 Welcome to this talk on drought risk and vulnerability assessment, a global perspective. This talk is part of the MOOC on GIS applications and agriculture. My name is Balaji. I work for the Commonwealth of Learning. My co-author in this talk is Dr. Nagarajan, who is the lead faculty in this course. Another co-author is Dr. Sridhar, based in India. At the end of this talk, you'd have learned why context is important in risk and vulnerability assessment. Why micro-level assessment is important for mitigation. Micro-level assessment is something we spoke about in another lecture, and that is very important for mitigation. Importance of context must be known to everyone. We all by now understand what it is to assess vulnerability, and we learned in the earlier part of the course about adaptive capacity. Adaptive capacity is a very important thing. Adaptive capacity is essentially local capacity to adapt to drought. It is estimated using local parameters. For example, if farmers are able to follow advanced water conservation practices, then the impact of drought would be much less on them. That is their adaptive capacity, and it has a role in final assessment of vulnerability. And that's why contextual information is very important in planning drought mitigation. Let us look at vulnerability assessment from a very large-scale overview. Here is an overview of an entire continent presented in terms of vulnerability to water shortages. Water availability is estimated in per capita availability, and different parameters are set up to measure vulnerability all the way to scarcity. What you see from this map is that almost all countries in Africa are vulnerable to water shortages, and some almost one-third are facing scarcity, acute shortages of water in fact. But then this overview takes place at the level of a whole continent. Here is another view of vulnerability to drought. Again, it's on a continent scale. You find that quite a good part of the continent is highly prone to failed rainfall, failed season rather. And whenever such failures occur, serious food shortages can set in and cause immense stress to large chunks of human and animal populations. And this is a known phenomenon, and this is very clearly visible from a continental-scale overview. But to plan actual action at ground level by national and local agencies, we need another view, a higher-resolution view. Let's take an example from here. This example comes from the United States, from Colorado. If you look at this map displayed here, it displays results of Palmer index severity over a period of 100 years. And when you look at Colorado, marked here with an arrow, you find that it is one of the worst affected states. And in fact, it looks like it has practically no region at all, which is not severely drought prone. And we need to hover to plan action in the state. Authorities there looked at it from a higher resolution. For example, look at this map, which shows county borders, and it also shows potential population growth in the state. And a similar map is available on the same scale to convey to agricultural vulnerability to drought. And what you notice here is that agricultural vulnerability is not uniform. It's not uniformly severe. That is a view you got when you looked at it from a country-level overview. And now when you go down to this level of overview, you find that there are, in fact, spots that are not affected by drought very much at all. So there is a reasonable variation here. And this is visible only when we went down to a higher resolution or to a different level, not from the global or country level. We'll look at one more example. You looked at this map of drought vulnerability at a micro scale for a cluster of about 300 villages in South Central India. It was presented in one of the earlier lectures. When you look at drought vulnerability from here, what you would estimate is that just over half the villages here, almost 150 villages, are reasonably and highly drought prone. That's the result that you get by looking at this assessment. Now when you combine this with adaptive capacity, which was also presented in an earlier lecture, and that lecture also discussed how adaptive capacity is computed and calculated, when you combine adaptive capacity, which is presented in this map, with vulnerability, which is presented in an earlier map here, you would conclude that more than half the villages are less vulnerable to drought, which is very different from the conclusion you arrived at. That's because you are able to combine contextual information with information available only from overviews. GIS can help mitigation at micro level. Mitigation is action planned on the basis of contextual information. When you combine GIS tools, you can offer more precise crop planning advisory. You can give far more targeted advice on local water rights management, and you can offer advice on very, very advanced conservation and very focused conservation practices, both for water as well as for forest resources management. And a number of these possibilities can be listed. In summary, global scale risk and vulnerability assessment is important. It gives very good overviews and can help national and international agencies prepare. Whereas information on context is necessary to decide on mitigation steps. To plan very effective and very, very focused mitigation steps, micro level assessment is necessary. Except for what you have seen in this course, there is not much progress in this area. GIS tools can make a very big contribution here. Here is where many of you who are from agricultural science background, your students or faculty, you would be able to build enough capacity among key actors in the local areas in helping formulate micro level assessment. That would be a big contribution this community can make. While closing, I would like to mention that this lecture, this particular talk, and the slides are available under a Creative Commons license. Please cite and redistribute as much as you find it necessary. Some screenshots have copyright ownership, which are mentioned in the respective URLs. Thank you.