A Comparative Evaluation of Short-Term Streamflow Forecasting Using Time Series Analysis and Rainfall-Runoff Models in eWater Source

被引:0
|
作者
Dushmanta Dutta
Wendy D. Welsh
Jai Vaze
Shaun S. H. Kim
David Nicholls
机构
[1] CSIRO Land and Water,CSIRO Water for a Healthy Country National Research Flagship
[2] DA Nicholls Pty Ltd,eWater Cooperative Research Centre
[3] University of Canberra,undefined
来源
关键词
Stream flow forecast; Time series analysis; Rainfall-runoff model; River system model; eWater source;
D O I
暂无
中图分类号
学科分类号
摘要
Over the past few decades, many numerical streamflow prediction techniques using observed time series (TS) have been developed and widely used in water resources planning and management. Recent advances in quantitative rainfall forecasting by numerical weather prediction (NWP) models have made it possible to produce improved streamflow forecasts using continuous rainfall-runoff (RR) models. In the absence of a suitable integrated system of NWP, RR and river system models, river operators in Australia mostly use spreadsheet-based tools to forecast streamflow using gauged records. The eWater Cooperative Research Centre of Australia has recently developed a new generation software package called eWater Source, which allows a seamless integration of continuous RR and river system models for operational and planning purposes. This paper presents the outcomes of a study that was carried out using Source for a comparative evaluation of streamflow forecasting by several well-known TS based linear techniques and RR models in two selected sub-basins in the upper Murray river system of the Murray-Darling Basin in Australia. The results were compared with the actual forecasts made by the Murray River operators and the observed data. The results show that while streamflow forecasts by the river operators were reasonably accurate up to day 3 and traditional TS based approaches were reasonably accurate up to 2 days. Well calibrated RR models can provide better forecasts for longer periods when using high quality quantitative precipitation forecasts. The river operators tended to underestimate large magnitude flows.
引用
收藏
页码:4397 / 4415
页数:18
相关论文
共 50 条
  • [1] A Comparative Evaluation of Short-Term Streamflow Forecasting Using Time Series Analysis and Rainfall-Runoff Models in eWater Source
    Dutta, Dushmanta
    Welsh, Wendy D.
    Vaze, Jai
    Kim, Shaun S. H.
    Nicholls, David
    WATER RESOURCES MANAGEMENT, 2012, 26 (15) : 4397 - 4415
  • [2] A Comparative Evaluation of Conceptual Rainfall-Runoff Models for a Catchment in Victoria Australia Using eWater Source
    Zafari, Najibullah
    Sharma, Ashok
    Navaratna, Dimuth
    Jayasooriya, Varuni M.
    McTaggart, Craig
    Muthukumaran, Shobha
    WATER, 2022, 14 (16)
  • [3] Estimation of the added value of using rainfall-runoff transformation and statistical models for seasonal streamflow forecasting
    Sittichok, Ketvara
    Seidou, Ousmane
    Djibo, Abdouramane Gado
    Rakangthong, Neeranat Kaewprasert
    HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES, 2018, 63 (04): : 630 - 645
  • [4] Using time domain and geographic source tracers to conceptualize streamflow generation processes in lumped rainfall-runoff models
    Birkel, Christian
    Tetzlaff, Doerthe
    Dunn, Sarah M.
    Soulsby, Chris
    WATER RESOURCES RESEARCH, 2011, 47
  • [5] Comparative evaluation of conceptual and physical rainfall-runoff models
    Jaiswal, R. K.
    Ali, Sohrat
    Bharti, Birendra
    APPLIED WATER SCIENCE, 2020, 10 (01)
  • [6] FORECASTING OF SHORT-TERM RAINFALL USING ARMA MODELS
    BURLANDO, P
    ROSSO, R
    CADAVID, LG
    SALAS, JD
    JOURNAL OF HYDROLOGY, 1993, 144 (1-4) : 193 - 211
  • [7] State space neural networks for short term rainfall-runoff forecasting
    Pan, TY
    Wang, RY
    JOURNAL OF HYDROLOGY, 2004, 297 (1-4) : 34 - 50
  • [8] Rainfall-runoff modelling using Long Short-Term Memory (LSTM) networks
    Kratzert, Frederik
    Klotz, Daniel
    Brenner, Claire
    Schulz, Karsten
    Herrnegger, Mathew
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2018, 22 (11) : 6005 - 6022
  • [9] UNCERTAINTY ON A SHORT-TERM FLOOD FORECAST WITH RAINFALL-RUNOFF MODEL
    Kardhana, Hadi
    Mano, Akira
    ADVANCES IN WATER RESOURCES AND HYDRAULIC ENGINEERING, VOLS 1-6, 2009, : 88 - 92
  • [10] SHORT-TERM FORECASTING OF SNOWMELT RUNOFF USING ARMAX MODELS
    HALTINER, JP
    SALAS, JD
    WATER RESOURCES BULLETIN, 1988, 24 (05): : 1083 - 1089