Long-term Monthly Discharge Prediction for Cimanuk Watershed

Marliana Tri Widyastuti, Muh Taufik


Although streamflow data is important for water resource planning, it’s long-term availability for Indonesian rivers is limited. One factor could be identified for example lack of observation. Here, we presented observation-based modeling to predict long-term discharge data for Cimanuk watershed in Indonesia. The watershed is categorized as one of the critical watersheds, meanwhile it supports to more than one million people. A well-known hydrological model called Soil and Water Assessment Tools (SWAT) was used to predict monthly discharge. The model was fed with monthly climate data, topography, land use and soil characteristics. We calibrated the model with the observed data from 1974 to 1994 (20 years). Our results showed that the model was a good performance in estimating monthly discharge as indicated by three statistical metrics used. Based on statistical evaluation, the calibration resulted a low percent bias (3.20%), strong correlation (0.73), and high Kling-Gupta Efficiency (0.78). Further, we did a sensitivity analysis for the model, and we found that hydrological response unit was the most influential parameters for the Cimanuk watershed. A long-term discharge data indicated a monsoonal pattern for this watershed.


Marliana Tri Widyastuti
Muh Taufik
mtaufik@apps.ipb.ac.id (Primary Contact)
WidyastutiM. T., & TaufikM. (2019). Long-term Monthly Discharge Prediction for Cimanuk Watershed. Agromet, 33(2), 96-104. https://doi.org/10.29244/j.agromet.33.2.96-104
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