Ayob Katimon

Hydrological behaviour of a drained agricultural peat catchment in the tropics. 2: Time series transfer function modelling approach

Abstract Transfer function models of the rainfall–runoff relationship with various complexities are developed to investigate the hydrological behaviour of a tropical peat catchment that has undergone continuous drainage for a long time. The study reveals that a linear transfer function model of order one and noise term of ARIMA (1,0,0) best represents the monthly rainfall–runoff relationship of a drained peat catchment. The best-fitted transfer function model is capable of illustrating the cumulative hydrological effects of the catchment when subjected to drainage. Transfer function models of daily rainfall–runoff relationships for each year of the period 1983–1993 are also developed to decipher the changes in hydrological behaviour of the catchment due to drainage. The results show that the amount of rain water temporarily stored in the peat soil decreased and the catchment has become more responsive to rainfall over the study period. Editor Z.W. Kundzewicz; Associate editor D. Hughes Citation Katimon, A., Shahid, S., Abd Wahab, A.K., and Shabri, A., 2013. Hydrological behaviour of a drained agricultural peat catchment in the tropics. 2: Time series transfer function modelling approach. Hydrological Sciences Journal, 58 (6), 1310–1325.

Hydrological behaviour of a drained agricultural peat catchment in the tropics. 1: Rainfall, runoff and water table relationships

Abstract Hydrological data of a drained tropical peat catchment have been analysed through conventional quantitative hydrological approaches to characterize its hydrological behaviours and changes due to continuous drainage for a long period. The results show that the hydrology of the catchment is extremely dynamic and the catchment is flashy in nature. A decreasing trend in peak flow amount and an increasing trend in baseflow amount was observed in the catchment, indicating that continuous drainage has reduced the risk of both flooding and water scarcity in the catchment. Correlation analysis among rainfall, runoff and groundwater table reveals that saturation excess-near surface flow is the dominant mechanism responsible for rapid runoff generation in the catchment. Therefore, any physical alterations or disturbances to the upper part of the peat profile would definitely affect the overall hydrological behaviour of the peat catchment. Editor Z.W. Kundzewicz; Associate editor D. Hughes Citation Katimon, A., Shahid, S., Abd Wahab, A.K., and Ali, M.H., 2013. Hydrological behaviour of a drained agricultural peat catchment in the tropics. Part 1: Rainfall, runoff and water table relationships. Hydrological Sciences Journal, 58 (6), 1297–1309.

Modelling surface runoff in a large-scale paddy field in Malaysia

A few models to simulate surface runoff generation at the agricultural field scale are available. However, most of the available models are developed for particular setup with certain assumptions, which preclude their universal use. There are no guidelines to choose a model best suited for a particular agricultural field. The major objective of this study is to estimate the surface runoff in the Muda irrigation scheme, by applying seven well-known hydrological models. The surface runoff amounts estimated using these models are compared with the observed runoff collected at an agricultural block in the scheme. The model performances are evaluated based on the mean runoff to precipitation ratio, relative mean absolute error, and the coefficient of determination criteria. The results suggest that the Smith-Parlange nonlinear model has matched satisfactorily with the observed surface runoff. The performances of the Philip, ARNO and Morel-Seytoux models are found to be close to the Smith-Parlange model. Thus, the mean runoff estimated by Smith-Parlange, Philip, ARNO, and Morel-Seytoux models can be regarded as the surface runoff in the study area.

Modeling water quality and hydrological variables using ARIMA: a case study of Johor River, Malaysia

Long-term trends in water quality and hydrological variables of natural systems reveal information about physical, chemical and biological changes and variations due to manmade and seasonal interventions. The objective of this study was to develop suitable stochastic models for predicting river water quality and hydrological variables through the establishment of dynamic relationship among the variables using transfer function modeling approaches. Autoregressive integrated moving average (ARIMA) model containing autoregressive (AR), integrated (I) and moving average (MA) was used for this purpose. The water quality variables, namely pH, color (TCU), turbidity (ppm), Al3+ (ppm), Fe2+ (ppm), NH4+ (ppm) and Mn2+ (ppm), and hydrological variables, namely rainfall and river discharge for Johor River, Malaysia, recorded for the period 2004–2007 were used in the study. Results showed that except Al3+, Fe2+, NH4+ and rainfall, all other variables are stationary. The non-stationary time series can be fitted with ARIMA (p, 1, q), while the stationary time series can be fitted with AR model with 1–5 time lags. The autocorrelations of all the samples were found within the 95% confidence bounds and the model residuals were found to follow normal probability distribution, which indicate the suitability of the models in forecasting water quality and hydrological variables. It is expected that the modeling approach developed in this paper can be replicated in other river basins for reliable prediction of river water quality due to changes in rainfall–runoff processes.