The NITI Aayog's sobering report on India's Composite Water Management Index warns that 21 Indian cities are on the verge of running out of groundwater. This national crisis is compounded by a systemic failure in our clean-up efforts. While ambitious government programs and a clear vision to restore our rivers have led to a consensus on the need for decentralised sewage treatment plants (STPs), the grim reality of polluted waterways and dry taps persists. The flaw in the flow is not the lack of infrastructure, but its fragmented, opaque management, a systemic disconnect that has hobbled progress for decades.
Urban India generates over 72 billion litres of sewage per day, yet less than a third of this is treated. The rest, a torrent of untreated waste, is discharged into rivers that once sustained communities and now flow as little more than open sewers. Our strategy of building decentralised STPs, while conceptually sound, has failed at the crucial stage of implementation. These plants often become "islands of inefficiency," plagued by poor maintenance, inconsistent performance, and underutilisation. The reasons are a litany of well-documented failures: inaccurate design for local conditions, operational errors by untrained staff, and the frequent breakdowns that plague poorly monitored sites. These are not merely technical glitches; they are fundamental failures that undermine the entire mission.
The solution is not more of the same. It is a new blueprint for management-a digital backbone powered by AI and e-governance to connect and optimise every plant, transforming them into a single, cohesive, and accountable network. The first component of this backbone is AI. Internet of Things (IoT) sensors, a type of AI technology, can be deployed on every decentralised plant, regardless of its size or location. These sensors would provide real-time monitoring of critical parameters like pH, Biochemical Oxygen Demand (BOD), and Chemical Oxygen Demand (COD). This hands-off approach eliminates the potential for data manipulation inherent in a human-reporting system, providing a verifiable source of truth on water quality. Furthermore, AI can enable predictive maintenance, analysing data patterns to forecast equipment failure before it happens, thereby preventing costly downtime and ensuring plants operate at peak efficiency. This can also lead to significant energy savings, a win for both the environment and the municipal budget.
The second, and equally vital, component is a robust e-governance framework. We must propose a centralised, publicly accessible dashboard where the data from every single decentralised STP is automatically relayed. This would be a system of radical transparency. The Central Pollution Control Board (CPCB) is already implementing a similar system for large industries, known as Online Continuous Effluent Monitoring Systems (OCEMS). This model can and should be scaled and made mandatory for all urban STPs.
The CPCB's mandate carries legal teeth, backed by powerful legislation like the Environment (Protection) Act, 1986, which allows it to issue directions, levy heavy financial penalties, and even shut down non-compliant plants. Yet, a system relying on intermittent, delayed, or manipulated data is like a vigilant watchman with no eyes. The live dashboard would display water quality in real-time, instantly flagging non-compliant plants and triggering automated alerts to authorities. Beyond mere compliance, this transparency would foster public trust and engagement, empowering citizens to become direct stakeholders in the health of their local water bodies.
The fiscal benefits of this approach would be immediate and transformative. A structured, tech-enabled system would not just generate revenue from a new resource; it would also plug several significant fiscal leaks in the public budget. For instance, cities facing water stress spend exorbitant amounts on water tankers. In a major city like Bengaluru, the cost of a private tanker can be as high as approximately `3,000 for a single 12,000-litre tanker. A reliable, decentralised system would provide a local, consistent source of non-potable water, drastically reducing the need for these expensive and inefficient fleets.
Similarly, by providing nutrient-rich treated wastewater for irrigation, we can contribute to a more sustainable budget by reducing the reliance on government-subsidised inputs like agricultural electricity (for groundwater pumps) and chemical fertilisers. As of 2025, the government's fertiliser subsidy stands at a staggering `1.92 lakh crore.
By making wastewater a viable alternative for agriculture, we can chip away at this enormous expenditure while simultaneously helping recharge aquifers. These savings, combined with the avoided healthcare costs from waterborne diseases-a burden that the WHO estimates at over $100 billion-make this approach a fiscally responsible policy, not just a green initiative.
The economic value of treated wastewater extends to the construction sector as well, where there is a growing demand for non-potable water for concrete mixing and curing, which can be met by a secure and transparent supply. Ultimately, a river is only as clean as the sum of its parts. By connecting every decentralised plant with a digital nervous system, we can turn a silent tide of waste into a flowing, transparent asset. This is how we will heal our rivers, one data point at a time.
Tanmoy Chakrabarty is Founder & Director of Chakrabarty Consulting Services and Vanshita Garg is a Consultant with Chakrabarty Consulting Services Tanmoy Chakrabarty is Founder & Director of Chakrabarty Consulting Services and Vanshita Garg is a Consultant with Chakrabarty Consulting Services
