This paper describes the implementation of a sensor network to monitor meteorological and hydrological conditions in Yosemite National Park. The sensor network, consisting of 20 instruments, was designed to be low-maintenance, low-powered, and unobtrusive. It measured water levels, temperatures, conductivities, snow depth, and radiation over several years in the Merced and Tuolumne River basins. The data collected helped scientists better understand changes in snowmelt patterns and their impacts on streamflow in the region. However, the paper did not provide many technical details about the sensor network itself.
Five most promising topics of research in hydrologyMrinmoy Majumder
Hydrology is a very old subject still; a lot of scope is left in this subject which are hitherto unearthed. Below is the list of five most popular topic of research which have steadily gained its presence in the hydrology related publications, in the last five years
Objectives
- Develop an approach to identify the land-surface changes due to wildfires
- Detect land-surface property changes for multiple mega-fires in the U.S.
- Develop a scheme to parameterize the changes
Five most promising topics of research in hydrologyMrinmoy Majumder
Hydrology is a very old subject still; a lot of scope is left in this subject which are hitherto unearthed. Below is the list of five most popular topic of research which have steadily gained its presence in the hydrology related publications, in the last five years
Objectives
- Develop an approach to identify the land-surface changes due to wildfires
- Detect land-surface property changes for multiple mega-fires in the U.S.
- Develop a scheme to parameterize the changes
Thomas Zurbuchen, Professor of Space Science and Aerospace Engineering, University of Michigan, Ann Arbor
June 2016 - UCAR Congressional Briefing on Space Weather Prediction
Video of this presentation will be available soon.
Nonproportionality Studies in Single Crystal Scintillators: Towards Improved ...Martin Gascon
Nonproportionality Studies in Single Crystal Scintillators:
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How to nail your estimates and act at the right time
When you use inaccurate data, the further you are into the growing season, the greater the estimate will differ from reality. For longer season crops, the difference could be quite significant, which is a problem because plant maturity, flowering, and pest/disease GDD targets often have tight windows.
In this 20-minute webinar, Dr. Colin Campbell discusses what you need to know for more accurate models, so you can be confident in your management decisions.
Dear Friends, this is just a rough draft, based a an accumulation of ideas that I have been building an interdisciplinary vision for...
the just of this vision is adaptation and mitigation of climate change and ocean acidification, adaptation and mitigation of and for Food security, ocean acidification for species survivability , and the preservation of traditional relationships with culturally iconic populations, with a sound business plan that should be built on sustainable aquaculture of culinary and medicinal seaweeds and aquatic plants as bio filtration of both Ocean Acidification and marine aquaculture related water quality relative to marine fin fish and shell fish hatchery and growth, including the use of artificial tide-pools, within an integrated system that is exercised by the site specific natural energy abundance....
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Decrease chances of crop damage with one simple practice
Find out how you can increase the accuracy of your predictive models and decrease frost, insect, and disease incidents by doing just one thing differently—improving the quality of your weather data. Discover:
- Microclimates: what are the conditions like inside a crop canopy versus outside?
- Virtual data vs. weather station data: Which is better?
- How do site-specific weather data vs. regional network data compare?
- How much does a small decrease in data quality affect the accuracy of your models?
- What’s the value of in-orchard measurements?
- What are some best practices for higher data quality?
Presenter
For 20 years as a faculty member at Montana State University and Washington State University (WSU) Dr. Dave Brown pursued research on soil sensors, spatial data science and digital agriculture. At both universities, he served in many leadership roles for major research projects, academic programs and most recently as Director of the WSU AgWeatherNet program. In this capacity, Dr. Brown hired and supervised a team of meteorologists who pursued research and extension activities focused on evaluating and improving the quality of weather data used for agricultural decisions.
DSD-INT 2017 Moth plant dispersion Modelling based on synoptic weather patter...Deltares
Presentation by Chris van Diemen, University of Amsterdam (UvA), Netherlands, at the Delft3D - User Days (Day 1: Hydrodynamics), during Delft Software Days - Edition 2017. Monday, 30 October 2017, Delft.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Thomas Zurbuchen, Professor of Space Science and Aerospace Engineering, University of Michigan, Ann Arbor
June 2016 - UCAR Congressional Briefing on Space Weather Prediction
Video of this presentation will be available soon.
Nonproportionality Studies in Single Crystal Scintillators: Towards Improved ...Martin Gascon
Nonproportionality Studies in Single Crystal Scintillators:
Towards Improved Energy Resolution for Nuclear and Radiological Detectors. Bi-annual Spanish Conference in Physics. Santander, Sept. 24th, 2011
How to nail your estimates and act at the right time
When you use inaccurate data, the further you are into the growing season, the greater the estimate will differ from reality. For longer season crops, the difference could be quite significant, which is a problem because plant maturity, flowering, and pest/disease GDD targets often have tight windows.
In this 20-minute webinar, Dr. Colin Campbell discusses what you need to know for more accurate models, so you can be confident in your management decisions.
Dear Friends, this is just a rough draft, based a an accumulation of ideas that I have been building an interdisciplinary vision for...
the just of this vision is adaptation and mitigation of climate change and ocean acidification, adaptation and mitigation of and for Food security, ocean acidification for species survivability , and the preservation of traditional relationships with culturally iconic populations, with a sound business plan that should be built on sustainable aquaculture of culinary and medicinal seaweeds and aquatic plants as bio filtration of both Ocean Acidification and marine aquaculture related water quality relative to marine fin fish and shell fish hatchery and growth, including the use of artificial tide-pools, within an integrated system that is exercised by the site specific natural energy abundance....
Weather Data: Virtual, In-Field, or Regional Network—Does It Matter?METER Group, Inc. USA
Which data source is better?
In the world of specialty crops, there is disagreement on how well weather-driven insect, disease, and frost prediction models actually perform. Dr. Dave Brown, former director of Washington State University’s AgWeatherNet spent years comparing different weather data sources and how those data affect the accuracy of common environmental models used by orchard growers. In this 20-minute webinar, he shares the surprising things he learned.
Decrease chances of crop damage with one simple practice
Find out how you can increase the accuracy of your predictive models and decrease frost, insect, and disease incidents by doing just one thing differently—improving the quality of your weather data. Discover:
- Microclimates: what are the conditions like inside a crop canopy versus outside?
- Virtual data vs. weather station data: Which is better?
- How do site-specific weather data vs. regional network data compare?
- How much does a small decrease in data quality affect the accuracy of your models?
- What’s the value of in-orchard measurements?
- What are some best practices for higher data quality?
Presenter
For 20 years as a faculty member at Montana State University and Washington State University (WSU) Dr. Dave Brown pursued research on soil sensors, spatial data science and digital agriculture. At both universities, he served in many leadership roles for major research projects, academic programs and most recently as Director of the WSU AgWeatherNet program. In this capacity, Dr. Brown hired and supervised a team of meteorologists who pursued research and extension activities focused on evaluating and improving the quality of weather data used for agricultural decisions.
DSD-INT 2017 Moth plant dispersion Modelling based on synoptic weather patter...Deltares
Presentation by Chris van Diemen, University of Amsterdam (UvA), Netherlands, at the Delft3D - User Days (Day 1: Hydrodynamics), during Delft Software Days - Edition 2017. Monday, 30 October 2017, Delft.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The use of solar energy for water desalination becomes vital for sustainable water supply.
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theoretical results of temperatures and the impact of wind speed on water production are in good
agreement with experimental findings. It is found that the temperature augments with augmenting the wind speed until a critical value, where the temperature starts to drop. In addition, water
production increases with increasing speed. In this way, we determined the optimum wind speed
to have maximum water production with minimum energy consumption simultaneously. The validation of the theoretical model allows us to predict the DSSS production under different climatic
conditions and to scale DSSS dimensions according to the need of water. The salinity of the water
is not a determining factor in its production. The production at 4.2 kWh/m2 daily insolation was
0.58 L/d. The volume of distilled water reaches a maximum value (62.3% efficiency) when glass
and environment temperatures are similar. This phenomenon occurs at 5.5 m/s wind speed
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Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
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Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
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CW RADAR, FMCW RADAR, FMCW ALTIMETER, AND THEIR PARAMETERSveerababupersonal22
It consists of cw radar and fmcw radar ,range measurement,if amplifier and fmcw altimeterThe CW radar operates using continuous wave transmission, while the FMCW radar employs frequency-modulated continuous wave technology. Range measurement is a crucial aspect of radar systems, providing information about the distance to a target. The IF amplifier plays a key role in signal processing, amplifying intermediate frequency signals for further analysis. The FMCW altimeter utilizes frequency-modulated continuous wave technology to accurately measure altitude above a reference point.
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2. Aboutthe Paper
PaperTitle: Meteorology and Hydrology inYosemite National
Park:A Sensor Network Application
Date of Published: 2003
Published in:
Book title: Information Processing in Sensor Networks
Pages :518-528
Publisher: Springer Berlin Heidelberg
Total Citations: 88 times
Reference:
http://scholar.google.com.ph/citations?view_op=view_citation&hl=en&user=JbFKaYUAAAAJ&cstart=20&citati
on_for_view=JbFKaYUAAAAJ:3fE2CSJIrl8C
3. Aboutthe Authors
Jessica D. Lundquist
• Professor of Civil and Environmental Engineering, University of
Washington
• Research focuses on spatial patterns of snow and weather in the
mountains and how those patterns are likely to affect stream flow and
water resources in a changing climate.
• 2002-2013 (39 publications)
Daniel R. Cayan
•ClimateAtmospheric Science and Physical Oceanography (CASPO)Scripps
Institution of Oceanography andWater Resources Discipline, U.S.Geological Survey
•Research interest: Seasonal – inter decadal climate variations, climate change, and
climate impacts on water, wildfire, health, and agriculture in California and western
North America
• 1980 – 2013 (137 publications)
Michael D Dettinger
• Research Hydrologist, US Geological Survey
• Research focuses on hydrology, climate, and water resources of the
West, focusing on regional surface water and groundwater
resources, hydroclimatic variability, and climate-change impacts.
• 186 publications
7. The Problem(s)
Few measurements exist
FACTORS:
Severe terrain
Remote area
Limited access
Area of study is in Protected areas
SOLUTION:
A monitoring system that of low maintenance, low powered and
unobtrusive
The paper is addressing the
following problems.
8. Overview
Naturally most of the data
gathered for studies are
from areas accessible and
mostly in the less elevated
area.
9. Overview
Test Basins: Merced River andTuolumne River inYosemite national
Park (Highway 120)
Elevation: 1200 to 3700 m
Why Merced River?
-because it has a long daily record (1916-present)
11. Time line
Water level
Conductiviti
es
Temperatur
es
Snow depth
and
Downward
Shortwave
Radiation
(CDWR)
Obtained
permit,
Installation of
20 instrument
forWater level
and
temperature
in MR andTR
,Deployment
of 4
conductivity
sensor
Stream chemistry
measurements, and
25 internally
recording
temperature/relative
humidity sensors
(highway 120)
10 water pressure
sensor
Published
20032002200120001999
Water level Conductivities Temperatures
20. The Novelty
What is new?
The application of sensor network in meteorological and
hydrological study of change in snowmelt runoff inYosemite
National Park. However we cannot say that there is novelty
claimed by the authors.
Novelty applies to:
The device used so it can be suitable to the requirement the
authors specifications. (Low maintenance, low-powered,
unobtrusive, the circuit design. etc.)
What is new?
21. SimilarWorks
Cayan, Daniel R., Michael D. Dettinger, SusanA. Kammerdiener,
Joseph M. Caprio, David H. Peterson, 2001: Changes in the Onset
of Spring in the Western United States. Bull. Amer. Meteor. Soc.,
82, 399–415.
Dettinger, Michael D., Daniel R. Cayan, 1995: Large-Scale
Atmospheric Forcing of RecentTrends toward Early Snowmelt
Runoff in California. J.Climate, 8, 606–623.
Stewart, I.T., D.R. Cayan, M.D. Dettinger, 2002. Changes in
Snowmelt RunoffTiming inWestern North America under a
“Business as Usual” Climate Change Scenario. Submitted to
Climate Change 10/31/02.
No research prior to this that uses
sensor network for meteorological
and hydrological application.
24. Strength and
Weaknesses
Plus
The implementation of the prototype of sensor network in this study
opens to wide area of researches and better numerical models for
the climate change .
CON
The authors did not include details about the type of sensor or any
technicality about it.
The title is broad.
The study did not clearly state the method of how they collected the
data using the data logger.
It is more focus on the meteorological and hydrological side than of
the sensor network.
Some figures as published are not coherent with his discussion.
No detail about the network and how it was implemented and all
the technicality in engineering side.
25. Recommendations
It could have been better if the sensor network
developer, Douglas Alden, co-authored with this article
to have support the science.
The title tells us that the sensor network was applied to the meteorology and hydrology study in Yosemite national park.
to detect and understand changes and provide ground truth for numerical models. If we
Unobtrusive means discreet and does not attract much attention, inconspicuous. …m-w.com
Topography is the arrangement of the natural and artificial physical features of an area.
Methods to monitor the atmosphere are of two types—in situ measurements and remote sensing observations. In situ measurements require that the instrumentation be located directly at the point of interest and in contact with the subject of interest
They want to quantify simple characteristics, such as the distribution and timing of snow accumulation, snowmelt, and runoff into rivers with elevation.
Downward Shortwave Radiation (CDWR) ; this augment the measures iof air temperature, humidity, precipitation and snow loquid water content
Novelty means
We can presume IP reasons
The authors did not provide details about the logger other than the general specification of the device