Ensemble Flood Prediction by Cascading the Uncertainty From Rainfall to Runoff Short-Term Prediction

Abstract

Ensemble short-term rainfall-runoff prediction in urban river basin is presented. An ensemble rainfall prediction is built by perturbing initial condition of the extrapolation model. The five ensemble members are subsequently considered as uncertain input of the distributed hydrological model. GLUE method is used to calibrate the rainfall-runoff model and quantify the uncertainty. Four sensitive parameters of rainfall-runoff model are considered. The set of behavioral simulations develop an ensemble of flood prediction. This approach allows a cascading of uncertainty from rainfall prediction to the flood prediction. The methodology is demonstrated throughout case studies in Kofu urban river basin, Japan. Having demonstrated the plausible results, this approach could serve as a reliable and effective method for estimating the uncertainty range of short-term prediction of runoff dynamics for operational flood disaster prevention in urban area.

Distributed flood simulation based on satellite rainfall data at the Ciliwung River Basin, Jawa, Indonesia

“…Recently, the intensity of rainfall has increased and its local variation such as diurnal cycle is very high [9,10]. Several studies related with rainfall-runoff simulation have been conducted especially in Jakarta and surrounding regions [11][12][13]. The short-term extreme rainfall response to the flash flood events, therefore the distributed hydrological model was needed for detecting and taking preventive measures.…”

Prediksi Hujan untuk Manajemen Bencana dan Risiko Pertanian

“…Pendekatan struktural menitikberatkan pada pembangunan fisik, misalnya konstruksi bendungan atau rekayasa bangunan tahan bencana. Pendekatan non-struktural dilakukan melalui peningkatan kesiapsiagaaan dan kemampuan untuk menghadapi tingkat bahaya bencana (Hapsari et al, 2012;Ginige et al, 2022;Jayawardhena, 2015).…”

“…Pengamatan dan peramalan atas kejadian, intensitas, dan evolusi bencana hidrometeorologi merupakan komponen penting dalam upaya mitigasi non-struktural. Dalam analisa respon permukaan terhadap hujan, model hidrologi dengan input data hasil prediksi curah hujan yang akurat menjadi syarat utama dalam setiap sistem deteksi dini bencana hidrometeorologi (Syarifuddin, 2018;Syarifuddin et al, 2009;2017a;Hapsari et al, 2012;Jayawardhena, 2015).…”

“…Metode ekstrapolasi digunakan untuk nowcasting, dan diakui superioritasnya dalam mitigasi banjir bandang, longsor, maupun aliran debris (Hapsari et al, 2012;2019;Syarifuddin et al, 2017a). Metode ekstrapolasi mengidentifikasi pergerakan sistem cuaca berdasarkan data hujan di masa lampau hasil pengamatan satelit atau radar cuaca.…”

“…Salah satu model ekstrapolasi adalah model translasi (Shiiba et al, 1984;Hapsari et al, 2012). Model ini memprediksi pergerakan awan hujan yang dinamis dari perubahan intensitas hujan menurut waktu dan ruang berdasarkan vektor adveksi penentu pergerakan awan secara horizontal.…”