 Next we have Dr. Michael Kosh from USDA. So I'm going to give a different kind of talk. I didn't even have this slide show until yesterday as I watched these presentations and thought about why am I here? Antar, why am I here? Let you know where soil moisture is and where we're going with relation to groundwater. And then kind of to define some terms that would be useful because I hear a lot of people talk about models and data and more data and big data. And that's, I have different definitions than many people. So let's talk about it. National Groundwater Monitoring Network, I remember Matt gave a discussion yesterday where he said, well we compared to the network data that was available, not all of them, not everything, a subset that was good. Good data. We all say we want more data. I can get you a lot of data. I don't know if I can get you more good data. That's a piece of trouble there. As well, how much good data do I need, really, especially if my decision is binary, yes or no? Do I do this or do I do that? How much water should I put onto my field for irrigation purposes? That's a very fine tuned high accuracy. You need a very good certainty of your number. But if in the end you just make a decision, A or B, well, I just need to know that eventually my decision was right. So my uncertainty, I don't really care as long as my outcome is the good one in the end, which you only know when you're finished. So building on what some referred to today as the AQUI, the subcommittee on groundwater, there's also a sub, we're following their pattern for soil moisture. And this is what soil moisture looks like throughout the world. You notice there's a lot of green dots over the U.S. When it comes to developed worlds, the U.S. is the most heavily monitored soil moisture region in the world. Those red dots are false. Those are a long term periodic data sampling in Russia that are no longer collected. So if you just take those out, just imagine that you're only seeing the green dots, it's the U.S. And then the rest of the world are in a different category. So we're trying to zoom in on the U.S. So we're trying to make a database that would collect all of the in-situ data in the U.S. And put it all in one resource just like groundwater. You'll see that we have lots of states outlined. We have really densely monitored states like Oklahoma, New York, Georgia. One of our challenges is these are all inimpedently run state networks that have to fund themselves. And to do that, they often charge for data. We can't afford that. So negotiating contracts so that they can help inform our decisions with regards to drought estimation is really where we're heading right now. This is an initiative out of NITIS, National Integrated Drought Information System. So we have this problem that we're trying to solve and we're following groundwater's lessons. But there are many different aspects of this and I don't want to go into which sensor do we use, what's the spacing, how much data do we have, what data rate. But we're asking these questions when we're exploring them. And this is all hard numbers. But in the end, this is for very specific numerical purposes. Satellite CalVal, groundwater monitoring, surface flux estimation. These are all easy science questions. Now you say easy, this is science, this is hard. Well, but it's numbers and you can eventually figure out the numbers, right? You can follow a pattern. And when you can't follow a pattern, that's where the challenge really starts. When you talk to a human interaction with these processes, that's where it gets fun. So one of the questions is how do we get more data? How do we get good data? So this is a Quadra Observer Program out of NOAA. This is our temperature equipment sites. There's about 4,000 of these. These are citizens that are collecting data and sharing it with NOAA. And sometimes this is a month later, they're writing it down a piece of paper. It's my mom. She's got maybe a white box or she goes out. And every morning she writes down what temperature is at 6 a.m. or what time she wakes up. Or similarly, there's catch gauges measuring how much rain has come in. And they write that down. Maybe if they're lucky they have a data logger that actually stores everything and they pull out that little SD card and they put it in the mail and they mail it off to the co-op facility here in D.C. And then they collate that data to make a climate record. This is what 4,000 stations look like in the U.S. And you're all like, oh man, if I had 4,000 stations, a groundwater, what would I do? What would you do if you had 10,000? What if you had 10,000 cooperators who were sending you their water use data? Now you're not getting all the data, but you're getting a person's data maybe on their well. And you believe that that person's data could be used and they're freely giving it to you as a cooperator telling you, this is how I and my local municipality is using my water from my well. Maybe I'm competing for a best cooperator that year. That's what they do with the co-op network. So this is one of those avenues of how can we get more data but in a manageable way. Because if I were to run this out of a central location, can you imagine how many millions and billions of dollars I would need to have this properly maintained? And I'm not getting great data. I'm getting my mom reading off that rain gauge or I'm getting my mom pulling out the SD card and shipping it off to me. So it's not always highly calibrated equipment, but it is information that's helping to inform my decisions in a qualitative way sometimes. And I have to be able to accept that. We're talking about water use. There's a shift. Don't strain when I just quickly go away from maps. This is what water use is currently. This comes out of USGS. I pulled this up yesterday in Groundwater.org. And the irrigation, we all have this vision. What is irrigation? What are we using irrigation for? It's the drips over my corn field or my wheat field or in the houses that have tomatoes or onions or something like that. So irrigation is a big part of this as well as public supply. And there are definitely efficiencies that can be earned in this. Maybe it's not just what is the water available, but how can we keep the water that we bring in that we pump out? Is there a conservancy conservation efforts that could be targeted to improve this? And this is where the irrigation happens. This is current status, 2012, so seven years ago, from NAS. So this is someone asked, where's the irrigation happening? Well, here's a map of where it's happening, little blue dots. And this changes over time. It's not like everything's always in the same place. This is where it's changing over a five-year period. So you can see that it's moving out of places that are now water challenged and going to places where they aren't. There's more readily available water that's less difficult. It's less challenging legally to draw as much water as you want. This is all online and the data is available. Getting it into a resource that may be more useful would be interesting. And this is what it's using to grow. I'm posting things on here and it took me a while. I never found a reputable resource. I only had YouTube that would tell me this one. But this is all the cash crops and the irrigation by cash crop for the different states. They divide east-west. And if you were to take corn and wheat together across the U.S., there was another crop on here that is not listed. That is more than corn and wheat added. And that's turf grass, lawns, golf courses. Things like that. So there's a mysterious number out there that's not being tracked by agriculture necessarily, which is the usage of water for public use that's also probably being very much wasted. And golf courses are getting better. Farmers are getting better about using information and managing their water resources better. Where can this information come from? Well, let's get a monitor everywhere. Let's get a monitor on every well we can find. Let's develop a co-op program to have people send us their data. Or let's monitor Twitter and see how many people are going out golfing today. Or see how many people, I just mentioned to Antar, people go out and eat dinner. They take pictures of their food. And their diets change over time. And those changing diets change the food that's being produced because there's more people buying radishes. And that has a different water use. And that's an interesting and challenging avenue to research as far as water use into the future. So I'm just challenging you all to think of different ways. Imagine just brainstorm something that's completely ridiculous and say, how can I use that for science? And you'd be surprised what you can come up with. This interesting story, GPS reflectometers in the western United States Plate Boundary Observatory has these stations that just basically monitor plate movement. And this plate movement, these big towers, they might be five-meter towers, five-meter posts to tell you exactly where that plate position is in relation to the world. And how it slowly moves a centimeter or two every year. And they had this noise as a GPS satellite comes over. There's this little wiggle in the reading. They said, well, what's that noise? We don't care, we just knock it out because we're worried about when it's over, but our purpose is to know where this plate is. And they noticed that wiggle was not the scene from day to day. They found out that they're using L-band radiometry to know where that is. L-band is also used for soil moisture. And they found out that they were getting a bounce and that told them what soil moisture was in the footprint of all of their plate boundary observatory systems. So that's an interesting side of now they had hundreds of stations measuring soil moisture that wasn't even intended. So think about that as you go forward.