 Namaste and welcome back to the video course on watershed management. In module number 6 on use of modern techniques in watershed management lecture number 24, today we will discuss decision support systems and applications in watershed management. So, some of the topics covered in today's lecture include decision support system, its basics, characteristics of decision support system, components of decision support system, DSS structure, you know DSS in water management, applications of DSS in watershed management. Some of the keywords, decision support system, characteristics, components and structure. So, as we discussed in some of our earlier lectures, so when we deal with watershed management we have to develop different plans, different scenarios. So, for each plan, each kind of say for example, if you are going to develop a say check dam structure. So, there can be different scenarios like say we can have different locations for the particular check dam or we can have this a specific height of the dam can vary. So, like that various scenarios can be there. So, but each scenario say when we are considering a dam in a particular area in a watershed, then it has its own impact say like say how much water can be stored and then how much flooding can takes place within the watershed. So, all those impacts will be there. So, when such a plan comes to the decision maker who is going to implement the project and then who is the deciding the what is to be done, where to be done all those things. So, then we will have different scenarios. So, different options are there in front of the decision maker. So, the decision maker has to make a decision that yes this is the best solution and then he has to adopt it and then he has to go for implementation. So, that way when we are looking for say taking a particular scenario or considering a particular scenario or particular option. So, we can have a system called decision support system. So, decision support system means a system which helps the decision maker to make a specific decision. So, that way the decision support system say we can say that decision is a recent choice among alternatives. So, we can have different alternatives among that the recent choice is so called the decision and it is done by the decision maker and a decision support system or a DSS means a system that supports a manager or managers working as a problem solving team in the solution of a semi-structured problem by providing information or making suggestions concerning a specific decision. So, decisions so as I mentioned so we can have different options or different scenarios. So, auto that the decision maker has to make a specific decision this is what particular thing which he has to do. So, this can be a single manager decision or a group of managers will be taking the decision as a team and then say DSS a decision support system means it is a semi-structured say system which helps the decision maker to take the specific decision or the specific decisions. So, in general terms the decision support systems are computer based system designed to support decision makers interactively in thinking and making decisions. So, here say the very interactively in thinking and making decision is the words these are very important words in DSS decision support system. So, the decision maker can interact with the various scenarios and then see the outcome of that particular scenario and then accordingly he can take the decision. So, DSS it is a dedicated system restricted, but well defined area of applications. So, that way we can see that the decision support system dedicated one and it is but it is restricted, but with well defined area of applications. So, and then DSS are systems incorporating modeling analysis with data, database management systems and facilitate logistics of decision making process. So, it is DSS is a group of say various applications say like it can be it can include modeling and then it can be include analysis with the data and then digital system or database management systems and then various logistics that support or that help the decision maker. So, that way finally, when we look into all the systems we can say that DSS are the interactive systems that help decision maker systematize the decision making process. So, that way we can say that the decision maker interact use the DSS that means he is interact with the DSS or it is an interactive systems that help the decision maker to take the decision. So, that way when we look into the DSS or decision support system say the say two process are there one is the process of decision making and then the various things which supports the decision. So, that way we can see the differences between the decision making and the decision support. So, decision making is as I already mentioned it is actually a decision actually a decision is a choice between alternatives to meet specific objectives. So, we have got the specific objectives like the construction of a check dam or the various rainwater harvesting implementation or whatever it is. So, that there is a specific choice for the decision maker. So, and that your choices will have the specific objectives. So, that the decision making the it is the process of say which represents different courses of actions. So, we we have to do say actually the objective may be one objective or different objectives. So, but the there will be different courses of actions as far as the the decision and then its implementation is concerned. And then as far as the decision is concerned or the the various choices which we make different hypothesis can be used and a different use of a geographical entity all these are possible in decision making. And then now coming back to decision support I mean the decision support means it can be a model or any other system which supports the decision maker to make the decision. So, decision support actually the it is the role is to aid the decision maker in the process. And then say the simplest level of decision support there there can be an expert advice regarding a decision between the alternatives. So, the engineers or scientists make different alternatives and the decision maker has to take the decision say by considering the various aspects of the of the different scenarios. So, and then this is what is happening in the simplest level and in the most complex level say there can be dedicated computer system or dedicated software. And then this decision support system say for example, say a general climatic model. So, general climatic model which concerns so many alternatives, so many scenarios and then a system which is totally dedicated and then what is the possible this thing. So, for that the decision maker accordingly the various things can be done as far as the the the system which he is for the system which he is taking trying to take the decision. So, that way decision support system say so there is the process of decision making and then the things which are helping to take the decision so called decision support. So, that way as we have seen the decision support system it has got its own characteristics it include many computer models and then generally a graphical use interface where the decision maker or the the other people can interact with that and then say that this is what is going to happen and this way decision can be taken. So, let us look into some of the important characteristics of the decision support system. So, this include the ability to support complex decision making. So, the DSS should the ability to support complex decision making then it should be the DSS should be fast should give fast response to unexpected situations. Say for example, if there is a flash say heavy rainfall takes take is going to take place and then say the there are possibility of flooding in particular area and then the decision maker has to make whether the people should be shifted from particular locality. So, that way the decision support system should be very fast at any kind of unexpected situations so that the decision maker can make the decision easily. And then other characteristics include the ability to try different strategies quickly and objectively. So, the different strategies to be tried say very quickly and objectively according to the set objectives then the DSS should improve the management control and organizational performance. So, the system the so called DSS should help the manager or the decision maker to improve the total system and should have better control over the system and performance should be improved. And then the DSS should reduce the cost of modeling considerably. So, we say the DSS then number of say models and number of system behave things will be there and the this total system should help the manager to reduce the cost say as far as the particular say selection or particular implementation is concerned. And then large data handling capability should be there for the DSS say especially when we are dealing with water source management or watershed management we have to deal with large quantity of data like geographical data then climatic data then land related data like that. So, that way the system should be able to handle large data and then there should be good modeling capabilities and then interactive and a graphical function to make data easily usable. So, that these are some of the important characteristics as far as DSS is concerned like the modeling capabilities interactive and then say appropriate graphical user interface should be there. So, that those who are feeding the data and then after feeding the data we have to run the models and then various scenarios has to be generated and that corresponding thing should be seen in the interface. And then so that the decision maker can easily understand what are the various scenarios or alternative plans and then accordingly he can or she can take the decision. So, now within this context let us look say why do we need a DSS. So, decision support system as we have seen the characteristics we have seen and then say why we let us look into why do we need a DSS. So, as we can see that many of the water source related problems or water management problems the problems are very complex and then simply the decision maker cannot take a decision without considering the various aspects of the problem and then without considering various alternatives or scenarios or plans. So, accordingly to deal with such complex system we need the decision support system. So, that way here I have listed some of the important points like a semi structured approach to problem solving as far as DSS is concerned and then say wherever large volume fee information is there then DSS is very useful and then DSS integrates many information sources. So, either through web or through various computer network say the DSS can integrate many information sources and then say most of the time models are very difficult to use if there is no appropriate decision support system is there and then DSS deals with trade-offs like the trade-offs between the social, economic, bio-physical, legislation etcetera. So, that gives the DSS gives appropriate links and appropriate scenarios when it deals with various things related to social aspects, economical aspects or bio-physical aspects especially when we deal with a watershed management or water related problems and then DSS identify the preferred options for further follow up. So, that is also another important point that is why we have to go for DSS. So, generally what happens is that say when particular decision to be made to be made by the decision maker. So, various alternatives will be there and then say to meet the specific objectives often conflicts will be there. I mean if you implement particular scenario, particular plans then what will be the problems and then another scenario some other problems. So, there can be in conflicts. So, solving this conflict is the art of good decision making. So, each scenario or each alternatives have its own problems and then there will be conflicts between the alternatives. So, that way as far as the decision making is concerned we can say good decision means to solve this conflicts and then come up with the best solution. So, that way the DSS will help the decision maker to make the best solution. As we can see that decision support system is not making the decision, the decision say there is always the manager or decision maker will be always there only it is a support system to the decision maker. So, DSS as such does not take the decision, the decision maker has to take the decisions, but it provides timely information then communicate result to a larger audience open and unbiased working then scenario analysis. So, all these things are possible with the decision support system. So, using a DSS a person responsible for the actual project is able to make a rational use of the system without an in-depth knowledge of modeling techniques. So, we can see that when various alternatives or various scenarios or various plans are there we may have to deal we have to say make models and then run the models to see that what will happen if that particular scenario is done or the plan is done. So, actually the decision maker he does not need or she does not need to know about all this modeling techniques. So, the modeling take this models will run within the background of the decision support system and then the various alternatives and its corresponding outcome will be generated and only decision maker has to understand this outcomes and then accordingly he has to choose the particular alternative or particular plan. So, that way decision support system is a supporting system for the decision maker to come to a particular decision. So, now let us look into say typical decision support system there can be various subsystems within their decision support system. So, we can see that in most of the our problems especially water or watershed management problems main thing is we have to deal with large quantity of data. So, to deal with large quantity of data we have seen in some of the previous lectures geographic information system or remote sensing all these helps. So, most of the time when we deal with watershed or water water issues GIS is always a good preprocessing tool. So, GIS we one of the component and then based upon the available data database can be generated and then a knowledge base where the appropriate data can be put and corresponding preprocessing can be done. So, that is called a knowledge base and then corresponding hypertext file where anybody can look into those files and then say the comments. So, that way one of the important part of a typical decision support system is the preprocessing tools as listed here. And then of course, say by using this data we have to run various simulation models or optimization models or various kinds of modeling we have to do and then we have to run this models within the computer. So, that is the processing or the within these subsystems are called computer models. So, based upon this preprocessed data the computer models will run and then particular scenarios will be generated and these scenarios say actually a computer gives in terms of numbers. So, the decision maker will not understand what are those data. So, that way we need another subsystem called a post processing tools. So, here say it can be this post processing of the simulated results it can be represented in terms of say graphical forms in bar charts or in animations or in conduits or in tabular form. So, that way this results or this outcomes are given to the decision maker by using the graphical user interface. So, and this graphical user interface should be interactive. So, that decision maker can even feed various things within the system and then see that what will be happening if any alternative solutions are possible. So, that way typical decision support system mainly there will be three components one is the preprocessing tools and then second one is the modeling tools like computer models and third one is the post processing tools. So, now say like that as we can say this is the typical structure of a decision support system and then depending upon the decision support system various modeling to be done or various things within the system various components can be there. So, various components of a decision support system I have listed here. So, first one is the database. So, database generally it can be the spatial variation that means spatial data and then time dependent or temporal data and then we can as I mentioned GIS or remote sensing we can use for spatial data like various maps and all those thing can be generated and then another one is the mathematical models. So, the computer models which you be running and then generate the results and then another component can be the expert systems. So, this expert system for each kind of say particular problem or the model we can have expert system with related to simulation or optimizations and then that can be also component of the decision support system and then say we can also use the statistical models, graphical software, spreadsheets etcetera within the DSS. So, that whatever useful for the depiction of particular scenarios. So, accordingly we can utilize and then so one of the most important component the other important component is the user interface. So, generally nowadays we are having very effective interactive graphical user interface. So, that is also one of the important component of any of the effective decision support system and then the database in a decision support system. So, as I already mentioned data that are stored in a large pool of from which different applications with the different data requirements can retrieve. So, in an effective efficient DSS system there will be a database. So, that from using that database we can retrieve the data or we can give the input the data and then we can get the output in various formats. So, that that can be directly utilized in the particular computer models and then say as far as a database is concerned for major categories of data can be the special data. I mean the special variations in say three dimensions X, Y, Z and then temporal data like a time varying data, then relation data and then attribute data. So, like that various data sets for the particular system, particular problem can be there within the database of the DSS which we consider. And then the other most important component is so called a user interface. So, user interface is a software that helps the decision maker to use the application easily and effectively. So, as I mentioned the decision maker, so it is not essential that he should understand all the aspects of the problems or all the modeling what is happening within the system. So, that way the user interface is the what is interacting with the decision maker. So, this helps the decision maker to deal with the problem or to understand the problem and then take a decision easily and effectively. So, well defined user interfaces can free the user from learning complex command languages. So, earlier we say when we used to how this DOS based system we how to use very complex commands, but now with a graphical user interface there is no need of such commands by just clicking the button we can say get to various things. So, that way now the graphical user interface is play a major role in the most of the decisions of the system. A major part of the DSS development efforts. So, that way goes to the design of appropriate user interface. So, this way appropriate is very important. So, depending upon the problem. So, we have to design the DSS interface. So, like various questions or various output. So, all those things should be there within the interface. So, that the data input can be given easily and then the output can be taken easily and then the decision maker can easily understand the system and then other important component of the DSS is the mathematical models. Actually mathematical models are important component of DSS. So, as I mentioned it can be simulation models or optimization models which helps to understand say a particular scenario is implemented or particular plan is implemented what will happen within the system. So, that is what the mathematical models predicts say as a simulation model or an optimization model. So, the commonly used models include optimization, simulation, statistical models, decision analysis, then artificial engineering techniques, genetic algorithms, neural networks etcetera. So, number of mathematical models or computer models are used nowadays. So, that way when we look into decision support system. So, we can see that say it is actually a semi structured system. So, that means it is not fully computerized. So, that the computer take the decision. No, it is a decision maker is there. So, it is actually a system which helps the decision maker to take the decision. So, that way here in the slides I have shown say for example, an unstructured system. So, where the decision maker manager has to find the solution on his own there are no support system and then here there is a computer based solution. So, the entire solution is through the computer model. So, there is no role for the decision maker or manager, but generally most certain decision support system means it is a semi structured system where the manager or decision maker and computer come together and then take the decision. So, it is that way semi structured system. So, the basic DS structure include as I mentioned a database subsystem, model based subsystem, user interface or dialogue subsystems and then knowledge subsystems. So, the subsystems are database, model base, then user interface and the knowledge base subsystems. So, let us look into some of the important aspects of these subsystems. So, the database management tools of the database system software used for the management of the database. So, this include the data inputs then its processing to appropriate formatting and then the output and then model based subsystem it is the actually the heart of the system. So, where the various models will be running. So, that we can say that this model based subsystem is the heart of the system and then as far as user interface is concerned this gives the dialogues as far as the to understand the system or understand the problem. So, that way we can say that it is a phase of the system and then the knowledge base subsystem that gives the expertise for solving critical problems stored as rules to be followed during typical situations. So, if then what will happen? So, like that the knowledge base subsystem. So, this system provide intelligence to decision makers so that a particular decision can be made by the decision maker. So, that way we can see that say all this database of system or model based subsystem or the user interface of system or knowledge base of system all are important in a decision support systems say in its own way, but the heart of the system we can say as the model based and the phase of the system we can say as the dialogues of system or the user interface. So, now say as far as the DSS decision support system structure is concerned when we deal with the database management tools. So, this database management tools contains a procedural language along with the hierarchical and relational data structure. So, that way the key capabilities of the database which we consider the database of system include extraction, updating, interrelate data from different sources and then retrieve the data, provide comprehensive data security, complex data manipulation, then manage the data through data dictionary. So, these are some of the key capabilities as far as a particular database within a DSS. So, there should be option for input the data then say extraction the data then updating the data then retrieving the data and then various manipulation of the data. So, all those things should be there in the database of system of the DSS which we consider. And then now say the model based subsystem is concerned the details are listed here. So, it contains four basic types of models as we already seen strategic models, tactical models, then operational models, model building blocks and subroutines. So, that way the strategy these are some of the important components of the model based subsystem. So, the key capabilities of the model based input it creates new models quickly. So, if a particular scenario selected a particular plan is selected. So, this model based subsystem create new models quickly, maintain wide range of models to support all levels of management. Then it interrelates the models with the database then access and integrate the model building blocks. So, we can say that from one building blocks to another blocks there will be connection or connectivity should be there. So, all those things should be there in the model based subsystem. Then manage model based with management functions analogous to database management. So, the management is very similar to what is there with with respect to database management. So, but the model based subsystems say as we have seen it is actually heart of the system. So, which has to run for various scenarios or various alternatives and then the output should be the should come and then based upon that the post processing should be done to understand the system behavior. So, that way the model based tools as I already mentioned different modeling techniques commonly used in this support systems include optimization models like say linear programming dynamic programming like that. Then numerical models like final pattern method, final difference method. So, mainly for simulation purpose then artificial neural network or artificial intelligence techniques like artificial neural networks, genetic algorithm. Then fuzzy logic based models then of course, geographic information system and more sensing based models also nowadays used when we have to deal with a large database or larger area like river basin or a like say watershed larger area which we have to deal generally. Let us have a brief look into various model based tools. So, as I already mentioned the optimization models are generally used in the DSS support systems. Actually optimization is done to either minimize the cost or maximize the benefits. So, that is that is very important in most of the say decision making process since most of the time and the decision maker wants to reduce the cost or minimize the cost and he wants to maximize the benefits with respect to various scenarios or with respect to various cases. So, say we can have depending upon the problem we can have various models like linear programming, non-linear programming, dynamic programming then artificial intelligence techniques like genetic algorithm. So, these are all optimization models and depending upon the problem say for example, if the objective function and the constraints are linear in nature then we can go for linear programming and if the constraints or the objective function non-linear we can go for non-linear programming and then if it is stage wise then we can go for dynamic programming. Then say depending upon the data and then say problem we can also go for artificial intelligence techniques like a genetic algorithm. Then say other type of model based tools like numerical models. So, numerical models say especially to solve partial differential equations or differential equations we use a numerical model especially for simulation purpose. So, this simulation is very important say once we say that a particular plan or particular scenario is not then we can run that scenario and then see what will happen. So, that way most of the time numerical models or different types of models will be very useful and then that gives the simulation simulator results for that particular scenario. So, especially since water related or water shed related problems are very complex. So, that way we have to model we have to solve partial differential equations like Saint-Venant's equations or Navier-Stokes equations. So, in those cases there are no analytical solutions available. So, that way we have to use the numerical models like final element method, final difference methods as we have seen in some of the previous lectures. So, we can use these techniques as a simulator or simulating tool and that can be also a part of the decision support systems. Then say when we are going for special modeling geography information systems as I already mentioned earlier. So, GIS based systems we can utilize. So, as we discussed in one of the previous lectures GIS is a computer based systems used for storing manipulating and analyzing the data. So, it provides timely information in a readily usable form. So, based upon the data we can manipulate the data and then generate different maps like topo graphical maps, then land use map, land cover map, soil map, digital elevation model. So, all these aspects we have seen. So, GIS is very helpful especially in the case of water management or water resource management. So, that way GIS can be effectively used as a part of the decision support systems and then remote sensing tools wherever huge data is needed and then the temporal variations to be considered then we can use the remote sensing. So, remote sensing data gives the detailed distribution of the parameters based in wireless say like river based in or the watershed basis. Then it is useful for distributed modeling of the watershed. So, if we are going for a physically based models then remote sensing data is very useful especially land use, land cover and then the spatial variation, then delineation of watershed, soil type, land use, classification, etcetera and all these places we can use remote sensing tools as a model based tool. Then say what we are discussing about the components of the decision support systems. So, now say most of the time say especially related to watershed management or water related issues we have to deal the spatial variation say either a watershed basis or river basin scale or a catchment basis or the state wise or the country wise. So, that way we have to see the spatial variation say and then when we can generate a decision support system based upon the spatial variation specifically then we can call that type of system as spatial decision support systems. So, spatial decision support systems provide the decision making environment to enable the analysis of geographical information specifically. So, spatial decision support system or SDSS are DSS with the mechanisms for input of spatial data and the SDSS allow representation of the complex spatial relations and the structures commonly found in spatial data. Then SDSS include analytical techniques unique to spatial and geographical analysis including the statistics. So, generally the GIS is also part of this SDSS or spatial decision support systems. So, SDSS very similar to is very similar to the DSS. So, SDSS generally in so the three levels of architecture will be there. So, first one is the tools. So, general purpose like hardware and software tools that can be assembled to build a variety of system modules very similar to what is there in the DSS. Then the technical supporter. So, SDSS that can be configured to address specific problems through modeling. So, that is the technical supporter then the builder. So, builder takes domain specific data and develops the SDSS for a given applications. So, for particular application whether water related or soil related then we can have the specific spatial decision support systems. So, then say very similar to DSS any type of DSS spatial decision support systems will have the data base and then model base. So, like that. So, here again in this slide the various components of spatial decision support systems are described. The DBMS or the data base management systems. So, like locational topological and thematic data types to support cartographic display, spatial query, analytical modeling etcetera. So, DBMS will be effectively a part of most of the SDSS. Then MBMS or model based management systems as we have seen for DSS very similar to that here spatial decision support system also will be having the model based management system to support statistical and numerical models which stores the models instead of data. Then each model may be a small piece of code to solve a part of particular algorithm. So, that way we can plan in the DSS or DSS. The knowledge based reasoning image processing can also be part of the management say or model based management system or MBMS. Then graphical and table report generators very similar to DSS are there in the case of SDSS also. And this can be two dimensional or three dimensional the displays can be in two dimensions or three dimensions. And then also we can choose either bar charts, pie charts, scatter plots, land plots etcetera within the SDSS very similar to DSS. Then say it can be also application specific plots and reports can be generated within the SDSS. So, that way SDSS or spatial decision support system is DSS only. So, but generally when we deal with either watershed or river basins scale then we have to deal with a lot of spatial data and that way we call this DSS as spatial DSS or spatial SDSS. So, now before going to discuss the various aspects of waters resource management or watershed management related to DSS. So, let us look into the development methodology as far as decision support system is concerned. So, here the various steps I have listed here. Before we develop a DSS we should assess the needs. So, what are the things that is we are expected from a decision support systems. So, what are the things should be there within the systems and what will be the input, what will be the output from the system. So, that way we have to do a needs assessment when we develop a DSS. Then a DSS model conceptualization. So, very similar to we conceptualize a model we have to conceptualize the various components of the decision support systems. And then as given in the slides the database development. So, we have to develop the database. So, that is one of the essential component of the DSS. Then next step is generic DSS development we can based upon all these aspects we can have generalized DSS system. And then say for the particular problems said to deal with the particular way the water related soil related or land related issues we can customize the system. So, that is so called DSS customization. So, that is the next step and then once it is done the system is ready. So, now we can go for testing and then further we can refine and then see how the system is working. So, that is the next step as shown in the slide. So, DSS testing and refinements. Then say once it is testing is done and if it is working properly then we can go for typical applications. So, that way DSS applications and demonstrations. So, we can for the particular area or particular system or particular plans we can how the DSS applications and then demonstrate. And then we can evaluate the system and then fine tune it. Then say of course, once it is ready we have to train the people who are going to use it. So, that way dissemination training and outreach plans we can prepare. So, then say based upon the needs we can prepare a final report also. So, these are some of the essential steps as far as the DSS development is concerned. So, a systematic approach we can follow as far as DSS development is concerned. So, now we will discuss say water related issues. So, whatever we have discussed the so far were related to general aspects of desert support system or SDSS special desert support systems, various components then its structure and then various subsystems like that. So, now when we deal with water related issues so as we have seen in many of our earlier lectures in this course. So, the water related like rainfall to run off or various things including the climate the changes are drastic from one location to another location special variation is too much and then temporal variation or time dependent variations also there. So, that way the main need of desert support system say due to all these changes desert support system is very essential say when we deal with water related issues or water source plans or watershed development plans. So, say here say the temporal variations can be either daily variation, weekly variation, monthly variation or seasonal variation or yearly variation or decadal variation or sensory variation where especially climate change issues are there especially when we deal with water related issues then how user rainfall variation temperature variation drought pattern. So, the weather forecast are very important. So, the spatial scale can be either say few square kilometer or say large area like 1000 square kilometers or even million square kilometer like that. So, then this is temporal variation spatial variation and then the issues are concerned like either weather forecasting or extended seasonal weather predictions and climate outlook and then if it is long time prediction or long time effects then decadal variation, decadal variability or climate change which is say we have to consider sensory variations then say especially various problems like flood problem or drought problem or water availability problem. So, that various problems we will be considering and then say within the area river basin scale or watershed scale then if the reservoir is there how to operate the reservoirs or reservoir operation then surface water management, ground water management then ecosystems management then of course, watershed based management system. So, all these things we can consider say within a decision support systems. So, in a nutshell we can say that when we deal with especially water related or watershed related problems decision support system is very essential since we have to evaluate various plans, various scenarios and then we can come up with appropriate outcome. So, that way decision support systems will be very useful to deal with the water related issues, water resource management or watershed management plans. So, now DSS for water resource planning. So, decision support system provides water management authority say well structured user friendly practical and complete water resource management information systems. So, that when we have a number of software number of packages are available nowadays. So, we can have user friendly practical and complete water resource management plans. Then DSS may assist decision makers in taking the right decisions on the basis of good comparisons of different strategies under various scenarios and combine the benefits of information systems, expert systems and simulation models. So, various things we can combine together within the DSS decision support systems. So, that way DSS is very essential in water resource planning and management and also say within the context of watershed management. So, water resource planning problems are generally resource wise complexities too much, society wise complexities too much and the necromic wise complexity too also there. So, water resource or watershed planning and management that is that way it is a daunting challenge. So, that way DSS decision support system will be very useful to deal with water resource plans or watershed management plans. So, a typical components of a DSS related to water resource planning the various components I have listed here. So, of course, the basic components as we have seen earlier like an database management system, say management based model systems then the user interface these are all essential components. But various other components related to hydrological aspects or related to modeling aspects these are listed here like hydrological information systems, geographic information systems then information system for other required data then remote sensing data analysis systems then a statistical and time series analysis tool and demand projection module hydrological data analysis system and planning optimization and assimilation module economic analysis module graphical user interface. So, like that say many of these components can be there depending upon the problem depending upon the river base in our watershed for which we are developing the decisions support system. So, especially say typically when we consider hydrological information system and data processing say like water resource or watershed system is concerned and we can set the objectives and then we can have the various data from the various agencies then say we can record it validate it process it and store it then the users like decision makers can use it policy makers engineers and these user groups. So, various users can utilize it. So, that way we can develop the systems. So, now here in this slides a typical decision support system related to watershed management is shown here. So, as I mentioned the temporal data then special data then socio-economic data. So, all this data we should have within the DSS system and then we should have the data base or hydraulic information systems and then various tools like statistical or optimization tools can be there and of course, since very much data intensive is the process. So, that way geographic information systems and remote sensing we can integrate. Then say related to the various say for example, if the problem is related to water then we can assess the water demands for the particular watershed and water available, water supply then we can have the prediction models. Then we can find out water balance studies using the models then demand management events. Then we can have the hydrological modeling systems where we can run various models then using simulation models or optimization models and then we can generate the alternative plans depending upon the problems and then we can have the expert systems for that depending upon the problem and then these all these things will be represented in a graphical user interface integrated in GIS or hydrological information systems. So, GUI integrated in GIS or HIS. So, that way finally, now various plans are available and then the decision maker can use the total systems to select particular alternative or particular plan or particular scenario. So, this shows a typical decision support system related to watershed management. So, in the literature if you go through number of DSS software are available for water resource planning and management. So, some of the important software I have listed here like Mooli Nordic support system from Italy, then Mike Basin from DHI, Basins from US EPA, then SDSS from Technic University of Athens, then IQQM from Q-Instant Department of Natural Resources, then NC's Norwegian Institute of Water Research, RLM from Australia, RIBAS, Riebeisim, Bader-Hadwalex, WAP by Stockholm Environment Institute, Accuatool, IRAS. So, like that number of decision support systems are available. So, depending upon the new depending upon the problem we can choose particular decision support systems. So, now before closing today's lecture that let us look into one specific case study how effectively a decision support system is a especially GIS based system can help the decision maker to understand how the scenario related to development of a reservoir and then it is a flooding region. So, this here this is the case study is barbie reservoir or barbie river in Badalapur in Maharashtra. So, this is the area barbie river here and this is the reservoir area. So, these details are taken from a paper and report by Professor Vengala Chalam and JK Suri in 1995. So, this is the barbie catchment drainage map. So, here say the details of the drainage system is given here. So, the length of the dam is 746.7 meter, storage capacity 178.5 million cubic meter and then catchment here is about 166 square kilometer. So, this is the origin is from barbie river at village Pimbole, Thaluka here this is the location. So, here the objective of this study was to generate current land use land cover information from the remote sensing then simulate a new submergence for each value of raised height of barbie reservoir and compute increase in capacity of reservoir then identify the submergence village wise land use land cover wise then provide necessary inputs for the decision makers to take optimal decisions based on cost versus benefit analysis. So, this were the objective. So, this study. So, here the part of DS using GIS is presented. So, actually the existing height in this dam was earlier 67 meter. So, if the 67 meter dam is there then the say water body typically will be like this. So, here as I mentioned in earlier slide say the water spread area and then the capacity is there. So, the question is if the reservoirs or the dam size is increased the height is increased and then reservoir area will be increased then how much flooding can take place, but to correspond how much will be the storage capacity will be available. So, that is what the study has been done here. So, this is the barbie catchment land use map. So, here this shows the water body then green color shows the forest then this color degraded forest and then open scrub agriculture land is the yellow and then say based upon available data Professor Vanga Rajilman her team say studied in detail in a GIS environment the decision support system in a GIS environment. So, this shows if the level of the dam is raised to 70.6 meter from the previous 67 meter then how much area will be flooded. So, you can see that the corresponding to this say so much area will be flooded and then corresponding storage is increased to 96.3 million cubic meter. So, correspondingly the increase will be this much will be the storage capacity increase. Then say if the level is increased to when the level is raised to 72.6 then how the storage capacity is gone to 145.6 million cubic meter and then you can see that how which are the area will be flooded and then again if it is increased to 76 meter then how much area will be flooded. So, like that the studies were conducted by the experts. So, GIS method is used to utilize alternative scenarios of impact on land use and population and different elevation levels with the increased volume of water storage and presented to the government to take suitable action. So, how much area will be say the level is this 70.6 or 72.6 or 76 how much is the area will be affected in a submergence in hectare is shown here. So, the corresponding elevation level and increased storage capacity in a million cubic meter is also shown here. So, using such a system the decision maker can make a decision if this is the level what will be the flooding and what will be the benefits like how much water can be stored. So, that way when we put the system in GIS environment. So, a decision support system is generated and that can be used by the decision maker. So, to conclude this today's lecture some of the remarks like water management involves many processes which are modeled individually or collectively by the decision support systems and DSS helps the water managers to take the optimal decisions in complex situations as we have already seen and DSS are developed applied to a particular basin or a basin with similar characteristics. So, depending upon the problem the case will be say we have to specifically make the DSS depending upon the needs and DSS needed for a all the irrigation water sheds to make most of the available fresh water which was in an effective way. And then water shed management is concerned since the people have to interact participative decision making we have to do. So, interactive decision support system is always very effective or always the need of the hour. So, this interactive DSS the advantage is that end user can input his data and analyze and query to get output. Solution in less time with a minimum cost. So, what will happen the various scenarios can be generated easily. So, these are some of the advantages of such a decision support systems. So, these are some of the references used for today's lecture and some of the questions from today's lecture critically study role of decision support systems in development of effective water shed management plans. So, these details you can get from internet evaluate the capabilities of various DSS softwares used for water source planning as we have seen one on a slide and details you can get from the internet. Then few other questions for self evaluation illustrate characteristics of a typical DSS what are the important components of a DSS. Describe important model based tools mentioned step by step methodology for DSS development and implementation. Describe a typical hydrological information systems. So, these details you can answer based upon today's lecture. Then few assignment questions why do we need a DSS explain the typical structure of a DSS illustrate the characteristics of special DSS describe the typical features of DSS for water source planning and management illustrate a typical decision support systems for water shed management. So, these details if you go through the lecture you can get all these the answers to all these questions. So, as an unsolved problem for your water shed areas for the possibility of using a DSS for effective water management plans from the literature identify suitable DSS package for water shed management plans which are the other areas where DSS can be effectively used in water shed management development plans. So, water related issues we have seen. So, even soil related soil erosion problems or rainwater harvesting or various schemes we can have the decision support systems. So, today we have discussed about the decision support systems and its role in water resource management and water shed management plans. So, that is what we discussed in today's lecture. So, further we will see how an integrated say system of GIS remote sensing and computer modeling can effectively utilized in water shed development plans. Thank you.