Articles | Volume 20, issue 6
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Modeling 25 years of spatio-temporal surface water and inundation dynamics on large river basin scale using time series of Earth observation data
Mirela G. Tulbure
School of Biological, Earth & Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia
School of Biological, Earth & Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia
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M. G. Tulbure, M. Broich, and Stephen V. Stehman
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 403–404,
M. Broich, A. Huete, M. G. Tulbure, X. Ma, Q. Xin, M. Paget, N. Restrepo-Coupe, K. Davies, R. Devadas, and A. Held
Biogeosciences, 11, 5181–5198,
Related subject area
Subject: Global hydrology | Techniques and Approaches: Modelling approachesPoor correlation between large-scale environmental flow violations and freshwater biodiversity: implications for water resource management and the freshwater planetary boundaryAccuracy of five ground heat flux empirical simulation methods in the surface-energy-balance-based remote-sensing evapotranspiration modelsCoupling a global glacier model to a global hydrological model prevents underestimation of glacier runoffRevisiting large-scale interception patterns constrained by a synthesis of global experimental dataInvestigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured meshUsing a long short-term memory (LSTM) neural network to boost river streamflow forecasts over the western United StatesQuantifying overlapping and differing information of global precipitation for GCM forecasts and El Niño–Southern OscillationGlobally widespread and increasing violations of environmental flow envelopesInundation prediction in tropical wetlands from JULES-CaMa-Flood global land surface simulationsSoil moisture estimation in South Asia via assimilation of SMAP retrievalsToward hyper-resolution global hydrological models including human activities: application to Kyushu island, JapanTowards hybrid modeling of the global hydrological cycleThe importance of vegetation in understanding terrestrial water storage variationsLarge-scale sensitivities of groundwater and surface water to groundwater withdrawalA hydrography upscaling method for scale-invariant parametrization of distributed hydrological modelsA novel method to identify sub-seasonal clustering episodes of extreme precipitation events and their contributions to large accumulation periodsBright and blind spots of water research in Latin America and the CaribbeanLand surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation and land cover parametersNonstationary weather and water extremes: a review of methods for their detection, attribution, and managementRobust historical evapotranspiration trends across climate regimesA note on leveraging synergy in multiple meteorological data sets with deep learning for rainfall–runoff modelingGlobal scenarios of irrigation water abstractions for bioenergy production: a systematic reviewCoordination and control – limits in standard representations of multi-reservoir operations in hydrological modelingUncertainty of simulated groundwater recharge at different global warming levels: a global-scale multi-model ensemble studyUbiquitous increases in flood magnitude in the Columbia River basin under climate changeEvaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensorsThe role of household adaptation measures in reducing vulnerability to flooding: a coupled agent-based and flood modelling approachAssessing global water mass transfers from continents to oceans over the period 1948–2016Weak sensitivity of the terrestrial water budget to global soil texture maps in the ORCHIDEE land surface modelThe influence of assimilating leaf area index in a land surface model on global water fluxes and storagesComparison of generalized non-data-driven lake and reservoir routing models for global-scale hydrologic forecasting of reservoir outflow at diurnal time stepsThe pantropical response of soil moisture to El NiñoHESS Opinions: Beyond the long-term water balance: evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watershedsGlobal assessment of how averaging over spatial heterogeneity in precipitation and potential evapotranspiration affects modeled evapotranspiration ratesEvaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modelingQuantification of drainable water storage volumes on landmasses and in river networks based on GRACE and river runoff using a cascaded storage approach – first application on the AmazonGlobal catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimationProjected increases in magnitude and socioeconomic exposure of global droughts in 1.5 and 2 °C warmer climatesSpatiotemporal assimilation–interpolation of discharge records through inverse streamflow routingTowards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasetsClimate change, reforestation/afforestation, and urbanization impacts on evapotranspiration and streamflow in EuropeMulti-decadal hydrologic change and variability in the Amazon River basin: understanding terrestrial water storage variations and drought characteristicsMultimodel assessments of human and climate impacts on mean annual streamflow in ChinaImproving soil moisture and runoff simulations at 3 km over Europe using land surface data assimilationToward continental hydrologic–hydrodynamic modeling in South AmericaGlobal re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershedThe effect of climate type on timescales of drought propagation in an ensemble of global hydrological modelsJoint assimilation of soil moisture retrieved from multiple passive microwave frequencies increases robustness of soil moisture state estimationRemote land use impacts on river flows through atmospheric teleconnectionsUnderstanding terrestrial water storage variations in northern latitudes across scales
Chinchu Mohan, Tom Gleeson, James S. Famiglietti, Vili Virkki, Matti Kummu, Miina Porkka, Lan Wang-Erlandsson, Xander Huggins, Dieter Gerten, and Sonja C. Jähnig
Hydrol. Earth Syst. Sci., 26, 6247–6262,Short summary
The relationship between environmental flow violations and freshwater biodiversity at a large scale is not well explored. This study intended to carry out an exploratory evaluation of this relationship at a large scale. While our results suggest that streamflow and EF may not be the only determinants of freshwater biodiversity at large scales, they do not preclude the existence of relationships at smaller scales or with more holistic EF methods or with other biodiversity data or metrics.
Hydrol. Earth Syst. Sci., 26, 6207–6226,Short summary
Ground heat flux (G) accounts for a significant fraction of the surface energy balance (SEB), but there is insufficient research on these models compared with other flux. The accuracy of G simulation methods in the SEB-based remote sensing evapotranspiration models is evaluated. Results show that the accuracy of each method varied significantly at different sites and at half-hour intervals. Further improvement of G simulations is recommended for the remote sensing evapotranspiration modelers.
Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 5971–5986,Short summary
We test whether coupling a global glacier model (GloGEM) with a global hydrological model (PCR-GLOBWB 2) leads to a more realistic glacier representation and to improved basin runoff simulations across 25 large-scale basins. The coupling does lead to improved glacier representation, mainly by accounting for glacier flow and net glacier mass loss, and to improved basin runoff simulations, mostly in strongly glacier-influenced basins, which is where the coupling has the most impact.
Feng Zhong, Shanhu Jiang, Albert I. J. M. van Dijk, Liliang Ren, Jaap Schellekens, and Diego G. Miralles
Hydrol. Earth Syst. Sci., 26, 5647–5667,Short summary
A synthesis of rainfall interception data from past field campaigns is performed, including 166 forests and 17 agricultural plots distributed worldwide. These site data are used to constrain and validate an interception model that considers sub-grid heterogeneity and vegetation dynamics. A global, 40-year (1980–2019) interception dataset is generated at a daily temporal and 0.1° spatial resolution. This dataset will serve as a benchmark for future investigations of the global hydrological cycle.
Dongyu Feng, Zeli Tan, Darren Engwirda, Chang Liao, Donghui Xu, Gautam Bisht, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 5473–5491,Short summary
Sea level rise, storm surge and river discharge can cause coastal backwater effects in downstream sections of rivers, creating critical flood risks. This study simulates the backwater effects using a large-scale river model on a coastal-refined computational mesh. By decomposing the backwater drivers, we revealed their relative importance and long-term variations. Our analysis highlights the increasing strength of backwater effects due to sea level rise and more frequent storm surge.
Kieran M. R. Hunt, Gwyneth R. Matthews, Florian Pappenberger, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 26, 5449–5472,Short summary
In this study, we use three models to forecast river streamflow operationally for 13 months (September 2020 to October 2021) at 10 gauges in the western US. The first model is a state-of-the-art physics-based streamflow model (GloFAS). The second applies a bias-correction technique to GloFAS. The third is a type of neural network (an LSTM). We find that all three are capable of producing skilful forecasts but that the LSTM performs the best, with skilful 5 d forecasts at nine stations.
Tongtiegang Zhao, Haoling Chen, Yu Tian, Denghua Yan, Weixin Xu, Huayang Cai, Jiabiao Wang, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 26, 4233–4249,Short summary
This paper develops a novel set operations of coefficients of determination (SOCD) method to explicitly quantify the overlapping and differing information for GCM forecasts and ENSO teleconnection. Specifically, the intersection operation of the coefficient of determination derives the overlapping information for GCM forecasts and the Niño3.4 index, and then the difference operation determines the differing information in GCM forecasts (Niño3.4 index) from the Niño3.4 index (GCM forecasts).
Vili Virkki, Elina Alanärä, Miina Porkka, Lauri Ahopelto, Tom Gleeson, Chinchu Mohan, Lan Wang-Erlandsson, Martina Flörke, Dieter Gerten, Simon N. Gosling, Naota Hanasaki, Hannes Müller Schmied, Niko Wanders, and Matti Kummu
Hydrol. Earth Syst. Sci., 26, 3315–3336,Short summary
Direct and indirect human actions have altered streamflow across the world since pre-industrial times. Here, we apply a method of environmental flow envelopes (EFEs) that develops the existing global environmental flow assessments by methodological advances and better consideration of uncertainty. By assessing the violations of the EFE, we comprehensively quantify the frequency, severity, and trends of flow alteration during the past decades, illustrating anthropogenic effects on streamflow.
Toby R. Marthews, Simon J. Dadson, Douglas B. Clark, Eleanor M. Blyth, Garry D. Hayman, Dai Yamazaki, Olivia R. E. Becher, Alberto Martínez-de la Torre, Catherine Prigent, and Carlos Jiménez
Hydrol. Earth Syst. Sci., 26, 3151–3175,Short summary
Reliable data on global inundated areas remain uncertain. By matching a leading global data product on inundation extents (GIEMS) against predictions from a global hydrodynamic model (CaMa-Flood), we found small but consistent and non-random biases in well-known tropical wetlands (Sudd, Pantanal, Amazon and Congo). These result from known limitations in the data and the models used, which shows us how to improve our ability to make critical predictions of inundation events in the future.
Jawairia A. Ahmad, Barton A. Forman, and Sujay V. Kumar
Hydrol. Earth Syst. Sci., 26, 2221–2243,Short summary
Assimilation of remotely sensed data into a land surface model to improve the spatiotemporal estimation of soil moisture across South Asia exhibits potential. Satellite retrieval assimilation corrects biases that are generated due to an unmodeled hydrologic phenomenon, i.e., irrigation. The improvements in fine-scale, modeled soil moisture estimates by assimilating coarse-scale retrievals indicates the utility of the described methodology for data-scarce regions.
Naota Hanasaki, Hikari Matsuda, Masashi Fujiwara, Yukiko Hirabayashi, Shinta Seto, Shinjiro Kanae, and Taikan Oki
Hydrol. Earth Syst. Sci., 26, 1953–1975,Short summary
Global hydrological models (GHMs) are usually applied with a spatial resolution of about 50 km, but this time we applied the H08 model, one of the most advanced GHMs, with a high resolution of 2 km to Kyushu island, Japan. Since the model was not accurate as it was, we incorporated local information and improved the model, which revealed detailed water stress in subregions that were not visible with the previous resolution.
Basil Kraft, Martin Jung, Marco Körner, Sujan Koirala, and Markus Reichstein
Hydrol. Earth Syst. Sci., 26, 1579–1614,Short summary
We present a physics-aware machine learning model of the global hydrological cycle. As the model uses neural networks under the hood, the simulations of the water cycle are learned from data, and yet they are informed and constrained by physical knowledge. The simulated patterns lie within the range of existing hydrological models and are plausible. The hybrid modeling approach has the potential to tackle key environmental questions from a novel perspective.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Andreas Güntner, and Martin Jung
Hydrol. Earth Syst. Sci., 26, 1089–1109,Short summary
We assess the effect of how vegetation is defined in a global hydrological model on the composition of total water storage (TWS). We compare two experiments, one with globally uniform and one with vegetation parameters that vary in space and time. While both experiments are constrained against observational data, we found a drastic change in the partitioning of TWS, highlighting the important role of the interaction between groundwater–soil moisture–vegetation in understanding TWS variations.
Marc F. P. Bierkens, Edwin H. Sutanudjaja, and Niko Wanders
Hydrol. Earth Syst. Sci., 25, 5859–5878,Short summary
We introduce a simple analytical framework that allows us to estimate to what extent large-scale groundwater withdrawal affects groundwater levels and streamflow. It also calculates which part of the groundwater withdrawal comes out of groundwater storage and which part from a reduction in streamflow. Global depletion rates obtained with the framework are compared with estimates from satellites, from global- and continental-scale groundwater models, and from in situ datasets.
Dirk Eilander, Willem van Verseveld, Dai Yamazaki, Albrecht Weerts, Hessel C. Winsemius, and Philip J. Ward
Hydrol. Earth Syst. Sci., 25, 5287–5313,Short summary
Digital elevation models and derived flow directions are crucial to distributed hydrological modeling. As the spatial resolution of models is typically coarser than these data, we need methods to upscale flow direction data while preserving the river structure. We propose the Iterative Hydrography Upscaling (IHU) method and show it outperforms other often-applied methods. We publish the multi-resolution MERIT Hydro IHU hydrography dataset and the algorithm as part of the pyflwdir Python package.
Jérôme Kopp, Pauline Rivoire, S. Mubashshir Ali, Yannick Barton, and Olivia Martius
Hydrol. Earth Syst. Sci., 25, 5153–5174,Short summary
Episodes of extreme rainfall events happening in close temporal succession can lead to floods with dramatic impacts. We developed a novel method to individually identify those episodes and deduced the regions where they occur frequently and where their impact is substantial. Those regions are the east and northeast of the Asian continent, central Canada and the south of California, Afghanistan, Pakistan, the southwest of the Iberian Peninsula, and north of Argentina and south of Bolivia.
Alyssa J. DeVincentis, Hervé Guillon, Romina Díaz Gómez, Noelle K. Patterson, Francine van den Brandeler, Arthur Koehl, J. Pablo Ortiz-Partida, Laura E. Garza-Díaz, Jennifer Gamez-Rodríguez, Erfan Goharian, and Samuel Sandoval Solis
Hydrol. Earth Syst. Sci., 25, 4631–4650,Short summary
Latin America and the Caribbean face many water-related stresses which are expected to worsen with climate change. To assess the vulnerability, we reviewed over 20 000 multilingual research articles using machine learning and an understanding of the regional landscape. Results reveal that the region’s inherent vulnerability is compounded by research blind spots in niche topics (reservoirs and risk assessment) and subregions (Caribbean nations), as well as by its reliance on one country (Brazil).
Michiel Maertens, Gabriëlle J. M. De Lannoy, Sebastian Apers, Sujay V. Kumar, and Sarith P. P. Mahanama
Hydrol. Earth Syst. Sci., 25, 4099–4125,Short summary
In this study, we simulated the water balance over the South American Dry Chaco and assessed the impact of land cover changes thereon using three different land surface models. Our simulations indicated that different models result in a different partitioning of the total water budget, but all showed an increase in soil moisture and percolation over the deforested areas. We also found that, relative to independent data, no specific land surface model is significantly better than another.
Louise J. Slater, Bailey Anderson, Marcus Buechel, Simon Dadson, Shasha Han, Shaun Harrigan, Timo Kelder, Katie Kowal, Thomas Lees, Tom Matthews, Conor Murphy, and Robert L. Wilby
Hydrol. Earth Syst. Sci., 25, 3897–3935,Short summary
Weather and water extremes have devastating effects each year. One of the principal challenges for society is understanding how extremes are likely to evolve under the influence of changes in climate, land cover, and other human impacts. This paper provides a review of the methods and challenges associated with the detection, attribution, management, and projection of nonstationary weather and water extremes.
Sanaa Hobeichi, Gab Abramowitz, and Jason P. Evans
Hydrol. Earth Syst. Sci., 25, 3855–3874,Short summary
Evapotranspiration (ET) links the water, energy and carbon cycle on land. Reliable ET estimates are key to understand droughts and flooding. We develop a new ET dataset, DOLCE V3, by merging multiple global ET datasets, and we show that it matches ET observations better and hence is more reliable than its parent datasets. Next, we use DOLCE V3 to examine recent changes in ET and find that ET has increased over most of the land, decreased in some regions, and has not changed in some other regions
Frederik Kratzert, Daniel Klotz, Sepp Hochreiter, and Grey S. Nearing
Hydrol. Earth Syst. Sci., 25, 2685–2703,Short summary
We investigate how deep learning models use different meteorological data sets in the task of (regional) rainfall–runoff modeling. We show that performance can be significantly improved when using different data products as input and further show how the model learns to combine those meteorological input differently across time and space. The results are carefully benchmarked against classical approaches, showing the supremacy of the presented approach.
Fabian Stenzel, Dieter Gerten, and Naota Hanasaki
Hydrol. Earth Syst. Sci., 25, 1711–1726,Short summary
Ideas to mitigate climate change include the large-scale cultivation of fast-growing plants to capture atmospheric CO2 in biomass. To maximize the productivity of these plants, they will likely be irrigated. However, there is strong disagreement in the literature on how much irrigation water is needed globally, potentially inducing water stress. We provide a comprehensive overview of global irrigation demand studies for biomass production and discuss the diverse underlying study assumptions.
Charles Rougé, Patrick M. Reed, Danielle S. Grogan, Shan Zuidema, Alexander Prusevich, Stanley Glidden, Jonathan R. Lamontagne, and Richard B. Lammers
Hydrol. Earth Syst. Sci., 25, 1365–1388,Short summary
Amid growing interest in using large-scale hydrological models for flood and drought monitoring and forecasting, it is important to evaluate common assumptions these models make. We investigated the representation of reservoirs as separate (non-coordinated) infrastructure. We found that not appropriately representing coordination and control processes can lead a hydrological model to simulate flood and drought events that would not occur given the coordinated emergency response in the basin.
Robert Reinecke, Hannes Müller Schmied, Tim Trautmann, Lauren Seaby Andersen, Peter Burek, Martina Flörke, Simon N. Gosling, Manolis Grillakis, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Wim Thiery, Yoshihide Wada, Satoh Yusuke, and Petra Döll
Hydrol. Earth Syst. Sci., 25, 787–810,Short summary
Billions of people rely on groundwater as an accessible source of drinking water and for irrigation, especially in times of drought. Groundwater recharge is the primary process of regenerating groundwater resources. We find that groundwater recharge will increase in northern Europe by about 19 % and decrease by 10 % in the Amazon with 3 °C global warming. In the Mediterranean, a 2 °C warming has already lead to a reduction in recharge by 38 %. However, these model predictions are uncertain.
Laura E. Queen, Philip W. Mote, David E. Rupp, Oriana Chegwidden, and Bart Nijssen
Hydrol. Earth Syst. Sci., 25, 257–272,Short summary
Using a large ensemble of simulated flows throughout the northwestern USA, we compare daily flood statistics in the past (1950–1999) and future (2050–1999) periods and find that nearly all locations will experience an increase in flood magnitudes. The flood season expands significantly in many currently snow-dominant rivers, moving from only spring to both winter and spring. These results, properly extended, may help inform flood risk management and negotiations of the Columbia River Treaty.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40,Short summary
We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Yared Abayneh Abebe, Amineh Ghorbani, Igor Nikolic, Natasa Manojlovic, Angelika Gruhn, and Zoran Vojinovic
Hydrol. Earth Syst. Sci., 24, 5329–5354,Short summary
The paper presents a coupled agent-based and flood model for Hamburg, Germany. It explores residents’ adaptation behaviour in relation to flood event scenarios, economic incentives and shared and individual strategies. We found that unique trajectories of adaptation behaviour emerge from different flood event series. Providing subsidies improves adaptation behaviour in the long run. The coupled modelling technique allows the role of individual measures in flood risk management to be examined.
Denise Cáceres, Ben Marzeion, Jan Hendrik Malles, Benjamin Daniel Gutknecht, Hannes Müller Schmied, and Petra Döll
Hydrol. Earth Syst. Sci., 24, 4831–4851,Short summary
We analysed how and to which extent changes in water storage on continents had an effect on global ocean mass over the period 1948–2016. Continents lost water to oceans at an accelerated rate, inducing sea level rise. Shrinking glaciers explain 81 % of the long-term continental water mass loss, while declining groundwater levels, mainly due to sustained groundwater pumping for irrigation, is the second major driver. This long-term decline was partly offset by the impoundment of water in dams.
Salma Tafasca, Agnès Ducharne, and Christian Valentin
Hydrol. Earth Syst. Sci., 24, 3753–3774,Short summary
In land surface models (LSMs), soil properties are inferred from soil texture. In this study, we use different input global soil texture maps from the literature to investigate the impact of soil texture on the simulated water budget in an LSM. The medium loamy textures give the highest evapotranspiration and lowest total runoff rates. However, the different soil texture maps result in similar water budgets because of their inherent similarities, especially when upscaled at the 0.5° resolution.
Xinxuan Zhang, Viviana Maggioni, Azbina Rahman, Paul Houser, Yuan Xue, Timothy Sauer, Sujay Kumar, and David Mocko
Hydrol. Earth Syst. Sci., 24, 3775–3788,Short summary
This study assesses the extent to which a land surface model can be optimized via the assimilation of leaf area index (LAI) observations at the global scale. The model performance is evaluated by the model-estimated LAI and five water flux/storage variables. Results show the LAI assimilation reduces errors in the model-estimated LAI. The LAI assimilation also improves the five water variables under wet conditions, but some of the model-estimated variables tend to be worse under dry conditions.
Joseph L. Gutenson, Ahmad A. Tavakoly, Mark D. Wahl, and Michael L. Follum
Hydrol. Earth Syst. Sci., 24, 2711–2729,Short summary
Global-scale hydrologic forecasts should account for attenuation through lakes and reservoirs. There is no consensus on the best approach to estimating this attenuation in large-spatial-scale hydrologic forecasts. This article investigates two existing parsimonious approaches to estimating reservoir outflows. We test each method at 60 reservoirs in the United States. We find that a method first developed in 2003 can provide a reasonable approximation of diurnal reservoir outflows.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322,Short summary
We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
A. Sankarasubramanian, Dingbao Wang, Stacey Archfield, Meredith Reitz, Richard M. Vogel, Amirhossein Mazrooei, and Sudarshana Mukhopadhyay
Hydrol. Earth Syst. Sci., 24, 1975–1984,Short summary
The Budyko framework which relies on the supply and demand concept could be effectively adapted and extended to quantify the role of drivers – both changing climate and local human disturbances – in altering the land-surface response. This framework is extended with a few illustrative examples for quantifying the variability in land-surface fluxes for natural and human-altered watersheds. Potential for using observed and remotely sensed datasets in capturing this variability is also discussed.
Elham Rouholahnejad Freund, Ying Fan, and James W. Kirchner
Hydrol. Earth Syst. Sci., 24, 1927–1938,Short summary
Evapotranspiration (ET) rates and properties that regulate them are spatially heterogeneous. Averaging over spatial heterogeneity in precipitation (P) and potential evapotranspiration (PET) as the main drivers of ET may lead to biased estimates of energy and water fluxes from the land to the atmosphere. We show that this bias is largest in mountainous terrains, in regions with temperate climates and dry summers, and in landscapes where spatial variations in P and PET are inversely correlated.
Shufen Pan, Naiqing Pan, Hanqin Tian, Pierre Friedlingstein, Stephen Sitch, Hao Shi, Vivek K. Arora, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Catherine Ottlé, Benjamin Poulter, Sönke Zaehle, and Steven W. Running
Hydrol. Earth Syst. Sci., 24, 1485–1509,Short summary
Evapotranspiration (ET) links global water, carbon and energy cycles. We used 4 remote sensing models, 2 machine-learning algorithms and 14 land surface models to analyze the changes in global terrestrial ET. These three categories of approaches agreed well in terms of ET intensity. For 1982–2011, all models showed that Earth greening enhanced terrestrial ET. The small interannual variability of global terrestrial ET suggests it has a potential planetary boundary of around 600 mm yr-1.
Hydrol. Earth Syst. Sci., 24, 1447–1465,Short summary
The combined use of GRACE mass anomalies and observed river discharge for the first time allows us to quantify the water storage volumes drainable by gravity on global scales. Modelling of catchment and river network storages in a cascade with different dynamics reveals the time lag between total mass and runoff is caused by a non-zero river network storage. This allows catchment and river network storage volumes to be distinguished and is thus of great importance for water resources management.
Berit Arheimer, Rafael Pimentel, Kristina Isberg, Louise Crochemore, Jafet C. M. Andersson, Abdulghani Hasan, and Luis Pineda
Hydrol. Earth Syst. Sci., 24, 535–559,Short summary
How far can we reach in predicting river flow globally, using integrated catchment modelling and open global data? For the first time, a catchment model was applied world-wide, covering the entire globe with a relatively high resolution. The results show that stepwise calibration provided better performance than traditional modelling of the globe. The study highlights that open data and models are crucial to advance hydrological sciences by sharing knowledge and enabling transparent evaluation.
Lei Gu, Jie Chen, Jiabo Yin, Sylvia C. Sullivan, Hui-Min Wang, Shenglian Guo, Liping Zhang, and Jong-Suk Kim
Hydrol. Earth Syst. Sci., 24, 451–472,Short summary
Focusing on the multifaceted nature of droughts, this study quantifies the change in global drought risks for 1.5 and 2.0 °C warming trajectories by a multi-model ensemble under three representative concentration pathways (RCP2.6, 4.5 and 8.5). Socioeconomic exposures are investigated by incorporating the dynamic shared socioeconomic pathways (SSPs) into the drought impact assessment. The results show that even the ambitious 1.5 °C warming level can cause substantial increases on the global scale.
Colby K. Fisher, Ming Pan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 24, 293–305,Short summary
Poorly monitored river flows in many regions of the world have been hindering our ability to accurately estimate global water usage. In this paper we present a method to derive continuous records of streamflow from a set of in situ gauges. Applying this method to the Ohio River basin, we found that we could reliably generate estimates of streamflow throughout the basin using only a small set of streamflow gauges, which can be useful for global river basins where we do not have good observations.
Frederik Kratzert, Daniel Klotz, Guy Shalev, Günter Klambauer, Sepp Hochreiter, and Grey Nearing
Hydrol. Earth Syst. Sci., 23, 5089–5110,Short summary
A new approach for regional rainfall–runoff modeling using long short-term memory (LSTM)-based models is presented and benchmarked against a range of well-known hydrological models. The approach significantly outperforms regionally calibrated hydrological models but also basin-wise calibrated models. Furthermore, we propose an adaption of the LSTM that allows us to extract the learned catchment understanding of the model and show that it matches our hydrology expert knowledge.
Adriaan J. Teuling, Emile A. G. de Badts, Femke A. Jansen, Richard Fuchs, Joost Buitink, Anne J. Hoek van Dijke, and Shannon M. Sterling
Hydrol. Earth Syst. Sci., 23, 3631–3652,Short summary
Over the past decades, changes in land use and climate over Europe have impacted the average flow of water flowing through rivers and reservoirs (the so-called
water yield). We quantify these changes using a simple but widely tested modelling approach constrained by observations of lysimeters across Europe. Results show that the contribution of land use to changes in water yield are of the same order as changes in climate, showing that impacts of land use changes cannot be neglected.
Suyog Chaudhari, Yadu Pokhrel, Emilio Moran, and Gonzalo Miguez-Macho
Hydrol. Earth Syst. Sci., 23, 2841–2862,Short summary
Comprehensive characterization of extreme drought events in the Amazon is provided with respect to their cause, type, spatial extent, and impact on different water stores. Basin-averaged trends in water storage indicate that the Amazon is getting wetter; however its southern and southeastern portions are getting drier. Water deficit is found to be 3-fold higher than the total water supplied during some drought years. Water deficit due to low precipitation events is absorbed by the groundwater.
Xingcai Liu, Wenfeng Liu, Hong Yang, Qiuhong Tang, Martina Flörke, Yoshimitsu Masaki, Hannes Müller Schmied, Sebastian Ostberg, Yadu Pokhrel, Yusuke Satoh, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 23, 1245–1261,Short summary
Human activities associated with water resource management have significantly increased in China during the past decades. This assessment helps us understand how streamflow has been affected by climate and human activities in China. Our analyses indicate that the climate impact has dominated streamflow changes in most areas, and human activities (in terms of water withdrawals) have increasingly decreased streamflow in the northern basins of China which are vulnerable to future climate change.
Bibi S. Naz, Wolfgang Kurtz, Carsten Montzka, Wendy Sharples, Klaus Goergen, Jessica Keune, Huilin Gao, Anne Springer, Harrie-Jan Hendricks Franssen, and Stefan Kollet
Hydrol. Earth Syst. Sci., 23, 277–301,Short summary
This study investigates the value of assimilating coarse-resolution remotely sensed soil moisture data into high-resolution land surface models for improving soil moisture and runoff modeling. The soil moisture estimates in this study, with complete spatio-temporal coverage and improved spatial resolution from the assimilation, offer a new reanalysis product for the monitoring of surface soil water content and other hydrological fluxes at 3 km resolution over Europe.
Vinícius A. Siqueira, Rodrigo C. D. Paiva, Ayan S. Fleischmann, Fernando M. Fan, Anderson L. Ruhoff, Paulo R. M. Pontes, Adrien Paris, Stéphane Calmant, and Walter Collischonn
Hydrol. Earth Syst. Sci., 22, 4815–4842,Short summary
Providing reliable estimates of water fluxes at the continental scale is challenging. We extended a regional hydrological model to the entirety of South America and assessed its performance using multiple observations. After a comparison with global models, we show the extent to which estimates of daily river discharge can be improved, even by using global forcing data. Issues of global-/continental-scale modeling and future directions for simulating discharge in this continent are discussed.
David R. Casson, Micha Werner, Albrecht Weerts, and Dimitri Solomatine
Hydrol. Earth Syst. Sci., 22, 4685–4697,Short summary
In high-latitude (> 60° N) watersheds, measuring the snowpack and predicting of snowmelt runoff are uncertain due to the lack of data and complex physical processes. This provides challenges for hydrological assessment and operational water management. Global re-analysis datasets have great potential to aid in snowpack representation and snowmelt prediction when combined with a distributed hydrological model, though they still have clear limitations in remote boreal forest and tundra environments.
Anouk I. Gevaert, Ted I. E. Veldkamp, and Philip J. Ward
Hydrol. Earth Syst. Sci., 22, 4649–4665,Short summary
Drought is a natural hazard that has severe environmental and socioeconomic impacts around the globe. Here, we quantified the time taken for drought to propagate from precipitation droughts to soil moisture and streamflow droughts. Results show that propagation timescales are strongly related to climate type, with fast responses in tropical regions and slow responses in arid regions. Insight into the timescales of drought propagation globally may help improve seasonal drought forecasting.
Anouk I. Gevaert, Luigi J. Renzullo, Albert I. J. M. van Dijk, Hans J. van der Woerd, Albrecht H. Weerts, and Richard A. M. de Jeu
Hydrol. Earth Syst. Sci., 22, 4605–4619,Short summary
We assimilated three satellite soil moisture retrievals based on different microwave frequencies into a hydrological model. Two sets of experiments were performed, first assimilating the retrievals individually and then assimilating each set of two retrievals jointly. Overall, assimilation improved agreement between model and field-measured soil moisture. Joint assimilation resulted in model performance similar to or better than assimilating either retrieval individually.
Lan Wang-Erlandsson, Ingo Fetzer, Patrick W. Keys, Ruud J. van der Ent, Hubert H. G. Savenije, and Line J. Gordon
Hydrol. Earth Syst. Sci., 22, 4311–4328,Short summary
Winds carry air moisture from one place to another. Thus, land-use change that alters air moisture content can also modify downwind rainfall and distant river flows. This aspect has rarely been taken into account in studies of river flow changes. We show here that remote land-use change effect on rainfall can exceed that of local, and that foreign nation influence on river flows is much more prevalent than previously thought. This has important implications for both land and water governance.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Annette Eicker, Manfred Fink, Christoph Niemann, and Martin Jung
Hydrol. Earth Syst. Sci., 22, 4061–4082,Short summary
In this study, we adjust a simple hydrological model to several observational datasets, including satellite observations of the land's total water storage. We apply the model to northern latitudes and find that the dominating factor of changes in the total water storage depends on both the spatial and temporal scale of analysis. While snow dominates seasonal variations, liquid water determines year-to-year variations, yet with increasing contribution of snow when averaging over larger regions.
Aksoy, H., Unal, N. E., Eris, E., and Yuce, M. I.: Stochastic modeling of Lake Van water level time series with jumps and multiple trends, Hydrol. Earth Syst. Sci., 17, 2297–2303, https://doi.org/10.5194/hess-17-2297-2013, 2013.
Alfons, A.: cvTools: Cross-validation tools for regression models, R package version 0.3.2., available at: http://CRAN.R-project.org/package=cvTools, last access: 12 May 2016, 2012.
Alsdorf, D. E., Rodríguez, E., and Lettenmaier, D. P.: Measuring Surface Water from Space, Rev. Geophys, 45, 1–24, https://doi.org/10.1029/2006RG000197, 2007.
Arlot, S. and Celisse, A.: A survey of cross-validation procedures for model selection, Stat. Surv., 4, 40–79, https://doi.org/10.1214/09-SS054, 2010.
Baker, C., Lawrence, R., Montagne, C., and Patten, D.: Change detection of Wetland ecosystems using Landsat Imagery and change vector analysis, Wetlands, 27, 610–619, https://doi.org/10.1672/0277-5212(2007)27[610:CDOWEU]2.0.CO;2, 2007.
Bakker, K.: Water Security: Research Challenges and Opportunities, Science, 337, 914–915, https://doi.org/10.1126/science.1226337, 2012.
Bennett, N. D., Croke, B. F. W., Guariso, G., Guillaume, J. H. A., Hamilton, S. H., Jakeman, A. J., Marsili-Libelli, S., Newham, L. T. H., Norton, J. P., Perrin, C., Pierce, S. A., Robson, B., Seppelt, R., Voinov, A. A., Fath, B. D., and Andreassian, V.: Characterising performance of environmental models, Environ. Modell. Softw., 40, 1–20, https://doi.org/10.1016/j.envsoft.2012.09.011, 2013.
Box, G. E. P. and Jenkins, G. M.: Time series analysis, forecasting and control, Holden-day series in time series analysis, Holden-Day, Oakland, CA, 1970.
Broich, M., Hansen, M. C., Potapov, P., Adusei, B., Lindquist, E., and Stehman, S. V: Time-series analysis of multi-resolution optical imagery for quantifying forest cover loss in Sumatra and Kalimantan, Indonesia, Int. J. Appl. Earth Obs., 13, 277–291, https://doi.org/10.1016/j.jag.2010.11.004, 2011.
BRS (Bureau of Rural Sciences): Combined irrigation areas of Australia dataset, BRS, Canberra, 2008.
Bunn, S. E., Thoms, M. C., Hamilton, S. K., and Capon, S. J.: Flow variability in dryland rivers: Boom, bust and the bits in between, River Res. Appl., 22, 179–186, https://doi.org/10.1002/rra.904, 2006.
Cauduro, R., De Paiva, D., Buarque, D. C., Collischonn, W., and Bonnet, M.: Large-scale hydrologic and hydrodynamic modeling of the Amazon River basin, Water Resour. Res., 49, 1226–1243, https://doi.org/10.1002/wrcr.20067, 2013.
Chen, Y., Cuddy, S. M., Merrin, L. E., Huang, C., Pollock, D., Sims, N., Wang, B., and Bai, Q.: Murray–Darling Basin Floodplain Inundation Model Version 2.0 (MDB-FIM2), Technical report, CSIRO Water for a Healthy Country Flagship, 2012.
Chen, Y., Wang, B., Pollino, C. A., Cuddy, S. M., Merrin, L. E., and Huang, C.: Estimate of flood inundation and retention on wetlands using remote sensing and GIS, Ecohydrology, 7, 1412–1420, https://doi.org/10.1002/eco.1467, 2014.
Commonwealth of Australia (Bureau of Meteorology): Australian Geofabric, available at: http://www.bom.gov.au/water/geofabric/, last access: 12 May 2016, 2012.
Commonwealth of Australia (Bureau of Meteorology): Australian Daily Rainfall Gridded Data, available at: http://www.bom.gov.au/climate/how/newproducts/IDCdrgrids.shtml, last access: 12 April 2016, 2015.
Costanza, R., de Groot, R., Sutton, P., van der Ploeg, S., Anderson, S. J., Kubiszewski, I., Farber, S., and Turner, R. K.: Changes in the global value of ecosystem services, Global Environ. Chang., 26, 152–158, https://doi.org/10.1016/j.gloenvcha.2014.04.002, 2014.
Costelloe, J. F., Grayson, R. B., Argent, R. M., and McMahon, T. A.: Modelling the flow regime of an arid zone floodplain river, Diamantina River, Australia, Environ. Modell. Softw., 18, 693–703, https://doi.org/10.1016/S1364-8152(03)00071-9, 2003.
CSIRO: Water Availability in the Murray–Darling Basin, A report from CSIRO to the Australian Government from the CSIRO Murray–Darling Basin Sustainable Yields Project, CSIRO, Australia, 2008.
Environment Australia: A directory of important wetlands in Australia, 3rd Edn., Environment Australia, Canberra, 2001.
Finlayson, C. M. and Spiers, A. G.: Global Review of Wetland Resources and Priorities for Inventory, Supervising Scientist Report No. 144, Canberra, 1999.
Finlayson, C. M., Davidson, N. C., Spiers, A. G., and Stevenson, N. J.: Global wetland inventory – current status and future priorities, Mar. Freshwater Res., 50, 717–727, https://doi.org/10.1071/MF99098, 1999.
Frazier, P. and Page, K.: A Reach-Scale Remote Sensing Technique to Relate Wetland Inundation to River Flow, River Res. Appl., 25, 836–849, https://doi.org/10.1002/rra.1183, 2009.
Geoscience Australia and CSIRO: 1 Second SRTM Derived Digital Elevation Models User Guide, Version 1.0.4. Canberra, ACT, Geoscience Australia, 2011.
Getirana, A. C. V., Boone, A., Yamazaki, D., Decharme, B., Mognard, N., and Papa, F.: The Hydrological Modeling and Analysis Platform (HyMAP): Evaluation in the Amazon Basin, J. Hydrometeorol., 13, 1641–1665, https://doi.org/10.1175/JHM-D-12-021.1, 2012.
Government of South Australia: WaterConnect, available at: http://www.waterconnect.sa.gov.au, last access: 12 April 2016, 2015.
Gumbricht, T., Wolski, P., Frost, P., and McCarthy, T.: Forecasting the spatial extent of the annual flood in the Okavango delta, Botswana, J. Hydrol., 290, 178–191, https://doi.org/10.1016/j.jhydrol.2003.11.010, 2004.
Hamilton, S. K.: Wetlands of Large Rivers: Flood plains, in: River ecosystem ecology: a global perspective: a derivative of Encyclopedia of inland waters, Elsevier Inc., 607–610, 2010.
Huang, C., Chen, Y., and Wu, J.: GIS-based spatial zoning for flood inundation modelling in the Murray–Darling Basin, in 20th International Congress on Modelling and Simulation, Adelaide, Australia, 1–6 December 2013, available at: www.mssanz.org.au/modsim2013, last access: 12 May 2016, 2013.
Huang, C., Chen, Y., and Wu, J.: Mapping spatio-temporal flood inundation dynamics at large river basin scale using time-series flow data and MODIS imagery, Int. J. Appl. Earth Obs., 26, 350–362, https://doi.org/10.1016/j.jag.2013.09.002, 2014a.
Huang, C., Peng, Y., Lang, M., Yeo, I.-Y., and McCarty, G.: Wetland inundation mapping and change monitoring using Landsat and airborne LiDAR data, Remote Sens. Environ., 141, 231–242, https://doi.org/10.1016/j.rse.2013.10.020, 2014b.
Jones, K., Lanthier, Y., van der Voet, P., van Valkengoed, E., Taylor, D., and Fernández-Prieto, D.: Monitoring and assessment of wetlands using Earth Observation: the GlobWetland project, J. Environ. Manage., 90, 2154–69, https://doi.org/10.1016/j.jenvman.2007.07.037, 2009.
Jung, H. C., Alsdorf, D., Moritz, M., Lee, H., and Vassolo, S.: Analysis of the relationship between flooding area and water height in the Logone floodplain, Phys. Chem. Earth, 36, 232–240, https://doi.org/10.1016/j.pce.2011.01.010, 2011.
Keele, L. and Kelly, N. J.: Dynamic models for dynamic theories: The ins and outs of lagged dependent variables, Polit. Anal., 14, 186–205, https://doi.org/10.1093/pan/mpj006, 2006.
Kingsford, R.: Ecological impacts of dams, water diversions and river management on floodplain wetlands in Australia, Austral. Ecol., 25, 109–127, 2000.
Kingsford, R. T., Thomas, R. F., and Curtin, A. L.: Conservation of wetlands in the Paroo and Warrego River catchments in arid Australia, Pacific Conservation Biology, 7, 21–33, 2001.
Kingsford, R. T., Brandis, K., Thomas, R. F., Crighton, P., Knowles, E., and Gale, E.: Classifying landform at broad spatial scales: the distribution and conservation of wetlands in New South Wales, Australia, Mar. Freshwater Res., 55, 17–31, https://doi.org/10.1071/MF03075, 2004.
Klein, I., Dietz, A. J., Gessner, U., Galayeva, A., Myrzakhmetov, A., and Kuenzer, C.: Evaluation of seasonal water body extents in Central Asia over the past 27 years derived from medium-resolution remote sensing data, Int. J. Appl. Earth Obs., 26, 335–349, https://doi.org/10.1016/j.jag.2013.08.004, 2014.
Kuenzer, C., Klein, I., Ullmann, T., Georgiou, E., Baumhauer, R., and Dech, S.: Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series, Remote Sens., 7, 8516–8542, https://doi.org/10.3390/rs70708516, 2015.
Lamontagne, S. and Herczeg, A. L.: Hydrology and ecohydrology of Australian semi-arid wetlands, Hydrol. Process., 23, 3413–3414, https://doi.org/10.1002/hyp.7462, 2009.
Leauthaud, C., Belaud, G., Duvail, S., Moussa, R., Grünberger, O., and Albergel, J.: Characterizing floods in the poorly gauged wetlands of the Tana River Delta, Kenya, using a water balance model and satellite data, Hydrol. Earth Syst. Sci., 17, 3059–3075, https://doi.org/10.5194/hess-17-3059-2013, 2013.
Leblanc, M., Tweed, S., Van Dijk, A., and Timbal, B.: A review of historic and future hydrological changes in the Murray–Darling Basin, Global Planet. Change, 80–81, 226–246, https://doi.org/10.1016/j.gloplacha.2011.10.012, 2012.
Lemly, A., Kingsford, R., and Thompson, J.: Irrigated Agriculture and Wildlife Conservation: Conflict on a Global Scale, Environ. Manage., 25, 485–512, https://doi.org/10.1007/s002679910039, 2000.
Liu, Y. Y., Dorigo, W. A., Parinussa, R. M., de Jeu, R. A. M., Wagner, W., McCabe, M. F., Evans, J. P., and van Dijk, A. I. J. M.: Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sens. Environ., 123, 280–297, https://doi.org/10.1016/j.rse.2012.03.014, 2012.
Maltby, E. and Acreman, M. C.: Ecosystem services of wetlands: pathfinder for a new paradigm, Hydrol. Sci. J., 56, 1341–1359, https://doi.org/10.1080/02626667.2011.631014, 2011.
Mccarthy, J. M., Gumbricht, T., Mccarthy, T., Frost, P., Wessels, K., and Seidel, F.: Flooding Patterns of the Okavango Wetland in Botswana between 1972 and 2000, Ambio, 32, 453–457, 2003.
MDBA: Guide to the proposed Basin Plan Technical background, Murray–Darling Basin Authority, Canberra, 2010.
Nativi, S., Mazzetti, P., Santoro, M., Papeschi, F., Craglia, M., and Ochiai, O.: Big Data challenges and solutions in building the Global Earth Observation System of Systems, Environ. Modell. Softw., 68, 1–26, https://doi.org/10.1016/j.envsoft.2015.01.017, 2015.
Neal, J., Schumann, G., and Bates, P.: A subgrid channel model for simulating river hydraulics and floodplain inundation over large and data sparse areas, Water Resour. Res., 48, W11506, https://doi.org/10.1029/2012WR012514, 2012.
Neal, J. C., Odoni, N. A., Trigg, M. A., Freer, J. E., Garcia-Pintado, J., Mason, D. C., Wood, M., and Bates, P. D.: Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models, J. Hydrol., 529, 169–183, https://doi.org/10.1016/j.jhydrol.2015.07.026, 2015.
New South Wales Government: Waterinfo, available at: http://waterinfo.nsw.gov.au/pinneena/cm.shtml, last access: 12 April 2016, 2015.
Overton, I. C.: Modelling floodplain inundation on a regulated river: integrating GIS, remote sensing and hydrological models, River Res. Appl., 21, 991–1001, https://doi.org/10.1002/rra.867, 2005.
Overton, I. C., McEwan, K., and Sherrah, J. R.: The River Murray Floodplain Inundation Model (RiM-FIM) Hume Dam to Lower Lakes. CSIRO Water for a Healthy Country Technical Report 2006, CSIRO, Canberra, 2006.
Overton, I. C., Colloff, M. J., Doody, T. M., Henderson, B., and Cuddy, S. M.: "Ecological Outcomes of Flow Regimes in the Murray–Darling Basin", Report prepared for the National Water Commission by CSIRO Water for a Healthy Country Flagship, CSIRO, Canberra, 2009.
Penton, D. J. and Overton, I. C.: Spatial Modelling of Floodplain Inundation Combining Satellite Imagery and Elevation Models, in: MODSIM 2007 International Congress on Modelling and Simulation, edited by: Oxley, L. and Kulasiri, D., Modelling and Simulation Society of Australia and New Zealand, 1464–1470, 2007.
Powell, S. J., Letcher, R. A., and Croke, B. F. W.: Modelling floodplain inundation for environmental flows: Gwydir wetlands, Australia, Ecol. Model., 211, 350–362, https://doi.org/10.1016/j.ecolmodel.2007.09.013, 2008.
Queensland Government: Water Monitoring Portal, available at: https://www.dnrm.qld.gov.au/water/water-monitoring-and-data/portal, last access: 12 April 2016, 2015.
R Development Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, available at: http://www.R-project.org, last access: 12 May 2016, 2008.
Ramsar Convention Secretariat: The List of Wetlands of International Importance, available at: http://www.ramsar.org/library, last access: 12 May 2016, 2014.
Ren, S., Kingsford, R. T., and Thomas, R. F.: Modelling flow to and inundation of the Macquarie Marshes in arid Australia, Environmetrics, 21, 549–561, https://doi.org/10.1002/env.1002, 2010.
Robertson, A. I., Bunn, S. E., Boon, P. I., and Walker, K. F.: Sources, sinks and transformations of organic carbon in Australian floodplain rivers, Mar. Freshwater Res., 50, 813–829, 1999.
Sakamoto, T., Van Nguyen, N., Kotera, A., Ohno, H., Ishitsuka, N., and Yokozawa, M.: Detecting temporal changes in the extent of annual flooding within the Cambodia and the Vietnamese Mekong Delta from MODIS time-series imagery, Remote Sens. Environ., 109, 295–313, https://doi.org/10.1016/j.rse.2007.01.011, 2007.
Sampson, C. C., Smith, A. M., Bates, P. D., Neal, J. C., Alfieri, L., and Freer, J. E.: A high-resolution global flood hazard model, Water Resour. Res., 51, 7358–7381, https://doi.org/10.1002/2015WR016954, 2015.
Sánchez-Carrillo, S., Angeler, D. G., Sánchez-Andrés, R., Alvarez-Cobelas, M., and Garatuza-Payán, J.: Evapotranspiration in semi-arid wetlands: relationships between inundation and the macrophyte-cover:open-water ratio, Adv. Water Resour., 27, 643–655, https://doi.org/10.1016/j.advwatres.2004.02.018, 2004.
Shaikh, M., Green, D., and Cross, H.: A remote sensing approach to determine environmental flows for wetlands of the Lower Darling River, New South Wales, Australia, Int. J. Remote Sens., 22, 1737–1751, 2001.
Shmueli, G.: To Explain or to Predict?, Stat. Sci., 25, 289–310, https://doi.org/10.1214/10-STS330, 2010.
Shumway, R. H. and Stoffer, D. S.: Time Series Analysis and Its Applications: With R Examples, Springer, New York, 2006.
Sims, N. C., Warren, G., Overton, I. C., Austin, J., Gallant, J., King, D. J., Merrin, L. E., Donohue, R., McVicar, T. R., Hodgen, M. J., Penton, D., Chen, Y., Huang, C., and Cuddy, S.: RiM-FIM Floodplain Inundation Modelling for the Edward-Wakool, Lower Murrumbidgee and Lower Darling River Systems. Report prepared for the Murray–Darling Basin Authority, CSIRO Water for a Healthy Country Flagship, Canberra, 2014.
State Government Victoria: Water Monitoring, available at: http://data.water.vic.gov.au/monitoring.htm, last access: 12 April 2016, 2015.
Teferi, E., Uhlenbrook, S., Bewket, W., Wenninger, J., and Simane, B.: The use of remote sensing to quantify wetland loss in the Choke Mountain range, Upper Blue Nile basin, Ethiopia, Hydrol. Earth Syst. Sci., 14, 2415–2428, https://doi.org/10.5194/hess-14-2415-2010, 2010.
Timms, B. V: Waterbirds of the Saline Lakes of the Paroo, arid-zone Australia?: A review with special reference to diversity and conservation, Nat. Resour. Env. Iss., 15, 46, 8 pp., 2009.
Tockner, K., Pennetzdorfer, D., Reiner, N., Schiemer, F., and Ward, J. V.: Hydrological connectivity, and the exchange of organic matter and nutrients in a dynamic river-floodplain system (Danube, Austria), Freshwater Biol., 41, 521–535, https://doi.org/10.1046/j.1365-2427.1999.00399.x, 1999.
Tulbure, M. G. and Broich, M.: Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011, ISPRS J. Photogramm., 79, 44–52, https://doi.org/10.1016/j.isprsjprs.2013.01.010, 2013.
Tulbure, M. G., Broich, M., Stehman, S. V., and Kommareddy, A.: Surface water extent dynamics from three decades of seasonally continuous Landsat time series at subcontinental scale in a semi-arid region, Remote Sens. Environ., 178, 142–157, https://doi.org/10.1016/j.rse.2016.02.034, 2016.
Vaze, J., Viney, N., Stenson, M., Renzullo, L., Van Dijk, A., Dutta, D., Crosbie, R., Lerat, J., Penton, D., Vleeshouwer, J., Peeters, L., Teng, J., Kim, S., Hughes, J., Dawes, W., Zhang, Y., Leighton, B., Joehnk, K., Yang, A., Wang, B., Frost, A., Elmahdi, A., Smith, A., and Daamen, C.: The Australian Water Resource Assessment Modelling System (AWRA), in: 20th International Congress on Modelling and Simulation, Adelaide, Australia, 1–6 December 2013, available at: www.mssanz.org.au/modsim2013, last access: 12 May 2016, 2013.
Viney, N., Vaze, J., Crosbie, R., Wang, B., Dawes, W., and Frost, A.: AWRA-L v4.5: technical description of model algorithms and inputs, CSIRO, Australia, 2014.
Vörösmarty, B. C. J., Hoekstra, A. Y., Bunn, S. E., Conway, D., and Gupta, J.: What scale for water governance?, Science, 349, 478–479, https://doi.org/10.1126/science.349.6247.478-a, 2015.
Wagner, W., Dorigo, W., De Jeu, R., Fernandez, D., Benveniste, J., Haas, E., and Ertl, M.: Fusion of active and passive microwave observations to create an essential climate variable data record on soil moisture, in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume I-7, 2012 XXII ISPRS Congress, 25 August–1 September 2012, Melbourne, Australia, 2012.
Wagner, W., Dech, S. W., and Kuenzer, C.: Remote Sensing Time Series: Revealing Land Surface Dynamics, Springer, Cham, Switzerland, 2015.
Westra, T. and De Wulf, R. R.: Modelling yearly flooding extent of the Waza-Logone floodplain in northern Cameroon based on MODIS and rainfall data, Int. J. Remote Sens., 30, 5527–5548, https://doi.org/10.1080/01431160802672872, 2009.
Yamazaki, D., Kanae, S., Kim, H., and Oki, T.: A physically based description of floodplain inundation dynamics in a global river routing model, Water Resour. Res., 47, 1–21, https://doi.org/10.1029/2010WR009726, 2011.
Yan, K., Di Baldassarre, G., Solomatine, D. P., and Schumann, G. J. P.: A review of low-cost space-borne data for flood modelling: topography, flood extent and water level, Hydrol. Process., 29, 3368–3387, https://doi.org/10.1002/hyp.10449, 2015.
Ye, N., Walker, J. P., Guerschman, J., Ryu, D., and Gurney, R. J.: Standing water effect on soil moisture retrieval from L-band passive microwave observations, Remote Sens. Environ., 169, 232–242, https://doi.org/10.1016/j.rse.2015.08.013, 2015.
Zarfl, C., Lumsdon, A. E., Berlekamp, J., Tydecks, L., and Tockner, K.: A global boom in hydropower dam construction, Aquat. Sci., 77, 161–170, https://doi.org/10.1007/s00027-014-0377-0, 2015.
Zeileis A.: dynlm: Dynamic Linear Regression, R package version 0.3-3., available at: http://CRAN.R-project.org/package=dynlm, last access: 12 May 2016, 2014.
Zeileis, A. and Grothendieck, G.: zoo: S3 Infrastructure for Regular and Irregular Time, J. Stat. Softw., 14, 27 pp., 2005.
Zhao, X., Stein, A., and Chen, X.-L.: Monitoring the dynamics of wetland inundation by random sets on multi-temporal images, Remote Sens. Environ., 115, 2390–2401, https://doi.org/10.1016/j.rse.2011.05.002, 2011.
We statistically modeled surface water extent (SWE) and inundation dynamics from a unique Landsat-based time series (1986–2011) for Australia's Murray–Darling Basin as a function of river flow and spatially explicit time series of rainfall, evapotranspiration and soil moisture. We present a data-driven and transferable approach that allowed us to model SWE through periods of flooding and drying for 363 floodplain units and to identify local combinations of variables that drive SWE dynamics.
We statistically modeled surface water extent (SWE) and inundation dynamics from a unique...