Governance

Data on sugarcane in Maharashtra after floods shows why accurate assessment is critical

 
By Charmi Mehta
Last Updated: Wednesday 22 April 2020
A sugarcane field blooms in Satara. Kolhapur, Sangli and Satara account for 40 per cent of Maharashtra's sugarcane crop Photo: Flickr

The August 2019 floods in Maharashtra unleashed massive damage, especially sugarcane and crops pertaining to horticulture. Sugarcane was planted over 1.52 lakh hectares in Kolhapur and 95, 827 hectares in Sangli, according to the state’s sugar directorate.

Kolhapur, Sangli and Satara — the top three sugarcane-producing districts in the state — witnessed submerged fields for over 20 days. This led to wilted and stunted leaves, with a quickly spreading fungus that ate into the sugarcane leaf.

The surety of water in this region, rich soil and a supportive cooperative movement ensured a prosperous rural economy for decades.

In the course of my detailed study of sugarcane in Maharashtra, I interacted with many stakeholders — who are part of the sugar industry — on the implicit and explicit effects of floods on the sugarcane crop.

A glaring revelation was the inconsistency in data around flood-affected areas: Reports prepared by different stakeholders reflected altogether different realities.

An estimated 40 per cent of the sugar stock would be affected as most parts of Kolhapur, Sangli and Satara were affected, according to an August 2019 report by the state’s agricultural officers. The three areas contribute over 40 per cent of Maharashtra’s cane crop.

One expected accurate figures to be released by February 2020, months after effects of the flood had subsided, but this was not the case.

Data for sugarcane is gathered and maintained by the statistics wing of the agriculture department as well as sugar factories (for the fields within their jurisdiction). The data I received from the statistics wing showed the flood-affected area (for Kolhapur) at 62,000 hectares whereas that from the sugar directorate (collaborated data from all sugar factories) showed 32,000 hectares to be affected by floods.

“The term ‘flood-affected’ has multiple interpretations. We use 33 per cent of the crop or greater as the mark to qualify a field as affected, while the sugar directorate might use 50-60 per cent affected as their mark,” said an official of the statistics wing of Kolhapur’s agricultural department. “This is why our figures show a higher quantum of crop as affected,” he added.  

The root of this problem lay in the fact that there exist vast inconsistencies in determining the area under sugarcane cultivation itself, the official said, adding that this resulted in inconsistencies in subsequent data calculations as well.

This is because there are three departments to carry out their own set of calculations, each of them using different parameters and different techniques.

The revenue department carries outs estimations on the basis of 7/12 documents (an extract from the land register of any rural/semi-rural district in Maharashtra that details vital information).

Farmers generally have a tendency to under-report to revenue officials as the 7/12 extract is used for tax collection purposes and under reportage of their landholding is beneficial to them here.

Calculations by sugar factories, on the other hand, are based on the registrations by its stakeholders (farmers) who usually over-exaggerate their landholding to get a preference during the cane cutting and collection period, as larger fields are tended to first.

The third authority involved — the agricultural department — gathers data on flood and drought affected areas through surveys and eye estimates that need to be assimilated quickly to give the state government statistics during the time of disaster so they can demand funds for rehabilitation from the Union government.

Little to no coordination between these authorities is what causes the chaos, and what we are left with are approximations and estimations, sometimes as far apart as 30,000 hectares.

In an attempt to enable more effective estimation of climatic damages caused, India needs to fully adopt remote-sensing data analysis through our multiple satellites. These images can be used to cross-verify claims made by local authorities to provide accurate and timely information.

Damage assessment can be further improved by adjusting remotely-sensed topographical data with ground observed elevation data for certain points and also by using locally available land-cover data to reflect actual local conditions.

Uniformly assessing the damage to crops (through comparisons with pre-disaster baseline information) also helps allied industries make projections about their expected losses.

Countries also began developing damage curves to reflect actual characteristics of cultivation patterns (for each significant crop atleast). Hydrological cycle and flood simulation models are also becoming globally accepted forms of accurate assessment.

International flood assessment is ideally carried out by identifying the areas affected (topographical exposure), assessing inundation levels using a hydrological model (defining hazard level) and projecting these on a ‘damage curve’ for a crop, to reflect the vulnerability of the crop at different levels of submersion and rainfall.

A combined evaluation of exposure, hazard and vulnerability levels can give us the quantum of agricultural economic loss suffered by a crop in a region. For drought, the appropriate model may need to take temperature into account as well.

How much damage is enough damage? When does one carry out this assessment? Which authority should be tasked with this?

Answers to these questions are important today: If current climatic trends are anything to go by, we must be prepared with models and practices for accurate estimation so we are not left directionless at the time of a disaster.

As we attempt to survive in a world ravaged by climate change, we also need to move away from approximation towards identifying accurate assessment models.

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