Steps towards Integrated Open Water Data

Multiplicity of data collection agencies, formats, and disclosure practices and conditionalities make it very difficult to access interoperable and open data about water resources and systems in India. Barriers to accessing water data impede not only academic and applied research on related topics but also public consumption of information and critical decision making. DataMeet and CIS are proud to collaborate on identifying and addressing the challenges to open up and integrate data and information in the water sector. Supported by a generous grant from Arghyam, we are undertaking an initial study of open water data resources in India and taking first steps towards developing a Free and Open Source data portal for water resources information in India. Here is an initial note about the project. The key leaders and contributors of this project are Craig Dsouza, Namita Bhatawdekar, Riddhi Munde, and Jinda Sandbhor, all of whom are members of the Pune Chapter of DataMeet.

 

Project website: https://datameet-pune.github.io/open-water-data/

Contact: [email protected]


The problem statement

Following devastating precipitation of more than 300mm in 24 hours in early December 2015 the city of Chennai was flooded unlike anything it had seen in recent history. A combination of bad urban planning along with heavy precipitation events had made such eventualities all the more likely. But in the case of such storms what parts of the city are likely to flood? What parts will remain unaffected by the deluge. Specific answers to these questions would help city planners plan better for such emergencies.

Only two months after Chennai was waist deep in water, the city of Latur in 2016 ran dry. The Manjara reservoir, on the river of the same name, the city's source of municipal water supply had not a drop left. With more than 4 months left until the rains would replenish the waters of the dam, the city was now reliant on water being transported in bulk via train tankers from more than 300 kms away, news that made daily headlines. The scale of sugarcane cultivation in the region was being called into question.. Was it possible that lowering the allocation of water to irrigation could have preserved enough water for the city's domestic water needs?

Each of these questions call for answers relating to the exact stock of water resources, and how fast the water flows from one part of the water cycle to another. For example, knowing current soil moisture levels and daily precipitation can we estimate groundwater recharge with a high degree of accuracy? If seasonal groundwater fluctuations and river flows in a watershed or sub-basin is known can we estimate actual quantum groundwater footprint of the crop irrigated with groundwater in that river basin? If new industries are being set up in close proximity to each other what might be the effect of these industries on groundwater stocks in the vicinity.

 

Towards an (integrated and open) data solution

Deriving cause-effect links between the scale of use of water in a particular region and its possible effect on the status of water resources in the vicinity is an extremely difficult exercise because water stocks and flows are affected by so many causal links which need to be studied and quantified in an integrated manner. An integral part of any water resource study is developing a water balance model to estimate water availability and water demand.

Water availability

  • Precipitation in the form of rainfall and snowfall,
  • Live storage capacity in reservoirs,
  • Soil moisture,
  • Groundwater levels (and fluctuation), and
  • Surface water flows in rivers.

Water use/demand

  • Domestic water use: Human Population x estimated per capita consumption (or prescribed norm for domestic water consumption),
  • Livestock water use: Livestock population x estimated per capita requirement,
  • Agriculture and Forests: Evapotranspiration data (derived from temperatures (daily/monthly), wind speeds, humidity (daily/monthly), soil moisture & type, type of Agricultural land use, stage of plant growth, and
  • Industry: Nature of industry and annual production x water required per unit of production.

Overcoming the data challenge

Unknown to many, reasonably high resolution data does exist of these variables both across space and time, as described in detail below. Much of this data though hasn't been made inter-operable. We need tools to model water data, putting together real-time data for water availability and demand onto one platform that can facilitate discussions around it. However what we have are either proprietary river basin modeling software (expensive) OR free open source tools (programming/skill intensive).

They demand:

  • knowledge of programming or know-how of technical tools and unavoidably
  • knowledge of the various data sources (to piece together the puzzle)

What if instead, we had access to a tool, open, free, accessible to everyone through a browser (hence no need to download software) and most importantly intuitive to use and understand to someone with little technical or programming knowledge.

 

What we propose and who is it for?

To understand and take the first steps towards developing a completely free and open source data portal for water resources information in India.

Different groups would have different kinds of needs for water data. Researchers for instance tend to think of larger scales (river basins, sub-basins) whereas Gram Panchayat members may not think beyond the village or watershed scale. Hence this proposal aims at macro and micro scales, trying to determine needs at each level and enhancing our platform to meet these different needs.

The project will generate:

  • A web app prototype that will collate secondary data,
  • A paper that outlines sources of data, type of data, level to which available (GP, village, etc.) and nature of the source (Paid/ unpaid/ format available etc.), and
  • A model WSP format, along with indications for what data already exists in secondary sources.

The users of this work will be:

  • Researchers/Journalists in the water sector, and
  • Gram Panchayat Members (to effectively develop water security plans, monitor and govern their local water resources).

 

Project Team

The project team is supported by Nisha Thompson (Director, DataMeet) and Sumandro Chattapadhyay.

Craig Dsouza

Craig is an independent researcher in the development sector with a keen interest in water resources and agriculture. He has a Master’s degree in Energy and Environmental Policy (2013) and has worked as a researcher with the Society for Promoting Participative Ecosystem Mgmt, undertaking river basin studies in central and eastern India. Craig believes that the democratization of data and tools to derive insights from it holds tremendous potential for addressing issues of inequity and environmental sustainability in India. He contributes to these efforts as co-ordinator of Datameet-Pune, a city chapter of datameet.org.

GitHub: https://github.com/craigdsouza
Twitter: https://twitter.com/dsouza_craig
Website: http://unravellingindia.in/

Namita Bhatawdekar

Namita is a web developer with 10 years of experience developing web applications and web-based data visualizations. She has worked on developing data Visuaizations for corporate businesses as well as in the research sector. She worked with Singapore-MIT Alliance for Research and Development (MIT's research lab in Singapore) as a Data Visualization expert where she visualized simulation outputs of autonomous vehicles to evaluate urban transport policies. Her work was showcased in many national and international conferences. She has a keen interest in solving social problems using data and is part of Datameet Pune, city chapter of datameet.org.

GitHub: https://github.com/bnamita
LinkedIn: https://www.linkedin.com/in/namitabhatawdekar/
Website: https://bnamita.github.io/Portfolio/

Riddhi Munde

Riddhi is a GIS and Remote Sensing professional with 2.5 yrs of experience. She has a Master's degree in Geoinformatics and Earth Observation from ITC, University of Twente, The Netherlands. Her project experience includes implementing GIS and remote sensing solutions across a number of industries. She is interested in location and remote sensing analytics, ML, Image processing, web based visualizations and is proficient in ArcGIS, QGIS, PostGIS, Web mapping, algorithm development in Python and R and cloud computing. At Datameet she contributes with her know how of remote sensing to further improve data access in water and agriculture.

LinkedIn: https://www.linkedin.com/in/riddhimunde/

Jinda Sandbhor

Jinda Sandbhor is an action researcher associated with Manthan Adhyayan Kendra, Pune, where he works to document and analyze issues related to the water and energy sectors in India. He actively supports socio-political movements in Maharashtra, Odisha and North Karnataka. In the past he has conducted research studies on water conflicts around rivers and major dams, socio-economic impacts of droughts, impacts of coal based thermal power on water and the local environment. He has been associated with the Datameet-Pune chapter since its beginning in 2015 and here seeks to improve access to data on social and environmental subjects.

Website: http://jinda.manthan-india.org/author/jinda/

 

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