HydroGIS 96: Application of Geographic Information Systems in Hydrology and Water Resources Management (Proceedings of the Vienna Conference, April 1996). IAHS Publ. no. 235, 1996. 669

An object-oriented approach to model integration: a river basin information system example

K. FEDRA Environmental Software & Services GmbH, PO Box 100, A-2352 Gumpoldskirchen, Austria

D. G. JAMIESON University of Newcastle-upon-Tyne, Department of Civil Engineering, Newcastle-upon-Tyne NE1 7RU, UK

Abstract This paper describes the WaterWare system, an object oriented information and decision support system for river basin management. The basic data framework combines a hybrid GIS as the overall structure with classes of objects, including river basin elements, models and model scenarios, and tasks or decision problems. River basin elements are spati­ally referenced, and represent, for example, subcatchments, reservoirs, treatment plants, river reaches, etc. From the GIS perspective, they are polygons, lines, points, or regular cell grids. Their state, in a context defined by other objects in the system, is determined by a set of methods, which are models or sets of rules for an embedded expert system. Tasks are specific, problem oriented views of river basin objects or combinations of objects. They present their state, usually over time, given a number of decision variables or scenario assumptions, to the user to support planning or management decisions. The various objects are linked explicitly, e.g. a reservoir might be linked to the subcatchment that provides its inflow, an observationstation thatmonitors the hydrometeorological data, and anirri-gation district it supplies. Models such as a rainfall-runoff model or an irri­gation water demand estimation model are used to update the state of these respective objects, and thus provide inputs (time series of demand or supply) to a water resources model. The water resources model, in turn, provides input to a water quality model, that again operates in the context of other objects such as discharge nodes (treatmentplants, industries, munici­palities), orextractionandmonitoring points. TheGIS, with the underlying spatial data such as landuse, geology, and topography, also provides the display functions ; spatial model output is dynamically mapped onto the map background as animated topical map coverages. Textual, numerical, and pictorial attributes of an object, and meta data providing background infor­mation to the user, are accessible through a multi-media hypertext system, that objects use to present themselves to the user. The multimedia nature of the system's interface also makes its extension into a networked client/ server version for access through the World Wide Web straightforward.

INTRODUCTION

River basin management has obvious spatial dimensions, since it is focused on a spatial unit, the hydrological catchment, in the first place. This makes the use of GIS, and its

670 K. Fedra & D. G. Jamieson

integration with traditional water resources models, and obvious strategy for the development of river basin management systems (Fedra, 1993a; Maidment, 1993).

While the GIS is used to capture, analyse, and display spatial data, the models provide the tools for complex and dynamic analysis. Input for spatially distributes models, as well as their output, can be treated as map overlays and topical maps (Fedra, 1994). The familiar format of maps supports the understanding of model results, but provides also a convenient interface to spatially referenced data. And expert systems, simulation and optimization models add the possibility for complex, and dynamic analysis to the GIS (Fedra, 1992, 1993b).

The main challenge in building effective river basin information systems is the integration of dynamic models with the capabilities of GIS. The GIS can provide a common framework of reference for the various tools and models addressing a range of problems in river basin management. In a multi-media framework, it can also provide a common interface to the various functions of an integrated river basin information and decision support system. This interface has to translate the data and model functionality available into information that can directly support decision making processes (Fedra, 1995).

Obj ect-oriented design provides some of the flexibility for building highly integrated information systems, utilizing existing software components, but supporting a high degree of customization (Abbott 1993; Raper & Livingstone, 1995).

The Water Ware system

Developed originally within the framework of a EUREKA project (EU 487), and in a case study of the River Thames, Water Ware has been further developed for applica­tions to the Lerma basin in Mexico in a project with the National Water Commission (Jamieson & Fedra, 1995), and both the West Bank and the Gaza strip in Palestine, in a project with the Palestinian Hydrology Group (Jamieson & Fedra, 1996b). The system is based on a modular framework of GIS and databases, that allows to link various simulation and optimization models into this framework, providing a common user interface and consistent, shared data resources as well as mechanisms for the communication between the modules of the system (Jamieson & Fedra, 1996a). From a users point of view, Water Ware consists of a central information systems component with GIS and databases as well as the multi-media hypertext system, that provides background information and describes a specific river basin. Linked to this data layer are a set of models, that can perform scenario analysis, i.e. answer WHAT-IF and HOW-TO questions for various water quantity and quality issues, as well as related engineering, environmental, and economic aspects (Fedra & Jamieson, 1996). Water Ware currently includes a dynamic (daily) rainfall-runoff model; an irrigation water demand estimation model based on FAO's CROPWAT; a 2D, vertically integrated finite-difference groundwater flow and transport model; a dynamic water resources model; and both a stochastic and a dynamic river water quality model, that use a waste load allocation optimization model as a post-processor, and a rule-based environmental impact assessment expert system.

These tools are embedded into a user interface that translates the specific functionality of a given model into a decision support tool: the component models and

An object-oriented approach to model integration 671

tools are restructured in terms of decision variables and performance variables, relating to the objectives, criteria, and constraints of various tasks and decision problems.

River basin objects

Water Ware describes a river basin by sets of interacting objects, which are spatially referenced. RiverBasinObjects represent real world entities: such as catchments, reservoirs, cities, or treatment plants. NetworkObjects represent a different layer of (model specific) abstraction, including the nodes and reaches of a network representation of the surface water system. ScenarioObjects represent model oriented collections of instantiations of NetworkObjects that are partially derived from, and linked to, the RiverBasinObj ects.

All objects are spatially referenced, that is, they are known by location, both through their coordinates as well as through being members of larger geographical object classes such as administrative units (states, provinces, communities) or hydro-graphic units (subcatchments). This allows their display on the various maps and the selection of objects from the map, as a single point (observation station), as a reference point designating a larger object (lake, city), as a rectangle including one or several points or polygons (irrigation district), or a as polygon (subcatchment). It also makes it possible to aggregate or average their behaviour over these units. The GIS provides the base layer of data, as well as a set of display functions (Fig. 1).

Objects have two main functions: - they can obtain or update their current state (load, compute, infer, etc.) in a given

context, referring to sources of information (which may be other objects); - and they can report their current state or parts of the their state to clients (an X

Windows server, an http client, to each other, to models, a hard-copy device, etc.). For example, subcatchment objects (Fig. 2) use the rainfall-runoff model RRM

(Fig. 3) to obtain the runoff from the catchment under a set of landuse, internal water use, and meteorological conditions (the latter are obtained as time series from one or several climate station objects) ; this runoff, in turn, is used by the water resources model WRM as input for a start node (subcatchment node). In the same way, demand nodes in WRM are linked to various river basin objects (settlement, industries, irrigation districts), and obtain their detailed behaviour over time (e.g. water demand, consumptive use coefficients, losses, etc.) from these objects. Through the location of objects, the linkage to the GIS layers is established, so that spatial concepts (such as catchment, river reach, or the neighbourhood of a point location, elevation, slope, and distance) can be used for calculations (methods) by the objects.

The RiverBasinObjects in Water Ware are grouped by classes. Classes currently supported are:

Climate stations Industries Gates and sluices Flow stations Animal farms and feedlots Abstractions Water quality station Irrigation districts Cross-sections Observation time series Subcatchments Aquifers Settlements Dams and reservoirs Wells Water works Natural lakes Boreholes Treatment plants Weirs and falls Scenic sites

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674 K. Fedra & D. G. Jamieson

Each of these classes may have any number of elements. Each class has a set of specific attributes, organized in a set of data structures and associated methods.

Individual objects (instantiations) inherit their basic properties from their class. They may be linked to other objects, for example, a treatment plant may lead on to a flow and a water quality observation station and its data, and objects have links to hypertext files that provide further explanation, meta data, and context. Objects have methods available, which allow them to obtain some of their dynamic or derived individual properties in a specific context. Many object properties are static and can be stored in their respective databases and files; since methods are arbitrary functions, these references can be simple read statements from local files, an embedded SQL call to a local or network-accessible database, or a URL for a call to an http server over local or wide-are networks, or any remote procedure call (rpc) that can utilize a remote information resource.

Other object properties, such as the outflow from a subcatchment or the monthly water requirements of an irrigation district, depend on numerous controlling variables or plans, decisions, and assumptions, that is they have their own context and possibly need to update their state if the context has changed. Models such as the RRM rain-runoff model or the irrigation water demand estimation model can be triggered by the respective objects (i.e. subcatchments, irrigation districts) to estimate such values as their attributes. They can in turn be fed to a subcatchment start node or an irrigation demand node in the river network, and provide input the corresponding simulation models. Alternatively, the context can be defined by a model specific scenario (including, for example, the selection of a specific year or period and its hydrometeorological characteristics), and, within this constraint, by a set of user specified assumptions.

A practical example

To demonstrate the interaction of the various objects in WaterWare and their linkage to the GIS level, consider the following example of a typical waste management problem. It is, however, embedded into a broader water resources management context. For a given subsection of the river network, severe water quality problems are observed due to massive BOD load from industrial, domestic, and agriculture sources, aggravated by reduced flow due to massive abstractions for irrigation purposes.

In terms of the components of WaterWare, the ultimate decision problem is supported by the waste load allocation model, a post-processor of the water quality models. Alternative treatment strategies or technologies, each with investment and operating costs are required for each of the sources considered. Sources can include both point sources such as treatment plants or diffuse sources such as intensively used agricultural areas, each represented by the corresponding RiverBasinObject. They are used together with the simulation model results to find a cost efficient strategy to meet water quality targets.

Input to the water quality model (the model's ScenarioObjects) comes in part from the RiverNetworkObjects, in part from the Water Resources Model that provides the flow regime for a range of demand and supply conditions. The Water Resources Model, in turn, uses its own ScenarioObjects and their RiverNetworkObjects that supply the available flows as well as the water demand in the network. The dominant agricultural

An object-oriented approach to model integration 675

water demand can be computed by models such as the Irrigation Water Demand Model, and, where the conjunctive use of surface and groundwater is important, by the groundwater resources model. The available flow for the subcatchments feeding into the network comes either from the observation time series of an observation station (a RiverBasinObject), or is computed by the rainfall-runoff model. The latter, in turn, uses the information from a subcatchment object (which provides geometry and land use) together with the time series for precipitation and temperature from one or several hydrometeorlogical observation stations.

The river network

The water quality model uses a network representation of the river section under study; this network provides the river geometry, as well as the linkage to the functional elements. River networks consist of the following object classes: the RiverNetwork itself, RiverNodes, Reaches, and CrossSections.

A RiverNetworkObject may contain a set of RiverNode, Reach and CrossSection objects. Each of these object classes have data which can be divided into two layers, a generic and a model specific one. While there is a single generic representation for each network which primarily contains the connectivity information and provides the linkage to the actual geographical, positional information, there may be several model specific extensions for different models and their different data requirements. RiverNodes are inheriting basic information from the corresponding RiverBasinObjects; Reaches can also derive some of their attributes such as lateral inflow from RiverBasinObjects, e.g., an irrigation district or an aquifer.

A specific interactive network editor assists in the design of networks and facilitates the linking of concrete RiverBasinObjects to the abstract RiverNodes of the schematic network. In addition to inheritance of properties from these objects, the embedded expert system supports estimation of node- or reach specific parameters such as roughness.

Model integration

Both the water resources model as well as the water quality model (Fig. 4) use network-based scenarios. Through sharing the generic layer of the RiverNetworkObject, and therefore the linked RiverBasinObjects, the consistency of the scenarios of various related models can be guaranteed.

The models, though spatially distributed, operate on a schematic representation of the river; this, in turn, is linked to the actual spatial location, and thus can be mapped at the GIS level, through the spatially referenced RiverBasinObjects of the system, which in turn link to the spatial objects (overlays) in the GIS.

A different strategy is used for the spatially aggregated irrigation water demand estimation model and the rainfall-runoff model. They both operate with spatially averag­ed parameters defined for unit irrigation ares or hydrologically homogeneous subcatch­ments. These parameters are derived from the underlying, more detailed spatial objects such as a digital elevation model, and geological, soil, and landuse maps. The translation

676 K. Fedra & D. G. Jamieson

between a fully spatially explicit description, where available, and the model's interpretation is accomplished by the methods of the ModelScenarioObject that draws its data from the respective RiverBasinObjects and their underlying GIS layers; when using alternative models, that have a different spatial resolution, the only necessary change is the addition of another method to derive the appropriate data representation.

Discussion

For any practical information and decision support system, it often becomes necessary to use more than a single model representation for different aspects of the same problem. The differences between a fully spatially distributed dynamic simulation model and an optimization model that usually requires a somewhat simplified physical representation of the system should illustrate this point. The need for interactive use, as well as limited data availability in practical applications, in many cases poses additional constraints in terms of resolution, complexity, and computational performance of models.

To make the use of alternative models both efficient and consistent in terms of the underlying data, including the coupling to the spatial data that are central to any environmental information and decision support system, a flexible strategy is required. An object oriented design and implementation, that links spatial data objects with dynamic model objects through a set of methods that encapsulate the interpretation and data requirements of the model seems to provide the necessary flexibility and efficiency to build complex yet easy to use and directly useful - which also means highly customized — environmental information systems.

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Fedra, K. (1993a) Models, GIS and expert systems: integrated water resources models. In: Application of Geographic Information Systems in Hydrology and Water Resources Management (ed. by K. Kovar & H. P. Nachtnebel) (Proc. Int. Conf. HydroGIS'93, Vienna, April 1993), 297-308. IAHS Publ. no. 211.

Fedra, K. (1993b) Expert systems in water resources simulation and optimization. In: Stochastic Hydrology and its Use in Water Resources Systems Simulation and Optimization (ed. by J. B. Marco, R. Harboe & J. D. Salas), 397-412. Kluwer Academic Press Publishers.

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Jamieson, D. G. & Fedra, K. (1996a) The WaterWare decision-support system for river basin planning: 1. Conceptual design. / . Hydrol., special issue, in press.

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