Reseach Approach

Software for Spatial Modelling
The TYDAC SPANS GIS Ver 5.3 (1993) and Ver. 5.4 (1994) running on IBM Operating System 2 (OS/2) was the GIS software environment used for hydrological modelling. In addition, GIS and image processing facilities available in ERDAS Ver. 7.5 and IDRISI operating in DOS environment were also used for data conversion, formatting and processing.

Data for Hydrological and Spatial Modelling
Daily rainfall data for a period of 30 years (1964 - 1993) from 64 gauging locations in the UMCA or its close proximity were collected and formatted for Lotus 1-2-3 and Approach database. Fog interception data were retrieved from recent research results carried out in Horton Plane and Kundasale, Sri Lanka. Pan evaporation data were also collected for seven (7) locations within UMCA to generate open-water evaporation parameters. Flow data were also collected for nine (9) stations for the same 30-year period. Hydrological model parameters were derived from the supervised classification of IRS LISS II imagery for different land use categories based on their hydrological significance. In the classification process, a systematic random sampling with a sampling fraction of 1.16 was adopted for the ground truth information. Direct expansion estimates from ground data and image classification were compared. The resolution used for the classification was 40 m. An extensive GPS survey was carried out to determine the location information for gauging stations and ground truth sampling frames.

Hydrological Modelling
The UMCA hydrological model is a simplified version of a set of water balance equations to calculate runoff response from the catchment. It calculates daily runoff depending on the daily precipitation while taking water losses and soil moisture fluctuations into account. The lumped hydrological model was structured as a Turbo C++ programme. The model includes the basic hydrological processes as shown in Fig. 01. The total precipitation includes rainfall and fog interception (Gunawardene, 1996) in natural forests and forest plantations where elevation is 1000 m from mean sea level. The interception is estimated by means of an exponential stochastic interception model (Calder, 1986). Evaporation is approximated using soil moisture and moisture stress moderator (Robert and Harding, 1996). A water balance was simulated for each day. Depending on the available water status which was derived from hydrologically important land use categories, runoff predictions were made for the individual day.

Spatial Modelling in GIS
The lumped hydrological model was required to run on a spatial platform to estimate the river flow status. In selecting the modelling functionality in SPANS GIS, the main criterion was the capability of direct spatial data processing in the modelling exercise. Map modelling functionality was chosen ahead of table modelling and point modelling considering its capability of linking spatially distributed data and imported attribute data efficiently in binary form. Map modelling allows to use spatially distributed and tabulated data through various mathematical processes to derive associated data and information. It was noted that the accuracy of model representation was dependent on the quad resolution of the data and data analysis process. Hence, the selection of the best quad level was made carefully after considering the accuracy of data representations, storage requirements, and computational efficiency. The quad level 11 was rated as the best in terms of these variables. Several interpolation methods were attempted to represent spatial distribution of rainfall in GIS. Thiessen polygon method was adopted due to its computational efficiency with the time invariant spatial boundary demarcation.

Spatial Model Structure
A series of equations were formulated using map modelling language codes of SPANS GIS. Each sub model of the UMCA hydrological model was represented in a set of equations and additional equations were required to increment the file pointer along the columns of the data tables for daily rainfall. In the case of Thiessen polygons, representative areas for each gauging station are directly identified from the morton numbers of the gauging locations. Morton numbers are hexa-decimal numbers used for spatial referencing in SPANS GIS. For a particular day, the hydrological model reads the relevant column of the rainfall data tables and calculate the fog interception according to the season. The total precipitation is then assigned to the corresponding Thiessen polygons. Based on sub models, it calculates the spatial distribution of interception and evaporation losses according to the hydrological parameters assigned for each land use. It also takes into account the spatial variation of antecedent moisture and the soil moisture stress. Finally, the model calculates the daily runoff and changes in soil moisture regime through the water balance equations. It then updates spatial coverage for cumulative runoff, soil moisture, cumulative interception and evaporation, stored in thematic maps. The updated map of soil moisture provides antecedent moisture status for the water balance calculations of the following day. The entire model structure was set-up to run on actual numerical values of each quad cell of thematic coverage.

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