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Messages - Karthikeyan L

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1
Programming / rworldmap: A New R package for Mapping Global Data
« on: August 12, 2017, 05:48:30 PM »
rworldmap is a relatively new package available on CRAN for the mapping and visualisation of global data. The vision is to make the display of global data easier, to facilitate understanding and communication. The initial focus is on data referenced by country or grid due to the frequency of use of such data in global assessments. Tools to link data referenced by country (either name or code) to a map, and then to display the map are provided as are functions to map global gridded data. Country and gridded functions accept the same arguments to specify the nature of categories and colour and how legends are formatted. This package builds on the functionality of existing packages, particularly sp, maptools and fields. Example code is provided to produce maps, to link with the packages classInt, RColorBrewer and ncdf, and to plot examples of publicly available country and gridded data.


link: https://journal.r-project.org/archive/2011-1/RJournal_2011-1_South.pdf
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2
Data / SOI toposheet data : 1:250K scale
« on: July 12, 2017, 12:04:23 PM »
Data can be downloaded free @ http://www.lib.utexas.edu/maps/ams/india/
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3
Data / New data product of microwave Tb maps in 2017
« on: December 22, 2016, 10:29:30 AM »
Dear all,

A 37 year calibrated passive microwave daily EASE - Grid 2.0 brightness temperature Earth
System Data Record will be made freely available to researchers in 2017.
[ Courtesy: Group of researchers from the Microwave Earth Remote Sensing Laboratory at Brigham Young University and the National Snow and Ice Data Center (NSIDC) at the Cooperative Institute for Research in Environmental Sciences of the University of Colorado Boulder ]

More details are available at:

https://eos.org/project-updates/bringing-earths-microwave-maps-into-sharper-focus

regards
Indu
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4
Programming / R vs Python
« on: December 08, 2016, 05:46:27 PM »
This blog gives a nice intro and comparison between R and Python. Some popular packages and the scripting language to choose for your work are described eloquently.

https://www.datacamp.com/community/tutorials/r-or-python-for-data-analysis#gs.3KXWxKM
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5
Programming / Rstudio V1
« on: November 02, 2016, 01:18:39 PM »
A new major release of Rstudio V1 is released with lot of improvements and bug fixes.
[Link][/https://blog.rstudio.org/2016/11/01/announcing-rstudio-v1-0/] to Rstudion blog announcing latest release.
[Link][/https://www.rstudio.com/products/rstudio/release-notes/] for various bug fixes and improvements in latest version
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6
Data / Villages Boundaries
« on: October 05, 2016, 05:35:48 PM »
The below contains village level boundary for India in JSON file format.
https://archive.org/details/IndiaVillageBoundaries
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7
Post your question/information / Re: Variable Infiltration Capacity
« on: July 06, 2016, 04:10:45 PM »
Here are the point-wise answers:

1.Can I apply the VIC for my area?

Given your large area (~50,000 sq km), VIC can definitely be applied. It is meant to be applied for large catchments.

2.As, the reservoirs play a significant role in the basin, is there any provision in VIC to include the reservoirs and their operation rules.

There is no reservoir module by default in VIC. I found a free module that does reservoir routing, but haven't ever coupled it with VIC (https://github.com/hydrotian/Reservoir_Model_05). If your main purpose is to study how different regulation policies will affect streamflow, I definitely will recommend SWAT over VIC. The reservoir module support for VIC is not upto the mark (for free users).

3.Is there any provision that I can include outside sources.

Instead of using APHRODITE as a rainfall forcing, I will recommend using IMD gridded precipitation data (available at 0.25 x 0.25 degree). If you cannot pay for that product (IMD), you may use TRMM data. It is a known fact that TRMM precipitation estimates are better than those of APHRODITE. See the papers below for more details

http://journals.ametsoc.org/doi/abs/10.1175/JHM-D-15-0115.1
http://journals.ametsoc.org/doi/10.1175/JHM-D-14-0106.1

For wind speed, you can use CFSR wind data, which is freely available at 0.5 x 0.5 deg spatial resolution. You can obtain it from the below links
http://rda.ucar.edu/datasets/ds093.1/
http://rda.ucar.edu/datasets/ds094.1/
http://rda.ucar.edu/#!lfd?nb=y&b=proj&v=NCEP Climate Forecast System Reanalysis

4.If the water can enter into a grid cell only through atmosphere, how is the water that is supplied during irrigation by reservoir included in the VIC.

It maybe difficult to resolve the spatial resolution. A simple approach maybe to add amount of irrigation to precipitation for the particular grid. Although, VIC may not be the best choice for application to irrigation scheduling.

5.Is it possible to draw conclusions on soil moisture based agricultural drought, using any hydro-logical model, weather it is SWAT or VIC, when it is not validated against soil moisture.(I dont know about VIC.But in SWAT only stream flows are validated.

Generally, hydrologic models are calibrated using streamflow. VIC gives soil moisture output, so you can validate it using data from flux tower (if any available). You may get a better idea from the paper below.
http://journals.ametsoc.org/doi/abs/10.1175/JHM-D-14-0041.1

6.For Hydro logic modeling, how many years of data are required ideally.

There is no fixed period, it totally depends on your data availability. Based on the length of available streamflow data, you need to decide the length of calibration and validation.

Overall, if reservoir regulation is an important part of your study, I would recommend using SWAT. VIC is mostly used for unregulated catchments.

Hope this helps. Let me know if you need any assistance.
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8
Announcements / New feature added in the forum
« on: June 16, 2016, 06:20:12 PM »
Dear all,
Now you can use the "Say Thanks" option to thank a user for his/her post/reply.
You can see this option in each posts.
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9
Models / Re: Anybody working with VIC model
« on: June 16, 2016, 03:46:35 PM »
Dear karthikeyan
Good job.. :) nicely explained
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