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

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Abstract

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.

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Abbreviations

ACCESS:

Australian Community Climate and Earth-System Simulator

ANN:

Artificial Neural Networks

AR:

Auto-Regressive

ARIMA:

Auto-Regressive Integrated Moving Average

ARMA:

Auto-Regressive Moving Averages

ARMAX:

ARMA model with exogenous or independent variables

AWBM:

Australian Water Balance Model

BoM:

Australian Bureau of Meteorology

CRC:

Cooperative Research Centre

CSIRO:

The Commonwealth Scientific and Industrial Research Organisation

DLL:

Dynamically Linked Library

GR4J:

Modele du Genie Rural a 4 parametres journalier

IHACRES:

Instantaneous unit Hydrograph And Component flows from Rainfall, Evapotranspiration and Streamflow data

IQQM:

Integrated Quantify and Quality Model

MAE:

Mean Absolute Error

MAPE:

Mean Absolute Percentage Error

MDB:

Murray-Darling Basin

MDBA:

Murray-Darling Basin Authority

MSM:

Monthly Simulation Model

NMOC:

National Meteorological and Oceanographic Centre

NSE:

Nash-Sutcliffe Efficiency co-efficient

NWP:

Numerical Weather Prediction

QPF:

Quantitative Precipitation Forecasts

R2:

Coefficient of Determination

REALM:

Resource Allocation Model

RM:

River Manager

RO:

River Operator

RR:

Rainfall-Runoff

SILO:

Spatialised Information for Landholders and Organisations

SIMHYD:

Simplified HYDROLOG

SMARG:

Soil Moisture Accounting and Routing Model

TIME:

The Invisible Modelling Environment

TS:

Time Series

WBE:

Water Balance Error

WIRADA:

Water Information Research and Development Alliance

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Acknowledgement

The following are greatly acknowledged for their contributions:

• Andrew Bishop, MDBA, for the Murray River system operators’ spreadsheets,

• Tom Pagano, CSIRO, for NWP data from WIRADA project and

• Kerrie Tomkins and Mohammed Mainuddin, CSIRO, for some very insightful review comments.

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Authors and Affiliations

  1. CSIRO Water for a Healthy Country National Research Flagship, CSIRO Land and Water, GPO Box 1666, Canberra, ACT, 2601, Australia

    Dushmanta Dutta, Wendy D. Welsh, Jai Vaze & Shaun S. H. Kim

  2. DA Nicholls Pty Ltd, Nicholls, ACT, 2913, Australia

    David Nicholls

  3. eWater Cooperative Research Centre, University of Canberra, Canberra, ACT, 2601, Australia

    Dushmanta Dutta, Wendy D. Welsh, Jai Vaze, Shaun S. H. Kim & David Nicholls

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  1. Dushmanta Dutta
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  2. Wendy D. Welsh
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Correspondence to Dushmanta Dutta.

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Dutta, D., Welsh, W.D., Vaze, J. et al. A Comparative Evaluation of Short-Term Streamflow Forecasting Using Time Series Analysis and Rainfall-Runoff Models in eWater Source. Water Resour Manage 26, 4397–4415 (2012). https://doi.org/10.1007/s11269-012-0151-9

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