Suspended sediment, which is an important water quality characteristic concerning effluents from agricultural areas, was studied in relatively small rivers that drain agricultural watersheds with considerable rice paddy areas. Suspended sediment load (SL) was observed daily for thirty three months and analysed – applying data stratification. Suspended sediment prediction models were established and the effect of rice transplanting activities on the rivers' SL was estimated. Results showed that data stratification improved the discharge–SL correlation and reduced regression and curve-fitting errors, thereby improving the efficiency of the derived model equations. Clustering the months into the rice- and non-rice transplanting seasons also improved the resulting regression equations, although not statistically significantly. Suspended SL was found to be higher during the rice transplanting season and the activities contributed a considerable amount of suspended sediment during the period, supporting the conjecture that sediments come from sources other than natural soil erosion.

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