Questions
- UNDP has recently praised aspirational districts' programmes for local area development in a decentralized manner. Enumerating its features, enlist the success of this scheme. (15 marks)
- Though India has developed methods to predict cyclones, there is difficulty in predicting cloudbursts and the resultant flash floods. Explaining the current method of flash flood prediction, enumerate the issues involved in their prediction. (10 marks)
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Model Solutions
1. UNDP has recently praised aspirational districts' programmes for local area development in a decentralized manner. Enumerating its features, enlist the success of this scheme. (15 marks)
Model Structure
Introduction
- Aspirational Districts Programme by NITI Aayog aims to improve 112 aspirational districts and their socio-economic status who have minimal progress in few development parameters. The development of these districts is important because they have more than 20% of the country’s population.
Main body
- Main strategies of this program include focussing each district’s strength, reaping low hanging fruits and fostering a sense of competition. In this context, its main features are-
- Autonomy to states and districts for local development in accordance with the bottom up model because local challenges require customized remedies.
- Involvement of the private sector and not for profit organizations helps bring in expertise and benefits in areas where the government can’t.
- This programme focuses on improving governance, smart use of resources and outcome oriented planning. Like Unayan Banka, which is a smart classroom initiative of Bihar aiming to improve learning outcomes.
- Culture of healthy competition among districts and rankings has further given an incentive to districts.
- Launched in 2018, its success in the past four years include-
- Global recognition of the programme along with its principles of 3Cs which include convergence, collaboration and competition.
- It covers five main areas like health, nutrition, education, agriculture and infrastructure on which overall socio economic development of a country depends.
- Model Anganwadi centers in these districts help improve health and education indicators as seen in increased institutional deliveries.
- Use of digital analytics for better planning and intervention as in Poshan application which observes child-growth, bed and staff availability etc.
- Many districts suffer from connectivity issues and steps like mobile health ambulances in Assam’s Baksa district ensures access to healthcare service delivery.
- Innovation in education, like the ‘Hamara Vidyalaya’ model of Namsai, has improved learning outcomes and teaching to a large extent.
- Improved infrastructure in remote naxal affected districts like Bijapur and Malkangiri. Financial inclusion by micro-ATMs in Gadchiroli to women self-help groups has helped improve access to capital for self employment.
Conclusion
- The Aspirational Districts Programme is a flagship initiative for most backward regions which has given ample case studies on how to tackle local challenges. Few improvements like financial autonomy to local administration, independent surveys for better data quality etc can further enhance objectives of the scheme.
2. Though India has developed methods to predict cyclones, there is difficulty in predicting cloudbursts and the resultant flash floods. Explaining the current method of flash flood prediction, enumerate the issues involved in their prediction. (10 marks)
Model Structure
Introduction
- Cloudburst is localized but there is a huge amount of precipitation in a very short time usually followed by thunder and flood conditions. By standard parameters, it is a cloudburst if it rains 10 cm or more per hour in around 10 km² area.
Main Body
- Though not very well developed, there are some methods to predict heavy rainfall events like-
- Indian Meteorological Department is the nodal agency to forecast rainfall events and heavy to very heavy rainfall events are forecast four to five days prior to actual occurrence.
- Extremely heavy rainfall events are forecast six to twelve hours in advance. These events have potential to trigger flash flood events.
- Another proposed method is data mining and deep learning techniques to understand seasonal patterns and enhance preparedness.
- But being a sudden activity with no build up time, there are few issues in prediction like-
- Any weather forecast involves a large geographical area, like a region, meteorological sub-division, or a district. But cloudburst is limited to a small area which further curtails the ability to predict cloudbursts and flash floods events.
- IMD lacks the capacity to predict the amount of rainfall which has an impact on the capacity to forecast flash floods.
- Cloudburst is localized which makes it financially tedious to install equipment at many places with less success ratio. Because cloudbursts are localized and random phenomena, there can't be a targeted prediction mechanism.
Way forward
- Urgent need to work on Flash Flood Guidance System developed by IMD and USA’s weather mechanism system.
- Mitigation measures can be adopted like like non-structural real-time flood forecasting, dam break simulation, flood hazard and flood plain zoning etc.
Conclusion
- India has developed technology but climate change and increased frequency of extreme weather events makes prediction difficult. Thus there is a need to develop better capabilities and technical capacities to predict such events in advance.
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