Managing resources in a major irrigation scheme needs more attention on system performance in order to get optimum production out of available resources. In Sri Lanka most major irrigation schemes are managed using conventional management strategies together with the traditional experiences of farmers and managers. In most instances a systematic approach for observation or resource use and management are not adhered to either by scheme managers or by farmers. It is often observed that this results in low productivity. As such there is a need to evaluate irrigation scheme performance using suitable performance indicators in order to identify shortcomings and to find out solutions for increasing the productivity of such schemes. Since there are many factors affecting productivity of an irrigation scheme, most relevant factors should be identified in order to ascertain the most relevant data, minimum time, money, and expert services are spent. It is commonly believed that the present way of data collection by the majority for scheme evaluations do not serve the purpose since they are not designed for Sri Lanka’s national needs. The present work is towards the development of a suitable performance assessment program for irrigation schemes in Sri Lanka considering water use efficiency, irrigation practices and land productivity. A critical comparison and review of available indicators were done considering the adequacy to monitor service delivery, productivity and agricultural economics and financing on irrigation system sustainability. One new indicator for water service delivery reflecting the effect of actual rainfall received was identified in this study along with two new indicators as Government Involvement and Beneficiary Involvement. This is proposed to monitor system sustenance which is a very important issue in the light of recent state policy of handing over of irrigation schemes to farmers. The present work after a systematic evaluation identified eleven suitable indicators for system performance measurement that would require minimum efforts on additional data collection and mobilising of fresh resources
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