ICID & IRRIGATION AUSTRALIA 22 – 29 June 2012, ADELAIDE, AUSTRALIA ICID: 63rd IEC MEETING AND 7th ASIAN REGIONAL CONFERENCE IRRIGATION AUSTRALIA 2012 CONFERENCE & TRADE SHOW A Knowledge/Rule-Based Expert System for Deciding Covering Requirement in Rivers and Drainage Channels Dr. Önder ÖKMEN Civil Engineer Ministry of Forestry and Water Affairs General Directorate of State Hydraulic Works (DSİ) Ankara, TURKEY

Contents  Introduction  Expert Systems  Methods, Materials & Scope  Development of Channel Covering Decision Support Expert System (CCES) CCES frames and instances CCES rules  Case Study  Conclusions

Introduction This study presents an expert system for channel covering decision support with the aid of high-level computer language, which combines knowledge- and rule-based programming techniques. The proposed expert system has been called the “Channel Covering Decision Support Expert System” and abbreviated as “CCES”. Channel coverings (lining), which are used to protect water-carrying routes from erosion, are an important issue in irrigation and drainage projects. However, few countries have a dense soil and channel erosion research network that provides a good understanding of main erosion factors and possibilities for validation of hypotheses. A logical decision about channel lining and appropriate lining material for uncovered drainage channels and rivers included in a project will prevent fatal collapses and sediment transportation problems. This subject is an important part of the area of responsibility of project designers and drainage system managers.

Introduction Expert systems are intelligent tools that serve as support in decision-making processes. CCES helps the user when deciding whether covering (lining) is necessary in rivers or open drainage channels, and it finds out whether or not the properties of the covering material types offered by the user are sufficient in case coverage is required. Furthermore, CCES offers the most appropriate covering type from the covering type database built by the user by taking technical and economical considerations into account. In this study, the applicability of CCES has also been validated by a case study related to an irrigation project carried out in Turkey.

Expert Systems Expert Systems are computer programs that use non-numerical domain-specific knowledge to solve problems with a competence similar to that of human experts. The basic idea behind Expert Systems is simply expertise, which is the vast body of task-specific knowledge transferred from humans to computer. This knowledge is then stored in the computer and users call upon the computers for specific advice as needed. The computer can make inferences and arrive at a specific conclusion. The expert system technique has been the emerging area in the last two decades and is being applied to irrigation and water resource engineering problems. The knowledge base, which is essential in irrigation and drainage, might come from experts as well as other pertinent sources. Rule-based expert systems have been widely developed and applied in the irrigation engineering domain. These systems are based on the premise that expert knowledge can be treated in a set of (IF-THEN) rules. In rule-based systems, the rules are fired when all the conditions in a rule are satisfied, in the same that the event in rule based system is identified after the event has occurred. The applicability of rule-based systems is improved by integration of the procedural analytic programming approach. Numerical, optimization and stochastic methods are implemented in rules and these rules form the knowledge-reasoning and decision-making machine of the system. Thus, the system gives more precise results and practical advice

Components of Expert Systems Expert Systems A hybrid expert system integrates algorithmic techniques with expert system concepts. The aim of using a hybrid expert system is to improve decision-making by enriching the heuristic and expert knowledge with numerical knowledge. Conventional knowledge-based expert systems crucially depend on vast expert and heuristic knowledge. Knowledge-based systems, especially when applied to broad domain problems, suffer from considerable uncertainties in the knowledge-reasoning and decision-making stages.

Methods, Materials & Scope A description of the architecture, development and implementation of the proposed system (CCES) is given first. Later, the validation of CCES is shown by a case study related to the Aslantaş Dam-Yumurtalık Irrigation and Drainage Project that has been realized to irrigate a portion of the farming areas in Çukurova, which is a huge plain in the Mediterranean region of Turkey. The knowledge base and explanation facility of rule-based system have been developed by using a commercially available hybrid expert system shell called GoldWorks III. The GCLlSP Developer, which serves as the programming language platform for GoldWorks III, provides the user with the power of a full Common LISP Language. The scope of the study only consists of non-cohesive soils and stone coverings. The computation method of cohesive soils and other types of channel covering are out of scope. Aslantaş Dam Location of Çukurova Region within Turkey

CCES frames are designed by considering the tractive force of water and the tractive strength of non-cohesive soils, and by using the computation criteria of requirement to covering and required covering thickness. The general topographical shape of a channel is also taken into account. Development of CCES /CCES Frames & Instances CCES frames

Development of CCES /CCES Frames & Instances

CCES frames with entered instances CCES flowchart

Development of CCES /CCES Rules CCES rules provide relations between the instance and slots of the CCES frames. They compute and enter the required parameters, carry out the defined comparisons and finally select and find out which sections of the channel require covering. Moreover, they offer possible covering types that can be used, and finally, they offer the most appropriate covering type for these sections. The rules take technical and economic criteria into consideration when recommending appropriate covering types. Furthermore, CCES can propose the sufficient covering thickness. CCES consists of 12 main rules and 3 sub-rules and each rule has been named according to the function it performs.

Development of CCES /CCES Rules

LISP screen after CCES execution

Case Study One of the secondary drainage channels, which is called Secondary-2 in preliminary drawings, in Aslantaş Dam-Yumurtalık Irrigation and Drainage Project is 4 km long and the current case study has been implemented on Secondary-2 drainage channel. The channel was divided into 10 sections according to the soil characteristics, hydraulic parameters and the existence of curb. Database of the case study has been built by entering 6 stone covering types; each has different parametric properties and unit costs. Data of channel sections

Case Study Database of the case study has been built by entering 6 stone covering types; each has different parametric properties and unit costs. After constituting the frames, the 9th section of the channel has been queried as an example. Before running the program, section-id of the section which is P241S2-9 must have been entered into the SECTION-ID slot of the POSSIBLE COVERING-MATERIAL. Then, the program was run. As previously mentioned, CCES gives all the results of the run on Golden Common LISP window. All of the sections which require covering, the most appropriate covering type and the required covering thickness for the 9th section have been recorded on this resultant LISP window. CCES records these results also within the POSSIBLE-COVERING-MATERIAL frame after running. This window also includes all of the possible covering material types for the channel section in question as an additional information. Data of covering types

Case Study Frames and Instances of the case study

Case Study Query window of the 9th channel section before running Query window of the 9th channel section after running

Case Study LISP screen of the 9th channel section query after running

Conclusions Deciding on the channel lining requirement and choosing an optimum lining material are important subjects in irrigation and drainage projects. These decisions require complete expert knowledge and a vast knowledge database formed by utilizing previous relevant projects and heuristic information. In this regard, this study presents the applicability of hybrid analytic/rule-based expert system programming to the problem of channel-lining decisions and choosing optimum lining material in drainage systems. The decision mechanism of the proposed new expert system (called the «Channel Covering Decision Support Expert System» and abbreviated as «CCES») was improved by combining conventional knowledge-based programming with the rule-based procedural analytical programming. A case study was carried out in order to show the applicability of CCES. The project analyzed through the case study is an irrigation and drainage project that has been realized to irrigate a portion of the farming areas in Çukurova which is a large plain in the Mediterranean region of Turkey. The findings of the case study showed that CCES is quite accurate, practical and very useful for inexperienced decision makers in drainage and irrigation management systems.

CCES has also some limitations. One of them is that it only produces recommendation for the channels opened in non-cohesive soils. Therefore, it can be developed by adding analysis capability of channels opened in cohesive soils. Another limitation of the program is its low data entrance serviceability. This limitation can be developed by investigating data transferring means to Goldworks III from other programs such as MS Excel. Although the program conducts the query of whether covering is required or not for all of the sections only in one run, it can't offer the optimum covering type and covering thickness for all of the sections once at a time. Instead, it produces the results just for the section queried in that run. This can be accepted also as a limitation. Conclusions

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