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Messages - Subir Paul

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Keep in mind that journal impact factor is just one metrics, so don’t take it too seriously! (Qiusheng Wu)
https://lidarblog.com/2019-06-20-journal-impact-factor?fbclid=IwAR1N4CNLH3PBBT4ZsyzfO6MTeFgeIpSKTi070l0dBkr7JJwu1xill6IOG-w
The following users thanked this post: Sonali, Harikrishna KS

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Abstract: This paper is the outcome of a community initiative to identify major unsolved scientific problems
in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure
involved a public consultation through on-line media, followed by two workshops through which a
large number of potential science questions were collated, prioritised, and synthesised. In spite of
the diversity of the participants (230 scientists in total), the process revealed much about
community priorities and the state of our science: a preference for continuity in research questions
rather than radical departures or redirections from past and current work. Questions remain focussed
on process-based understanding of hydrological variability and causality at all space and time scales.
Increased attention to environmental change drives a new emphasis on understanding how change
propagates across interfaces within the hydrological system and across disciplinary boundaries. In
particular, the expansion of the human footprint raises a new set of questions related to human
interactions with nature and water cycle feedbacks in the context of complex water management
problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will
help guide research efforts for some years to come.
https://www.researchgate.net/publication/333685614_Twenty-three_Unsolved_Problems_in_Hydrology_UPH_-_a_community_perspective

You may find this article interesting!
The following users thanked this post: Sonali

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The work is carried out by Dr. Sonali Pattanayak along with Prof. Ravi S. Nanjundiah and Prof. D. Nagesh Kumar titled "Detection and attribution of climate change signal in South India maximum and minimum temperatures" got published in the Climate Research.

Abstract: South India has seen significant changes in climate. Previous studies have shown that southern part of India is more susceptible to impact of climate change than the rest of the country. A rigorous climate model-based detection and attribution analysis is performed to determine the root cause of the recent changes in climate over South India using fingerprint analysis. Modified Mann-Kendall test signalized non-stationariness in Tmax and Tmin in most of the season during the period 1950-2012. The diminishing cloud cover trend might be inducing significant changes in temperature during the considered time period. Significant downward trends in RH during most of the season could act as an evidence of the recent significant warming. The observed seasonal Tmax, Tmin change patterns are strongly associated with El Niño Southern Oscillation. Significant positive associations between South India temperatures and Niño3.4 are found in all the seasons. Deployment of fingerprint approach indicated that the natural internal variability obtained from 14 climate model control simulations could not explain these significant changes in Tmax (post-monsoon) and Tmin (pre- monsoon and monsoon) of South India. Moreover the experiment simulating natural external forcings (solar and volcanic) do not coincide with the observed signal strength. The dominant external factor leading to climate change is GHGs and its impact is eminent compared to other factors such as, land use change and anthropogenic aerosols. Anthropogenic signals are identifiable in observed changes in Tmax and Tmin of South India and these changes can be explained only when anthropogenic forcing are involved.

Sonali can be contacted at iisc.sonali@gmail.com

https://www.int-res.com/prepress/c01530.html
The following users thanked this post: Sonali

4
The work is carried out by B.N.Priyanka along with Prof. M.S. Mohan Kumar titled "Estimating anisotropic heterogeneous hydraulic conductivity and dispersivity in a layered coastal aquifer of dakshina kannada district, karnataka" is recently published in the Journal of Hydrology.

Abstract: The solution for the inverse problem of seawater intrusion at an aquifer scale has not been studied as extensively as forward modeling, because of the conceptual and computational difficulties involved. A three-dimensional variable-density conceptual phreatic model is developed by constraining with real-field data such as layering, aquifer bottom topography and appropriate initial conditions. The initial aquifer parameters are layered heterogeneous and spatially homogeneous that are based on discrete field measurements. The developed conceptual model shows poor correlation with observed state variables (hydraulic head and solute concentration), signifying the importance of spatial heterogeneity in hydraulic conductivity and dispersivity of all the layers. The conceptual model is inverted to estimate the anisotropic spatially varying hydraulic conductivity and the longitudinal dispersivity at the pilot points by minimizing the least square error of state variables across the observation wells. The inverse calibrated model is validated for the hydraulic head at validation wells and the solute concentration is validated with equivalent solute concentration derived from the electrical resistivity, which shows good results against the field measurements. The verification of estimated anisotropic hydraulic conductivity with the electrical resistivity tomography image shows good agreement. This investigation gives an insight about constraining the highly parameterized inverse model with real-field data to estimate spatially varying aquifer parameters for an effective simulation of the seawater intrusion in a layered coastal aquifer.

https://www.sciencedirect.com/science/article/pii/S0022169418306280#!
The following users thanked this post: B N Priyanka

6
The India Village-Level Geospatial Socio-Economic Data Set: 1991, 2001 is a compilation of the finest level of administrative boundaries in India (village/town-level) and over 200 socio-economic variables collected during the Indian Census in 1991 and 2001.
http://beta.sedac.ciesin.columbia.edu/data/set/india-india-village-level-geospatial-socio-econ-1991-2001
   
India Annual Winter Cropped Area, v1 (2001 – 2016): http://beta.sedac.ciesin.columbia.edu/theme/agriculture
The following users thanked this post: Karthikeyan L

7
Programming / Hydrological Models in an R Package (airGR)
« on: November 20, 2017, 05:27:06 PM »
airGR is a package which brings into the R software the hydrological modelling tools used and developed at the Catchment Hydrology Research Group of Irstea (France), including the GR rainfall-runoff models and a snowmelt and accumulation model, CemaNeige. The airGR package has been designed to fulfill two major requirements: to facilitate the use by non-expert users and to allow flexibility regarding the addition of external criteria, models or calibration algorithms.
https://odelaigue.github.io/airGR/
https://cran.r-project.org/web/packages/airGR/airGR.pdf
The following users thanked this post: Alok Pandey

8
FREEWAT is an HORIZON 2020 project financed by the EU Commission under the call WATER INNOVATION: BOOSTING ITS VALUE FOR EUROPE.
FREEWAT main result is an open source and public domain GIS integrated modelling environment (the FREEWAT platform) for the simulation of water quantity and quality in surface water and groundwater with an integrated water management and planning module.
If you are interested in water management and in simulation tools (and you are especially dealing with groundwater management) please visit the Software and Training page of this web site.
FREEWAT is conceived as a composite plugin for the well-known QGIS (http://qgis.org)GIS open source desktop software.

As composite plugin, FREEWAT is designed as a modular ensemble of different tools: some of them can be used independently, while some modules require the preliminary execution of other tools. In this framework, the following tool classifications can be defined:

Tools for the analysis, interpretation and visualization of hydrogeological and hydrochemical data and quality issues, also focusing on advanced time series analysis, embedded in akvaGIS module.

Simulation of models related to the hydrological cycle and water resources management:  flow models, transport models, crop growth models, management and optimization models (also related to irrigation management and rural issues).

Tools to perform model calibration, sensitivity analysis and uncertainty quantifications.

Additional tools for general GIS operations to prepare input data, and post-processing functionalities (module OAT – Observation and Analysis Tool).

http://www.freewat.eu/
The following users thanked this post: Sonali

9
SAC invites on-line applications for position of Junior Research Fellows (JRF) and Research
Associates (RA):
http://www.sac.gov.in/Vyom/careers.jsp
https://recruitment.sac.gov.in/OSAR/
The following users thanked this post: adrijaroy1994

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Post your question/information / Water Balance App
« on: October 19, 2017, 06:18:41 PM »
This app is based on data from NASA’s Global Land Data Assimilation System (GLDAS-2.1), which uses weather observations like temperature, humidity, and rainfall to run the Noah land surface model. This model estimates how much of the rain becomes runoff, how much evaporates, and how much infiltrates into the soil. These output variables, calculated every three hours, are aggregated into monthly averages, giving us a record of the hydrologic cycle going all the way back to January 2000.
http://monde-geospatial.com/water-balance-app/
The following users thanked this post: B N Priyanka

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Study material / Online Free Courses on Remote Sensing
« on: September 06, 2017, 07:41:10 PM »
Online free courses on remote sensing:
1/ Earth observation from space (by ESA-course just started):
https://www.futurelearn.com/cour…/optical-earth-observation/
2/Monitoring the Oceans from Space (by EUMETSAT-starts on October, 16th): https://www.futurelearn.com/courses/oceans-from-space
3/Monitoring Climate from Space (by ESA-date TBA):
https://www.futurelearn.com/courses/climate-from-space
The following users thanked this post: Sonali

12
Announcements / INDIA-UK Exchange
« on: September 06, 2017, 09:32:25 AM »
The India-UK Water Centre is inviting proposals from members of its Open Network of Water Scientists to apply for funding under one of two researcher exchange schemes. Funding is available to support at least two researcher exchanges to be undertaken during the period 01 January 2018 - 30 June 2018: at least one exchange by an Indian water scientist to the UK and at least one exchange by a UK water scientist to India.
1st September 2017: call opens
22nd September 2017: deadline for submission of application webform
10th October 2017: applicants notified of outcome
http://www.iukwc.org/open-call-invitation-apply-researcher-exchange-0
The following users thanked this post: Sonali, Diwan

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Programming / Remote Sensing Code Library (RSCL)
« on: August 02, 2017, 10:23:20 AM »
http://rscl-grss.org/index.php
The following users thanked this post: subash

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Are you serving as a referee for journals? Want to add this into your CV? Now, you have Publons! Scientists rarely get credit for one of their most important jobs — the unpaid task of peer reviewing papers. The startup Publons was created to change that by encouraging researchers to post their peer-review history online.
https://publons.com/home/
https://www.nature.com/news/the-scientists-who-get-credit-for-peer-review-1.16102
The following users thanked this post: Chandan Banerjee

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Announcements / 2017 AGU Fall Meeting
« on: July 02, 2017, 09:53:29 AM »
Early Abstract Submissions Deadline: July 26, 2017
Abstract Submissions Deadline: August 2, 2017
2017 Fall Meeting Begins: December 11, 2017
http://fallmeeting.agu.org/2017/
http://fallmeeting.agu.org/2017/abstract_overview/abstract-submissions/
Some Important Sessions:
General Surface Hydrology: https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session24952
Emerging Technologies for Hydrologic Remote Sensing: https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session26397
Applications of machine learning in hydrology: https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session24633
Drones in Hydrology: How are Unmanned Aerial Vehicles Advancing our Understanding of Earth’s Critical Zone?: https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session25667
Hydroclimatic Extremes: Drought: https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session29430
Remote Sensing and Modeling of the Terrestrial Water Cycle: https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session23042
Advances in hyperspectral infrared remote sensing in cloudy atmospheres: https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session25458
Remote Sensing Applications for Water Resources Management, Including Droughts, Floods and Associated Water Cycle Extremes: https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session23335
Evapotranspiration: Advances in In Situ Measurements and Remote Sensing Based Modeling Approaches: https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session29394

The following users thanked this post: Sonali

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