Drowning in data gaps: Lack of reliable information imperils rivers' revival

India’s rivers are drying, polluted and poorly monitored. Yet policy and infrastructure decisions continue to rely on patchy, inaccessible data. River management remains reactive, not knowledge-driven. Strengthening India’s data systems is no longer a luxury; it is an urgent governance necessity.

The Condition Assessment and Management Plan (CAMP), a national initiative under the Ministry of Jal Shakti’s National River Conservation Directorate, offers a glimmer of change. It aims to prepare scientific, basin-level management plans for six major river basins: Cauvery, Godavari, Krishna, Mahanadi, Narmada, and Periyar. The programme brings together institutions such as IISc and several IITs/NITs to assess the present conditions and recommend interventions for river rejuvenation. 

As the panel discussions and presentations progressed in the second meeting of the Stakeholder Advisory Committee (SAC) for the CAMP at the IISc, Bengaluru, there was a sense of optimism that government and academia were finally sitting together to discuss the state of India’s rivers in a structured way.

The SAC-2 meeting revealed both the promise and the persistent paralysis in our water-governance ecosystem. “Lack of data” dominated the presentations—a familiar chorus in India’s environmental dialogues. The senior official chairing the meeting emphasised using whatever data is available, coordinating with state departments to obtain missing datasets, and proceeding to actionable recommendations for the government.

All the research teams stressed the need to monitor rivers at higher frequency and finer spatial scales. Everyone agreed that robust data are the foundation for good river management. But how to overcome the institutional bottlenecks that make even existing data inaccessible or unreliable was not addressed. 

One major takeaway was the inadequacy of our flow-monitoring network.
The Central Water Commission (CWC) stations are simply too sparse to capture today’s ground reality. For instance, there are only two discharge stations on the 172 km long Arkavathi River, which drains a 4,178 sq km catchment. Both are located near the downstream stretches, leaving the highly urbanised upper reaches (read Bengaluru’s outflows) completely unmonitored. Without such information, designing sewage- or effluent-treatment plants becomes guesswork. 

Where monitoring does exist, it often serves as compliance. Reports are filed and numbers recorded, but insights rarely feed back into planning. Take the National Water Monitoring Programme (NWMP), 2017 guidelines, which classify monitoring locations as Baseline, Trend, Flux (or Impact) and Hotspot stations, each to be monitored with defined parameters and frequencies.

In practice, this categorisation is absent. The State Pollution Control Boards continue to monitor and report water quality, assigning water bodies an A–E “designated best use” classification. Yet, the very basis of what the intended best use should be for each river stretch or lake is undefined, leaving the entire exercise floating without context.

Moreover, the current water quality standards for irrigation in India address only a narrow set of basic parameters. As India becomes a global hub for pharmaceutical and chemical manufacturing, our regulations and monitoring protocols must evolve, becoming far more comprehensive and stringent to detect and manage emerging contaminants that now flow freely in our rivers and aquifers.

Through the discussions, it was evident that most participants knew the familiar problems that ailed our rivers. Yet deep understanding demands knowing where, what kind, and why specific degradations occur. This spatial understanding is missing. We seldom map pollution sources or hydrological changes with sufficient resolution to see local patterns. Without that, we cannot define the problem precisely enough to design solutions. Spatially mapped, local-scale data would make an immediate difference.

Even when datasets exist, accessing them from government departments often involves prolonged correspondence and repeated visits. At the meeting, researchers were encouraged to obtain data by physically visiting departmental offices and waiting until officials released the information.

One individual who managed to secure such data was lauded as the “data man”, and his persistence was cited as a model for others. Yet this highlights a systemic problem. Experts are forced to expend months pursuing essential data that should already be publicly accessible.

If such datasets were open-source and standardised, we could move faster from:
data—>diagnosis—>decision —>implementation —>monitoring —> learning.

Transparent data is not just a technical need; it is a democratic necessity. When information about rivers is public, citizens can engage, question and contribute. Our national scientific temperament grows when ordinary people can see, interpret and debate the same evidence that experts and officials rely on. Access to shared data transforms people from subjects to citizens. It builds accountability because decisions can then be verified, not just announced. 

CAMP represents a hopeful shift, an attempt to weave science into river-governance decisions. But its success will depend on how courageously institutions confront their own information deficits. Data are infrastructure; without them, every intervention is speculative.

If we can make data accessible, reliable and transparent, our rivers stand a chance of revival, and our governance, a chance of reform.

(The writer is a researcher and curator at Paani Earth Foundation, Bengaluru)

(Disclaimer: The views expressed above are the author's own. They do not necessarily reflect the views of DH.)