Articles | Volume 22, issue 6
https://doi.org/10.5194/hess-22-3533-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-22-3533-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Jun 2018
Research article |
| 29 Jun 2018
| 29 Jun 2018
Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods
Stephen P. Charles
CORRESPONDING AUTHOR
CSIRO Land and Water, Floreat, 6014, Australia
Quan J. Wang
The University of Melbourne, Parkville, 3010, Australia
Mobin-ud-Din Ahmad
CSIRO Land and Water, Canberra, 2601, Australia
Danial Hashmi
Water and Power Development Authority, Lahore, Pakistan
Andrew Schepen
CSIRO Land and Water, Dutton Park, 4102, Australia
Geoff Podger
CSIRO Land and Water, Canberra, 2601, Australia
David E. Robertson
CSIRO Land and Water, Clayton, 3168, Australia
Related authors
Nicholas J. Potter, Francis H. S. Chiew, Stephen P. Charles, Guobin Fu, Hongxing Zheng, and Lu Zhang
Hydrol. Earth Syst. Sci., 24, 2963–2979, https://doi.org/10.5194/hess-24-2963-2020, https://doi.org/10.5194/hess-24-2963-2020, 2020
Short summary
Short summary
There is a growing need for information about possible changes to water resource availability in the future due to climate change. Large-scale outputs from global climate models need to be translated to finer-resolution spatial scales before hydrological modelling. Biases in this downscaled data often need to be corrected. We show that usual bias correction methods can retain residual biases in multi-day occurrences of rainfall, which can result in biases in modelled runoff.
Stephen P. Charles, Francis H. S. Chiew, Nicholas J. Potter, Hongxing Zheng, Guobin Fu, and Lu Zhang
Hydrol. Earth Syst. Sci., 24, 2981–2997, https://doi.org/10.5194/hess-24-2981-2020, https://doi.org/10.5194/hess-24-2981-2020, 2020
Short summary
Short summary
This paper assesses the suitability of bias-corrected (BC) WRF daily rainfall across the state of Victoria, Australia, for input to hydrological models to determine plausible climate change impacts on runoff. It compares rainfall and runoff changes using BC WRF with those obtained from empirical scaling (ES) using raw WRF changes. It concludes that BC-derived changes are more plausible than ES-derived changes but that remaining biases in BC WRF daily data add uncertainty to runoff projections.
Neal Hughes, Donald Gaydon, Mihir Gupta, Andrew Schepen, Peter Tan, Geoffrey Brent, Andrew Turner, Sean Bellew, Wei Ying Soh, Christopher Sharman, Peter Taylor, John Carter, Dorine Bruget, Zvi Hochman, Ross Searle, Yong Song, Heidi Horan, Patrick Mitchell, Yacob Beletse, Dean Holzworth, Laura Guillory, Connor Brodie, Jonathon McComb, and Ramneek Singh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3731, https://doi.org/10.5194/egusphere-2024-3731, 2024
Short summary
Short summary
Droughts can impact agriculture and regional economies, and their severity is rising with climate change. Our research introduces a new system, the Australian Agricultural Drought Indicators (AADI), which measures droughts based on their effects on crops, livestock, and farm profits rather than traditional weather metrics. Using climate data and modelling, AADI predicts drought impacts more accurately, helping policymakers prepare and respond to financial and social challenges during droughts.
Yuan Li, Kangning Xü, Zhiyong Wu, Zhiwei Zhu, and Quan J. Wang
Hydrol. Earth Syst. Sci., 27, 4187–4203, https://doi.org/10.5194/hess-27-4187-2023, https://doi.org/10.5194/hess-27-4187-2023, 2023
Short summary
Short summary
A spatial–temporal projection-based calibration, bridging, and merging (STP-CBaM) method is proposed. The calibration model is built by post-processing ECMWF raw forecasts, while the bridging models are built using atmospheric intraseasonal signals as predictors. The calibration model and bridging models are merged through a Bayesian modelling averaging (BMA) method. The results indicate that the newly developed method can generate skilful and reliable sub-seasonal precipitation forecasts.
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
Qichun Yang, Quan J. Wang, Andrew W. Western, Wenyan Wu, Yawen Shao, and Kirsti Hakala
Hydrol. Earth Syst. Sci., 26, 941–954, https://doi.org/10.5194/hess-26-941-2022, https://doi.org/10.5194/hess-26-941-2022, 2022
Short summary
Short summary
Forecasts of evaporative water loss in the future are highly valuable for water resource management. These forecasts are often produced using the outputs of climate models. We developed an innovative method to correct errors in these forecasts, particularly the errors caused by deficiencies of climate models in modeling the changing climate. We apply this method to seasonal forecasts of evaporative water loss across Australia and achieve significant improvements in the forecast quality.
Qichun Yang, Quan J. Wang, Kirsti Hakala, and Yating Tang
Hydrol. Earth Syst. Sci., 25, 4773–4788, https://doi.org/10.5194/hess-25-4773-2021, https://doi.org/10.5194/hess-25-4773-2021, 2021
Short summary
Short summary
Forecasts of water losses from land surface to the air are highly valuable for water resource management and planning. In this study, we aim to fill a critical knowledge gap in the forecasting of evaporative water loss. Model experiments across Australia clearly suggest the necessity of correcting errors in input variables for more reliable water loss forecasting. We anticipate that the strategy developed in our work will benefit future water loss forecasting and lead to more skillful forecasts.
Nicholas J. Potter, Francis H. S. Chiew, Stephen P. Charles, Guobin Fu, Hongxing Zheng, and Lu Zhang
Hydrol. Earth Syst. Sci., 24, 2963–2979, https://doi.org/10.5194/hess-24-2963-2020, https://doi.org/10.5194/hess-24-2963-2020, 2020
Short summary
Short summary
There is a growing need for information about possible changes to water resource availability in the future due to climate change. Large-scale outputs from global climate models need to be translated to finer-resolution spatial scales before hydrological modelling. Biases in this downscaled data often need to be corrected. We show that usual bias correction methods can retain residual biases in multi-day occurrences of rainfall, which can result in biases in modelled runoff.
Stephen P. Charles, Francis H. S. Chiew, Nicholas J. Potter, Hongxing Zheng, Guobin Fu, and Lu Zhang
Hydrol. Earth Syst. Sci., 24, 2981–2997, https://doi.org/10.5194/hess-24-2981-2020, https://doi.org/10.5194/hess-24-2981-2020, 2020
Short summary
Short summary
This paper assesses the suitability of bias-corrected (BC) WRF daily rainfall across the state of Victoria, Australia, for input to hydrological models to determine plausible climate change impacts on runoff. It compares rainfall and runoff changes using BC WRF with those obtained from empirical scaling (ES) using raw WRF changes. It concludes that BC-derived changes are more plausible than ES-derived changes but that remaining biases in BC WRF daily data add uncertainty to runoff projections.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 24, 2951–2962, https://doi.org/10.5194/hess-24-2951-2020, https://doi.org/10.5194/hess-24-2951-2020, 2020
Short summary
Short summary
BARRA is a high-resolution reanalysis dataset over the Oceania region. This study evaluates the performance of sub-daily BARRA precipitation at point and spatial scales over Australia. We find that the dataset reproduces some of the sub-daily characteristics of precipitation well, although it exhibits some spatial displacement errors, and it performs better in temperate than in tropical regions. The product is well suited to complement other estimates derived from remote sensing and rain gauges.
Ashley J. Wright, David E. Robertson, Jeffrey P. Walker, and Valentijn R. N. Pauwels
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-450, https://doi.org/10.5194/hess-2019-450, 2019
Revised manuscript not accepted
Short summary
Short summary
This paper details the development of a methodology to optimize the weighting of rainfall gauges for hydrologic simulation. In particular, catchments with a low gauge density and/or proportion of observations available are not well suited to this methodology. Application of this methodology with models that are consistent with a conceptual understanding of the rainfall-runoff process yield improvements of 7.1 % in evaluation periods.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 23, 3387–3403, https://doi.org/10.5194/hess-23-3387-2019, https://doi.org/10.5194/hess-23-3387-2019, 2019
Short summary
Short summary
BARRA is a novel regional reanalysis for Australia. Our research demonstrates that it is able to characterize a rich spatial variation in daily precipitation behaviour. In addition, its ability to represent large rainfalls is valuable for the analysis of extremes. It is a useful complement to existing precipitation datasets for Australia, especially in sparsely gauged regions.
Andrew Schepen, Tongtiegang Zhao, Quan J. Wang, and David E. Robertson
Hydrol. Earth Syst. Sci., 22, 1615–1628, https://doi.org/10.5194/hess-22-1615-2018, https://doi.org/10.5194/hess-22-1615-2018, 2018
Short summary
Short summary
Rainfall forecasts from dynamical global climate models (GCMs) require post-processing before use in hydrological models. Existing methods generally lack the sophistication to achieve calibrated forecasts of both daily amounts and seasonal accumulated totals. We develop a new statistical method to post-process Australian GCM rainfall forecasts for 12 perennial and ephemeral catchments. Our method produces reliable forecasts and outperforms the most commonly used statistical method.
Nicola Grigg, Tira Foran, Toni Darbas, Mac Kirby, Matthew J. Colloff, Mobin-ud-Din Ahmad, and Geoff Podger
Proc. IAHS, 376, 9–13, https://doi.org/10.5194/piahs-376-9-2018, https://doi.org/10.5194/piahs-376-9-2018, 2018
Short summary
Short summary
We draw on previous work examining likely future water use and food availability in Pakistan and extend the analysis to consider hydropower generation and energy demand in food production. The biophysical limits of the water-energy-food nexus are just one piece of the picture. We also draw on critical social science and resilience or adaptation-oriented perspectives to consider options usually deemed out of scope for biophysical scientists or water, energy and agricultural authorities.
James C. Bennett, Quan J. Wang, David E. Robertson, Andrew Schepen, Ming Li, and Kelvin Michael
Hydrol. Earth Syst. Sci., 21, 6007–6030, https://doi.org/10.5194/hess-21-6007-2017, https://doi.org/10.5194/hess-21-6007-2017, 2017
Short summary
Short summary
We assess a new streamflow forecasting system in Australia. The system is designed to meet the need of water agencies for 12-month forecasts. The forecasts perform well in a wide range of rivers. Forecasts for shorter periods (up to 6 months) are generally informative. Forecasts sometimes did not perform well in a few very dry rivers. We test several techniques for improving streamflow forecasts in drylands, with mixed success.
Sean W. D. Turner, James C. Bennett, David E. Robertson, and Stefano Galelli
Hydrol. Earth Syst. Sci., 21, 4841–4859, https://doi.org/10.5194/hess-21-4841-2017, https://doi.org/10.5194/hess-21-4841-2017, 2017
Short summary
Short summary
This study investigates the relationship between skill and value of ensemble seasonal streamflow forecasts. Using data from a modern forecasting system, we show that skilled forecasts are more likely to provide benefits for reservoirs operated to maintain a target water level rather than reservoirs operated to satisfy a target demand. We identify the primary causes for this behaviour and provide specific recommendations for assessing the value of forecasts for reservoirs with supply objectives.
Ashley Wright, Jeffrey P. Walker, David E. Robertson, and Valentijn R. N. Pauwels
Hydrol. Earth Syst. Sci., 21, 3827–3838, https://doi.org/10.5194/hess-21-3827-2017, https://doi.org/10.5194/hess-21-3827-2017, 2017
Short summary
Short summary
The accurate reduction of hydrologic model input data is an impediment towards understanding input uncertainty and model structural errors. This paper compares the ability of two transforms to reduce rainfall input data. The resultant transforms are compressed to varying extents and reconstructed before being evaluated with standard simulation performance summary metrics and descriptive statistics. It is concluded the discrete wavelet transform is most capable of preserving rainfall time series.
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.
Ming Li, Q. J. Wang, James C. Bennett, and David E. Robertson
Hydrol. Earth Syst. Sci., 20, 3561–3579, https://doi.org/10.5194/hess-20-3561-2016, https://doi.org/10.5194/hess-20-3561-2016, 2016
C. Alvarez-Garreton, D. Ryu, A. W. Western, C.-H. Su, W. T. Crow, D. E. Robertson, and C. Leahy
Hydrol. Earth Syst. Sci., 19, 1659–1676, https://doi.org/10.5194/hess-19-1659-2015, https://doi.org/10.5194/hess-19-1659-2015, 2015
Short summary
Short summary
We assimilate satellite soil moisture into a rainfall-runoff model for improving flood prediction within a data-scarce region. We argue that the spatially distributed satellite data can alleviate the model prediction limitations. We show that satellite soil moisture DA reduces the uncertainty of the streamflow ensembles. We propose new techniques for the DA scheme, including seasonal error characterisation, bias correction of the satellite retrievals, and model error representation.
M. Li, Q. J. Wang, J. C. Bennett, and D. E. Robertson
Hydrol. Earth Syst. Sci., 19, 1–15, https://doi.org/10.5194/hess-19-1-2015, https://doi.org/10.5194/hess-19-1-2015, 2015
J. C. Bennett, Q. J. Wang, P. Pokhrel, and D. E. Robertson
Nat. Hazards Earth Syst. Sci., 14, 219–233, https://doi.org/10.5194/nhess-14-219-2014, https://doi.org/10.5194/nhess-14-219-2014, 2014
D. E. Robertson, D. L. Shrestha, and Q. J. Wang
Hydrol. Earth Syst. Sci., 17, 3587–3603, https://doi.org/10.5194/hess-17-3587-2013, https://doi.org/10.5194/hess-17-3587-2013, 2013
D. L. Shrestha, D. E. Robertson, Q. J. Wang, T. C. Pagano, and H. A. P. Hapuarachchi
Hydrol. Earth Syst. Sci., 17, 1913–1931, https://doi.org/10.5194/hess-17-1913-2013, https://doi.org/10.5194/hess-17-1913-2013, 2013
P. Pokhrel, D. E. Robertson, and Q. J. Wang
Hydrol. Earth Syst. Sci., 17, 795–804, https://doi.org/10.5194/hess-17-795-2013, https://doi.org/10.5194/hess-17-795-2013, 2013
D. E. Robertson, P. Pokhrel, and Q. J. Wang
Hydrol. Earth Syst. Sci., 17, 579–593, https://doi.org/10.5194/hess-17-579-2013, https://doi.org/10.5194/hess-17-579-2013, 2013
Related subject area
Subject: Water Resources Management | Techniques and Approaches: Modelling approaches
Modeling hydropower operations at the scale of a power grid: a demand-based approach
Determining the threshold of issuing flash flood warnings based on people's response process simulation
Modeling water balance components of conifer species using the Noah-MP model in an eastern Mediterranean ecosystem
Assessment of upscaling methodologies for daily crop transpiration using sap flows and two-source energy balance models in almonds under different water statuses and production systems
Making a case for power-sensitive water modelling: a literature review
Developing water supply reservoir operating rules for large-scale hydrological modelling
An investigation of anthropogenic influences on hydrologic connectivity using model stress tests
The H2Ours game to explore water use, resources and sustainability: connecting issues in two landscapes in Indonesia
Drainage assessment of irrigation districts: on the precision and accuracy of four parsimonious models
Impact of reservoir evaporation on future water availability in north-eastern Brazil: a multi-scenario assessment
How economically and environmentally viable are multiple dams in the upper Cauvery Basin, India? A hydro-economic analysis using a landscape-based hydrological model
Leveraging a novel hybrid ensemble and optimal interpolation approach for enhanced streamflow and flood prediction
Optimising Ensemble Streamflow Predictions with Bias-Correction and Data Assimilation Techniques
Extracting Spatiotemporal Flood Information from News Texts Using Machine Learning for a National Dataset in China
The interprovincial green water flow in China and its tele-connected effects on socio-economy
Spatially explicit assessment of water scarcity and potential mitigating solutions in a large water-limited basin: the Yellow River basin in China
A generalised ecohydrological landscape classification for assessing ecosystem risk in Australia due to an altering water regime
A scalable and modular reservoir implementation for large scale integrated hydrologic simulations
Process-based three-layer synergistic optimal-allocation model for complex water resource systems considering reclaimed water
Joint optimal operation of the South-to-North Water Diversion Project considering the evenness of water deficit
Employing the generalized Pareto distribution to analyze extreme rainfall events on consecutive rainy days in Thailand's Chi watershed: implications for flood management
How to account for irrigation withdrawals in a watershed model
Inferring reservoir filling strategies under limited-data-availability conditions using hydrological modeling and Earth observations: the case of the Grand Ethiopian Renaissance Dam (GERD)
The precision of satellite-based net irrigation quantification in the Indus and Ganges basins
Developing a Bayesian network model for understanding river catchment resilience under future change scenarios
Quantifying the trade-offs in re-operating dams for the environment in the Lower Volta River
Dynamically coupling system dynamics and SWAT+ models using Tinamït: application of modular tools for coupled human–water system models
Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes
Cooperation in a transboundary river basin: a large-scale socio-hydrological model of the Eastern Nile
Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts
An improved model of shade-affected stream temperature in Soil & Water Assessment Tool
Seasonal forecasting of snow resources at Alpine sites
Operationalizing equity in multipurpose water systems
Evaluation of a new observationally based channel parameterization for the National Water Model
High-resolution drought simulations and comparison to soil moisture observations in Germany
Cooperation under conflict: participatory hydrological modeling for science policy dialogues for the Aculeo Lake
Socio-hydrological modeling of the tradeoff between flood control and hydropower provided by the Columbia River Treaty
Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP
A system dynamic model to quantify the impacts of water resources allocation on water–energy–food–society (WEFS) nexus
Net irrigation requirement under different climate scenarios using AquaCrop over Europe
The role of multi-criteria decision analysis in a transdisciplinary process: co-developing a flood forecasting system in western Africa
Unfolding the relationship between seasonal forecast skill and value in hydropower production: a global analysis
Drought impact links to meteorological drought indicators and predictability in Spain
Opportunities for seasonal forecasting to support water management outside the tropics
Probabilistic modelling of the inherent field-level pesticide pollution risk in a small drinking water catchment using spatial Bayesian belief networks
Are maps of nitrate reduction in groundwater altered by climate and land use changes?
Historical simulation of maize water footprints with a new global gridded crop model ACEA
Future upstream water consumption and its impact on downstream water availability in the transboundary Indus Basin
Identifying the dynamic evolution and feedback process of water resources nexus system considering socioeconomic development, ecological protection, and food security: A practical tool for sustainable water use
Optimizing a backscatter forward operator using Sentinel-1 data over irrigated land
Laure Baratgin, Jan Polcher, Patrice Dumas, and Philippe Quirion
Hydrol. Earth Syst. Sci., 28, 5479–5509, https://doi.org/10.5194/hess-28-5479-2024, https://doi.org/10.5194/hess-28-5479-2024, 2024
Short summary
Short summary
Hydrological modeling is valuable for estimating the potential impact of climate change on hydropower generation. This study presents a comprehensive approach to modeling the management of hydroelectric reservoirs in hydrological models. The total power grid demand for hydropower is distributed to the various power plants to compute their release. The method is tested on the French national power grid, and it is demonstrated that it successfully reproduces the observed behavior of reservoirs.
Ruikang Zhang, Dedi Liu, Lihua Xiong, Jie Chen, Hua Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 28, 5229–5247, https://doi.org/10.5194/hess-28-5229-2024, https://doi.org/10.5194/hess-28-5229-2024, 2024
Short summary
Short summary
Flash flood warnings cannot be effective without people’s responses to them. We propose a method to determine the threshold of issuing warnings based on a people’s response process simulation. The results show that adjusting the warning threshold according to people’s tolerance levels to the failed warnings can improve warning effectiveness, but the prerequisite is to increase forecasting accuracy and decrease forecasting variance.
Mohsen Amini Fasakhodi, Hakan Djuma, Ioannis Sofokleous, Marinos Eliades, and Adriana Bruggeman
Hydrol. Earth Syst. Sci., 28, 5209–5227, https://doi.org/10.5194/hess-28-5209-2024, https://doi.org/10.5194/hess-28-5209-2024, 2024
Short summary
Short summary
This study examined the water use of pine and cypress trees in a semiarid Mediterranean forest environment. We applied a widely used land surface model (Noah-MP) to simulate the water balance of the ecosystem. We found good modeling results for soil moisture. However, the model underestimated the transpiration of the trees during the dry summer months. These findings indicate that more research is needed to improve the modeling of ecosystem responses to climate and land use change.
Manuel Quintanilla-Albornoz, Xavier Miarnau, Ana Pelechá, Héctor Nieto, and Joaquim Bellvert
Hydrol. Earth Syst. Sci., 28, 4797–4818, https://doi.org/10.5194/hess-28-4797-2024, https://doi.org/10.5194/hess-28-4797-2024, 2024
Short summary
Short summary
Remote sensing can be a helpful tool for monitoring crop transpiration (T) for agricultural water management. Since remote sensing provides instantaneous data, upscaling techniques are required to estimate T on a daily scale. This study assesses optimal image acquisition times and four upscaling approaches to estimate daily T. The results indicate that the main errors derive from measurement time and water stress levels, which can be mitigated by choosing a proper upscaling approach.
Rozemarijn ter Horst, Rossella Alba, Jeroen Vos, Maria Rusca, Jonatan Godinez-Madrigal, Lucie V. Babel, Gert Jan Veldwisch, Jean-Philippe Venot, Bruno Bonté, David W. Walker, and Tobias Krueger
Hydrol. Earth Syst. Sci., 28, 4157–4186, https://doi.org/10.5194/hess-28-4157-2024, https://doi.org/10.5194/hess-28-4157-2024, 2024
Short summary
Short summary
The exact power of models often remains hidden, especially when neutrality is claimed. Our review of 61 scientific articles shows that in the scientific literature little attention is given to the power of water models to influence development processes and outcomes. However, there is a lot to learn from those who are openly reflexive. Based on lessons from the review, we call for power-sensitive modelling, which means that people are critical about how models are made and with what effects.
Saskia Salwey, Gemma Coxon, Francesca Pianosi, Rosanna Lane, Chris Hutton, Michael Bliss Singer, Hilary McMillan, and Jim Freer
Hydrol. Earth Syst. Sci., 28, 4203–4218, https://doi.org/10.5194/hess-28-4203-2024, https://doi.org/10.5194/hess-28-4203-2024, 2024
Short summary
Short summary
Reservoirs are essential for water resource management and can significantly impact downstream flow. However, representing reservoirs in hydrological models can be challenging, particularly across large scales. We design a new and simple method for simulating river flow downstream of water supply reservoirs using only open-access data. We demonstrate the approach in 264 reservoir catchments across Great Britain, where we can significantly improve the simulation of reservoir-impacted flow.
Amelie Herzog, Jost Hellwig, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 28, 4065–4083, https://doi.org/10.5194/hess-28-4065-2024, https://doi.org/10.5194/hess-28-4065-2024, 2024
Short summary
Short summary
Surface water–groundwater interaction can vary along a river. This study used a groundwater model that reproduced relative observed longitudinal and vertical connectivity patterns in the river network to assess the system's response to imposed stress tests. For the case study, imposed groundwater abstraction appears to influence connectivity relatively more than altered recharge, but a quantification of absolute exchange flows will require further model improvements.
Lisa Tanika, Rika Ratna Sari, Arief Lukman Hakim, Meine van Noordwijk, Marielos Peña-Claros, Beria Leimona, Edi Purwanto, and Erika N. Speelman
Hydrol. Earth Syst. Sci., 28, 3807–3835, https://doi.org/10.5194/hess-28-3807-2024, https://doi.org/10.5194/hess-28-3807-2024, 2024
Short summary
Short summary
The H2Ours game is designed to facilitate knowledge transfer and sharing among stakeholders to trigger commitment and collaborative action to restore hydrological conditions. The adaptability of the H2Ours game was proven in two different landscapes: groundwater recharge in upper to middle sub-watersheds with (over)use of water in the lowland zone and a peatland with drainage, rewetting, oil palm conversion and fire as issues. The game evaluation shows that the H2Ours game meets its purpose.
Pierre Laluet, Luis Olivera-Guerra, Víctor Altés, Vincent Rivalland, Alexis Jeantet, Julien Tournebize, Omar Cenobio-Cruz, Anaïs Barella-Ortiz, Pere Quintana-Seguí, Josep Maria Villar, and Olivier Merlin
Hydrol. Earth Syst. Sci., 28, 3695–3716, https://doi.org/10.5194/hess-28-3695-2024, https://doi.org/10.5194/hess-28-3695-2024, 2024
Short summary
Short summary
Monitoring agricultural drainage flow in irrigated areas is key to water and soil management. In this paper, four simple drainage models are evaluated on two irrigated sub-basins where drainage flow is measured daily. The evaluation of their precision shows that they simulate drainage very well when calibrated with drainage data and that one of them is slightly better. The evaluation of their accuracy shows that only one model can provide rough drainage estimates without calibration data.
Gláuber Pontes Rodrigues, Arlena Brosinsky, Ítalo Sampaio Rodrigues, George Leite Mamede, and José Carlos de Araújo
Hydrol. Earth Syst. Sci., 28, 3243–3260, https://doi.org/10.5194/hess-28-3243-2024, https://doi.org/10.5194/hess-28-3243-2024, 2024
Short summary
Short summary
The research focuses on a 4-million-inhabitant tropical region supplied by a network of open-water reservoirs where the dry season lasts for 8 months (Jun−Dec). We analysed the impact of four climate change scenarios on the evaporation rate and the associated availability (water yield distributed per year). The worst-case scenario shows that by the end of the century (2071−2099), the evaporation rate in the dry season could increase by 6 %, which would reduce stored water by about 80 %.
Anjana Ekka, Yong Jiang, Saket Pande, and Pieter van der Zaag
Hydrol. Earth Syst. Sci., 28, 3219–3241, https://doi.org/10.5194/hess-28-3219-2024, https://doi.org/10.5194/hess-28-3219-2024, 2024
Short summary
Short summary
For the first time, we analyse the economic and ecological performance of existing multiple big reservoirs on a daily timescale for a major river basin (upper Cauvery) in India, where pre-intervention data were not available but where there are increasing calls for such assessments. Results show that smaller reservoirs on smaller streams that maximize the economic value of stored water are better for the basin economy and the environment. The approach can help to prioritize dam removals.
Mohamad El Gharamti, Arezoo Rafieeinasab, and James L. McCreight
Hydrol. Earth Syst. Sci., 28, 3133–3159, https://doi.org/10.5194/hess-28-3133-2024, https://doi.org/10.5194/hess-28-3133-2024, 2024
Short summary
Short summary
This study introduces a hybrid data assimilation scheme for precise streamflow predictions during intense rainfall and hurricanes. Tested in real events, it outperforms traditional methods by up to 50 %, utilizing ensemble and climatological background covariances. The adaptive algorithm ensures reliability with a small ensemble, offering improved forecasts up to 18 h in advance, marking a significant advancement in flood prediction capabilities.
Maliko Tanguy, Michael Eastman, Amulya Chevuturi, Eugene Magee, Elizabeth Cooper, Robert H. B. Johnson, Katie Facer-Childs, and Jamie Hannaford
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-179, https://doi.org/10.5194/hess-2024-179, 2024
Preprint under review for HESS
Short summary
Short summary
Our research compares two techniques, Bias-Correction (BC) and Data Assimilation (DA), for improving river flow forecasts across 316 UK catchments. BC, which corrects errors post-simulation, showed broad improvements, while DA, adjusting model states pre-forecast, excelled in specific conditions like snowmelt and high base flows. Each method's unique strengths suit different scenarios. These insights can enhance forecasting systems, offering reliable and user-friendly hydrological predictions.
Shengnan Fu, David M. Schultz, Heng Lyu, Zhonghua Zheng, and Chi Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-146, https://doi.org/10.5194/hess-2024-146, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
To address the lack of county-level flood dataset in China, we used machine learning techniques to accurately identify flood events and locations from news reports. This dataset offers crucial insights into the spatiotemporal distribution of urban flooding from 2000 to 2022, highlighting increases in flood occurrences and identifying key vulnerable areas. These findings are vital for enhancing urban planning in China, aiming to mitigate the impact of future floods.
Shan Sang, Yan Li, Chengcheng Hou, Shuangshuang Zi, and Huiqing Lin
EGUsphere, https://doi.org/10.5194/egusphere-2024-1420, https://doi.org/10.5194/egusphere-2024-1420, 2024
Short summary
Short summary
Green water flow among each province in China embodies substantial socio-economic values. Green water flow and its tele-connected socio-economic effects should be considered in water resources management in additional to blue water.
Weibin Zhang, Xining Zhao, Xuerui Gao, Wei Liang, Junyi Li, and Baoqing Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-88, https://doi.org/10.5194/hess-2024-88, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
An integrated framework was applied in the Yellow River basin to assess the water crisis. Results indicate worsening water scarcity during 1965‒2013, driven by irrigation and climate changes. Local water yield and upstream flows are key drivers of sub-basin water availability. To reduce the water deficit of 10 km3 by 2030s, enhancing irrigation efficiency and water transfer project are crucial, emphasizing the imperative of combining supply and demand-oriented measures to solve the water crisis.
Alexander Herr, Linda E. Merrin, Patrick J. Mitchell, Anthony P. O'Grady, Kate L. Holland, Richard E. Mount, David A. Post, Chris R. Pavey, and Ashley D. Sparrow
Hydrol. Earth Syst. Sci., 28, 1957–1979, https://doi.org/10.5194/hess-28-1957-2024, https://doi.org/10.5194/hess-28-1957-2024, 2024
Short summary
Short summary
We develop an ecohydrological classification for regions with limited hydrological records. It provides causal links of landscape features and their water requirement. The classification is an essential framework for modelling the impact of future coal resource developments via water on the features. A rule set combines diverse data with prioritisation, resulting in a transparent, repeatable and adjustable approach. We show examples of linking ecohydrology with environmental impacts.
Benjamin D. West, Reed M. Maxwell, and Laura E. Condon
EGUsphere, https://doi.org/10.5194/egusphere-2024-965, https://doi.org/10.5194/egusphere-2024-965, 2024
Short summary
Short summary
This article describes the addition of reservoirs to the hydrologic model, ParFlow. ParFlow is particularly good at helping us understand some of the broader drivers behind different parts of the water cycle. By having reservoirs in such a model we hope to be better able to understand both our impacts on the environment, and how to adjust our management of reservoirs to changing conditions.
Jing Liu, Yue-Ping Xu, Wei Zhang, Shiwu Wang, and Siwei Chen
Hydrol. Earth Syst. Sci., 28, 1325–1350, https://doi.org/10.5194/hess-28-1325-2024, https://doi.org/10.5194/hess-28-1325-2024, 2024
Short summary
Short summary
Applying optimal water allocation models to simultaneously enable economic benefits, water preferences, and environmental demands at different decision levels, timescales, and regions is a challenge. In this study, a process-based three-layer synergistic optimal-allocation model (PTSOA) is established to achieve these goals. Reused, reclaimed water is also coupled to capture environmentally friendly solutions. Network analysis was introduced to reduce competition among different stakeholders.
Bing-Yi Zhou, Guo-Hua Fang, Xin Li, Jian Zhou, and Hua-Yu Zhong
Hydrol. Earth Syst. Sci., 28, 817–832, https://doi.org/10.5194/hess-28-817-2024, https://doi.org/10.5194/hess-28-817-2024, 2024
Short summary
Short summary
The current unreasonable inter-basin water transfer operation leads to the problem of spatial and temporal imbalances in water allocation. This paper defines a water deficit evenness index and incorporates it into a joint optimization model for the Jiangsu section of the South-to-North Water Diversion Project considering ecology and economy. At the same time, the lake storage capacity performs well, and the water transfer efficiency of the river is significantly improved.
Tossapol Phoophiwfa, Prapawan Chomphuwiset, Thanawan Prahadchai, Jeong-Soo Park, Arthit Apichottanakul, Watchara Theppang, and Piyapatr Busababodhin
Hydrol. Earth Syst. Sci., 28, 801–816, https://doi.org/10.5194/hess-28-801-2024, https://doi.org/10.5194/hess-28-801-2024, 2024
Short summary
Short summary
This study examines the impact of extreme rainfall events on flood risk management in Thailand's Chi watershed. By analyzing historical data, we identified regions, notably Udon Thani and Chaiyaphum, with a high risk of flash flooding. To aid in flood risk assessment, visual maps were created. The study underscores the importance of preparing for extreme rainfall events, particularly in the context of climate change, to effectively mitigate potential flood damage.
Elisabeth Brochet, Youen Grusson, Sabine Sauvage, Ludovic Lhuissier, and Valérie Demarez
Hydrol. Earth Syst. Sci., 28, 49–64, https://doi.org/10.5194/hess-28-49-2024, https://doi.org/10.5194/hess-28-49-2024, 2024
Short summary
Short summary
This study aims to take into account irrigation withdrawals in a watershed model. The model we used combines agriculture and hydrological modeling. Two different crop models were compared, the first based on air temperature and the second based on Sentinel-2 satellite data. Results show that including remote sensing data leads to better emergence dates. Both methods allow us to simulate the daily irrigation withdrawals and downstream flow with a good accuracy, especially during low-flow periods.
Awad M. Ali, Lieke A. Melsen, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 27, 4057–4086, https://doi.org/10.5194/hess-27-4057-2023, https://doi.org/10.5194/hess-27-4057-2023, 2023
Short summary
Short summary
Using a new approach based on a combination of modeling and Earth observation, useful information about the filling of the Grand Ethiopian Renaissance Dam can be obtained with limited data and proper rainfall selection. While the monthly streamflow into Sudan has decreased significantly (1.2 × 109–5 × 109 m3) with respect to the non-dam scenario, the negative impact has been masked due to higher-than-average rainfall. We reveal that the dam will need 3–5 more years to complete filling.
Søren J. Kragh, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 27, 2463–2478, https://doi.org/10.5194/hess-27-2463-2023, https://doi.org/10.5194/hess-27-2463-2023, 2023
Short summary
Short summary
This study investigates the precision of irrigation estimates from a global hotspot of unsustainable irrigation practice, the Indus and Ganges basins. We show that irrigation water use can be estimated with high precision by comparing satellite and rainfed hydrological model estimates of evapotranspiration. We believe that our work can support sustainable water resource management, as it addresses the uncertainty of a key component of the water balance that remains challenging to quantify.
Kerr J. Adams, Christopher A. J. Macleod, Marc J. Metzger, Nicola Melville, Rachel C. Helliwell, Jim Pritchard, and Miriam Glendell
Hydrol. Earth Syst. Sci., 27, 2205–2225, https://doi.org/10.5194/hess-27-2205-2023, https://doi.org/10.5194/hess-27-2205-2023, 2023
Short summary
Short summary
We applied participatory methods to create a hybrid equation-based Bayesian network (BN) model to increase stakeholder understanding of catchment-scale resilience to the impacts of both climatic and socio-economic stressors to a 2050 time horizon. Our holistic systems-thinking approach enabled stakeholders to gain new perspectives on how future scenarios may influence their specific sectors and how their sector impacted other sectors and environmental conditions within the catchment system.
Afua Owusu, Jazmin Zatarain Salazar, Marloes Mul, Pieter van der Zaag, and Jill Slinger
Hydrol. Earth Syst. Sci., 27, 2001–2017, https://doi.org/10.5194/hess-27-2001-2023, https://doi.org/10.5194/hess-27-2001-2023, 2023
Short summary
Short summary
The construction of two dams in the Lower Volta River, Ghana, adversely affected downstream riverine ecosystems and communities. In contrast, Ghana has enjoyed vast economic benefits from the dams. Herein lies the challenge; there exists a trade-off between water for river ecosystems and water for anthropogenic water demands such hydropower. In this study, we quantify these trade-offs and show that there is room for providing environmental flows under current and future climatic conditions.
Joel Z. Harms, Julien J. Malard-Adam, Jan F. Adamowski, Ashutosh Sharma, and Albert Nkwasa
Hydrol. Earth Syst. Sci., 27, 1683–1693, https://doi.org/10.5194/hess-27-1683-2023, https://doi.org/10.5194/hess-27-1683-2023, 2023
Short summary
Short summary
To facilitate the meaningful participation of stakeholders in water management, model choice is crucial. We show how system dynamics models (SDMs), which are very visual and stakeholder-friendly, can be automatically combined with physically based hydrological models that may be more appropriate for modelling the water processes of a human–water system. This allows building participatory SDMs with stakeholders and delegating hydrological components to an external hydrological model.
Erhu Du, Feng Wu, Hao Jiang, Naliang Guo, Yong Tian, and Chunmiao Zheng
Hydrol. Earth Syst. Sci., 27, 1607–1626, https://doi.org/10.5194/hess-27-1607-2023, https://doi.org/10.5194/hess-27-1607-2023, 2023
Short summary
Short summary
This study develops an integrated socio-hydrological modeling framework that can simulate the entire flood management processes, including flood inundation, flood management policies, public responses, and evacuation activities. The model is able to holistically examine flood evacuation performance under the joint impacts of hydrological conditions, management policies (i.e., shelter location distribution), and human behaviors (i.e., evacuation preparation time and route-searching strategy).
Mohammad Ghoreishi, Amin Elshorbagy, Saman Razavi, Günter Blöschl, Murugesu Sivapalan, and Ahmed Abdelkader
Hydrol. Earth Syst. Sci., 27, 1201–1219, https://doi.org/10.5194/hess-27-1201-2023, https://doi.org/10.5194/hess-27-1201-2023, 2023
Short summary
Short summary
The study proposes a quantitative model of the willingness to cooperate in the Eastern Nile River basin. Our results suggest that the 2008 food crisis may account for Sudan recovering its willingness to cooperate with Ethiopia. Long-term lack of trust among the riparian countries may have reduced basin-wide cooperation. The model can be used to explore the effects of changes in future dam operations and other management decisions on the emergence of basin cooperation.
Richard Laugesen, Mark Thyer, David McInerney, and Dmitri Kavetski
Hydrol. Earth Syst. Sci., 27, 873–893, https://doi.org/10.5194/hess-27-873-2023, https://doi.org/10.5194/hess-27-873-2023, 2023
Short summary
Short summary
Forecasts may be valuable for user decisions, but current practice to quantify it has critical limitations. This study introduces RUV (relative utility value, a new metric that can be tailored to specific decisions and decision-makers. It illustrates how critical this decision context is when evaluating forecast value. This study paves the way for agencies to tailor the evaluation of their services to customer decisions and researchers to study model improvements through the lens of user impact.
Efrain Noa-Yarasca, Meghna Babbar-Sebens, and Chris Jordan
Hydrol. Earth Syst. Sci., 27, 739–759, https://doi.org/10.5194/hess-27-739-2023, https://doi.org/10.5194/hess-27-739-2023, 2023
Short summary
Short summary
Riparian vegetation has been identified as a strategy to control rising stream temperatures by shading streams. Riparian vegetation is included within a sub-basin-scale hydrological model and evaluated for full and efficient restoration scenarios. Results showed average temperature reductions of 0.91 and 0.86 °C for full and efficient riparian restoration, respectively. Notwithstanding the similar benefits, efficient restoration was 14.4 % cheaper than full riparian vegetation restoration.
Silvia Terzago, Giulio Bongiovanni, and Jost von Hardenberg
Hydrol. Earth Syst. Sci., 27, 519–542, https://doi.org/10.5194/hess-27-519-2023, https://doi.org/10.5194/hess-27-519-2023, 2023
Short summary
Short summary
Reliable seasonal forecasts of the abundance of mountain snowpack over the winter/spring ahead provide valuable information for water management, hydropower production and ski tourism. We present a climate service prototype to generate multi-model ensemble seasonal forecasts of mountain snow depth, based on Copernicus seasonal forecast system meteorological data used to force the SNOWPACK model. The prototype shows skill at predicting snow depth below and above normal and extremely dry seasons.
Guang Yang, Matteo Giuliani, and Andrea Castelletti
Hydrol. Earth Syst. Sci., 27, 69–81, https://doi.org/10.5194/hess-27-69-2023, https://doi.org/10.5194/hess-27-69-2023, 2023
Short summary
Short summary
Participatory decision-making is a well-established approach to address the increasing pressure on water systems that searches for system-wise efficient solutions but often does not quantify how the resulting benefits are distributed across stakeholders. In this work, we show how including equity principles into the design of water system operations enriches the solution space by generating more compromise solutions that balance efficiency and justice.
Aaron Heldmyer, Ben Livneh, James McCreight, Laura Read, Joseph Kasprzyk, and Toby Minear
Hydrol. Earth Syst. Sci., 26, 6121–6136, https://doi.org/10.5194/hess-26-6121-2022, https://doi.org/10.5194/hess-26-6121-2022, 2022
Short summary
Short summary
Measurements of channel characteristics are important for accurate forecasting in the NOAA National Water Model (NWM) but are scarcely available. We seek to improve channel representativeness in the NWM by updating channel geometry and roughness parameters using a large, previously unpublished, dataset of approximately 48 000 gauges. We find that the updated channel parameterization from this new dataset leads to improvements in simulated streamflow performance and channel representation.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx
Hydrol. Earth Syst. Sci., 26, 5137–5161, https://doi.org/10.5194/hess-26-5137-2022, https://doi.org/10.5194/hess-26-5137-2022, 2022
Short summary
Short summary
In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Anahi Ocampo-Melgar, Pilar Barría, Cristián Chadwick, and Cesar Rivas
Hydrol. Earth Syst. Sci., 26, 5103–5118, https://doi.org/10.5194/hess-26-5103-2022, https://doi.org/10.5194/hess-26-5103-2022, 2022
Short summary
Short summary
This article examines how a hydrological model exploring the causes of a lake desiccation was turned into a 5-step participatory process to better adjust the model to address questions that were causing suspicions and conflicts in the community. Although the process was key in finding a combination of strategies that were of moderate impact and higher local acceptability, we address the challenges of such collaboration in modeling when conflict is deeply embedded in the context.
Ashish Shrestha, Felipe Augusto Arguello Souza, Samuel Park, Charlotte Cherry, Margaret Garcia, David J. Yu, and Eduardo Mario Mendiondo
Hydrol. Earth Syst. Sci., 26, 4893–4917, https://doi.org/10.5194/hess-26-4893-2022, https://doi.org/10.5194/hess-26-4893-2022, 2022
Short summary
Short summary
Equitable sharing of benefits is key to successful cooperation in transboundary water resource management. However, external changes can shift the split of benefits and shifts in the preferences regarding how an actor’s benefits compare to the other’s benefits. To understand how these changes can impact the robustness of cooperative agreements, we develop a socio-hydrological system dynamics model of the benefit sharing provision of the Columbia River Treaty and assess a series of scenarios.
Sara Modanesi, Christian Massari, Michel Bechtold, Hans Lievens, Angelica Tarpanelli, Luca Brocca, Luca Zappa, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 4685–4706, https://doi.org/10.5194/hess-26-4685-2022, https://doi.org/10.5194/hess-26-4685-2022, 2022
Short summary
Short summary
Given the crucial impact of irrigation practices on the water cycle, this study aims at estimating irrigation through the development of an innovative data assimilation system able to ingest high-resolution Sentinel-1 radar observations into the Noah-MP land surface model. The developed methodology has important implications for global water resource management and the comprehension of human impacts on the water cycle and identifies main challenges and outlooks for future research.
Yujie Zeng, Dedi Liu, Shenglian Guo, Lihua Xiong, Pan Liu, Jiabo Yin, and Zhenhui Wu
Hydrol. Earth Syst. Sci., 26, 3965–3988, https://doi.org/10.5194/hess-26-3965-2022, https://doi.org/10.5194/hess-26-3965-2022, 2022
Short summary
Short summary
The sustainability of the water–energy–food (WEF) nexus remains challenge, as interactions between WEF and human sensitivity and water resource allocation in water systems are often neglected. We incorporated human sensitivity and water resource allocation into a WEF nexus and assessed their impacts on the integrated system. This study can contribute to understanding the interactions across the water–energy–food–society nexus and improving the efficiency of resource management.
Louise Busschaert, Shannon de Roos, Wim Thiery, Dirk Raes, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 3731–3752, https://doi.org/10.5194/hess-26-3731-2022, https://doi.org/10.5194/hess-26-3731-2022, 2022
Short summary
Short summary
Increasing amounts of water are used for agriculture. Therefore, we looked into how irrigation requirements will evolve under a changing climate over Europe. Our results show that, by the end of the century and under high emissions, irrigation water will increase by 30 % on average compared to the year 2000. Also, the irrigation requirement is likely to vary more from 1 year to another. However, if emissions are mitigated, these effects are reduced.
Judit Lienert, Jafet C. M. Andersson, Daniel Hofmann, Francisco Silva Pinto, and Martijn Kuller
Hydrol. Earth Syst. Sci., 26, 2899–2922, https://doi.org/10.5194/hess-26-2899-2022, https://doi.org/10.5194/hess-26-2899-2022, 2022
Short summary
Short summary
Many western Africans encounter serious floods every year. The FANFAR project co-designed a pre-operational flood forecasting system (FEWS) with 50 key western African stakeholders. Participatory multi-criteria decision analysis (MCDA) helped prioritize a FEWS that meets their needs: it should provide accurate, clear, and timely flood risk information and work reliably in tough conditions. As a theoretical contribution, we propose an assessment framework for transdisciplinary hydrology research.
Donghoon Lee, Jia Yi Ng, Stefano Galelli, and Paul Block
Hydrol. Earth Syst. Sci., 26, 2431–2448, https://doi.org/10.5194/hess-26-2431-2022, https://doi.org/10.5194/hess-26-2431-2022, 2022
Short summary
Short summary
To fully realize the potential of seasonal streamflow forecasts in the hydropower industry, we need to understand the relationship between reservoir design specifications, forecast skill, and value. Here, we rely on realistic forecasts and simulated hydropower operations for 753 dams worldwide to unfold such relationship. Our analysis shows how forecast skill affects hydropower production, what type of dams are most likely to benefit from seasonal forecasts, and where these dams are located.
Herminia Torelló-Sentelles and Christian L. E. Franzke
Hydrol. Earth Syst. Sci., 26, 1821–1844, https://doi.org/10.5194/hess-26-1821-2022, https://doi.org/10.5194/hess-26-1821-2022, 2022
Short summary
Short summary
Drought affects many regions worldwide, and future climate projections imply that drought severity and frequency will increase. Hence, the impacts of drought on the environment and society will also increase considerably. Monitoring and early warning systems for drought rely on several indicators; however, assessments on how these indicators are linked to impacts are still lacking. Our results show that meteorological indices are best linked to impact occurrences.
Leah A. Jackson-Blake, François Clayer, Elvira de Eyto, Andrew S. French, María Dolores Frías, Daniel Mercado-Bettín, Tadhg Moore, Laura Puértolas, Russell Poole, Karsten Rinke, Muhammed Shikhani, Leon van der Linden, and Rafael Marcé
Hydrol. Earth Syst. Sci., 26, 1389–1406, https://doi.org/10.5194/hess-26-1389-2022, https://doi.org/10.5194/hess-26-1389-2022, 2022
Short summary
Short summary
We explore, together with stakeholders, whether seasonal forecasting of water quantity, quality, and ecology can help support water management at five case study sites, primarily in Europe. Reliable forecasting, a season in advance, has huge potential to improve decision-making. However, managers were reluctant to use the forecasts operationally. Key barriers were uncertainty and often poor historic performance. The importance of practical hands-on experience was also highlighted.
Mads Troldborg, Zisis Gagkas, Andy Vinten, Allan Lilly, and Miriam Glendell
Hydrol. Earth Syst. Sci., 26, 1261–1293, https://doi.org/10.5194/hess-26-1261-2022, https://doi.org/10.5194/hess-26-1261-2022, 2022
Short summary
Short summary
Pesticides continue to pose a threat to surface water quality worldwide. Here, we present a spatial Bayesian belief network (BBN) for assessing inherent pesticide risk to water quality. The BBN was applied in a small catchment with limited data to simulate the risk of five pesticides and evaluate the likely effectiveness of mitigation measures. The probabilistic graphical model combines diverse data and explicitly accounts for uncertainties, which are often ignored in pesticide risk assessments.
Ida Karlsson Seidenfaden, Torben Obel Sonnenborg, Jens Christian Refsgaard, Christen Duus Børgesen, Jørgen Eivind Olesen, and Dennis Trolle
Hydrol. Earth Syst. Sci., 26, 955–973, https://doi.org/10.5194/hess-26-955-2022, https://doi.org/10.5194/hess-26-955-2022, 2022
Short summary
Short summary
This study investigates how the spatial nitrate reduction in the subsurface may shift under changing climate and land use conditions. This change is investigated by comparing maps showing the spatial nitrate reduction in an agricultural catchment for current conditions, with maps generated for future projected climate and land use conditions. Results show that future climate flow paths may shift the catchment reduction noticeably, while implications of land use changes were less substantial.
Oleksandr Mialyk, Joep F. Schyns, Martijn J. Booij, and Rick J. Hogeboom
Hydrol. Earth Syst. Sci., 26, 923–940, https://doi.org/10.5194/hess-26-923-2022, https://doi.org/10.5194/hess-26-923-2022, 2022
Short summary
Short summary
As the global demand for crops is increasing, it is vital to understand spatial and temporal patterns of crop water footprints (WFs). Previous studies looked into spatial patterns but not into temporal ones. Here, we present a new process-based gridded crop model to simulate WFs and apply it for maize in 1986–2016. We show that despite the average unit WF reduction (−35 %), the global WF of maize production has increased (+50 %), which might harm ecosystems and human livelihoods in some regions.
Wouter J. Smolenaars, Sanita Dhaubanjar, Muhammad K. Jamil, Arthur Lutz, Walter Immerzeel, Fulco Ludwig, and Hester Biemans
Hydrol. Earth Syst. Sci., 26, 861–883, https://doi.org/10.5194/hess-26-861-2022, https://doi.org/10.5194/hess-26-861-2022, 2022
Short summary
Short summary
The arid plains of the lower Indus Basin rely heavily on the water provided by the mountainous upper Indus. Rapid population growth in the upper Indus is expected to increase the water that is consumed there. This will subsequently reduce the water that is available for the downstream plains, where the population and water demand are also expected to grow. In future, this may aggravate tensions over the division of water between the countries that share the Indus Basin.
Yaogeng Tan, Zengchuan Dong, Sandra M. Guzman, Xinkui Wang, and Wei Yan
Hydrol. Earth Syst. Sci., 25, 6495–6522, https://doi.org/10.5194/hess-25-6495-2021, https://doi.org/10.5194/hess-25-6495-2021, 2021
Short summary
Short summary
The rapid increase in economic development and urbanization is contributing to the imbalances and conflicts between water supply and demand and further deteriorates river ecological health, which intensifies their interactions and causes water unsustainability. This paper proposes a methodology for sustainable development of water resources, considering socioeconomic development, food safety, and ecological protection, and the dynamic interactions across those water users are further assessed.
Sara Modanesi, Christian Massari, Alexander Gruber, Hans Lievens, Angelica Tarpanelli, Renato Morbidelli, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 6283–6307, https://doi.org/10.5194/hess-25-6283-2021, https://doi.org/10.5194/hess-25-6283-2021, 2021
Short summary
Short summary
Worldwide, the amount of water used for agricultural purposes is rising and the quantification of irrigation is becoming a crucial topic. Land surface models are not able to correctly simulate irrigation. Remote sensing observations offer an opportunity to fill this gap as they are directly affected by irrigation. We equipped a land surface model with an observation operator able to transform Sentinel-1 backscatter observations into realistic vegetation and soil states via data assimilation.
Cited articles
Afzal, M., Haroon, M. A., Rana, A. S., and Imran, A.: Influence of North
Atlantic Oscillations and Southern Oscillations on winter precipitation of
northern Pakistan, Pakistan J. Meteorol., 9, 1–8, 2013.
Ahmed, K. and Sanchez, M.: A study of the factors and processes involved in the
sedimentation of Tarbela reservoir, Pakistan, Environ. Earth Sci., 62, 927–933,
https://doi.org/10.1007/s12665-010-0578-3, 2011.
Alford, D., Archer, D., Bookhagen, B., Grabs, W., Halvorson, S., Hewitt, K.,
Immerzeel, W., Kamp, U., and Krumwiede, B.: Monitoring of glaciers, climate
and runoff in the Hindu Kush-Himalaya mountains, South Asia Water Initiative
Report No. 67668-SAS, World Bank, Washington, D.C., 2014.
Anghileri, D., Voisin, N., Castelletti, A., Pianosi, F., Nijssen, B., and
Lettenmaier, D. P.: Value of long-term streamflow forecasts to reservoir
operations for water supply in snow-dominated river catchments, Water Resour.
Res., 52, 4209–4225, https://doi.org/10.1002/2015WR017864, 2016.
Archer, D. R. and Fowler, H. J.: Spatial and temporal variations in precipitation
in the Upper Indus Basin, global teleconnections and hydrological implications,
Hydrol. Earth Syst. Sci., 8, 47–61, https://doi.org/10.5194/hess-8-47-2004, 2004.
Ashok, K. and Saji, N. H.: On the impacts of ENSO and Indian Ocean dipole events
on sub-regional Indian summer monsoon rainfall, Nat. Hazards, 42, 273–285,
https://doi.org/10.1007/s11069-006-9091-0, 2007.
Ashok, K., Guan, Z., Saji, N. H., and Yamagata, T.: Individual and combined
influences of ENSO and the Indian Ocean Dipole on the Indian Summer Monsoon,
J. Climate, 17, 3141–3155, https://doi.org/10.1175/1520-0442(2004)017<3141:IACIOE>2.0.CO;2, 2004.
Asian Development Bank: Asian water development outlook 2016: Strengthening
water security in Asia and the Pacific, Asian Development Bank, Mandaluyong
City, Philippines, 2016.
Bennett, J. C., Wang, Q. J., Li, M., Robertson, D. E., and Schepen, A.: Reliable
long-range ensemble streamflow forecasts: Combining calibrated climate forecasts
with a conceptual runoff model and a staged error model, Water Resour. Res.,
52, 8238–8259, https://doi.org/10.1002/2016WR019193, 2016.
Bierkens, M. F. P. and van Beek, L. P. H.: Seasonal Predictability of European
Discharge: NAO and Hydrological Response Time, J. Hydrometeorol., 10, 953–968,
https://doi.org/10.1175/2009JHM1034.1, 2009.
Bogacki, W. and Ismail, M. F.: Seasonal forecast of Kharif flows from Upper
Jhelum catchment, Proc. IAHS, 374, 137–142, https://doi.org/10.5194/piahs-374-137-2016, 2016.
Butt, M. J. and Bilal, M.: Application of snowmelt runoff model for water
resource management, Hydrol. Process., 25, 3735–3747, https://doi.org/10.1002/hyp.8099, 2011.
Cash, B. A., Manganello, J. V., and Kinter, J. L.: Evaluation of NMME temperature
and precipitation bias and forecast skill for South Asia, Clim. Dynam.,
https://doi.org/10.1007/s00382-017-3841-4, in press, 2017.
Charles, S. P.: Hydroclimate of the Indus – synthesis of the literature relevant
to Indus basin hydroclimate processes, trends, seasonal forecasting and climate
change, CSIRO Sustainable Development Investment Portfolio project, CSIRO Land
and Water, Australia, 48 pp., 2016.
Chiew, F. H. S., Zhou, S. L., and McMahon, T. A.: Use of seasonal streamflow
forecasts in water resources management, J. Hydrol., 270, 135–144,
https://doi.org/10.1016/S0022-1694(02)00292-5, 2003.
Crochemore, L., Ramos, M. H., Pappenberger, F., and Perrin, C.: Seasonal
streamflow forecasting by conditioning climatology with precipitation indices,
Hydrol. Earth Syst. Sci., 21, 1573–1591, https://doi.org/10.5194/hess-21-1573-2017, 2017.
del Río, S., Anjum Iqbal, M., Cano-Ortiz, A., Herrero, L., Hassan, A., and
Penas, A.: Recent mean temperature trends in Pakistan and links with
teleconnection patterns, Int. J. Climatol., 33, 277–290, https://doi.org/10.1002/joc.3423, 2013.
Doblas-Reyes, F. J., García-Serrano, J., Lienert, F., Biescas, A. P., and
Rodrigues, L. R. L.: Seasonal climate predictability and forecasting: status
and prospects, Wiley Interdisciplin. Rev.: Clim. Change, 4, 245–268,
https://doi.org/10.1002/wcc.217, 2013.
Döll, P., Fiedler, K., and Zhang, J.: Global-scale analysis of river flow
alterations due to water withdrawals and reservoirs, Hydrol. Earth Syst. Sci.,
13, 2413–2432, https://doi.org/10.5194/hess-13-2413-2009, 2009.
Filippi, L., Palazzi, E., von Hardenberg, J., and Provenzale, A.: Multidecadal
Variations in the Relationship between the NAO and Winter Precipitation in the
Hindu Kush–Karakoram, J. Climate, 27, 7890–7902, https://doi.org/10.1175/JCLI-D-14-00286.1, 2014.
Gneiting, T., Balabdaoui, F., and Raftery, A. E.: Probabilistic forecasts,
calibration and sharpness, J. Roy. Stat. Soc. B, 69, 243–268, https://doi.org/10.1111/j.1467-9868.2007.00587.x, 2007.
Hall, D. K., Riggs, G. A., Foster, J. L., and Kumar, S. V.: Development and
evaluation of a cloud-gap-filled MODIS daily snow-cover product, Remote Sens.
Environ., 114, 496–503, https://doi.org/10.1016/j.rse.2009.10.007, 2010.
Hasson, S., Lucarini, V., Khan, M. R., Petitta, M., Bolch, T., and Gioli, G.:
Early 21st century snow cover state over the western river basins of the Indus
River system, Hydrol. Earth Syst. Sci., 18, 4077–4100, https://doi.org/10.5194/hess-18-4077-2014, 2014.
Hurrell, J. W.: Decadal Trends in the North Atlantic Oscillation: Regional
Temperatures and Precipitation, Science, 269, 676–679, 1995.
Immerzeel, W. W., Droogers, P., de Jong, S. M., and Bierkens, M. F. P.:
Large-scale monitoring of snow cover and runoff simulation in Himalayan river
basins using remote sensing, Remote Sens. Environ., 113, 40–49, https://doi.org/10.1016/j.rse.2008.08.010, 2009.
Ismail, M. F. and Bogacki, W.: Scenario approach for the seasonal forecast of
Kharif flows from the Upper Indus Basin, Hydrol. Earth Syst. Sci., 22, 1391–1409,
https://doi.org/10.5194/hess-22-1391-2018, 2018.
Kar, S. and Rana, S.: Interannual variability of winter precipitation over
northwest India and adjoining region: impact of global forcings, Theor. Appl.
Climatol., 116, 609–623, https://doi.org/10.1007/s00704-013-0968-z, 2014.
Kim, H.-M., Webster, P., Curry, J., and Toma, V.: Asian summer monsoon prediction
in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts, Clim. Dynam.,
39, 2975–2991, https://doi.org/10.1007/s00382-012-1470-5, 2012.
Kirby, M., Ahmad, M.-u.-D., Mainuddin, M., Khaliq, T., and Cheema, M. J. M.:
Agricultural production, water use and food availability in Pakistan: Historical
trends, and projections to 2050, Agr. Water Manage., 179, 34–46, https://doi.org/10.1016/j.agwat.2016.06.001, 2017.
Kirtman, B. P., Min, D., Infanti, J. M., Kinter, J. L., Paolino, D. A., Zhang,
Q., van den Dool, H., Saha, S., Mendez, M. P., Becker, E., Peng, P., Tripp, P.,
Huang, J., DeWitt, D. G., Tippett, M. K., Barnston, A. G., Li, S., Rosati, A.,
Schubert, S. D., Rienecker, M., Suarez, M., Li, Z. E., Marshak, J., Lim, Y.-K.,
Tribbia, J., Pegion, K., Merryfield, W. J., Denis, B., and Wood, E. F.: The
North American Multimodel Ensemble: Phase-1 Seasonal-to-Interannual Prediction; P
hase-2 toward Developing Intraseasonal Prediction, B. Am. Meteorol. Soc., 95,
585–601, https://doi.org/10.1175/BAMS-D-12-00050.1, 2013.
Koster, R. D., Mahanama, S. P. P., Livneh, B., Lettenmaier, D. P., and Reichle,
R. H.: Skill in streamflow forecasts derived from large-scale estimates of soil
moisture and snow, Nat. Geosci., 3, 613–616, 2010.
Laio, F. and Tamea, S.: Verification tools for probabilistic forecasts of
continuous hydrological variables, Hydrol. Earth Syst. Sci., 11, 1267–1277,
https://doi.org/10.5194/hess-11-1267-2007, 2007.
Li, H., Luo, L., Wood, E. F., and Schaake, J.: The role of initial conditions
and forcing uncertainties in seasonal hydrologic forecasting, J. Geophys.
Res.-Atmos., 114, D04114, https://doi.org/10.1029/2008JD010969, 2009.
Li, M., Wang, Q. J., Bennett, J. C., and Robertson, D. E.: Error reduction and
representation in stages (ERRIS) in hydrological modelling for ensemble
streamflow forecasting, Hydrol. Earth Syst. Sci., 20, 3561–3579, https://doi.org/10.5194/hess-20-3561-2016, 2016.
Mahmood, R., Babel, M. S., and Jia, S.: Assessment of temporal and spatial
changes of future climate in the Jhelum river basin, Pakistan and India,
Weather Clim. Extr., 10, 40–55, https://doi.org/10.1016/j.wace.2015.07.002, 2015.
Martinec, J., Rango, A., and Roberts, R.: Snowmelt Runoff Model (SRM) User's
Manual, New Mexico State University, Las Cruces, New Mexico, 178 pp, http://aces.nmsu.edu/pubs/research/water/SRMSpecRep100.pdf
(last access: 27 June 2018), 2008.
Maurer, E. P. and Lettenmaier, D. P.: Predictability of seasonal runoff in the
Mississippi River basin, J. Geophys. Res.-Atmos., 108, 8607, https://doi.org/10.1029/2002JD002555, 2003.
Molteni, F., Stockdale, T. M., Balmaseda, A., Balsamo, G., Buizza, R., Ferranti,
L., Magnusson, L., Mogensen, K., Palmer, T., and Vitart, F.: The new ECMWF
seasonal forecast system (System 4), ECMWF Technical Memorandum 656, ECMWF – European
Centre for Medium Range Weather Forecasts, Shinfield Park, Reading, Berkshire, England, 2011.
Mukhopadhyay, B. and Khan, A.: A reevaluation of the snowmelt and glacial melt
in river flows within Upper Indus Basin and its significance in a changing
climate, J. Hydrol., 527, 119–132, https://doi.org/10.1016/j.jhydrol.2015.04.045, 2015.
NESPAK, AHT, and DELTARES: Hydrological Flow Forecast Model for Mangla Catchment,
Upgrading of Tools, Water Resources Database, Management Systems and Models
Under Sub Component “B1” of WCAP, Final Report, Lahore, Pakistan, 2012.
Pagano, T. C., Hartmann, H. C., and Sorooshian, S.: Factors affecting seasonal
forecast use in Arizona water management: a case study of the 1997–98 El Niño,
Clim. Res., 21, 259–269, 2002.
Plummer, N., Tuteja, N., Wang, Q. J., Wang, E., Robertson, D., Zhou, S., Schepen,
A., Alves, O., Timbal, B., and Puri, K.: A seasonal water availability prediction
service: opportunities and challenges, in: 18th World IMACS/MODSIM Congress,
13–17 July 2009, Cairns, Australia, 80–94, 2009.
Pokhrel, P., Wang, Q. J., and Robertson, D. E.: The value of model averaging
and dynamical climate model predictions for improving statistical seasonal
streamflow forecasts over Australia, Water Resour. Res., 49, 6671–6687,
https://doi.org/10.1002/wrcr.20449, 2013.
Ramos, M. H., van Andel, S. J., and Pappenberger, F.: Do probabilistic forecasts
lead to better decisions?, Hydrol. Earth Syst. Sci., 17, 2219–2232, https://doi.org/10.5194/hess-17-2219-2013, 2013.
Rango, A. and Martinec, J.: Snow accumulation derived from modified depletion
curves of snow coverage, Hydrological Aspects of Alpine and High Mountain Areas,
in: Proceedings of the Exeter Symposium, July 1982, Exeter, 83–90, 1982.
Rayner, S., Lach, D., and Ingram, H.: Weather Forecasts are for Wimps: Why
Water Resource Managers Do Not Use Climate Forecasts, Climatic Change, 69,
197–227, https://doi.org/10.1007/s10584-005-3148-z, 2005.
Robertson, D. E. and Wang, Q. J.: Seasonal Forecasts of Unregulated Inflows
into the Murray River, Australia, Water Resour. Manage., 27, 2747–2769,
https://doi.org/10.1007/s11269-013-0313-4, 2013.
Robertson, D. E. and Wang, Q. J.: A Bayesian approach to predictor selection
for seasonal streamflow forecasting, J. Hydrometeorol., 13, 155–171,
https://doi.org/10.1175/JHM-D-10-05009.1, 2012.
Robertson, D. E., Pokhrel, P., and Wang, Q. J.: Improving statistical forecasts
of seasonal streamflows using hydrological model output, Hydrol. Earth Syst.
Sci., 17, 579–593, https://doi.org/10.5194/hess-17-579-2013, 2013.
Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.
J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin, J. K.,
Walker, J. P., Lohmann, D., and Toll, D.: The Global Land Data Assimilation
System, B. Am. Meteorol. Soc., 85, 381–394, https://doi.org/10.1175/BAMS-85-3-381, 2004.
Romshoo, S. A., Dar, R. A., Rashid, I., Marazi, A., Ali, N., and Zaz, S. N.:
Implications of Shrinking Cryosphere Under Changing Climate on the Streamflows
in the Lidder Catchment in the Upper Indus Basin, India, Arct. Antarct. Alp.
Res., 47, 627–644, https://doi.org/10.1657/AAAR0014-088, 2015.
Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Behringer, D.,
Hou, Y.-T., Chuang, H.-Y., Iredell, M., Ek, M., Meng, J., Yang, R., Mendez, M.
P., van den Dool, H., Zhang, Q., Wang, W., Chen, M., and Becker, E.: The NCEP
Climate Forecast System Version 2, J. Climate, 27, 2185–2208, https://doi.org/10.1175/JCLI-D-12-00823.1, 2014.
Schepen, A., Wang, Q. J., and Robertson, D.: Evidence for Using Lagged Climate
Indices to Forecast Australian Seasonal Rainfall, J. Climate, 25, 1230–1246,
https://doi.org/10.1175/JCLI-D-11-00156.1, 2012.
Schepen, A., Zhao, T., Wang, Q. J., Zhou, S., and Feikema, P.: Optimising
seasonal streamflow forecast lead time for operational decision making in
Australia, Hydrol. Earth Syst. Sci., 20, 4117–4128, https://doi.org/10.5194/hess-20-4117-2016, 2016.
Schlosser, C. A., Strzepek, K., Gao, X., Fant, C., Blanc, É., Paltsev, S.,
Jacoby, H., Reilly, J., and Gueneau, A.: The future of global water stress: An
integrated assessment, Earth's Future, 2, 341–361, https://doi.org/10.1002/2014EF000238, 2014.
Shi, X., Wood, A. W., and Lettenmaier, D. P.: How essential is hydrologic model
calibration to seasonal streamflow forecasting?, J. Hydrometeorol., 9, 1350–1363,
https://doi.org/10.1175/2008JHM1001.1, 2008.
Shukla, S. and Lettenmaier, D. P.: Seasonal hydrologic prediction in the United
States: understanding the role of initial hydrologic conditions and seasonal
climate forecast skill, Hydrol. Earth Syst. Sci., 15, 3529–3538, https://doi.org/10.5194/hess-15-3529-2011, 2011.
Shukla, S., Sheffield, J., Wood, E. F., and Lettenmaier, D. P.: On the sources
of global land surface hydrologic predictability, Hydrol. Earth Syst. Sci., 17,
2781–2796, https://doi.org/10.5194/hess-17-2781-2013, 2013.
Syed, F. S., Giorgi, F., Pal, J. S., and King, M. P.: Effect of remote forcings
on the winter precipitation of central southwest Asia part 1: observations,
Theor. Appl. Climatol., 86, 147–160, https://doi.org/10.1007/s00704-005-0217-1, 2006.
Syed, F. S., Giorgi, F., Pal, J. S., and Keay, K.: Regional climate model
simulation of winter climate over Central–Southwest Asia, with emphasis on
NAO and ENSO effects, Int. J. Climatol., 30, 220–235, https://doi.org/10.1002/joc.1887, 2010.
Tahir, A. A., Chevallier, P., Arnaud, Y., Neppel, L., and Ahmad, B.:
Modeling snowmelt-runoff under climate scenarios in the Hunza River basin,
Karakoram Range, Northern Pakistan, Journal of Hydrology, 409, 104-117,
dx.doi.org/10.1016/j.jhydrol.2011.08.035, 2011.
Thyer, M., Renard, B., Kavetski, D., Kuczera, G., Franks, S. W., and Srikanthan,
S.: Critical evaluation of parameter consistency and predictive uncertainty in
hydrological modeling: A case study using Bayesian total error analysis, Water
Resour. Res., 45, W00B14, https://doi.org/10.1029/2008WR006825, 2009.
Trenberth, K. E.: Signal Versus Noise in the Southern Oscillation, Mon. Weather
Rev., 112, 326–332, https://doi.org/10.1175/1520-0493(1984)112<0326:SVNITS>2.0.CO;2, 1984.
van Dijk, A. I. J. M., Peña-Arancibia, J. L., Wood, E. F., Sheffield, J.,
and Beck, H. E.: Global analysis of seasonal streamflow predictability using
an ensemble prediction system and observations from 6192 small catchments
worldwide, Water Resour. Res., 49, 2729–2746, https://doi.org/10.1002/wrcr.20251, 2013.
Wada, Y., van Beek, L. P. H., and Bierkens, M. F. P.: Modelling global water
stress of the recent past: on the relative importance of trends in water demand
and climate variability, Hydrol. Earth Syst. Sci., 15, 3785–3808, https://doi.org/10.5194/hess-15-3785-2011, 2011.
Wang, Q. J. and Robertson, D. E.: Multisite probabilistic forecasting of seasonal
flows for streams with zero value occurrences, Water Resour. Res., 47, W02546,
https://doi.org/10.1029/2010WR009333, 2011.
Wang, Q. J., Robertson, D. E., and Chiew, F. H. S.: A Bayesian joint
probability modeling approach for seasonal forecasting of streamflows at
multiple sites, Water Resour. Res., 45, W05407, https://doi.org/10.1029/2008WR007355, 2009.
Wang, Q. J., Schepen, A., and Robertson, D. E.: Merging Seasonal Rainfall
Forecasts from Multiple Statistical Models through Bayesian Model Averaging,
J. Climate, 25, 5524–5537, https://doi.org/10.1175/JCLI-D-11-00386.1, 2012a.
Wang, Q. J., Shrestha, D. L., Robertson, D. E., and Pokhrel, P.: A log-sinh
transformation for data normalization and variance stabilization, Water Resour.
Res., 48, W05514, https://doi.org/10.1029/2011WR010973, 2012b.
Whateley, S., Palmer, R. N., and Brown, C.: Seasonal Hydroclimatic Forecasts
as Innovations and the Challenges of Adoption by Water Managers, J. Water Resour.
Pl. Manage., 141, 04014071, https://doi.org/10.1061/(ASCE)WR.1943-5452.0000466, 2015.
Wolter, K., and Timlin, M. S.: Measuring the strength of ENSO events: How does
1997/98 rank?, Weather, 53, 315-324, https://doi.org/10.1002/j.1477-8696.1998.tb06408.x, 1998.
Wolter, K. and Timlin, M. S.: El Niño/Southern Oscillation behaviour
since 1871 as diagnosed in an extended multivariate ENSO index (MEI.ext), Int.
J. Climatol., 31, 1074–1087, https://doi.org/10.1002/joc.2336, 2011.
Wood, A. W. and Lettenmaier, D. P.: An ensemble approach for attribution of
hydrologic prediction uncertainty, Geophys. Res. Lett., 35, L14401, https://doi.org/10.1029/2008GL034648, 2008.
Wood, A. W. and Schaake, J. C.: Correcting Errors in Streamflow Forecast Ensemble
Mean and Spread, J. Hydrometeorol., 9, 132–148, https://doi.org/10.1175/2007JHM862.1, 2008.
Wood, A. W., Kumar, A., and Lettenmaier, D. P.: A retrospective assessment of
National Centers for Environmental Prediction climate model-based ensemble
hydrologic forecasting in the western United States, J. Geophys. Res.-Atmos.,
110, D04105, https://doi.org/10.1029/2004JD004508, 2005.
Wood, A. W., Hopson, T., Newman, A., Brekke, L., Arnold, J., and Clark, M.:
Quantifying Streamflow Forecast Skill Elasticity to Initial Condition and
Climate Prediction Skill, J. Hydrometeorol., 17, 651–668, https://doi.org/10.1175/JHM-D-14-0213.1, 2015.
Yadav, R. K., Rupa Kumar, K., and Rajeevan, M.: Increasing influence of ENSO
and decreasing influence of AO/NAO in the recent decades over northwest India
winter precipitation, J. Geophys. Res.-Atmos., 114, D12112, https://doi.org/10.1029/2008JD011318, 2009a.
Yadav, R. K., Yoo, J. H., Kucharski, F., and Abid, M. A.: Why is ENSO influencing
northwest India winter precipitation in recent decades?, J. Climate, 23,
1979–1993, https://doi.org/10.1175/2009JCLI3202.1, 2009b.
Yeo, I.-K. and Johnson, R. A.: A New Family of Power Transformations to Improve
Normality or Symmetry, Biometrika, 87, 954–959, 2000.
Yossef, N. C., Winsemius, H., Weerts, A., van Beek, R., and Bierkens, M. F. P.:
Skill of a global seasonal streamflow forecasting system, relative roles of
initial conditions and meteorological forcing, Water Resour. Res., 49, 4687–4699,
https://doi.org/10.1002/wrcr.20350, 2013.
Yuan, X., Wood, E. F., and Ma, Z.: A review on climate-model-based seasonal
hydrologic forecasting: physical understanding and system development, Wiley
Interdisciplin. Rev.: Water, 2, 523–536, https://doi.org/10.1002/wat2.1088, 2015.
Zheng, H. X., Wang, Q. J., Aynul, K., Shao, Q. X., Shin, D., and Tuteja, N.:
Evaluation of Downscaled POAMA M24 for Monthly and 3-Monthly Streamflow Forecasts,
in: 20th International Congress on Modelling and Simulation (Modsim2013),
1–6 December 2013, Adelaide, Australia, 2799–2805, 2013.
Short summary
Predictions of irrigation-season water availability are important for water-limited Pakistan. We assess a Bayesian joint probability approach, using flow and climate indices as predictors, to produce streamflow forecasts for inflow to Pakistan's two largest dams. The approach produces skilful and reliable forecasts. As it is simple and quick to apply, it can be used to provide probabilistic seasonal streamflow forecasts that can inform Pakistan's water management.
Predictions of irrigation-season water availability are important for water-limited Pakistan. We...
Special issue