Shreevidya Nargolkar & Kalyani Kadam
Adv. Balasaheb Apte College of Law, Mumbai & S.N.D.T. Law School, Mumbai
Introduction:
As India grapples through the vagaries of monsoon every year, floods appear to inevitably accompany the same. Floods have claimed more than 800 lives, affecting millions throughout the nation in the ongoing monsoon season. The latest push for flood plain zoning legislation by the Centre comes at a time when floods have affected several states. On 10th August 2020, the Hon’ble Prime Minister of India held a meeting with 6 Chief Ministers perceiving the potential and colossal damage that floods may cause. The agenda of the said meeting was to review their preparedness to deal with south-west monsoon and current flood situation in the country. A need for enhanced centre-state coordination coupled with permanent system for forecasting of floods and extensive use of innovative technologies for improving forecast and warning system were discussed. During the said deliberations emphasis was laid upon the need to develop in the following two aspects:
- Structural or Physical
- Technical or Technological
After perusing the current mechanism and laws pertaining to this subject-matter, one may infer that there is a third aspect which also requires development. It is perceived that the field of legislative drafting or planning also needs further development. This article will attempt to breakdown the central issues surrounding flood forecasting in two parts. Part I shall deal with an introduction to the various available mechanisms and the administrative challenges including drawbacks of the same. Part II of the article shall brainstorm practical solutions to improve the accuracy of flood forecasting.
Weather Forecasts as a subject-matter for legislation finds its place under Entry 68 of the List- I (Union List) of the Seventh Schedule. The need for flood plain zoning had received recognition in the 1970’s and the Union Government circulated a model draft bill for flood plain zoning in 1975 to all the states. Unfortunately, the legislation was delayed.
Before dwelling into the complexity of the current functioning of the MoES so far as flood forecasts and its management is concerned, it is pertinent to clear the cloud of confusion regarding the current functioning of this subject and so we may briefly advert to the importance of institutions such as the IMD, CWC, IITM, NCMRWF and CWC.
In furtherance of the strategy for laying more emphasis on non-structures, a Nationwide Flood forecasting and warning system has been established by Central Water Commission (‘CWC’). With reliable advance information / warning about impending floods, loss of human lives and moveable properties and human miseries can be reduced to a considerable extent. The flood forecasting system of CWC in India functions under ‘Member River Management’ and is responsible for hydrological-meteorological data collections. The flood forecasting network of the CWC covers most of the flood prone inter-state river basins in India. Early warning is especially extremely valuable in cases of flashy floods which are quite frequent on Himalayan Rivers and their tributaries due to heavy landslides. Likewise, such warnings are also extremely useful in cases of flooding by cyclones and storms surges in coastal parts of the country.
Prevailing Flood Forecasting Mechanisms:
Today, droughts and floods are no more considered as an anomaly however; their coexistence poses a potent threat. The danger cannot be remedied by eradication but the destruction resulting from it can be managed. This posed to be an acute concern for India in 1950s when the country’s post-Independence economic development program was launched. The Government of India under its Third Five Year Plan formed the Institute of Tropical Meteorology (ITM) Pune, as a distinct-unit of the IMD. Consequently, the Institute of Tropical Meteorology was recognised as an autonomous organization as IITM. After the recognition of MoES, it has been under the administrative control of the said Ministry.
The flood forecasting departments are spearheaded by the Ministry of Earth Sciences (hereinafter referred to as ‘MoES’). MoES has administrative control over the India Meteorological Department (‘IMD’), Indian Institute of Tropical Meteorology (‘IITM’) and National Centre for Medium Range Weather Forecasting (‘NCMRWF’). The scientific programs of MoES are being carried out vide schemes & policies which, inter alia, aim to achieve development in the earth system science realm towards socio-economic benefit of the society and also provide services for weather, climate, ocean, coastal state, natural hazards, etc.
The India Meteorological Department is the National Meteorological Service of the country and the principal government agency in all matters relating to meteorology and allied subjects. It has been formed to warn against severe weather phenomena like tropical cyclones, heavy rains, cold and heat waves, etc. IMD has adopted a Numerical-Weather-Prediction Model called the Global-Ensemble-Forecasting-System (‘GEFS’), which has apparently enhanced the weather predictions. The Data Supply Portal is formed under IMD for online management of all activities related to Supply of Meteorological Data.
The National Centre for Medium Range Weather Forecasting (hereinafter referred as ‘NCMRWF’) is a Centre of Excellence in Weather and Climate Modelling under the Ministry of Earth Sciences. NCMRWF receives global meteorological observations through the Global-Telecommunication-System (‘GTS’) via Regional-Telecommunication-Hub (‘RTH’). The mission of the centre is to develop advanced numerical weather prediction systems, with increased reliability and accuracy over India and neighbouring regions. Apart from the above-mentioned mission, the centre also handles the ‘Severe Weather Forecasting Demonstration Project’ aiming to deliver improved forecasts and warnings of severe weather to save lives, livelihoods, and property. It also provides services such as Rainfall Information, Monsoon, Cyclone, Climate Services, City Forecast, Severe-Weather-Monitoring Extremes Charts and is also involved in Modern Julian Oscillation (‘MJO’) monitoring.
Administrative Challenges Owing To Which Forecasts & Weather Conditions Do Not Correspond:
Prima facie, it is apparent that there are several departments and institutions which strive to forecast the vagaries of nature. The accuracy of forecasts is however of 2-3 weeks only. It indubiously is a high accuracy rate when compared to several other developing nations however, considering the amount of human resource engaged in this field, the accuracy rate can effortlessly soar to greater heights. We may now divert to the probable reasons owing to which the forecast machinery falls short to function in full swing.
Despite wide ranging recommendations for flood management over the decades since 1954, short term measures and engineering structures continue to dominate the formal management approach. On assessment of the extant policies, institutional weakness and implementation history, it appears that the failure to address the issue of flood and erosion are, absence of a comprehensive long-term policy on disaster management and lack of basin wide approach that brings all the river-basin sharing countries as well as Indian States on board.
The Model Bill of 1975 on flood plain zoning provides for flood zoning authorities, surveys and delineation of floodplain area, notification of limits of floodplains, prohibition or restriction of the use of the floodplains, compensation and power to remove obstructions. Besides, keeping in mind the huge backlog due to insufficient funds, the ministry has also decided to focus on implementation of better coordination between Central and State agencies to have a permanent system for forecasting and the use of innovative technologies to improve forecast and warning system. Manipur enacted a floodplain zoning legislation in 1978, but the demarcation of flood zones has not been done, as yet. Rajasthan has also enacted the legislation. Uttarakhand also passed the Flood Plain Zoning Act on December 16, 2012, but the demarcation of flood zones has again not been completed.
Currently, a gamut of policies and departments exist working towards the same objective, howbeit, in disintegration. A webster of these efforts may lead to enhanced results. A counterargument to this suggestion may be that pragmatic challenges would be faced as the different departments follow different strategies and schemes to forecast weather. Furthermore, there are different types of forecasts given by these departments.
The lack of homogeneity in the functioning of the various bodies which function for the same object, to forecast, is apparent. A new method can be evolved which will help create accurate statistical data by combining model forecasts systems. This is plausible through quantitative precipitation forecasting (‘QPF’) models of large-scale features with known past values of temperature, humidity, and winds at different pressure levels from the surface to the upper atmosphere. Using QPF, one can calculate the probable amount of melted precipitation that accumulates over a particular geographical area and timeframe. The forecasts can be verified through use of rain gauge measurements & weather radar estimates after taking topography into consideration. According to research analysts, the QPF system has been proved to increase the accuracy from 20% to 90% for Day-5. This system will not only be economically efficient but also will help running high-resolution region-specific models. However, for effective implementation of this idea, a proper mechanism is required to be set up so as to enable proper coordination between the different forecasting departments.
It is note-worthy that not only the methodology of functioning is heterogeneous, but even the geographical distribution of departments is unequal. A sparse web of weather stations exists in the Himalayas each of which is approximately 80-90 kms away from each other. Similarly, a meagre number of stations exist in Jammu and Kashmir, Himachal Pradesh and Uttarakhand. There are around 8,000 stations in the rest of the country however several of those are non-functional. If uniformity in the density of weather stations is achieved, major issues can be resolved. This can be done by the government directly. The government can also chalk out a non-conventional solution by incentivising ‘Personal Weather Stations’. Reverting to the problem of heterogeneity, there exists lack of coordination between agencies tracking the weather as per the weather scientists. A proper mechanism enhancing the coordination is thus, a must-have at this point of time.
The MoES does not have any set norms and it reasons the same as a consequence of ‘no service provided to the public’. The mandate of IMD however, categorically states that it exists for ‘Public Welfare’. The vision of IMD apparently is to help the State to protect the right of persons envisaged under Article 21 i.e. the Right to Life. This is in consonance with the vision of MoES i.e. to achieve socio-economic development. As mentioned previously, colossal damage is caused to life and property of persons if the forecasting department does not function in a disciplined manner.
Although the SMRF have demonstrated enhanced accuracy in weather predictions, it cannot be denied that the uncertainties in predicting extreme vagaries of weather is still extremely poor. Furthermore, public opinion alleges that the ‘false alarm ratio’ whereby high rainfall is wrongly predicted is also high. An atmosphere of panic is caused by such false alarms which lead to disturbance in the lives of hundreds of people. Schools have been cancelled after IMD had issued faulty warnings in the past.
As the current departments are indeed capable of achieving higher accuracies, Hon’ble Prime Minister Shri Narendra Modi held a meeting inviting suggestions which will enhance the forecasting accuracy rate. In the light of the same, we have also brainstormed certain simple yet pragmatic recommendations, which shall elaborately be discussed in part II of this article.
