features

  11. Data processing for water monitoring system

    Science.gov (United States)

    Monford, L.; Linton, A. T.

    1978-01-01

    Water monitoring data acquisition system is structured about central computer that controls sampling and sensor operation, and analyzes and displays data in real time. Unit is essentially separated into two systems: computer system, and hard wire backup system which may function separately or with computer.

  12. Snow accretion on overhead wires

    Energy Technology Data Exchange (ETDEWEB)

    Sakamoto, Y. [Meteorological Research Inst. for Technology Co. Ltd., Tokyo (Japan); Tachizaki, S.; Sudo, N. [Tohoku Electric Power Co. Ltd., Miyagi (Japan)

    2005-07-01

    Wet snow accretion can cause extensive damage to transmission systems. This paper reviewed some of the difficulties faced by researchers in the study of wet snow accretion on overhead lines in Japan. The study of snow accretion phenomena is complicated by the range of phase changes in water. Snowflakes produced in an upper atmospheric layer with a temperature below freezing do not melt when they go through a lower atmospheric layer with a temperature above freezing, but are in a mixed state of solid and liquid due to the latent heat of melting. The complicated properties of water make studies of snow accretion difficult, as well as the fact that snow changes its physical properties rapidly, due to the effects of ambient temperature, rainfall, and solar radiation. The adhesive forces that cause snow accretion include freezing; bonding through freezing; sintering; condensation and freezing of vapor in the air; mechanical intertwining of snowflakes; capillary action due to liquids; coherent forces between ice particles and water formed through the metamorphosis of snowflakes. In addition to these complexities, differences in laboratory room environments and natural snow environments can also pose difficulties for researchers. Equations describing the relationship between the density of accreted snow and the meteorological parameters involved were presented, as well as empirical equations which suggested that snow accretion efficiency has a dependency on air temperature. An empirical model for estimating snow loads in Japan was outlined, as well as various experiments observing show shedding. Correlations for wet snow accretion included precipitation intensity; duration of precipitation; air temperature; wind speed and wind direction in relation to the overhead line. Issues concerning topography and wet snow accretion were reviewed. It was concluded that studies of snow accretion will benefit by the collection of data in each matrix of the relevant parameters. 12 refs

  13. Reconstructing Snow Water Equivalent in the Rio Grande Headwaters: a Multi-Resolution, Multi-Sensor Comparison

    Science.gov (United States)

    Margulis, S.; Molotch, N. P.

    2006-12-01

    Time series of fractional snow covered area (SCA) estimates from Landsat Enhanced Thematic Mapper (ETM+), Moderate Resolution Imaging Spectoradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) data were combined with a spatially distributed snowmelt model to reconstruct snow water equivalent (SWE) in the Rio Grande headwaters (3,419 km2). In this reconstruction approach, modeled snowmelt over each pixel is integrated over the time of satellite observed snow cover to estimate SWE. Considerable differences in the magnitude of SWE were simulated during the two-snowmelt season study; basin-wide mean SWE was 2.6 times greater in April 2001 versus 2002 when using the ETM+ data in the model. Despite the climatological differences in 2001 versus 2002, model performance using ETM+ data aggregated to 100-m resolution was robust with a mean absolute error (MAE) of 23% relative to observed SWE from field campaigns. Model performance deteriorated when MODIS (MAE = 57%) and AVHRR (MAE = 90%) data were used and when simulations were run at coarser resolutions; MAE = 26, 34, and 47%, for ETM+ simulations run at 250-m, 500-m, and 1-km resolution, respectively. Basin-average maximum SWE using MODIS and AVHRR was 27% and 57% lower than ETM+ estimates, respectively. Maximum SWE decreased by 28% when ETM+ simulations were run at 1-km versus 100-m resolution. This research illustrates the utility and limitations of the reconstruction technique for obtaining high-resolution SWE estimates at larger scales (e.g. > 1000 km2) and in locations where detailed hydrometeorological observations are scarce.

  14. Mesoscale modeling of lake effect snow over Lake Erie - sensitivity to convection, microphysics and the water temperature

    NARCIS (Netherlands)

    Theeuwes, N.E.; Steeneveld, G.J.; Krikken, F.; Holtslag, A.A.M.

    2010-01-01

    Lake effect snow is a shallow convection phenomenon during cold air advection over a relatively warm lake. A severe case of lake effect snow over Lake Erie on 24 December 2001 was studied with the MM5 and WRF mesoscale models. This particular case provided over 200 cm of snow in Buffalo (NY), caused

  15. Spatial and temporal variability of snow depth and SWE in a small mountain catchment

    Directory of Open Access Journals (Sweden)

    T. Grünewald

    2010-01-01

    Full Text Available The spatio-temporal variability of the mountain snow cover determines the avalanche danger, snow water storage, permafrost distribution and the local distribution of fauna and flora. Using a new type of terrestrial laser scanner (TLS, which is particularly suited for measurements of snow covered surfaces, snow depth, snow water equivalent (SWE and melt rates have been monitored in a high alpine catchment during an ablation period. This allowed for the first time to get a high resolution (2.5 m cell size picture of spatial variability and its temporal development. A very high variability in which maximum snow depths between 0–9 m at the end of the accumulation season was found. This variability decreased during the ablation phase, although the dominant snow deposition features remained intact. The spatial patterns of calculated SWE were found to be similar to snow depth. Average daily melt rate was between 15 mm/d at the beginning of the ablation period and 30 mm/d at the end. The spatial variation of melt rates increased during the ablation rate and could not be explained in a simple manner by geographical or meteorological parameters, which suggests significant lateral energy fluxes contributing to observed melt. It could be qualitatively shown that the effect of the lateral energy transport must increase as the fraction of snow free surfaces increases during the ablation period.

  16. Constraining snowmelt in a temperature-index model using simulated snow densities

    Science.gov (United States)

    Bormann, Kathryn J.; Evans, Jason P.; McCabe, Matthew F.

    2014-09-01

    Current snowmelt parameterisation schemes are largely untested in warmer maritime snowfields, where physical snow properties can differ substantially from the more common colder snow environments. Physical properties such as snow density influence the thermal properties of snow layers and are likely to be important for snowmelt rates. Existing methods for incorporating physical snow properties into temperature-index models (TIMs) require frequent snow density observations. These observations are often unavailable in less monitored snow environments. In this study, previous techniques for end-of-season snow density estimation (Bormann et al., 2013) were enhanced and used as a basis for generating daily snow density data from climate inputs. When evaluated against 2970 observations, the snow density model outperforms a regionalised density-time curve reducing biases from -0.027 g cm-3 to -0.004 g cm-3 (7%). The simulated daily densities were used at 13 sites in the warmer maritime snowfields of Australia to parameterise snowmelt estimation. With absolute snow water equivalent (SWE) errors between 100 and 136 mm, the snow model performance was generally lower in the study region than that reported for colder snow environments, which may be attributed to high annual variability. Model performance was strongly dependent on both calibration and the adjustment for precipitation undercatch errors, which influenced model calibration parameters by 150-200%. Comparison of the density-based snowmelt algorithm against a typical temperature-index model revealed only minor differences between the two snowmelt schemes for estimation of SWE. However, when the model was evaluated against snow depths, the new scheme reduced errors by up to 50%, largely due to improved SWE to depth conversions. While this study demonstrates the use of simulated snow density in snowmelt parameterisation, the snow density model may also be of broad interest for snow depth to SWE conversion. Overall, the

  17. Constraining snowmelt in a temperature-index model using simulated snow densities

    KAUST Repository

    Bormann, Kathryn J.

    2014-09-01

    Current snowmelt parameterisation schemes are largely untested in warmer maritime snowfields, where physical snow properties can differ substantially from the more common colder snow environments. Physical properties such as snow density influence the thermal properties of snow layers and are likely to be important for snowmelt rates. Existing methods for incorporating physical snow properties into temperature-index models (TIMs) require frequent snow density observations. These observations are often unavailable in less monitored snow environments. In this study, previous techniques for end-of-season snow density estimation (Bormann et al., 2013) were enhanced and used as a basis for generating daily snow density data from climate inputs. When evaluated against 2970 observations, the snow density model outperforms a regionalised density-time curve reducing biases from -0.027gcm-3 to -0.004gcm-3 (7%). The simulated daily densities were used at 13 sites in the warmer maritime snowfields of Australia to parameterise snowmelt estimation. With absolute snow water equivalent (SWE) errors between 100 and 136mm, the snow model performance was generally lower in the study region than that reported for colder snow environments, which may be attributed to high annual variability. Model performance was strongly dependent on both calibration and the adjustment for precipitation undercatch errors, which influenced model calibration parameters by 150-200%. Comparison of the density-based snowmelt algorithm against a typical temperature-index model revealed only minor differences between the two snowmelt schemes for estimation of SWE. However, when the model was evaluated against snow depths, the new scheme reduced errors by up to 50%, largely due to improved SWE to depth conversions. While this study demonstrates the use of simulated snow density in snowmelt parameterisation, the snow density model may also be of broad interest for snow depth to SWE conversion. Overall, the

  18. Precision of estimated snow water equivalent (SWE) derived from the new sensor snow power in Quebec (Canada); Precision de l'estimation de l'equivalent en eau de la neige obtenue avec la sonde snowpower au Quebec (Canada)

    Energy Technology Data Exchange (ETDEWEB)

    Niang, M.; Durand, Y. [Meteo France/CEN, 38 - Saint Martin d' Heres (France); Bernier, M. [Institut National de la Recherche Scientifique (INRS-ETE), Centre Eau, Terre et Environnement, Quebec (Canada); Van Bochove, E. [Agriculture et Agroalimentaire, Quebec (Canada)

    2006-07-01

    This paper is about the accuracy gotten to determine the Snow Water Equivalent (SWE) and the snow moisture using a new in situ sensor, the 'SNOWPOWER' probe. This sensor can estimate simultaneously the snow density and the snow moisture by measuring the dielectric constant of the snow at low and high frequencies along a 10 to 20-m long flat-band cable. The high frequencies signal is measured with a Time Domain Reflectometer (TDR), the low frequencies signal is measured with an impedance analyser. The proposed original methodology allows also to extract the snow height and then to use the sensor for SWE estimation. This paper gives the results of one experimental season, the winter 2003-2004, in a agricultural field located near Quebec City in Canada (48 deg. 28'12''N, 71 deg. 10'48''W). The estimated derived from the new automatic sensor are compared with manual measurements of the snow properties. The results show a good estimation of the snow liquid water content (0.40% volumetric) and the SWE (14.07 mm). However, results show the importance of the selection of the low frequency and of the algorithm for the snow temperature extrapolation for the accuracy of the estimation. Finally, we discuss the integration of the sensor's densities to the EQeau model for mapping the SWE using radar satellite data. (authors)

  19. Better interpretation of snow remote sensing data with physics-based models

    Science.gov (United States)

    Sandells, M.; Davenport, I. J.; Quaife, T. L.; Flerchinger, G. N.; Marks, D. G.; Gurney, R. J.

    2012-12-01

    Interpretation of remote sensing data requires a model and some assumptions, and the quality of the end product depends on the accuracy and appropriateness of these. Snow is a vital component of the water cycle, both socially and economically, so accurate monitoring of this resource is important. However, the snow mass products from passive microwave data may have large errors in them, and were deemed too unreliable for consideration in the latest Intergovernmental Panel on Climate Change Assessment Report. The SSM/I passive microwave snow mass retrieval algorithm uses a linear brightness temperature difference model, and assumptions that snow has a fixed grain diameter of 0.8mm and density of 300 kg m-3. In reality, the properties of the snow vary in time and space depending on its thermal history, and scattering of microwave radiation is very sensitive to snow properties. If snow mass retrievals are to be made from remote sensing data, then these properties must be known rather well. Layered physics-based models are capable of simulating the evolution of profiles of temperature, water content in the snow or soil, and snow grain size. These simulations could be used to provide information to help understand remote sensing data. Additional information from other remote sensing sources could enhance the accuracy of the product. For example, surface snow grain size can be obtained from near-infrared reflectance observations, and these data can be used to constrain the physically-based model, as could thermal observations. Here, we will present a new method that could be used to derive better estimates of snow mass and soil moisture. The system is comprised of a physically-based model of the snow and soil to derive snow and soil properties, a snow microwave emission model to estimate the satellite observations and ancillary data to constrain the physically-based model. These components will be used to estimate snow mass from passive microwave data with data

  20. Suppression of the water ice and snow albedo feedback on planets orbiting red dwarf stars and the subsequent widening of the habitable zone

    CERN Document Server

    Joshi, M

    2012-01-01

    M-stars comprise 80% of main-sequence stars, and so their planetary systems provide the best chance for finding habitable planets, i.e.: those with surface liquid water. We have modelled the broadband albedo or reflectivity of water ice and snow for simulated planetary surfaces orbiting two observed red dwarf stars (or M-stars) using spectrally resolved data of the Earth's cryosphere. The gradual reduction of the albedos of snow and ice at wavelengths greater than 1 ?m, combined with M-stars emitting a significant fraction of their radiation at these same longer wavelengths, mean that the albedos of ice and snow on planets orbiting M-stars are much lower than their values on Earth. Our results imply that the ice/snow albedo climate feedback is significantly weaker for planets orbiting M-stars than for planets orbiting G-type stars such as the Sun. In addition, planets with significant ice and snow cover will have significantly higher surface temperatures for a given stellar flux if the spectral variation of c...

  1. Suppression of the water ice and snow albedo feedback on planets orbiting red dwarf stars and the subsequent widening of the habitable zone.

    Science.gov (United States)

    Joshi, Manoj M; Haberle, Robert M

    2012-01-01

    M stars comprise 80% of main sequence stars, so their planetary systems provide the best chance for finding habitable planets, that is, those with surface liquid water. We have modeled the broadband albedo or reflectivity of water ice and snow for simulated planetary surfaces orbiting two observed red dwarf stars (or M stars), using spectrally resolved data of Earth's cryosphere. The gradual reduction of the albedos of snow and ice at wavelengths greater than 1 μm, combined with M stars emitting a significant fraction of their radiation at these same longer wavelengths, means that the albedos of ice and snow on planets orbiting M stars are much lower than their values on Earth. Our results imply that the ice/snow albedo climate feedback is significantly weaker for planets orbiting M stars than for planets orbiting G-type stars such as the Sun. In addition, planets with significant ice and snow cover will have significantly higher surface temperatures for a given stellar flux if the spectral variation of cryospheric albedo is considered, which in turn implies that the outer edge of the habitable zone around M stars may be 10-30% farther away from the parent star than previously thought.

  2. Navigating the "Research-to-Operations" Bridge of Death: Collaborative Transition of Remotely-Sensed Snow Data from Research into Operational Water Resources Forecasting

    Science.gov (United States)

    Miller, W. P.; Bender, S.; Painter, T. H.; Bernard, B.

    2016-12-01

    Water and resource management agencies can benefit from hydrologic forecasts during both flood and drought conditions. Improved predictions of seasonal snowmelt-driven runoff volume and timing can assist operational water managers with decision support and efficient resource management within the spring runoff season. Using operational models and forecasting systems, NOAA's Colorado Basin River Forecast Center (CBRFC) produces hydrologic forecasts for stakeholders and water management groups in the western United States. Collaborative incorporation of research-oriented remote sensing data into CBRFC operational models and systems is one route by which CBRFC forecasts can be improved, ultimately for the benefit of water managers. Successful navigation of research-oriented remote sensing products across the "research-to-operations"/R2O gap (also known as the "valley of death") to operational destinations requires dedicated personnel on both the research and operations sides, working in a highly collaborative environment. Since 2012, the operational CBRFC has collaborated with the research-oriented Jet Propulsion Laboratory (JPL) under funding from NASA to transition remotely-sensed snow data into CBRFC's operational models and forecasting systems. Two specific datasets from JPL, the MODIS Dust Radiative Forcing in Snow (MODDRFS) and the MODIS Snow Covered-Area and Grain size (MODSCAG) products, are used in CBRFC operations as of 2016. Over the past several years, JPL and CBRFC have worked together to analyze patterns in JPL's remote sensing snow datasets from the operational perspective of the CBRFC and to develop techniques to bridge the R2O gap. Retrospective and real-time analyses have yielded valuable insight into the remotely-sensed snow datasets themselves, CBRFC's operational systems, and the collaborative R2O process. Examples of research-oriented JPL snow data, as used in CBRFC operations, are described. A timeline of the collaboration, challenges

  3. Energy and water balance studies of a snow cover during snowmelt period at a high arctic site

    Science.gov (United States)

    Bruland, O.; Maréchal, D.; Sand, K.; Killingtveit, Å.

    The predicted global warming is supposed to have an enhanced effect on the arctic regions. How this will influence the water, carbon dioxide and methane balances in the European arctic tundra is the objective of the EU-funded project ``Understanding Land Surface Physical Processes in the Arctic'' (LAPP), to which where SINTEF is one of several contributors. The snow cover is one of the limiting factors for these exchange processes and knowledge of how it behaves and will behave under a different climate is important. Data collected for water and energy balance studies in an area close to Ny-Ålesund at 79°N at Svalbard are the basis of this study. Measurements during the ablation periods since 1992 show an average air temperature for the periods of 2.1°C, an average incoming shorwave radiation of 230W/m2 and an average measured runoff intensity of 14mm/day with a maximum of 68mm/day. Three models of different complexity are tested in order to simulate the water and energy balance of a snow cover on the arctic tundra. The three models are: a complex numerical model (CROCUS), a simple energy balance model and a temperature index model. The simulations were carried out for the melt periods in 1992 and 1996 as these two periods represent very different meteorological conditions. The results of these simulations exposed weaknesses in all the models. The energy balance model lacks calculation of cold content in the snowpack. This influences both the outgoing longwave radiation and the timing of the melt. Due to the effect of compensating errors in the simulations, CROCUS performed better than the simple energy balance model but also this model has problems with the simulation of outgoing longwave radiation. The temperature index model does not perform well for snowmelt studies in regions were radiation is the main driving energy source for the melt.

  4. 40 CFR 257.22 - Ground-water monitoring systems.

    Science.gov (United States)

    2010-07-01

    ... operator. When physical obstacles preclude installation of ground-water monitoring wells at the relevant... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Ground-water monitoring systems. 257... Waste Disposal Units Ground-Water Monitoring and Corrective Action § 257.22 Ground-water......

  5. Monitoring water quality by remote sensing

    Science.gov (United States)

    Brown, R. L. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. A limited study was conducted to determine the applicability of remote sensing for evaluating water quality conditions in the San Francisco Bay and delta. Considerable supporting data were available for the study area from other than overflight sources, but short-term temporal and spatial variability precluded their use. The study results were not sufficient to shed much light on the subject, but it did appear that, with the present state of the art in image analysis and the large amount of ground truth needed, remote sensing has only limited application in monitoring water quality.

  6. Temporal Monitoring of the Soil Freeze-Thaw Cycles over a Snow-Covered Surface by Using Air-Launched Ground-Penetrating Radar

    KAUST Repository

    Jadoon, Khan

    2015-09-18

    We tested an off-ground ground-penetrating radar (GPR) system at a fixed location over a bare agricultural field to monitor the soil freeze-thaw cycles over a snow-covered surface. The GPR system consisted of a monostatic horn antenna combined with a vector network analyzer, providing an ultra-wideband stepped-frequency continuous-wave radar. An antenna calibration experiment was performed to filter antenna and back scattered effects from the raw GPR data. Near the GPR setup, sensors were installed in the soil to monitor the dynamics of soil temperature and dielectric permittivity at different depths. The soil permittivity was retrieved via inversion of time domain GPR data focused on the surface reflection. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and dielectric permittivity measurements. In particular, five freeze and thaw events were clearly detectable, indicating that the GPR signals respond to the contrast between the dielectric permittivity of frozen and thawed soil. The GPR-derived permittivity was in good agreement with sensor observations. Overall, the off-ground nature of the GPR system permits non-invasive time-lapse observation of the soil freeze-thaw dynamics without disturbing the structure of the snow cover. The proposed method shows promise for the real-time mapping and monitoring of the shallow frozen layer at the field scale.

  7. Temporal Monitoring of the Soil Freeze-Thaw Cycles over a Snow-Covered Surface by Using Air-Launched Ground-Penetrating Radar

    Directory of Open Access Journals (Sweden)

    Khan Zaib Jadoon

    2015-09-01

    Full Text Available We tested an off-ground ground-penetrating radar (GPR system at a fixed location over a bare agricultural field to monitor the soil freeze-thaw cycles over a snow-covered surface. The GPR system consisted of a monostatic horn antenna combined with a vector network analyzer, providing an ultra-wideband stepped-frequency continuous-wave radar. An antenna calibration experiment was performed to filter antenna and back scattered effects from the raw GPR data. Near the GPR setup, sensors were installed in the soil to monitor the dynamics of soil temperature and dielectric permittivity at different depths. The soil permittivity was retrieved via inversion of time domain GPR data focused on the surface reflection. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and dielectric permittivity measurements. In particular, five freeze and thaw events were clearly detectable, indicating that the GPR signals respond to the contrast between the dielectric permittivity of frozen and thawed soil. The GPR-derived permittivity was in good agreement with sensor observations. Overall, the off-ground nature of the GPR system permits non-invasive time-lapse observation of the soil freeze-thaw dynamics without disturbing the structure of the snow cover. The proposed method shows promise for the real-time mapping and monitoring of the shallow frozen layer at the field scale.

  8. Radionuclide Sensors for Subsurface Water Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Timothy DeVol

    2006-06-30

    Contamination of the subsurface by radionuclides is a persistent and vexing problem for the Department of Energy. These radionuclides must be measured in field studies and monitoed in the long term when they cannot be removed. However, no radionuclide sensors existed for groundwater monitoring prior to this team's research under the EMSP program Detection of a and b decays from radionuclides in water is difficult due to their short ranges in condensed media.

  9. Field Monitoring Protocol: Heat Pump Water Heaters

    Energy Technology Data Exchange (ETDEWEB)

    Sparn, B.; Earle, L.; Christensen, D.; Maguire, J.; Wilson, E.; Hancock, E.

    2013-02-01

    This document provides a standard field monitoring protocol for evaluating the installed performance of Heat Pump Water Heaters in residential buildings. The report is organized to be consistent with the chronology of field test planning and execution. Research questions are identified first, followed by a discussion of analysis methods, and then the details of measuring the required information are laid out. A field validation of the protocol at a house near the NREL campus is included for reference.

  10. Field Monitoring Protocol. Heat Pump Water Heaters

    Energy Technology Data Exchange (ETDEWEB)

    Sparn, B. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Earle, L. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Christensen, D. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Maguire, J. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Wilson, E. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Hancock, C. E. [Mountain Energy Partnership, Longmont, CO (United States)

    2013-02-01

    This document provides a standard field monitoring protocol for evaluating the installed performance of Heat Pump Water Heaters in residential buildings. The report is organized to be consistent with the chronology of field test planning and execution. Research questions are identified first, followed by a discussion of analysis methods, and then the details of measuring the required information are laid out. A field validation of the protocol at a house near the NREL campus is included for reference.

  11. LANDSAT-4 Science Characterization Early Results. Volume 4: Applications. [agriculture, soils land use, geology, hydrology, wetlands, water quality, biomass identification, and snow mapping

    Science.gov (United States)

    Barker, J. L. (Editor)

    1985-01-01

    The excellent quality of TM data allows researchers to proceed directly with applications analyses, without spending a significant amount of time applying various corrections to the data. The early results derived of TM data are discussed for the following applications: agriculture, land cover/land use, soils, geology, hydrology, wetlands biomass, water quality, and snow.

  12. Initial Survey Instructions for Spring Water Monitoring : Quality

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Initial survey instructions for 1.04 spring water monitoring (quality) and 1.06 management unit water monitoring (quality) at Fish Springs National Wildlife Refuge....

  13. One decade of scientific studies of snow management on Austria's glacier ski resorts

    Science.gov (United States)

    Fischer, Andrea; Helfricht, Kay

    2016-04-01

    After the extremely warm summer of 2003, when melt affected Austria's glaciers up to the highest elevations, a scientific study on artificial modification of mass balance was initiated. It examined the effects of glacier covers and water injection, but also various grooming methods and snow accumulations based on monitoring and modelling of snow and energy balance. The results showed that covering the glacier was the most effective and cheapest method, saving about 70% of glacier melt in places. But covers are restricted to a small portion of the area, as they require high maintenance. In recent years, snow production and snow accumulation by wind drift have gained more and more importance, not only modifying glacier mass balance, but also guaranteeing an early season start. Initially about 35 ha of the glacier area (ski resort area and less than one per mille of the total glacier area in Austria) were covered and later the area was reduced as snow production possibilities increased. Snow depots are often used as fun parks for snow boarders. Glacier covers are not primarily used for keeping snow for early season start on ski tracks, but to maintain the surface, especially close to cable car infrastructure, at a constant elevation and slope. Despite glacier dynamics, glacier surfaces with snow management show reduced decrease of surface elevation , both on piste and along lift tracks.

  14. Monitoring snow melt characteristics on the Greenland ice sheet using a new MODIS land surface temperature and emissivity product (MOD21)

    Science.gov (United States)

    Hulley, G. C.; Hall, D. K.; Hook, S. J.

    2013-12-01

    Land Surface Temperature (LST) and emissivity are sensitive energy-balance parameters that control melt and energy exchange between the surface and the atmosphere. MODIS LST is currently used to monitor melt zones on glaciers and can be used for glacier or ice sheet mass balance calculations. Much attention has been paid recently to the warming of the Arctic in the context of global warming, with a focus on the Greenland ice sheet because of its importance with sea-level rise. Various researchers have shown a steady decline in the extent of the Northern Hemisphere sea ice, both the total extent and the extent of the perennial or multiyear ice. Surface melt characteristics over the Greenland ice sheet have been traditionally monitored using the MODIS LST and albedo products (e.g. MOD11 and MOD10A1). Far fewer studies have used thermal emissivity data to monitor surface melt characteristics due to the lack of suitable data. In theory, longwave emissivity combined with LST information should give a more direct measure of snow melt characteristics since the emissivity is an intrinsic property of the surface, whereas the albedo is dependent on other factors such as solar zenith angle, and shadowing effects. Currently no standard emissivity product exists that can dynamically retrieve changes in longwave emissivity consistently over long time periods. This problem has been addressed with the new MOD21 product, which uses the ASTER TES algorithm to dynamically retrieve LST and spectral emissivity (bands 29, 31, 32) at 1-km resolution. In this study we show that using a new proposed index termed the snow emissivity difference index (SEDI) derived from the MOD21 longwave emissivity product, combined with the LST, will improve our understanding of snow melt and freezeup dynamics on ice sheets such as Greenland. The results also suggest that synergistic use of both thermal-based and albedo data will help to improve our understanding of snow melt dynamics on glaciers and ice

  15. Continuous monitoring of plant water potential.

    Science.gov (United States)

    Schaefer, N L; Trickett, E S; Ceresa, A; Barrs, H D

    1986-05-01

    Plant water potential was monitored continuously with a Wescor HR-33T dewpoint hygrometer in conjunction with a L51 chamber. This commercial instrument was modified by replacing the AC-DC mains power converter with one stabilized by zener diode controlled transistors. The thermocouple sensor and electrical lead needed to be thermally insulated to prevent spurious signals. For rapid response and faithful tracking a low resistance for water vapor movement between leaf and sensor had to be provided. This could be effected by removing the epidermis either by peeling or abrasion with fine carborundum cloth. A variety of rapid plant water potential responses to external stimuli could be followed in a range of crop plants (sunflower (Helianthus annuus L., var. Hysun 30); safflower (Carthamus tinctorious L., var. Gila); soybean (Glycine max L., var. Clark); wheat (Triticum aestivum L., var. Egret). These included light dark changes, leaf excision, applied pressure to or anaerobiosis of the root system. Water uptake by the plant (safflower, soybean) mirrored that for water potential changes including times when plant water status (soybean) was undergoing cyclical changes.

  16. 40 CFR 130.4 - Water quality monitoring.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 21 2010-07-01 2010-07-01 false Water quality monitoring. 130.4... QUALITY PLANNING AND MANAGEMENT § 130.4 Water quality monitoring. (a) In accordance with section 106(e)(1.../quality control guidance. (b) The State's water monitoring program shall include collection and analysis...

  17. 40 CFR 258.51 - Ground-water monitoring systems.

    Science.gov (United States)

    2010-07-01

    ... preclude installation of ground-water monitoring wells at the relevant point of compliance at existing... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Ground-water monitoring systems. 258... CRITERIA FOR MUNICIPAL SOLID WASTE LANDFILLS Ground-Water Monitoring and Corrective Action § 258.51...

  18. Water equivalent of snow retrieved from data of passive microwave scanning with the use of artificial neural networks over the Russian Federation territory

    Directory of Open Access Journals (Sweden)

    A. A. Volchek

    2016-01-01

    Full Text Available Using of the Chang model for calculation of the snow water equivalent on the basis of measurements of the Earth thermo-microwave radiation by means of scanning polarimeters (SMMR, SSM/I, AMSR-E from board of orbital satellites does not allow obtaining the accuracy needed hydrological purposes. Low accuracy of the calculations is caused by both simplified character of the mathematical model, and due to significant influence of the surface characteristics (relief, vegetation and complex structure of snow thickness upon the microwave radiation propagation. This work was aimed at finding a way to increase accuracy of calculations of the snow water equivalent on the Russian Federation territory with its different climate conditions by means of application the neural network approach for processing of results of the passive microwave scanning of the Earth surface. Feed-forward multi-layer artificial neural network was trained by back-propagation algorithm using SSM/I data and results of snow water equivalent in situ measurements obtained at 117 meteorological stations during the period from January 1st, 1988 till December 31st, 1988. Validation was performed using data from the same sources collected during 7 years (1992–1998. Results of performed numerical experiments and obtained values of rootmean-square error (σ = 24.9 мм; r = 0.39±0,01 allow coming to conclusion that the best estimation of water equivalent of a snow cover is provided by artificial neural network using as the input data a set of the SSM/I channels 19.35, 37.0, 85.5 GHz of horizontal and vertical polarizations with meteorological data differentiated by types of the snow survey route.It is shown that low correlation coefficients (< 0.5 as compared with similar studies on small areas is not caused by the chosen mathematical model and its realization but it is due to a strong diversity of climatic conditions and low density of meteorological stations on the land areas

  19. Remote Sensing-based Methodologies for Snow Model Adjustments in Operational Streamflow Prediction

    Science.gov (United States)

    Bender, S.; Miller, W. P.; Bernard, B.; Stokes, M.; Oaida, C. M.; Painter, T. H.

    2015-12-01

    Water management agencies rely on hydrologic forecasts issued by operational agencies such as NOAA's Colorado Basin River Forecast Center (CBRFC). The CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate research-oriented, remotely-sensed snow data into CBRFC operations and to improve the accuracy of CBRFC forecasts. The partnership has yielded valuable analysis of snow surface albedo as represented in JPL's MODIS Dust Radiative Forcing in Snow (MODDRFS) data, across the CBRFC's area of responsibility. When dust layers within a snowpack emerge, reducing the snow surface albedo, the snowmelt rate may accelerate. The CBRFC operational snow model (SNOW17) is a temperature-index model that lacks explicit representation of snowpack surface albedo. CBRFC forecasters monitor MODDRFS data for emerging dust layers and may manually adjust SNOW17 melt rates. A technique was needed for efficient and objective incorporation of the MODDRFS data into SNOW17. Initial development focused in Colorado, where dust-on-snow events frequently occur. CBRFC forecasters used retrospective JPL-CBRFC analysis and developed a quantitative relationship between MODDRFS data and mean areal temperature (MAT) data. The relationship was used to generate adjusted, MODDRFS-informed input for SNOW17. Impacts of the MODDRFS-SNOW17 MAT adjustment method on snowmelt-driven streamflow prediction varied spatially and with characteristics of the dust deposition events. The largest improvements occurred in southwestern Colorado, in years with intense dust deposition events. Application of the method in other regions of Colorado and in "low dust" years resulted in minimal impact. The MODDRFS-SNOW17 MAT technique will be implemented in CBRFC operations in late 2015, prior to spring 2016 runoff. Collaborative investigation of remote sensing-based adjustment methods for the CBRFC operational hydrologic forecasting environment will continue over the next several years.

  20. GNSS-Reflectometry based water level monitoring

    Science.gov (United States)

    Beckheinrich, Jamila; Schön, Steffen; Beyerle, Georg; Apel, Heiko; Semmling, Maximilian; Wickert, Jens

    2013-04-01

    Due to climate changing conditions severe changes in the Mekong delta in Vietnam have been recorded in the last years. The goal of the German Vietnamese WISDOM (Water-related Information system for the Sustainable Development Of the Mekong Delta) project is to build an information system to support and assist the decision makers, planners and authorities for an optimized water and land management. One of WISDOM's tasks is the flood monitoring of the Mekong delta. Earth reflected L-band signals from the Global Navigation Satellite System show a high reflectivity on water and ice surfaces or on wet soil so that GNSS-Reflectometry (GNSS-R) could contribute to monitor the water level in the main streams of the Mekong delta complementary to already existing monitoring networks. In principle, two different GNSS-R methods exist: the code- and the phase-based one. As the latter being more accurate, a new generation of GORS (GNSS Occultation, Reflectometry and Scatterometry) JAVAD DELTA GNSS receiver has been developed with the aim to extract precise phase observations. In a two week lasting measurement campaign, the receiver has been tested and several reflection events at the 150-200 m wide Can Tho river in Vietnam have been recorded. To analyze the geometrical impact on the quantity and quality of the reflection traces two different antennas height were tested. To track separately the direct and the reflected signal, two antennas were used. To derive an average height of the water level, for a 15 min observation interval, a phase model has been developed. Combined with the coherent observations, the minimum slope has been calculated based on the Least- Squares method. As cycle slips and outliers will impair the results, a preprocessing of the data has been performed. A cycle slip detection strategy that allows for automatic detection, identification and correction is proposed. To identify outliers, the data snooping method developed by Baarda 1968 is used. In this

  1. Hydrogeophysical monitoring of water infiltration processes

    Science.gov (United States)

    Bevilacqua, Ivan; Cassiani, Giorgio; Deiana, Rita; Canone, Davide; Previati, Maurizio

    2010-05-01

    Non-invasive subsurface monitoring is growing in the last years. Techniques like ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) can be useful in soil water content monitoring (e.g., Vereecken et al., 2006). Some problems remain (e.g. spatial resolution), but the scale is consistent with many applications and hydrological models. The research has to to provide even more quantitative tools, without remaining in the qualitative realm. This is a very crucial step in the way to provide data useful for hydrological modeling. In this work a controlled field infiltration experiment has been done in August 2009 in the experimental site of Grugliasco, close to the Agricultural Faculty of the University of Torino, Italy. The infiltration has been monitored in time lapse by ERT, GPR, and TDR (Time Domain Reflectometry). The sandy soil characteristics of the site has been already described in another experiment [Cassiani et al. 2009a].The ERT was èperformed in dipole-dipole configuration, while the GPR had 100 MHz and 500 MHz antennas in WARR configuration. The TDR gages had different lengths. The amount of water which was sprinkled was also monitored in time.Irrigation intensity has been always smaller than infiltration capacity, in order not toh ave any surface ponding. Spectral induced polarization has been used to infer constitutive parameters from soil samples [Cassiani et al. 2009b]. 2D Richards equation model (Manzini and Ferraris, 2004) has been then calibrated with the measurements. References. Cassiani, G., S. Ferraris, M. Giustiniani, R. Deiana and C.Strobbia, 2009a, Time-lapse surface-to-surface GPR measurements to monitor a controlled infiltration experiment, in press, Bollettino di Geofisica Teorica ed Applicata, Vol. 50, 2 Marzo 2009, pp. 209-226. Cassiani, G., A. Kemna, A.Villa, and E. Zimmermann, 2009b, Spectral induced polarization for the characterization of free-phase hydrocarbon contamination in sediments with low clay content

  2. A precise monitoring of snow surface height in the region of Lambert Glacier basin-Amery Ice Shelf, East Antarctica

    Institute of Scientific and Technical Information of China (English)

    XIAO Cunde; QIN Dahe; BIAN Lingen; ZHOU Xiuji; I. Allison; YAN Ming

    2005-01-01

    The net surface snow accumulation on the Antarctic ice sheet is determined by a combination of precipitation, sublimation and wind redistribution. We present a one-year record of hourly snow-height measurements at LGB69 (70°50'S, 77°04(E,1850 m a.s.l.), east side of Lambert Glacier basin (LGB), and 4 year record at G3 (70°53'S, 69°52'E, 84 m a.s.l.), Amery Ice Shelf (AIS). The measurements were made with ultrasonic sensors mounted on automatic weather stations installed at two sites. The snow accumulation at LGB69 is approximately 70 cm. Throughout the winter, between April and September, there was little change in surface snow height (SSH) at the two sites. The negative SSH change is due to densification at LGB69, and is due to both ablation and densification at G3. The strongest accumulation at two sites occurred during the period between Octobers and March (accounting for 101.6% at LGB69), with four episodic increasing events occurring during 2002 for LGB69, and eight events during 1999-2002 for G3 (2 to 3 events per year). At LGB69, these episodic events coincided with obvious humidity "pulses" and decreases of incoming solar radiation as recorded by the AWS. Observations of the total cloud amount at Davis station, 160 km NNE of LGB69, showed good correlation with major accumulation events recorded at LGB69. There was an obvious anti-correlation between the lowest cloud height at Davis and the daily accumulation rate at LGB69. Although there was no correlation over the total year between wind speed and accumulation at LGB69, large individual accumulation events are associated with episodes of strong wind (>7 m/s), we estimate drift snow may contribute to total SSH up to 35%. Strong accumulation events at LGB69 are associated with major storms in the region and inland transport of moist air masses from the coast.

  3. Principles of snow hydrology

    National Research Council Canada - National Science Library

    DeWalle, David R; Rango, Albert

    2008-01-01

    ... Hydrology describes the factors that control the accumulation, melting, and runoff of water from seasonal snowpacks over the surface of the earth. The book addresses not only the basic principles governing snow in the hydrologic cycle, but also the latest applications of remote sensing, and principles applicable to modelling streamflow from snowmelt across lar...

  4. The use of remotely-sensed canopy variables and ultrasonic snow depth sensors to improve the understanding of forest - snow interactions (Invited)

    Science.gov (United States)

    Varhola, A.; Coops, N.; Teti, P.; Weiler, M.

    2013-12-01

    Current methods to estimate snow accumulation and ablation at the plot and watershed levels can be improved as new technologies offer alternative approaches to more accurately monitor snow dynamics and their drivers. Here we conduct a meta-analysis of snow and vegetation data collected in British Columbia to explore the relationships between a wide range of forest structure variables --obtained from Light Detection and Ranging (LiDAR), hemispherical photography (HP) and Landsat Thematic Mapper-- and several indicators of snow accumulation and ablation estimated from manual snow surveys and ultrasonic range sensors. By merging and standardizing all the ground plot information available in the study area, we demonstrate how LiDAR-derived forest cover above 0.5 m was the variable explaining the highest percentage of absolute peak snow water equivalent (SWE) (33%), while HP-derived leaf area index and gap fraction (45° angle of view) were the best potential predictors of snow ablation rate (SAR) (explaining 57% of variance). This study reveals how continuous SWE data from ultrasonic sensors are fundamental to obtain statistically-significant relationships between snow indicators and structural metrics by increasing mean coefficient of determination by 20% when compared to manual surveys. The relationships between vegetation and some spectral indices from Landsat and snow indicators, not explored before, were almost as high as those shown by LiDAR or HP and thus point towards a new line of research with important practical implications. While the use of different data sources from two snow seasons prevented us from developing models with predictive capacity, a large sample size allowed us to identify outliers that weakened the relationships and suggest improvements for future research. A concise overview of the limitations of this and previous studies is provided along with propositions to consistently improve experimental designs to take advantage of remote sensing

  5. Assessment of dynamic probabilistic methods for mapping snow cover in Québec Canada

    Science.gov (United States)

    De Seve, D.; Perreault, L.; Vachon, F.; Guay, F.; choquette, Y.

    2012-04-01

    Hydro-Quebec is the leader in electricity production in North America and uses hydraulic resources to generate 97% of its overall production where snow represents 30% of its annual energy reserve. Information on snow cover extent (SC) and snow water equivalent (SWE) is crucial for hydrological forecasting, particularly in Nordic regions where a majority of total precipitations falls as snow. Accurate estimation of the spatial distribution of snow cover variables is required to measure the extent of this resource but snow surveys are expensive due to inaccessibility factors and to the large extent nature of the Quebec geography. Consequently, the follow-up of snowmelt is particularly challenging for operational forecasting resulting in the need to develop a new approach to assist forecasters. For improved understanding of the dynamics of snow melting over watersheds and to generate optimized power production, Hydro-Québec's Research Institute (IREQ) has developed expertise in in-situ, remote sensing monitoring and statistical treatment of such data. The main goal of this Hydro-Quebec project is to develop an automatic and dynamic snow mapping system providing a daily snow map by merging remote sensing (AVHRR and SSMI) and in situ data. This paper focuses on the work accomplished on passive microwave SSM/I data to follow up snow cover. In our problematic, it is highly useful to classify snow, more specifically during the snowmelt period. The challenge is to be able to discriminate ground from wet snow as it will react as a black body, therefore, adding noise to global brightness temperature. Two dynamic snow classifiers were developed and tested. For this purpose, channels at 19 and 37 GHz in vertical polarization have been used to feed each model. SWE values from gamma ray in situ stations (GMON) and data snow depth from ultrasonic sensor (SR50) were used to validate the output models. The first algorithm is based on a standard K-mean clustering approach, combined

  6. Application of the Markov Chain Monte Carlo method for snow water equivalent retrieval based on passive microwave measurements

    Science.gov (United States)

    Pan, J.; Durand, M. T.; Vanderjagt, B. J.

    2015-12-01

    Markov Chain Monte Carlo (MCMC) method is a retrieval algorithm based on Bayes' rule, which starts from an initial state of snow/soil parameters, and updates it to a series of new states by comparing the posterior probability of simulated snow microwave signals before and after each time of random walk. It is a realization of the Bayes' rule, which gives an approximation to the probability of the snow/soil parameters in condition of the measured microwave TB signals at different bands. Although this method could solve all snow parameters including depth, density, snow grain size and temperature at the same time, it still needs prior information of these parameters for posterior probability calculation. How the priors will influence the SWE retrieval is a big concern. Therefore, in this paper at first, a sensitivity test will be carried out to study how accurate the snow emission models and how explicit the snow priors need to be to maintain the SWE error within certain amount. The synthetic TB simulated from the measured snow properties plus a 2-K observation error will be used for this purpose. It aims to provide a guidance on the MCMC application under different circumstances. Later, the method will be used for the snowpits at different sites, including Sodankyla, Finland, Churchill, Canada and Colorado, USA, using the measured TB from ground-based radiometers at different bands. Based on the previous work, the error in these practical cases will be studied, and the error sources will be separated and quantified.

  7. Pavement Snow Melting

    Energy Technology Data Exchange (ETDEWEB)

    Lund, John W.

    2005-01-01

    The design of pavement snow melting systems is presented based on criteria established by ASHRAE. The heating requirements depends on rate of snow fall, air temperature, relative humidity and wind velocity. Piping materials are either metal or plastic, however, due to corrosion problems, cross-linked polyethylene pipe is now generally used instead of iron. Geothermal energy is supplied to systems through the use of heat pipes, directly from circulating pipes, through a heat exchanger or by allowing water to flow directly over the pavement, by using solar thermal storage. Examples of systems in New Jersey, Wyoming, Virginia, Japan, Argentina, Switzerland and Oregon are presented. Key words: pavement snow melting, geothermal heating, heat pipes, solar storage, Wyoming, Virginia, Japan, Argentina, Klamath Falls.

  8. Snow Melting and Freezing on Older Townhouses

    DEFF Research Database (Denmark)

    Nielsen, Anker; Claesson, Johan

    2011-01-01

    The snowy winter of 2009/2010 in Scandinavia prompted many newspaper articles on icicles falling from buildings and the risk this presented for people walking below. The problem starts with snow melting on the roof due to heat loss from the building. Melt water runs down the roof and some...... of it will freeze on the overhang. The rest of the water will either run off or freeze in gutters and downpipes or turn into icicles. This paper describes use of a model for the melting and freezing of snow on roofs. Important parameters are roof length, overhang length, heat resistance of roof and overhang......, outdoor and indoor temperature, snow thickness and thermal conductivity. If the snow thickness is above a specific limit value – the snow melting limit- some of the snow will melt. Another interesting limit value is the dripping limit. All the melt water will freeze on the overhang, if the snow thickness...

  9. Geoelectrical monitoring of water movement in the unsaturated zone

    Science.gov (United States)

    Berthold, Susann; Geib, Tobias

    2013-04-01

    To continually track the water movement in the unsaturated zone and monitor groundwater recharge, two geoelectrical profiles were permanently installed in the catchment area of a waterworks. The geoelectrical profiles were set up in areas with different groundwater recharge. One profile was installed on a forest clearing, where the unsaturated zone is eight meters thick and dominated by sand. The second profile was installed in heathland, where the unsaturated zone is eleven meters thick and dominated by fine sand. The profile length for the geoelectrical measurements and the number of electrodes per profile were chosen depending on the depth of the groundwater table. The geoelectrical measurements were carried out autonomously twice a day. Remote data transmission made the data instantaneously available for analysis and evaluation. During the entire period of investigation, that is August 2011 to December 2012, the geoelectrical profiles worked independently with low maintenance. During this period, approximately 800 data sets were recorded at each location. Each individual data set contained several thousand measuring points in the geoelectrical cross section. To handle the large amounts of data and efficiently interpret them, a largely automatic algorithm, the so-called ELMON algorithm, was developed. The algorithm reads in the raw measurement values and allows fast acquisition of incorrect measurements and, where appropriate, initiation of maintenance (for example, to troubleshoot browsing by game). The detected erroneous measurements are automatically removed. Then, the change in soil electrical conductivity is determined via a physically founded calculation method developed in the framework of the project. The change in soil electrical conductivity is represented compared to a reference state, e.g. the day prior to a rain event. Using the ELMON algorithm, the water movement through the unsaturated zone could be monitored over a period of more than a year

  10. Monitoring and modeling of microbial and biological water quality

    Science.gov (United States)

    Microbial and biological water quality informs on the health of water systems and their suitability for uses in irrigation, recreation, aquaculture, and other activities. Indicators of microbial and biological water quality demonstrate high spatial and temporal variability. Therefore, monitoring str...

  11. Service Water and Impoundment Monitoring Database (SWIM1)

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The Service Water and Impoundment Monitoring (SWIM1) database was developed for the purpose of managing water level and water quality (salinity) data for areas...

  12. Service Water and Impoundment Monitoring Database (SWIM2)

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The Service Water and Impoundment Monitoring (SWIM2) database was developed for the purpose of managing water level and water quality (salinity) data for areas...

  13. The stepwise discriminant algorithm for snow cover mapping based on FY-3/MERSI data

    Science.gov (United States)

    Han, Tao; Wang, Dawei; Jiang, Youyan; Wang, Xiaowei

    2013-10-01

    Medium Resolution Spectral Imager (MERSI) on board China's new generation polar orbit meteorological satellite FY- 3A provides a new data source for snow monitoring in large area. As a case study, the typical snow cover of Qilian Mountains in northwest China was selected in this paper to develop the algorithm to map snow cover using FY- 3A/MERSI. By analyzing the spectral response characteristics of snow and other surface elements, as well as each channel image quality on FY-3A/MERSI, the widely used Normalized Difference Snow Index (NDSI) was defined to be computed from channel 2 and channel 7 for this satellite data. Basing on NDSI, a tree-structure prototype version of snow identification model was proposed, including five newly-built multi-spectral indexes to remove those pixels such as forest, cloud shadow, water, lake ice, sand (salty land), or cloud that are usually confused with snow step by step, especially, a snow/cloud discrimination index was proposed to eliminate cloud, apart from use of cloud mask product in advance. Furthermore, land cover land use (LULC) image has been adopted as auxiliary dataset to adjust the corresponding LULC NDSI threshold constraints for snow final determination and optimization. This model is composed as the core of FY-3A/MERSI snow cover mapping flowchart, to produce daily snow map at 250m spatial resolution, and statistics can be generated on the extent and persistence of snow cover in each pixel for time series maps. Preliminary validation activities of our snow identification model have been undertaken. Comparisons of the 104 FY- 3A/MERSI snow cover maps in 2010-2011 snow season with snow depth records from 16 meteorological stations in Qilian Mountains region, the sunny snow cover had an absolute accuracy of 92.8%. Results of the comparison with the snow cover identified from 6 Terra/MODIS scenes showed that they had consistent pixels about 85%. When the two satellite resultant snow cover maps compared with the 6

  14. Impact of intra- versus inter-annual snow depth variation on water relations and photosynthesis for two Great Basin Desert shrubs

    OpenAIRE

    Loik, ME; Griffith, AB; Alpert, H; Concilio, AL; Wade, CE; Martinson, SJ

    2015-01-01

    © 2015, Springer-Verlag Berlin Heidelberg. Snowfall provides the majority of soil water in certain ecosystems of North America. We tested the hypothesis that snow depth variation affects soil water content, which in turn drives water potential (Ψ) and photosynthesis, over 10 years for two widespread shrubs of the western USA. Stem Ψ (Ψstem) and photosynthetic gas exchange [stomatal conductance to water vapor (gs), and CO2 assimilation (A)] were measured in mid-June each year from 2004 to 2013...

  15. Needs assessment to strengthen capacity in water and sanitation research in Africa: experiences of the African SNOWS consortium.

    Science.gov (United States)

    Hunter, Paul R; Abdelrahman, Samira H; Antwi-Agyei, Prince; Awuah, Esi; Cairncross, Sandy; Chappell, Eileen; Dalsgaard, Anders; Ensink, Jeroen H J; Potgieter, Natasha; Mokgobu, Ingrid; Muchiri, Edward W; Mulogo, Edgar; van der Es, Mike; Odai, Samuel N

    2014-12-15

    Despite its contribution to global disease burden, diarrhoeal disease is still a relatively neglected area for research funding, especially in low-income country settings. The SNOWS consortium (Scientists Networked for Outcomes from Water and Sanitation) is funded by the Wellcome Trust under an initiative to build the necessary research skills in Africa. This paper focuses on the research training needs of the consortium as identified during the first three years of the project. We reviewed the reports of two needs assessments. The first was a detailed needs assessment led by one northern partner, with follow-up visits which included reciprocal representation from the African universities. The second assessment, led by another northern partner, focused primarily on training needs. The reports from both needs assessments were read and stated needs were extracted and summarised. Key common issues identified in both assessments were supervisory skills, applications for external research funding, research management, and writing for publication in the peer-reviewed scientific literature. The bureaucratisation of university processes and inconsistencies through administration processes also caused problems. The lack of specialist laboratory equipment presented difficulties, particularly of inaccessibility through a lack of skilled staff for operation and maintenance, and of a budget provision for repairs and running costs. The lack of taught PhD modules and of research training methods also caused problems. Institutionally, there were often no mechanisms for identifying funding opportunities. On the other hand, grantees were often unable to understand or comply with the funders' financial and reporting requirements and were not supported by their institution. Skills in staff recruitment, retention, and performance were poor, as were performance in proposal and paper writing. The requirements for ethical clearance were often not known and governance issues not understood

  16. Guidelines for use of water-quality monitors

    Science.gov (United States)

    Gordon, A. Brice; Katzenbach, Max S.

    1983-01-01

    This manual contains methods and procedures used by the U.S. Geological Survey (USGS) for collecting specific conductance, dissolved oxygen, water temperature, and pH data for ground water, streams, lakes, reservoirs, and estuaries by means of permanently installed, continuously recording, water quality monitors. The topics discussed include the selection of monitoring sites, selection and installation of shelters and equipment, and standard methods of calibration, operation and maintenance of water-quality monitors.

  17. Macroscopic modeling of heat and water vapor transfer with phase change in dry snow based on an upscaling method: Influence of air convection

    Science.gov (United States)

    Calonne, N.; Geindreau, C.; Flin, F.

    2015-12-01

    At the microscopic scale, i.e., pore scale, dry snow metamorphism is mainly driven by the heat and water vapor transfer and the sublimation-deposition process at the ice-air interface. Up to now, the description of these phenomena at the macroscopic scale, i.e., snow layer scale, in the snowpack models has been proposed in a phenomenological way. Here we used an upscaling method, namely, the homogenization of multiple-scale expansions, to derive theoretically the macroscopic equivalent modeling of heat and vapor transfer through a snow layer from the physics at the pore scale. The physical phenomena under consideration are steady state air flow, heat transfer by conduction and convection, water vapor transfer by diffusion and convection, and phase change (sublimation and deposition). We derived three different macroscopic models depending on the intensity of the air flow considered at the pore scale, i.e., on the order of magnitude of the pore Reynolds number and the Péclet numbers: (A) pure diffusion, (B) diffusion and moderate convection (Darcy's law), and (C) strong convection (nonlinear flow). The formulation of the models includes the exact expression of the macroscopic properties (effective thermal conductivity, effective vapor diffusion coefficient, and intrinsic permeability) and of the macroscopic source terms of heat and vapor arising from the phase change at the pore scale. Such definitions can be used to compute macroscopic snow properties from 3-D descriptions of snow microstructures. Finally, we illustrated the precision and the robustness of the proposed macroscopic models through 2-D numerical simulations.

  18. Monitoring of Population Density of Snow Leopard in Xinjiang.%新疆雪豹种群密度监测方法探讨

    Institute of Scientific and Technical Information of China (English)

    马鸣; 徐峰; Bariushaa Munkhtsog; 吴逸群; Tomas McCarthy; Kyle McCarthy

    2011-01-01

    the group began to take infrared photos, conducted survey of food sources of the leopards, investigated fur market and paths of trading, and cases of killing, and carry out civil survey through questionnaire, non-government organization community service and research on conflicts between grazing and wildlife protection. A total of 36 infrared cameras were laid out, working a total of about 2 094 days or 50 256 hours. A total 71 rolls of film were collected and developed, including 32 clear pictures of snow leopards, thus making up a shooting rate or capture rate of 1.53%. It was ascertained that in Tomur Peak area, there were 5 -8 snow leopards roaming within a range of 250 km2,forming a population density of 2.0 -3.2 per 100 km2. After comparing the various monitoring results, the advantages and limitations of different monitoring methods have been discussed.

  19. SNOW CLEARING

    CERN Multimedia

    Groupe de Transport/Transport Group

    1999-01-01

    In order to facilitate snow-clearing operations, which commence at 4.30 every morning, drivers of CERN vehicles are kindly requested to group their cars together in the car parks. This will greatly help us in our work. Thank you for your co-operation.Transport Group / ST-HMTel. 72202

  20. Snow clearance

    CERN Multimedia

    Mauro Nonis

    2005-01-01

    In reply to the numerous questions received, we should like to inform you of the actions and measures taken in an effort to maintain the movements of vehicles and pedestrians since the heavy snow fall on Sunday 23 January. Our contractor's employees began clearing the snow during the morning of Sunday 23 January on the main CERN sites (Meyrin, Prévessin), but an accident prevented them from continuing. The vehicle in question was repaired by Monday morning when two other vehicles joined it to resume snow clearing; priority was given to access points to the main sites and the LHC sites, as well as to the main roads inside the sites. The salt sprinklers were also brought into action that same day; the very low temperature during the night from Monday to Tuesday prevented the snow from melting and compacted the ice; the continuing cold during the day on Tuesday (-6°C at 10:00 on the Meyrin site) meant that all efforts to remove the ice were doomed to failure. In order to ensure more efficie...

  1. Using ground penetrating radar to assess the variability of snow water equivalent and melt in a mixed canopy forest, Northern Colorado

    Science.gov (United States)

    Webb, Ryan W.

    2017-09-01

    Snow is an important environmental variable in headwater systems that controls hydrological processes such as streamflow, groundwater recharge, and evapotranspiration. These processes will be affected by both the amount of snow available for melt and the rate at which it melts. Snow water equivalent (SWE) and snowmelt are known to vary within complex subalpine terrain due to terrain and canopy influences. This study assesses this variability during the melt season using ground penetrating radar to survey multiple plots in northwestern Colorado near a snow telemetry (SNOTEL) station. The plots include south aspect and flat aspect slopes with open, coniferous (subalpine fir, Abies lasiocarpa and engelman spruce, Picea engelmanii), and deciduous (aspen, populous tremuooides) canopy cover. Results show the high variability for both SWE and loss of SWE during spring snowmelt in 2014. The coefficient of variation for SWE tended to increase with time during snowmelt whereas loss of SWE remained similar. Correlation lengths for SWE were between two and five meters with melt having correlation lengths between two and four meters. The SNOTEL station regularly measured higher SWE values relative to the survey plots but was able to reasonably capture the overall mean loss of SWE during melt. Ground Penetrating Radar methods can improve future investigations with the advantage of non-destructive sampling and the ability to estimate depth, density, and SWE.

  2. Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments

    Science.gov (United States)

    Griessinger, Nena; Seibert, Jan; Magnusson, Jan; Jonas, Tobias

    2016-09-01

    In Alpine catchments, snowmelt is often a major contribution to runoff. Therefore, modeling snow processes is important when concerned with flood or drought forecasting, reservoir operation and inland waterway management. In this study, we address the question of how sensitive hydrological models are to the representation of snow cover dynamics and whether the performance of a hydrological model can be enhanced by integrating data from a dedicated external snow monitoring system. As a framework for our tests we have used the hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) in the version HBV-light, which has been applied in many hydrological studies and is also in use for operational purposes. While HBV originally follows a temperature-index approach with time-invariant calibrated degree-day factors to represent snowmelt, in this study the HBV model was modified to use snowmelt time series from an external and spatially distributed snow model as model input. The external snow model integrates three-dimensional sequential assimilation of snow monitoring data with a snowmelt model, which is also based on the temperature-index approach but uses a time-variant degree-day factor. The following three variations of this external snow model were applied: (a) the full model with assimilation of observational snow data from a dense monitoring network, (b) the same snow model but with data assimilation switched off and (c) a downgraded version of the same snow model representing snowmelt with a time-invariant degree-day factor. Model runs were conducted for 20 catchments at different elevations within Switzerland for 15 years. Our results show that at low and mid-elevations the performance of the runoff simulations did not vary considerably with the snow model version chosen. At higher elevations, however, best performance in terms of simulated runoff was obtained when using the snowmelt time series from the snow model, which utilized data assimilation

  3. Spatial and temporal variability in seasonal snow density

    KAUST Repository

    Bormann, Kathryn J.

    2013-03-01

    Snow density is a fundamental physical property of snowpacks used in many aspects of snow research. As an integral component in the remote sensing of snow water equivalent and parameterisation of snow models, snow density may be used to describe many important features of snowpack behaviour. The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data. Total winter precipitation was shown to be the most prominent driver of snow densification rates, with mean air temperature and melt-refreeze events also found to be locally significant. Densification rate variance is very high at Australian sites, very low throughout the former Soviet Union and between these extremes throughout much of the US. Spring snow densities were estimated using a statistical model with climate variable inputs and best results were achieved when snow types were treated differently. Given the importance of snow density information in many snow-related research disciplines, this work has implications for current methods of converting snow depths to snow water equivalent, the representation of snow dynamics in snow models and remote sensing applications globally. © 2013 Elsevier B.V.

  4. The value of snow cover

    Science.gov (United States)

    Sokratov, S. A.

    2009-04-01

    Snow is the natural resource, like soil and water. It has specific properties which allow its use not just for skiing but also for houses cooling in summer (Swedish experience), for air fields construction (Arctic and Antarctic), for dams (north of Russia), for buildings (not only snow-houses of some Polar peoples but artistic hotel attracting tourists in Sweden), and as art material (Sapporo snow festival, Finnish events), etc. "Adjustment" of snow distribution and amount is not only rather common practice (avalanche-protection constructions keeping snow on slopes) but also the practice with long history. So-called "snow irrigation" was used in Russia since XIX century to protect winter crop. What is now named "artificial snow production", is part of much larger pattern. What makes it special—it is unavoidable in present climate and economy situation. 5% of national income in Austria is winter tourism. 50% of the economy in Savoy relay on winter tourism. In terms of money this can be less, but in terms of jobs and income involved this would be even more considerable in Switzerland. As an example—the population of Davos is 14000 in Summer and 50000 in Winter. Skiing is growing business. In present time you can find ski slopes in Turkey and Lebanon. To keep a cite suitable for attracting tourists you need certain amount of sunny days and certain amount of snow. The snow cannons are often the only way to keep a place running. On the other hand, more artificial snow does not necessary attract more tourists, while heavy natural snowfall does attract them. Artificial snow making is costly and requires infrastructure (ponds and electric lines) with very narrow range of weather conditions. Related companies are searching for alternatives and one of them can be "weather regulation" by distribution of some chemical components in clouds. It did not happen yet, but can happen soon. The consequences of such interference in Nature is hardly known. The ski tourism is not the

  5. Residual water bactericide monitor development program

    Science.gov (United States)

    1973-01-01

    A silver-ion bactericidal monitor is considered for the Space Shuttle Potable Water System. Potentiometric measurement using an ion-selective electrode is concluded to be the most feasible of available techniques. Four commercially available electrodes and a specially designed, solid-state, silver-sulfide electrode were evaluated for their response characteristics and suitability for space use. The configuration of the solid-state electrode with its Nernstian response of 10 to 10,000 ppb silver shows promise for use in space. A pressurized double-junction reference electrode with a quartz-fiber junction and a replaceable bellows electrolyte reservoir was designed verification-tested, and paired with a solid-state silver-sulfide electrode in a test fixture.

  6. An Expert System Applied in Construction Water Quality Monitoring

    Directory of Open Access Journals (Sweden)

    Leila Ooshaksaraie

    2011-01-01

    Full Text Available Problem statement: An untoward environmental impact of urban growth in Malaysia has been deterioration in a number of watercourses due to severe siltation and other pollutants from the construction site. Water quality monitoring is a plan for decision makers to take into account the adverse impacts of construction activities on the receiving water bodies. It is also a process for collecting the construction water quality monitoring, baseline data and standard level. Approach: In recent years, expert systems have been used extensively in different applications areas including environmental studies. In this study, expert system software -CWQM- developed by using Microsoft Visual Basic was introduced. CWQM to be used for water quality monitoring during construction activities was designed based on the legal process in Malaysia. Results: According to the water quality monitoring regulation enacted in Malaysia, construction activities require mandatory water quality monitoring plans duly approved by Department of Environment before staring activities. CWQM primarily aims to provide educational and support system for water quality monitoring engineers and decision-makers during construction activities. It displays water quality monitoring plan in report form, water sampling location in GIS format and water quality monitoring data in graph. Conclusion: When the use of CWQM in construction water quality monitoring becomes widespread, it is highly possible that it will be benefited in terms of having more accurate and objective decisions on construction projects which are mainly focused on reducing the stormwater pollution.

  7. Real time water chemistry monitoring and diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Gaudreau, T.M.; Choi, S.S. [EPRIsolutions, Palo Alto, CA (United States)

    2002-07-01

    EPRI has produced a real time water chemistry monitoring and diagnostic system. This system is called SMART ChemWorks and is based on the EPRI ChemWorks codes. System models, chemistry parameter relationships and diagnostic approaches from these codes are integrated with real time data collection, an intelligence engine and Internet technologies to allow for automated analysis of system chemistry. Significant data management capabilities are also included which allow the user to evaluate data and create automated reporting. Additional features have been added to the system in recent years including tracking and evaluation of primary chemistry as well as the calculation and tracking of primary to secondary leakage in PWRs. This system performs virtual sensing, identifies normal and upset conditions, and evaluates the consistency of on-line monitor and grab sample readings. The system also makes use of virtual fingerprinting to identify the cause of any chemistry upsets. This technology employs plant-specific data and models to determine the chemical state of the steam cycle. (authors)

  8. Snow economics and the NOHRSC Snow Information System (SNOW-INFO) for the United States

    Science.gov (United States)

    Carroll, T.; Cline, D.; Berkowitz, E.; Savage, D.

    2003-04-01

    The National Operational Hydrologic Remote Sensing Center (NOHRSC) in the National Weather Service (NWS), National Oceanic and Atmospheric Administration (NOAA), provides remotely sensed and modeled snow cover products and data sets to support river and flood forecasting in the United States and also to enhance the national economy. Nationwide, on average, about 16% of the total annual precipitation occurs as snowfall. Many sectors of the U.S. economy rely on surface water from snowfall for production, including manufacturing, mining, thermoelectric power, agriculture, and others. Snow contributes 1.7 trillion annually (16%) to the Nation's gross domestic product (GDP) of 10.5 trillion. Manufacturing is by far the largest contributor to the Nation's GDP and is also the Nation's largest surface-water user. The contribution of snow to manufacturing revenue totals 1.6 trillion annually for the Nation and ranges from just a few billion dollars in the southeastern U.S. to over 200 billion each in Michigan and New York. Hydropower supplies about 10% of the electricity used in the United States, enough to serve the needs of 28 million people. Annual hydroelectric power production exceeds 250 billion kilowatt-hours with the contribution from snow exceeding 6 billion in energy revenue each year (i.e., 30% of the Nation's annual hydroelectric production of 20 billion). Seasonal snowpacks are an essential component of agricultural water supplies throughout most of the U.S. and provide much of the surface water used to irrigate over 55 million acres of U.S. farmland each year. Agriculture net revenue supported by snowmelt exceeds 33 billion annually. Surface water supplies are essential for thermoelectric power generation by coal-fired, oil-fired, and nuclear power plants. Providing about 90% of the Nation's electricity supply, thermoelectric power revenues exceed 215 billion each year while water from snow contributes about 25 billion to this revenue annually. With 1

  9. A Water Quality Monitoring Programme for Schools and Communities

    Science.gov (United States)

    Spellerberg, Ian; Ward, Jonet; Smith, Fiona

    2004-01-01

    A water quality monitoring programme for schools is described. The purpose of the programme is to introduce school children to the concept of reporting on the "state of the environment" by raising the awareness of water quality issues and providing skills to monitor water quality. The programme is assessed and its relevance in the…

  10. A Water Quality Monitoring Programme for Schools and Communities

    Science.gov (United States)

    Spellerberg, Ian; Ward, Jonet; Smith, Fiona

    2004-01-01

    A water quality monitoring programme for schools is described. The purpose of the programme is to introduce school children to the concept of reporting on the "state of the environment" by raising the awareness of water quality issues and providing skills to monitor water quality. The programme is assessed and its relevance in the…

  11. Investigating the role of topography on snow cover duration and distribution in the Italian Apennines by means of MODIS data

    Science.gov (United States)

    Da Ronco, Pierfrancesco; Piperno, Peter; Avanzi, Francesco; De Michele, Carlo

    2016-04-01

    Snow cover plays an important role in the water cycle influencing water resource availability. As the seasonal cycle of snowpack is highly sensitive to variations of precipitation and temperature, the expected future changes in the atmospheric forcings may impact on the timing of snow accumulation and melt. In this work we investigated the effects of the complex topography of a mountain range on snow dynamics by means of MODIS data of snow cover (2003 - 2014) and a 500 m-resolution Digital Elevation Model. The study area is the central Apennines, having peaks in elevation over 2800 m asl in the Majella and Gran Sasso massifs. Firstly, we carried out a validation of MOD10A1/MYD10A1 SCA products comparing ground data of snow depth measured by seven monitoring stations with the remote sensing time series of snow covered area. The comparison confirms the accuracy of MODIS products in snow cover mapping in mountain areas, in agreement with what found in other regions around the world. Then, we subjected Aqua and Terra snow cover maps to a cloud removal procedure ensuring a pixel-scale estimate of snow cover presence at daily temporal resolution. The new cloud-free dataset was used for deriving trends of snow cover duration and snow cover distribution for different classes of aspect, slope and concavity within the mountain part of the domain. The analysis has allowed us to quantify the impacts of these topographic features on the accumulation and melting processes. In particular, the north-facing slopes show a lower snowline altitude in all seasons and a longer snow duration in spring.

  12. Monitoring drinking water quality in South Africa: Designing ...

    African Journals Online (AJOL)

    In South Africa, the management and monitoring of drinking water quality is governed by policies and regulations based .... The measures for improvement of monitoring were: .... purposes, the effectiveness and desirability of a government.

  13. Radio Frequency Based Water Level Monitor and Controller for ...

    African Journals Online (AJOL)

    Radio Frequency Based Water Level Monitor and Controller for Residential Applications. ... Nigerian Journal of Technology ... This paper elucidates a radio frequency (RF) based transmission and reception system used to remotely monitor ...

  14. Initial Survey Instructions for Spring Water Monitoring : Flow

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Initial survey instructions for the Spring Water Monitoring - Flow 1.02 survey at Fish Springs National Wildlife Refuge. This coop baseline monitoring survey has...

  15. Characterization of Electrospray Ionization for Spaceflight Water Monitoring Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Current methods for monitoring the water used on the ISS rely heavily on ground analysis of archival samples. Air monitors presently on board the ISS could be used...

  16. 融雪剂对地表水及地下水的影响%The Influence of Snow-melting Agent on Surface Water and Groundwater

    Institute of Scientific and Technical Information of China (English)

    蔡雯璐

    2011-01-01

    The changes of aquatic environment after using snow-melting agent on highway are studied by detecting the relevant indexes of surface water and groundwater samples.The result shows that: the using of snow-melting agent increases the content of chlorine ion and other relevant metal salt ions in surface water and groundwater,among which surface water is influenced more seriously by snow-melting agent and the highest increasing rate of chloride content is 56.77%.%通过对地表水和地下水样品相关指标进行检测,对公路在使用融雪剂后水体环境的变化情况进行研究。结果表明:融雪剂的使用提高了地表水和地下水中的氯离子和其它相关金属盐离子的含量。其中地表水受融雪剂影响较大,氯化物含量增加率最高为56.77%。

  17. Monitoring of recharge water quality under woodland

    Science.gov (United States)

    Krajenbrink, G. J. W.; Ronen, D.; Van Duijvenbooden, W.; Magaritz, M.; Wever, D.

    1988-03-01

    The study compares the quality of groundwater in the water table zone and soil moisture below the root zone, under woodland, with the quality of the regional precipitation. The water quality under forest shows evidence of the effect of atmospheric deposition of acidic components (e.g. SO 2) and ammonia volatilized from land and feed lots. Detailed chemical profiles of the upper meter of groundwater under different plots of forest, at varying distances from cultivated land, were obtained with a multilayer sampler, using the dialysis-cell method. Porous ceramic cups and a vacuum method were used to obtain soil moisture samples at 1.20 m depth under various types of trees, an open spot and arable land, for the period of a year. The investigation took place in the recharge area of a pumping station with mainly mixed forest, downwind of a vast agricultural area with high ammonia volatilization and underlain by an ice-deformed aquifer. Very high NO -3 concentrations were observed in soil moisture and groundwater (up to 21 mg Nl -1) under coniferous forest, especially in the border zone. This raises the question of the dilution capacity of recharge water under woodland in relation to the polluted groundwater under farming land. The buffering capacity of the unsaturated zone varies substantially and locally a low pH (4.5) was observed in groundwater. The large variability of leachate composition on different scales under a forest and the lesser but still significant concentration differences in the groundwater prove the importance of a monitoring system for the actual solute flux into the groundwater.

  18. Application of Snpp/viirs Data in Near Real-Time Supra-Snow Flood Detection

    Science.gov (United States)

    Li, S.; Sun, D.; Goldberg, M.; Sjoberg, B.; Plumb, E. W.; Holloway, E.; Lindsey, S.; Kreller, M.

    2015-12-01

    Supra-snow/ice flood is very common in high latitude areas from winter to spring break-up seasons along rivers flowing to even higher latitude areas, but this flood type doesn't draw much attention due to poor ground conditions for river watch and ground observations. Satellite data from SNPP/VIIRS (Suomi-National Polar-orbit Partnership/Visible/Infrared Imager Radiometer Suite) instead have shown great advantages in supra-snow/ice flood detection due to its large swath coverage, multiple daily observations in high latitude areas and moderate spatial resolution. Thus, methods for supra-snow/ice water detection were developed to detect near real-time supra-snow/ice floods automatically using SNPP/VIIRS imagery. The methods were mainly based on spectral features of supra-snow/ice floodwater, assisting by geometry-based algorithm and object-based algorithm to remove cloud shadows and terrain shadows over snow/ice surface. The detected supra-snow/ice floodwater was further applied in water fraction retrieval for better representation of flood extent using a modified histogram method based on linear combination model. The developed methods were successfully applied in dynamic monitoring of 2015's supra-snow/ice flood along Sag River in Alaska, which was claimed as a state disaster by Alaska state government, and further tested with more than 1000 VIIRS granules year around. Analyses through visual inspection with VIIRS false-color composite images and quantitative comparison with Landsat-8 OLI images show promising and robust performance in detection of supra-snow/ice floodwater, indicating a high feasibility for the method to be applied in operations for near real-time supra-snow/ice flood detection.

  19. Estimating Snow Budget of Karaj Dam Reservoir

    Directory of Open Access Journals (Sweden)

    Manijeh G. Tali

    2009-01-01

    Full Text Available Problem statement: Most of the cold period precipitation of Karaj Basin falls in the form of snow. This snow and its run off are important to the dam and the local needs such as agriculture and the drinking water of Tehran. But due to the scarcity and in some elevations the lack of weather stations, measuring this snow cover and its run off is difficult. We have decided to estimate the amount of this snow cover by using surrogate methods such as satellite images of MODIS and temperature thresholds. Approach: To estimate the snow water budget of the Karaj Dam Reservoir Basin, first a temperature threshold of 3° Celsius was defined according to the analysis of daily temperature and precipitation values of Nesa station during 1960-2000. The elevation of this temperature was as low as 1590 m in February and 5734 m in August. During each month the melting snow was computed over the area between 3 and zero degrees Celsius and precipitation below zero degrees was considered as permanent snow cover. The precipitation of areas above 3° was computed as rain. Using this temperature threshold and the DEM map of the basin we estimated the snow cover and snow melt water of the basin. The snow cover area on the MODIS images was estimated and compared with that computed from temperature threshold. Both methods gave relatively similar results. At the end the snow melt water of the whole cold period was calculated and added up to estimate the total snow water budget. Results: The results showed that during the study months most (67.7% of the precipitation comes in the form of snow. And most of this snow (97.5% melts during months March and onward. Its monthly distributions are 3.8% in March, 22.7% in April and 71% in May. The total snow water entering the dam was about 181.73 million cubic meters. Conclusion: The comparison of the results from temperature thresholds with the MODIS images snow cover showed very little and negligible discrepancy. Therefore, this

  20. Drought and Snow: Analysis of Drivers, Processes and Impacts of Streamflow Droughts in Snow-Dominated Regions

    Science.gov (United States)

    Van Loon, Anne; Laaha, Gregor; Van Lanen, Henny; Parajka, Juraj; Fleig, Anne; Ploum, Stefan

    2016-04-01

    reservoir levels and, consequently, on drinking water and electricity production. Snow storage therefore, is an important factor to consider in drought monitoring, prediction and management.

  1. Dazzled by Ice and Snow: Improving Medium Spatial Resolution Ocean Color Images in Arctic Waters

    Science.gov (United States)

    Goyens, Clemence; Belanger, Simon; Babin, Marcel

    2016-08-01

    Ocean color sensors carried on-board satellites represent a valuable tool providing synoptic views of extreme environments such as the Arctic Ocean. However, in icy waters inaccuracies are frequent due to, among others, adjacent and sub-pixel sea-ice contamination. Therefore, there is a need to improve atmospheric correction (AC) algorithms to ensure accurate ocean color images in the vicinity of the ice edge. The present study compares the performance of different AC methods through an in-situ-satellite match-up exercise and investigates the possibility to improve these algorithms in presence of sea-ice floes. Results confirm the large errors resulting from sea-ice contamination and illustrate the difficulty in improving these algorithms due to, among others, the optically complex waters encountered in the Arctic Ocean.

  2. A stratification model of surface snow at Dome Fuji Station, Antarctica

    OpenAIRE

    2002-01-01

    A stratification model of surface snow on the ice sheet, which includes snow density evolution, is proposed. Using the temperature profile in the surface snow layer obtained at Dome Fuji Station, Antarctica, snow density evolution under various accumulation conditions was simulated. It is demonstrated that water vapor diffusion is very important for the snow density evolution, and temperature and accumulation at the snow surface are the most important factors that determine the future snow de...

  3. A stratification model of surface snow at Dome Fuji Station, Antarctica

    OpenAIRE

    2002-01-01

    A stratification model of surface snow on the ice sheet, which includes snow density evolution, is proposed. Using the temperature profile in the surface snow layer obtained at Dome Fuji Station, Antarctica, snow density evolution under various accumulation conditions was simulated.It is demonstrated that water vapor diffusion is very important for the snow density evolution, and temperature and accumulation at the snow surface are the most important factors that determine the future snow den...

  4. 'Snow Queen' Animation

    Science.gov (United States)

    2008-01-01

    This animation consists of two close-up images of 'Snow Queen,' taken several days apart, by the Robotic Arm Camera (RAC) aboard NASA's Phoenix Mars Lander. Snow Queen is the informal name for a patch of bright-toned material underneath the lander. Thruster exhaust blew away surface soil covering Snow Queen when Phoenix landed on May 25, 2008, exposing this hard layer comprising several smooth rounded cavities beneath the lander. The RAC images show how Snow Queen visibly changed between June 15, 2008, the 21st Martian day, or sol, of the mission and July 9, 2008, the 44th sol. Cracks as long as 10 centimeters (about four inches) appeared. One such crack is visible at the left third and the upper third of the Sol 44 image. A seven millimeter (one-third inch) pebble or clod appears just above and slightly to the right of the crack in the Sol 44 image. Cracks also appear in the lower part of the left third of the image. Other pieces noticeably shift, and some smooth texture has subtly roughened. The Phoenix team carefully positioned and focused RAC the same way in both images. Each image is about 60 centimeters, or about two feet, wide. The object protruding in from the top on the right half of the images is Phoenix's thermal and electrical conductivity probe. Snow Queen and other ice exposed by Phoenix landing and trenching operations on northern polar Mars is the first time scientists have been able to monitor Martian ice at a place where temperatures are cold enough that the ice doesn't immediately sublimate, or vaporize, away. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  5. Storing snow for the next winter: Two case studies on the application of snow farming.

    Science.gov (United States)

    Grünewald, Thomas; Wolfsperger, Fabian

    2016-04-01

    Snow farming is the conservation of snow during the warm half-year. This means that large piles of snow are formed in spring in order to be conserved over the summer season. Well-insulating materials such as chipped wood are added as surface cover to reduce melting. The aim of snow farming is to provide a "snow guaranty" for autumn or early winter - this means that a specific amount of snow will definitively be available, independent of the weather conditions. The conserved snow can then be used as basis for the preparation of winter sports grounds such as cross-country tracks or ski runs. This helps in the organization of early winter season sport events such as World Cup races or to provide appropriate training conditions for athletes. We present a study on two snow farming projects, one in Davos (Switzerland) and one in the Martell valley of South Tyrol. At both places snow farming has been used for several years. For the summer season 2015, we monitored both snow piles in order to assess the amount of snow conserved. High resolution terrestrial laser scanning was performed to measure snow volumes of the piles at the beginning and at the end of the summer period. Results showed that only 20% to 30 % of the snow mass was lost due to ablation. This mass loss was surprisingly low considering the extremely warm and dry summer. In order to identify the most relevant drivers of snow melt we also present simulations with the sophisticated snow cover models SNOWPACK and Alpine3D. The simulations are driven by meteorological input data recorded in the vicinity of the piles and enable a detailed analysis of the relevant processes controlling the energy balance. The models can be applied to optimize settings for snow farming and to examine the suitability of new locations, configurations or cover material for future snow farming projects.

  6. Ground-water monitoring sites for Carson Valley, Nevada

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This data set contains the monitoring sites where water levels were collected and used to develop a spatial ground-water data base in Carson Valley, west-central...

  7. The influence of snow sublimation and meltwater evaporation on δD of water vapor in the atmospheric boundary layer of central Europe

    Science.gov (United States)

    Christner, Emanuel; Kohler, Martin; Schneider, Matthias

    2017-01-01

    Post-depositional fractionation of stable water isotopes due to fractionating surface evaporation introduces uncertainty to various isotope applications such as the reconstruction of paleotemperatures, paleoaltimetry, and the investigation of groundwater formation. In this study, we investigate isotope fractionation at snow-covered moisture sources by combining 17 months of observations of isotope concentration ratios [HD16O] / [H216O] in low-level water vapor in central Europe with a new Lagrangian isotope model. The isotope model is capable of reproducing variations of the observed isotope ratios with a correlation coefficient R of 0.82. Observations from 38 days were associated with cold snaps and moisture uptake in snow-covered regions. Deviations between modeled and measured isotope ratios during the cold snaps were related to differences in skin temperatures (Tskin). Analysis of Tskin provided by the Global Data Assimilation System (GDAS) of the NCEP implies the existence of two regimes of Tskin with different types of isotope fractionation during evaporation: a cold regime with Tskin studies at snow-covered sites are needed to better constrain the Tsubl,max and to further investigate isotope fractionation in the two regimes.

  8. MOBILLAB-NIVA - a complete station for monitoring water quality

    OpenAIRE

    A. Henriksen; Røgeberg, E.; Andersen, S.; Veidel, A.

    1986-01-01

    MOBILLAB-NIVA is a complete mobile station for monitoring water quality with telemetric transmission of recorded data to a central receiving station. It is intended for use in studies of rapid changes in water quality and its effects on aquatic life and short term studies to decide on water quality monitoring strategy. The present version of Mobillab-niva is specially designed to study effects of acid inputs on water chemistry, fish and invertebrates. The station is equipped with physical and...

  9. Ground water and snow sensor based on directional detection of cosmogenic neutrons

    Energy Technology Data Exchange (ETDEWEB)

    Cooper, Robert Lee [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Marleau, Peter [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Griffin, Patrick J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2011-06-01

    A fast neutron detector is being developed to measure the cosmic ray neutron flux in order to measure soil moisture. Soil that is saturated with water has an enhanced ability to moderate fast neutrons, removing them from the backscatter spectrum. The detector is a two-element, liquid scintillator detector. The choice of liquid scintillator allows rejection of gamma background contamination from the desired neutron signal. This enhances the ability to reconstruct the energy and direction of a coincident neutron event. The ability to image on an event-by-event basis allows the detector to selectively scan the neutron flux as a function of distance from the detector. Calibrations, simulations, and optimization have been completed to understand the detector response to neutron sources at variable distances and directions. This has been applied to laboratory background measurements in preparation for outdoor field tests.

  10. Real-time estimation of snow water equivalent in the Upper Colorado River Basin using MODIS-based SWE Reconstructions and SNOTEL data

    Science.gov (United States)

    Schneider, Dominik; Molotch, Noah P.

    2016-10-01

    Changes in climate necessitate improved snowpack information to better represent anomalous distributions of snow water equivalent (SWE) and improve water resource management. We estimate the spatial distribution of SWE for the Upper Colorado River basin weekly from January to June 2001-2012 in quasireal-time by two regression techniques: a baseline regression of in situ operationally measured point SWE using only physiographic information and regression of these in situ points combining both physiographic information and historical SWE patterns from a remote sensing-based SWE reconstruction model. We compare the baseline regression approach to our new regression in the context of spatial snow surveys and operational snow measuring stations. When compared to independent distributed snow surveys, the new regression reduces the bias of SWE estimates from -5.5% to 0.8%, and RMSE of the SWE estimates by 8% from 0.25 m to 0.23 m. Notable improvements were observed in alpine terrain with bias declining from -38% to only 3.4%, and RMSE was reduced by 13%, from 0.47 to 0.41 m. The mean increase in cross-validated r2 for the new regression compared to the baseline regression is from 0.22 to 0.33. The largest increase in r2 in any one year is 0.19, an 83% improvement. The new regression estimates, on average, 31% greater SWE depth than the baseline regression in areas above 3000 m elevation, which contributes up to 66% of annual SWE volume in the driest year. This indicates that the historical SWE patterns from the reconstruction adds information to the interpolation beyond the physiographic conditions represented by the SNOTEL network. Given that previous works using SWE reconstructions were limited to retrospective analyses by necessity, the work presented here represents an important contribution in that it extends SWE reconstructions to real-time applications and illustrates that doing so significantly improves the accuracy of SWE estimates.

  11. Value of long-term streamflow forecasts to reservoir operations for water supply in snow-dominated river catchments

    Science.gov (United States)

    Anghileri, D.; Voisin, N.; Castelletti, A.; Pianosi, F.; Nijssen, B.; Lettenmaier, D. P.

    2016-06-01

    We present a forecast-based adaptive management framework for water supply reservoirs and evaluate the contribution of long-term inflow forecasts to reservoir operations. Our framework is developed for snow-dominated river basins that demonstrate large gaps in forecast skill between seasonal and inter-annual time horizons. We quantify and bound the contribution of seasonal and inter-annual forecast components to optimal, adaptive reservoir operation. The framework uses an Ensemble Streamflow Prediction (ESP) approach to generate retrospective, one-year-long streamflow forecasts based on the Variable Infiltration Capacity (VIC) hydrology model. We determine the optimal sequence of daily release decisions using the Model Predictive Control (MPC) optimization scheme. We then assess the forecast value by comparing system performance based on the ESP forecasts with the performances based on climatology and perfect forecasts. We distinguish among the relative contributions of the seasonal component of the forecast versus the inter-annual component by evaluating system performance based on hybrid forecasts, which are designed to isolate the two contributions. As an illustration, we first apply the forecast-based adaptive management framework to a specific case study, i.e., Oroville Reservoir in California, and we then modify the characteristics of the reservoir and the demand to demonstrate the transferability of the findings to other reservoir systems. Results from numerical experiments show that, on average, the overall ESP value in informing reservoir operation is 35% less than the perfect forecast value and the inter-annual component of the ESP forecast contributes 20-60% of the total forecast value.

  12. Simulation of water available for runoff in clearcut forest openings during rain-on-snow events in the western Cascade Range of Oregon and Washington

    Science.gov (United States)

    van Heeswijk, Marijke; Kimball, J.S.; Marks, Danny

    1996-01-01

    Rain-on-snow events are common on mountain slopes within the transient-snow zone of the Pacific Northwest. These events make more water available for runoff than does precipitation alone by melting the snowpack and by adding a small amount of condensate to the snowpack. In forest openings (such as those resulting from clearcut logging), the amount of snow that accumulates and the turbulent- energy input to the snowpack are greater than below forest stands. Both factors are believed to contribute to a greater amount of water available for runoff during rain-on-snow events in forest openings than forest stands. Because increased water available for runoff may lead to increased downstream flooding and erosion, knowledge of the amount of snowmelt that can occur during rain on snow and the processes that control snowmelt in forest openings is useful when making land-use decisions. Snow accumulation and melt were simulated for clearcut conditions only, using an enery- balance approach that accounts for the most important energy and mass exchanges between a snowpack and its environment. Meteorological measurements provided the input for the simulations. Snow accumulation and melt were not simulated in forest stands because interception of precipitation processes are too complex to simulate with a numerical model without making simplifying assumptions. Such a model, however, would need to be extensively tested against representative observations, which were not available for this study. Snowmelt simulated during three rain-on-snow events (measured in a previous study in a clearcut in the transient-snow zone of the H.J. Andrews Experimental Forest in Oregon) demonstrated that melt generation is most sensitive to turbulent- energy exchanges between the air and the snowpack surface. As a result, the most important climate variable that controls snowmelt is wind speed. Air temperature, however, is a significant variable also. The wind speeds were light, with a maximum of 3

  13. PBO H2O: Monitoring the Terrestrial Water Cycle with reflected GPS signals recorded by the Plate Boundary Observatory Network

    Science.gov (United States)

    Small, E. E.; Fairfax, E. J.; Chew, C. C.; Larson, K. M.

    2015-12-01

    Data from NSF's EarthScope Plate Boundary Observatory (PBO), and similar GPS networks worldwide, can be used to monitor the terrestrial water cycle. GPS satellites transmit L-band microwave signals, which are strongly influenced by water at the surface of the Earth. GPS signals take two different paths: (1) the "direct" signal travels from the satellite to the antenna; (2) the "reflected" signal interacts with the Earth's surface before travelling to the antenna. The direct signal is used by geophysicists to measure the position of the antenna. By analyzing these GPS data over multiple years, the motion of the site can be estimated. The effects of reflected signals are generally ignored by geophysicists because they are small. This is not happenstance, as significant effort has been made to design and deploy a GPS antenna that suppresses ground reflections. Our group has developed a remote sensing technique to retrieve terrestrial water cycle variables from GPS data. We extract the water cycle products from signal strength data that measures the interference between the direct and reflected GPS signals. The sensing footprint is intermediate in scale between in situ observations and most remote sensing measurements. Snow depth, snow water equivalent (SWE), near surface soil moisture, and an index of vegetation water content are currently estimated from nearly 500 PBO sites. These PBO H2O products are updated daily and are available online (http://xenon.colorado.edu/portal/index.php). Validation studies show that retrieved products are of sufficient quality to be used in a variety of applications. The root mean square error (RMSE) of GPS-based SWE is 2 cm, based on a comparison to snow survey data at nearly 20 GPS sites. The RMSE of near surface volumetric soil moisture is moisture and similar products.

  14. Monitoring water storage variations with a superconducting gravimeter in a field enclosure

    Science.gov (United States)

    Güntner, Andreas; Mikolaj, Michal; Reich, Marvin; Schröder, Stephan; Wziontek, Hartmut

    2016-04-01

    Water storage dynamics are notoriously difficult to monitor in a comprehensive way beyond the point scale. Superconducting gravimeters (SG) measure temporal variations of the Earth's acceleration of gravity with very high precision and temporal resolution. They have been shown to be sensitive to mass variations induced by hydrological processes in their surroundings, typically within a radius of few 100 meters around the instrument. Thus, in turn, SGs are unique instruments for monitoring water storage variations in the landscape in an integrative way, accounting for soil moisture, vadose zone and groundwater storage, snow, and surface water bodies if existent. Nevertheless, hydrological applications of SGs so far have usually been hindered by the instruments being located in observatory buildings. This infrastructure disturbs the local hydrology and causes many uncertainties due to the often poorly known geometry of the construction, non-natural flow paths of water, and unknown water storage variations below and/or on top of the infrastructure. By deploying the SG in a small enclosure, these disturbances and unknowns are minimized. We report on the first experiences with exposing a SG of the latest generation (iGrav) in a small housing of less than 1 m2 footprint to temperate hydro-meteorological conditions. The system has been set up on a grassland site at the Geodetic Observatory in Wettzell, Bavarian Forest, Germany, in early 2015. We present the technical layout and challenges in running the gravimeter system. Additionally, we report on the quality of data acquired so far and present comparisons to in-situ soil moisture monitoring with TDR and TOMST sensors, a lysimeter, and groundwater observations, and two SGs located in nearby observatory buildings. We discuss the value of SG observations for estimating water storage variations, evapotranspiration and groundwater recharge beyond the point scale.

  15. Monitoring the Dynamics of Water Flow at a High-Mountain Permafrost Site Using Electrical Self-Potential Measurements

    Science.gov (United States)

    Kemna, A.; Weigand, M.; Wagner, F.; Hilbich, C.; Hauck, C.

    2016-12-01

    Flow of (liquid) water plays a crucial role in the dynamics of coupled thermo-hydro-mechanical processes in terrestrial permafrost systems. To better understand these processes in the active layer of permafrost regions, with the ultimate goal of adequately incorporating them in numerical models for improved scenario prediction, monitoring approaches offering high spatial and temporal resolution, areal coverage, and especially sensitivity to subsurface water flow, are highly desired. This particularly holds for high-mountain slopes, where strong variability in topography, precipitation, and snow cover, along with significant subsurface soil/rock heterogeneity, gives rise to complex spatio-temporal patterns of water flow during seasonal thawing and freezing periods. The electrical self-potential (SP) method is well known to, in theory, meeting the above monitoring demands by measuring the electrical streaming potential which is generated at the microscopic scale when water flows along electrically non-neutral interfaces. Despite its inherent sensitivity to subsurface water flow, the SP method has not yet been used for the monitoring of high-mountain permafrost sites. We here present first results from an SP monitoring survey conducted at the Schilthorn (2970 m asl) in the Bernese Alps, Switzerland, where SP data have been collected since September 2013 at a sampling rate of 10 min on a permanently installed array of 12 non-polarizing electrodes covering an area of 35 m by 15 m. While the SP time series exhibit systematic daily variations, with part of the signal clearly correlated with temperature, in particular in the snow-free periods, the largest temporal changes in the SP signal occur in spring, when the snow cover melts and thawing sets on in the active layer. The period of higher temporal SP variations continues until autumn, when the signal gradually returns to relatively low variations, coinciding with the freezing of the ground. Our results suggest that the

  16. Healthy Water Healthy People Field Monitoring Guide

    Science.gov (United States)

    Project WET Foundation, 2003

    2003-01-01

    This 100-page manual serves as a technical reference for the "Healthy Water, Healthy People Water Quality Educators Guide" and the "Healthy Water Healthy People Testing Kits". Yielding in-depth information about ten water quality parameters, it answers questions about water quality testing using technical overviews, data interpretation guidelines,…

  17. [The research of the relationship between snow properties and the bidirectional polarized reflectance from snow surface].

    Science.gov (United States)

    Sun, Zhong-Qiu; Wu, Zheng-Fang; Zhao, Yun-Sheng

    2014-10-01

    In the context of remote sensing, the reflectance of snow is a key factor for accurate inversion for snow properties, such as snow grain size, albedo, because of it is influenced by the change of snow properties. The polarized reflectance is a general phenomenon during the reflected progress in natural incident light In this paper, based on the correct measurements for the multiple-angle reflected property of snow field in visible and near infrared wavelength (from 350 to 2,500 nm), the influence of snow grain size and wet snow on the bidirectional polarized property of snow was measured and analyzed. Combining the results measured in the field and previous conclusions confirms that the relation between polarization and snow grain size is obvious in infrared wavelength (at about 1,500 nm), which means the degree of polarization increasing with an increase of snow grain size in the forward scattering direction, it is because the strong absorption of ice near 1,500 nm leads to the single scattering light contributes to the reflection information obtained by the sensor; in other word, the larger grain size, the more absorption accompanying the larger polarization in forward scattering direction; we can illustrate that the change from dry snow to wet snow also influences the polarization property of snow, because of the water on the surface of snow particle adheres the adjacent particles, that means the wet snow grain size is larger than the dry snow grain size. Therefore, combining the multiple-angle polarization with reflectance will provide solid method and theoretical basis for inversion of snow properties.

  18. Analysis of MODIS snow cover time series over the alpine regions as input for hydrological modeling

    Science.gov (United States)

    Notarnicola, Claudia; Rastner, Philipp; Irsara, Luca; Moelg, Nico; Bertoldi, Giacomo; Dalla Chiesa, Stefano; Endrizzi, Stefano; Zebisch, Marc

    2010-05-01

    Snow extent and relative physical properties are key parameters in hydrology, weather forecast and hazard warning as well as in climatological models. Satellite sensors offer a unique advantage in monitoring snow cover due to their temporal and spatial synoptic view. The Moderate Resolution Imaging Spectrometer (MODIS) from NASA is especially useful for this purpose due to its high frequency. However, in order to evaluate the role of snow on the water cycle of a catchment such as runoff generation due to snowmelt, remote sensing data need to be assimilated in hydrological models. This study presents a comparison on a multi-temporal basis between snow cover data derived from (1) MODIS images, (2) LANDSAT images, and (3) predictions by the hydrological model GEOtop [1,3]. The test area is located in the catchment of the Matscher Valley (South Tyrol, Northern Italy). The snow cover maps derived from MODIS-images are obtained using a newly developed algorithm taking into account the specific requirements of mountain regions with a focus on the Alps [2]. This algorithm requires the standard MODIS-products MOD09 and MOD02 as input data and generates snow cover maps at a spatial resolution of 250 m. The final output is a combination of MODIS AQUA and MODIS TERRA snow cover maps, thus reducing the presence of cloudy pixels and no-data-values due to topography. By using these maps, daily time series starting from the winter season (November - May) 2002 till 2008/2009 have been created. Along with snow maps from MODIS images, also some snow cover maps derived from LANDSAT images have been used. Due to their high resolution (manto nevoso in aree alpine con dati MODIS multi-temporali e modelli idrologici, 13th ASITA National Conference, 1-4.12.2009, Bari, Italy. [3] Zanotti F., Endrizzi S., Bertoldi G. and Rigon R. 2004. The GEOtop snow module. Hydrological Processes, 18: 3667-3679. DOI:10.1002/hyp.5794.

  19. Snow cover regime in Livingston and Deception Islands (Maritime Antarctic) using multitemporal analysis of ASAR imagery from 2009.

    Science.gov (United States)

    Mora, Carla; Vieira, Gonçalo; Ramos, Miguel

    2010-05-01

    ASAR images from Envisat (WSW and IMM) are analyzed to study the snow cover regime of Deception and Livingston Islands (South Shetlands, Antarctic Peninsula) during 2009. The study is part of the project PERMANTAR focusing on monitoring and modeling the thermal regime of permafrost. For a GIS-based spatial modelling of snow cover distribution, spatially distributed data is required and the exploration of microwave remote sensing is the most suitable technique for mapping the snow cover characteristics and regime. This becomes especially true due to the long winter night and unstable weather conditions of the northern Antarctic Peninsula region. For this purpose a multitemporal ASAR imagery analysis was conducted in order to distinguish wet snow cover from snow free terrain using the absorption dependency of the radar signal on the liquid water content of the snow to set a threshold on the differential backscatter between scenes. The imagery was analyzed using the processing chains from NEST (ESA SAR Toolbox). Preliminary results of the analysis of the time-series show strong seasonal changes in the backscattering due to the variations of liquid water content in snow. Validation of the results obtained from the microwave imagery is done using the ground truth data. In January and February 2009 we have installed in Livingston and Deception islands time-lapse camera in key-areas, ultra-sonic sensors of the snow thickness and probes with snow temperature mini-loggers. This data will be collected from field sites n January 2010 and used for the calibration of the results. Satellite immagery is provided by the European Space Agency in the framework of the Proposal Category-1: Snow cover characteristics and regime in the South Shetlands (Maritime Antarctic) - SnowAntar.

  20. Contamination Control and Monitoring of Tap Water as Fluid in Industrial Tap Water Hydraulic Systems

    DEFF Research Database (Denmark)

    Conrad, Finn; Adelstorp, Anders

    1998-01-01

    Presentation of results and methods addressed to contamination control and monitoring of tap water as fluid in tap water hydraulic systems.......Presentation of results and methods addressed to contamination control and monitoring of tap water as fluid in tap water hydraulic systems....

  1. Contamination Control and Monitoring of Tap Water as Fluid in Industrial Tap Water Hydraulic Systems

    DEFF Research Database (Denmark)

    Conrad, Finn; Adelstorp, Anders

    1998-01-01

    Presentation of results and methods addressed to contamination control and monitoring of tap water as fluid in tap water hydraulic systems.......Presentation of results and methods addressed to contamination control and monitoring of tap water as fluid in tap water hydraulic systems....

  2. Stability monitoring for boiling water reactors

    Science.gov (United States)

    Cecenas-Falcon, Miguel

    1999-11-01

    A methodology is presented to evaluate the stability properties of Boiling Water Reactors based on a reduced order model, power measurements, and a non-linear estimation technique. For a Boiling Water Reactor, the feedback reactivity imposed by the thermal-hydraulics has an important effect in the system stability, where the dominant contribution to this feedback reactivity is provided by the void reactivity. The feedback reactivity is a function of the operating conditions of the system, and cannot be directly measured. However, power measurements are relatively easy to obtain from the nuclear instrumentation and process computer, and are used in conjunction with a reduced order model to estimate the gain of the thermal-hydraulics feedback using an Extended Kalman Filter. The reduced order model is obtained by estimating the thermal-hydraulic transfer function from the frequency-domain BWR code LAPUR, and the stability properties are evaluated based on the pair of complex conjugate eigenvalues. Because of the recursive nature of the Kalman Filter, an estimate of the decay ratio is generated every sampling time, allowing continuous estimation of the stability parameters. A test platform based on a nuclear-coupled boiling channel is developed to validate the capability of the BWR stability monitoring methodology. The thermal-hydraulics for the boiling channel is modeled and coupled with neutron kinetics to analyze the non-linear dynamics of the closed-loop system. The model uses point kinetics to study core-wide oscillations, and normalized modal kinetics are introduced to study out-of-phase oscillations. The coolant flow dynamics is dominant in the power fluctuations observed by in-core nuclear instrumentation, and additive white noise is added to the solution for the channel flow in the thermal-hydraulic model to generate noisy power time series. The operating conditions of the channel can be modified to accommodate a wide range of stability conditions

  3. From the clouds to the ground - snow precipitation patterns vs. snow accumulation patterns

    Science.gov (United States)

    Gerber, Franziska; Besic, Nikola; Mott, Rebecca; Gabella, Marco; Germann, Urs; Bühler, Yves; Marty, Mauro; Berne, Alexis; Lehning, Michael

    2017-04-01

    Knowledge about snow distribution and snow accumulation patterns is important and valuable for different applications such as the prediction of seasonal water resources or avalanche forecasting. Furthermore, accumulated snow on the ground is an important ground truth for validating meteorological and climatological model predictions of precipitation in high mountains and polar regions. Snow accumulation patterns are determined by many different processes from ice crystal nucleation in clouds to snow redistribution by wind and avalanches. In between, snow precipitation undergoes different dynamical and microphysical processes, such as ice crystal growth, aggregation and riming, which determine the growth of individual particles and thereby influence the intensity and structure of the snowfall event. In alpine terrain the interaction of different processes and the topography (e.g. lifting condensation and low level cloud formation, which may result in a seeder-feeder effect) may lead to orographic enhancement of precipitation. Furthermore, the redistribution of snow particles in the air by wind results in preferential deposition of precipitation. Even though orographic enhancement is addressed in numerous studies, the relative importance of micro-physical and dynamically induced mechanisms on local snowfall amounts and especially snow accumulation patterns is hardly known. To better understand the relative importance of different processes on snow precipitation and accumulation we analyze snowfall and snow accumulation between January and March 2016 in Davos (Switzerland). We compare MeteoSwiss operational weather radar measurements on Weissfluhgipfel to a spatially continuous snow accumulation map derived from airborne digital sensing (ADS) snow height for the area of Dischma valley in the vicinity of the weather radar. Additionally, we include snow height measurements from automatic snow stations close to the weather radar. Large-scale radar snow accumulation

  4. Hanford Site ground-water monitoring for 1994

    Energy Technology Data Exchange (ETDEWEB)

    Dresel, P.E.; Thorne, P.D.; Luttrell, S.P. [and others

    1995-08-01

    This report presents the results of the Ground-Water Surveillance Project monitoring for calendar year 1994 on the Hanford Site, Washington. Hanford Site operations from 1943 onward produced large quantities of radiologic and chemical waste that have impacted ground-water quality on the Site. Monitoring of water levels and ground-water chemistry is performed to track the extent of contamination and trends in contaminant concentrations. The 1994 monitoring was also designed to identify emerging ground-water quality problems. The information obtained is used to verify compliance with applicable environmental regulations and to evaluate remedial actions. Data from other monitoring and characterization programs were incorporated to provide an integrated assessment of Site ground-water quality. Additional characterization of the Site`s geologic setting and hydrology was performed to support the interpretation of contaminant distributions. Numerical modeling of sitewide ground-water flow also supported the overall project goals. Water-level monitoring was performed to evaluate ground-water flow directions, to track changes in water levels, and to relate such changes to changes in site disposal practices. Water levels over most of the Hanford Site continued to decline between June 1993 and June 1994. These declines are part of the continued response to the cessation of discharge to U Pond and other disposal facilities. The low permeability in this area which enhanced mounding of waste-water discharge has also slowed the response to the reduction of disposal.

  5. Analyzing the importance of wind-blown snow accumulations on Mount

    Science.gov (United States)

    Nestler, Alexander; Huss, Matthias; Ambartsumian, Rouben; Hambarian, Artak; Mohr, Sandra; Santi, Flavio

    2013-04-01

    Armenia's climate has a predominantly continental character with high amounts of precipitation and low temperatures during wintertime and a lack of precipitation together with high temperatures during summer. On the volcano Mount Aragatz, snow is relocated by strong winds into massive accumulations between 2500 and 4100 m a.s.l. during the winter season. These snow accumulations appear every winter in regular patterns as cornices on the lee side of sharp edges, such as those of ridges and canyons, which are arranged in a radial manner around the central crater. The biggest cornices almost outlast the hot period and provide considerable amounts of melt water until they disappear completely by the end of August. Snow melt water is known to have a high economic importance for agriculture on the slopes of Mount Aragatz and in the surroundings of Armenia's captial Yerewan. The aim of this study is to estimate the quantity of water naturally stored as snow on Mount Aragatz, and to what degree the use of geotextiles can prolong the lives of these snow accumulations. The characteristics and the spatial distribution of snow cornices on Mount Aragatz were determined using classical glaciological methods in June/July 2011 and 2012, involving snow depth soundings, water equivalent measurements and snow melt monitoring using ablation stakes, together with GPS mappings and classifications obtained from satellite images of the snow cornices. The combination of these data with ASTER DEMs and local weather data allows the modelling of the formation of wind-driven snow accumulations. Statistical relationships between the measured extent and volume of the snow cornices and surface parameters such as slope, aspect and curvature are established. In order to analyze the meltdown of the snow accumulations and the consequent impacts on runoff generation and the hydrological regime, a glacio-hydrological model integrating topographic parameters and meteorological data is applied. The

  6. An Inexpensive, Implantable Electronic Sensor for Autonomous Measurement of Snow Pack Parameters

    Science.gov (United States)

    De Roo, R. D.; Haengel, E.; Rogacki, S.

    2015-12-01

    Snow accumulations on the ground are an important source of water in many parts of the world. Mapping the accumulation, usually represented as the snow water equivalent (SWE), is valuable for water resource management. The longest record of regional and global maps of SWE are from orbiting microwave radiometers, which do not directly measure SWE but rather measure the scatter darkening from the snow pack. Robustly linking the scatter darkening to SWE eludes us to this day, in part because the snow pack is highly variable in both time and space. The data needed is currently collected by hand in "snow pits," and the labor-intensive process limits the size of the data sets that can be obtained. In particular, time series measurements are only a one or two samples per day at best, and come at the expense of spatial sampling. We report on the development of a low-power wireless device that can be embedded within a snow pack to report on some of the critical parameters needed to understand scatter darkening. The device autonomously logs temperature, the microwave dielectric constant and infrared backscatter local to the device. The microwave dielectric constant reveals the snow density and the presence of liquid water, while the infrared backscatter measurement, together with the density measurement, reveals a characteristic grain size of the snow pack. The devices are made to be inexpensive (less than $200 in parts each) and easily replicated, so that many can be deployed to monitor variations vertically and horizontally in the snow pack. The low-power operation is important both for longevity of observations as well as insuring minimal anomalous metamorphism of the snow pack. The hardware required for the microwave measurement is intended for wireless communications, and this feature will soon be implemented for near real-time monitoring of snow conditions. We will report on the design, construction and initial deployment of about 30 of these devices in northern lower

  7. Characterizing pyroclastic-flow interactions with snow and water using environmental magnetism at Augustine Volcano: Chapter 11 in The 2006 eruption of Augustine Volcano, Alaska

    Science.gov (United States)

    Beget, James E.; Power, John A.; Coombs, Michelle L.; Freymueller, Jeffrey T.

    2010-01-01

    In-place measurements of environmental magnetic susceptibility of pyroclastic flows, surges and lahars emplaced during the 2006 eruption of Augustine Volcano show that primary volume magnetic susceptibilities of pyroclastic materials decreased where the flows encountered water and steam. The Rocky Point pyroclastic flow, the largest flow of the eruption sequence, encountered a small pond near the north coast of Augustine Island where local interactions with water and steam caused susceptibilities to decrease from 1,084±128×10-5 SI to 615±114×10-5 SI. Ash produced during phreatic explosions and pyroclastic surges that crossed snow also produced deposits with reduced susceptibilities, while lahar deposits derived from pyroclastic flows showed even greater reductions in susceptibility (430±129×10-5 SI). The susceptibility reductions are probably largely attributable to oxidation of iron in magnetite and other minerals within the pyroclastic flows, although other physiochemical processes may play a role. Measurements of the magnetic properties of pyroclastic flows, surges, and lahar deposits can be a useful tool in understanding the processes that occur when pyroclastic flows encounter ice, snow, and water and interact with water and steam on the slopes of active volcanoes.

  8. R2 Water Quality Portal Monitoring Stations

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Water Quality Data Portal (WQP) provides an easy way to access data stored in various large water quality databases. The WQP provides various input parameters on...

  9. Preliminary monitoring of faecal indicator organisms of surface water ...

    African Journals Online (AJOL)

    Preliminary monitoring of faecal indicator organisms of surface water: A case study ... in Mvudi River used as a source of domestic water for people who live around it. ... of Water Affairs and Forestry of South Africa (DWAF) and the World Health ...

  10. Numerical Simulation of the Evolution of Snow Cover and Its Sensitivity Experiments

    Institute of Scientific and Technical Information of China (English)

    CHEN Haishan; SUN Zhaobo

    2005-01-01

    By using Comprehensive Land Surface Model (CLSM), three snow cases, i.e., France Col de Porte 1993/1994, 1994/1995 and BOREAS SSA-OJP 1994/1995, were simulated. The simulated results were compared with the observations to examine the capability of the model to describe the evolutions of snow cover under two different land cover conditions. Several sensitivity experiments were performed to investigate the effects of the parameterization schemes of some snow cover internal processes and vegetation on the model results. Results suggest that the CLSM simulates the basic processes of snow cover accurately and describes the features of snow cover evolutions reasonably, indicating that the model has the potential to model the processes related to the snow cover evolution. It is also found that the different parameterization schemes of the snowfall density and snow water holding capacity have significant effects on the simulation of snow cover. The estimation of snowfall density mainly impacts the simulated snow depth, and the underestimation (overestimation) of the snowfall density increases (decreases) the snow depth simulated significantly but with little effect on the simulated snow water equivalent (SWE). The parameterization of the snow water holding capacity plays a crucial role in the evolution of snow cover, especially in the ablation of snow cover. Larger snow water holding capacity usually leads to larger snow density and heat capacity by storing more liquid water in the snow layer, and makes the temperature of snow cover and the snow ablation vary more slowly.To a smaller snow water holding capacity, contrary is the case. The results also show that the physical processes related to the snow cover variation are different, which are dependent on the vegetation existed.Vegetation plays an important role in the evolution of soil-snow system by changing the energy balance at the snow-soil surface. The existence of vegetation is favorable to the maintenance of snow

  11. Environmental Monitoring, Water Quality - Water Pollution Control Facilities

    Data.gov (United States)

    NSGIC Education | GIS Inventory — A Water Pollution Control Facility is a DEP primary facility type related to the Water Pollution Control Program. The sub-facility types related to Water Pollution...

  12. Water quality monitoring for high-priority water bodies in the Sonoran Desert network

    Science.gov (United States)

    Terry W. Sprouse; Robert M. Emanuel; Sara A. Strorrer

    2005-01-01

    This paper describes a network monitoring program for “high priority” water bodies in the Sonoran Desert Network of the National Park Service. Protocols were developed for monitoring selected waters for ten of the eleven parks in the Network. Park and network staff assisted in identifying potential locations of testing sites, local priorities, and how water quality...

  13. Future water quality monitoring - Adapting tools to deal with mixtures of pollutants in water resource management

    NARCIS (Netherlands)

    Altenburger, R.; Ait-Aissa, S.; Antczak, P.; Backhaus, T.; Barcelo, D.; Seiler, T.; Brion, F.; Focks, A.

    2015-01-01

    Environmental quality monitoring of water resources is challenged with providing the basis for safeguarding the environment against adverse biological effects of anthropogenic chemical contamination from diffuse and point sources. While current regulatory efforts focus on monitoring and assessing a

  14. Drinking water quality monitoring using trend analysis.

    Science.gov (United States)

    Tomperi, Jani; Juuso, Esko; Eteläniemi, Mira; Leiviskä, Kauko

    2014-06-01

    One of the common quality parameters for drinking water is residual aluminium. High doses of residual aluminium in drinking water or water used in the food industry have been proved to be at least a minor health risk or even to increase the risk of more serious health effects, and cause economic losses to the water treatment plant. In this study, the trend index is developed from scaled measurement data to detect a warning of changes in residual aluminium level in drinking water. The scaling is based on monotonously increasing, non-linear functions, which are generated with generalized norms and moments. Triangular episodes are classified with the trend index and its derivative. The severity of the situations is evaluated by deviation indices. The trend episodes and the deviation indices provide good tools for detecting changes in water quality and for process control.

  15. Learner's Guide: Water Quality Monitoring. An Instructional Guide for the Two-Year Water Quality Monitoring Curriculum.

    Science.gov (United States)

    Glazer, Richard B.; And Others

    This learner's guide is designed to meet the training needs for technicians involved in monitoring activities related to the Federal Water Pollution Act and the Safe Drinking Water Act. In addition it will assist technicians in learning how to perform process control laboratory procedures for drinking water and wastewater treatment plant…

  16. Monitoring of ground water aquifer by electrical prospecting; Denki tansaho ni yoru chikasui monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Ushijima, K. [Kyushu University, Fukuoka (Japan)] [Faculty of Engineering (Japan)

    1997-12-01

    This paper describes three case studies for monitoring ground water aquifers by electrical prospecting. An example in the Hofu plain, Yamaguchi Prefecture is presented, where the ground water environment has been monitored for more than 30 years from the viewpoint of hydrology. Then, transition from the fresh ground water to sea water is evaluated by a sharp boundary as salt-water wedges through the field survey in a coastal area of a large city for a short term using vertical electrical prospecting. Moreover, streaming potential measurements are described to grasp the real-time behavior of ground water flow. From the long-term monitoring of ground water aquifer, it was found that the variation of ground water streaming can be evaluated by monitoring the long-term successive change in the resistivity of ground water aquifer. From the vertical electrical prospecting, water quality can be immediately judged through data analysis. From the results of streaming potential measurements and vertical electrical prospecting using Schlumberger method, streaming behavior of ground water in the area of spring water source can be estimated by determining three-dimensional resistivity structure. 17 refs., 15 figs.

  17. Hanford Site ground-water monitoring for 1993

    Energy Technology Data Exchange (ETDEWEB)

    Dresel, P.E.; Luttrell, S.P.; Evans, J.C. [and others

    1994-09-01

    This report presents the results of the Ground-Water Surveillance Project monitoring for calendar year 1993 on the Hanford Site, Washington. Hanford Site operations from 1943 onward produced large quantities of radiological and chemical waste that have impacted ground-water quality on the Site. Monitoring of water levels and ground-water chemistry is performed to track the extent of contamination and trends in contaminant concentrations. The 1993 monitoring was also designed to identify emerging ground-water quality problems. The information obtained is used to verify compliance with applicable environmental regulations and to evaluate remedial actions. Data from other monitoring and characterization programs were incorporated to provide an integrated assessment of Site ground-water quality. Additional characterization of the Site`s geologic setting and hydrology was performed to support the interpretation of contaminant distributions. Numerical modeling of sitewide ground-water flow also supported the overall project goals. Water-level monitoring was performed to evaluate ground-water flow directions, to track changes in water levels, and to relate such changes to changes in site disposal practices. Water levels over most of the Hanford Site continued to decline between June 1992 and June 1993. The greatest declines occurred in the 200-West Area. These declines are part of the continued response to the cessation of discharge to U Pond and other disposal facilities. The low permeability in this area which enhanced mounding of waste-water discharge has also slowed the response to the reduction of disposal. Water levels remained nearly constant in the vicinity of B Pond, as a result of continued disposal to the pond. Water levels measured from wells in the unconfined aquifer north and east of the Columbia River indicate that the primary source of recharge is irrigation practices.

  18. Climate-driven changes in grassland vegetation, snow cover, and lake water of the Qinghai Lake basin

    Science.gov (United States)

    Wang, Xuelu; Liang, Tiangang; Xie, Hongjie; Huang, Xiaodong; Lin, Huilong

    2016-07-01

    Qinghai Lake basin and the lake have undergone significant changes in recent decades. We examine MODIS-derived grassland vegetation and snow cover of the Qinghai Lake basin and their relations with climate parameters during 2001 to 2010. Results show: (1) temperature and precipitation of the Qinghai Lake basin increased while evaporation decreased; (2) most of the grassland areas improved due to increased temperature and growing season precipitation; (3) weak relations between snow cover and precipitation/vegetation; (4) a significantly negative correlation between lake area and temperature (r=-0.9, presponsible for the degradation of vegetation cover in Namco Lake basin. These results suggest different responses to the similar warming climate: improved (degraded) ecological condition and productive capacity of the Qinghai Lake basin (Namco Lake basin).

  19. Water-Level Monitoring Plan for the Hanford Groundwater Monitoring Project

    Energy Technology Data Exchange (ETDEWEB)

    D.R. Newcomer; J.P. McDonald; M.A. Chamness

    1999-09-30

    This document presents the water-level monitoring plan for the Hanford Groundwater Monitoring Project, conducted by the Pacific Northwest National Laboratory (PNNL). Water-level monitoring of the groundwater system beneath the Hanford Site is performed to fulfill the requirements of various state and federal regulations, orders, and agreements. The primary objective of this monitoring is to determine groundwater flow rates and directions. To meet this and other objectives, water-levels are measured annually in monitoring wells completed within the unconfined aquifer system, the upper basalt-confined aquifer system, and in the lower basalt-confined aquifers for surveillance monitoring. At regulated waste units, water levels are taken monthly, quarterly, semi-annually, or annually, depending on the hydrogeologic conditions and regulatory status of a given site. The techniques used to collect water-level data are described in this document along with the factors that affect the quality of the data and the strategies employed by the project to minimize error in the measurement and interpretation of water levels. Well networks are presented for monitoring the unconfined aquifer system, the upper basalt-confined aquifer system, and the lower basalt-confined aquifers, all at a regional scale (surveillance monitoring), as well as the local-scale well networks for each of the regulated waste units studied by this project (regulated-unit monitoring). The criteria used to select wells for water-table monitoring are discussed. It is observed that poor well coverage for surveillance water-table monitoring exists south and west of the 200-West Area, south of the 100-F Area, and east of B Pond and the Treated Effluent Disposal Facility (TEDF). This poor coverage results from a lack of wells suitable for water-table monitoring, and causes uncertainty in representation of the regional water-table in these areas. These deficiencies are regional in scale and apply to regions outside

  20. Airborne LiDAR and hyperspectral mapping of snow depth and albedo in the Upper Colorado River Basin, Colorado, USA by the NASA JPL Airborne Snow Observatory

    Science.gov (United States)

    Deems, J. S.; Painter, T. H.

    2014-12-01

    Operational hydrologic simulation and forecasting in snowmelt-dominated watersheds currently relies on indices of snow accumulation and melt from measurements at a small number of point locations or geographically-limited manual surveys. These data sources cannot adequately characterize the spatial distribution of snow depth/water equivalent, which is the primary determinant of snowpack volume and runoff rates. The NASA JPL Airborne Snow Observatory's airborne laser scanning system maps snow depth at high spatial and temporal resolutions, and is paired with a hyperspectral imager to provide an unprecedented snowpack monitoring capability and enabling a new operational paradigm. We present the initial results from this new application of multi-temporal LiDAR and hyperspectral mapping. During the snowmelt seasons of 2013 and 2014, the ASO mapped snow depth and albedo in the Uncompahgre River Basin in Colorado's Upper Colorado River Basin on a nominally monthly basis. These products enable an assessment and comparison of spatial snow accumulation and melt processes in two years with very different snowmelt hydrographs.

  1. La Parguera, Puerto Rico Water Quality Monitoring Data 2003 - Present

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These water quality data are one of many studies being done to assess and monitor coral reef ecosystems. The intent of this work is three fold: (1) to spatially...

  2. St. John, USVI Water Quality Monitoring Data 2003 - Present

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These water quality data are one of many studies being done to assess and monitor coral reef ecosystems. The intent of this work is three fold: (1) to spatially...

  3. Initial Survey Instructions for management unit water monitoring : level

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Initial survey instructions for 1.08 management unit water monitoring (level) survey on Fish Springs National Wildlife Refuge. This survey is conducted weekly and is...

  4. Recent Advances in Point-of-Access Water Quality Monitoring

    Science.gov (United States)

    Korostynska, O.; Arshak, K.; Velusamy, V.; Arshak, A.; Vaseashta, Ashok

    Clean water is one of our most valuable natural resources. In addition to providing safe drinking water it assures functional ecosystems that support fisheries and recreation. Human population growth and its associated increased demands on water pose risks to maintaining acceptable water quality. It is vital to assess source waters and the aquatic systems that receive inputs from industrial waste and sewage treatment plants, storm water systems, and runoff from urban and agricultural lands. Rapid and confident assessments of aquatic resources form the basis for sound environmental management. Current methods engaged in tracing the presence of various bacteria in water employ bulky laboratory equipment and are time consuming. Thus, real-time water quality monitoring is essential for National and International Health and Safety. Environmental water monitoring includes measurements of physical characteristics (e.g. pH, temperature, conductivity), chemical parameters (e.g. oxygen, alkalinity, nitrogen and phosphorus compounds), and abundance of certain biological taxa. Monitoring could also include assays of biological activity such as alkaline phosphatase, tests for toxins such as microcystins and direct measurements of pollutants such as heavy metals or hydrocarbons. Real time detection can significantly reduce the level of damage and also the cost to remedy the problem. This paper presents overview of state-of-the-art methods and devices used for point-of-access water quality monitoring and suggest further developments in this area.

  5. Principles and Practices of Water Quality Monitoring

    Science.gov (United States)

    J.L. Michael

    2001-01-01

    There are many activities in forest management that may affect water quality, i.e., timber harvestine, road building,mechanical and chemical site preparation, release operations, fuel reduction,wildlife opening maintenance, etc. How severely they affect water quality depends on how well the person in charge of the operation understands the activity itself, the...

  6. The Role of Monitoring in Controlling Water Pollution

    Science.gov (United States)

    Hirsch, Allan

    1971-01-01

    The purpose of this paper is to provide an overview of trends in the national water pollution control effort and to describe the role of monitoring in that effort, particularly in relation to the responsibilities of the Environmental Protection Agency (EPA). I hope the paper will serve as a useful framework for the more specific discussions of monitoring technology to follow.

  7. 改进AMSR-E雪水当量算法研究%On Improvement of Snow Water Equivalence Estimation for Passive Microwave Instrument-AMSR/E

    Institute of Scientific and Technical Information of China (English)

    蒋玲梅; 施建成; 张立新

    2007-01-01

    为了发展雪水当量物理反演算法,本文对不同散射阶模型--零阶、一阶、多次散射模型进行敏感性试验与分析,结果表明我们必须在前向理论模型和反演模型中考虑多次散射作用.本文采用的多次散射积雪辐射理论模型--双矩阵法(Matrix Doubling)求解辐射传输方程,用致密介质理论模型(DMRT)模拟积雪发射和消光特性,用AIEM模型模拟地表辐射及作为辐射传输方程的边界条件.由于该多次散射积雪辐射理论模型的复杂性,拟发展出简单且高精度的积雪辐射参数化模型,以发展雪水当量物理反演算法.因此,在包括多次散射的积雪理论模型基础上,本文通过建立针对AMSR-E传感器参数设置的积雪辐射模拟数据库,该数据库包含了各种可能的自然积雪和地表特性参数.从而在模拟数据库基础上,本文发展了针对AMSR-E的积雪参数化模型.%In this paper, we evaluate the capability of a multi-scattering microwave emission model that includes the Dense Media Radiative Transfer Model(DMRT) and Advanced Integral Equation Model(AIEM) to simulate dry snow emission with the Matrix Doubling approach. We compared the predictions of this model with ground experimental measurements. The comparison showed that our snow microwave emission model agreed well with the experimental measurements. In order to develop retrieval snow properties: snow depth or snow water equivalence(SWE) retrieval algorithm, we carried out the sensitivity test between the emission models with the different scattering-order: the zeroth-order, the first-order and the multi-scattering models. The results indicated that the multi-scattering effects have to be taken into account in the snow emission model, especially for large grain size. Due to the complexity of the multi-scattering model, we developed a parameterized inversion model using our multi-scattering emission model with a wide range of snow and under

  8. Water Quality Monitoring of Texas Offshore Artificial Reefs

    Science.gov (United States)

    Bodkin, L.; Lee, M.

    2016-02-01

    Artificial reefs provide a habitat for marine organisms and abundant ecosystem services. In reef ecosystems, several organisms tolerate a small range of physical water properties and any change in water quality could affect their survival. Therefore, monitoring how these artificial reefs respond to environmental changes due to natural and anthropogenic causes is essential for management. The U.S. Geological Survey (USGS) and the Texas Parks and Wildlife Department (TPWD-ARP) are collaboratively monitoring artificial reefs located in the Gulf of Mexico in order to understand the productivity of these ecosystems, and their response to environmental changes. To accomplish this, TPWD use established protocols for biological monitoring, and the USGS collects physical and chemical water quality data. The selected artificial reef sites are located nearby national marine sanctuaries to facilitate comparison to natural reefs, but also provide enough spatial variability for comparison purposes. Additionally, the sites differ in artificial reef foundation providing an opportunity to evaluate variability in reefing structure. Physical water quality parameter profiles are collected to: (1)document variability of water quality between sites, (2)characterize the environmental conditions at the artificial reefs, and (3)monitor the reefs for potential impacts from anthropogenic stresses. Monitors have also been deployed at selected locations between trips to obtain a continuous record of physical water quality parameters. Water quality samples for nutrients, chlorophyll a, Pheophytin a, and an assortment of metal analytes are collected by USGS divers at the top of each artificial reef structure. Collecting long-term monitoring data with targeted sampling for constituents of concern at artificial reefs may provide a foundation to determine their current status and establish trends that can be used for future management. A record of hydrographic variables could be used to explain and

  9. User requirements for satellite snow data service

    Energy Technology Data Exchange (ETDEWEB)

    Kolberg, S.; Standley, A.; Hiltbrunner, D.; Hallikainen, M.

    1997-12-31

    This report discusses the answers given by ten users or potential users of remotely sensed snow data when asked about their data needs and present measurements, their requirements for remote sensing data and potential of using such, and the models or other analysis tools in which the information is used. The answers show both consensus and differences among the respondents` use of snow data and requirements for remote sensing snow products. For water resources planning and management, the most important variable is snow water equivalent, with acceptable errors around 10%. Acceptable spatial error is typically in the range of 200 m to 1 km. For flood forecasting and short-term runoff simulation, snow covered area is more important, with a classification of 5 to 8 steps being generally sufficient. Meteorologists tend to focus on albedo and snow coverage data, with 5% steps desired for albedo. Geometric resolution and accuracy is less important, temporal resolution and delivery time is more important than in water resource management. For avalanche use, most snow variables except water equivalent are important, several in depth profiles. Spatial and temporal requirements are high. In all user groups there is a desire for models which can use measured values quantitatively. Today, measured snow information is largely interpreted manually and subjectively and lead to actions based on experience and judgement. The organizing of measurements, simulations and calibrated sub-models with varying uncertainty levels is partly a conceptual problem, partly a software problem. 1 ref.

  10. Constraining snow model choices in a transitional snow environment with intensive observations

    Science.gov (United States)

    Wayand, N. E.; Massmann, A.; Clark, M. P.; Lundquist, J. D.

    2014-12-01

    The performance of existing energy balance snow models exhibits a large spread in the simulated snow water equivalent, snow depth, albedo, and surface temperature. Indentifying poor model representations of physical processes within intercomparison studies is difficult due to multiple differences between models as well as non-orthogonal metrics used. Efforts to overcome these obstacles for model development have focused on a modeling framework that allows multiple representations of each physical process within one structure. However, there still exists a need for snow study sites within complex terrain that observe enough model states and fluxes to constrain model choices. In this study we focus on an intensive snow observational site located in the maritime-transitional snow climate of Snoqualmie Pass WA (Figure 1). The transitional zone has been previously identified as a difficult climate to simulate snow processes; therefore, it represents an ideal model-vetting site. From two water years of intensive observational data, we have learned that a more honest comparison with observations requires that the modeled states or fluxes be as similar to the spatial and temporal domain of the instrument, even if it means changing the model to match what is being observed. For example, 24-hour snow board observations do not capture compaction of the underlying snow; therefore, a modeled "snow board" was created that only includes new snow accumulation and new snow compaction. We extend this method of selective model validation to all available Snoqualmie observations to constrain model choices within the Structure for Understanding Multiple Modeling Alternatives (SUMMA) framework. Our end goal is to provide a more rigorous and systematic method for diagnosing problems within snow models at a site given numerous snow observations.

  11. Instrumentation for Environmental Monitoring: Water, Volume 2.

    Science.gov (United States)

    California Univ., Berkeley. Lawrence Berkeley Lab.

    This volume is one of a series discussing instrumentation for environmental monitoring. Each volume contains an overview of the basic problems, comparisons among the basic methods of sensing and detection, and notes that summarize the characteristics of presently available instruments and techniques. The text of this survey discusses the…

  12. Operational Surface Water Detection and Monitoring Using Radarsat 2

    Directory of Open Access Journals (Sweden)

    Sandra Bolanos

    2016-03-01

    Full Text Available Traditional on-site methods for mapping and monitoring surface water extent are prohibitively expensive at a national scale within Canada. Despite successful cost-sharing programs between the provinces and the federal government, an extensive number of water features within the country remain unmonitored. Particularly difficult to monitor are the potholes in the Canadian Prairie region, most of which are ephemeral in nature and represent a discontinuous flow that influences water pathways, runoff response, flooding and local weather. Radarsat-2 and the Radarsat Constellation Mission (RCM offer unique capabilities to map the extent of water bodies at a national scale, including unmonitored sites, and leverage the current infrastructure of the Meteorological Service of Canada to monitor water information in remote regions. An analysis of the technical requirements of the Radarsat-2 beam mode, polarization and resolution is presented. A threshold-based procedure to map locations of non-vegetated water bodies after the ice break-up is used and complemented with a texture-based indicator to capture the most homogeneous water areas and automatically delineate their extents. Some strategies to cope with the radiometric artifacts of noise inherent to Synthetic Aperture Radar (SAR images are also discussed. Our results show that Radarsat-2 Fine mode can capture 88% of the total water area in a fully automated way. This will greatly improve current operational procedures for surface water monitoring information and impact a number of applications including weather forecasting, hydrological modeling, and drought/flood predictions.

  13. Environmental Monitoring, Water Quality - TMDL Lakes

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — The Clean Water Act Section 303(d) establishes the Total Maximum Daily Load (TMDL) program. The purpose of the TMDL program is to identify sources of pollution and...

  14. Environmental Monitoring, Water Quality - TMDL Lakes

    Data.gov (United States)

    NSGIC Education | GIS Inventory — The Clean Water Act Section 303(d) establishes the Total Maximum Daily Load (TMDL) program. The purpose of the TMDL program is to identify sources of pollution and...

  15. Environmental Monitoring, Water Quality - Lakes Assessments - Attaining

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This layer shows only attaining lakes of the Integrated List. The Lakes Integrated List represents lake assessments in an integrated format for the Clean Water Act...

  16. Analytical chemistry in water quality monitoring during manned space missions

    Science.gov (United States)

    Artemyeva, Anastasia A.

    2016-09-01

    Water quality monitoring during human spaceflights is essential. However, most of the traditional methods require sample collection with a subsequent ground analysis because of the limitations in volume, power, safety and gravity. The space missions are becoming longer-lasting; hence methods suitable for in-flight monitoring are demanded. Since 2009, water quality has been monitored in-flight with colorimetric methods allowing for detection of iodine and ionic silver. Organic compounds in water have been monitored with a second generation total organic carbon analyzer, which provides information on the amount of carbon in water at both the U.S. and Russian segments of the International Space Station since 2008. The disadvantage of this approach is the lack of compound-specific information. The recently developed methods and tools may potentially allow one to obtain in-flight a more detailed information on water quality. Namely, the microanalyzers based on potentiometric measurements were designed for online detection of chloride, potassium, nitrate ions and ammonia. The recent application of the current highly developed air quality monitoring system for water analysis was a logical step because most of the target analytes are the same in air and water. An electro-thermal vaporizer was designed, manufactured and coupled with the air quality control system. This development allowed for liberating the analytes from the aqueous matrix and further compound-specific analysis in the gas phase.

  17. EPA Office of Water (OW): STORET Water Quality Monitoring Stations Source Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Storage and Retrieval for Water Quality Data (STORET and the Water Quality Exchange, WQX) defines the methods and the data systems by which EPA compiles monitoring...

  18. EPA Office of Water (OW): STORET Water Quality Monitoring Stations NHDPlus Indexed Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Storage and Retrieval for Water Quality Data (STORET and the Water Quality Exchange, WQX) defines the methods and the data systems by which EPA compiles monitoring...

  19. EPA Office of Water (OW): STORET Water Quality Monitoring Stations Source Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Storage and Retrieval for Water Quality Data (STORET and the Water Quality Exchange, WQX) defines the methods and the data systems by which EPA compiles monitoring...

  20. Phoenix's Snow White Trench

    Science.gov (United States)

    2008-01-01

    A soil sample taken from the informally named 'Snow White' trench at NASA's Phoenix Mars Lander work site produced minerals that indicate evidence of past interaction between the minerals and liquid water. This image was taken by the Surface Stereo Imager on Sol 103, the 103rd day since landing (Sept. 8, 2008). The trench is approximately 23 centimeters (9 inches) long. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by JPL, Pasadena, Calif. Spacecraft development was by Lockheed Martin Space Systems, Denver.

  1. A dense medium electromagnetic scattering model for the InSAR correlation of snow

    Science.gov (United States)

    Lei, Yang; Siqueira, Paul; Treuhaft, Robert

    2016-05-01

    Snow characteristics, such as snow water equivalent (SWE) and snow grain size, are important characteristics for the monitoring of the global hydrological cycle and as indicators of climate change. This paper derives an interferometric synthetic aperture radar (InSAR) scattering model for dense media, such as snow, which takes into account multiple scattering effects through the Quasi-Crystalline Approximation. The result of this derivation is a simplified version of the InSAR correlation model derived for relating the InSAR correlation measurements to the snowpack characteristics of grain size, volume fraction, and layer depth as well as those aspects of the volume-ground interaction that affects the interferometric observation (i.e., the surface topography and the ratio of ground-to-volume scattering). Based on the model, the sensitivity of the InSAR correlation measurements to the snow characteristics is explored by simulation. Through this process, it is shown that Ka-band InSAR phase has a good sensitivity to snow grain size and volume fraction, while for lower frequency signals (Ku-band to L-band), the InSAR correlation magnitude and phase have a sensitivity to snow depth. Since the formulation depends, in part, on the pair distribution function, three functional forms of the pair distribution function are implemented and their effects on InSAR phase measurements compared. The InSAR scattering model described in this paper is intended to be an observational prototype for future Ka-band and L-band InSAR missions, such as NASA's Surface Water and Ocean Topography and NASA-ISRO Synthetic Aperture Radar missions, planned for launch in the 2020-2021 time frame. This formulation also enables further investigation of the InSAR-based snow retrieval approaches.

  2. A blending snow cover data base on MODIS and AMSR-E snow cover in Qinghai-Tibet Plateau

    Science.gov (United States)

    Xiaohua, H.; Wang, J.; Che, T.; Dai, L. Y.

    2012-04-01

    combination of AMSR-E snow water depth data and different spatial and temporal information, to reduce cloud obscuration from MODIS snow-cover images. Each step was performed in sequence and the output from each step was the input for the next step. The analysis was done in Arc GIS.

  3. IMPROVING CYANOBACTERIA AND CYANOTOXIN MONITORING IN SURFACE WATERS FOR DRINKING WATER SUPPLY

    Directory of Open Access Journals (Sweden)

    Jing Li

    2017-06-01

    Full Text Available Cyanobacteria in fresh water can cause serious threats to drinking water supplies. Managing cyanobacterial blooms particularly at small drinking water treatment plants is challenging. Because large amount of cyanobacteria may cause clogging in the treatment process and various cyanotoxins are hard to remove, while they may cause severe health problems. There is lack of instructions of what cyanobacteria/toxin amount should trigger what kind of actions for drinking water management except for Microcystins. This demands a Cyanobacteria Management Tool (CMT to help regulators/operators to improve cyanobacteria/cyanotoxin monitoring in surface waters for drinking water supply. This project proposes a CMT tool, including selecting proper indicators for quick cyanobacteria monitoring and verifying quick analysis methods for cyanobacteria and cyanotoxin. This tool is suggested for raw water management regarding cyanobacteria monitoring in lakes, especially in boreal forest climate. In addition, it applies to regions that apply international WHO standards for water management. In Swedish context, drinking water producers which use raw water from lakes that experience cyanobacterial blooms, need to create a monitoring routine for cyanobacteria/cyanotoxin and to monitor beyond such as Anatoxins, Cylindrospermopsins and Saxitoxins. Using the proposed CMT tool will increase water safety at surface water treatment plants substantially by introducing three alerting points for actions. CMT design for each local condition should integrate adaptive monitoring program.

  4. Oxygen isotope composition of water and snow-ice cover of isolated lakes at various stages of separation from the White Sea

    Science.gov (United States)

    Lisitzin, A. P.; Vasil'chuk, Yu. K.; Shevchenko, V. P.; Budantseva, N. A.; Krasnova, E. D.; Pantyulin, A. N.; Filippov, A. S.; Chizhova, Ju. N.

    2013-04-01

    This study aimed to analyze the oxygen isotope composition of water, ice, and snow in water bodies isolated from the White Sea and to identify the structural peculiarities of these pools during the winter period. The studies were performed during early spring in Kandalaksha Bay of the White Sea, in Velikaya Salma Strait and in Rugoserskaya Inlet. The studied water bodies differ in their degree of isolation from the sea. In particular, Ermolinskaya Inlet has normal water exchange with the sea; the Lake on Zelenyi Cape represents the first stage of isolation; i. e., it has permanent water exchange with the sea by the tide. Kislo-Sladkoe Lake receives sea water from time to time. Trekhtsvetnoe Lake is totally isolated from the sea and is a typical meromictic lake. Finally, Nizhnee Ershovskoe Lake exhibits some features of a saline water body. The oxygen isotope profile of the water column in Trekhtsvetnoe Lake allows defining three layers; this lake may be called typically meromictic. The oxygen isotope profile of the water column in Kislo-Sladkoe Lake is even from the surface to the bottom. The variability of δ18O is minor in Lake on Zelenyi Cape. A surface layer (0-1 m) exists in Nizhnee Ershovskoe Lake, and the oxygen isotope variability is well pronounced. Deeper, where the freshwater dominates, the values of ?18Îvary insignificantly disregarding the water depth and temperature. This fresh water lake is not affected by the seawater and is not stratified according to the isotope profile. It is found that applying the values of ?18Î and profiles of temperature and salinity may appear as an effective method in defining the water sources feeding the water bodies isolated from the sea environment.

  5. Assimilation of satellite information in a snowpack model to improve characterization of snow cover for runoff simulation and forecasting

    Directory of Open Access Journals (Sweden)

    L. S. Kuchment

    2009-08-01

    Full Text Available A new technique for constructing spatial fields of snow characteristics for runoff simulation and forecasting is presented. The technique incorporates satellite land surface monitoring data and available ground-based hydrometeorological measurements in a physical based snowpack model. The snowpack model provides simulation of temporal changes of the snow depth, density and water equivalent (SWE, accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with a special focus on forest cover effects. The model was first calibrated against available ground-based snow measurements and then was applied to calculate the spatial distribution of snow characteristics using satellite data and interpolated ground-based meteorological data. The remote sensing data used in the model consist of products derived from observations of MODIS and AMSR-E instruments onboard Terra and Aqua satellites. They include daily maps of snow cover, snow water equivalent (SWE, land surface temperature, and weekly maps of surface albedo. Maps of land cover classes and tree cover fraction derived from NOAA AVHRR were used to characterize the vegetation cover. The developed technique was tested over a study area of approximately 200 000 km2 located in the European part of Russia (56° N to 60° N, and 48° E to 54° E. The study area comprises the Vyatka River basin with the catchment area of 124 000 km2. The spatial distributions of SWE, obtained with the coupled model, as well as solely from satellite data were used as the inputs in a physically-based model of runoff generation to simulate runoff hydrographs on the Vyatka river for spring seasons of 2003, 2005. The comparison of simulated hydrographs with the observed ones has shown that suggested procedure gives a higher accuracy of snow cover spatial distribution representation and hydrograph simulations than the direct use of satellite SWE data.

  6. Assimilation of satellite information in a snowpack model to improve characterization of snow cover for runoff simulation and forecasting

    Science.gov (United States)

    Kuchment, L. S.; Romanov, P.; Gelfan, A. N.; Demidov, V. N.

    2009-08-01

    A new technique for constructing spatial fields of snow characteristics for runoff simulation and forecasting is presented. The technique incorporates satellite land surface monitoring data and available ground-based hydrometeorological measurements in a physical based snowpack model. The snowpack model provides simulation of temporal changes of the snow depth, density and water equivalent (SWE), accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with a special focus on forest cover effects. The model was first calibrated against available ground-based snow measurements and then was applied to calculate the spatial distribution of snow characteristics using satellite data and interpolated ground-based meteorological data. The remote sensing data used in the model consist of products derived from observations of MODIS and AMSR-E instruments onboard Terra and Aqua satellites. They include daily maps of snow cover, snow water equivalent (SWE), land surface temperature, and weekly maps of surface albedo. Maps of land cover classes and tree cover fraction derived from NOAA AVHRR were used to characterize the vegetation cover. The developed technique was tested over a study area of approximately 200 000 km2 located in the European part of Russia (56° N to 60° N, and 48° E to 54° E). The study area comprises the Vyatka River basin with the catchment area of 124 000 km2. The spatial distributions of SWE, obtained with the coupled model, as well as solely from satellite data were used as the inputs in a physically-based model of runoff generation to simulate runoff hydrographs on the Vyatka river for spring seasons of 2003, 2005. The comparison of simulated hydrographs with the observed ones has shown that suggested procedure gives a higher accuracy of snow cover spatial distribution representation and hydrograph simulations than the direct use of satellite SWE data.

  7. Statistical Framework for Recreational Water Quality Criteria and Monitoring

    DEFF Research Database (Denmark)

    Halekoh, Ulrich

    2008-01-01

    Administrators of recreational waters face the basic tasks of surveillance of water quality and decisions on beach closure in case of unacceptable quality. Monitoring and subsequent decisions are based on sampled water probes and fundamental questions are which type of data to extract from......-term actions, such as the closing of beaches and long-term monitoring tasks. Chapter 4 compares sampling plans as control charts and acceptance sampling and relates them to decision rules for closing beach waters. Chapter 5 contrasts modeling approaches using design-based sampling strategies either...... recreational governmental authorities controlling water quality. The book opens with a historical account of water quality criteria in the USA between 1922 and 2003. Five chapters are related to sampling strategies and decision rules. Chapter 2 discusses the dependence of decision-making rules on short...

  8. Remotely Measuring Snow Depth in Inaccessible Terrain

    Science.gov (United States)

    Dixon, D.; Boon, S.

    2010-12-01

    In watershed-scale studies of snow accumulation, high alpine areas are typically important accumulation areas. While snow depth measurements may not be collected in these regions due to avalanche danger, failing to include them in basin-wide estimates of snow accumulation may lead to large underestimates of basin-scale water yield. We present a new method to measure spatially distributed point snow depths remotely. Previously described methods using terrestrial laser scanning (TLS) systems, airborne light detection and ranging (LiDAR) systems, and hand-held laser distance meters have several limitations related to cost, data processing, and accuracy, thus reducing their applicability. The use of a modern robotic total station attempts to resolve these limitations. Total stations have much greater measurement accuracy than laser distance meters, and are significantly less expensive then TLS and LiDAR systems. Data can be output in common data formats, simplifying data processing and management. Measurement points can also be resampled repeatedly throughout the season with high accuracy and precision. Simple trigonometry is used to convert total station measurements into estimates of snow depth perpendicular to the slope. We present results of remote snow depth measurements using a Leica Geosystems TCRP 1201+ robotic total station. Snow depth estimates from the station are validated against measured depths in a field trial. The method is then applied in a basin-scale study to collect and calculate high elevation snow depth, in combination with traditional snow surveys at lower elevations.

  9. Monitoring eastern Oklahoma lake water quality using Landsat

    Science.gov (United States)

    Barrett, Clay

    The monitoring of public waters for recreational, industrial, agricultural, and drinking purposes is a difficult task assigned to many state water agencies. The Oklahoma Water Resources Board (OWRB) is only physically monitoring a quarter of the lakes it is charged with monitoring in any given year. The minimal sample scheme adopted by the OWRB is utilized to determine long-term trends and basic impairment but is insufficient to monitor the water quality shifts that occur following influx from rains or to detect algal blooms, which may be highly localized and temporally brief. Recent work in remote sensing calibrates reflectance coefficients between extant water quality data and Landsat imagery reflectance to estimate water quality parameters on a regional basis. Remotely-sensed water quality monitoring benefits include reduced cost, more frequent sampling, inclusion of all lakes visible each satellite pass, and better spatial resolution results. The study area for this research is the Ozark foothills region in eastern Oklahoma including the many lakes impacted by phosphorus flowing in from the Arkansas border region. The result of this research was a moderate r2 regression value for turbidity during winter (0.52) and summer (0.65), which indicates that there is a seasonal bias to turbidity estimation using this methodology and the potential to further develop an estimation equation for this water quality parameter. Refinements that improve this methodology could provide state-wide estimations of turbidity allowing more frequent observation of water quality and allow better response times by the OWRB to developing water impairments.

  10. Characteristics of snow cover in the forest-steppe of Cisbaikalia

    Directory of Open Access Journals (Sweden)

    E. V. Maksyutova

    2012-01-01

    Full Text Available Statistical parameters and tendencies of the long-term changes in snow cover characteristics of forest-steppe in Fore-Baykal region were evaluated according to the observational data obtained at meteorological stations by means of permanent snow stake as well as using snow survey in the field and in the forest for the long-term period 1961–2000. Duration of snow cover decreases. The snow depth according to the permanent snow stake increases. The observed values of snow survey show that in the field without any significant changes in the snow depth manifest itself the local effect of water supply reduction in the snow cover. The largest rates of decrease of snow depth and snow storage has experienced in the forest. The maximum snow density decreases both in the field and in forest.

  11. Estimating maritime snow density from seasonal climate variables

    Science.gov (United States)

    Bormann, K. J.; Evans, J. P.; Westra, S.; McCabe, M. F.; Painter, T. H.

    2013-12-01

    Snow density is a complex parameter that influences thermal, optical and mechanical snow properties and processes. Depth-integrated properties of snowpacks, including snow density, remain very difficult to obtain remotely. Observations of snow density are therefore limited to in-situ point locations. In maritime snowfields such as those in Australia and in parts of the western US, snow densification rates are enhanced and inter-annual variability is high compared to continental snow regions. In-situ snow observation networks in maritime climates often cannot characterise the variability in snowpack properties at spatial and temporal resolutions required for many modelling and observations-based applications. Regionalised density-time curves are commonly used to approximate snow densities over broad areas. However, these relationships have limited spatial applicability and do not allow for interannual variability in densification rates, which are important in maritime environments. Physically-based density models are relatively complex and rely on empirical algorithms derived from limited observations, which may not represent the variability observed in maritime snow. In this study, seasonal climate factors were used to estimate late season snow densities using multiple linear regressions. Daily snow density estimates were then obtained by projecting linearly to fresh snow densities at the start of the season. When applied spatially, the daily snow density fields compare well to in-situ observations across multiple sites in Australia, and provide a new method for extrapolating existing snow density datasets in maritime snow environments. While the relatively simple algorithm for estimating snow densities has been used in this study to constrain snowmelt rates in a temperature-index model, the estimates may also be used to incorporate variability in snow depth to snow water equivalent conversion.

  12. A proposed ground-water quality monitoring network for Idaho

    Science.gov (United States)

    Whitehead, R.L.; Parliman, D.J.

    1979-01-01

    A ground water quality monitoring network is proposed for Idaho. The network comprises 565 sites, 8 of which will require construction of new wells. Frequencies of sampling at the different sites are assigned at quarterly, semiannual, annual, and 5 years. Selected characteristics of the water will be monitored by both laboratory- and field-analysis methods. The network is designed to: (1) Enable water managers to keep abreast of the general quality of the State 's ground water, and (2) serve as a warning system for undesirable changes in ground-water quality. Data were compiled for hydrogeologic conditions, ground-water quality, cultural elements, and pollution sources. A ' hydrologic unit priority index ' is used to rank 84 hydrologic units (river basins or segments of river basins) of the State for monitoring according to pollution potential. Emphasis for selection of monitoring sites is placed on the 15 highest ranked units. The potential for pollution is greatest in areas of privately owned agricultural land. Other areas of pollution potential are residential development, mining and related processes, and hazardous waste disposal. Data are given for laboratory and field analyses, number of site visits, manpower, subsistence, and mileage, from which costs for implementing the network can be estimated. Suggestions are made for data storage and retrieval and for reporting changes in water quality. (Kosco-USGS)

  13. Monitoring of radon in water of Taiwan

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Yu-Ming; Chen, Chin-Chiang (Taiwan Radiation Monitoring Station, Atomic Energy Council of Executive Yuan, Kaohsiung Hsien (Republic of China))

    1983-03-01

    The toluene extraction-liquid scintillation counting method was used to measure the radon concentration in water samples of Taiwan, R.O.C. The experimental results showed that the counting efficiency for both ..cap alpha.. and ..beta.. emitted from radon and its daughters could reach 100%. The separation of activity of /sup 222/Rn from /sup 220/Rn was performed according to Bunny method. Thirty sampling stations including water samples from wells and hot springs throughout Taiwan were analyzed. The measured data show that /sup 220/Rn has much higher concentration than /sup 222/Rn. The concentration for the former is in the order of 10/sup -7/ Ci/l while that for the later is about 10/sup -10/ Ci/l.

  14. Assessing temporal representativeness of water quality monitoring data.

    Science.gov (United States)

    Anttila, Saku; Ketola, Mirva; Vakkilainen, Kirsi; Kairesalo, Timo

    2012-02-01

    The effectiveness of different monitoring methods in detecting temporal changes in water quality depends on the achievable sampling intervals, and how these relate to the extent of temporal variation. However, water quality sampling frequencies are rarely adjusted to the actual variation of the monitoring area. Manual sampling, for example, is often limited by the level of funding and not by the optimal timing to take samples. Restrictions in monitoring methods therefore often determine their ability to estimate the true mean and variance values for a certain time period or season. Consequently, we estimated how different sampling intervals determine the mean and standard deviation in a specific monitoring area by using high frequency data from in situ automated monitoring stations. Raw fluorescence measurements of chlorophyll a for three automated monitoring stations were calibrated by using phycocyanin fluorescence measurements and chlorophyll a analyzed from manual water samples in a laboratory. A moving block bootstrap simulation was then used to estimate the standard errors of the mean and standard deviations for different sample sizes. Our results showed that in a temperate, meso-eutrophic lake, relatively high errors in seasonal statistics can be expected from monthly sampling. Moreover, weekly sampling yielded relatively small accuracy benefits compared to a fortnightly sampling. The presented method for temporal representation analysis can be used as a tool in sampling design by adjusting the sampling interval to suit the actual temporal variation in the monitoring area, in addition to being used for estimating the usefulness of previously collected data.

  15. A Seamless Framework for Global Water Cycle Monitoring and Prediction

    Science.gov (United States)

    Sheffield, J.; Wood, E. F.; Chaney, N.; Fisher, C. K.; Caylor, K. K.

    2013-12-01

    The Global Earth Observation System of Systems (GEOSS) Water Strategy ('From Observations to Decisions') recognizes that 'water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity', and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the development of a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions

  16. [Review of monitoring soil water content using hyperspectral remote sensing].

    Science.gov (United States)

    Wu, Dai-hui; Fan, Wen-jie; Cui, Yao-kui; Yan, Bin-yan; Xu, Xi-ru

    2010-11-01

    Soil water content is a key parameter in monitoring drought. In recent years, a lot of work has been done on monitoring soil water content based on hyperspectral remotely sensed data both at home and abroad. In the present review, theories, advantages and disadvantages of the monitoring methods using different bands are introduced first. Then the unique advantages, as well as the problems, of the monitoring method with the aid of hyperspectral remote sensing are analyzed. In addition, the impact of soil water content on soil reflectance spectrum and the difference between values at different wavelengths are summarized. This review lists and summarizes the quantitative relationships between soil water content and soil reflectance obtained through analyzing the physical mechanism as well as through statistical way. The key points, advantages and disadvantages of each model are also analyzed and evaluated. Then, the problems in experimental study are pointed out, and the corresponding solutions are proposed. At the same time, the feasibility of removing vegetation effect is discussed, when monitoring soil water content using hyperspectral remote sensing. Finally, the future research trend is prospected.

  17. Modelling high-resolution snow cover precipitation supply for German river catchments with SNOW 4

    Science.gov (United States)

    Böhm, Uwe; Reich, Thomas; Schneider, Gerold; Fiedler, Anett

    2013-04-01

    Formation of snow cover causes a delayed response of surface to precipitation. Both melting of snow and release of liquid water retained within the snow cover form precipitation supply which contributes to runoff and infiltration. The model SNOW 4 is developed to simulate snow cover accumulation and depletion and the resulting precipitation supply on a regular grid. The core of the model is formed by a set of equations which describe the snow cover energy and mass balance. The snow surface energy balance is calculated as a result of the radiation balance and the heat fluxes between atmosphere, soil and snow cover. The available melting heat enters the mass balance computation part of the model and melting of snow or freezing of liquid water within the snow layer takes place depending on its sign. Retention, aging and snow cover regeneration are taken into consideration. The model runs operationally 4 times a day and provides both a snow cover and precipitation supply analysis for the last 30 hours and a forecast for up to 72 hours. For the 30-hour analysis, regionalised observations are used both to define the initial state and force the model. Hourly measurements of air temperature, water vapour pressure, wind speed, global radiation or sunshine duration and precipitation are interpolated to the model grid. For the forecast period, SNOW 4 obtains the required input data from the operational products of the COSMO-EU weather forecast model. The size of a grid box is 1km2. The model area covers a region of 1100x1000km2 and includes the catchments of the German rivers completely. The internal time step is set to 1 hour. Once a day, the compliance between model and regionalized snow cover data is assessed. If discrepancies exceed certain thresholds, the model must be adjusted by a weighted approach towards the observations. The model simulations are updated every six hours based on the most recent observations and weather forecasts. The model works operationally since

  18. Monitoring water quality in Lake Atitlan, Guatemala using Earth Observations

    Science.gov (United States)

    Flores Cordova, A. I.; Christopher, S. A.; Griffin, R.; Limaye, A. S.; Irwin, D.

    2014-12-01

    Frequent and spatially continuous water quality monitoring is either unattainable or challenging for developing nations if only standard methods are used. Such standard methods rely on in situ water sampling, which is expensive, time-consuming and point specific. Through the Regional Visualization and Monitoring System (SERVIR), Lake Atitlan's water quality was first monitored in 2009 using Earth observation satellites. Lake Atitlan is a source of drinking water for the towns located nearby and a major touristic attraction for the country. Several multispectral sensors were used to monitor the largest algal bloom known to date for the lake, which covered 40% of the lake's 137 square kilometer surface. Red and Near-Infrared bands were used to isolate superficial algae from clean water. Local authorities, media, universities and local communities, broadly used the information provided by SERVIR for this event. It allowed estimating the real extent of the algal bloom and prompted immediate response for the government to address the event. However, algal blooms have been very rare in this lake. The lake is considered oligotrophic given its relatively high transparency levels that can reach 15 m in the dry season. To continue the support provided by SERVIR in the algal bloom event, an algorithm to monitor chlorophyll a (Chl a) concentration under normal conditions was developed with the support of local institutions. Hyperspectral data from Hyperion on board EO-1 and in situ water quality observations were used to develop a semi-empirical algorithm for the lake. A blue to green band ratio successfully modeled Chl a concentration in Lake Atitlan with a relative error of 33%. This presentation will explain the process involved from providing an emergency response to developing a tailored tool for monitoring water quality in Lake Atitlan, Guatemala.

  19. Alternative techniques for deep-water monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Matveev, Viktor A. [Institute for Nuclear Research, Russian Academy of Sciences, 60th October Anniversary Prospect 7a, Moscow 117312 (Russian Federation); Zheleznykh, Igor M., E-mail: zhelezny@minus.inr.ac.r [Institute for Nuclear Research, Russian Academy of Sciences, 60th October Anniversary Prospect 7a, Moscow 117312 (Russian Federation); Korotin, Pavel I. [Institute of Applied Physics, Russian Academy of Sciences, Ul' yanov Str., 46, Nizhnii Novgorod 603950 (Russian Federation); Paka, Vadim T. [P.P. Shirshov Institute of Oceanology - Atlantic Branch, Russian Academy of Sciences, Mir Prospect 1, Kaliningrad 236022 (Russian Federation); Surin, Nikolai M. [N.S. Enikolopov Institute of Synthetic Polymer Materials, Russian Academy of Sciences, Profsojuznaya Str. 70, Moscow 117393 (Russian Federation)

    2011-01-21

    A cruise of the Soviet R/V 'Dmitry Mendeleyev' in the Mediterranean Sea in 1989 is mentioned as the first step towards an international cooperation for high energy neutrino astrophysics in the Mediterranean. New proposals are considered related to carrying out common investigations connected with the construction of a large-scale neutrino telescope in the Mediterranean. In these investigations new techniques, which were developed in the last years or are being developed now by the Russian institutes, could be used, and in particular: (1) a system of multi-parameter non-tethered probes for deep-water hydrographic measurements, (2) a bottom-mounted acoustical antenna consisting of smart digital hydrophones, and (3) a deep-water scintillation spectrometer for the determination of the composition and for measuring the concentration of dissolved radionuclides. Given the necessity of making a best choice for the KM3 Neutrino Telescope construction, the idea of using light-weight flexible elements for making a 'flexible tower' presented at the Taormina Workshop in 1997 is reviewed.

  20. Agricultural Applications for Remotely Sensed Evapotranspiration Data in Monitoring Water Use, Water Quality, and Water Security

    Science.gov (United States)

    Anderson, M. C.; Hain, C.; Gao, F.; Yang, Y.; Sun, L.; Dulaney, W.; Sharifi, A.; Holmes, T. R.; Kustas, W. P.

    2016-12-01

    Across the U.S. and globally there are ever increasing and competing demands for freshwater resources in support of food production, ecosystems services and human/industrial consumption. Recent studies using the GRACE satellite have identified severely stressed aquifers globally, which are being unsustainably depleted due to over-extraction primarily in support of irrigated agriculture. In addition, historic droughts and ongoing political conflicts threaten food and water security in many parts of the world. To facilitate wise water management, and to develop sustainable agricultural systems that will feed the Earth's growing population into the future, there is a critical need for robust assessments of daily water use, or evapotranspiration (ET), over a wide range in spatial scales - from field to globe. While Earth Observing (EO) satellites can play a significant role in this endeavor, no single satellite provides the combined spatial, spectral and temporal characteristics required for actionable ET monitoring world-wide. In this presentation we discuss new methods for combining information from the current suite of EO satellites to address issues of water use, water quality and water security, particularly as they pertain to agricultural production. These methods fuse multi-scale diagnostic ET retrievals generated using shortwave, thermal infrared and microwave datasets from multiple EO platforms to generate ET datacubes with both high spatial and temporal resolution. We highlight several case studies where such ET datacubes are being mined to investigate changes in water use patterns over agricultural landscapes in response to changing land use, land management, and climate forcings.

  1. Applications for remotely sensed evapotranspiration data in monitoring water quality, water use, and water security

    Science.gov (United States)

    Anderson, Martha; Hain, Christopher; Feng, Gao; Yang, Yun; Sun, Liang; Yang, Yang; Dulaney, Wayne; Sharifi, Amir; Kustas, William; Holmes, Thomas

    2017-04-01

    Across the globe there are ever-increasing and competing demands for freshwater resources in support of food production, ecosystems services and human/industrial consumption. Recent studies using the GRACE satellite have identified severely stressed aquifers that are being unsustainably depleted due to over-extraction, primarily in support of irrigated agriculture. In addition, historic droughts and ongoing political conflicts threaten food and water security in many parts of the world. To facilitate wise water management, and to develop sustainable agricultural systems that will feed the Earth's growing population into the future, there is a critical need for robust assessments of daily water use, or evapotranspiration (ET), over a wide range in spatial scales - from field to globe. While Earth Observing (EO) satellites can play a significant role in this endeavor, no single satellite provides the combined spatial, spectral and temporal characteristics required for actionable ET monitoring world-wide. In this presentation we discuss new methods for combining information from the current suite of EO satellites to address issues of water quality, water use and water security, particularly as they pertain to agricultural production. These methods fuse multi-scale diagnostic ET retrievals generated using shortwave, thermal infrared and microwave datasets from multiple EO platforms to generate ET datacubes with both high spatial and temporal resolution. We highlight several case studies where such ET datacubes are being mined to investigate changes in water use patterns over agricultural landscapes in response to changing land use, land management, and climate forcings.

  2. Pesticides in Drinking Water – The Brazilian Monitoring Program

    Science.gov (United States)

    Barbosa, Auria M. C.; Solano, Marize de L. M.; Umbuzeiro, Gisela de A.

    2015-01-01

    Brazil is the world largest pesticide consumer; therefore, it is important to monitor the levels of these chemicals in the water used by population. The Ministry of Health coordinates the National Drinking Water Quality Surveillance Program (Vigiagua) with the objective to monitor water quality. Water quality data are introduced in the program by state and municipal health secretariats using a database called Sisagua (Information System of Water Quality Monitoring). Brazilian drinking water norm (Ordinance 2914/2011 from Ministry of Health) includes 27 pesticide active ingredients that need to be monitored every 6 months. This number represents <10% of current active ingredients approved for use in the country. In this work, we analyzed data compiled in Sisagua database in a qualitative and quantitative way. From 2007 to 2010, approximately 169,000 pesticide analytical results were prepared and evaluated, although approximately 980,000 would be expected if all municipalities registered their analyses. This shows that only 9–17% of municipalities registered their data in Sisagua. In this dataset, we observed non-compliance with the minimum sampling number required by the norm, lack of information about detection and quantification limits, insufficient standardization in expression of results, and several inconsistencies, leading to low credibility of pesticide data provided by the system. Therefore, it is not possible to evaluate exposure of total Brazilian population to pesticides via drinking water using the current national database system Sisagua. Lessons learned from this study could provide insights into the monitoring and reporting of pesticide residues in drinking water worldwide. PMID:26581345

  3. PESTICIDES IN DRINKING WATER - THE BRAZILIAN MONITORING PROGRAM

    Directory of Open Access Journals (Sweden)

    Auria Maria Cavalvante Barbosa

    2015-11-01

    Full Text Available Brazil is the world largest pesticide consumer, therefore it is important to monitor the levels of these chemicals in the water used by population. The Ministry of Health coordinates the National Drinking Water Quality Surveillance Program (Vigiagua with the objective to monitor water quality. Water quality data are introduced in the program by state and municipal health secretariats using a database called Sisagua (Information System of Water Quality Monitoring. Brazilian drinking water norm (Ordinance 2914/2011 from Ministry of Health includes 27 pesticide active ingredients that need to be monitored every six months. This number represents less than 10% of current active ingredients approved for use in the country. In this work we analyzed data compiled in Sisagua database in a qualitative and quantitative way. From 2007 to 2010, approximately 169,000 pesticide analytical results were prepared and evaluated, although approximately 980,000 would be expected if all municipalities registered their analyses. This shows that only 9 to 17% of municipalities registered their data in Sisagua. In this dataset we observed noncompliance with the minimum sampling number required by the norm, lack of information about detection and quantification limits, insufficient standardization in expression of results, and several inconsistencies, leading to low credibility of pesticide data provided by the system. Therefore, it is not possible to evaluate exposure of total Brazilian population to pesticides via drinking water using the current national database system Sisagua. Lessons learned from this study could provide insights into the monitoring and reporting of pesticide residues in drinking water worldwide.

  4. Plausibility check of a redesigned rain-on-snow simulator (RASA)

    Science.gov (United States)

    Rössler, Ole; Probst, Sabine; Weingartner, Rolf

    2016-04-01

    Rain-on-snow events are fascinating but still not completely understood processes. Although, several studies and equations have been published since decades that describe past events and theoretical descriptions, empirical data of what is happening in the snow cover is far less available. A way to fill this gap of empirical data, rain-on-snow-simulators might be of help. In 2013, Juras et al. published their inspiring idea of a portable rain-on-snow simulator. The huge advantage of this devise - in contrast to other purely field-based experiments - are their fixed, and mostly standardized conditions and the possibility to measure all required data to monitor the water fluxes and melting processes at a time. Mounted in a convenient location, a large number of experiments are relatively easy conductible. We applied and further developed the original device and plausified the results of this redesigned version, called RASA. The principal design was borrowed from the original version being a frame with a sprinkler on top and a snow sample in a box at the bottom, from which the outflow is measured with a tipping gauge. We added a moving sprinkling plate to ensure a uniform distribution of raindrops on the snow, and - most importantly - we suspended the watered snow sampled on weighting cells. The latter enables to continuous measurement of the snow sample throughout the experiment and thus the indirect quantification of liquid water saturation, water holding capacity, and snowmelt amount via balance equations. As it is remains unclear if this device is capable to reproduce known processes, a hypothesis based plausibility check was accomplished. Thus, eight hypothesizes were derived from literature and tested in 28 experiments with the RASA mounted at 2000 m elevation. In general, we were able to reproduce most of the hypotheses. The RASA proved to be a very valuable device that can generate suitable results and has the potential to extend the empirical-experimental data

  5. Snowpack displacement measured by terrestrial radar interferometry as precursor for wet snow avalanches

    Science.gov (United States)

    Caduff, Rafael; Wiesmann, Andreas; Bühler, Yves

    2016-04-01

    Wet snow and full depth gliding avalanches commonly occur on slopes during springtime when air temperatures rise above 0°C for longer time. The increase in the liquid water content changes the mechanical properties of the snow pack. Until now, forecasts of wet snow avalanches are mainly done using weather data such as air and snow temperatures and incoming solar radiation. Even tough some wet snow avalanche events are indicated before the release by the formation of visible signs such as extension cracks or compressional bulges in the snow pack, a large number of wet snow avalanches are released without any previously visible signs. Continuous monitoring of critical slopes by terrestrial radar interferometry improves the scale of reception of differential movement into the range of millimetres per hour. Therefore, from a terrestrial and remote observation location, information on the mechanical state of the snow pack can be gathered on a slope wide scale. Recent campaigns in the Swiss Alps showed the potential of snow deformation measurements with a portable, interferometric real aperture radar operating at 17.2 GHz (1.76 cm wavelength). Common error sources for the radar interferometric measurement of snow pack displacements are decorrelation of the snow pack at different conditions, the influence of atmospheric disturbances on the interferometric phase and transition effects from cold/dry snow to warm/wet snow. Therefore, a critical assessment of those parameters has to be considered in order to reduce phase noise effects and retrieve accurate displacement measurements. The most recent campaign in spring 2015 took place in Davos Dorf/GR, Switzerland and its objective was to observe snow glide activity on the Dorfberg slope. A validation campaign using total station measurements showed good agreement to the radar interferometric line of sight displacement measurements in the range of 0.5 mm/h. The refinement of the method led to the detection of numerous gliding

  6. Evaluating the potential of MSG-SEVIRI snow cover images for hydrological modeling

    Science.gov (United States)

    Surer, S.; Parajka, J.; Akyurek, Z.; Bloeschl, G.

    2012-12-01

    Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board of MSG (METEOSAT Second Generation) geostationary satellite enables snow cover monitoring at very high temporal resolution (15 min). It is a key component of the recent EUMETSAT programme for Satellite Application Facility on Support to operational Hydrology and Water Management (H-SAF) project. The main aim of the project is to develop and test new satellite products, which will comply the requirements for operational hydrology and water resources management. The objective of this study is (a) to compare snow cover product (H10) derived from MSG-SEVIRI with MODIS (MOD10A1) snow cover product, (b) to examine the MSG-SEVIRI snow mapping accuracy against in situ snow observations, (c) to test potential of H10 snow cover products for calibration and validation of a conceptual hydrologic model. We compare MSG-SEVIRI, MODIS grid maps and daily snow depth measurements at 272 climate stations over Austria in the period from October 2007 to June 2012. The results indicate that temporal merging of 15 minutes MSG-SEVIRI observations allows a reduction of cloud coverage at daily time scale. The relative number of days with cloud coverage in winter season is on average 35% for MSG-SEVIRI, compared to 65% for MODIS dataset. The coarser spatial resolution of MSG-SEVIRI, namely 0.05o, however, resulted in lower mapping accuracy. The overall snow cover mapping error is 5% for MODIS and 15% for MSG-SEVIRI, respectively. Our results showed that for MSG-SEVIRI dataset the underestimation errors dominate and tend to increase with increasing altitude of climate stations. Our results showed that for MSG-SEVIRI dataset the underestimation errors dominated. The potential of MSG-SEVIRI product (H10) for hydrological modeling is examined in two mountain catchments in Austria and Turkey. We will evaluate the potential of snow cover data from the MSG-SEVIRI for calibrating and validating a conceptual semi

  7. Monitoring the water vapor isotopic composition in the temperate North Atlantic

    Science.gov (United States)

    Sveinbjörnsdottir, Arny E.; Steen-Larsen, Hans Christian; Jonsson, Thorsteinn; Johnsen, Sigfus J.

    2013-04-01

    Water stable isotopes have during many decades been used as climate proxies and indicators for variations in the hydrological cycle. However we are to a great extent still using simple empirical relationships without any deeper theoretical understanding. In order to properly relate changes in the climate and hydrological cycle to changes in the observed stable water isotopic signal we must understand the underlying physical processes. Furthermore it is a challenge for General Climate Models to adequately represent the isotopes in the hydrological cycle because of lack of in-situ measurements of the atmospheric water-vapor composition in the source regions. During the fall of 2010 we installed an autonomous water vapor spectroscopy laser (from Los Gatos Research) in a lighthouse on the South Coast of Iceland (63.83 N 21.47W) with the plan to be operational for several years. The purpose of this installation was through monitoring of the water vapor isotopic composition to understand the physical processes governing the isotopic composition of the water vapor evaporated from the ocean as well as the processes of mixing between the free troposphere and marine boundary layer. Because of the remoteness of the monitoring site and simple topography we are able to isolate the 'fingerprint' on the isotopic signal in the water vapor from respectively the ocean and the interior highland leading to a near perfect case-study area. Using back-trajectories we find a strong influence of the origin of the air masses on the measured isotopic composition. The mixing of the marine-boundary layer is found to strongly influence the measured isotopic composition. The second order isotopic parameter, d-excess, is contrary to theory and previous observations found not to depend on the relative humidity. However we do find a good correlation between the d-excess and the measured isotopic composition. We speculate that the lack of correlation between d-excess and relative humidity can be

  8. Effects of substrate differences on water availability for Arctic lichens during the snow-free summers in the High Arctic glacier foreland

    Science.gov (United States)

    Inoue, Takeshi; Kudoh, Sakae; Uchida, Masaki; Tanabe, Yukiko; Inoue, Masakane; Kanda, Hiroshi

    2014-12-01

    We used observational and experimental analyses to investigate the photosynthetic activity and water relationships of five lichen species attached to different substrates in a glacier foreland in the High Arctic, Ny-Ålesund, Svalbard (79°N) during the snow-free season in 2009 and 2010. After the rains ceased, lichens and their attached substrates quickly dried, whereas photosynthetic activity in the lichens decreased gradually. The in situ photosynthetic activity was estimated based on the relative electron transportation rate (rETR) in four fruticose lichens: Cetrariella delisei, Flavocetraria nivalis, Cladonia arbuscula ssp. mitis, and Cladonia pleurota. The rETR approached zero around noon, although the crustose lichen Ochrolechia frigida grown on biological soil crust (BSC) could acquire water from the BSC and retain its WC to perform positive photosynthesis. The light-rETR relationship curves of the five well-watered lichens were characterized into two types: shade-adapted with photoinhibition for the fruticose lichens, and light-adapted with no photoinhibition for O. frigida. The maximum rETR was expected to occur when they could acquire water from the surrounding air or from substrates during the desiccation period. Our results suggest that different species of Arctic lichens have different water availabilities due to their substrates and/or morphological characteristics, which affect their photosynthetic active periods during the summer.

  9. Snow modeling using SURFEX with the CROCUS snow scheme for Norway

    Science.gov (United States)

    Vikhamar-Schuler, D.; Müller, K.

    2012-04-01

    In 2010 a research project was initiated with the aim to investigate methods to establish a regional snow avalanche forecasting system for Norway. A part of this project concerns snow models that simulate snow stratigraphy and physical parameters in the snow pack. For this purpose we have used the CROCUS snow scheme within the land surface model SURFEX for the location of 18 weather stations in Norway. We have carried out a sensitivity study of available meteorological data. Few weather stations have measurements of all the parameters used by the model on an hourly basis. Therefore it is interesting to investigate if certain parameters can be replaced by short-term prognoses from the operational weather prediction models (Unified Model-4 km, HARMONIE-4 km and postprocessed prognoses of temperature and precipitation). This study indicates that short-term prognoses of radiation, air humidity, wind and air pressure may replace observations without loosing the quality of the snow simulations. For all stations the modeled snow depth is validated with the observed snow depth for the last 2-3 winter seasons. Our results show that the modeled snow depth is most sensitive to precipitation and air temperature. Overall, very good estimates of the snow depth are obtained using the CROCUS snow scheme, except for very wind exposed stations. Temperatures within the snowpack were compared with observations of snow temperature at the Filefjell station, showing promising results. A cold bias was observed, but daily variations were reasonably modeled. During the winter 2011/2012 a series of snow stratigraphy observations from the Filefjell station is carried out for validation purposes of other intra-snowpack physical properties (density, liquid water content, temperature, grain type).

  10. Application of Bayesian decision theory to airborne gamma snow measurement

    Science.gov (United States)

    Bissell, V. C.

    1975-01-01

    Measured values of several variables are incorporated into the calculation of snow water equivalent as measured from an aircraft by snow attenuation of terrestrial gamma radiation. Bayesian decision theory provides a snow water equivalent measurement by taking into account the uncertainties in the individual measurement variables and filtering information about the measurement variables through prior notions of what the calculated variable (water equivalent) should be.

  11. Modelling of snow exceedances

    Science.gov (United States)

    Jordanova, Pavlina K.; Sadovský, Zoltán; Stehlík, Milan

    2017-07-01

    Modelling of snow exceedances is of great importance and interest for ecology, civil engineering and general public. We suggest the favorable fit for exceedances related to the exceptional snow loads from Slovakia, assuming that the data is driven by Generalised Pareto Distribution or Generalized Extreme Value Distribution. Further, the statistical dependence between the maximal snow loads and the corresponding altitudes is studied.

  12. Comparison of methods for quantifying surface sublimation over seasonally snow-covered terrain

    Science.gov (United States)

    Sexstone, Graham A.; Clow, David W.; Stannard, David I.; Fassnacht, Steven R.

    2016-01-01

    Snow sublimation can be an important component of the snow-cover mass balance, and there is considerable interest in quantifying the role of this process within the water and energy balance of snow-covered regions. In recent years, robust eddy covariance (EC) instrumentation has been used to quantify snow sublimation over snow-covered surfaces in complex mountainous terrain. However, EC can be challenging for monitoring turbulent fluxes in snow-covered environments because of intensive data, power, and fetch requirements, and alternative methods of estimating snow sublimation are often relied upon. To evaluate the relative merits of methods for quantifying surface sublimation, fluxes calculated by the EC, Bowen ratio–energy balance (BR), bulk aerodynamic flux (BF), and aerodynamic profile (AP) methods and their associated uncertainty were compared at two forested openings in the Colorado Rocky Mountains. Biases between methods are evaluated over a range of environmental conditions, and limitations of each method are discussed. Mean surface sublimation rates from both sites ranged from 0.33 to 0.36 mm day−1, 0.14 to 0.37 mm day−1, 0.10 to 0.17 mm day−1, and 0.03 to 0.10 mm day−1 for the EC, BR, BF and AP methods, respectively. The EC and/or BF methods are concluded to be superior for estimating surface sublimation in snow-covered forested openings. The surface sublimation rates quantified in this study are generally smaller in magnitude compared with previously published studies in this region and help to refine sublimation estimates for forested openings in the Colorado Rocky Mountains.

  13. STUDIES ON THE HARDNESS OF WET SNOW AND ITS DECREASE DUE TO SOLAR RADIATION

    OpenAIRE

    Izumi, Kaoru

    1987-01-01

    As wet snow plays one of the most important roles in the release of avalanches in temperate snowy districts, observations and experiments were made on the characteristics of hardness of wet snow in the field and laboratory. By measuring Kinosita's hardness of natural wet snow over a wide range of snow density, a relation among hardness, dry density and free water content of wet snow was obtained for each snow type. As hardness of snow decreased with an increase in water content according to t...

  14. Application of MODIS snow cover products: wildfire impacts on snow and melt in the Sierra Nevada

    Directory of Open Access Journals (Sweden)

    P. D. Micheletty

    2014-07-01

    Full Text Available The current work evaluates the spatial and temporal variability in snow after a large forest fire in northern California with Moderate Resolution Imaging Spectroradiometer (MODIS snow covered area and grain size (MODSCAG algorithm. MODIS MOD10A1 fractional snow covered area and MODSCAG fractional snow cover products are utilized to detect spatial and temporal changes in snowpack after the 2007 Moonlight Fire and an unburned basin, Grizzly Ridge, for water years (WY 2002–2012. Estimates of canopy adjusted and non-adjusted MODSCAG fractional snow covered area (fSCA are smoothed and interpolated to provide a continuous timeseries of daily basin average snow extent over the two basins. The removal of overstory canopy by wildfire exposes more snow cover; however, elemental pixel comparisons and statistical analysis show that the MOD10A1 product has a tendency to overestimate snow coverage pre-fire, muting the effects of wildfire. The MODSCAG algorithm better distinguishes sub-pixel snow coverage in forested areas and is highly correlated to soil burn severity after the fire. Annual MODSCAG fSCA estimates show statistically significant increased fSCA in the Moonlight Fire study area after the fire (WY 2008–2011; P < 0.01 compared to pre-fire averages and the control basin. After the fire, the number of days exceeding a pre-fire high snow cover threshold increased by 81%. Canopy reduction increases exposed viewable snow area and the amount of solar radiation that reaches the snowpack leading to earlier basin average melt-out dates compared to the nearby unburned basin. There is also a significant increase in MODSCAG fSCA post-fire regardless of slope or burn severity. Alteration of regional snow cover has significant implications for both short and long-term water supplies for downstream communities and resource managers.

  15. Applications of remote sensing and GIS in surface hydrology: Snow cover, soil moisture and precipitation

    Science.gov (United States)

    Wang, Xianwei

    Studies on surface hydrology can generally be classified into two categories, observation for different components of surface water, and modeling their dynamic movements. This study only focuses on observation part of surface water components: snow cover, soil moisture, and precipitation. Moreover, instead of discussion on the detailed algorithm and instrument technique behind each component, this dissertation pours efforts on analysis of the standard remotely sensed products and their applications under different settings. First in Chapter 2, validation of MODIS Terra 8-day maximum snow cover composite (MOD10A2) in the Northern Xinjiang, China, from 2000-2006, shows that the 8-day MODIS/Terra product has high agreements with in situ measurements as the in situ snow depth is larger or equal to 4 cm, while the agreement is low for the patchy snow as the in situ snow depth less than 4 cm. According to the in situ observation, this chapter develops an empirical algorithm to separate the cloud-covered pixels into snow and no snow. Continued long-term production of MODIS-type snow cover product is critical to assess water resources of the study area, as well as other larger scale global environment monitoring. Terra and Aqua satellites carry the same MODIS instrument and provide two parallel MODIS daily snow cover products at different time (local time 10:30 am and 1:30 pm, respectively). Chapter 3 develops an algorithm and automated scripts to combine the daily MODIS Terra (MOD10A1) and Aqua (MYD10A1) snow cover products, and to automatically generate multi-day Terra-Aqua snow cover image composites, with flexible starting and ending dates and a user-defined cloud cover threshold. Chapter 4 systematically compares the difference between MODIS Terra and Aqua snow cover products within a hydrologic year of 2003-2004, validates the MODIS Terra and Aqua snow cover products using in situ measurements in Northern Xinjiang, and compares the accuracy among the standard MODIS

  16. Monitoring water quality from LANDSAT. [satellite observation of Virginia

    Science.gov (United States)

    Barker, J. L.

    1975-01-01

    Water quality monitoring possibilities from LANDSAT were demonstrated both for direct readings of reflectances from the water and indirect monitoring of changes in use of land surrounding Swift Creek Reservoir in a joint project with the Virginia State Water Control Board and NASA. Film products were shown to have insufficient resolution and all work was done by digitally processing computer compatible tapes. Land cover maps of the 18,000 hectare Swift Creek Reservoir watershed, prepared for two dates in 1974, are shown. A significant decrease in the pine cover was observed in a 740 hectare construction site within the watershed. A measure of the accuracy of classification was obtained by comparing the LANDSAT results with visual classification at five sites on a U-2 photograph. Such changes in land cover can alert personnel to watch for potential changes in water quality.

  17. Snow Drift Management: Summit Station Greenland

    Science.gov (United States)

    2016-05-01

    ER D C/ CR RE L TR -1 6- 6 Engineering for Polar Operations, Logistics, and Research (EPOLAR) Snow Drift Management Summit Station...Drift Management Summit Station Greenland Robert B. Haehnel and Matthew F. Bigl U.S. Army Engineer Research and Development Center (ERDC) Cold...Engineering for Polar Operations, Logistics, and Research (EPOLAR) EP-ARC-15-33, “Monitoring and Managing Snow Drifting at Summit Station, Greenland” ERDC

  18. A comparison between remote sensing approaches to water extent monitoring

    Science.gov (United States)

    elmi, omid; javad tourian, mohammad; sneeuw, nico

    2013-04-01

    Monitoring the variation of water storage in a long period is a primary issue for understanding the impact of climate change and human activities on earth water resources. In order to obtain the change in water volume in a lake and reservoir, in addition to water level, water extent must be repeatedly determined in an appropriate time interval. Optical satellite imagery as a passive system is the main source of determination of coast line change as it is easy to interpret. Optical sensors acquire the reflected energy from the sunlight in various bands from visible to near infrared. Also, panchromatic mode provides more geometric details. Establishing a ratio between visible bands is the most common way of extract coastlines because with this ratio, water and land can be separated directly. Also, since the reflectance value of water is distinctly less than soil in infrared bands, applying a histogram threshold on this band is a effective way of coastline extraction. However, optical imagery is highly vulnerable to occurrence of dense clouds and fog. Moreover, the coastline is hard to detect where it is covered by dense vegetation. Synthetic aperture radar (SAR) as an active system provides an alternative source for monitoring the spatial change in coastlines. Two methods for monitoring the shoreline with SAR data have been published. First, the backscatter difference is calculated between two images acquired at different times. Second, the change in coastline is detected by computing the coherence of two SAR images acquired at different times. A SAR system can operate in all weather, so clouds and fog don't impact its efficiency. Also, it can penetrate into the plant canopy. However, in comparison with optical imagery, interpretation of SAR image in this case is relatively hard because of limitation in the number of band and polarization modes, also due to effects caused by speckle noises, slant-range imaging and shadows. The primary aim of this study is a

  19. Characteristics, dynamics and significance of marine snow

    Science.gov (United States)

    Alldredge, Alice L.; Silver, Mary W.

    Macroscopic aggregates of detritus, living organisms and inorganic matter known as marine snow, have significance in the ocean both as unique, partially isolated microenvironments and as transport agents: much of surface-derived matter in the ocean fluxes to the ocean interior and the sea floor as marine snow. As microhabitats, marine snow aggregates contain enriched microbial communities and chemical gradients within which processes of photosynthesis, decomposition, and nutrient regeneration occur at highly elevated levels. Microbial communities associated with marine snow undergo complex successional changes on time scales of hours to days which significantly alter the chemical and biological properties of the particles. Marine snow can be produced either de novo by living plants and animals especially as mucus feeding webs of zooplankton, or by the biologically-enhanced physical aggregation of smaller particles. By the latter pathway, microaggregates, phytoplankton, fecal pellets, organic debris and clay-mineral particles collide by differential settlement or physical shear and adhere by the action of various, biologically-generated, organic compounds. Diatom flocculation is a poorly understood source of marine snow of potential global significance. Rates of snow production and breakdown are not known but are critical to predicting flux and to understanding biological community structure and transformations of matter and energy in the water column. The greatest challenge to the study of marine snow at present is the development of appropriate technology to measure abundances and characteristics of aggregates in situ.

  20. Monitoring and remediation technologies of organochlorine pesticides in drainage water

    Directory of Open Access Journals (Sweden)

    Ismail Ahmed

    2015-03-01

    Full Text Available This study was carried out to monitor the presence of organochlorine in drainage water in Kafr-El-Sheikh Governorate, Egypt. Furthermore, to evaluate the efficiencies of different remediation techniques (advanced oxidation processes [AOPs] and bioremediation for removing the most frequently detected compound (lindane in drainage water. The results showed the presence of several organochlorine pesticides in all sampling sites. Lindane was detected with high frequency relative to other detected organochlorine in drainage water. Nano photo-Fenton like reagent was the most effective treatment for lindane removal in drainage water. Bioremediation of lindane by effective microorganisms (EMs removed 100% of the lindane initial concentration. There is no remaining toxicity in lindane contaminated-water after remediation on treated rats relative to control with respect to histopathological changes in liver and kidney. Advanced oxidation processes especially with nanomaterials and bioremediation using effective microorganisms can be regarded as safe and effective remediation technologies of lindane in water.

  1. 40 CFR 141.29 - Monitoring of consecutive public water systems.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Monitoring of consecutive public water... PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS Monitoring and Analytical Requirements § 141.29 Monitoring of consecutive public water systems. When a public water system supplies water to...

  2. Gender Sensitive Planning, Monitoring and Evaluation in Agricultural Water Management

    OpenAIRE

    Gautam, Suman Rimal; Kuriakose, Anne

    2016-01-01

    Agricultural water management projects that take an inclusive, participatory gendersensitive approach at all levels of the project cycle help increase project effectiveness and improve account of livelihood concerns of women and the rural poor. Participatory planning methods; creation of genderspecific indicators; continuous monitoring; and beneficiary-led impact assessment are key features of this approach.

  3. Understanding Local Ecology: Syllabus for Monitoring Water Quality.

    Science.gov (United States)

    Iowa Univ., Iowa City.

    This syllabus gives detailed information on monitoring water quality for teachers and students. It tells how to select a sample site; how to measure physical characteristics such as temperature, turbidity, and stream velocity; how to measure chemical parameters such as alkalinity, dissolved oxygen levels, phosphate levels, and ammonia nitrogen…

  4. Single-dish monitoring of circumstellar water masers

    CERN Document Server

    Brand, J; Engels, D

    2002-01-01

    We present an overview of the long-term water maser monitoring program of a sample of late-type stars, carried out with the Medicina 32-m and Effelsberg 100-m telescopes, and describe the results in some detail. The role the SRT (Sardinia Radio Telescope) could play in this program is outlined.

  5. A controlled experiment for water front monitoring using GPR technology

    NARCIS (Netherlands)

    Miorali, M.; Slob, E.C.; Arts, R.J.

    2010-01-01

    We use a stepped frequency continuous wave (SFCW) radar and an impulse radar to monitor a water flood experiment in a sand box. The SFCW system operates in the bandwidth from 800 MHz to 2.8 GHz. The impulse radar system is bi-static and works with a central frequency of 1 GHz. The sand box is a mete

  6. A controlled experiment for water front monitoring using GPR technology

    NARCIS (Netherlands)

    Miorali, M.; Slob, E.C.; Arts, R.J.

    2010-01-01

    We use a stepped frequency continuous wave (SFCW) radar and an impulse radar to monitor a water flood experiment in a sand box. The SFCW system operates in the bandwidth from 800 MHz to 2.8 GHz. The impulse radar system is bi-static and works with a central frequency of 1 GHz. The sand box is a

  7. Monitoring Water Targets in the Post-2015 Development Goals

    Science.gov (United States)

    Lawford, R. G.

    2015-12-01

    The Water Sustainable Development Goal (SDG) provides a comprehensive approach to developing water services in a way that ensures social equity, health, well-being and sustainability for all. In particular, the water goal includes targets related to sanitation, wastewater, water quality, water efficiency, integrated water management and ecosystems (details to be finalized in September 2015). As part of its implementation, methods to monitor target indicators must be developed. National governments will be responsible for reporting on progress toward these targets using national data sets and possibly information from global data sets that applies to their countries. Oversight of this process through the use of global data sets is desirable for encouraging the use of standardized information for comparison purposes. Disparities in monitoring due to very sparse data networks in some countries can be addressed by using geospatially consistent data products from space-based remote sensing. However, to fully exploit these data, capabilities will be needed to downscale information, to interpolate and assimilate data both in time and space, and to integrate these data with socio-economic data sets, model outputs and survey data in a geographical information system framework. Citizen data and other non-standard data types may also supplement national data systems. A comprehensive and integrated analysis and dissemination system is needed to enable the important contributions that satellites could make to achieving Water SDG targets. This presentation will outline the progress made in assessing the needs for information to track progress on the Water SDG, options for meeting these needs using existing data infrastructure, and pathways for expanding the role of Earth observations in SDG monitoring. It will also discuss the potential roles of Future Earth's Sustainable Water Futures Programme (SWFP) and the Group on Earth Observations (GEO) in coordinating these efforts.

  8. Drifting snow and its sublimation in turbulent boundary layer

    Science.gov (United States)

    Li, Guang; Huang, Ning; Wang, Zhengshi

    2017-04-01

    Drifting snow is a special process of mass-energy transport in hydrological cycle especially in alpine region. It can not only change the snow distribution, but also result in phase change of ice crystal into water vapour, which is so called drifting snow sublimation. Thus drifting snow is of glaciological and hydrological importance in cold regions. In this paper, recent research on drifting snow and its sublimation is reviewed, and some new progresses by our research team in Lanzhou University are also introduced.

  9. Antineutrino monitoring for the Iranian heavy water reactor

    CERN Document Server

    Christensen, Eric; Jaffke, Patrick; Shea, Thomas

    2014-01-01

    In this note we discuss the potential application of antineutrino monitoring to the Iranian heavy water reactor at Arak, the IR-40, as a non-proliferation measure. We demonstrate that an above ground detector positioned right outside the IR-40 reactor building could meet and in some cases significantly exceed the verification goals identified by IAEA for plutonium production or diversion from declared inventories. In addition to monitoring the reactor during operation, observing antineutrino emissions from long-lived fission products could also allow monitoring the reactor when it is shutdown. Antineutrino monitoring could also be used to distinguish different levels of fuel enrichment. Most importantly, these capabilities would not require a complete reactor operational history and could provide a means to re-establish continuity of knowledge in safeguards conclusions should this become necessary.

  10. Measured black carbon deposition on the Sierra Nevada snow pack and implication for snow pack retreat

    Directory of Open Access Journals (Sweden)

    O. L. Hadley

    2010-04-01

    Full Text Available Modeling studies show that the darkening of snow and ice by black carbon (BC deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition on the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain at a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.

  11. Measured black carbon deposition on the Sierra Nevada snow pack and implication for snow pack retreat

    Directory of Open Access Journals (Sweden)

    O. L. Hadley

    2010-08-01

    Full Text Available Modeling studies show that the darkening of snow and ice by black carbon deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition to the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain at a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.

  12. Measured Black Carbon Deposition on the Sierra Nevada Snow Pack and Implication for Snow Pack Retreat

    Energy Technology Data Exchange (ETDEWEB)

    Hadley, O.L.; Corrigan, C.E.; Kirchstetter, T.W.; Cliff, S.S.; Ramanathan, V.

    2010-01-12

    Modeling studies show that the darkening of snow and ice by black carbon deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition to the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain at a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.

  13. Water quality monitoring in the Paul do Boquilobo Biosphere Reserve

    Science.gov (United States)

    Baptista, C.; Santos, L.

    2016-08-01

    The Paul do Boquilobo is an important wetland ecosystem classified by Unesco as a MAB Biosphere reserve also awarded Ramsar site status, representing one of the most important habitats for the resident nesting colony of Cattle Egret (Bulbucus ibis). Yet owing to its location, it suffers from human induced impacts which include industrial and domestic effluent discharges as well as agricultural land use which have negatively impacted water quality. The current study reports the results obtained from the introductory monitoring programme of surface water quality in the Nature Reserve to emphasize the detrimental impact of the anthropogenic activities in the water quality of such an important ecosystem. The study involved physicochemical and biotic variables, microbial parameters and biological indicators. Results after 3 years of monitoring bring to evidence a poor water quality further impaired by seasonal patterns. Statistical analysis of data attributed water quality variation to 3 main parameters - pH, dissolved oxygen and nitrates, indicating heavy contamination loads from both organic and agricultural sources. Seasonality plays a role in water flow and climatic conditions, where sampling sites presented variable water quality data, suggesting a depurative function of the wetland.

  14. Energy Efficient Networks for Monitoring Water Quality in Subterranean Rivers

    Directory of Open Access Journals (Sweden)

    Fei Ge

    2016-05-01

    Full Text Available The fresh water in rivers beneath the Earth’s surface is as significant to humans as that on the surface. However, the water quality is difficult to monitor due to its unapproachable nature. In this work, we consider building networks to monitor water quality in subterranean rivers. The network node is designed to have limited functions of floating and staying in these rivers when necessary. We provide the necessary conditions to set up such networks and a topology building method, as well as the communication process between nodes. Furthermore, we provide every an node’s energy consumption model in the network building stage, the data acquiring and transmission stage. The numerical results show that the energy consumption in every node is different, and the node number should be moderate to ensure energy efficiency.

  15. Simulating snow maps for Norway: description and statistical evaluation of the seNorge snow model

    Directory of Open Access Journals (Sweden)

    T. M. Saloranta

    2012-11-01

    Full Text Available Daily maps of snow conditions have been produced in Norway with the seNorge snow model since 2004. The seNorge snow model operates with 1 × 1 km resolution, uses gridded observations of daily temperature and precipitation as its input forcing, and simulates, among others, snow water equivalent (SWE, snow depth (SD, and the snow bulk density (ρ. In this paper the set of equations contained in the seNorge model code is described and a thorough spatiotemporal statistical evaluation of the model performance from 1957–2011 is made using the two major sets of extensive in situ snow measurements that exist for Norway. The evaluation results show that the seNorge model generally overestimates both SWE and ρ, and that the overestimation of SWE increases with elevation throughout the snow season. However, the R2-values for model fit are 0.60 for (log-transformed SWE and 0.45 for ρ, indicating that after removal of the detected systematic model biases (e.g. by recalibrating the model or expressing snow conditions in relative units the model performs rather well. The seNorge model provides a relatively simple, not very data-demanding, yet nonetheless process-based method to construct snow maps of high spatiotemporal resolution. It is an especially well suited alternative for operational snow mapping in regions with rugged topography and large spatiotemporal variability in snow conditions, as is the case in the mountainous Norway.

  16. Using multi-year data to evaluate performance of one-layer and multi-layer models in snow hydrology: an example from Col De Porte

    Science.gov (United States)

    Avanzi, Francesco; De Michele, Carlo; Morin, Samuel; Carmagnola, Carlo Maria; Ghezzi, Antonio; Lejeune, Yves

    2016-04-01

    Snow mass dynamics prediction represents an important task for snow hydrologists, since snow on the ground influences local/global water availability and streamflow timing and amount. Different modeling tools have been formulated for decades to predict snowmelt runoff dynamics and therefore to integrate snow mass dynamics in watershed hydrology modeling. Typical variables of interest include snow depth, snow bulk density, snow water equivalent (SWE) and snowmelt runoff. All these variables have been monitored at several locations worldwide for several decades in order to evaluate model performance. As a result, several multi-year datasets are now available to perform extensive evaluation tests. In this presentation, we report an example of these evaluations by discussing the performance of two models of different complexity in reproducing observed data of snow dynamics at a site in French Alps (Col De Porte, 1325 m AMSL), where 18 continuous-time years of observations are available. We consider Crocus as an example of multi-layer physically-based complex models and HyS (De Michele et al. 2013) as an example of a one-layer temperature-index models. Using multi-year data allows us to compare models performance over long periods of time, thus considering different climatic and snow conditions. Moreover, the use of continuous-time data allows to evaluate models performance at different temporal resolutions. De Michele, C., Avanzi, F., Ghezzi, A., and Jommi, C.: Investigating the dynamics of bulk snow density in dry and wet conditions using a one-dimensional model, The Cryosphere, 7, 433-444, doi:10.5194/tc-7-433-2013, 2013.

  17. Biological Status Monitoring of European Fresh Water with Sentinel-2

    Science.gov (United States)

    Serra, Romain; Mangin, Antoine; Fanton d'Andon, Odile Hembise; Lauters, Francois; Thomasset, Franck; Martin-Lauzer, Francois-Regis

    2016-08-01

    Thanks to a widening range of sensors available, the observation of continental water quality for lakes and reservoirs is gaining more and more consistency and accuracy.Consistency because back in 2012, the only free sensor with a sufficient resolution (30m) was Landsat-7 which has truncated data since 2003 and a 16-day revisit time. But today, Landsat-8 and Sentinel-2A are now operating so depending on the latitude of interest, the combined revisit time dropped to 2 to 4 days which is more appropriate for such a monitoring (especially considering the cloud cover).Accuracy because Landsat-7 has a poor contrast over water whereas Landsat-8 and Sentinel-2A have a better radiometric sensitivity (more bit) and moreover Sentinel-2 offers additional spectral bands in the visible which are helpful for Chlorophyll-A concentration assessment. To sum up, with Sentinel-2, continental water quality monitoring capabilities are making a giant leap and it is important to exploit this potential the sooner. ACRI-HE has already built a strong basis to prepare Sentinel-2 by using Landsat data.Indeed, more than 600 lakes are already constantly monitored using Landsat data and their biological statuses are available on EyeOnWater (see eyeonwater.eu). Chlorophyll-A retrieval from (fresh) water leaving reflectances is the result of research activities conducted by ACRI-HE in parallel with EDF (Electricité de France) to respond to an emerging very demanding environmental monitoring through European regulations (typically the Water Framework Directive). Two parallel and complementary algorithms have thus been derived for Chlorophyll-a retrieval.Upstream of Eyeonwater, there is a complex and complete system automatically collecting images, extracting areas of interest around lakes, applying atmospheric correction (very sensitive part as atmosphere can contribute to 90% of the signal at sensor level) and then algorithms to retrieve water transparency (Secchi disk), turbidity and Chlorophyll

  18. South Asia transboundary water quality monitoring workshop summary report.

    Energy Technology Data Exchange (ETDEWEB)

    Betsill, Jeffrey David; Littlefield, Adriane C.; Luetters, Frederick O.; Rajen, Gaurav

    2003-04-01

    The Cooperative Monitoring Center (CMC) promotes collaborations among scientists and researchers in several regions as a means of achieving common regional security objectives. To promote cooperation in South Asia on environmental research, an international working group made up of participants from Bangladesh, India, Nepal, Pakistan, and the United States convened in Kathmandu, Nepal, from February 17-23,2002. The workshop was held to further develop the South Asia Transboundary Water Quality Monitoring (SATWQM) project. The project is sponsored in part by the CMC located at Sandia National Laboratories in Albuquerque, New Mexico through funding provided by the US. Department of State, Regional Environmental Affairs Office, American Embassy, Kathmandu, Nepal, and the National Nuclear Security Administration's (NNSA) Office of Nonproliferation and National Security. This report summarizes the SATWQM project, the workshop objectives, process and results. The long-term interests of the participants are to develop systems for sharing regional environmental information as a means of building confidence and improving relations among South Asian countries. The more immediate interests of the group are focused on activities that foster regional sharing of water quality data in the Ganges and Indus River basins. Issues of concern to the SATWQM network participants include studying the impacts from untreated sewage and industrial effluents, agricultural run-off, salinity increases in fresh waters, the siltation and shifting of river channels, and the environmental degradation of critical habitats such as wetlands, protected forests, and endangered aquatic species conservation areas. The workshop focused on five objectives: (1) a deepened understanding of the partner organizations involved; (2) garnering the support of additional regional and national government and non-government organizations in South Asia involved in river water quality monitoring; (3) identification

  19. ADCP application for long-term monitoring of coastal water

    Institute of Scientific and Technical Information of China (English)

    YOSHIOKA Hiroshi; TAKAYAMA Tomotsuka; SERIZAWA Shigeatsu

    2005-01-01

    Three kind of application of ADCP is reported for long-term monitoring in coastal sea.(1)The rourine monitoring of water qualities.The water quality and ADCP echo data (600 kHz) observed in the long-term are analgzed at MT (Marine Tower) Station of Kansai International Airport in the Osaka Bay, Japan. The correlation between the turbidity and echo intensity in the surface layer is not good because air bubbles generated by breaking wave are not detected by the turbidity meter, but detected well by ADCP. When estimating the turbidity consists of plankton population from echo intensity, the effect ofbubbles have to be eliminated. (2) Monitoring stirring up of bottom sediment. The special observation was carded out by using following two ADCP in the Osaka Bay, One ADCP was installed upward on the sea. The other ADCP was hanged downward at the gate type stand about 3 m above from the bottom. At the spring tide, high echo intensities indicating the stirring up of bottom sediment were observed. (3) The monitoring for the boundary condition of water mixing at an estuary. In summer season, the ADCP was set at the mouth of Tanabe Bay in Wakayama Prefecture, Japan.During the observation, water temperature near the bottom showed remarkable falls with interval of about 5~7 d. When the bottom temperature fell, the inflow current with low echo intensity water appears at the bottom layer in the ADCP record. It is concluded that when occasional weak northeast wind makes weak coastal upwelling at the mouth of the bay, the combination of upwelling with internal tidal flow causes remarkable water exchange and dispels the red tide.

  20. Monitoring And Modeling Environmental Water Quality To Support Environmental Water Purchase Decision-making

    Science.gov (United States)

    Null, S. E.; Elmore, L.; Mouzon, N. R.; Wood, J. R.

    2016-12-01

    More than 25 million cubic meters (20,000 acre feet) of water has been purchased from willing agricultural sellers for environmental flows in Nevada's Walker River to improve riverine habitat and connectivity with downstream Walker Lake. Reduced instream flows limit native fish populations, like Lahontan cutthroat trout, through warm daily stream temperatures and low dissolved oxygen concentrations. Environmental water purchases maintain instream flows, although effects on water quality are more varied. We use multi-year water quality monitoring and physically-based hydrodynamic and water quality modeling to estimate streamflow, water temperature, and dissolved oxygen concentrations with alternative environmental water purchases. We simulate water temperature and dissolved oxygen changes from increased streamflow to prioritize the time periods and locations that environmental water purchases most enhance trout habitat as a function of water quality. Monitoring results indicate stream temperature and dissolved oxygen limitations generally exist in the 115 kilometers upstream of Walker Lake (about 37% of the study area) from approximately May through September, and this reach acts as a water quality barrier for fish passage. Model results indicate that low streamflows generally coincide with critically warm stream temperatures, water quality refugia exist on a tributary of the Walker River, and environmental water purchases may improve stream temperature and dissolved oxygen conditions for some reaches and seasons, especially in dry years and prolonged droughts. This research supports environmental water purchase decision-making and allows water purchase decisions to be prioritized with other river restoration alternatives.

  1. A conceptual, distributed snow redistribution model

    Science.gov (United States)

    Frey, S.; Holzmann, H.

    2015-11-01

    When applying conceptual hydrological models using a temperature index approach for snowmelt to high alpine areas often accumulation of snow during several years can be observed. Some of the reasons why these "snow towers" do not exist in nature are vertical and lateral transport processes. While snow transport models have been developed using grid cell sizes of tens to hundreds of square metres and have been applied in several catchments, no model exists using coarser cell sizes of 1 km2, which is a common resolution for meso- and large-scale hydrologic modelling (hundreds to thousands of square kilometres). In this paper we present an approach that uses only gravity and snow density as a proxy for the age of the snow cover and land-use information to redistribute snow in alpine basins. The results are based on the hydrological modelling of the Austrian Inn Basin in Tyrol, Austria, more specifically the Ötztaler Ache catchment, but the findings hold for other tributaries of the river Inn. This transport model is implemented in the distributed rainfall-runoff model COSERO (Continuous Semi-distributed Runoff). The results of both model concepts with and without consideration of lateral snow redistribution are compared against observed discharge and snow-covered areas derived from MODIS satellite images. By means of the snow redistribution concept, snow accumulation over several years can be prevented and the snow depletion curve compared with MODIS (Moderate Resolution Imaging Spectroradiometer) data could be improved, too. In a 7-year period the standard model would lead to snow accumulation of approximately 2900 mm SWE (snow water equivalent) in high elevated regions whereas the updated version of the model does not show accumulation and does also predict discharge with more accuracy leading to a Kling-Gupta efficiency of 0.93 instead of 0.9. A further improvement can be shown in the comparison of MODIS snow cover data and the calculated depletion curve, where

  2. Snow observations in Mount Lebanon (2011-2016)

    Science.gov (United States)

    Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; Fanise, Pascal; Drapeau, Laurent; Somma, Janine; Fadel, Ali; Bitar, Ahmad Al; Escadafal, Richard

    2017-08-01

    We present a unique meteorological and snow observational dataset in Mount Lebanon, a mountainous region with a Mediterranean climate, where snowmelt is an essential water resource. The study region covers the recharge area of three karstic river basins (total area of 1092 km2 and an elevation up to 3088 m). The dataset consists of (1) continuous meteorological and snow height observations, (2) snowpack field measurements, and (3) medium-resolution satellite snow cover data. The continuous meteorological measurements at three automatic weather stations (MZA, 2296 m; LAQ, 1840 m; and CED, 2834 m a.s.l.) include surface air temperature and humidity, precipitation, wind speed and direction, incoming and reflected shortwave irradiance, and snow height, at 30 min intervals for the snow seasons (November-June) between 2011 and 2016 for MZA and between 2014 and 2016 for CED and LAQ. Precipitation data were filtered and corrected for Geonor undercatch. Observations of snow height (HS), snow water equivalent, and snow density were collected at 30 snow courses located at elevations between 1300 and 2900 m a.s.l. during the two snow seasons of 2014-2016 with an average revisit time of 11 days. Daily gap-free snow cover extent (SCA) and snow co