Alexander Zaporozec
4.5 Data management
The foundation for any successful groundwater contamination inventory is the collection, storage, and management of data – a data management system. Data management is the process of maintaining data in a logical fashion to facilitate information retrieval and analysis. Data management begins with a set of procedures for entering the data in a systematic fashion and for checking, sorting, and classifying data. Data are the raw material from which information is generated.
Conceptually, data are assembled into records and files for management purposes (U.S.
EPA, 1991a). A data record is made up of a small group of related data items, and a collection of data records is known as a data file or data set. A data record that belongs to a particular data file also can be cross-referenced to other data files that contain additional information (relational data bases). For example, land use categories can be linked to a file containing typical chemicals found within these categories. An orderly collection of data files forms a data base.
Whatever its purpose and detail, the groundwater contamination inventory should incorporate the basic steps in gathering and interpreting data as outlined below. The purpose of this section is to provide an overview and a working guideline for recording and managing data collected for the contamination inventory process.
4.5.1 Data recording
Appropriate, standardised forms for recording data should be prepared to be used by all staff and volunteers involved in the inventory. If field notebooks are used during field searches or surveys, all field notes should be transferred to standardised inventory forms. Examples of inventory forms are shown in Tables 4.2 and 4.3. The completed forms are filed in an organised and easily retrievable manner.
The selection of a uniform base map, on which the information obtained during the Groundwater contamination inventory
inventory will be recorded, is a very important step. Each data point is plotted on topographical maps or on specially selected and prepared base maps. Each map has an assigned unique iden-tification (ID) number. There are many types of maps available for the purpose of the inventory.
Preferably, standard topographic quadrangle maps of the large scale (1:25,000 or larger) should be used. These maps are easily reproduced, provide enough detail to determine streets and boundaries, and will make the eventual transfer to a digital, computer-based format possible.
They are available from the official national/state topographic mapping agencies or from certified topographic map dealers. Other regional or local maps may be available from urban and regional planning agencies or city/village offices.
All data points need to be entered into a data base, updated, and maintained at a central location, either in a manual or, preferably, in a computerised form. In order to enter data into the data base, each data point needs to have a unique ID number, which is also recorded on the inventory forms; geolocator; and the ID number of a map on which it is plotted. The types and qualities of data that are to be incorporated into the data base need to be specified and evaluated. Location and source attribute information must be verified to meet established data standards.
4.5.2 Creating a data base
The inventory process requires an accurate, appropriate, and sufficient system for the collection, review, storage, and retrieval of data for later use – a data base. A data base is a collection of data records and files that are logically organised to facilitate the manipulation of data. It makes no difference whether the data are in a field notebook, in a filing cabinet, or on a computer disk, as long as the collection of data is logically consistent with the objectives and goals of the inventory.
The primary objective of developing a data base is to enable the processing, analysis, and retrieval of data. The function of a data base is to organize a volume of data and to make the data accessible, so that they become information. Various approaches to the design and management of geological data bases and examples of their uses are included in Giles (1995). The development of a data base would typically follow a series of procedures such as:
1) formulation of data base specifications;
2) designation of data base operator and/or manager;
3) data collection and recording;
4) data investigation;
5) data base design (or selection of a commercially available one);
6) data base implementation;
7) data base evaluation and modification.
4.5.3 Data storage, access, and maintenance
The inventoried data can be either filed manually or stored in a computer. Although computer storage and manipulation of data is preferable, the high costs of digitalisation and manipulation of data, hardware and software needs, and training of personnel may preclude the use of a computer in some cases or in some parts of the world.
For a small amount data, a manual filing system may well be adequate. A manual system is inexpensive and does not require special equipment and specialised training. As long as the data base is not going to be shared or updated frequently, a manual filing system is generally sufficient to manage a limited volume of data from a source inventory. Its disadvantages are:
cannot be easily shared, inflexibility, possibility of data redundancy, slow retrieval, and limited data analysis and processing capabilities. In addition, the manual filing system is often too labour intensive for an individual to manually cross-reference even a small number of data files in a timely manner.
When dealing with a larger amount of data, a computerised data base is ideal because it can deal with a large quantity of data and perform complex data processing tasks. Its advantages are:
great flexibility in data analysis, easy accessibility and retrieval of data, and centralised control of data, which help ensure the integrity of the data base and data security. The disadvantages
include: costs of hardware and software acquisition and maintenance, specialised training, and risk of losing or corrupting data if backup protocols are inadequate or lacking (U.S. EPA, 1991a).
Under a proper data management scheme, the data must be securely stored to minimise any chances of accidental destruction or gradual degradation over time. It should also not be possible for any unauthorised person to alter the contents of the data. Access to data bases should be available to all inventory staff, but data entry and corrections should be made only by an appointed data base operator or manager (Fig. 4.6). A data manager is an essential element of a data base. The data manager’s role is critical especially in ensuring data quality. The single most important reason for the failure of data bases is the absence of a data manager.
All data management systems require some sort of periodic maintenance. Once an inven-tory has been completed, the data must continue to be updated. Through data base verification and updating, a computerised data management system can be fine-tuned and modified to increase the effectiveness and efficiency of the system for data retrieval and analysis. Maintenance of a computerised data base also can involve training of new users and updating the skills of previous users whenever modifications are made to the system. In addition, backup and recovery procedures should be well established to minimise the risk of losing data due to error or malfunction (U.S. EPA, 1991a).
Data Base Management Systems (DBMS) provide storage, maintenance, and access capabilities for large amounts of data. Storing the data in a DBMS with adequate access capabilities would allow the data to be reused without extensive reformatting. Fig. 4.6 illustrates the proper access to data bases. Users want to use the inventory data for many types of analyses.
They can access the data base directly through DBMS utilities and query the data base, using a data query language, or retrieve the data. However, if the users (inventory staff) want to enter new data or correct the old ones, they have to forward the data or corrections to the data base operator.
4.5.4 Data processing and presentation
Electronic spreadsheets, non-relational data bases, or structured DBMS can be used for processing the data. Spreadsheets are designed for the entry and display of numerical data in a grid pattern.
Although spreadsheets have limited processing capabilities, they are effective enough for small data set analyses. Non-relational data bases (such as dBase) are sufficient for most purposes but they do not have a good control in exporting of data. Structured DBMS (such as ORACLE), which show the interrelationships between attributes, fields, etc., are more complicated and expensive.
However, the long-term benefits of using such systems can easily outweigh the costs, because these systems provide a much better basis for complex data processing, decision-making support, and cross program integration.
Results of the contamination source inventory should be tabulated and displayed on maps according to the predetermined source categories. All sources should be properly located,
Groundwater contamination inventory
FIGURE4.6 Proper access to a data base (Adapted from:Dodson, 1993)
accurately referenced spatially, and plotted on maps. The scale of maps should be compatible with the scale of other maps constructed for the project. Various types of maps resulting from the contamination source inventory are described in Chapter 6.
Several types of graphic applications are available for presentation of data (Dodson, 1993):
•
Computer-Assisted Drafting and Design (CADD) programs;•
Image Processing Systems (IMS);•
Geographical Information Systems (GIS).CADD programs provide powerful tools for the input of inventory and field survey data.
The most widely used is the AutoCADTMprogram, which can be used for mapping and general technical drawing. CADD programs generally deal with vector data (points, lines, and arcs). They do not include capabilities for displaying or editing raster data (e.g. data files from scanners).
Image processing systems store, enhance, analyse, and display digitised images such as those received from high-altitude photography and other forms of remote sensing. Image processing systems are based on raster data.
A geographical information system (GIS) is a powerful computer-based tool for integrating and analysing data obtained from a wide range of sources. It is explained in more detail in Chapter 6 (para. 6.3). GIS is an example of an integrated data base management system. It presents a graphic picture of the location of contamination sources in relation to other data elements. GIS contains a base map and several layers of data. GIS may deal with vector data as well as raster data. Once stored, the data can be easily validated, analysed, extracted, reformatted, updated, and mapped.
5.1 Introduction
The purpose of a groundwater contamination source inventory could vary, ranging from the identification of major sources on a national level to the detailed description of sources within a local area, for example, a wellhead protection area. In most cases, to make the maximum use of the data gathered in an inventory, some kind of classification, ranking, and/or rating of the contamination sources is desirable. Various classification schemes are presented in Chapter 3 and a classification based on origin is advocated. Such a classification does not explicitly tell anything about the potential hazard of the type of source or of the single object. However, in general, different types of contamination sources are known to pose more or less serious threats to groundwater.
The term ranking in this guideline is used for the relative, subjective arrangement of contamination sources from the most to the least hazardous or by any other priority. Ranking of contamination sources usually is done by government officials or decision-makers based on local preferences, and is briefly addressed in para. 4.3.2 and Chapter 7. The term rating is used for a procedure where contamination sources are given a quantitative or qualitative measure of the potential hazard they pose to groundwater. A quantitative value could, for example, be a quantity or a concentration, e.g. quantity of deposition of airborne acidifying substances or concentration of pesticides leaching from the root zone. A qualitative measure of the contamination potential could be expressed as ranging from high to low or as a numerical index. Rating of contamination sources is the focus of this chapter.
Rankings and ratings are useful to give an indication of the size of the problem and to make priorities for more detailed studies as well as for areas and objects to be considered for regulatory and engineering measures. The ranking and rating can be based on varying degrees of infor-mation and can also be used during the inventory to prioritise contamination sources to be studied in more detail.
Groundwater contamination is to a great extent controlled by the type and volume of the contaminant and its mode of disposition. However, the usefulness of the rating of groundwater contamination sources as a planning tool will increase if it is combined with assessments of the vulnerability and aquifer value (see Chapter 6, case study 8.4, and Johansson et al., 1999). In a long-term sustainability context, the vulnerability is less important when dealing with very mobile and persistent contaminants.