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Physically based hydrological modelling
S.M. Seth
Director, National Institute of Hydrology
Roorkee-247667 (U.P.), INDIA
nihr@sirnetd.ernet.in
The Mahaweli
Development Programme in Sri Lanka was implemented with the aims of providing
water to the dry zone of the country through a massive diversion scheme and also
generating hydropower.
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The Mahaweli is the longest river in Sri Lanka, covering a catchment area of 10,400 sq. km. The upper catchment is defined as the area above 150 m elevation from mean sea level encompassing an area of 3124 sq.km. The Mahaweli Development Programme, a major undertaking in the Upper Mahaweli Catchment Area (UMCA) was implemented with the aims of providing water to the dry zone of the country through a massive diversion scheme and also generating hydropower. Under this development programme, a series of large reservoirs was constructed across the main water course at Kotmale, Polgolla, Victoria, Randenigala and Rantembe. The construction of these reservoirs inundated a considerable agricultural land area (5400 ha) and the accompanied developments were responsible for the displacement of several settlements (14000 families).
The changes made on the catchment environment are very prominent due to both the short time span in which they occurred and the high magnitude of the impact. The diplaced peasants have been settled in the unsuitable terrain. Steep slopes have been put under cultivation without proper conservation measures. Agricultural objectives have been derived to obtain short-term benefits without any concern on the sustainability of the land and water resources.
Present Problems and a Future Crisis
Critics now say that the hydrological regime has been adversely affected due to indiscriminate land use changes. It is also pointed out that the river flows have diminished significantly during the last two decades. Productivity of the agricultural land has declined. This has directly affected the income status of the farmers thus creating social problems. Further, reservoir siltation and eutrophication demand considerable maintenance expenditure. Frequent landslides have threatened human life and infrastructure. If these problems are not properly resolved, a future crisis is inevitable and that will jeopardise the expectations of the Mahaweli Development Programme.
Mitigation Concepts
A large-scale afforesttion/ reforestation scheme has been introduced considering the environmental benefits of the forest cover in terms of the hydrological stability and the sustainability of the catchment resources. However, the hydrological consequences of reforestation and the other land resource conservation measures could lead to high water losses from the catchment system. In contrast, trees at proper locations can intercept water from clouds and improve the water yield. Hence, it is required to find strategic locations for tree plantations to ensure positive water budget in the catchment while providing extensive benefits in the other sectors. This created the need for a comprehensive model to simulate the hydrological dynamics of the catchment to answer ‘what if’ questions for different conservation scenarios.
Hydrological Modelling and GIS
Most of the hydrological models are numerical and computer based, and assume some form of spatially averaging process for parameter definitions. The lack of recognition of spatial diversity at catchment sale has been a serious constraint hampering the simulation, validation and practical application of the hydrological modelling results.
In contrast, GIS is well suited for spatial modelling with large and complex databases. However, the present GIS have an inherent limitation of representing time in its spatial data structures. Hence, GIS and hydrological modelling can be considered as complimentary. GIS could benefit from the temporal modelling capabilities of hydrological models and hydrologic models can benefit from the spatial modelling capabilities of GIS. Within this conceptual framework, this study was focussed on developing a spatiotemporal hydrological model in GIS to investigate and analyse the hydrological dynamics and behaviour of UMCA in Sri Lanka.
Data and Software 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.
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.
Hydrological Modelling
Hydrological model parameters were derived from the supervised classification of IRS LISS II imagery for different land use categories based on their hydrological significance. An extensive GPS survey was carried out to determine the location information for gauging stations and ground truth sampling frames.
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 model includes the basic hydrological processes as shown in Fig. 1. The total precipitation includes rainfall and fog interception 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. Evaporation is approximated using soil moisture and moisture stress moderator . 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.
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