Articles | Volume 22, issue 5
https://doi.org/10.5194/hess-22-2987-2018
© Author(s) 2018. 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-22-2987-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 May 2018
Research article |
| 22 May 2018
| 22 May 2018
Framework for developing hybrid process-driven, artificial neural network and regression models for salinity prediction in river systems
School of Civil, Environmental and Mining Engineering, The University
of Adelaide, Adelaide, 5005 SA, Australia
Holger R. Maier
School of Civil, Environmental and Mining Engineering, The University
of Adelaide, Adelaide, 5005 SA, Australia
Matthew S. Gibbs
School of Civil, Environmental and Mining Engineering, The University
of Adelaide, Adelaide, 5005 SA, Australia
Department of Environment and Water, GPO Box 2384, Adelaide, 5001 SA, Australia
Eloise R. Foale
School of Civil, Environmental and Mining Engineering, The University
of Adelaide, Adelaide, 5005 SA, Australia
Naomi A. Grosvenor
School of Civil, Environmental and Mining Engineering, The University
of Adelaide, Adelaide, 5005 SA, Australia
Nathan P. Harders
School of Civil, Environmental and Mining Engineering, The University
of Adelaide, Adelaide, 5005 SA, Australia
Tahali C. Kikuchi-Miller
School of Civil, Environmental and Mining Engineering, The University
of Adelaide, Adelaide, 5005 SA, Australia
Related authors
No articles found.
Matthew S. Gibbs, David McInerney, Greer Humphrey, Mark A. Thyer, Holger R. Maier, Graeme C. Dandy, and Dmitri Kavetski
Hydrol. Earth Syst. Sci., 22, 871–887, https://doi.org/10.5194/hess-22-871-2018, https://doi.org/10.5194/hess-22-871-2018, 2018
Short summary
Short summary
This work developed models to predict how much water will be available in the next month to maximise environmental and social outcomes in southern Australia. Initialising the models with observed streamflow data, instead of warmed up by rainfall data, improved the results, even at a monthly lead time, making sure only data representative of the forecast period to develop the models were also important. If this step was ignored, and instead all data were used, poor predictions could be produced.
Danlu Guo, Seth Westra, and Holger R. Maier
Hydrol. Earth Syst. Sci., 21, 2107–2126, https://doi.org/10.5194/hess-21-2107-2017, https://doi.org/10.5194/hess-21-2107-2017, 2017
Short summary
Short summary
This study assessed the impact of baseline climate conditions on the sensitivity of potential evapotranspiration (PET) to a large range of plausible changes in temperature, relative humidity, solar radiation and wind speed at 30 Australian locations. Around 2-fold greater PET changes were observed at cool and humid locations compared to others, indicating potential for elevated water loss in the future. These impacts can be useful to inform the selection of PET models under a changing climate.
Related subject area
Subject: Water Resources Management | Techniques and Approaches: Modelling approaches
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
Dynamically Coupling System Dynamics and SWAT+ Models using Tinamït: Applications of Modular Tools for Coupled Human-Water Systems Models
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
Cooperation in a Transboundary River Basin: a Large Scale Socio-hydrological Model of the Eastern Nile
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
Robustness of a parsimonious subsurface drainage model at the French national scale
Spatially distributed impacts of climate change and groundwater demand on the water resources in a wadi system
Delineation of dew formation zones in Iran using long-term model simulations and cluster analysis
Streamflow estimation at partially gaged sites using multiple-dependence conditions via vine copulas
Water resources management and dynamic changes in water politics in the transboundary river basins of Central Asia
Assessing interannual variability in nitrogen sourcing and retention through hybrid Bayesian watershed modeling
Minimizing the impact of vacating instream storage of a multi-reservoir system: a trade-off study of water supply and empty flushing
Global cotton production under climate change – Implications for yield and water consumption
Signatures of human intervention – or not? Downstream intensification of hydrological drought along a large Central Asian river: the individual roles of climate variability and land use change
Field-scale soil moisture bridges the spatial-scale gap between drought monitoring and agricultural yields
Socio-hydrologic modeling of the dynamics of cooperation in the transboundary Lancang–Mekong River
Multi-level storylines for participatory modeling – involving marginalized communities in Tz'olöj Ya', Mayan Guatemala
Benchmarking an operational hydrological model for providing seasonal forecasts in Sweden
Impact of the quality of hydrological forecasts on the management and revenue of hydroelectric reservoirs – a conceptual approach
A novel causal structure-based framework for comparing a basin-wide water–energy–food–ecology nexus applied to the data-limited Amu Darya and Syr Darya river basins
Projection of irrigation water demand based on the simulation of synthetic crop coefficients and climate change
Comparative analysis of kernel-based versus ANN and deep learning methods in monthly reference evapotranspiration estimation
Assessing the value of seasonal hydrological forecasts for improving water resource management: insights from a pilot application in the UK
From skill to value: isolating the influence of end user behavior on seasonal forecast assessment
The value of citizen science for flood risk reduction: cost–benefit analysis of a citizen observatory in the Brenta-Bacchiglione catchment
Risk assessment in water resources planning under climate change at the Júcar River basin
Interplay of changing irrigation technologies and water reuse: example from the upper Snake River basin, Idaho, USA
The benefit of using an ensemble of seasonal streamflow forecasts in water allocation decisions
Evapotranspiration partition using the multiple energy balance version of the ISBA-A-gs land surface model over two irrigated crops in a semi-arid Mediterranean region (Marrakech, Morocco)
Irrigation return flow causing a nitrate hotspot and denitrification imprints in groundwater at Tinwald, New Zealand
Multi-objective calibration by combination of stochastic and gradient-like parameter generation rules – the caRamel algorithm
A novel data-driven analytical framework on hierarchical water allocation integrated with blue and virtual water transfers
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.
Joel Z. Harms, Julien J. Malard, Jan F. Adamowski, Ashutosh Sharma, and Albert Nkwasa
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-306, https://doi.org/10.5194/hess-2022-306, 2022
Revised manuscript accepted for HESS
Short summary
Short summary
To facilitate the meaningful participation of stakeholders in water management, model choice is crucial. Here it is shown how System Dynamics models (SDM), which are very visual and stakeholder-friendly, may 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 the building of participatory SDMs with stakeholders, delegating hydrological components to an external hydrological model.
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.
Mohammad Ghoreishi, Amin Elshorbagy, Saman Razavi, Günter Blöschl, Murugesu Sivapalan, and Ahmed Abdelkader
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-172, https://doi.org/10.5194/hess-2022-172, 2022
Revised manuscript accepted for HESS
Short summary
Short summary
We propose a quantitative model of the willingness to cooperate at the national and 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 operation and other management decisions on the emergence of basin cooperation.
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.
Alexis Jeantet, Hocine Henine, Cédric Chaumont, Lila Collet, Guillaume Thirel, and Julien Tournebize
Hydrol. Earth Syst. Sci., 25, 5447–5471, https://doi.org/10.5194/hess-25-5447-2021, https://doi.org/10.5194/hess-25-5447-2021, 2021
Short summary
Short summary
The hydrological subsurface drainage model SIDRA-RU is assessed at the French national scale, using a unique database representing the large majority of the French drained areas. The model is evaluated following its capacity to simulate the drainage discharge variability and the annual drained water balance. Eventually, the temporal robustness of SIDRA-RU is assessed to demonstrate the utility of this model as a long-term management tool.
Nariman Mahmoodi, Jens Kiesel, Paul D. Wagner, and Nicola Fohrer
Hydrol. Earth Syst. Sci., 25, 5065–5081, https://doi.org/10.5194/hess-25-5065-2021, https://doi.org/10.5194/hess-25-5065-2021, 2021
Short summary
Short summary
In this study, we assessed the sustainability of water resources in a wadi region with the help of a hydrologic model. Our assessment showed that the increases in groundwater demand and consumption exacerbate the negative impact of climate change on groundwater sustainability and hydrologic regime alteration. These alterations have severe consequences for a downstream wetland and its ecosystem. The approach may be applicable in other wadi regions with different climate and water use systems.
Nahid Atashi, Dariush Rahimi, Victoria A. Sinclair, Martha A. Zaidan, Anton Rusanen, Henri Vuollekoski, Markku Kulmala, Timo Vesala, and Tareq Hussein
Hydrol. Earth Syst. Sci., 25, 4719–4740, https://doi.org/10.5194/hess-25-4719-2021, https://doi.org/10.5194/hess-25-4719-2021, 2021
Short summary
Short summary
Dew formation potential during a long-term period (1979–2018) was assessed in Iran to identify dew formation zones and to investigate the impacts of long-term variation in meteorological parameters on dew formation. Six dew formation zones were identified based on cluster analysis of the time series of the simulated dew yield. The distribution of dew formation zones in Iran was closely aligned with topography and sources of moisture. The dew formation trend was significantly negative.
Kuk-Hyun Ahn
Hydrol. Earth Syst. Sci., 25, 4319–4333, https://doi.org/10.5194/hess-25-4319-2021, https://doi.org/10.5194/hess-25-4319-2021, 2021
Short summary
Short summary
This study proposes a multiple-dependence model for estimating streamflow at partially gaged sites. The evaluations are conducted on a case study of the eastern USA and show that the proposed model is suited for infilling missing values. The performance is further evaluated with six other infilling models. Results demonstrate that the proposed model produces more reliable streamflow estimates than the other approaches. The model can be applicable to other hydro-climatological variables.
Xuanxuan Wang, Yaning Chen, Zhi Li, Gonghuan Fang, Fei Wang, and Haichao Hao
Hydrol. Earth Syst. Sci., 25, 3281–3299, https://doi.org/10.5194/hess-25-3281-2021, https://doi.org/10.5194/hess-25-3281-2021, 2021
Short summary
Short summary
The growing water crisis in Central Asia and the complex water politics of the region's transboundary rivers are a hot topic for research, while the dynamic changes of water politics in Central Asia have yet to be studied in depth. Based on the Gini coefficient, water political events and social network analysis, we analyzed the matching degree between water and socio-economic elements and the dynamics of hydropolitics in transboundary river basins of Central Asia.
Jonathan W. Miller, Kimia Karimi, Arumugam Sankarasubramanian, and Daniel R. Obenour
Hydrol. Earth Syst. Sci., 25, 2789–2804, https://doi.org/10.5194/hess-25-2789-2021, https://doi.org/10.5194/hess-25-2789-2021, 2021
Short summary
Short summary
Within a watershed, nutrient export can vary greatly over time and space. In this study, we develop a model to leverage over 30 years of streamflow, precipitation, and nutrient sampling data to characterize nitrogen export from various livestock and land use types across a range of precipitation conditions. Modeling results reveal that urban lands developed before 1980 have remarkably high levels of nitrogen export, while agricultural export is most responsive to precipitation.
Chia-Wen Wu, Frederick N.-F. Chou, and Fong-Zuo Lee
Hydrol. Earth Syst. Sci., 25, 2063–2087, https://doi.org/10.5194/hess-25-2063-2021, https://doi.org/10.5194/hess-25-2063-2021, 2021
Short summary
Short summary
This paper promotes the feasibility of emptying instream storage through joint operation of multiple reservoirs. The trade-off between water supply and emptying reservoir storage and alleviating impacts on downstream environment are thoroughly discussed. Operation of reservoirs is optimized to calibrate the optimal parameters defining the activation and termination of emptying reservoir. The optimized strategy limits the water shortage and maximizes the expected benefits of emptying reservoir.
Yvonne Jans, Werner von Bloh, Sibyll Schaphoff, and Christoph Müller
Hydrol. Earth Syst. Sci., 25, 2027–2044, https://doi.org/10.5194/hess-25-2027-2021, https://doi.org/10.5194/hess-25-2027-2021, 2021
Short summary
Short summary
Growth of and irrigation water demand on cotton may be challenged by future climate change. To analyze the global cotton production and irrigation water consumption under spatially varying present and future climatic conditions, we use the global terrestrial biosphere model LPJmL. Our simulation results suggest that the beneficial effects of elevated [CO2] on cotton yields overcompensate yield losses from direct climate change impacts, i.e., without the beneficial effect of [CO2] fertilization.
Artemis Roodari, Markus Hrachowitz, Farzad Hassanpour, and Mostafa Yaghoobzadeh
Hydrol. Earth Syst. Sci., 25, 1943–1967, https://doi.org/10.5194/hess-25-1943-2021, https://doi.org/10.5194/hess-25-1943-2021, 2021
Short summary
Short summary
In a combined data analysis and modeling study in the transboundary Helmand River basin, we analyzed spatial patterns of drought and changes therein based on the drought indices as well as on absolute water deficits. Overall the results illustrate that flow deficits and the associated droughts clearly reflect the dynamic interplay between temporally varying regional differences in hydro-meteorological variables together with subtle and temporally varying effects linked to human intervention.
Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, and Justin Sheffield
Hydrol. Earth Syst. Sci., 25, 1827–1847, https://doi.org/10.5194/hess-25-1827-2021, https://doi.org/10.5194/hess-25-1827-2021, 2021
Short summary
Short summary
Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or (infrequent) vegetation indexes that do not always indicate the conditions farmers face in the field. Consequently, decision-making based on these indices can often be disconnected from the farmer reality. Our study focuses on smallholder farming systems in data-sparse developing countries, and it shows how field-scale soil moisture can leverage and improve crop yield prediction and drought impact assessment.
You Lu, Fuqiang Tian, Liying Guo, Iolanda Borzì, Rupesh Patil, Jing Wei, Dengfeng Liu, Yongping Wei, David J. Yu, and Murugesu Sivapalan
Hydrol. Earth Syst. Sci., 25, 1883–1903, https://doi.org/10.5194/hess-25-1883-2021, https://doi.org/10.5194/hess-25-1883-2021, 2021
Short summary
Short summary
The upstream countries in the transboundary Lancang–Mekong basin build dams for hydropower, while downstream ones gain irrigation and fishery benefits. Dam operation changes the seasonality of runoff downstream, resulting in their concerns. Upstream countries may cooperate and change their regulations of dams to gain indirect political benefits. The socio-hydrological model couples hydrology, reservoir, economy, and cooperation and reproduces the phenomena, providing a useful model framework.
Jessica A. Bou Nassar, Julien J. Malard, Jan F. Adamowski, Marco Ramírez Ramírez, Wietske Medema, and Héctor Tuy
Hydrol. Earth Syst. Sci., 25, 1283–1306, https://doi.org/10.5194/hess-25-1283-2021, https://doi.org/10.5194/hess-25-1283-2021, 2021
Short summary
Short summary
Our research suggests a method that facilitates the inclusion of marginalized stakeholders in model-building activities to address problems in water resources. Our case study showed that knowledge produced by typically excluded stakeholders had significant and unique contributions to the outcome of the process. Moreover, our method facilitated the identification of relationships between societal, economic, and hydrological factors, and it fostered collaborations across different communities.
Marc Girons Lopez, Louise Crochemore, and Ilias G. Pechlivanidis
Hydrol. Earth Syst. Sci., 25, 1189–1209, https://doi.org/10.5194/hess-25-1189-2021, https://doi.org/10.5194/hess-25-1189-2021, 2021
Short summary
Short summary
The Swedish hydrological warning service is extending its use of seasonal forecasts, which requires an analysis of the available methods. We evaluate the simple ESP method and find out how and why forecasts vary in time and space. We find that forecasts are useful up to 3 months into the future, especially during winter and in northern Sweden. They tend to be good in slow-reacting catchments and bad in flashy and highly regulated ones. We finally link them with areas of similar behaviour.
Manon Cassagnole, Maria-Helena Ramos, Ioanna Zalachori, Guillaume Thirel, Rémy Garçon, Joël Gailhard, and Thomas Ouillon
Hydrol. Earth Syst. Sci., 25, 1033–1052, https://doi.org/10.5194/hess-25-1033-2021, https://doi.org/10.5194/hess-25-1033-2021, 2021
Haiyang Shi, Geping Luo, Hongwei Zheng, Chunbo Chen, Olaf Hellwich, Jie Bai, Tie Liu, Shuang Liu, Jie Xue, Peng Cai, Huili He, Friday Uchenna Ochege, Tim Van de Voorde, and Philippe de Maeyer
Hydrol. Earth Syst. Sci., 25, 901–925, https://doi.org/10.5194/hess-25-901-2021, https://doi.org/10.5194/hess-25-901-2021, 2021
Short summary
Short summary
Some river basins are considered to be very similar because they have a similar background such as a transboundary, facing threats of human activities. But we still lack understanding of differences under their general similarities. Therefore, we proposed a framework based on a Bayesian network to group watersheds based on similarity levels and compare the causal and systematic differences within the group. We applied it to the Amu and Syr Darya River basin and discussed its universality.
Michel Le Page, Younes Fakir, Lionel Jarlan, Aaron Boone, Brahim Berjamy, Saïd Khabba, and Mehrez Zribi
Hydrol. Earth Syst. Sci., 25, 637–651, https://doi.org/10.5194/hess-25-637-2021, https://doi.org/10.5194/hess-25-637-2021, 2021
Short summary
Short summary
In the context of major changes, the southern Mediterranean area faces serious challenges with low and continuously decreasing water resources mainly attributed to agricultural use. A method for projecting irrigation water demand under both anthropogenic and climatic changes is proposed. Time series of satellite imagery are used to determine a set of semiempirical equations that can be easily adapted to different future scenarios.
Mohammad Taghi Sattari, Halit Apaydin, Shahab S. Band, Amir Mosavi, and Ramendra Prasad
Hydrol. Earth Syst. Sci., 25, 603–618, https://doi.org/10.5194/hess-25-603-2021, https://doi.org/10.5194/hess-25-603-2021, 2021
Short summary
Short summary
The aim of study is to estimate the reference evapotranspiration (ET0) amount with artificial intelligence using minimum meteorological parameters in the Corum region, which is an agricultural center of Turkey. Kernel-based GPR and SVR and BFGS-ANN and LSTM models were used to estimate ET0 amounts in 10 different combinations. The results show that all four methods used predicted ET0 amounts at acceptable accuracy and error levels. The BFGS-ANN model showed higher success than the others.
Andres Peñuela, Christopher Hutton, and Francesca Pianosi
Hydrol. Earth Syst. Sci., 24, 6059–6073, https://doi.org/10.5194/hess-24-6059-2020, https://doi.org/10.5194/hess-24-6059-2020, 2020
Short summary
Short summary
In this paper we evaluate the potential use of seasonal weather forecasts to improve reservoir operation in a UK water supply system. We found that the use of seasonal forecasts can improve the efficiency of reservoir operation but only if the forecast uncertainty is explicitly considered. We also found the degree of efficiency improvement is strongly affected by the decision maker priorities and the hydrological conditions.
Matteo Giuliani, Louise Crochemore, Ilias Pechlivanidis, and Andrea Castelletti
Hydrol. Earth Syst. Sci., 24, 5891–5902, https://doi.org/10.5194/hess-24-5891-2020, https://doi.org/10.5194/hess-24-5891-2020, 2020
Short summary
Short summary
This paper aims at quantifying the value of hydroclimatic forecasts in terms of potential economic benefit to end users in the Lake Como basin (Italy), which allows the inference of a relation between gains in forecast skill and gains in end user profit. We also explore the sensitivity of this benefit to both the forecast system setup and end user behavioral factors, showing that the estimated forecast value is potentially undermined by different levels of end user risk aversion.
Michele Ferri, Uta Wehn, Linda See, Martina Monego, and Steffen Fritz
Hydrol. Earth Syst. Sci., 24, 5781–5798, https://doi.org/10.5194/hess-24-5781-2020, https://doi.org/10.5194/hess-24-5781-2020, 2020
Short summary
Short summary
As part of the flood risk management strategy of the
Brenta-Bacchiglione catchment (Italy), a citizen observatory for flood risk management is currently being implemented. A cost–benefit analysis of the citizen observatory was undertaken to demonstrate the value of this approach in monetary terms. Results show a reduction in avoided damage of 45 % compared to a scenario without implementation of the citizen observatory. The idea is to promote this methodology for future flood risk management.
Sara Suárez-Almiñana, Abel Solera, Jaime Madrigal, Joaquín Andreu, and Javier Paredes-Arquiola
Hydrol. Earth Syst. Sci., 24, 5297–5315, https://doi.org/10.5194/hess-24-5297-2020, https://doi.org/10.5194/hess-24-5297-2020, 2020
Short summary
Short summary
This work responds to the need for an effective methodology that integrates climate change projections into water planning and management to guide complex basin decision-making. This general approach is based on a model chain for management and drought risk assessments and applied to the Júcar River basin (Spain), showing a worrying deterioration of the basin's future water resources availability and drought indicators, despite a considerable uncertainty of results from the mid-century onwards.
Shan Zuidema, Danielle Grogan, Alexander Prusevich, Richard Lammers, Sarah Gilmore, and Paula Williams
Hydrol. Earth Syst. Sci., 24, 5231–5249, https://doi.org/10.5194/hess-24-5231-2020, https://doi.org/10.5194/hess-24-5231-2020, 2020
Short summary
Short summary
In our case study we find that increasing the efficiency of irrigation technology will have unintended consequences like reducing water available for aquifer replenishment or for other irrigators. The amount of water needed to stabilize regional aquifers exceeds the amount that could be saved by improving irrigation efficiency. Since users depend upon local groundwater storage, which is more sensitive to management decisions than river flow, comanagement of surface and groundwater is critical.
Alexander Kaune, Faysal Chowdhury, Micha Werner, and James Bennett
Hydrol. Earth Syst. Sci., 24, 3851–3870, https://doi.org/10.5194/hess-24-3851-2020, https://doi.org/10.5194/hess-24-3851-2020, 2020
Short summary
Short summary
This paper was developed from PhD research focused on assessing the value of using hydrological datasets in water resource management. Previous studies have assessed how well data can help in predicting river flows, but there is a lack of knowledge of how well data can help in water allocation decisions. In our research, it was found that using seasonal streamflow forecasts improves the available water estimates, resulting in better water allocation decisions in a highly regulated basin.
Ghizlane Aouade, Lionel Jarlan, Jamal Ezzahar, Salah Er-Raki, Adrien Napoly, Abdelfattah Benkaddour, Said Khabba, Gilles Boulet, Sébastien Garrigues, Abdelghani Chehbouni, and Aaron Boone
Hydrol. Earth Syst. Sci., 24, 3789–3814, https://doi.org/10.5194/hess-24-3789-2020, https://doi.org/10.5194/hess-24-3789-2020, 2020
Short summary
Short summary
Our objective is to question the representation of the energy budget in surface–vegetation–atmosphere transfer models for the prediction of the convective fluxes in crops with complex structures (row) and under transient hydric regimes due to irrigation. The main result is that a coupled multiple energy balance approach is necessary to properly predict surface exchanges for these complex crops. It also points out the need for other similar studies on various crops with different sparsity levels.
Michael Kilgour Stewart and Philippa Lauren Aitchison-Earl
Hydrol. Earth Syst. Sci., 24, 3583–3601, https://doi.org/10.5194/hess-24-3583-2020, https://doi.org/10.5194/hess-24-3583-2020, 2020
Short summary
Short summary
This paper is important for water resource management, being concerned with irrigation return flow causing
hotspotsin nitrate concentrations in groundwater and
denitrification imprintswhere nitrate concentrations are reduced by denitrification although the dissolved oxygen concentration is not low. The work is highly significant for modelling of nitrate transport through soil–groundwater systems, for understanding denitrification processes, and for managing fertilizer application to land.
Céline Monteil, Fabrice Zaoui, Nicolas Le Moine, and Frédéric Hendrickx
Hydrol. Earth Syst. Sci., 24, 3189–3209, https://doi.org/10.5194/hess-24-3189-2020, https://doi.org/10.5194/hess-24-3189-2020, 2020
Short summary
Short summary
Environmental modelling is complex, and models often require the calibration of several parameters that are not able to be directly evaluated from a physical quantity or a field measurement. Based on our experience in hydrological modelling, we propose combining two algorithms to obtain a fast and accurate way of calibrating complex models (many parameters and many objectives). We built an R package, caRamel, so that this multi-objective calibration algorithm can be easily implemented.
Liming Yao, Zhongwen Xu, Huijuan Wu, and Xudong Chen
Hydrol. Earth Syst. Sci., 24, 2769–2789, https://doi.org/10.5194/hess-24-2769-2020, https://doi.org/10.5194/hess-24-2769-2020, 2020
Short summary
Short summary
Results show that coalitional strategy of blue and virtual water transfers can substantially save water and improve utilization efficiency without harming sectors' benefits and increasing ecological stresses. Under various polices, we use data-driven analysis to simulate hydrological and economic parameters, such as available water, crop import price, and water market price. Different water allocation and transfer results are obtained by adjusting hydrological and economic parameters.
Cited articles
Adamowski, J. and Chan, H. F.: A wavelet neural network conjunction model for groundwater level forecasting, J. Hydrol, 407, 28–40, https://doi.org/10.1016/j.jhydrol.2011.06.013, 2011.
Alvarez-Garreton, C., Ryu, D., Western, A. W., Su, C.-H., Crow, W. T., Robertson, D. E., and Leahy, C.: Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes, Hydrol. Earth Syst. Sci., 19, 1659–1676, https://doi.org/10.5194/hess-19-1659-2015, 2015.
Banerjee, P., Singh, V. S., Chatttopadhyay, K., Chandra, P. C., and Singh, B.: Artificial neural network model as a potential alternative for groundwater salinity forecasting, J. Hydrol., 398, 212–220, https://doi.org/10.1016/j.jhydrol.2010.12.016, 2011.
Barnett, S.: Gurra Gurra Wetland Complex – Groundwater Data Review, Dept. of Water, Land and Biodiversity Conservation, 4, 2007.
Beecham, R., Arranz, P., Boddy, J., Burrell, M., Gilmore, R., Javam, A., Martin, J., O'Neill, R., and Salbe, I.: Implementing daily salinity models in the NSW Murray Darling Basin tributaries, in: Modsim 2003, International Congress on Modelling and Simulation, Vol 1–4: Vol 1: Natural Systems, Pt 1; Vol 2: Natural Systems, Pt 2; Vol 3: Socio-Economic Systems; Vol 4: General Systems, 362–367, 2003.
Bowden, G. J., Maier, H. R., and Dandy, G. C.: Optimal division of data for neural network models in water resources applications, Water Resour. Res., 38, 1010, https://doi.org/10.1029/2001wr000266, 2002.
Bowden, G. J., Maier, H. R., and Dandy, G. C.: Input determination for neural network models in water resources applications. Part 1. Background and methodology, J. Hydrol., 301, 75–92, https://doi.org/10.1016/j.jhydrol.2004.06.021, 2005a.
Bowden, G. J., Maier, H. R., and Dandy, G. C.: Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river, J. Hydrol., 301, 93–107, https://doi.org/10.1016/j.jhydrol.2004.06.020, 2005b.
Bowden, G. J., Maier, H. R., and Dandy, G. C.: Real-time deployment of artificial neural network forecasting models: Understanding the range of applicability, Water Resour. Res., 48, W10549, https://doi.org/10.1029/2012WR011984, 2012.
Chang, F.-J. and Chang, Y.-T.: Adaptive neuro-fuzzy inference system for prediction of water level in reservoir, Adv. Water Resour., 29, 1–10, https://doi.org/10.1016/j.advwatres.2005.04.015, 2006.
Chang, F.-J. and Tsai, M.-J.: A nonlinear spatio-temporal lumping of radar rainfall for modeling multi-step-ahead inflow forecasts by data-driven techniques, J. Hydrol., 535, 228–236, https://doi.org/10.1016/j.jhydrol.2016.01.056, 2016.
Chang, F.-J., Tsai, W.-P., Chen, H.-K., Yam, R. S.-W., and Herricks, E. E.: A self-organizing radial basis network for estimating riverine fish diversity, J. Hydrol., 476, 280–289, https://doi.org/10.1016/j.jhydrol.2012.10.038, 2013.
Chang, F.-J., Chen, P.-A., Chang, L.-C., and Tsai, Y.-H.: Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques, Sci. Total Environ., 562, 256–269, https://doi.org/10.1016/j.scitotenv.2016.03.219, 2016.
Clark, M. P., Kavetski, D., and Fenicia, F.: Pursuing the method of multiple working hypotheses for hydrological modeling, Water Resour. Res., 47, W09301, https://doi.org/10.1029/2010WR009827, 2011.
Commonwealth of Australia: Water Act (An act to make provision for the management of the water resources of the Murray-Darling Basin, and to make provision for other matters of national interest in relation to water and water information, and for related purposes), Commonwealth Consolidated Acts, Sects. 28–32, 2007.
Corzo, G. and Solomatine, D.: Baseflow separation techniques for modular artificial neural network modelling in flow forecasting, Hydrol. Sci. J., 52, 491–507, https://doi.org/10.1623/hysj.52.3.491, 2007.
Corzo, G. A., Solomatine, D. P., Hidayat, de Wit, M., Werner, M., Uhlenbrook, S., and Price, R. K.: Combining semi-distributed process-based and data-driven models in flow simulation: a case study of the Meuse river basin, Hydrol. Earth Syst. Sci., 13, 1619–1634, https://doi.org/10.5194/hess-13-1619-2009, 2009.
Dessie, M., Verhoest, N. E. C., Pauwels, V. R. N., Admasu, T., Poesen, J., Adgo, E., Deckers, J., and Nyssen, J.: Analyzing runoff processes through conceptual hydrological modeling in the Upper Blue Nile Basin, Ethiopia, Hydrol. Earth Syst. Sci., 18, 5149–5167, https://doi.org/10.5194/hess-18-5149-2014, 2014.
Duan, W. L., He, B., Takara, K., Luo, P. P., Nover, D., and Hu, M. C.: Modeling suspended sediment sources and transport in the Ishikari River basin, Japan, using SPARROW, Hydrol. Earth Syst. Sci., 19, 1293–1306, https://doi.org/10.5194/hess-19-1293-2015, 2015.
Duku, C., Rathjens, H., Zwart, S. J., and Hein, L.: Towards ecosystem accounting: a comprehensive approach to modelling multiple hydrological ecosystem services, Hydrol. Earth Syst. Sci., 19, 4377–4396, https://doi.org/10.5194/hess-19-4377-2015, 2015.
Fenicia, F., Kavetski, D., and Savenije, H. H. G.: Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development, Water Resour. Res., 47, W11510, https://doi.org/10.1029/2010wr010174, 2011.
Galelli, S., Humphrey, G. B., Maier, H. R., Castelletti, A., Dandy, G. C., and Gibbs, M. S.: An evaluation framework for input variable selection algorithms for environmental data-driven models, Environ. Modell. Softw., 62, 33–51, https://doi.org/10.1016/j.envsoft.2014.08.015, 2014.
Gallice, A., Schaefli, B., Lehning, M., Parlange, M. B., and Huwald, H.: Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model, Hydrol. Earth Syst. Sci., 19, 3727–3753, https://doi.org/10.5194/hess-19-3727-2015, 2015.
Gibbs, M. S., Maier, H. R., and Dandy, G. C.: A generic framework for regression regionalization in ungauged catchments, Environ. Modell. Softw., 27–28, 1–14, https://doi.org/10.1016/j.envsoft.2011.10.006, 2012.
Gibbs, M. S., McInerney, D., Humphrey, G., Thyer, M. A., Maier, H. R., Dandy, G. C., and Kavetski, D.: State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application, Hydrol. Earth Syst. Sci., 22, 871–887, https://doi.org/10.5194/hess-22-871-2018, 2018.
Goss, K. F.: Environmental flows, river salinity and biodiversity conservation: managing trade-offs in the Murray & Darling basin, Aust. J. Bot., 51, 619–625, https://doi.org/10.1071/BT03003, 2003.
Government of South Australia, Department of Environment, Water and Natural Resources (DEWNR): WaterConnect groundwater data, available at: www.waterconnect.sa.gov.au (last access: 9 November 2017), 2015.
Gragne, A. S., Sharma, A., Mehrotra, R., and Alfredsen, K.: Improving real-time inflow forecasting into hydropower reservoirs through a complementary modelling framework, Hydrol. Earth Syst. Sci., 19, 3695–3714, https://doi.org/10.5194/hess-19-3695-2015, 2015.
Grayson, R. B. and Blöschl, G.: Spatial patterns in catchment hydrology: Observations and modelling, Cambridge University Press, UK, https://doi.org/10.1002/esp.378, 2000.
Guo, D., Westra, S., and Maier, H. R.: An R package for modelling actual, potential and reference evapotranspiration, Environ. Modell. Softw., 78, 216–224, https://doi.org/10.1016/j.envsoft.2015.12.019, 2016.
Habib, E., Nuttle, W. K., Rivera-Monroy, V. H., Gautam, S., Wang, J., Meselhe, E., and Twilley, R. R.: Assessing effects of data limitations on salinity forecasting in Barataria basin, Louisiana, with a Bayesian analysis, J. Coastal Res., 23, 749–763, https://doi.org/10.2112/06-0723.1, 2007.
Hamilton, S. H., ElSawah, S., Guillaume, J. H. A., Jakeman, A. J., and Pierce, S. A.: Integrated assessment and modelling: Overview of salient dimensions, Environ. Modell. Softw., 64, 215–229, https://doi.org/10.1016/j.envsoft.2014.12.005, 2015.
Harrington, N., Van den Akker, J., and Brown, K.: Padthaway Salt Accession Study Volume Three: Conceptual Models, Government of South Australia, Dept. of Water, Land and Biodiversity Conservation, Adelaide, 11, 15–16, 38, 112, 2006.
Hart, B. T., Bailey, P., Edwards, R., Hortle, K., James, K., McMahon, A., Meredith, C., and Swadling, K.: A Review of the Salt Sensitivity of the Australian Fresh-Water Biota, Hydrobiologia, 210, 105–144, https://doi.org/10.1007/bf00014327, 1991.
Hsu, K. L., Gupta, H. V., Gao, X. G., Sorooshian, S., and Imam, B.: Self-organizing linear output map (SOLO): An artificial neural network suitable for hydrologic modeling and analysis, Water Resour. Res., 38, 1302, https://doi.org/10.1029/2001wr000795, 2002.
Huang, W. R. and Foo, S.: Neural network modeling of salinity variation in Apalachicola River, Water Res., 36, 356–362, https://doi.org/10.1016/s0043-1354(01)00195-6, 2002.
Humphrey, G. B., Gibbs, M. S., Dandy, G. C., and Maier, H. R.: A hybrid approach to monthly streamflow forecasting: Integrating hydrological model outputs into a Bayesian artificial neural network, J. Hydrol., 540, 623–640, https://doi.org/10.1016/j.jhydrol.2016.06.026, 2016.
Humphrey, G. B., Maier, H. R., Wu, W., Mount, N. J., Dandy, G. C., Abrahart, R. J., and Dawson, C. W.: Improved validation framework and R-package for artificial neural network models, Environ. Modell. Softw., 92, 82–106, https://doi.org/10.1016/j.envsoft.2017.01.023, 2017.
Jain, A. and Kumar, S.: Dissection of trained neural network hydrological models for knowledge extraction, Water Resour. Res., 45, W07420, https://doi.org/10.1029/2008WR007194, 2009.
Jain, A., Sudheer, K. P., and Srinivasulu, S.: Identification of physical processes inherent in artificial neural network rainfall runoff models, Hydrol. Process., 18, 571–581, https://doi.org/10.1002/hyp.5502, 2004.
Jakeman, A. J., Letcher, R. A., and Norton, J. P.: Ten iterative steps in development and evaluation of environmental models, Environ. Modell. Softw., 21, 602–614, https://doi.org/10.1016/j.envsoft.2006.01.004, 2006.
Kasiviswanathan, K. S., He, J., Sudheer, K. P., and Tay, J.-H.: Potential application of wavelet neural network ensemble to forecast streamflow for flood management, J. Hydrol., 536, 161–173, https://doi.org/10.1016/j.jhydrol.2016.02.044, 2016.
Kavetski, D. and Fenicia, F.: Elements of a flexible approach for conceptual hydrological modeling: 2. Application and experimental insights, Water Resour. Res., 47, W11511, https://doi.org/10.1029/2011wr010748, 2011.
Kelly, R. A., Jakeman, A. J., Barreteau, O., Borsuk, M. E., ElSawah, S., Hamilton, S. H., Henriksen, H. J., Kuikka, S., Maier, H. R., Rizzoli, A. E., van Delden, H., and Voinov, A. A.: Selecting among five common modelling approaches for integrated environmental assessment and management, Environ. Modell. Softw., 47, 159–181, https://doi.org/10.1016/j.envsoft.2013.05.005, 2013.
Kingston, G. B., Lambert, M. F., and Maier, H. R.: Bayesian training of artificial neural networks used for water resources modeling, Water Resour. Res., 41, W12409, https://doi.org/10.1029/2005wr004152, 2005.
Kisi, O. and Demir, V.: Evapotranspiration estimation using six different multi-layer perceptron algorithms, Irrigation & Drainage Systems Engineering, 5, 164, https://doi.org/10.4172/2168-9768.1000164, 2016.
Kisi, O. and Parmar, K. S.: Application of least square support vector machine and multivariate adaptive regression spline models in long term prediction of river water pollution, J. Hydrol., 534, 104–112, https://doi.org/10.1016/j.jhydrol.2015.12.014, 2016.
Kornelsen, K. and Coulibaly, P.: Comparison of Interpolation, Statistical, and Data-Driven Methods for Imputation of Missing Values in a Distributed Soil Moisture Dataset, J. Hydrol. Eng., 19, 26–43, https://doi.org/10.1061/(asce)he.1943-5584.0000767, 2014.
Li, L., Maier, H. R., Partington, D., Lambert, M. F., and Simmons, C. T.: Performance assessment and improvement of recursive digital baseflow filters for catchments with different physical characteristics and hydrological inputs, Environ. Modell. Softw., 54, 39–52, https://doi.org/10.1016/j.envsoft.2013.12.011, 2014.
Liu, W. C., Chen, W. B., Cheng, R. T., Hsu, M. H., and Kuo, A. Y.: Modeling the influence of river discharge on salt intrusion and residual circulation in Danshuei River estuary, Taiwan, Cont. Shelf Res., 27, 900–921, https://doi.org/10.1016/j.csr.2006.12.005, 2007.
Maier, H. R. and Dandy, G. C.: The use of artificial neural networks for the prediction of water quality parameters, Water Resour. Res., 32, 1013–1022, 1996.
Maier, H. R., Jain, A., Dandy, G. C., and Sudheer, K. P.: Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions, Environ. Modell. Softw., 25, 891–909, https://doi.org/10.1016/j.envsoft.2010.02.003, 2010.
Markstrom, S. L., Hay, L. E., and Clark, M. P.: Towards simplification of hydrologic modeling: identification of dominant processes, Hydrol. Earth Syst. Sci., 20, 4655–4671, https://doi.org/10.5194/hess-20-4655-2016, 2016.
MDBC: Setting up of MSM-BIGMOD modelling Suite for the River Murray System, Technical, Murray-Darling Basin Commission, 2002.
Mohanty, S., Jha, M. K., Raul, S. K., Panda, R. K., and Sudheer, K. P.: Using artificial neural network approach for simultaneous forecasting of weekly groundwater levels at multiple sites, Water Resour. Manag., 29, 5521–5532, https://doi.org/10.1007/s11269-015-1132-6, 2015.
Mount, N. J., Abrahart, R. J., Dawson, C. W., and Ab Ghani, N.: The need for operational reasoning in data-driven rating curve prediction of suspended sediment, Hydrol. Process., 26, 3982–4000, https://doi.org/10.1002/hyp.8439, 2012.
Mount, N. J., Maier, H. R., Toth, E., Elshorbagy, A., Solomatine, D., Chang, F. J., and Abrahart, R. J.: Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan, Hydrolog. Sci. J., 61, 1182–1208, https://doi.org/10.1080/02626667.2016.1159683, 2016.
Moxey, A.: Agriculture and Water Quality: Monetary Costs and Benefits across OECD Countries, 11–12, 2012.
Noori, N. and Kalin, L.: Coupling SWAT and ANN models for enhanced daily streamflow prediction, J. Hydrol., 533, 141–151, https://doi.org/10.1016/j.jhydrol.2015.11.050, 2016.
Parasuraman, K., Elshorbagy, A., and Carey, S. K.: Modelling the dynamics of the evapotranspiration process using genetic programming, Hydrol. Sci. J., 52, 563–578, https://doi.org/10.1623/hysj.52.3.563, 2007.
Pulido-Velazquez, M., Peña-Haro, S., García-Prats, A., Mocholi-Almudever, A. F., Henriquez-Dole, L., Macian-Sorribes, H., and Lopez-Nicolas, A.: Integrated assessment of the impact of climate and land use changes on groundwater quantity and quality in the Mancha Oriental system (Spain), Hydrol. Earth Syst. Sci., 19, 1677–1693, https://doi.org/10.5194/hess-19-1677-2015, 2015.
Quiroga, V. M., Popescu, I., Solomatine, D. P., and Bociort, L.: Cloud and cluster computing in uncertainty analysis of integrated flood models, J. Hydroinform., 15, 55–70, https://doi.org/10.2166/hydro.2012.017, 2013.
Rath, J. S., Hutton, P. H., Chen, L., and Roy, S. B.: A hybrid empirical-Bayesian artificial neural network model of salinity in the San Francisco Bay-Delta estuary, Environ. Modell. Softw., 93, 193–208, https://doi.org/10.1016/j.envsoft.2017.03.022, 2017.
Rengasamy, P.: World salinization with emphasis on Australia, J. Exp. Bot., 57, 1017–1023, https://doi.org/10.1093/jxb/erj108, 2006.
Robertson, W. M. and Sharp, J. M.: Estimates of recharge in two arid basin aquifers: a model of spatially variable net infiltration and its implications (Red Light Draw and Eagle Flats, Texas, USA), Hydrogeol. J., 21, 1853–1864, https://doi.org/10.1007/s10040-013-1018-8, 2013.
Seibert, J.: On the need for benchmarks in hydrological modelling, Hydrol. Process., 15, 1063–1064, https://doi.org/10.1002/hyp.446, 2001.
Shamseldin, A. Y., Nasr, A. E., and O'Connor, K. M.: Comparison of different forms of the Multi-layer Feed-Forward Neural Network method used for river flow forecasting, Hydrol. Earth Syst. Sci., 6, 671–684, https://doi.org/10.5194/hess-6-671-2002, 2002.
Shiri, J., Shamshirband, S., Kisi, O., Karimi, S., Bateni, S. M., Nezhad, S. H. H., and Hashemi, A.: Prediction of water-level in the Urima Lake using the extreme learning machine approach, Water Resour. Res., 30, 5217–5229, https://doi.org/10.1007/s11269-016-1480-x, 2016.
Suen, J. P. and Lai, H. N.: A salinity projection model for determining impacts of climate change on river ecosystems in Taiwan, J. Hydrol., 493, 124–131, https://doi.org/10.1016/j.jhydrol.2013.04.020, 2013.
Tefler, A., Burnell, R., and Charles, A.: Salt interception schemes and instream processes, in Mallee Salinity Workshop, Mallee Catchment Management Authority, 30 May 2012.
Tsai, M.-J., Abrahart, R. J., Mount, N. J., and Chang, F.-J.: Including spatial distribution in a data-driven rainfall-runoff model to improve reservoir inflow forecasting in Taiwan, Hydrol. Process., 28, 1055–1070, https://doi.org/10.1002/hyp.9559, 2014.
Wang, W., Van Gelder, P., Vrijling, J. K., and Ma, J.: Forecasting daily streamflow using hybrid ANN models, J. Hydrol., 324, 383–399, https://doi.org/10.1016/j.jhydrol.2005.09.032, 2006.
Welsh, D. W., Vaze, J., Dutta, D., Rassam, D., Rahman, J. M., Jolly, I. D., Wallbrink, P., Podger, G. M., Bethune, M., Hardy, M. J., Teng, J., and Lerat, J.: An integrated modelling framework for regulated river systems, Env. Modell. Softw., 39, 81–102, https://doi.org/10.1016/j.envsoft.2012.02.022, 2013.
Williams, W. D.: Anthropogenic salinisation of inland waters, Hydrobiologia, 466, 329–337, https://doi.org/10.1023/a:1014598509028, 2001.
Woods, J.: Modelling salt dynamics on the River Murray floodplain in South Australia: Conceptual model, data review and salinity risk approaches, Goyder Institute for Water Research Technical Report Series No. 15/9, 2015.
Wu, W., Dandy, G. C., and Maier, H. R.: Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling, Environ. Modell. Softw., 54, 108–127, https://doi.org/10.1016/j.envsoft.2013.12.016, 2014.
Yaseen, Z. M., Jaafar, O., Deo, R. C., Kisi, O., Adamowski, J., Quilty, J., and El-Shafie, A.: Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq, J. Hydrol., 542, 603–614, https://doi.org/10.1016/j.jhydrol.2016.09.035, 2016.
Zhang, H. B., Singh, V. P., Bin Wang, B., and Yu, Y. H.: CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system, J. Hydrol., 540, 246–256, https://doi.org/10.1016/j.jhydrol.2016.06.029, 2016.
Zhang, Q. and Stanley, S. J.: Forecasting raw-water quality parameters for the North Saskatchewan River by neural network modeling, Water Res., 31, 2340–2350, https://doi.org/10.1016/s0043-1354(97)00072-9, 1997.
Zheng, F., Maier, H. R., Wu, W., Dandy, G. C., Gupta, H. V., and Zhang, T.: On lack of robustness in hydrological model development due to absence of guidelines for selecting calibration and evaluation data: Demonstration for data driven models, Water Resour. Res., 54, 1013–1030, https://doi.org/10.1002/2017WR021470, 2018.
Zounemat-Kermani, M., Kişi, Ö., Adamowski, J., and Ramezani-Charmahineh, A.: Evaluation of data driven models for river suspended sediment concentration modeling, J. Hydrol., 535, 457–472, https://doi.org/10.1016/j.jhydrol.2016.02.012, 2016.
Short summary
This research proposes a generalised hybrid model development framework and applies it to a case study of salinity prediction in a reach of the Murray River. The hybrid model combines five sub-models which describe one process of salt entry each and are developed based on the amount of system knowledge and data that are available to support each individual process. The model demonstrates increased performance over two benchmark models and has implications for future model development processes.
This research proposes a generalised hybrid model development framework and applies it to a case...
