 Hello and welcome to this section of tutorial 12 entitled, Hydrologic Modeling Using Microwave Remote Sensing. So Earth's global hydrologic cycle has benefited tremendously from advances in active and passive microwave sensors. And by now we know that they provide key information about parameters that are relevant in hydrology which are used in hydrological simulations such as soil moisture and the snow state. So in this section let us try to understand about soil, water and assessment tool that is SWAT. So this is an open source software supported by the USDA Agricultural Research Service and Texas A&M AgriLife Research which is part of Texas A&M University System. And over the past two decades or so this tool that is the SWAT model has been widely used across globe for various applications and of course with time there has been numerous additions to the individual components of the underlying codes. And shown here is the current version of SWAT+, which is like a revised version of the model and the utility of this tool is to simulate the quality and quantity of surface and groundwater. Now it is to be noted that SWAT allows various subunits to be defined within a watershed such as a subbasins, unlimited number of hydrological response units or HRUs, pond, wetland, point sources etc. So let us begin with the installation of SWAT+. So the installation requires QGIS and SWAT+, installer. So QSFAT+, is a plugin for QGIS and shown here is the installation process for Windows users. So if you are a Linux user, your Linux distribution may have QGIS package as part of its standard collection, otherwise one can visit the QGIS download page and follow the instructions for downloading. So I am going to go for Windows 64 bit version and again a similar process needs to be followed for users of macOS. More details are available if you access this particular website as shown here. It has a lot of documentation available for running and using SWAT+. So in my system, already QGIS is installed, so I do not need to install it again. As I mentioned earlier, please install QGIS before installing SWAT and the details about QSWAT and its various documentations are made available in this website for easy understanding. So once the download gets completed, let us click on the SWAT+, tools installer exe file which will take me through a list of processes for extracting the files into the C drive and then the SWAT+, editor will be set up. And I can check in the system and make out how the interface looks like. So what I am doing here is a hydrological response unit HRU that is part of the sample files given for demonstration purposes from the website we have just seen. This is shown just to give us an understanding that land area within a sub basin can be divided into HRUs. As I mentioned it is hydrological response units and they are nothing but part or portion of a sub basin which is having unique land use attributes. So HRUs were incorporated into SWAT as part of the hydrological unit model for the United States project and they simplify the run because they lump together all the similar land use areas as a single response unit. So for this tutorial I shall be using the sample files that are made available in the robbit underscore demo folder. Now this has been set up in the Q SWAT+, which means if I go and directly click on the particular file, it will open up the QGI's interface. Now please remember that you can also access the Q SWAT+, manual and set up your own project. The example data provided in the website in which we are now going to use it includes all the inputs required for SWAT+, and now we can try and explore what is available to us. There is an option known as manage the plugins wherein you can see Q SWAT and Q SWAT+, is checked. You can see the icon appearing here and you see the details represented here. If you have installed the SWAT+, you will see the icon here like this and we can explore the different data that is available for HRUs, hillshade, floodplain. You can see the different layers that are made available as part of the sample demonstration file. Details about soil, about slope, you can even check or uncheck these to see what difference it makes to the diagram. So now if you have installed SWAT+, as I mentioned earlier you will see a small icon here. So the moment you click on this icon, this is the interface that is going to open up interface of Q SWAT+, wherein you can see that the first two processes are marked as done that is process 1, delineate watershed and process 2 that is create HRUs. So they are shown as completed which means I can go ahead and click on the third step that is it will open up an editor project from Q SWAT+. So I am going to now import the GIS data into SWAT+, this is the project summary and there are different icons towards the left side which you can click and explore. So Robbit demo is the sample file that we are using. The details about channels, about basin, land use management all are made available in the left part, the parameters you can explore the details made available. What we have to do is we have to edit the inputs. For that let us try to decide about the weather data. So the weather generator needs to be set up for us for which there are different options provided. One can click on the import data and select the CSV files as the data format. So if you see here the project summary is visible. So if I just click on the add weather generator option and import data this is the interface that is going to open up and it gives us options to select the data format and the database file. You can either go for database or CSV file and there are different table names in database. Remember this is for the sample file that is made available. So I am going to click on the CSV files and go to the folder WGN wherein 2 files are available. This is for the station data and then I am clicking on the next data. So it will give the monthly values. So now I have imported and as you can see just a single row is made available. I can see the different variables that are being imported like maximum temperature, minimum temperature. So what we have done? We have imported the data by clicking on the weather generator option. So now the weather generator is set up and we need to select the weather stations which is also present at the top left. At any point of time you can edit these values and save the changes and there are different parameters and files codes that are available at the left side of the interface which you can explore and change as needed. So now I am going to go to the weather stations and you can see all the parameters are shown as null or either same SIM which means it has not been imported yet. So we have set up the weather generator and we need to select the weather stations that are at the top left. For that I can go to import option and again I can select the data format and the directory. I am going to use the sample files that are made available and the directory to save the input files there will be a default directory present here. So now the weather station data has been imported and you can see the values have been replaced now. So if I can open it in notepad and see that the data is made available from year 1990 to 2013, the precipitation data, solar radiation, temperature data all these are made available and it has been imported. So now the next step is to Run SWAT plus. Now before we click on the Run SWAT plus button, there are options for us to confirm the simulation settings as is visible at the top. For example I can choose where to write the input files. I can set the simulation period. There are advanced user options which you can explore. For example the time steps for rainfall, runoff and routing you can specify that. So once I make the necessary changes I can click on the save settings and run selected button which starts writing SWAT plus input files and basically it is running. It takes some time based upon the settings that you have made in the page that was shown. So typically after you run SWAT there is an option for us to select the SWAT plus check. Now we can perform SWAT plus check which reads model output from a SWAT plus project and performs many small simple checks. So as to identify the potential model problems, this is mainly done for example if you have some issue it helps us to identify the issue and they are brought to our attention. And this is often essential to find out the hidden problems which require us to say recalibrate the model that ends up consuming a lot of time. So once the run is completed this is the interface, the dialog box which will be visible for you that all the selected tasks have been completed and after that I am going to see the SWAT plus check just to check whether everything is in order. As I mentioned earlier the purpose is just to bring attention to unusual predictions. Now I have run the SWAT plus model and I have applied check SWAT plus check. The next step is to visualize the results. Now to visualize the results I am going to click the tab on visualize which is going to open up this interface for me. I will just expand it so that it is more clearly visible. There is an option known as plot wherein you get to plot the results. We get to choose SWAT plus output table. I have made the selection and then we get to choose the period that is the starting date and the finish date and then I get to add the units and the variable has been selected. So now you see it is visible. Let me just expand to show you that there is options for us to add the observed data file as well. This is the place where we add the observed data file. Now I press on plot and I am going to name it as trial. So the output is plotted here. This is the simulation output. Say if I had entered a CSV file for observation data it would have plotted the observation data versus the simulated data in the same plot with different colors. Just a few options which will be easy for you to use while dealing with SWAT plus. Now the details and demo files are available in these links and I am just useful for you to gain more understanding about SWAT plus. So till now throughout tutorial 12 we have started with trying to understand how does the hydrological model work and then we looked at the different types of hydrologic models and now we have tried to see how running a demo file in SWAT plus looks like. So with this background let me now take your attention to land surface model which is abbreviated as LSM. So LSMs are based on the solution of water and energy balance equations in the VEDOS zone and land atmosphere boundary and it mimics the physical conduct of flux transfer in soil plant and atmospheric continuum. So in particular let us try to understand more about NOAA LSM as part of this tutorial. Just to reiterate land surface models are nothing but integrated models that can assess the available water source as well as predict the impact of future changes in management and climate and it is an integral part of weather forecast models. Some of the widely used LSMs are the NCAR community land models CLM variable infiltration capacity model VIC and the NOAA model. So just a little bit about the history of land surface model because you know it started with the first generation model wherein there was no heat conduction into the soil constant soil depth was considered with fixed soil properties water content was limited and then the second generation of models happened wherein vegetation impacts energy and water budgets momentum transfer all these were included and several soil layers were also included followed by third generation of land surface model which also included carbon balance modeling and there was semi empirical representation of vegetation conductance. So a simple comparison between the NOAA CLM and VIC model is summarized in this table with respect to soil for example the NOAA model has 4 layers of soil moisture CLM has 10 layers of soil moisture VIC has 3 layer moisture and temperature similarly different vegetation that is adopted in NOAA CLM and VIC are shown here for example NOAA the dominant vegetation type is in one grid cell is seen dominant vegetation type in one grid cell. And for CLM up to 10 vegetation types are possible in one single grid cell and VIC there is tiling in one grid cell similarly for the option of snow. NOAA has one layer of snow CLM has 5 layers VIC has 2 layers so different land surface models have different underlying characteristics that is what I want to emphasize through this table. So just to visualize the concept of land surface model assume I am running a land surface model over India I have several meteorological forcing data that go as input into the land surface model okay and then I am trying to simulate realistically a hydrological variable say a runoff or soil moisture that is coming out from the model. So let us try to understand more details about the NOAA land surface model this is a schematic representation and model configuration of NOAA land surface model. If you remember in the earlier part of the tutorial we were trying to understand how a hydrologic model represents the different processes and we were trying to understand it through the water cycle. So with that background if we try to look at the schematic representation of NOAA LSM it is easy for us to understand that NOAA LSM has 4 layers of soil moisture the depths of each layer is given 10 centimeter for layer 1, layer 2 is 30 centimeter, layer 3 is 60 centimeter and layer 4 is 100 centimeter. Similarly we can have different processes okay and you see the long wave radiation incoming short wave radiation then there is direct soil evaporation infiltration happening transpiration happening and there is of course the soil temperature flux, soil moisture flux and gravitational flow happening just a schematic representation of what is contained in the NOAA LSM. So a 1D soil vegetation atmosphere transfer scheme underpins the NOAA LSM to compute the water and energy flux components for unified soil vegetation surface. Now owing to the 1D model assumption lateral flow is neglected in the NOAA model which is a valid assumption for terrain with moderate relief. So during the simulation process each grid cell is designed with its corresponding land cover and soil class which helps to determine the corresponding vegetation and soil parameters. Therefore the uncertainty in geostationary soil and vegetation parameters affect the model simulations. For instance the uncertainty in wilting point and soil porosity leads to erroneous estimation of evapotranspiration which in turn affects the movement of moisture and soil column when combined with uncertainty in saturated hydraulic conductivity. So moving on just to give you a glimpse of model thermodynamics the surface skin temperature in the model is determined following mart and pan by applying a single linearized surface energy balance equation along with the ground heat flux which is controlled by the diffusion equation for soil temperature. So here C is nothing but the volumetric heat capacity thermal conductivity is KT formulated as functions of volumetric soil water content that is theta. Moving on the flow of water in soil is described by the Richards equation that is derived from Darcy's law under the assumption of a rigid isotropic homogeneous one dimensional vertical flow domain. So here in the Richards equation theta is the volumetric soil moisture content, D is the soil water diffusivity, K is the hydraulic conductivity of the soil, Z is the depth of soil and F theta is the source and sinks of soil moisture that is precipitation and evaporation. Just to give you a glimpse of the underlying equations that are embedded or followed in NOILSM. Now shown here is a table which depicts the sample sources where you can find model for forcing data which can be used in NOILSM. For example, if you need say the near surface air temperature and near surface specific humidity and the details about pressure and wind and rainfall rate at a particular spatial resolution and say 3 hourly temporal resolution, you can go to the website of GDAS Global Data Assimilation System. So you know similarly this table summarizes the sources from where we can access the geostationary parameters. For example the land cover, modus, the soil texture, one source is the food and agriculture organization that is FAO. For the soil fraction also we can get it from FAO website and for the slope type it is found in NCEP list, elevation data, SATM, albedo, NCEP, greenness fraction, NCEP. Remember there are many other sources from where we get information about these variables shown here is just one sample source. Now for more details about the land information system I would urge you to visit this link that is shown here. So for this tutorial 12 we understood very briefly about hydrologic models and then we saw details about the SWAT model and then brief details about the NOAA model and among the different types of models available which is best for your application for example which model to choose from. So to answer this question some benchmarking studies need to be conducted which compare and evaluate the performance between different models. So please note that I am not endorsing any particular hydrologic model or commenting on the performance capability of any model shown here are the contents for demonstration purposes only. So let me hope that you found this tutorial useful. Thank you.