A stochastic rainfall generator model for simulation of daily rainfall events in Kurau catchment: model testing

Abstract

Reservoirs play a substantial role in meeting water demands in arid and semi-arid regions especially with increasing changes in global rainfall patterns. Kurau catchment located at Northwest Perak, Malaysia, is the largest source of water to Bukit Merah Reservoir. Based on climate change effects on rainfall pattern, it is important to develop a model to simulate rainfall occurrence and amount that flow into the reservoir. To address this problem, a stochastic rainfall generator model based on first-order two-state Markov chain approach was developed to simulate long-term daily rainfall series. Rainfall time series for a 30-year period (1976-2006) was assessed. The observed time series data were used as input to the stochastic model to generate a new set of daily time series data. The statistical properties of the new set of data including monthly mean, standard deviation, dry and wet spell lengths were compared with the observed data to gauge the model accuracy. The results obtained were satisfactory, giving motivation in applying the model for generating future rainfall series under different climate change scenarios.

Long-term rainfall projection based on CMIP6 scenarios for Kurau River Basin of rice-growing irrigation scheme, Malaysia

“…Table 1 shows a list of rainfall stations chosen for the study area. The data selected are within the study area due to the availability and suitability of the data for coupling with a stochastic rainfall generator [23]. The period of data used in this study is from 1976 to 2005 to validate rainfall from the CMIP6 model (historical period).…”

“…In comparison, Semenov and Barrow (1997) developed semi-parametric models that applied semi-empirical distributions to simulate rainfall processes. Details for further review on their history and previous successful application can be found from Wilby [22], Dlamini et al [8], Fadhil et al [23], and Liu et al [24].…”

Penerapan Model Pembangkit Curah Hujan Stokastik untuk Simulasi Curah Hujan Harian di Stasiun Badan Meteorologi Klimatologi dan Geofisika (BMKG) Kertajati Jawa Barat

“…Model pembangkit curah hujan stokastik merupakan model stokastik yang menggunakan data meteorologi historis untuk membuat deret waktu harian berdasarkan parameter. Pembangkit curah hujan stokastik sering menggunakan pendekatan rantai Markov untuk menggambarkan kejadian curah hujan dan jumlah curah hujan dengan memasang fungsi distribusi untuk semua hari hujan (Fadhil, 2017).…”

“…Model pembangkit curah hujan stokastik menggunakan pendekatan rantai Markov untuk menggambarkan kejadian curah hujan dan untuk membangkitkan jumlah curah hujan dengan menggunakan fungsi distribusi (Fadhil, 2017). Pemodelan Kejadian Curah Hujan Kejadian curah hujan dimodelkan menggunakan pendekatan rantai Markov.…”

Rainfall-Runoff Models with Fractional Derivatives Applied to Kurau River Basin, Perak, Malaysia

“…KRB is located between 04 51′ N and 05 10′ N latitude and 100 38′ E to 101 01′ E longitude in Perak State of Malaysia, having an area of 322 km 2 and being the main drainage artery pouring into Bukit Merah Reservoir (BMR) (Fadhil et al, 2017). Analysis of rainfall-runoff processes in KRB is important because BMR is the key structure for rice production, flood control, ecosystems, and tourism in the region (Hamidon et al, 2015).…”