Forecsting of Hydrological Time Series Data with Lag-one Markov Chain Model

Malaysia’s climate is overwhelmingly characterised by uniform temperature, high humidity, copious rainfall and light winds. As in any parts of equatorial doldrums, intermittent rain and sunshine within a day is a norm, as such, a long period of clear sky is rare. One of the commonly identified problems in water resource management in Malaysia is unavailability of long-term historical records. Where there is data availability, it was found to be discontinuous. Since forecasting using rainfall data requires long-term continuous recorded historical data, a stochastic type of model simulation that can cope with these situations is proposed.