English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The aim of this study is to assess the uncertainty in precipitation using a distributed hydrological model. Firstly, a true model is established and then error is applied to true precipitation. The uncertainty is analyzed by using sensitivity analysis approach for systematic error and Monte Carlo approach for random error. Next, the parameters of the model are calibrated with erroneous data. Finally, the impact of low precipitation is assessed by neglecting different levels of low precipitation. The result of the study for a Nepalese river basin shows that a systematic error exceeding +/-10% causes significant impact on simulated flows. The impact of normally distributed random error with standard deviation equals to 10% of observed precipitation is not substantial. The calibration of parameters can adjust the low error, but the higher errors should not be compensated by just fitting the curve. Error on low precipitation of amount less than 0.5mm measured with some error does not affect the flood discharge.

AN ASSESSMENT OF UNCERTAINTY IN PRECIPITATION ON RUNOFF SIMULATION