 Rural Water Resource Management NPTEL course. This is week 12, lecture three. In this week, we have been looking at some more data for understanding the rural water resources. And we have been using the water budget as a starting point. So from the water budget, we have been estimating different water availabilities and losses in the system so that we can capture more water and store it wisely or use the available resources more wisely without getting into losses. For that, let's look at some more descriptions. From the water balance, we understood that evapotranspiration is a big loss to the system. I'm just again redefining evapotranspiration, which was already defined. It is a combination word of evaporation and transpiration. Evaporation is from open bodies and land surfaces. For example, you have water body, lake, a pond, or a dam, and water is standing. From there, water evaporates because radiation is happening, is hitting on the water, there is some warming up, and then evaporation happens. It can also happen from open bodies as in rivers and streams while flowing, but it is much lesser compared to stagnant water because when water moves, it moves down. Then you have your land surface. On the land, there is soil moisture, there is some water pockets, and all those can evaporate, right? So that is where you see in a hot, hot day, you see the soil cracking because the water has lost taken up to evaporation and the soil cracks. So evaporation is kind of conversion from liquid state of water to vapor state and leaving behind the cooling. So the man wants to cool, so that's what happens. Same transpiration, we transpire, right? Our skin, we have holes, and when we work out or when we run, we sweat. And that sweat is transpiration where water takes up the heat and comes out of your body as sweat and you cool down. But there is also, some of it can also go to vapor stage. But most of the transpiration, which is bigger in budget and volume, happens from plants and trees where they take water, liquid water from the roots, pump it through the stem or trunk, and then pump it back to the leaves and from there, the leaves, it goes out as vapor. And this process happens during the photosynthesis. We would be reminded of the school experiments we did using a plant and a bottle, you cover it overnight and you see vapor on the side. So these are examples of transpiration. So transpiration does have to happen. You cannot control it, but you can actually understand the volume that is lost from the system from which you could see your water budget. So for example, you have a water volume in your groundwater storage. And per day, you're losing this much to ET. Let's say you have 100 cubic meters and then you're losing one cubic meter per day to transpiration or let's say ET, evapotranspiration. So it's very important to understand that you are left with only 100 days more unless you have to recharge or stop the evapotranspiration by lessening down the area of the crop or use the crop. So most of the time because this understanding is not there, what happens is the farmers would put more water on the feed, not conservatively, and then it grows, but it doesn't ripen. For example, the seeds don't come for rice, paddy, or the fruits don't come for tomato. And before that, the crop starts to die or dry. And at that point, there's no other way. You just let cattle and livestock eat the crop so that at least some energy and some feed is being created, but it's a big loss. It is still a loss, but you would see that's why some cattle are grazing in a field which is not fully grown. So that could be less lost if we know how much water we have to the rural water resource management framework. We have tanks, we have groundwater storage, we have dams, and then we have check dams. So we know how much water volume is there. And from the volume, we can siphon the water into the land and then get more out of it through transpiration, reduction, evaporation reduction, et cetera. You can also reduce it by limiting the acreage. For example, if I have 100 acres and it consumes one cubic meter per day, it's still a small number, I'm just telling. One cubic meter per day. You can say that I don't have that much water. So I'm just going to cut it by half, which means, yeah, I've put in the seeds for the one acre, but I'm just going to maintenance of half a acre, 0.5 acre, and that 0.5 acre only I'll supply water. So here, I know I have the land to get more profit, but I'm reducing my profit so that I don't get a loss. If you want the whole acreage, you might get a loss because the water won't be enough for the entire acreage. So all these are built up in the system through the evapotranspiration. Soil moisture tells you to irrigate or not, but how much to irrigate is taken from evapotranspiration. Okay, so now, as I said, these data is very important. Now we've set up why it's important, but we know that you cannot have each and every plant monitor per ET rate, whereas every plant contributes to ET, every tree contributes to ET. It is impossible to put a meter on every plant and tree, right? It's so expensive. And also the errors might be coming through different settings and stuff. So what a lot of countries use is remote sensing driven models. So they understand the physics behind evapotranspiration, which is basically you have to have water, you have to have an incoming energy which is going to heat the water and evaporate or transpire through plants. So radiation they know, they know the rainfall, the water storage, soil moisture, and then they know the characteristics of the plant, how much it can consume. And then from there, they estimate the evapotranspiration through a model. So one of the models that has been used widely is the variable infiltration capacity model or called the VIC model. And since it's driven by remote sensing data and NRAC data, it is called NRAC variable infiltration capacity model. So NRAC is under the ISRO, as I said in the soil moisture class. It is the National Remote Sensing Center and it does have mandate to provide these kind of unvisalized farmers. And the website looks like this. It is mostly with the India map when it starts, to the right hand side, it gives you the area of focus, the time when the data was taken, the average value and the other data metrics that you can download. Here, there's no sensitive data. So unlike your river data and storage, all the data is available. On the left, you have the parameters how you could select the data for your model. So now coming back is you have this evapotranspiration understood and because there is less data, for example, you'll have to put every tree or every plant and every plant has a different area or a bit different way. You don't see all the fruits of same weight, right? Similarly, all the leaves are not same area. Some leaves transpire more, some leaves transpire less. And so you have this issue between plants and other intakes. Moving on and that is why we have this remote sensing, but remote sensing also has a limitation on the pixel size. So depending on the area and the pixel size, the size of resolution of the camera in the remote sensing device or satellite, your estimation is based on that pixel size, okay? So here we are grouping the trees, the plants and water bodies together within one pixel and taking an average value because there is some characteristics which are reflected back to the satellite and those characteristics are used for estimating ET. It is kind of an estimation, but it holds good in most regions across the world and it has been very helpful for farmers to know this value because you cannot just look at a crop and then estimate ET always. Yes, there is the ET method where you have a crop coefficient method, you multiply it, et cetera, but the plant grows and there is demand based on rainfall and other characteristics, dryness, et cetera. All these are put in the VIC model. Whereas in the FAO method, it is just assuming that there is unlimited supply of water and the plant can grow freely, which is not always the case. There is a lot of constraints in growing and that is captured in these VIC models which are driven by real-time data from the satellites, near real-time, like two days, one week. With this, I will be showing the website. So I'm going to share the website. I'll take you back to the homepage and from the homepage, we go to water data and hydro materials to data. We also see agro-climatic zones. So these are zones which you see in the bottom. These are zones with similar rainfall, soil and geology type. And those types could be okay for your water assumptions, your ET assumptions, because you cannot say that across India, this is going to be the water storage. But for that, they have divided India into agro-climatic zones and each agro-climatic zone has its own type of geology, the rainfall, soil type, et cetera. So then you can club it instead of having it as big boundaries. You can at least club it in sections of agro-climatic zones. So you just click evapotranspiration. It does take time initially to load. The background is black. So to make it faster, I'm going to change the base layer into a street layer, which is much quicker. That you can do now once the highlighting is gone. I go to base layer map and I click streets. Good. So first things first we did, we just changed the base layer so that it quickly loads. And then the right-hand side, you see that automatically it has taken India as the boundary and it has taken two dates, three dates actually 28, 29, 30 and taken the average value automatically. It's still the data is populating while we talk, but I think we can continue until it populates. Okay, so it has taken three dates, 2020 to February 28th. Actually it is more than, it's a month. Sorry, it's a month date it has taken and it is averaged it out. So 0.81 is the average of almost a month because that's February 28th and then we have March 30th, right? And the average value is 0.81. So now the question is, is it okay to have an overall India average? It doesn't make sense because across India there is different rainfall, different sunlight, which is actually helping for evaporation and transpiration and different soil types that impose the water and release it for transpiration. So it won't be that useful to have an India average number, but they're just trying to show you that you can scale up or scale down depending on your interest. So moving on, we have the 0.81 as the average value and we have the statewide data. Okay, statewide what was the average for that particular period? And what do you see here is the daily evaporation average. So for the whole of India, what is the daily ET taken per date? And then you can see it comes down and then goes up slightly and comes down. Going up slightly could be your ruby season crop, whereas here it just goes down because it is drying from a high end. Now the point here to be understood is, let's first take zero. Because when you come down, you have states. So when you look at the states, is zero a correct value? How can a state have zero evapotranspiration similar to soil moisture we saw? Okay, so the understanding is, I'm just going to click on the monitor bar so that you can see it. It is very small size compared to the resolution of the satellites. So the satellite and data that goes into the VIC model cannot capture the dynamics inside the small island. And for that, it puts zero. Technically, it should have been in a value because when you put zero and when you average it, average across the states for India, the zero will pull down the value. Okay, so look at the graph here. You could see that it has been used widely for that. So other one is taking some time. Normally zeros don't have to show anything, but I just want to refresh it. Okay, so while it's refreshing, as I said, please understand that there is data for all of India and the states which are smaller in size or the unit territory which are smaller in size than the pixel will not have data. And for example, luxury will not have data. So you will have to not use this in the averaging. You can do a small exercise by yourself. You can take the India average and then the states per day is given. So you take the states total per day or average per day and average it for India with Andaman and luxury. Then you can do the same exercise without Andaman and luxury. You will find a different story. If the story is different, if the results are different, then the zero should not have been taken. Zero is not correct. Okay, if the values are the same, then zero technically means NAN values. I'm going to put the base layer back again so that we can have it load up. Okay, so I hope the luxury and Andaman Y zero is when it's correct, we understood. See luxury is also zero. So this cannot be zero, especially we know that Andaman has a lot of forest and trees transpire a lot, much more than plants. So saying that there is no transpiration or ET from that land is one. So you'll have to understand this when you write your reports and articles. So let's look at India now. So we have this data for entire India. This search box will come so don't entertain it. You can close it if you want. It just picks randomly states and districts. So for you to understand what you're looking at the data here, just go up, it will say India is the location where this data has been taken. Okay, so when you look at the data here, you see that there is some states which are blue, high ET. So now the high ET does it mean that there is a lot of water so it's evaporating and transpiring or people are pumping in water and then that pumps help to increase that transpiration. So the overall ET rate increases. Unfortunately in this region where we are, I'm showing the letter is the correct reason which is the values are not the same, they pump a lot. Okay, for example, Rajasthan, Gujarat are known to be highly using groundwater resources, Punjab, et cetera, Haryana. But they have good ET, so it means there's a lot of crop activity that goes on and for that crop activity, there has to be pumping of water into the land and that pumping of water is then taken up as evapotranspiration, okay? So this can be used to understand regions where excessive pumping, excessive cropping is going on so that we can manage the water resources better. If you look at the Ganges plain, not much water is there, use is there. So ET is still almost in the blue region, 0.5, 0.75, 0.25 region, whereas the evapotranspiration, if it is very, very high, okay? It is given as red, okay? In this region, we don't see much red color but we'll be changing the dates so that we see more of the red color. So I'm going to go back to the unit wise and if you come down here, you will see other states like Lakshadev and other regions. Now this side is clear. I'm going to go to that type of aggregate. So you want a sum, click it, last key, do you want the sum, the ET or average? Average is good because you take an average per day, whereas some would be adding up all the averages per day and most normally it looks kind of confusing if you look at some for ET because every day is just cumulatively growing, okay? Where you want to do is average and then you can multiply them by the area to get average daily water loss from the system. ET is a water loss, okay? It may have beneficial aspects. So for example, plan growth is important but at the end of the day, since it's a groundwater budget or a rural water budget, it is a loss to the system, ET is a loss. Okay, so I'm going to do average and there's only one source NRSCVIC model we can keep it. Let's do Maharashtra because there's a lot of sugarcane that grows here more than a year, it grows. Then we can say Java one and then slowly the map will zoom into Java one and then show us the data. If it doesn't, you can just pull the map to one location and it shows, yeah. So it doesn't center the map there but Java one is shown. Then what you do is you click on the data range. So now you have set the area of interest which is Java one and now we can set up the date range. And I'm going to do the monsoon, post monsoon period until the summer right now, before the summer period which is the March end, okay. Oops, okay. So we have, I'm just going to go to June, June one. So which is before the onset of monsoon until the 30th March, which is the day we are in. So this is strike top which means that we don't have the data yet. So once you click it, automatically the data starts to populate. There's no submit button as in other databases for within WRIFs. So right now the data is running from the numbers while the map is being populated, you can see the data already here. So it says India, Maharashtra, Java one. So the steps are taken as India average, Maharashtra and then Java one. So we've zoomed in to Java one district and then taken average ET from 2021, one June, okay, to March end using NRSE, VIC model, et cetera. So it gives you around 1.87 millimeters per day is always there for ET, but it is not mentioned because we are doing a daily count. We cannot say daily is equal to millimeters per day, okay? So that is where when you know that you're giving a daily data, you can remove that per day out. So here we have daily wise evapotranspiration rate. So evapotranspiration in millimeters, there's no per day, but since here it is daily, you can just take it off and you can see it grow up and then come down. So the growing up is the growing period of the crop and then also the availability of water to evaporate because when they apply water, there's evaporation. Here, this period is mostly your cariff crop where rainfall is giving water and then there's a lot of transportation happening. The rainfall also gives water to the ponds, lakes, dams. So there is a lot of evaporation happening. And then it comes down because the rainfall has come down, but the crop also is trying to slow down. It has grown well and now it's going down. And right now before the summer, there's very less evapotranspiration happening because the crops are also being harvested most of them and or the water is not enough to sustain the entire area. So only some areas are given the water for cropping. So this is how you could look at one section in detail. Here is your data per day for this GIS website. You can also download it from here. So you have a video panel, which is not activated now, but you do have other aspects in the data columns, okay? And the others are given here just to report, download, et cetera, et cetera. To make it, we'll zoom out. I'm just going to use this and then you can have this box to show where the water is coming. Like where to zoom in and zoom out. Okay, so here's how you would do evapotranspiration data. It is per date, it is per location. You cannot go smaller than a district size block is not available. So you'll have to continue with the district size, okay? So here we are. We are combining both the systems of losses, evaporation and transpiration. One data is taken, which is driven by the NRA CVIC model. The data can be taken as a daily time step, which is correct. Monthly is kind of averaging and summing into monthly, but you can do that in Excel, right? Annual loss, et cetera. But normally, because rainfall is not annual, you can take an annual rate, but per day rainfall is available. So if you look at it, per day rainfall is there, per day soil moisture, per day evapotranspiration, per day river discharge is there. All this is per day. The groundwater, yes, storage is not per day, but you can kind of do it indirectly and then measure it at a monthly scale. That's where you put the monthly budgets in, monthly or seasonal, okay? So here we have downloaded the data. We've looked at how it looks on the screen. When you download it, it's the same thing on Excel sheet and we have picked one location for this study. That's it with evapotranspiration data. I will see you in the next class on more tools for data management. Thank you.