Prediksi Debit Aliran Musiman Berdasarkan Pendekatan Hidrologi Stokastik

Darmadi Darmadi(1*)

(1) Jurusan Teknologi Pangan dan Hasil Pertanian, Universitas Gadjah Mada, Yogyakarta
(*) Corresponding Author


Objective of the research is to predict seasonal river flow discharge from the several years previous data. Stochastic statistical theory of Markov's lag-1 was used to analyze the data. Modification has been needed for changing the number of total seasonal river flow from 2 to 24 in one year serial observation. The total 24 rivers flow observations based on a half-month time interval observation per year. Those interval based on the assumption irrigation interval has been practicing at the tertiary level. River flow discharge data from 1993 to 2003 of Cikunten and Cimulu river in Tasikmalaya (West Java) were used during the research. The model prediction shows that there is similarity between real flow and synthetic flow of the river from time to time observation. Therefore, application of modified Markov's lag-1 is valid for stochastic hydrological analysis in term of maintaining


Stochastic model; river flow; predicting

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agriTECH (print ISSN 0216-0455; online ISSN 2527-3825) is published by Faculty of Agricultural Technology, Universitas Gadjah Mada in colaboration with Indonesian Association of Food Technologies.

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