Ian W. Makin

A water-productivity framework for understanding and action

In Kijne, J. W.; Barker, R.; Molden. D. (Eds.). Water productivity in agriculture: limits and opportunities for improvement. Wallingford, UK: CABI; Colombo, Sri Lanka: International Water Management Institute (IWMI)Comprehensive Assessment of Water Management in Agriculture Series 1

Limits to leapfrogging: issues in transposing successful river basin management institutions in the developing world

In Mollinga, P. P.; Dixit, A.; Athukorala, K. (Eds). Integrated water resources management: global theory, emerging practices and local needs. New Delhi, India: Sage

A simple water balance modelling approach for determining water availability in an irrigation tank cascade system

Abstract This paper presents a water balance model Cascade formulated to account for the dynamic hydrologic components of an irrigation tank cascade system in Anuradhapura, Sri Lanka. The model is designed to estimate tank water availability on a daily basis, for the purpose of improving productive use of water resources in the tank cascade system. It represents the physical system using a node–link system configuration, and incorporates water balance components of different types of irrigation tanks including rainfall runoff, rainfall on tank, evaporation of tank water, tank seepage and percolation, irrigation water release, spillway discharge and return flow from upstream tanks. An important feature of Cascade is that it employs a modified runoff coefficient method for estimating runoff from rainfall, which incorporates a modified Antecedent Precipitation Index as an indicator of catchment wetness. This provided a simplified method for representing the non-linear runoff generation process. The model calculates tank seepage and percolation based on functions derived from an analysis of the observed tank water reduction during time periods without rainfall. The model was calibrated using field data collected at four tanks over a period of 21 months, which represented different agrometeorologic conditions encountered under both Maha and Yala growing seasons at the Thirappane tank cascade system in Anuradhapura, Sri Lanka. The model results agreed well with the measured data particularly in the two tail end tanks of the cascade, and clearly manifested the relative magnitudes of the tank water balance components and their temporal variations. An independent validation of the model could not be performed with the available data and thus the predictive capability of the model is not evaluated. The results of this study suggests that, with further improvements, the simple water balance modelling approach used in the model could potentially provide a basis for the development of a useful tool in the process of optimising usage of the limited water resources in similar tank cascade systems.