Prediction of the Daily Rainfall at Ungauged Regions Applying the Spatio – Temporal Neyman - Scott Rectangular pulses Method (Case Study: The Walnut Gulch Watershed)

Author

• Mahmoud Zakeri Niri

Abstract

       Rainfall data play an important role in hydrological sciences. Lack of sufficient or qualified data usually leads to unreliable and inadequate results. In such cases, synthetic time series, e.g., generated rainfall time series, are of great importance for performing the watershed management activities. In most previous studies, statistical methods such as those of Markov chain and ARIMA methods have been applied for the rainfall generation at a single site. As the rainfall spatial pattern has a significant effect on the flow hydrograph characteristics, multisite rainfall generation plays its vital role in hydrology. In the present research, the Spatio-temporal Neyman-Scott rectangular pulses (STNSRP) method was applied and fitted to 50-year daily data taken from 20 Rain gauges in the Walnut Gulch watershed, USA. Rain gauges were divided into real rain gauges (14) and virtual rain gauges (6), and the performance of STNSRP model was assessed. Different statistics such as mean, variance and probability of dry days were calculated and compared with both the generated and the observed rainfall time series.  The IDW method was used to produce rainfall maps using the generated rainfall values at real and virtual rain gauges. Results revealed that the STNSRP model has the ability to match the observed statistics adequately. Also, the rainfall map generated using the virtual rain gauges has less error as compared with the map generated from the rainfall values only at the real rain gauges.

Keywords

• Daily rainfall generation
• Point process model
• STNSRP model
• Walnut Gulch Watershed

20.1001.1.20086377.1395.9.31.8.5

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