Weatherproofing Farmers Through Climate Services

Unpredictable weather variations and extreme events are now being seen as signs of the coming of climate change. This variability in climate, as also highlighted by the Intergovernmental Panel on Climate Change (IPCC), poses risks for food security. This calls for evaluation of various adaptation and mitigation options that can secure farmers’ livelihoods and provide food for all.

Our farmers’ presumptive analysis of the weather through traditional knowledge and age-old experience has long held them and their crops in good stead. Today, climate information and advisory services sent to farmers, on their mobile phones, are helping make agriculture more resilient towards the impacts of a varying climate.

The 2 Ts boost – technology and telecom

In India, these services have seen a giant leap of a change in last 10 years. The traditional “Farmers’ Weather Bulletin” and TV broadcasts including All India Radio have now evolved into sophisticated climate products and services delivered using ‘techno-social’ tools – smart phones and mobile apps.

The years 2006-07 saw a surge in agro-met services with companies like Nokia Life tools and Reuters Market Light (RML) entering the Indian market, which for a long time was served only by the Indian Meteorological Department (IMD). Today, weather information is also accompanied with market-related information, helping farmers get fair bargains for their produce.

The growth in number of farmer subscribers for climate services has been overwhelming. Over 50 lakh farmers have been reached in the state of Maharashtra only, while the number across India is in excess of 1.5 crore.

Technologies for effective dissemination and outreach are kicking in and are being implemented at scale by IMD’s Agro Meteorology Programme, GKMS (Grameen Krishi Mausam Seva). Innovations at local levels are also being experimented with. For e.g. Watershed Organisation Trust’s (WOTR) Agro-Meteorology program uses Automated Weather Systems (AWS) to improve the effectiveness and accuracy of local weather information. The farmers are informed about their local weather conditions almost real time through AWS, allowing them take more weather informed decisions.

Scaling and Downscaling

Scaling up of such experiments is a must but it poses several challenges. Since India has diverse topography and climatic conditions, the extent of village-level, farmer -specific data available is very limited. Also, there are limitations for downscaling district level or block level weather forecasts right up to the village-level.

What makes scaling further complicated are the institutional challenges that arise due to the amount of coordination required for generating and delivering advisories. The climate services sector in India is an example of a consortium of knowledge networks made up of private, public and not-for-profit institutions, including universities. This means that every advisory service requires collaboration between at least 3-4 different institutions!

Bottom up Responses

Farmers at their end are also using technology to battle the forces of weather variations. Using their smart phones they have formed crop-specific Whatsapp groups, which act as hyper-local communication platforms for and by farmers. This is an example of a bottom-up process of development and implementation of adaptation measures. Farmers can self-advise and readily share information among peers, such as response to pest attacks, differences in market prices etc.

TERI has been studying climate services system in India through its Indo-Norwegian Research Project on Governance of Climate Services. The project is a three-year study that analyses conditions for effective governance of climate services in India. It compares 4 Indian agro-meteorological service systems, both public and private to study how they are governed and if they provide rural farmers with tailored and participatory services in Maharashtra.

The project’s findings would be up for discussion at this year’s World Sustainable Development Summit from 15th to 17th February 2018. Do join us!

For more information visit –


Challenge of Policy Making for Climate Change Adaptation

Farmers in India and across the world are witnessing new variations in weather and seasonal changes. The challenge to take decisions under these variations gets compounded because often there is no precedent to it. What decisions work best can be known through experimentation and mostly in hindsight. This makes adaptation to climate change a complex process. The cause-effect conundrum, i.e. which solution gives what result is almost impossible to predict with certainty. Thus, human decision making under such unforeseen situations needs to be aided by additional information or decision support systems. Climate Services, the delivery of weather based agriculture advisories using ICT, help aid farmer’s decision making process by providing timely weather forecasts and corresponding advisories on agricultural practices.

The information farmers receive on climate services provides them with an option of incorporating it into their agriculture decision making. But it is almost impossible to measure with certainty how much of this information do they incorporate, in what form and when. This makes impact evaluation of adaptation solutions, like climate services, a very challenging exercise. At times even the farmers are unable to clearly demarcate the important variables they use for their decision making process. This is so because in order to cope with weather variations there are many possible actions and solutions to be experimented with. But the most effective solutions may not be known to them at the early stages and thus their decision making keeps evolving as they experiment with a set of solutions. Through this process of iterative decision making they learn to adapt to weather variations. This makes adaptation a highly localized and continuous process with no clear traces of solution impact pathways. But a set of good practices evolve over time.

Challenges to measure or generate evidence of adaptation further hinder the uptake and popularity of good practices. There is also a theoretical difficulty in establishing units for measuring adaptation and establish monitoring systems for its evaluation. This makes communicating adaptation through evidence a very difficult task. It also challenges the imagination of policy makers who mostly rely on numbers for estimating impacts. For example, the climate mitigation negotiations use the 2°C limit of temperature rise as the reference for determining how much emissions need to be reduced to achieve this climate goal. But in case of adaptation there is a dearth of quantifiable numbers which could guide the policy planning process. Thus, policy making for adaptation requires a shift of two kinds

1)   Moving away from relying only on numbers, and

2)   Decentralization of policy making to account for localized adaptation processes.

This shift further brings up two challenges

1)   How to measure what is intangible or un-measured, and

2)   At what scale should the policy making process be localized.

Unless research on climate change adaptation focuses to find answer to these two challenges, policy making for adaptation to climate change would remain a very challenging task.

Note: This article was first posted on my linkedin on October 3, 2016 for TERI’s World Sustainable Development Summit 2016. Link:

My Journey of Systems Thinking – Part IV

Many people have been asking me how to use systems thinking, how to make models, what are the steps that I follow, how does the development process unfold? To be honest, there is not set template that one can follow and reach the end. As John Sterman says, “It is inherently a creative process.” But there are steps which can guide the model building process. Sterman in his book, Business Dynamics, mentions these steps in detail and I recommend everyone interested to go through them. I myself has used them to write proposals on research using systems thinking and modeling. But over time I realized that applying them required some degree of adaptation of these steps. Since in India the degree of complexity is relatively more as compared to other developed countries where data is available and reliable under most circumstances, we need to be very creative while trying to understand complex systems using systems thinking. To give an example, while working in rural areas one realizes how poor is the data availability even for critical resources such as ground water. I remember once on a water wind mill assessment trip we were struggling to identify water hand pumps which are dry and which are still pumping water, what is their depth, when they were installed etc. People in villages had some vague idea about their date or year of installation, depth etc. But all that was not good enough for us to take a call on whether to implement a water windmill or not. The only parameters for which data was available and reliable (to an extent) was the meteorological conditions i.e. the wind speed, direction, precipitation etc. That too because WOTR had Automated Weather Stations installed there. So this goes to show that while working in India data availability and reliability is a big constraint. The second constraint is the information and knowledge available to understand the local dynamics. Another example being, people in villages find it very difficult to estimate their household numbers be it water, finance, energy or livestock productivity. For eg. their income and expenses figures rarely tally. Giving them the benefit of doubt that they take short term loans, receive some money through family, friends etc. even then all these numbers would often not add up. I have had a first hand experience on this issue too. So modeling social, ecological and economic systems in informal setting in India is a hard, hard work. Lot of assumptions and (educated) guesstimates have to be done to complete any sort of modeling process.

All this relates to how one then applies systems thinking and modeling in dynamically complex situations and systems in India? Does John’s modeling process and steps help our cause? In my opinion they do, albeit to a limited extent. One needs to creatively adapt them and use his/her sensing to move ahead. In my experience serendipity also plays an important role. Almost every time I have been badly stuck in some of the most challenging modeling projects and then I have found a way out either by someone willfully joining the work or through some support. All of it being not part of original plan.

So after doing some modeling work in very un-ordered settings I have adapted John’s modeling steps and have penned them down.  The pre requirements before these steps are that the problem has been identified, modelers have familiarized themselves with it and proper scoping exercise has been done with the end user and experts.  The modeling steps then are:

  1. Define purpose of the model and read about the issue or system of interest
  2. List down sectors, sub systems and determine model boundary
  3. Create Dynamic Hypothesis (DH)
  4. Develop questions based on DH
  5. Show DH to community (end user) and experts
  6. Review the questions and DH after step 5
  7. Collect information and data using questions developed in step 6
  8. Develop initial versions of simulation model
  9. Review DH based on simulation model
  10. Show revised DH to community (end users) and experts
  11. Show initial simulation results to community (end users) and experts
  12. (Incorporate suggestions) Revise the model, its boundaries and develop questions to fill in information and data gaps
  13. Collect data and information to fill the gaps
  14. Develop progressive versions of model (eg. v2, 3…… v17….  and repeat step 13
  15. Perform model calibration, sensitivity runs, extreme conditions test and finalize the model (sometimes back-casting also helps in model evaluation)
  16. Share the results with community for mobilization and aiding action
  17. Make model readable and fit for publication and dissemination
  18. Get the model reviewed by an expert and incorporate suggestions
  19. Publish the model and results
  20. Plan for next phase and how to go deeper into the issue to initiate change process, then start from Step 12 or any other appropriate step as suited

The most important thing to remember is to celebrate learning at each step and document the learning process. You would often be surprised that the learning process is an equally important and influential outcome of the modeling process as much as the end simulation results are.

My Journey of Systems Thinking – Part III

Where did I learn systems thinking? The answer is simple but confusing, even to me. Technically, I learnt it at my post grad college, Sadhana Center for Management and Leadership Development, Pune. This was a subject in our curriculum. We studied it for two years. First year we had systems thinking and then an elective on system dynamics modeling. Sushil Bajpai and Rajinder Raina were our mentors, professors, friends and fellow systems thinkers. They had this impossible task of teaching systems thinking to 160 idiots. When I reflect now I think my performance in class and particularly in exams was below par. That is according to my standards and interpretation. But my mark-sheet tells a different story. May be my professors were liberal, may be they saw something more than what exam results or written answers told them. They had an insight and a foresight on how to identify, nurture interest and develop potential systems thinkers.

But I did not really learn systems thinking alone in my college. I was introduced to it there, I read and heard it there, I also practiced it, applying to some of our corporate strategy cases. I had used it to study Dell company’s strategy on how their business model was different from others. Organised a systems thinking seminar calling the commissioner of Pune plus more audience. Sushil and Rajinder got Shiela Damodaran to Pune to conduct that seminar and we did more stuff.  Linking Vipassana to Systems Thinking, the business model of Dabbawalas to principles of systems thinking. All that was very good but I was not really a systems thinking practitioner back then.

When I joined WOTR, Sept 2009, I worked with Sushil Bajpai and a bunch of brilliant folks there working on really complex social and ecological issues. The project was on climate change adaptation. It had all the elements of real world complexity that one can imagine. It also had institutional complexity which was to dealt with bringing in elements of learning organization pedagogy (more on this later). The project was a pioneering effort in the field of climate change adaptation in India. WOTR had a credible name and evidence in field which made them a potent force for community based natural resource management. But this project was a different animal and it brought in new animals at WOTR. I was one of them.

I learnt systems thinking outside my class room. A lot was learnt by observation and not implementation. For around 2 years, I was a fence watcher. Not committing myself into any one activity of the project but learning and observing about what is going on everywhere and what I think could happen. All these years I had the luxury to learn, read, observe, unlearn, relearn. This opportunity was rare, perhaps once in a lifetime. Did I made most of it? Only time will tell. But I had a ball. We use to have intense practical and philosophical discussions on what is true adaptation, why humans fail to understand how their actions are killing themselves, why peak oil would redesign our lives, would peak water hit us first or peak oil or are we living in an age of peak everything? Lot of systems thinking was used in our discussion. I was a mere spect-actor and Sushil did most of the thinking, talking and doing. It was like we had a high quality TED talk every week, coming from our field experiences and books that we use to read and the project ambitions. We use to be very critical of ourselves, our actions and the project itself. Questioning the sustainability of the institution, the project, ourselves and should we even live in cities anymore? Should we reverse migrate? Those were crazy discussions, beyond office space, at our homes, common meeting places, over beer and biryani.

I learnt systems thinking by looking and observing reality and then linking it with the theory of systems thinking. By reading books, not only on systems thinking but on multiple disciplines. I learnt systems thinking at WOTR, by listening to Sushil, by working on field with the team, by talking to community, friends, remembering the theories of books while seeing real world dynamics unfolding on field. I learnt it by practice but not only through implementation. I saw why and how implementation often is weak in rural areas and how, while I was leading some verticals of the projects, I was still making the same mistakes. I understood the power of the system we are in and how it influences our behavior. How we speak one thing, but do another and then still are unaware.

I think I did multiple post grads while at WOTR from 2009 till 2014. Un-parallel to any other experience. I learnt systems thinking through that journey and the journey still continues bringing in more surprises, twists and turns.

One happening and happy journey, I must say.

… to be contd. See part IV

My Journey of Systems Thinking – Part II

For many years people have asked me how is systems thinking different and what is so unique about it. What is the advantage of using it over other methods and techniques? To be honest, I did not had a short and convincing answer back then. It would take me 15 mins of talking to convey what I wanted to say and that too was incomplete. This of course meant that people did not get a clean and cogent answer to their question. I would also substantiate in the end by saying please read on systems thinking and then verbally mention couple of books. With more people asking me this question over time my responses improved incrementally. But they were still not good enough. Probably what was lacking in me was a thorough, continuous application of systems thinking and modeling on real world situations. Every now and then I use to use systems thinking tools to understand peak oil impacts, localisation benefits, resilience to climate change etc. but then the result was my improved understanding of these issues which would help me in my research and community work. This was particularly helpful for the climate change adaptation project that I was part of at WOTR. But how do I communicate this to others? What evidence exists?

Three years back I got an opportunity to apply systems thinking and modeling for urbanization project at TERI. Kabir and I spearheaded a team of young researchers and developed a city model representing urban carrying capacity and people’s quality of life. We did lot of systems thinking training and use of causal loop diagrams to draw how we understood the city system. A two day training was conducted on system dynamics modeling. The project was successfully delivered and generated much interest among its readers. Then we embarked on economics of grassland degradation project. This was an almost impossible project. We had the task of modeling a grassland ecosystem, Banni, in Kachch. There were so many unkowns in the system that at one point we thought of giving up. But then we worked hard and got very good support from our colleagues at TERI and research support by (institutions) Sahjeevan and ATREE. That project was a leap for us to understand the potential of applying systems thinking and modeling to solve real world problems.

After doing further projects on application of systems thinking and then teaching it to over 1000 students, now I feel I have a better answer to the question, ” What is the advantage of applying systems thinking?”. What I am about to write is purely my interpretation of the benefits I see and is not coming out of a text book. So one must be critical.

Let me quote the great Albert Einstein here, “We cannot solve our problems with the same thinking we used when we created them.” I paraphrase this, “Today’s problems come from yesterday’s solutions and today’s solutions will create tomorrow’s problems.” This speaks volumes about our journey in life and how we adapt and live. If this is true then I think systems thinking and modeling has a big role to play.

I think the real benefit of applying systems thinking to real world problems and even for theory development is that, ” It could help us take decisions and design policies, rules which would reduce the recurrence and severity of the problem we are trying to solve”. This I think is the biggest (potential) benefit of applying systems thinking and modeling. This could be achieved through multiple pathways. It is not necessary that one needs to implement the solutions and only then the results would come. Even the improvement in our understanding about the complexity of real world is instrumental in improving the policy design and decision rules which we use to run our families, companies, society and nations.

The only rider I would attach is that one needs to be very very honest while applying systems thinking and modeling because unlike other disciplines (statistics, math etc.) this discipline depends a lot more on who is modeling and whose mental models really matter. The reliance on the honesty and capability of the researcher and actor is of paramount importance if the potential benefit of applying systems thinking and modeling is to be achieved, as I describe it.

I think my biggest strength, that I discovered, was not my ability to do advance math or expertise in software or field research. It was my ability to stay put, pursue systems thinking and work through my limitations over time. There were a bunch of my classmates and colleagues who, in my opinion, were far better at systems thinking than me. But today I am the only one using it for a living. And I am no scholar or genius like them.

So systems thinking and modeling is for people like us, who are ready to learn and build their capacities. Why? Because I think it is very useful. How?  Because, ” It could help us take decisions and design policies, rules which would reduce the recurrence and severity of the problem we are trying to solve”

… to be contd. See part III

My Journey of Systems Thinking – Part I

I write this post today after an engaging day with students at ISDM on systems thinking and sustainability. The classes start at 9 am and continue till 5 pm. Today was the fourth day and it seems like we have come a long way, not only in terms of students learning systems thinking but the quality of engagement has reached a new level.

The striking point came when students asked me to explain my day at work, on how do I use systems thinking there and the process of its application. The question was striking because it made me feel like the students wanted to know how I have managed to reach this stage where I am doing professional projects using systems thinking and system dynamics. More so because for them the subject looked too difficult to apply in real world for finding solutions. They couldn’t really imagine on how diving deep into complexity of real world problems could yield fruitful results and generate solutions in today’s world. The question was also striking because it gave me a sense of honor because here were a bunch of 65 students interested to learn from my experience.

I feel motivated now to write this post and more on this subject to explain how I started my journey of becoming a systems thinker and convert my skills into professional occupation.

It was in July 2007 when I first learned about systems thinking. Mr. Sushil Bajpai and Mr. Rajinder Raina took our first class on systems thinking at Sadhana Center for Management and Leadership Development (SCMLD), Pune. The first presentation showed to us was of images from zoom book,  a view of life going from microscopic to telescopic. That first presentation made an impression on me. What a fantastic way it was to show how things are interconnected and that we live in a world of systems and sub systems.

The next deck of slides explained us the definition of A System. How do we know what is a system and what is not a system. This was a tricky question. Reads easy but when one thinks about it, it is not so easy to define it well. After some deliberation out came the answer, “A System is made up of parts which are interrelated, interconnected, interdependent having a purpose”. We all went berserk in identifying systems all around us. Since then the subject never really left me. I went on diving deep into it. In the next classes we were introduced to Mental Models. That class in particular was fascinating. It introduced us to the fact that how all of us interpret reality, build images in our mind and use them to take decisions. More importantly that these mental models are flawed, because we use rationality to simplify reality which implies that there are lot of assumptions there which make our mental models inadequate and incomplete. This was quite a revelation for me. I came from a financial markets experience and there the whole game was who has got it right and who knows reality the best in order to predict it and mint money. The best analysts would draw large pay based on how well their models performed in relation with reality. This thought was so well rooted in me that learning about mental models was actually life changing.

The initial few classes had cemented a space for systems thinking in my life. Interestingly, one night in my hostel room, Amey Phadke and I were chatting just before calling it a day. Lying on our beds, with lights put off, we were asking each other where do we see ourselves after five years from now. I cannot remember what Amey replied, but I do remember clearly what I had said, because I said what I really deeply believed. I said, “It looks like I will join stock markets after college, but if you really ask me – deep within I feel that I am made for systems thinking and that’s where I would land up. Honestly speaking I think I would be doing systems thinking”. I did join stock markets after my post grad building equity valuation models for oil and gas companies, doing commodity research and interacting with institutional investors. But within six months I switched careers and moved on to work with Mr. Sushil Bajpai at WOTR and there began my journey of systems thinking and system dynamics, on job. And here I am today writing a post on it after 10 years of having that conversation with Amey at my hostel room.

The journey so far has been full of turning points and life changing moments, some planned, most unplanned.

….. to be contd. See Part II

Systems Thinking Definition

I have struggled to put what is systems thinking into a succinct definition for a long time. I have also struggled to find a definition of systems thinking which makes most sense to me and captures the gist of systems thinking through that definition. My struggle began 10 years back, when systems thinking was first introduced in my post grad. Since then I have been giving long answers (and different versions every-time) to anyone who asks or writes to me “What is systems thinking?”.

Somewhere between 2015 and 2016 I decided to make a glossary of systems vocabulary, more for my personal use and then again came the question of what is systems thinking. So I decided to write down a definition which made most sense to me. The first version of it I shared with Gene Bellinger and after a brief exchange of emails with him I zeroed down on a definition that was acceptable to me.

Two days back I was taking a day long workshop cum lecture at Indian School of Development Management at Noida in NCR (National Capital Region of Delhi). After going through the slides explaining what is a system, what is not a system, how to identify systems, examples of systems, types of systems I came to the slide having my definition of systems thinking. Mr. Arun Maira, former member of Planning Commission of India, was there in the class, with whom I was doing team teaching. He expressed that it was one of the most refined definitions of systems thinking that he had seen or read. This motivated me and today I decided that I should publish the definition (via informal means like this for now) for gaining more feedback and to improve it further. Thus, I am posting the definition here for readers to evaluate it and provide feedback on how much sense does it make and how well it captures the essence of systems thinking. All views are welcome.

Systems Thinking Definition:

Systems thinking is the process of understanding relationships between variables within a system and between different systems and how they influence each other’s behavior over time.

The above definition is typed by me but I think many people, entities and their work has contributed to my learning which has lead me to this definition. I may not be able to remember them all and write down here, but let me try.

Sushil Bajpai, Rajinder Raina, MS Pillai, Rajesh Rajak, John Sterman, Donella Meadows, Khalid Saeed, Jay Forrester, Andrew Ford, Kenneth Boulding, Gene Bellinger, Arun Maira, Kabir Sharma, Pradnya Mathur, Sadhana Center for Management and Leadership Development (SCMLD), Tata Institute of Social Science (TISS), Watershed Organisation Trust (WOTR), The Energy and Resources Institute (TERI), Sustainability Dynamics (my own unregistered consultancy), International System Dynamics Society, System Dynamics Society of India (IIT Kharagpur) and All my students at TISS and SCMLD.

Drawdown, A Book on Reversing Climate Change

Dear Friends,

I am very pleased to share with you the release of book Drawdown by
Paul Hawken. The book analyses and simulates climate impacts (reduction in atmospheric CO2 eq ppm) of 100 climate solutions which if implemented at scale could reverse global warming. I was fortunate to be part of the project and did a fellowship to contribute to two chapters 1) Reducing Food Waste (#3 in climate impact ranking) and 2) Family Planning (#6/7 in climate impact ranking). It was a wonderful experience to be part of the global fellowship and do the number crunching exercises with technical writing.


The book is a first of its kind and a must read for everyone who is interested in sustainability, climate change, business, environment and even those who are climate skeptics. The solutions go beyond just climate change and offers future scenarios which could be useful for development of green businesses. The scope and potential is immense and the time to act is “Now”.

You can know more about the book, its solutions and buy a copy of it from

Please circulate it widely and we welcome your questions, thoughts and critics on the work.

Thank you,

Why we need Models, and why it’s hard to change them.

Re-blogging a post from make10louder which I found interesting and relevant.

Make 10 Louder

  •  It’s 460BC. Your job is a map maker, and your maps show the world to be flat. You’ve a lockup garage of flat earth maps to sell. But you also like astronomy, and understanding the planets.
    • Is a model of a flat earth of any use? Is it good?  It was good enough for me to get to work, and to drive a cart to London.
    • But it’s not good enough for astronomy, you need another model.
  • You hear of the model of the earth as a sphere. Hmm, this fits simple astronomy, but does it make your lockup full of flat earth maps worthless? Which model do you believe? How hard is it to change your mind to a new more complicated model?
    • Is the model good enough? It’s great when thinking on a global scale – like where is Australia relative to where you are.
    • But maybe…

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