Articles | Volume 27, issue 1
https://doi.org/10.5194/hess-27-229-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-229-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Jan 2023
Research article |
| 11 Jan 2023
| 11 Jan 2023
Regional significance of historical trends and step changes in Australian streamflow
Gnanathikkam Emmanuel Amirthanathan
Community Services, Bureau of Meteorology, Melbourne, Australia
Mohammed Abdul Bari
CORRESPONDING AUTHOR
Science and Innovation, Bureau of Meteorology, Perth, Australia
Fitsum Markos Woldemeskel
Community Services, Bureau of Meteorology, Melbourne, Australia
Narendra Kumar Tuteja
Science and Innovation, Bureau of Meteorology, Canberra, Australia
current address: Strategy and Performance, WaterNSW, Sydney, Australia
Paul Martinus Feikema
Community Services, Bureau of Meteorology, Melbourne, Australia
Related authors
No articles found.
David McInerney, Mark Thyer, Dmitri Kavetski, Richard Laugesen, Fitsum Woldemeskel, Narendra Tuteja, and George Kuczera
Hydrol. Earth Syst. Sci., 26, 5669–5683, https://doi.org/10.5194/hess-26-5669-2022, https://doi.org/10.5194/hess-26-5669-2022, 2022
Short summary
Short summary
Streamflow forecasts a day to a month ahead are highly valuable for water resources management. Current practice often develops forecasts for specific lead times and aggregation timescales. In contrast, a single, seamless forecast can serve multiple lead times/timescales. This study shows seamless forecasts can match the performance of forecasts developed specifically at the monthly scale, while maintaining quality at other lead times. Hence, users need not sacrifice capability for performance.
Hapu Arachchige Prasantha Hapuarachchi, Mohammed Abdul Bari, Aynul Kabir, Mohammad Mahadi Hasan, Fitsum Markos Woldemeskel, Nilantha Gamage, Patrick Daniel Sunter, Xiaoyong Sophie Zhang, David Ewen Robertson, James Clement Bennett, and Paul Martinus Feikema
Hydrol. Earth Syst. Sci., 26, 4801–4821, https://doi.org/10.5194/hess-26-4801-2022, https://doi.org/10.5194/hess-26-4801-2022, 2022
Short summary
Short summary
Methodology for developing an operational 7-day ensemble streamflow forecasting service for Australia is presented. The methodology is tested for 100 catchments to learn the characteristics of different NWP rainfall forecasts, the effect of post-processing, and the optimal ensemble size and bootstrapping parameters. Forecasts are generated using NWP rainfall products post-processed by the CHyPP model, the GR4H hydrologic model, and the ERRIS streamflow post-processor inbuilt in the SWIFT package
Fitsum Woldemeskel, David McInerney, Julien Lerat, Mark Thyer, Dmitri Kavetski, Daehyok Shin, Narendra Tuteja, and George Kuczera
Hydrol. Earth Syst. Sci., 22, 6257–6278, https://doi.org/10.5194/hess-22-6257-2018, https://doi.org/10.5194/hess-22-6257-2018, 2018
Short summary
Short summary
This paper evaluates several schemes for post-processing monthly and seasonal streamflow forecasts using the Australian Bureau of Meteorology's streamflow forecasting system. Through evaluation across 300 catchments, the best-performing scheme has been identified, which is found to substantially improve important aspects of the forecast quality. This finding is significant because the improved forecasts help water managers and users of the service to make better-informed decisions.
Andrew Schepen, Tongtiegang Zhao, Q. J. Wang, Senlin Zhou, and Paul Feikema
Hydrol. Earth Syst. Sci., 20, 4117–4128, https://doi.org/10.5194/hess-20-4117-2016, https://doi.org/10.5194/hess-20-4117-2016, 2016
Short summary
Short summary
Australian seasonal streamflow forecasts are issued by the Bureau of Meteorology with up to two weeks' delay. Timelier forecast release will enhance forecast value and enable sub-seasonal forecasting. The bureau's forecasting approach is modified to allow timelier forecast release, and changes in reliability and skill are quantified. The results are combined with insights into the forecast production process to recommend a more flexible forecasting system to better meet the needs of users.
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Mathematical applications
Spatial variability in Alpine reservoir regulation: deriving reservoir operations from streamflow using generalized additive models
River flooding mechanisms and their changes in Europe revealed by explainable machine learning
The Wasserstein distance as a hydrological objective function
Changes in nonlinearity and stability of streamflow recession characteristics under climate warming in a large glaciated basin of the Tibetan Plateau
A data-driven method for estimating the composition of end-members from stream water chemistry time series
Evaporation loss estimation of the river-lake continuum of arid inland river: Evidence from stable isotopes
Technical note: PMR – a proxy metric to assess hydrological model robustness in a changing climate
Causal effects of dams and land cover changes on flood changes in mainland China
Can the two-parameter recursive digital filter baseflow separation method really be calibrated by the conductivity mass balance method?
Simultaneously determining global sensitivities of model parameters and model structure
Technical note: Calculation scripts for ensemble hydrograph separation
Specific climate classification for Mediterranean hydrology and future evolution under Med-CORDEX regional climate model scenarios
A line-integral-based method to partition climate and catchment effects on runoff
Technical note: A two-sided affine power scaling relationship to represent the concentration–discharge relationship
On the flood peak distributions over China
New water fractions and transit time distributions at Plynlimon, Wales, estimated from stable water isotopes in precipitation and streamflow
Does the weighting of climate simulations result in a better quantification of hydrological impacts?
A 50-year analysis of hydrological trends and processes in a Mediterranean catchment
Technical Note: On the puzzling similarity of two water balance formulas – Turc–Mezentsev vs. Tixeront–Fu
Climate or land cover variations: what is driving observed changes in river peak flows? A data-based attribution study
Quantifying new water fractions and transit time distributions using ensemble hydrograph separation: theory and benchmark tests
Land cover effects on hydrologic services under a precipitation gradient
Technical note: Long-term persistence loss of urban streams as a metric for catchment classification
Responses of runoff to historical and future climate variability over China
Characterization and evaluation of controls on post-fire streamflow response across western US watersheds
Analysis and modelling of a 9.3 kyr palaeoflood record: correlations, clustering, and cycles
Climate change impacts on Yangtze River discharge at the Three Gorges Dam
Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?
Delineation of homogenous regions using hydrological variables predicted by projection pursuit regression
Multivariate hydrological data assimilation of soil moisture and groundwater head
On the propagation of diel signals in river networks using analytic solutions of flow equations
Dominant climatic factors driving annual runoff changes at the catchment scale across China
Data assimilation in integrated hydrological modelling in the presence of observation bias
Recent changes in climate, hydrology and sediment load in the Wadi Abd, Algeria (1970–2010)
Technical Note: Testing an improved index for analysing storm discharge–concentration hysteresis
Estimating spatially distributed soil water content at small watershed scales based on decomposition of temporal anomaly and time stability analysis
Improving flood forecasting capability of physically based distributed hydrological models by parameter optimization
Time series analysis of the long-term hydrologic impacts of afforestation in the Águeda watershed of north-central Portugal
Data assimilation in integrated hydrological modeling using ensemble Kalman filtering: evaluating the effect of ensemble size and localization on filter performance
Attribution of high resolution streamflow trends in Western Austria – an approach based on climate and discharge station data
A constraint-based search algorithm for parameter identification of environmental models
Hydrologic landscape classification evaluates streamflow vulnerability to climate change in Oregon, USA
Teleconnection analysis of runoff and soil moisture over the Pearl River basin in southern China
Assessing the predictive capability of randomized tree-based ensembles in streamflow modelling
Streamflow input to Lake Athabasca, Canada
Flood-initiating catchment conditions: a spatio-temporal analysis of large-scale soil moisture patterns in the Elbe River basin
Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation
Impact of climate change and anthropogenic activities on stream flow and sediment discharge in the Wei River basin, China
An effective depression filling algorithm for DEM-based 2-D surface flow modelling
Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities
Manuela Irene Brunner and Philippe Naveau
Hydrol. Earth Syst. Sci., 27, 673–687, https://doi.org/10.5194/hess-27-673-2023, https://doi.org/10.5194/hess-27-673-2023, 2023
Short summary
Short summary
Reservoir regulation affects various streamflow characteristics. Still, information on when water is stored in and released from reservoirs is hardly available. We develop a statistical model to reconstruct reservoir operation signals from observed streamflow time series. By applying this approach to 74 catchments in the Alps, we find that reservoir management varies by catchment elevation and that seasonal redistribution from summer to winter is strongest in high-elevation catchments.
Shijie Jiang, Emanuele Bevacqua, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 26, 6339–6359, https://doi.org/10.5194/hess-26-6339-2022, https://doi.org/10.5194/hess-26-6339-2022, 2022
Short summary
Short summary
Using a novel explainable machine learning approach, we investigated the contributions of precipitation, temperature, and day length to different peak discharges, thereby uncovering three primary flooding mechanisms widespread in European catchments. The results indicate that flooding mechanisms have changed in numerous catchments over the past 70 years. The study highlights the potential of artificial intelligence in revealing complex changes in extreme events related to climate change.
Jared C. Magyar and Malcolm S. Sambridge
EGUsphere, https://doi.org/10.5194/egusphere-2022-1117, https://doi.org/10.5194/egusphere-2022-1117, 2022
Short summary
Short summary
Measuring the similarity of distributions of water is a useful tool for model calibration and assessment. We provide a new way of measuring this similarity for streamflow time series. It is derived from the concept of the amount of 'work' required to rearrange one mass distribution into the other. We also use similar mathematical techniques for defining a type of 'average' between water distributions.
Jiarong Wang, Xi Chen, Man Gao, Qi Hu, and Jintao Liu
Hydrol. Earth Syst. Sci., 26, 3901–3920, https://doi.org/10.5194/hess-26-3901-2022, https://doi.org/10.5194/hess-26-3901-2022, 2022
Short summary
Short summary
The accelerated climate warming in the Tibetan Plateau after 1997 has strong consequences for hydrology, geography, and social wellbeing. In hydrology, the change in streamflow as a result of changes in dynamic water storage originating from glacier melt and permafrost thawing in a warming climate directly affects the available water resources for societies of some of the most populated nations in the world.
Esther Xu Fei and Ciaran Joseph Harman
Hydrol. Earth Syst. Sci., 26, 1977–1991, https://doi.org/10.5194/hess-26-1977-2022, https://doi.org/10.5194/hess-26-1977-2022, 2022
Short summary
Short summary
Water in streams is a mixture of water from many sources. It is sometimes possible to identify the chemical fingerprint of each source and track the time-varying contribution of that source to the total flow rate. But what if you do not know the chemical fingerprint of each source? Can you simultaneously identify the sources (called end-members), and separate the water into contributions from each, using only samples of water from the stream? Here we suggest a method for doing just that.
Guofeng Zhu, Zhigang Sun, Yuanxiao Xu, Yuwei Liu, Zhuanxia Zhang, Liyuan Sang, and Lei Wang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-75, https://doi.org/10.5194/hess-2022-75, 2022
Revised manuscript under review for HESS
Short summary
Short summary
We analyzed the stable isotopic composition of surface water and estimated its evaporative loss in the Shiyang River Basin. The characteristics of stable isotopes in surface water show a gradual enrichment from mountainous areas to deserts, and the evaporation loss of surface water also shows a gradually increasing trend from upstream to downstream. The study of evaporative losses in the river-lake continuum contributes to the sustainable use of water resources.
Paul Royer-Gaspard, Vazken Andréassian, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 25, 5703–5716, https://doi.org/10.5194/hess-25-5703-2021, https://doi.org/10.5194/hess-25-5703-2021, 2021
Short summary
Short summary
Most evaluation studies based on the differential split-sample test (DSST) endorse the consensus that rainfall–runoff models lack climatic robustness. In this technical note, we propose a new performance metric to evaluate model robustness without applying the DSST and which can be used with a single hydrological model calibration. Our work makes it possible to evaluate the temporal transferability of any hydrological model, including uncalibrated models, at a very low computational cost.
Wencong Yang, Hanbo Yang, Dawen Yang, and Aizhong Hou
Hydrol. Earth Syst. Sci., 25, 2705–2720, https://doi.org/10.5194/hess-25-2705-2021, https://doi.org/10.5194/hess-25-2705-2021, 2021
Short summary
Short summary
This study quantified the causal effects of land cover changes and dams on the changes in annual maximum discharges (Q) in 757 catchments of China using panel regressions. We found that a 1 % point increase in urban areas causes a 3.9 % increase in Q, and a 1 unit increase in reservoir index causes a 21.4 % decrease in Q for catchments with no dam before. This study takes the first step to explain the human-caused flood changes on a national scale in China.
Weifei Yang, Changlai Xiao, Zhihao Zhang, and Xiujuan Liang
Hydrol. Earth Syst. Sci., 25, 1747–1760, https://doi.org/10.5194/hess-25-1747-2021, https://doi.org/10.5194/hess-25-1747-2021, 2021
Short summary
Short summary
This study analyzed the effectiveness of the conductivity mass balance (CMB) method for correcting the Eckhardt method. The results showed that the approach of calibrating the Eckhardt method against the CMB method provides a
falsecalibration of total baseflow by offsetting the inherent biases in the baseflow sequences generated by the two methods. The reason for this phenomenon is the baseflow series generated by the two methods containing different transient water sources.
Juliane Mai, James R. Craig, and Bryan A. Tolson
Hydrol. Earth Syst. Sci., 24, 5835–5858, https://doi.org/10.5194/hess-24-5835-2020, https://doi.org/10.5194/hess-24-5835-2020, 2020
James W. Kirchner and Julia L. A. Knapp
Hydrol. Earth Syst. Sci., 24, 5539–5558, https://doi.org/10.5194/hess-24-5539-2020, https://doi.org/10.5194/hess-24-5539-2020, 2020
Short summary
Short summary
Ensemble hydrograph separation is a powerful new tool for measuring the age distribution of streamwater. However, the calculations are complex and may be difficult for researchers to implement on their own. Here we present scripts that perform these calculations in either MATLAB or R so that researchers do not need to write their own codes. We explain how these scripts work and how to use them. We demonstrate several potential applications using a synthetic catchment data set.
Antoine Allam, Roger Moussa, Wajdi Najem, and Claude Bocquillon
Hydrol. Earth Syst. Sci., 24, 4503–4521, https://doi.org/10.5194/hess-24-4503-2020, https://doi.org/10.5194/hess-24-4503-2020, 2020
Short summary
Short summary
With serious concerns about global change rising in the Mediterranean, we established a new climatic classification to follow hydrological and ecohydrological activities. The classification coincided with a geographical distribution ranging from the most seasonal and driest class in the south to the least seasonal and most humid in the north. RCM scenarios showed that northern classes evolve to southern ones with shorter humid seasons and earlier snowmelt which might affect hydrologic regimes.
Mingguo Zheng
Hydrol. Earth Syst. Sci., 24, 2365–2378, https://doi.org/10.5194/hess-24-2365-2020, https://doi.org/10.5194/hess-24-2365-2020, 2020
Short summary
Short summary
This paper developed a mathematically precise method to partition climate and catchment effects on streamflow. The method reveals that both the change magnitude and pathway (timing of change), not the magnitude alone, dictate the partition unless for a linear system. The method has wide relevance. For example, it suggests that the global warming effect of carbon emission is path dependent, and an optimal pathway would facilitate a higher global budget of carbon emission.
José Manuel Tunqui Neira, Vazken Andréassian, Gaëlle Tallec, and Jean-Marie Mouchel
Hydrol. Earth Syst. Sci., 24, 1823–1830, https://doi.org/10.5194/hess-24-1823-2020, https://doi.org/10.5194/hess-24-1823-2020, 2020
Short summary
Short summary
This paper deals with the mathematical representation of concentration–discharge relationships. We propose a two-sided affine power scaling relationship (2S-APS) as an alternative to the classic one-sided power scaling relationship (commonly known as
power law). We also discuss the identification of the parameters of the proposed relationship, using an appropriate numerical criterion, based on high-frequency chemical time series of the Orgeval-ORACLE observatory.
Long Yang, Lachun Wang, Xiang Li, and Jie Gao
Hydrol. Earth Syst. Sci., 23, 5133–5149, https://doi.org/10.5194/hess-23-5133-2019, https://doi.org/10.5194/hess-23-5133-2019, 2019
Julia L. A. Knapp, Colin Neal, Alessandro Schlumpf, Margaret Neal, and James W. Kirchner
Hydrol. Earth Syst. Sci., 23, 4367–4388, https://doi.org/10.5194/hess-23-4367-2019, https://doi.org/10.5194/hess-23-4367-2019, 2019
Short summary
Short summary
We describe, present, and make publicly available two extensive data sets of stable water isotopes in streamwater and precipitation at Plynlimon, Wales, consisting of measurements at 7-hourly intervals for 17 months and at weekly intervals for 4.25 years. We use these data to calculate new water fractions and transit time distributions for different discharge rates and seasons, thus quantifying the contribution of recent precipitation to streamflow under different conditions.
Hui-Min Wang, Jie Chen, Chong-Yu Xu, Hua Chen, Shenglian Guo, Ping Xie, and Xiangquan Li
Hydrol. Earth Syst. Sci., 23, 4033–4050, https://doi.org/10.5194/hess-23-4033-2019, https://doi.org/10.5194/hess-23-4033-2019, 2019
Short summary
Short summary
When using large ensembles of global climate models in hydrological impact studies, there are pragmatic questions on whether it is necessary to weight climate models and how to weight them. We use eight methods to weight climate models straightforwardly, based on their performances in hydrological simulations, and investigate the influences of the assigned weights. This study concludes that using bias correction and equal weighting is likely viable and sufficient for hydrological impact studies.
Nathalie Folton, Eric Martin, Patrick Arnaud, Pierre L'Hermite, and Mathieu Tolsa
Hydrol. Earth Syst. Sci., 23, 2699–2714, https://doi.org/10.5194/hess-23-2699-2019, https://doi.org/10.5194/hess-23-2699-2019, 2019
Short summary
Short summary
The long-term study of precipitation, flows, flood or drought mechanisms, in the Réal Collobrier research Watershed, located in South-East France, in the Mediterranean forest, improves knowledge of the water cycle and is unique tool for understanding of how catchments function. This study shows a small decrease in rainfall and a marked tendency towards a decrease in the water resources of the catchment in response to climate trends, with a consistent increase in drought severity and duration.
Vazken Andréassian and Tewfik Sari
Hydrol. Earth Syst. Sci., 23, 2339–2350, https://doi.org/10.5194/hess-23-2339-2019, https://doi.org/10.5194/hess-23-2339-2019, 2019
Short summary
Short summary
In this Technical Note, we present two water balance formulas: the Turc–Mezentsev and Tixeront–Fu formulas. These formulas have a puzzling numerical similarity, which we discuss in detail and try to interpret mathematically and hydrologically.
Jan De Niel and Patrick Willems
Hydrol. Earth Syst. Sci., 23, 871–882, https://doi.org/10.5194/hess-23-871-2019, https://doi.org/10.5194/hess-23-871-2019, 2019
James W. Kirchner
Hydrol. Earth Syst. Sci., 23, 303–349, https://doi.org/10.5194/hess-23-303-2019, https://doi.org/10.5194/hess-23-303-2019, 2019
Short summary
Short summary
How long does it take for raindrops to become streamflow? Here I propose a new approach to this old problem. I show how we can use time series of isotope data to measure the average fraction of same-day rainfall appearing in streamflow, even if this fraction varies greatly from rainstorm to rainstorm. I show that we can quantify how this fraction changes from small rainstorms to big ones, and from high flows to low flows, and how it changes with the lag time between rainfall and streamflow.
Ane Zabaleta, Eneko Garmendia, Petr Mariel, Ibon Tamayo, and Iñaki Antigüedad
Hydrol. Earth Syst. Sci., 22, 5227–5241, https://doi.org/10.5194/hess-22-5227-2018, https://doi.org/10.5194/hess-22-5227-2018, 2018
Short summary
Short summary
This study establishes relationships between land cover and river discharge. Using discharge data from 20 catchments of the Bay of Biscay findings showed the influence of land cover on discharge changes with the amount of precipitation, with lower annual water resources associated with the greater presence of forests. Results obtained illustrate the relevance of land planning to the management of water resources and the opportunity to consider it in future climate-change adaptation strategies.
Dusan Jovanovic, Tijana Jovanovic, Alfonso Mejía, Jon Hathaway, and Edoardo Daly
Hydrol. Earth Syst. Sci., 22, 3551–3559, https://doi.org/10.5194/hess-22-3551-2018, https://doi.org/10.5194/hess-22-3551-2018, 2018
Short summary
Short summary
A relationship between the Hurst (H) exponent (a long-term correlation coefficient) within a flow time series and various catchment characteristics for a number of catchments in the USA and Australia was investigated. A negative relationship with imperviousness was identified, which allowed for an efficient catchment classification, thus making the H exponent a useful metric to quantitatively assess the impact of catchment imperviousness on streamflow regime.
Chuanhao Wu, Bill X. Hu, Guoru Huang, Peng Wang, and Kai Xu
Hydrol. Earth Syst. Sci., 22, 1971–1991, https://doi.org/10.5194/hess-22-1971-2018, https://doi.org/10.5194/hess-22-1971-2018, 2018
Short summary
Short summary
China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal–spatial patterns of water resources. In this paper, the Budyko-based elasticity method was used to investigate the responses of runoff to historical and future climate variability over China at both grid and catchment scales. The results help to better understand the hydrological effects of climate change and adapt to a changing environment.
Samuel Saxe, Terri S. Hogue, and Lauren Hay
Hydrol. Earth Syst. Sci., 22, 1221–1237, https://doi.org/10.5194/hess-22-1221-2018, https://doi.org/10.5194/hess-22-1221-2018, 2018
Short summary
Short summary
We investigate the impact of wildfire on watershed flow regimes, examining responses across the western United States. On a national scale, our results confirm the work of prior studies: that low, high, and peak flows typically increase following a wildfire. Regionally, results are more variable and sometimes contradictory. Our results may be significant in justifying the calibration of watershed models and in contributing to the overall observational analysis of post-fire streamflow response.
Annette Witt, Bruce D. Malamud, Clara Mangili, and Achim Brauer
Hydrol. Earth Syst. Sci., 21, 5547–5581, https://doi.org/10.5194/hess-21-5547-2017, https://doi.org/10.5194/hess-21-5547-2017, 2017
Short summary
Short summary
Here we present a unique 9.5 m palaeo-lacustrine record of 771 palaeofloods which occurred over a period of 10 000 years in the Piànico–Sèllere basin (southern Alps) during an interglacial period in the Pleistocene (sometime between 400 000 and 800 000 years ago). We analyse the palaeoflood series correlation, clustering, and cyclicity properties, finding a long-range cyclicity with a period of about 2030 years superimposed onto a fractional noise.
Steve J. Birkinshaw, Selma B. Guerreiro, Alex Nicholson, Qiuhua Liang, Paul Quinn, Lili Zhang, Bin He, Junxian Yin, and Hayley J. Fowler
Hydrol. Earth Syst. Sci., 21, 1911–1927, https://doi.org/10.5194/hess-21-1911-2017, https://doi.org/10.5194/hess-21-1911-2017, 2017
Short summary
Short summary
The Yangtze River basin in China is home to more than 400 million people and susceptible to major floods. We used projections of future precipitation and temperature from 35 of the most recent global climate models and applied this to a hydrological model of the Yangtze. Changes in the annual discharge varied between a 29.8 % decrease and a 16.0 % increase. The main reason for the difference between the models was the predicted expansion of the summer monsoon north and and west into the basin.
Maurizio Mazzoleni, Martin Verlaan, Leonardo Alfonso, Martina Monego, Daniele Norbiato, Miche Ferri, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 21, 839–861, https://doi.org/10.5194/hess-21-839-2017, https://doi.org/10.5194/hess-21-839-2017, 2017
Short summary
Short summary
This study assesses the potential use of crowdsourced data in hydrological modeling, which are characterized by irregular availability and variable accuracy. We show that even data with these characteristics can improve flood prediction if properly integrated into hydrological models. This study provides technological support to citizen observatories of water, in which citizens can play an active role in capturing information, leading to improved model forecasts and better flood management.
Martin Durocher, Fateh Chebana, and Taha B. M. J. Ouarda
Hydrol. Earth Syst. Sci., 20, 4717–4729, https://doi.org/10.5194/hess-20-4717-2016, https://doi.org/10.5194/hess-20-4717-2016, 2016
Short summary
Short summary
For regional flood frequency, it is challenging to identify regions with similar hydrological properties. Therefore, previous works have mainly proposed to use regions with similar physiographical properties. This research proposes instead to nonlinearly predict the desired hydrological properties before using them for delineation. The presented method is applied to a case study in Québec, Canada, and leads to hydrologically relevant regions, while enhancing predictions made inside them.
Donghua Zhang, Henrik Madsen, Marc E. Ridler, Jacob Kidmose, Karsten H. Jensen, and Jens C. Refsgaard
Hydrol. Earth Syst. Sci., 20, 4341–4357, https://doi.org/10.5194/hess-20-4341-2016, https://doi.org/10.5194/hess-20-4341-2016, 2016
Short summary
Short summary
We present a method to assimilate observed groundwater head and soil moisture profiles into an integrated hydrological model. The study uses the ensemble transform Kalman filter method and the MIKE SHE hydrological model code. The proposed method is shown to be more robust and provide better results for two cases in Denmark, and is also validated using real data. The hydrological model with assimilation overall improved performance compared to the model without assimilation.
Morgan Fonley, Ricardo Mantilla, Scott J. Small, and Rodica Curtu
Hydrol. Earth Syst. Sci., 20, 2899–2912, https://doi.org/10.5194/hess-20-2899-2016, https://doi.org/10.5194/hess-20-2899-2016, 2016
Short summary
Short summary
We design and implement a theoretical experiment to show that, under low-flow conditions, observed streamflow discrepancies between early and late summer can be attributed to different flow velocities in the river network. By developing an analytic solution to represent flow along a given river network, we emphasize the dependence of streamflow amplitude and time delay on the geomorphology of the network. We also simulate using a realistic river network to highlight the effects of scale.
Zhongwei Huang, Hanbo Yang, and Dawen Yang
Hydrol. Earth Syst. Sci., 20, 2573–2587, https://doi.org/10.5194/hess-20-2573-2016, https://doi.org/10.5194/hess-20-2573-2016, 2016
Short summary
Short summary
The hydrologic processes have been influenced by different climatic factors. However, the dominant climatic factor driving annual runoff change is still unknown in many catchments in China. By using the climate elasticity method proposed by Yang and Yang (2011), the elasticity of runoff to climatic factors was estimated, and the dominant climatic factors driving annual runoff change were detected at catchment scale over China.
Jørn Rasmussen, Henrik Madsen, Karsten Høgh Jensen, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 20, 2103–2118, https://doi.org/10.5194/hess-20-2103-2016, https://doi.org/10.5194/hess-20-2103-2016, 2016
Short summary
Short summary
In the paper, observations are assimilated into a hydrological model in order to improve the model performance. Two methods for detecting and correcting systematic errors (bias) in groundwater head observations are used leading to improved results compared to standard assimilation methods which ignores any bias. This is demonstrated using both synthetic (user generated) observations and real-world observations.
Mohammed Achite and Sylvain Ouillon
Hydrol. Earth Syst. Sci., 20, 1355–1372, https://doi.org/10.5194/hess-20-1355-2016, https://doi.org/10.5194/hess-20-1355-2016, 2016
Short summary
Short summary
Changes of T, P, Q and sediment fluxes in a semi-arid basin little affected by human activities are analyzed from 40 years of measurements. T increased, P decreased, an earlier onset of first summer rains occurred. The flow regime shifted from perennial to intermittent. Sediment flux almost doubled every decade. The sediment regime shifted from two equivalent seasons of sediment delivery to a single major season regime. The C–Q rating curve ability declined due to enhanced hysteresis effects.
C. E. M. Lloyd, J. E. Freer, P. J. Johnes, and A. L. Collins
Hydrol. Earth Syst. Sci., 20, 625–632, https://doi.org/10.5194/hess-20-625-2016, https://doi.org/10.5194/hess-20-625-2016, 2016
Short summary
Short summary
This paper examines the current methodologies for quantifying storm behaviour through hysteresis analysis, and explores a new method. Each method is systematically tested and the impact on the results is examined. Recommendations are made regarding the most effective method of calculating a hysteresis index. This new method allows storm hysteresis behaviour to be directly compared between storms, parameters, and catchments, meaning it has wide application potential in water quality research.
W. Hu and B. C. Si
Hydrol. Earth Syst. Sci., 20, 571–587, https://doi.org/10.5194/hess-20-571-2016, https://doi.org/10.5194/hess-20-571-2016, 2016
Short summary
Short summary
Spatiotemporal SWC was decomposed into into three terms (spatial forcing, temporal forcing, and interactions between spatial and temporal forcing) for near surface and root zone; Empirical orthogonal function indicated that underlying patterns exist in the interaction term at small watershed scales; Estimation of spatially distributed SWC benefits from decomposition of the interaction term; The suggested decomposition of SWC with time stability analysis has potential in SWC downscaling.
Y. Chen, J. Li, and H. Xu
Hydrol. Earth Syst. Sci., 20, 375–392, https://doi.org/10.5194/hess-20-375-2016, https://doi.org/10.5194/hess-20-375-2016, 2016
Short summary
Short summary
Parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. A method for parameter optimization with particle swam optimization (PSO) algorithm has been proposed for physically based distributed hydrological model in catchment flood forecasting and validated in southern China. It has found that the appropriate particle number and maximum evolution number of PSO algorithm are 20 and 30 respectively.
D. Hawtree, J. P. Nunes, J. J. Keizer, R. Jacinto, J. Santos, M. E. Rial-Rivas, A.-K. Boulet, F. Tavares-Wahren, and K.-H. Feger
Hydrol. Earth Syst. Sci., 19, 3033–3045, https://doi.org/10.5194/hess-19-3033-2015, https://doi.org/10.5194/hess-19-3033-2015, 2015
J. Rasmussen, H. Madsen, K. H. Jensen, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 19, 2999–3013, https://doi.org/10.5194/hess-19-2999-2015, https://doi.org/10.5194/hess-19-2999-2015, 2015
C. Kormann, T. Francke, M. Renner, and A. Bronstert
Hydrol. Earth Syst. Sci., 19, 1225–1245, https://doi.org/10.5194/hess-19-1225-2015, https://doi.org/10.5194/hess-19-1225-2015, 2015
S. Gharari, M. Shafiei, M. Hrachowitz, R. Kumar, F. Fenicia, H. V. Gupta, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 4861–4870, https://doi.org/10.5194/hess-18-4861-2014, https://doi.org/10.5194/hess-18-4861-2014, 2014
S. G. Leibowitz, R. L. Comeleo, P. J. Wigington Jr., C. P. Weaver, P. E. Morefield, E. A. Sproles, and J. L. Ebersole
Hydrol. Earth Syst. Sci., 18, 3367–3392, https://doi.org/10.5194/hess-18-3367-2014, https://doi.org/10.5194/hess-18-3367-2014, 2014
J. Niu, J. Chen, and B. Sivakumar
Hydrol. Earth Syst. Sci., 18, 1475–1492, https://doi.org/10.5194/hess-18-1475-2014, https://doi.org/10.5194/hess-18-1475-2014, 2014
S. Galelli and A. Castelletti
Hydrol. Earth Syst. Sci., 17, 2669–2684, https://doi.org/10.5194/hess-17-2669-2013, https://doi.org/10.5194/hess-17-2669-2013, 2013
K. Rasouli, M. A. Hernández-Henríquez, and S. J. Déry
Hydrol. Earth Syst. Sci., 17, 1681–1691, https://doi.org/10.5194/hess-17-1681-2013, https://doi.org/10.5194/hess-17-1681-2013, 2013
M. Nied, Y. Hundecha, and B. Merz
Hydrol. Earth Syst. Sci., 17, 1401–1414, https://doi.org/10.5194/hess-17-1401-2013, https://doi.org/10.5194/hess-17-1401-2013, 2013
B. Gräler, M. J. van den Berg, S. Vandenberghe, A. Petroselli, S. Grimaldi, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 1281–1296, https://doi.org/10.5194/hess-17-1281-2013, https://doi.org/10.5194/hess-17-1281-2013, 2013
P. Gao, V. Geissen, C. J. Ritsema, X.-M. Mu, and F. Wang
Hydrol. Earth Syst. Sci., 17, 961–972, https://doi.org/10.5194/hess-17-961-2013, https://doi.org/10.5194/hess-17-961-2013, 2013
D. Zhu, Q. Ren, Y. Xuan, Y. Chen, and I. D. Cluckie
Hydrol. Earth Syst. Sci., 17, 495–505, https://doi.org/10.5194/hess-17-495-2013, https://doi.org/10.5194/hess-17-495-2013, 2013
Y. Liu, A. H. Weerts, M. Clark, H.-J. Hendricks Franssen, S. Kumar, H. Moradkhani, D.-J. Seo, D. Schwanenberg, P. Smith, A. I. J. M. van Dijk, N. van Velzen, M. He, H. Lee, S. J. Noh, O. Rakovec, and P. Restrepo
Hydrol. Earth Syst. Sci., 16, 3863–3887, https://doi.org/10.5194/hess-16-3863-2012, https://doi.org/10.5194/hess-16-3863-2012, 2012
Cited articles
Abdul Aziz, O. I. and Burn, D. H.: Trends and variability in the hydrological regime of the Mackenzie River Basin, J. Hydrol., 319, 282–294, https://doi.org/10.1016/j.jhydrol.2005.06.039, 2006.
Akpoti, K., Antwi, E. O., and Kabo-bah, A. T.: Impacts of rainfall variability, land use and land cover change on stream flow of the Black
Volta basin, West Africa, Hydrology, 3, 26, https://doi.org/10.3390/hydrology3030026, 2016.
Alfieri, L., Lorini, V., Hirpa, F. A., Harrigan, S., Zsoter, E., Prudhomme,
C., and Salamon, P.: A global streamflow reanalysis for 1980–2018, J.
Hydrol. X, 6, 100049, https://doi.org/10.1016/j.hydroa.2019.100049, 2020.
Asadieh, B., Krakauer, N. Y., and Fekete, B. M.: Historical trends in mean
and extreme runoff and streamflow based on observations and climate models,
Water, 8, 189, https://doi.org/10.3390/w8050189, 2016.
Atkinson, R., Power, R., Lemon, D., O'Hagan, R., Dovey, D., and Kinny, D.: The Australian Hydrological Geospatial Fabric – Development Methodology and Conceptual Architecture, CSIRO: Water for a Healthy Country National Research Flagship, Canberra, Australia, 57 pp., https://publications.csiro.au/rpr/download?pid=procite:5126351f-b297-409b-b472-654d3534e3ae&dsid=DS1 (last access: 10 January 2023), 2008.
Bawden, A. J., Burn, D. H., and Prowse, T. D.: Recent changes in patterns of
western Canadian river flow and association with Climatic drivers, Hydrol.
Res., 46, 551–565, https://doi.org/10.2166/nh.2014.032, 2015.
Birsan, M. V., Molnar, P., Burlando, P., and Pfaundler, M.: Streamflow trends
in Switzerland, J. Hydrol., 314, 312–329, https://doi.org/10.1016/j.jhydrol.2005.06.008, 2005.
BoM – Bureau of Meteorology: Hydrologic Reference Stations,
http://www.bom.gov.au/water/hrs/index.shtml, last access: 9 January 2023.
BoM – Bureau of Meteorology – and CSIRO: State of the Climate 2020, http://www.bom.gov.au/state-of-the-climate/documents/State-of-the-Climate-2020.pdf (last access: 10 January 2023), 2020.
Bradford, R. B. and Marsh, T. J.: Defining a network of benchmark catchments
for the UK, Proc. Inst. Civ. Eng. Water Marit. Eng., 156, 109–116, https://doi.org/10.1680/wame.2003.156.2.109, 2003.
Brimley, B., Cantin, J., Harvey, D., Kowalchuk, M., Marsh, P., Ouarda, T.,
and Yuzyk, T.: Establishment of the reference hydrometric basin network (RHBN) for Canada, Environment Canada Research Report, Ontario, Canada, 41 pp., 1999.
BoM – Bureau of Meteorology: Average annual, seasonal and monthly rainfall, Commonwealth of Australia, http://www.bom.gov.au/jsp/ncc/climate_averages/rainfall/index.jsp
(last access: 3 January 2023), 2022.
BoM – Bureau of Meteorology – and CSIRO: State of the Climate 2018, The
third report on Australia's climate by BOM and CSIRO, http://www.bom.gov.au/state-of-the-climate/ (last access: 3 January 2023), 2018.
Burn, D. H., Whitfield, P. H., and Sharif, M.: Identification of changes in
floods and flood regimes in Canada using a peaks over threshold approach,
Hydrol. Process., 39, 3303–3314, https://doi.org/10.1002/hyp.10861, 2016.
Chiew, F. H. S. and McMahon, T. A.: Detection of trend or change in annual
flow of Australian rivers, Int. J. Climatol., 13, 643–653, https://doi.org/10.1002/joc.3370130605, 1993.
Chiew, F. H. S. and Siriwardena, L.: TREND – trend/change detection software, CRC for Catchment Hydrology, 23 pp., 2005.
Coxon, G., Addor, N., Bloomfield, J. P., Freer, J., Fry, M., Hannaford, J., Howden, N. J. K., Lane, R., Lewis, M., Robinson, E. L., Wagener, T., and Woods, R.: CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain, Earth Syst. Sci. Data, 12, 2459–2483, https://doi.org/10.5194/essd-12-2459-2020, 2020.
Diop, L., Yaseen, Z. M., Bodian, A., Djaman, K., and Brown, L.: Trend analysis of streamflow with different time scales: a case study of the upper
Senegal River, ISH J. Hydraul. Eng., 24, 105–114, https://doi.org/10.1080/09715010.2017.1333045, 2018.
Dixon, H., Lawler, D. M., and Shamseldin, A. Y.: Streamflow trends in western
Britain, Geophys. Res. Lett., 33, L19406, https://doi.org/10.1029/2006GL027325, 2006.
Do, H. X., Westra, S., and Leonard, M.: A global-scale investigation of trends in annual maximum streamflow, J. Hydrol., 552, 28–43, https://doi.org/10.1016/j.jhydrol.2017.06.015, 2017.
Durrant, J. and Byleveld, S.: Streamflow trends in south-west Western
Australia, Surface water hydrology series – Report no. HY32, Department of Water, Government of Western Australia, 79 pp., https://www.water.wa.gov.au/__data/assets/pdf_file/0017/1592/87846.pdf (last access: 6 January 2023), 2009.
Falcone, J. A., Carlisle, D. M., Wolock, D. M., and Meador, M. R.: GAGES: A
stream gage database for evaluating natural and altered flow conditions in
the conterminous United States, Ecology, 91, 621, https://doi.org/10.1890/09-0889.1, 2010.
Ficklin, D. L., Abatzoglou, J. T., Robeson, S. M., Null, S. E., and Knouft,
J. H.: Natural and managed watersheds show similar responses to recent
climate change, P. Natl. Acad. Sci. USA, 115, 8553–8557, https://doi.org/10.1073/pnas.1801026115, 2018.
Fiddes, S. and Timbal, B.: Assessment and reconstruction of catchment
streamflow trends and variability in response to rainfall across Victoria,
Australia, Clim. Res., 67, 43–60, https://doi.org/10.3354/cr01355, 2016.
Fowler, K., Peel, M., Saft, M., Peterson, T. J., Western, A., Band, L., Petheram, C., Dharmadi, S., Tan, K. S., Zhang, L., Lane, P., Kiem, A., Marshall, L., Griebel, A., Medlyn, B. E., Ryu, D., Bonotto, G., Wasko, C., Ukkola, A., Stephens, C., Frost, A., Gardiya Weligamage, H., Saco, P., Zheng, H., Chiew, F., Daly, E., Walker, G., Vervoort, R. W., Hughes, J., Trotter, L., Neal, B., Cartwright, I., and Nathan, R.: Explaining changes in rainfall–runoff relationships during and after Australia's Millennium Drought: a community perspective, Hydrol. Earth Syst. Sci., 26, 6073–6120, https://doi.org/10.5194/hess-26-6073-2022, 2022.
Gergis, J., Gallant, A. J. E., Braganza, K., Karoly, D. J., Allen, K., Cullen, L., D'Arrigo, R., Goodwin, I., Grierson, P., and McGregor, S.: On the
long-term context of the 1997–2009 “Big Dry” in South-Eastern Australia:
Insights from a 206-year multi-proxy rainfall reconstruction, Climatic Change, 111, 923–944, https://doi.org/10.1007/s10584-011-0263-x, 2012.
Gu, X., Zhang, Q., Li, J., Liu, J., Xu, C. Y., and Sun, P.: The changing nature and projection of floods across Australia, J. Hydrol., 584, 124703, https://doi.org/10.1016/j.jhydrol.2020.124703, 2020.
Gudmundsson, L., Leonard, M., Do, H. X., Westra, S., and Seneviratne, S. I.:
Observed Trends in Global Indicators of Mean and Extreme Streamflow, Geophys. Res. Lett., 46, 756–766, https://doi.org/10.1029/2018GL079725, 2019.
Hamed, K. H.: Trend detection in hydrologic data: the Mann–Kendall trend test under the scaling hypothesis, J. Hydrol., 349, 350–363, https://doi.org/10.1016/j.jhydrol.2007.11.009, 2008.
Hamed, K. H.: Exact distribution of the Mann–Kendall trend test statistic for persistent data, J. Hydrol., 365, 86–94, https://doi.org/10.1016/j.jhydrol.2008.11.024, 2009.
Hamed, K. H. and Ramachandra Rao, A.: A modified Mann-Kendall trend test for
autocorrelated data, J. Hydrol., 204, 182–196, https://doi.org/10.1016/S0022-1694(97)00125-X, 1998.
Helsel, D. R., Hirsch, R. M., Ryberg, K. R., Archfield, S. A., and Gilroy, E. J.: Statistical methods in water resources: U.S. Geological Survey Techniques and Methods, in: book 4, chap. A3, p. 458, US Geological Survey, https://doi.org/10.3133/tm4a, 2020.
Herawati, H. and Suharyanto, S.: Impact of climate change on streamflow in the tropical lowland of Kapuas River, West Borneo, Indonesia, in: The 5th International Conference of Euro Asia Civil Engineering Forum (EACEF-5), Proced. Eng., 125 185–192, https://doi.org/10.1016/j.proeng.2015.11.027, 2015.
Hodgkins, G. A., Dudley, R. W., Russell, A. M., and Lafontaine, J. H.:
Comparing trends in modeled and observed streamflows at minimally altered
basins in the United States, Water, 12, 1728, https://doi.org/10.3390/W12061728, 2020.
Holper, P.: Autstralian rainfall: past, present and future, https://publications.csiro.au/publications/publication/PIcsiro:EP111937 (last access: 3 January 2023), 2011.
Hurst, H.: Long-term storage capacity of reservoirs, Trans. Am. Soc. Civ. Eng., 116, 770-799, 1951.
Ishak, E. H., Rahman, A., Westra, S., Sharma, A., and Kuczera, G.: Preliminary analysis of trends in Australian flood data, in: World Environmental and Water Resources Congress 2010: Challenges of Change –
Proceedings of the World Environmental and Water Resources Congress, Challenges of Change, 16–20 May 2010, Providence, Rhode Island, USA, 115–124, https://doi.org/10.1061/41114(371)14, 2010.
Johnson, F., White, C. J., van Dijk, A., Ekstrom, M., Evans, J. P., Jakob, D., Kiem, A. S., Leonard, M., Rouillard, A., and Westra, S.: Natural hazards in Australia: floods, Climatic Change, 139, 21–35, https://doi.org/10.1007/s10584-016-1689-y, 2016.
Kendall, M. G.: Rank Correlation Measures, Charles Griffin, London, 272 pp.,
ISBN 978-0195208375, 1975.
Khaliq, M. N., Ouarda, T. B. M. J., and Gachon, P.: Identification of temporal trends in annual and seasonal low flows occurring in Canadian rivers: The effect of short- and long-term persistence, J. Hydrol., 369, 183–197, https://doi.org/10.1016/j.jhydrol.2009.02.045, 2009.
Korhonen, J. and Kuusisto, E.: Long-term changes in the discharge regime in
Finland, Hydrol. Res., 41, 253–268, https://doi.org/10.2166/nh.2010.112, 2010.
Koutsoyiannis, D.: Climate change, the Hurst phenomenon, and hydrological
statistics, Hydrolog. Sci. J., 48, 3–24, https://doi.org/10.1623/hysj.48.1.3.43481, 2003.
Krakauer, N. Y. and Fung, I.: Mapping and attribution ofchange in streamflow in the coterminous United States, Hydrol. Earth Syst. Sci., 12,
1111—1120, https://doi.org/10.5194/hess-12-1111-2008, 2008.
Kumar, S., Merwade, V., Kam, J., and Thurner, K.: Streamflow trends in
Indiana: Effects of long term persistence, precipitation and subsurface
drains, J. Hydrol., 374, 171–183, https://doi.org/10.1016/j.jhydrol.2009.06.012, 2009.
Kundzewicz, Z. and Robson, A.: Detecting Trend and Other Changes, in: Hydrological Data, edited by: Kundzewicz, Z. W. and Robson, A., WCDMP – 45, WMO/TD-No. 1013, WCDMP, Geneva, 168 pp., https://library.wmo.int/index.php?lvl=notice_display&id=11628 (last access: 6 January 2023), 2000.
Li, L., Zou, Y., Li, Y., Lin, H., Liu, D. L., Wang, B., Yao, N., and Song,
S.: Trends, change points and spatial variability in extreme precipitation
events from 1961 to 2017 in China, Hydrol. Res., 51, 484–504, https://doi.org/10.2166/nh.2020.095, 2020.
Lins, H. F.: USGS Hydro-Climatic Data Network 2009 (HCDN–2009), US Geol.
Surv., https://pubs.usgs.gov/fs/2012/3047/ (last access: 6 January 2023), 2012.
Lins, H. F. and Slack, J. R.: Streamflow trends in the United States, Geophys. Res. Lett., 26, 227–230, https://doi.org/10.1029/1998GL900291, 1999.
Mallakpour, I. and Villarini, G.: A simulation study to examine the sensitivity of the Pettitt test to detect abrupt changes in mean, Hydrolog.
Sci. J., 61, 245–254, https://doi.org/10.1080/02626667.2015.1008482, 2016.
Mann, H. B.: Non-Parametric Test Against Trend, Econometrica, 13, 245–259, https://doi.org/10.2307/1907187, 1945.
McLeod, A. I. and Hipel, K. W.: Simulation procedures for Box–Jenkins Models, Water Resour. Res., 14, 969–975, https://doi.org/10.1029/WR014i005p00969, 1978.
McMahon, T. A. and Peel, M. C.: Uncertainty in stage–discharge rating curves: application to Australian Hydrologic Reference Stations data,
Hydrolog. Sci. J., 64, 255–275, https://doi.org/10.1080/02626667.2019.1577555, 2019.
Milly, P. C. D., Dunne, K. A., and Vecchia, A. V.: Global pattern of trends
in streamflow and water availability in a changing climate, Nature, 438, 347–350, https://doi.org/10.1038/nature04312, 2005.
Nicholls, N., Drosdowsky, W., and Lavery, B.: Australian rainfall variability
and change, Weather, 52, 66–71, https://doi.org/10.1002/j.1477-8696.1997.tb06274.x, 1997.
O'Neil, H. C. L., Prowse, T. D., Bonsal, B. R., and Dibike, Y. B.: Spatial
and temporal characteristics in streamflow-related hydroclimatic variables
over western Canada. Part 1: 1950–2010, Hydrol. Res., 48, 915–935, https://doi.org/10.2166/nh.2016.057, 2017.
Önöz, B. and Bayazit, M.: The power of statistical tests for trend
detection, Turkish J. Eng. Environ. Sci., 27, 247–251, https://doi.org/10.3906/sag-1205-120, 2003.
Pan, Z., Ruan, X., Qian, M., Hua, J., Shan, N., and Xu, J.: Spatio-temporal
variability of streamflow in the Huaihe River Basin, China: Climate
variability or human activities?, Hydrol. Res., 49, 177–193, https://doi.org/10.2166/nh.2017.155, 2018.
Perrin, C., Michel, C., and Andréassian, V.: Improvement of a parsimonious model for streamflow simulation, J. Hydrol., 279, 275–289, https://doi.org/10.1016/S0022-1694(03)00225-7, 2003.
Peterson, T. J., Saft, M., Peel, M. C., and John, A.: Watersheds may not recover from drought, Science, 372, 745–749, https://doi.org/10.1126/science.abd5085, 2021.
Petrone, K. C., Hughes, J. D., Van Niel, T. G., and Silberstein, R. P.:
Streamflow decline in southwestern Australia, 1950–2008, Geophys. Res. Lett., 37, L11401, https://doi.org/10.1029/2010GL043102, 2010.
Pettitt, A. N.: A Non-Parametric Approach to the Change-Point Problem, Appl.
Stat., 28, 126–135, https://doi.org/10.2307/2346729, 1979.
Poff, N. L. R., Olden, J. D., Pepin, D. M., and Bledsoe, B. P.: Placing
global stream flow variability in geographic and geomorphic contexts, River
Res. Appl., 22, 149–166, https://doi.org/10.1002/rra.902, 2006.
Politis, D. and White, H.: Automatic Block-Length Selection for the Dependent Bootstrap, Econ. Rev., 23, 53–70, https://doi.org/10.1081/ETC-120028836, 2004.
Politis, D. N.: The Impact of Bootstrap Methods on Time Series Analysis,
Stat. Sci., 18, 219–230, https://doi.org/10.1214/ss/1063994977, 2003.
Rao, A., Hamed, K., and Chen, H.: Nonstationarities in hydrologic and
environmental time series, Springer, ISBN 978-1402012976, 2003.
Raupach, M. R., Briggs, P. R., Haverd, V., King, E. A., Paget, M., and Trudinger, C. M.: Australian Water Availability Project (AWAP): CSIRO Marine and Atmospheric Research Component: Final Report for Phase 3, CAWCR Technical Report No. 013, 67 pp., https://www.cawcr.gov.au/technical-reports/CTR_013.pdf (last access: 3 January 2023), 2009.
Rice, J. S., Emanuel, R. E., Vose, J. M., and Nelson, S. A. C.: Continental
U.S. streamflow trends from 1940 to 2009 and their relationships with
watershed spatial characteristics, Water Resour. Res., 51, 6262–6275, https://doi.org/10.1002/2014WR016367, 2015.
Sagarika, S., Kalra, A., and Ahmad, S.: Evaluating the effect of persistence
on long-term trends and analyzing step changes in streamflows of the
continental United States, J. Hydrol., 517, 36–53, https://doi.org/10.1016/j.jhydrol.2014.05.002, 2014.
Sen, P. K.: Estimates of the Regression Coefficient Based on Kendall's Tau,
J. Am. Stat. Assoc., 63, 1379–1389, https://doi.org/10.1080/01621459.1968.10480934, 1968.
Sharma, A., Wasko, C., and Lettenmaier, D. P.: If Precipitation Extremes Are
Increasing, Why Aren't Floods?, Water Resour. Res., 54, 8545–8551, https://doi.org/10.1029/2018WR023749, 2018.
Silberstein, R. P., Aryal, S. K., Durrant, J., Pearcey, M., Braccia, M.,
Charles, S. P., Boniecka, L., Hodgson, G. A., Bari, M. A., Viney, N. R., and
McFarlane, D. J.: Climate change and runoff in south-western Australia, J.
Hydrol., 475, 441–455, https://doi.org/10.1016/j.jhydrol.2012.02.009, 2012.
State of the Climate: Report at a glance, http://www.bom.gov.au/state-of-the-climate/2020/ (last access: 3 January 2023), 2020.
Stern, H., De Hoedt, G., and Ernst, J.: Objective classification of Australian climates, Aust. Meteorol. Mag., 49, 87–96, 2000.
Su, L., Miao, C., Kong, D., Duan, Q., Lei, X., Hou, Q., and Li, H.: Long-term trends in global river flow and the causal relationships between river flow and ocean signals, J. Hydrol., 563, 818–833, https://doi.org/10.1016/j.jhydrol.2018.06.058, 2018.
Svensson, C., Kundzewicz, Z. W., and Maurer, T.: Trend detection in river
flow series: 2. Flood and low-flow index series, Hydrolog. Sci. J., 50, 811–824, https://doi.org/10.1623/hysj.2005.50.5.811, 2005.
Theil, H.: A Rank-Invariant Method of Linear and Polynomial Regression Analysis, in: Henri Theil's Contributions to Economics and Econometrics, Advanced Studies in Theoretical and Applied Econometrics, vol. 23, edited by: Raj, B. and Koerts, J., Springer, Dordrecht, https://doi.org/10.1007/978-94-011-2546-8_20, 1992.
Tran, H. and Ng, A.: Statistical trend analysis of river streamflows in
Victoria, in: H2O09: 32nd Hydrology and Water Resources Symposium,
Engineers Australia, 1019–1027, ISBN 97808258259461, 2009.
Turner, M.: Hydrologic Reference Station Selection Guidelines, 24 pp., http://www.bom.gov.au/water/hrs/media/static/papers/Selection_Guidelines.pdf (last access: 3 January 2023), 2012.
Van Dijk, A. I. J. M., Beck, H. E., Crosbie, R. S., De Jeu, R. A. M., Liu, Y. Y., Podger, G. M., Timbal, B., and Viney, N. R.: The Millennium Drought in
southeast Australia (2001–2009): Natural and human causes and implications
for water resources, ecosystems, economy, and society, Water Resour. Res.,
49, 1040–1057, https://doi.org/10.1002/wrcr.20123, 2013.
Villarini, G., Serinaldi, F., Smith, J. A., and Krajewski, W. F.: On the
stationarity of annual flood peaks in the continental United States during
the 20th century, Water Resour. Res., 45, W08417, https://doi.org/10.1029/2008WR007645, 2009.
von Storch, H.: Misuses of statistical analysis in climate research, in: Analysis of Climate Variability: Applications of Statistical Techniques, edited by: von Storch, H. and Navarra, A., Springer-Verlag, Berlin, https://doi.org/10.1007/978-3-662-03744-7_2, 1995.
Wasko, C. and Nathan, R.: Influence of changes in rainfall and soil moisture on trends in flooding, J. Hydrol., 575, 432–441, https://doi.org/10.1016/j.jhydrol.2019.05.054, 2019.
Wasko, C. and Sharma, A.: Global assessment of flood and storm extremes with
increased temperatures, Sci. Rep., 7, 7945, https://doi.org/10.1038/s41598-017-08481-1, 2017.
Wasko, C., Nathan, R., and Peel, M. C.: Trends in Global Flood and Streamflow
Timing Based on Local Water Year, Water Resour. Res., 56, e2020WR027233, https://doi.org/10.1029/2020WR027233, 2020.
Wasko, C., Shao, Y., Vogel, E., Wilson, L., Wang, Q. J., Frost, A., and Donnelly, C.: Understanding trends in hydrologic extremes across Australia, J. Hydrol., 593, 125877, https://doi.org/10.1016/j.jhydrol.2020.125877, 2021.
Whitfield, P. H., Burn, D. H., Hannaford, J., Higgins, H., Hodgkins, G. A.,
Marsh, T., and Looser, U.: Reference hydrologic networks I. The status and
potential future directions of national reference hydrologic networks for
detecting trends, Hydrolog. Sci. J., 57, 1562–1579, https://doi.org/10.1080/02626667.2012.728706, 2012.
Wilks, D. S.: On “field significance” and the false discovery rate, J. Appl. Meteorol. Clim., 45, 1181–1189, https://doi.org/10.1175/JAM2404.1, 2006.
Williams, A. N.: A new population curve for prehistoric Australia, P. Roy.
Soc. B, 280, 20130486, https://doi.org/10.1098/rspb.2013.0486, 2013.
Yue, S., Pilon, P., Phinney, B., and Cavadias, G.: The influence of autocorrelation on the ability to detect trend in hydrological series,
Hydrol. Process., 16, 1807–1829, https://doi.org/10.1002/hyp.1095, 2002.
Zamani, R., Mirabbasi, R., Abdollahi, S., and Jhajharia, D.: Streamflow trend analysis by considering autocorrelation structure, long-term persistence, and Hurst coefficient in a semi-arid region of Iran, Theor. Appl. Climatol., 129, 33–45, https://doi.org/10.1007/s00704-016-1747-4, 2017.
Zhang, X. S., Amirthanathan, G. E., Bari, M. A., Laugesen, R. M., Shin, D., Kent, D. M., MacDonald, A. M., Turner, M. E., and Tuteja, N. K.: How streamflow has changed across Australia since the 1950s: evidence from the network of hydrologic reference stations, Hydrol. Earth Syst. Sci., 20, 3947–3965, https://doi.org/10.5194/hess-20-3947-2016, 2016.
Zhang, Y. and Post, D.: How good are hydrological models for gap-filling streamflow data?, Hydrol. Earth Syst. Sci., 22, 4593–4604, https://doi.org/10.5194/hess-22-4593-2018, 2018.
Zhang, Y. Q., Viney, N., Frost, A., Oke, A., Brooks, M., Chen, Y., and Campbell, N.: Collation of Australian modeller's streamflow dataset for 780 unregulated Australian catchments, CSIRO, 115 pp., https://doi.org/10.4225/08/58b5baad4fcc2, 2013.
Short summary
We used statistical tests to detect annual and seasonal streamflow trends and step changes across Australia. The Murray–Darling Basin and other rivers in the southern and north-eastern areas showed decreasing trends. Only rivers in the Timor Sea region in northern Australia showed significant increasing trends. Our results assist with infrastructure planning and management of water resources. This study was undertaken by the Bureau of Meteorology with its responsibility under the Water Act 2007.
We used statistical tests to detect annual and seasonal streamflow trends and step changes...
