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SUMER. DEU Water Resources Management Research and Application Center. WP04 Data Compilation and Analysis by DEU W ater R esources Management R esearch and Application C enter (SUMER) , TURKEY. WORK PACKAGE: 04.
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SUMER DEU Water Resources Management Research and Application Center WP04 Data Compilation and Analysis by DEUWater Resources Management Research and Application Center (SUMER), TURKEY
WORK PACKAGE: 04 • ...the workpackage of SMART to compile, analyze and compare data used ineach case study by means of a standardized database. • The main objective of WP04 is... • ...to compile and process the data required for theindividual case study applications of the methods defined in WP02 and thenumerical tools described and configured in WP03, subject to the constraints... • ...for the final purpose of facilitating • the use of the common set of methods across case studies; and • ii. the comparative analysis across case studies.
WORK PACKAGE: 04 • Main Tasks: • Compilation, analysis, and processing of socio-economic data, which aredefined and detailed in WP02; • Compilation, analysis, and processing of physiographic and hydrological dataidentified inWP03; • Building of a consistent database across case studies, which cover all socioeconomicand modeling data; • Comparative analysis of the data on case studies with respect to theiravailability, completeness, consistency and plausibility; • Preparation of the data report.
WORK PACKAGE: 04 Further Tasks to be performed: All case study partners will prepare their own Data Compilation and Analysis Report. Having all reports forwarded to SUMER, the final “Data Compilation and Analysis Report” summary report will be prepared by SUMER as a deliverable. At the end ofWP04, a comprehensive database of SMART test cases will have been constructed, and thiswill enable the comparison of all case studies in view of data availability, consistencyand quality. Furthermore, this database will feed the analytical tools, Telemac andWaterWare. The scenario-based conditions will also be held in the database for eachcase study area.
NEED FOR A DATABASE IN SMART • A sound database provides in general; • Reliable information storage that allows retrieval at a later date • Up-to-date information, which requires well-defined functions for updating theInformation • Analytical functions that allow, amongst others, to pose what-if questions, torun simulations, • to assess alternative scenarios etc. • Formal database design is composed of certain steps as follows: • Requirements Analysis what data are to be stored in the database, what applications must be built on top of it, and what operations are the most frequent and subject to performance requirements. • Conceptual Design the formation of the Entity-Relationship (ER) Model, which is a popular high-level conceptual data model. • Logical Design the actual implementation of the database, using a commercial Database Management System (DBMS). • Physical Designinternalstorage structures (tabular structures) and fileorganisations for thedatabase are specified.
CONCEPTUAL DESIGN OF THE DATABASE FOR SOCIO-ECONOMIC DATA
CONCEPTUAL DESIGN OF THE DATABASE FOR MODELING DATA
LOGICAL DESIGN OF THE DATABASE FOR SOCIO-ECONOMIC DATA Relational Schema CASE_COUNTRY (CName, C_Code) REGION (RName, R_Code) MUNICIPALITY (MName, M_Code, R_Code) REG_POP (Year, Value, Pop_Char, R_Code) MUN_POP (Year, Value, Pop_Char, M_Code) IND_LOOKUP (Ind_Code, Ind_Name, Unit) NAT_IND (Ind_Code, Value, C_Code) REG_IND (Ind_Code, Value, R_Code) MUN_IND (Ind_Code, Value, M_Code) NAT_IND_DTL (Ind_Code, Class, Value, C_Code) REG_IND_DTL (Ind_Code, Class, Value, R_Code)
LOGICAL DESIGN OF THE DATABASE FOR SOCIO-ECONOMIC DATA
AREA-SCALED ENTITIES LOGICAL DESIGN OF THE DATABASE FOR SOCIO-ECONOMIC DATA
DEMOGRAPHIC ENTITIES LOGICAL DESIGN OF THE DATABASE FOR SOCIO-ECONOMIC DATA
INDICATOR DATA LOGICAL DESIGN OF THE DATABASE FOR SOCIO-ECONOMIC DATA
INDICATOR SUBCLASSES DATA LOGICAL DESIGN OF THE DATABASE FOR SOCIO-ECONOMIC DATA
LOGICAL DESIGN OF THE DATABASE FOR MODELING DATA Relational Schema RBO_LOOKUP (A_Code, A_Name, Class_Code, Explanation) RBO_TYPE (Class_Name, Class_Code) RBO_DATA (RBO_ID, A_Code, Value) RBO (RBO_ID, RBO_Type, RBO_Name, R_Code) PRECIPITATION (Year, Month, Day, Value, RBO_ID) STREAMFLOW (Year, Month, Day, Value, RBO_ID) AIR_TEMP (Year, Month, Day, Value, RBO_ID) LUSE_DATA (Percent_Value, LUse_Type, RBO_ID) SOIL_TYPE (Soil_Type) SOIL_DATA (Soil_Type, RBO_ID) HYPSO_CURVE (Elevation, Area, RBO_ID) RNO (RNO_ID, From_Node, To_Node, Length, Slope, Roughness, #_of_XS,R_Code) XS_DATA (XS_ID, Ref_X, Ref_Y, Ref_Z, RNO_ID)
LOGICAL DESIGN OF THE DATABASE FOR MODELING DATA
RIVER BASIN OBJECT GROUP DATA LOGICAL DESIGN OF THE DATABASE FOR MODELING DATA
TIME SERIES DATA LOGICAL DESIGN OF THE DATABASE FOR MODELING DATA
ADDITIONAL DATA LOGICAL DESIGN OF THE DATABASE FOR MODELING DATA
RIVER NETWORK OBJECT GROUP LOGICAL DESIGN OF THE DATABASE FOR MODELING DATA
Confluence Node 3 Confluence Node 2 Confluence Node 1 Diversion Alasehir Irrigation Buldan Weir Sarıgol Irrigation Afsar Reservoir Buldan Reservoir Subcatchment 1 Subcatchment 2 JUST AS AN EXAMPLE...
Confluence Node 3 Confluence Node 2 Confluence Node 1 Diversion Alasehir Irrigation Buldan Weir Sarıgol Irrigation Afsar Reservoir Buldan Reservoir Subcatch. 1 Subcatch. 2 JUST AS AN EXAMPLE...
INFORMATION EXTRACTION FROM THE DATABASE If wewant to get industrial water consumption per capita for all case-study regions... And the result is...
DATA AVAILABILITY (national level)
DATA AVAILABILITY (regional level)
DATA AVAILABILITY (municipal level) ...some data from Lebanon and Tunisia on other indicators...(?)