Archive for the ‘water’ Category
This panel of 12 images shows the change that takes place in a region of the Deccan. Each image shows what is called a Normalised Difference Vegetation Index (NDVI) for the region. This is a rolling eight-day series computed daily using imagery from the Terra/MODIS system and viewed using the NASA Worldview website.
The colours (green and brown shades, whitish shades) show us the vegetation health with deep green being better than light green, dark brown being better than light brown. The index is also used to signal where areas are beginning to experience arid and water-scarce conditions.
The region is the west-central Deccan – the Karnataka Plateau – corresponds to the Vijayapur (Bijapur) district of north Karnataka with parts of Bagalkot district and is part of the central Indian semi-arid bioclimatic zone.
The pictures in the panel show the vegetation extent and health (NDVI) calculated on that day for an eight-day period. Each picture is a fortnight apart, and this series starts on 4 November 2016 (bottom right) and ends on 7 April 2017 (top left). The retreat of the green is seen clearly from one fortnight to the next.
Of interest in this region is the Almatti dam and reservoir, in the Krishna river basin, which is visible in the lower centre of each picture. On 13 April there was no water in Almatti, which has a full capacity of 3.105 billion cubic metres (bcm). For the week ending 30 March it had 0.015 bcm of water, the week ending 6 April 0.001 bcm.
For the week ending 3 November 2016, which is when the panel of pictures begins, Almatti had 2.588 bcm of water. The reservoir water runs a hydroelectric power plant, of 240 MW, and which needs flowing water to turn the turbines.
When the reservoir is full, the hydel plant produces about 175 million units of electricity. But on 13 March the Central Electricity Authority’s daily report showed that Almatti could produce only 3.02 million units. On 10 April, this had plunged to 0.04 million units, but the hydel plant had produced no power since 1 April.
The 2015-16 fourth advance estimates for commercial crops, when compared with the annual averages for five year and ten year periods, visibly displays the need for more rational crop choices to be made at the level of district (and below), in agro-ecological regions and river sub-basins.
For this rapid overview of the output of commercial crops for 2015-16 I have compared the Fourth Advance Estimates of agricultural production, which have just been released by the Ministry of Agriculture, with two other kinds of production figures. One is the five-year average until 2014-15 and the second is the ten-year average until 2014-15.
While a yearwise comparison is often used to show the variation in produced crops (which are affected by price changes, policies, adequacy of the monsoon and climatic conditions), it is important to compare a current year’s nearly final crop production estimate with longer term averages. Doing so allows us to smooth the effects of variations in individual years and so gauge the performance in the current year against a wider recent historical pattern. (See ‘How our kisans bested drought to give 252.2 mt’.)
The output of the nine oilseeds taken together is less than both the five-year and ten-year averages. Significant drops are seen in the production of soyabean, groundnut and mustard and rape – these three account for 88% of the quantity of the nine oilseeds (castorseed, sesamum, nigerseed, linseed, safflower and sunflower are the others). Between the fibre crops – cotton, and jute and mesta – the output of cotton is considerably under the five-year average, while that of jute and mesta is under both the five and ten year averages.
It is in the figures for sugarcane that the message lies. The 2015-16 output of sugarcane is marginally above the five-year average and handily above the ten-year average. This needs to be considered against the background of two drought years (2014 and 2015) and the drought-like conditions that were experienced in many parts of the country during March to May 2016.
As these are near-final estimates, this only means that the allocation of water for such a large crop quantity – 352 million tons of sugarcane is about 100 mt more than the foodgrains output of 252 mt – was assured even during times of severe shortage of water.
This is a comparison that needs urgent and serious study, not with a view to change overall policy but to decentralise how crop – and therefore inputs and water – choices are determined locally so that self-sufficiency in food staples and the sustainability of cash crops can be achieved. These are quantities only and do not tell us the burdens of inputs (chemical fertiliser, hazardous pesticides, malignant credit terms) or the risks (as cotton cultivators have experienced this year) but where these are known from past experience their effects can well be gauged.
In an exercise to help determine how reports of the MGNREGA (Mahatma Gandhi National Rural Employment Guarantee Act or Nrega) can inform us, I have used the records of what the programme calls ‘outcomes’ in the form of ‘physical assets’ created for the community (or conditional use by groups of individuals, depending on the kind of asset) over a financial year.
The year is 2015-16 and the districts are those of Maharashtra (34, Mumbai excluded). There are at present 17 categories of physical assets and these are: rural connectivity, flood control and protection, water conservation and water harvesting, drought proofing, micro irrigation works, provision of irrigation, renovation of traditional water bodies, land development, any other activity approved, sewa kendra, coastal areas, rural drinking water, fisheries, rural sanitation, anganwadi, playground, food grain.
‘Works’ are recorded under each kind of physical asset, with these classified as having been ‘approved’, ‘taken up’ and ‘completed’ (with ‘taken up’ presumably meaning commenced but incomplete at the end of the financial year). What matters therefore is to study those that have been completed, as the kind of community asset created and certified as being completed would serve to indicate what the community has decided it needs as a priority.
When so filtered, the number of completed physical assets in the 34 districts of Maharashtra for the year 2015-16 totalled 71,554 – a large number that helps describe why the Nrega records are so very voluminous: 1,376 ‘works’ completed every week in 34 districts, with tens of thousands of Nrega beneficiary individuals and households working to build, repair, revive, create them, and with a complex inventory of raw materials being required to be transported and paid for so that these works may take shape.
What the list of completed works – type and number – describe is very instructive. Of the 17 categories, four (fisheries, anganwadi, playground and food grain) were recorded with not a single instance of having become a ‘work completed’ in any district. On the other hand, four kinds of physical assets accounted for a full 85% of the 71,554 works completed in Maharashtra’s 34 districts for 2015-16 and these were, in ascending order: drought proofing (8,110 and 11% of the total works), rural sanitation (12,234 and 17%), water conservation and water harvesting (14,384 and 20%), and provision of irrigation (26,496 and 37%).
The popularity of the latter four can be well understood, as much for how they are all linked as for the precarious living conditions that every taluka in Maharashtra’s semi-arid districts face when the winter months end. These biases towards certain works but not others still do however need to be read with conditions, and keeping in mind that these are the works for but one financial year out of the last ten (albeit the definition of what constitutes an asset under Nrega has been altered and added to several times).
The question that remains is: Maharashtra’s districts and blocks and villages occupy varying agro-ecological, hydrological and meteorological regions. Do their geographic and environmental circumstances not have a role to play in the decisions taken about what Nrega works should be taken up (and completed) as a priority over other kinds?
The charts presented here in groups of districts arranged according to their location amongst the six agro-ecological regions that Maharashtra occupies, indicate whether the Nrega ‘works’ process takes cognisance of the fundamental environmental factors upon which the village (and so panchayat, taluka, district) rest. The charts have been constrained to 200 on the vertical axis in order to preserve readability – values are given for each ‘work’ recorded by each district. The abbreviations for the ‘works’ (horizontal axis) are for the full forms found in the second paragraph.
The few paragraphs that follow are taken from my recent article for the TERI (The Energy and Resources Institute) magazine, Terragreen. Published in the 2016 May issue, the article links what we often call traditional knowledge with the ways in which we understand ecology and the ways in which we are defining ‘sustainable development’.
Sustainable development has today become a commonly used term, yet it describes a concept that is still being considered by different kinds of societies, by each in a manner of its choosing. This has happened because while historically how societies grew to be ‘developed’ was a process that took a variety of pathways, today the prescribed pathway to the ‘modern’ scarcely changes from one country to another.
Hence culturally what these societies have considered as being ‘sustainable’ behaviour – each according to its ecological context – is being replaced by a prescribed template in which interpretations are discouraged. Such a regime of prescription has led only to the obscuring of the many different kinds of needs felt by communities that desire a ‘development’ that makes cultural sense, but also of the kinds of knowledge which will allow that ‘development’ to be sustainable.
Some of this knowledge we can readily see. To employ labels whose origin is western, these streams of knowledge and practice are called traditional knowledge, intangible cultural heritage, indigenous wisdom, folk traditions, or indigenous and local knowledge. These labels help serve as gateways to understand both the ideas, ‘development’ and ‘sustainable’. It is well that they do for today, very much more conspicuously than 20 years earlier, there is a concern for declining biodiversity, about the pace and direction of global environmental change, a concern over the unsustainable human impact on the biosphere and the diminishing of community identity.
There is widespread acknowledgement of the urgency of the situation – this is perceived across cultures, geographical scales (that is, from local units such as a village, to national governments), and knowledge systems (and this includes both formal and non-formal ways of recognising these systems). The need for such a new dialogue on the situation is expressed in several global science-policy initiatives, both older and recent, such as the Convention for Biological Diversity (CBD) which is now 22 years old, and the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), whose first authoritative reports became available in 2015.
Development whose sustainability is defined locally and implemented locally means that the ‘investment’, ‘technology’ and ‘innovation’ (terms that have become popular to describe development efforts) comes from the people themselves. Many diverse agencies at this level – civil society, youth groups, vocational networks, small philanthropies – assist such development and provide the capacities needed. This is the level at which the greatest reliance on cultural approaches takes place, endogenously.
In domains such as traditional medicine, forestry, the conservation of biodiversity, the protection of wetlands, it is practitioners of intangible cultural heritage and bearers of traditional knowledge, together with the communities to which they belong, who observe and interpret phenomena at scales much finer than formal scientists are familiar with. Besides, they possess the ability to draw upon considerable temporal depth in their observations. For the scientific world, such observations are invaluable contributions that advance our knowledge about climate change. For the local world, indigenous knowledge and cultural practices are the means with which the effects of climate change are negotiated so that livelihoods are maintained, ritual and cultivation continue, and survival remains meaningful.
We lack not at all for experience with drought, yet have not grown used to treating water with the greatest of care. Drought does not strike in the manner a hailstorm does, yet our administrations seem unable to read the signals. Citizens and panchayats alike can contribute to our managing droughts better, provided all are willing to change both perception and behaviour.
It is because drought is such a forbidding condition for any state to fall into that it becomes at once threatening and emotive. Its every symptom becomes a new trial for a drought-afflicted population and simultaneously a likely indictment of the administration, whether local or regional. Food and crop, water and health, wages and relief: this is the short list for which action is demanded by a population concerned for those in the drought-affected districts and blocks.
The administration is bound to answer, as it is likewise bound to plan, prepare, anticipate and act. But where the interrogation of a government for its tardiness in providing immediate relief comes quickly, a consideration of the many factors that contribute to the set of conditions we call drought is done rarely, and scarcely at all when there is no drought. It is the gap between these two activities that has characterised most public criticism of the role of administration today when there is drought.
For farmers and district or block-level administrators alike, drought is a normal and recurrent feature of climate in the dryland regions of India. It occurs in nearly all climatic zones – our long recording history of droughts and floods in particular show that whereas in eastern India (West Bengal, Odisha and Bihar) a drought occurs once in every five years, in Gujarat, East Rajasthan and western Uttar Pradesh the frequency is once in three years. Although the characteristics of what we call drought varies significantly from one meteorological sub-division to another, and indeed from one agro-ecological zone to another, the drought condition arises from a deficiency in precipitation that persists long enough to produce a serious hydrological imbalance.
Drought is a complex phenomenon. There is first a need to distinguish between meteorological and agricultural droughts. A meteorological drought is a period of prolonged dry weather conditions due to below normal rainfall. An agricultural drought refers to the impact caused by precipitation shortages, temperature anomalies that lead to increased evapotranspiration by crops and vegetation, and consequently to a shortage of the water content in the soil, all being factors that adversely affect crop production and soil moisture. The National Commission on Agriculture has defined an agricultural drought differently for the kharif (monsoon cropping season, July to October) and rabi (winter cropping season, October to March).
What the country has witnessed during March and April is an agricultural drought, brought about by the high temperatures which raised mean and maximum temperatures into the heat-wave band. This we have witnessed in Odisha, Telengana, Vidarbha, Marathwada, north interior Karnataka, Rayalaseema, coastal Andhra Pradesh, Tamil Nadu, eastern Madhya Pradesh and Chhattisgarh, Jharkhand and West Bengal.
The Indian summer monsoon in 2016, for the months of June to September, will be normal to better-than-normal in almost all of the 36 meteorological sub-divisions. This is my reading of the seasonal climatic predictions provided by five different sources. Should the conditions that presage such a rainy season continue to be favourable, a normal monsoon coming after two years of faltering rain, and with drought conditions have set into many districts, will be a vast relief.
My outlook for the June to September 2016 monsoon period is based on an initial study of the three-monthly and seasonal predictions which are in the public domain, from the following agencies: The Climate Prediction and Monitoring Group of the India Meteorological Department (IMD), Ministry of Earth Sciences, Government of India; the Climate Forecast System Version 2 (CFSv2) by the Climate Prediction Center of the National Centers for Environmental Prediction (NCEP), USA; regionalised Multi-Model Ensemble (NMME) forecasts from the Climate Prediction Center which are based on models of the NOAA and NASA; and the Meteorological ‘Met’ Office of Britain which is a World Meteorological Organisation climate research centre.
Combining the indications from this early set of forecasts we see that after typical monsoon conditions have set in over southern and peninsular India, the June and July rainfall (quantities) should be normal for June with an increase in average rainfall for July (in the southern peninsula, the west coast, north-eastern states and the north India mountainous states). The five models currently also point to the August and September period recording above normal rainfall over most of India, and normal rainfall in central India.
Predictive capabilities have increased over the last few years, and a number of national weather service agencies collaborate to share data and expertise on climate models. There is much collaboration particularly for the Asian monsoons – our Indian summer monsoon and the monsoon of south-east Asia – because of the implications for the volumes of food crops, in particular rice and wheat, that are likely to be sown and then harvested.
The climatic prediction models whose forecasting products I examined make their predictions for 90-day periods (such as May, June and July together) based on conditions observed and calculated for a given month (January, February and March so far). Later in April and then twice again in May I will consolidate and expand the scope of this initial prognosis – which is of a normal to above normal monsoon – as the forecasts are updated. [This is also posted at India Climate Portal.]
In this panel of maps the relationship between the district of Parbhani (in the Marathwada region of Maharashtra) and water is graphically depicted over time. The blue squares are water bodies, as seen by a satellite equipped to do so. The intensity of the blue colour denotes how much water is standing in that coloured square by volume – the deeper the blue, the more the water.
Water bodies consist of all surface water bodies and these are: reservoirs, irrigation tanks, lakes, ponds, and rivers or streams. There will be variation in the spatial dimensions of these water bodies depending on how much rainfall the district has recorded, and how the collected water has been used during the season and year. In addition to these surface water bodies, there are other areas representing water surface that may appear, such as due to flood inundations, depressions in flood plains, standing water in rice crop areas during transplantation stages. Other than medium and large reservoirs, these water features are treated as seasonal and some may exist for only a few weeks.
The importance of monitoring water collection and use at this scale can be illustrated through a very brief outline of Parbhani. The district has 830 inhabited villages distributed through nine tehsils that together occupy 6,214 square kilometres, eight towns, 359,784 households in which a population of 1.83 million live (1.26 rural and 0.56 million urban). This population includes 317,000 agricultural labourers and 295,000 cultivators – thus water use and rainfall is of very great importance for this district, and indeed for the many like it all over India.
This water bodies map for Parbhani district is composed of 18 panels that are identical spatially – that is, centred on the district – and display the chronological progression of water accumulation or withdrawal. Each panel is a 15-day period, and the series of mapped fortnights begins on 1 January 2015.
The panels tell us that there are periods before the typical monsoon season (1 June to 30 September) when the accumulation of water in surface water bodies has been more than those 15-day periods found during the monsoon season. See in particular the first and second fortnights of March, and the first fortnight of April. [Here is a good quality image of the census map, 968KB.]
During the monsoon months, it is only the two fortnights of June in which the accumulation of water in the surface water bodies of Parbhani district can be seen. The first half of July and the second half of August in particular have been recorded as relatively dry.
This small demonstration of the value of such information, provided at no cost and placed in the public domain, is based on the programme ‘Satellite derived Information on Water Bodies Area (WBA) and Water Bodies Fraction (WBF)’ which is provided by the National Remote Sensing Centre (NRSC), Indian Space Research Organisation (ISRO), Department of Space, Government of India.
For any of our districts, such continuous monitoring is an invaluable aid to: facilitate the study of water surface dynamics in river basins and watersheds; analyse the relationships between regional rainfall scenarios and the collection and utilisation of water in major, medium reservoirs and irrigation tanks and ponds; inventory, map and administer the use of surface water area at frequent intervals, especially during the crop calendar applicable to district and agro-ecological zones. [Also posted on India Climate Portal.]
With two weeks of the June to September monsoon remaining in 2015, one of the end-of-season conclusions that the India Meteorological Department (IMD) has spoken of is that four out of ten districts in the country has had less rainfall than normal.
This overview is by itself alarming, but does not aid state governments and especially line ministries plan for coming months, particularly for agriculture and cultivation needs, water use, the mobilisation of resources for contingency measures, and to review the short- and medium-term objectives of development programmes. [See ‘A method for a post-carbon monsoon’ for a recent discussion.]
The detailed tabulation (done for 15 weeks) is meant to provide guidance of where this may be done immediately – in the next two to four weeks – and how this can be done in future. The districts are chosen on the basis of the size of their rural populations (calculated for 2015). Thus Purba Champaran in Bihar, Bhiwani in Haryana, Rewa in Madhya Pradesh and Viluppuram in Tamil Nadu are the districts in those states with the largest rural populations.
In this way, the effect of rainfall variability, from Week 1 (which ended on 3 June) to Week 15 (which ended on 9 September), in the districts with the largest rural populations can be analysed. Because a large rural population is also a large agricultural population, the overall seasonal impact on that district’s agricultural output can also be inferred.
The distribution of the districts is: six from Uttar Pradesh; five each from Andhra Pradesh, Bihar, Chhattisgarh, Gujarat, Haryana, Jharkhand, Karnataka, Maharashtra, Madhya Pradesh, Odisha, Punjab, Rajasthan, Tamil Nadu and West Bengal; four each from Assam, Jammu and Kashmir, and Kerala; three from Uttarakhand; two from Himachal Pradesh; one each from Arunachal Pradesh, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura.
Using the new 11-grade rainfall categorisation, a normal rainweek is one in which the rainfall is between +10% more and -10% less for that week. The overview for this group of 100 districts, only 11 have had five or more normal weeks of rain out of 15 weeks. In alarming contrast, there are 77 districts which have had three or fewer normal weeks of rain – that is, more than three-fourths of these most populous districts. Half the number (51 districts) have had two, one or no normal weeks of rain. And 22 of these districts have had only one or no normal weeks of rain.
From this group of 100 most populous (rural population) districts Gorakhpur in Uttar Pradesh and Nagaon in Assam have had the most deficit rainweeks, tallying 13, out of the 15 tabulated so far. There are ten districts which have had 12 deficit rainweeks out of 15 and they are (in decreasing order of rural population): Muzaffarpur (Bihar), Pune and Jalgaon (Maharashtra), Surguja (Chhattisgarh), Panch Mahals and Vadodara (Gujarat), Firozpur (Punjab), Thiruvananthapuram (Kerala), Hoshiarpur (Punjab) and Mewat (Haryana).
The uses to which we have put available climatic observations no longer suit an India which is learning to identify the impacts of climate change. Until 2002, the monsoon season was June to September, there was an assessment in May of how well (or not) the monsoon could turn out, and short-term forecasts of one to three days were available only for the major metros and occasionally a state that was in the path of a cyclone. But 2002 saw the first of the four El Niño spells that have occurred since 2000, and the effects on our Indian summer monsoon began to be felt and understood.
The India Meteorology Department (which has become an everyday abbreviation of IMD for farmers and traders alike) has added computational and analytical resources furiously over the last decade. The new research and observational depth is complemented by the efforts of a Ministry of Earth Sciences which has channelled the copious output from our weather satellites, under the Indian Space Research Organisation (ISRO), and which is interpreted by the National Remote Sensing Centre (NRSC), to serve meteorological needs.
The IMD, with 559 surface observatories, 100 Insat satellite-based data collection platforms, an ‘integrated agro-advisory service of India’ which has provided district-level forecasts since 2008, a High Performance Computing System commissioned in 2010 (whose servers run at Pune, Kolkata, Chennai, Mumbai, Guwahati, Nagpur, Ahmedabad, Bengaluru, Chandigarh, Bhubaneswar, Hyderabad and New Delhi) ploughs through an astonishing amount of numerical data every hour. Over the last four years, more ‘products’ (as the IMD system calls them) based on this data and its interpretation have been released via the internet into the public domain. These are reliable, timely (some observation series have three-hour intervals), and valuable for citizen and administrator alike.
Even so, the IMD’s framing of how its most popular measures are categorised is no longer capable of describing what rain – or the absence of rain – affects our districts. These popular measures are distributed every day, weekly and monthly in the form of ‘departures from normal’ tables, charts and maps. The rain adequacy categories are meant to guide alerts and advisories. There are four: ‘normal’ is rainfall up to +19% above a given period’s average and also down to -19% from that same average, ‘excess’ is +20% rain and more, ‘deficient’ is -20% to -59% and ‘scanty’ is -60% to -99%. These categories can mislead a great deal more than they inform, for the difference between an excess of +21% and an excess of +41% can be the difference between water enough to puddle rice fields and a river breaking its banks to ruin those fields.
In today’s concerns that have to do with the impacts of climate change, with the increasing variability of the monsoon season, and especially with the production of food crops, the IMD’s stock measurement ‘product’ is no longer viable. It ought to have been replaced at least a decade ago, for the IMD’s Hydromet Division maintains weekly data by meteorological sub-division and by district. This series of running records compares any given monsoon week’s rainfall, in a district, with the long period average (a 50-year period). Such fineness of detail must be matched by a measuring range-finder with appropriate interpretive indicators. That is why the ‘no rain’, ‘scanty’, ‘deficient’, ‘normal’ or ‘excess’ group of legacy measures must now be discarded.
In its place an indicator of eleven grades translates the numeric density of IMD’s district-level rainfall data into a much more meaningful code. Using this code we can immediately see the following from the chart ‘Gauging ten weeks of rain in the districts’:
1. That districts which have experienced weeks of ‘-81% and less’ and ‘-61% to -80%’ rain – that is, very much less rain than they should have had – form the largest set of segments in the indicator bars.
2. That districts which have experienced weeks of ‘+81% and over’ rain – that is, very much more rain than they should have had – form the next largest set of segments in the indicator bars.
3. That the indicator bars for ‘+10% to -10%’, ‘-11% to -20%’ and ‘+11% to +20%’ are, even together, considerably smaller than the segments that show degrees of excess rain and degrees of deficient rain.
Each bar corresponds to a week of district rainfall readings, and that week of readings is split into eleven grades. In this way, the tendency for administrations, citizens, the media and all those who must manage natural resources (particularly our farmers), to think in terms of an overall ‘deficit’ or an overall ‘surplus’ is nullified. Demands for water are not cumulative – they are made several times a day, and become more or less intense according to a cropping calendar, which in turn is influenced by the characteristics of a river basin and of an agro-ecological zone.
The advantages of the modified approach (which adapts the Food and Agriculture Organisation’s ‘Global Information and Early Warning System’ categorisation, designed to alert country food and agriculture administrators to impending food insecurity conditions) can be seen by comparing the single-most significant finding of the IMD’s normal method, with the finding of the new method, for the same point during the monsoon season.
By 12 August 2015 the Hydromet Division’s weekly report card found that 15% of the districts had recorded cumulative rainfall of ‘normal’ and 16% has recorded cumulative rainfall of ‘deficient’. There are similar tallies concerning rainfall distribution – by region and temporally – for the meteorological sub-divisions and for states. In contrast the new eleven-grade measure showed that in seven out of 10 weeks, the ‘+81% and over’ category was the most frequent or next-most frequent, and that likewise, the ‘-81% and less’ category was also the most frequent or next-most frequent in seven out of 10 weeks. This finding alone demonstrates the ability of the new methodology to provide early warnings of climatic trauma in districts, which state administrations can respond to in a targeted manner.
This year, the Global Information and Early Warning System (GIEWS, a project of the FAO) has brought into public domain a new rainfall and vegetation assessment indicator. The indicator takes the form of maps which describe conditions over blocks of ten days each, with each such block termed a dekad (from the Greek for ‘ten’). Thus we have visual views of divisions of thirds of a month which from a crop cultivation point of view, now lies between the weekly and fortnightly assessments regularly provided by agri-meteorological services.
In 2015, what was quickly called “out of season” rainfall was experienced in most of India during March and April. These conditions carried over into May and that is why the typical contrast between a hot and rainless May and a wet June is not seen.
The panel of maps shows the incidence of normal, below normal and above normal rain during six dekads of May and June. Greens signal above normal, yellows are normal and reds are below normal. The first dekad of May looks like what the second week of June normally does, but for the large above normal zone in the north-central Deccan. The second dekad of May has in this set had the largest number of above normal points, with more rain than usual over the southern peninsula, and over Chhattisgarh, Odisha, West Bengal. Rajasthan and Punjab.
The third dekad of May shows most of India as far below normal. This changes in the first dekad of June, with rain over the eastern coast registering much above normal for the period – Tamil Nadu, Rayalaseema, Andhra Pradesh and Odisha. During the second dekad of June, the divide north and south of the Vindhyas is visible, when northern India and the Gangetic belt continued to experience very hot days whereas over Telengana, Karnataka, Vidarbha and Madhya Maharashtra there was above normal rainfall. During the third dekad of June the picture was almost reversed as the southern states fell below their running rainfall averages.
This panel describes not rainfall but the anomalies (above and below) recorded in received rainfall. At the level of a meteorological sub-division or a river basin, the anomaly maps are a quick and reliable guide for judging the impacts of climate variability on crop phases (preparation, sowing, harvest) and on water stocks.