Indian Forum for Water Adroit

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The Parallel Data Assimilation Framework - PDAF - is a software environment for ensemble data assimilation. PDAF simplifies the implementation of the data assimilation system with existing numerical models. With this, users can obtain a data assimilation system with less work and can focus on applying data assimilation.
PDAF provides fully implemented and optimized data assimilation algorithms, in particular ensemble-based Kalman filters like LETKF and LSEIK. It allows users to easily test different assimilation algorithms and observations. PDAF is optimized for the application with large-scale models that usually run on big parallel computers and is applicable for operational applications. However, it is also well suited for smaller models and even toy models.
PDAF provides a standardized interface that separates the numerical model from the assimilation routines. This allows to perform the further development of the assimilation methods and the model independently. New algorithmic developments can be readily made available through the interface such that they can be immediately applied with existing implementations. The test suite of PDAF provides small models for easy testing of algorithmic developments and for teaching data assimilation.
PDAF is an open-source project. Its functionality will be further extended by input from research projects. In addition, users are welcome to contribute to the further enhancement of PDAF, e.g. by contributing additional assimilation methods or interface routines for different numerical models.

River Linking may have the potential to accelerate global warming on a short term in addition to its possible adverse effect  on monsoon rain-fall in India on a long term.

Article :
Rajamani, V., Mohanty, U.C., Ramesh, R., Bhat, G.S., Vinayachandran, P.N., Sengupta, D., PrasannaKumar, S. and Kolli, R.K., 2006. Linking Indian rivers vs Bay of Bengal monsoon activity. Indian Academy of Sciences.
Programming / List of R Packages for Hydro Research by Sam Zipper
« Last post by Alok Pandey on July 20, 2018, 03:42:50 PM »
Sam Zipper( @ZipperSam ) has compiled a list of packages which can be useful in water resources engineering and research.

Twitter Thread :
Link to Doc :
Interesting information / Do you know SM2RAIN? Read here its short story...
« Last post by Pankaj Dey on July 19, 2018, 09:04:55 PM »
SM2RAIN is an algorithm, it is not complex or difficult to understand. It is based on a simple concept, i.e., when it rains, soil moisture increases. Therefore, simply relying on the inversion of the soil water balance equation (that is the equation governing the water fluxes between the atmosphere and the land surface), we estimate RAINFALL from SOIL MOISTURE observations: "Soil as a natural raingauge" (JGR 2014).

To read the remaining part, please follow the link:

Dear All,

GIAN, MHRD, Govt. of India sponsored International Course on  " ENVIRONMENTAL AND WATER RESOURCES DECISION MAKING USING INFORMATION THEORY UNDER CLIMATE AND ANTHROPOGENIC CHANGES" will be held during November 26–30, 2018 at College of Technology, GBPUAT, Pantnagar.
The International expert faculty will be Prof. Vijay P. Singh is a Distinguished Professor and Caroline & William N. Lehrer Distinguished Chair in Water Engineering, Department of Biological and Agricultural Engineering and Zachry Department of Civil Engineering, Texas A & M University, College Station, Texas, USA.

His research interests include Surface-water Hydrology, Groundwater Hydrology, Hydraulics, Irrigation Engineering, Environmental Quality and Water Resources, and Hydrologic Impacts of Climate Change.
His professional heights include 850 papers published in refereed journals, 24 books, 57 edited books, 100 book chapters and many technical reports and special issues of journals. He is editor of many Journals. He has been awarded 2012 Texas A& M University Bush Excellence Award for Faculty in International Research; University Distinguished Professor Award 2013, Texas A & M University, 2013; and Lifetime Achievement Award, Environmental and Water Resources Institute, American Society of Civil Engineers, among more than 72 awards.
For registration visit

For course information visit

For updated information;

For GIAN information

Experts view:
Kindly circulate among your interested colleagues, research scholars, post graduate students, faculty, scientists, engineers.
Study material / Machine Learning study materials
« Last post by Diwan on July 18, 2018, 11:46:50 AM »
Dear all


Some useful study materials for machine learning is available at
Interesting information / Online Resources on Spatial Analysis and GIS using R
« Last post by Pankaj Dey on July 17, 2018, 10:01:41 PM »
Jakub Nowosad, a postdoc in the Space Informatics Lab at University of Cincinnati has develop these two courses on Spatial Analysis and GIS using R.

The relevant links are as follows:
Sample R Codes are also available with practical examples.

1. Introduction to Spatial Analysis using R.


2. GIS with R


3. Data Visualization and preprocessing

Link: 1.

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements ( ∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76 % of the experimental sites with agricultural land use as the dominant type (∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it.

Link to paper:

Link to dataset:
Announcements / PhD Position
« Last post by Diwan on July 13, 2018, 12:07:24 AM »
Dear all


Three well-paid and exciting PhD projects are available within the Environmental Hydrology and Water Resources Group, University of Melbourne.

1) Modelling shoreline vegetation to inform operations of Lake Victoria, NSW.

2) Understanding and managing climate risks to waterway health in unregulated river systems.

3) Improving flow-ecology models to improve environmental water management in a changing climate.

Last date by 29th July 2018
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