[MUSIC] Welcome, I will be talking to you today about regional water resources management. Why is this an interesting topic? Well, many people think that freshwater is the world's most critical natural resource. Actually, much more critical than, for instance, oil. The World Economic Forum every year issues a Global Risks Report. And in the 2015 edition of that Global Risk Report, Water Crises are actually listed as the top risk as terms of impact. Now, when we talk about water crisis, there's always three key issues that are coming up and that is flooding, water scarcity and loss of ecosystem services. Let's underpin that with a few global numbers. On this chart, you see that global production of food and global production of power has actually outpaced global population growth over the last 50 years or so. On this chart, you see that the increase in food production has actually been possible, been made possible by an increase in irrigated area, while the total agricultural area has stayed constant. So this means that the success story of being able to feed an ever growing world population is largely due to an increase in irrigated area and increase in irrigation agriculture. However, this has come at a price. If you look here you can see that the global area of natural wetlands has essentially collapsed, and we are now down to about 15% of the original size of the global wetlands. So, water crises are very often related to these issues, power, agriculture, and ecosystem services. What can we do as scientists to help decision makers and managers? I believe that two key components of scientific decision support are prediction and optimization. When you talk about prediction in the water resources context, it's about forecasting. So, predicting the future over the next few days, few hours, few months. Or scenario evaluation where we want to understand the consequences of planned actions a priori. Optimization, also has two aspects when we talk about water resources management. On the one hand it's about operational optimization. That is scheduling for instance reservoir releases, making best use of the available design, the available infrastructure, the available water resources. And on the other hand, it's planning problems which basically aim at finding the best solution, finding the best policy, finding the best set of infrastructure to manage water resources. There's consensus today that best forecasting skill is actually achieved when you combine simulation models with observations. However, our in-situ infrastructure for observing water resources has been in decline for at least the past 20 years. This is shown here with the number of operational river discharge gauges worldwide. At the same time, new observational infrastructure has become available based on satellite and airborne platforms. Most of the water bound components these days can be monitored remotely. Things like precipitation, actual evapotranspiration, river discharge and so on. And that includes also components that have been essentially unmeasurable with traditional technology, such as storage change and regional scales. Let me take you through this example of satellite radar altimetry. Satellite radar altimetry is a spaceborne technique that basically measures the altimetric height of water levels in rivers and lakes. These altimeters are mounted on satellites, and if the satellite is on a repeat orbit, then basically you get time series of river water level at the intersection points between the ground track of the satellite orbit and the river. So you basically get time series of river water level and they can complement existing in-situ discharge records. New missions have changed the orbit and are now on shifting, drifting orbits, like for instance CryoSat 2, and thereby having much, much higher spatial resolution. And as you can see on this chart, you can actually track the river water level all along the river course and get longitudinal water level profiles on big river systems. When it comes to ground water, and predicting ground water, then a subsurface heterogeneity is actually the key challenge I believe. Let's take this example of the Yucatan Peninsula in Mexico. Here you see the Yucatán Peninsula from above. So it looks fairly unexciting, just the homogenous land surface, a bush. However, if you look into the subsurface, then you see these huge long range river, underground river systems which can span over hundreds of kilometers. I think it's clear that if you're trying to predict ground water flow, contaminate transport, risks to ground water resources and you don't know about the location and the orientation of those underground river systems. Then you're really having an almost impossible job. However, new technology in this case, airborne electromagnetic mapping is actually quite efficient in terms of picking up the location of those underground river systems, and can really make a critical contribution to groundwater resources management on the Yucatan Peninsula. Water is always a multi-purpose commodity, you could say. It needs to serve many sectors. It needs to serve the power sector, it needs to serve the agricultural sector. It is essential for maintaining national ecosystem services. So when you manage water you're in this multi-objective inter-temporal framework. You also need to Balance, and benefits today, versus benefits in the future. All right, so there's this intertemporal issue also. We have worked with hydroeconomic optimization techniques, Stochastics, dynamic optimization techniques, which try to balance all these requirements, all these demands for water in objective Way based on an economic least cost criterion. You quantify costs in the power sector, you quantify costs in the agricultural sector. You balance them, you make the balance future versus present, and you come up with these objective, rational and quantitative decision rules for water resources management. To sum up and conclude a DTU environment, we develop science based decision support tools for regional water resources management. When we do that we focus on two key issues. And that is prediction and optimization. The use of new technology satellite and airborne remote sensoring techniques to increase the reliability and the sharpness of the predictions we deliver to water managers. And we perform hydroeconomic optimization to obtain rational objective Economics based decision rules for complex water resources management problems, such as, for instance, the Water-Energy-Food nexus. Thank you. [MUSIC]
