Articles | Volume 25, issue 4
https://doi.org/10.5194/hess-25-1827-2021
© Author(s) 2021. 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-25-1827-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Apr 2021
Research article |
| 09 Apr 2021
| 09 Apr 2021
Field-scale soil moisture bridges the spatial-scale gap between drought monitoring and agricultural yields
Civil and Environmental Engineering Department, Princeton University, Princeton, NJ, USA
Sitian Xiong
School of Geography, Clark University, Worcester, MA, USA
Lyndon Estes
School of Geography, Clark University, Worcester, MA, USA
Niko Wanders
Department of Physical Geography, Faculty of Geosciences, Utrecht University, Utrecht, the Netherlands
Nathaniel W. Chaney
Department of Civil and Environmental Engineering, Duke University, Durham, NC, USA
Eric F. Wood
Civil and Environmental Engineering Department, Princeton University, Princeton, NJ, USA
Megan Konar
Civil and Environmental Engineering Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Kelly Caylor
Department of Geography, University of California, Santa Barbara, CA, USA
Bren School of Environmental Science and Management, University of California, Santa Barbara, CA, USA
Hylke E. Beck
Civil and Environmental Engineering Department, Princeton University, Princeton, NJ, USA
Nicolas Gatti
Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Tom Evans
School of Geography, Development and Environment, University of Arizona, Tucson, AZ, USA
Justin Sheffield
School of Geography and Environmental Science, University of Southampton, Southampton, UK
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Dapeng Feng, Hylke Beck, Kathryn Lawson, and Chaopeng Shen
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Hydrol. Earth Syst. Sci., 26, 3785–3803, https://doi.org/10.5194/hess-26-3785-2022, https://doi.org/10.5194/hess-26-3785-2022, 2022
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Hydrol. Earth Syst. Sci., 26, 3315–3336, https://doi.org/10.5194/hess-26-3315-2022, https://doi.org/10.5194/hess-26-3315-2022, 2022
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Nat. Hazards Earth Syst. Sci., 22, 2201–2217, https://doi.org/10.5194/nhess-22-2201-2022, https://doi.org/10.5194/nhess-22-2201-2022, 2022
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M. G. Ziliani, M. U. Altaf, B. Aragon, R. Houborg, T. E. Franz, Y. Lu, J. Sheffield, I. Hoteit, and M. F. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1045–1052, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, 2022
Marc F. P. Bierkens, Edwin H. Sutanudjaja, and Niko Wanders
Hydrol. Earth Syst. Sci., 25, 5859–5878, https://doi.org/10.5194/hess-25-5859-2021, https://doi.org/10.5194/hess-25-5859-2021, 2021
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Most rivers worldwide are ungauged, which hinders the sustainable management of water resources. Regionalisation methods use information from gauged rivers to estimate streamflow over ungauged ones. Through hydrological modelling, we assessed how the selection of precipitation products affects the performance of three regionalisation methods. We found that a precipitation product that provides the best results in hydrological modelling does not necessarily perform the best for regionalisation.
Nathaniel W. Chaney, Laura Torres-Rojas, Noemi Vergopolan, and Colby K. Fisher
Geosci. Model Dev., 14, 6813–6832, https://doi.org/10.5194/gmd-14-6813-2021, https://doi.org/10.5194/gmd-14-6813-2021, 2021
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Although there have been significant advances in river routing and sub-grid heterogeneity (i.e., tiling) schemes in Earth system models over the past decades, there has yet to be a concerted effort to couple these two concepts. This paper aims to bridge this gap through the development of a two-way coupling between tiling schemes and river networks in the HydroBlocks land surface model. The scheme is implemented and tested over a 1 arc degree domain in Oklahoma, United States.
Peter Uhe, Daniel Mitchell, Paul D. Bates, Nans Addor, Jeff Neal, and Hylke E. Beck
Geosci. Model Dev., 14, 4865–4890, https://doi.org/10.5194/gmd-14-4865-2021, https://doi.org/10.5194/gmd-14-4865-2021, 2021
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We present a cascade of models to compute high-resolution river flooding. This takes meteorological inputs, e.g., rainfall and temperature from observations or climate models, and takes them through a series of modeling steps. This is relevant to evaluating current day and future flood risk and impacts. The model framework uses global data sets, allowing it to be applied anywhere in the world.
Maria Magdalena Warter, Michael Bliss Singer, Mark O. Cuthbert, Dar Roberts, Kelly K. Caylor, Romy Sabathier, and John Stella
Hydrol. Earth Syst. Sci., 25, 3713–3729, https://doi.org/10.5194/hess-25-3713-2021, https://doi.org/10.5194/hess-25-3713-2021, 2021
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Intensified drying of soil and grassland vegetation is raising the impact of fire severity and extent in Southern California. While browned grassland is a common sight during the dry season, this study has shown that there is a pronounced shift in the timing of senescence, due to changing climate conditions favoring milder winter temperatures and increased precipitation variability. Vegetation may be limited in its ability to adapt to these shifts, as drought periods become more frequent.
Camelia-Eliza Telteu, Hannes Müller Schmied, Wim Thiery, Guoyong Leng, Peter Burek, Xingcai Liu, Julien Eric Stanislas Boulange, Lauren Seaby Andersen, Manolis Grillakis, Simon Newland Gosling, Yusuke Satoh, Oldrich Rakovec, Tobias Stacke, Jinfeng Chang, Niko Wanders, Harsh Lovekumar Shah, Tim Trautmann, Ganquan Mao, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Luis Samaniego, Yoshihide Wada, Vimal Mishra, Junguo Liu, Petra Döll, Fang Zhao, Anne Gädeke, Sam S. Rabin, and Florian Herz
Geosci. Model Dev., 14, 3843–3878, https://doi.org/10.5194/gmd-14-3843-2021, https://doi.org/10.5194/gmd-14-3843-2021, 2021
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We analyse water storage compartments, water flows, and human water use sectors included in 16 global water models that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b. We develop a standard writing style for the model equations. We conclude that even though hydrologic processes are often based on similar equations, in the end these equations have been adjusted, or the models have used different values for specific parameters or specific variables.
Yuting Yang, Tim R. McVicar, Dawen Yang, Yongqiang Zhang, Shilong Piao, Shushi Peng, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 25, 3411–3427, https://doi.org/10.5194/hess-25-3411-2021, https://doi.org/10.5194/hess-25-3411-2021, 2021
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This study developed an analytical ecohydrological model that considers three aspects of vegetation response to eCO2 (i.e., stomatal response, LAI response, and rooting depth response) to detect the impact of eCO2 on continental runoff over the past 3 decades globally. Our findings suggest a minor role of eCO2 on the global runoff changes, yet highlight the negative runoff–eCO2 response in semiarid and arid regions which may further threaten the limited water resource there.
Sarah F. Kew, Sjoukje Y. Philip, Mathias Hauser, Mike Hobbins, Niko Wanders, Geert Jan van Oldenborgh, Karin van der Wiel, Ted I. E. Veldkamp, Joyce Kimutai, Chris Funk, and Friederike E. L. Otto
Earth Syst. Dynam., 12, 17–35, https://doi.org/10.5194/esd-12-17-2021, https://doi.org/10.5194/esd-12-17-2021, 2021
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Motivated by the possible influence of rising temperatures, this study synthesises results from observations and climate models to explore trends (1900–2018) in eastern African (EA) drought measures. However, no discernible trends are found in annual soil moisture or precipitation. Positive trends in potential evaporation indicate that for irrigated regions more water is now required to counteract increased evaporation. Precipitation deficit is, however, the most useful indicator of EA drought.
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, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
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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.
Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Joanna A. Horemans, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Graham P. Weedon, Justin Sheffield, Flurin Babst, Iliusi Vega del Valle, Felicitas Suckow, Simon Martel, Mats Mahnken, Martin Gutsch, and Katja Frieler
Earth Syst. Sci. Data, 12, 1295–1320, https://doi.org/10.5194/essd-12-1295-2020, https://doi.org/10.5194/essd-12-1295-2020, 2020
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Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development in Europe.
Colby K. Fisher, Ming Pan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 24, 293–305, https://doi.org/10.5194/hess-24-293-2020, https://doi.org/10.5194/hess-24-293-2020, 2020
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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.
Sjoukje Philip, Sarah Sparrow, Sarah F. Kew, Karin van der Wiel, Niko Wanders, Roop Singh, Ahmadul Hassan, Khaled Mohammed, Hammad Javid, Karsten Haustein, Friederike E. L. Otto, Feyera Hirpa, Ruksana H. Rimi, A. K. M. Saiful Islam, David C. H. Wallom, and Geert Jan van Oldenborgh
Hydrol. Earth Syst. Sci., 23, 1409–1429, https://doi.org/10.5194/hess-23-1409-2019, https://doi.org/10.5194/hess-23-1409-2019, 2019
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In August 2017 Bangladesh faced one of its worst river flooding events in recent history. For the large Brahmaputra basin, using precipitation alone as a proxy for flooding might not be appropriate. In this paper we explicitly test this assumption by performing an attribution of both precipitation and discharge as a flooding-related measure to climate change. We find the change in risk to be of similar order of magnitude (between 1 and 2) for both the meteorological and hydrological approach.
Sanaa Hobeichi, Gab Abramowitz, Jason Evans, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 23, 851–870, https://doi.org/10.5194/hess-23-851-2019, https://doi.org/10.5194/hess-23-851-2019, 2019
Hylke E. Beck, Ming Pan, Tirthankar Roy, Graham P. Weedon, Florian Pappenberger, Albert I. J. M. van Dijk, George J. Huffman, Robert F. Adler, and Eric F. Wood
Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, https://doi.org/10.5194/hess-23-207-2019, 2019
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We conducted a comprehensive evaluation of 26 precipitation datasets for the US using the Stage-IV gauge-radar dataset as a reference. The best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for reporting times. Our findings can be used as a guide to choose the most suitable precipitation dataset for a particular application.
Sara Sadri, Eric F. Wood, and Ming Pan
Hydrol. Earth Syst. Sci., 22, 6611–6626, https://doi.org/10.5194/hess-22-6611-2018, https://doi.org/10.5194/hess-22-6611-2018, 2018
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Of particular interest to NASA's SMAP-based agricultural applications is a monitoring product that assesses near-surface soil moisture in terms of probability percentiles for dry and wet conditions. However, the short SMAP record length poses a statistical challenge for the meaningful assessment of its indices. This study presents initial insights about using SMAP Level 3 and Level 4 for monitoring drought and pluvial regions with a first application over the contiguous United States (CONUS).
Albert I. J. M. van Dijk, Jaap Schellekens, Marta Yebra, Hylke E. Beck, Luigi J. Renzullo, Albrecht Weerts, and Gennadii Donchyts
Hydrol. Earth Syst. Sci., 22, 4959–4980, https://doi.org/10.5194/hess-22-4959-2018, https://doi.org/10.5194/hess-22-4959-2018, 2018
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Evaporation from wetlands, lakes and irrigation areas needs to be measured to understand water scarcity. So far, this has only been possible for small regions. Here, we develop a solution that can be applied at a very high resolution globally by making use of satellite observations. Our results show that 16% of global water resources evaporate before reaching the ocean, mostly from surface water. Irrigation water use is less than 1% globally but is a very large water user in several dry basins.
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533, https://doi.org/10.5194/hess-22-4513-2018, https://doi.org/10.5194/hess-22-4513-2018, 2018
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Observing the amount of water evaporated in nature is not easy, and we need to combine accurate local measurements with estimates from satellites, more uncertain but covering larger areas. This is the main topic of our paper, in which local observations are compared with global land evaporation estimates, followed by a weighting of the global observations based on this comparison to attempt derive a more accurate evaporation product.
Edwin H. Sutanudjaja, Rens van Beek, Niko Wanders, Yoshihide Wada, Joyce H. C. Bosmans, Niels Drost, Ruud J. van der Ent, Inge E. M. de Graaf, Jannis M. Hoch, Kor de Jong, Derek Karssenberg, Patricia López López, Stefanie Peßenteiner, Oliver Schmitz, Menno W. Straatsma, Ekkamol Vannametee, Dominik Wisser, and Marc F. P. Bierkens
Geosci. Model Dev., 11, 2429–2453, https://doi.org/10.5194/gmd-11-2429-2018, https://doi.org/10.5194/gmd-11-2429-2018, 2018
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PCR-GLOBWB 2 is an integrated hydrology and water resource model that fully integrates water use simulation and consolidates all features that have been developed since PCR-GLOBWB 1 was introduced. PCR-GLOBWB 2 can have a global coverage at 5 arcmin resolution and supersedes PCR-GLOBWB 1, which has a resolution of 30 arcmin only. Comparing the 5 arcmin with 30 arcmin simulations using discharge data, we clearly find improvement in the model performance of the higher-resolution model.
Stephen Blenkinsop, Hayley J. Fowler, Renaud Barbero, Steven C. Chan, Selma B. Guerreiro, Elizabeth Kendon, Geert Lenderink, Elizabeth Lewis, Xiao-Feng Li, Seth Westra, Lisa Alexander, Richard P. Allan, Peter Berg, Robert J. H. Dunn, Marie Ekström, Jason P. Evans, Greg Holland, Richard Jones, Erik Kjellström, Albert Klein-Tank, Dennis Lettenmaier, Vimal Mishra, Andreas F. Prein, Justin Sheffield, and Mari R. Tye
Adv. Sci. Res., 15, 117–126, https://doi.org/10.5194/asr-15-117-2018, https://doi.org/10.5194/asr-15-117-2018, 2018
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Measurements of sub-daily (e.g. hourly) rainfall totals are essential if we are to understand short, intense bursts of rainfall that cause flash floods. We might expect the intensity of such events to increase in a warming climate but these are poorly realised in projections of future climate change. The INTENSE project is collating a global dataset of hourly rainfall measurements and linking with new developments in climate models to understand the characteristics and causes of these events.
Andreas Marx, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Niko Wanders, Matthias Zink, Eric F. Wood, Ming Pan, Justin Sheffield, and Luis Samaniego
Hydrol. Earth Syst. Sci., 22, 1017–1032, https://doi.org/10.5194/hess-22-1017-2018, https://doi.org/10.5194/hess-22-1017-2018, 2018
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Hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K). The multi-model ensemble results show that the change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean, while they increase in the Alpine and Northern regions. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. Adaptation should make use of change and uncertainty information.
Marit Van Tiel, Adriaan J. Teuling, Niko Wanders, Marc J. P. Vis, Kerstin Stahl, and Anne F. Van Loon
Hydrol. Earth Syst. Sci., 22, 463–485, https://doi.org/10.5194/hess-22-463-2018, https://doi.org/10.5194/hess-22-463-2018, 2018
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Glaciers are important hydrological reservoirs. Short-term variability in glacier melt and also glacier retreat can cause droughts in streamflow. In this study, we analyse the effect of glacier changes and different drought threshold approaches on future projections of streamflow droughts in glacierised catchments. We show that these different methodological options result in different drought projections and that these options can be used to study different aspects of streamflow droughts.
John Musau, Sopan Patil, Justin Sheffield, and Michael Marshall
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2017-123, https://doi.org/10.5194/esd-2017-123, 2018
Manuscript not accepted for further review
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Three decades LAI data indicates diverse and often non-stationary vegetation changes in East Africa. Significant increase in vegetation variance is indicated in most of the region which is positively correlated to the variance of climate anomalies. The vegetation resistance to short-term drought and its memory effect are mainly positive and significant with noteworthy variations across landcover types. Further analysis is required to separated human-induced and climate-caused vegetation changes.
Yu Zhang, Ming Pan, Justin Sheffield, Amanda L. Siemann, Colby K. Fisher, Miaoling Liang, Hylke E. Beck, Niko Wanders, Rosalyn F. MacCracken, Paul R. Houser, Tian Zhou, Dennis P. Lettenmaier, Rachel T. Pinker, Janice Bytheway, Christian D. Kummerow, and Eric F. Wood
Hydrol. Earth Syst. Sci., 22, 241–263, https://doi.org/10.5194/hess-22-241-2018, https://doi.org/10.5194/hess-22-241-2018, 2018
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A global data record for all four terrestrial water budget variables (precipitation, evapotranspiration, runoff, and total water storage change) at 0.5° resolution and monthly scale for the period of 1984–2010 is developed by optimally merging a series of remote sensing products, in situ measurements, land surface model outputs, and atmospheric reanalysis estimates and enforcing the mass balance of water. Initial validations show the data record is reliable for climate related analysis.
Guiomar Ruiz-Pérez, Julian Koch, Salvatore Manfreda, Kelly Caylor, and Félix Francés
Hydrol. Earth Syst. Sci., 21, 6235–6251, https://doi.org/10.5194/hess-21-6235-2017, https://doi.org/10.5194/hess-21-6235-2017, 2017
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Plants are shaping the landscape and controlling the hydrological cycle, particularly in arid and semi-arid ecosystems. Remote sensing data appears as an appealing source of information for vegetation monitoring, in particular in areas with a limited amount of available field data. Here, we present an example of how remote sensing data can be exploited in a data-scarce basin. We propose a mathematical methodology that can be used as a springboard for future applications.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
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This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
Luis Samaniego, Rohini Kumar, Stephan Thober, Oldrich Rakovec, Matthias Zink, Niko Wanders, Stephanie Eisner, Hannes Müller Schmied, Edwin H. Sutanudjaja, Kirsten Warrach-Sagi, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 4323–4346, https://doi.org/10.5194/hess-21-4323-2017, https://doi.org/10.5194/hess-21-4323-2017, 2017
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We inspect the state-of-the-art of several land surface (LSMs) and hydrologic models (HMs) and show that most do not have consistent and realistic parameter fields for land surface geophysical properties. We propose to use the multiscale parameter regionalization (MPR) technique to solve, at least partly, the scaling problem in LSMs/HMs. A general model protocol is presented to describe how MPR can be applied to a specific model.
Yoshihide Wada, Marc F. P. Bierkens, Ad de Roo, Paul A. Dirmeyer, James S. Famiglietti, Naota Hanasaki, Megan Konar, Junguo Liu, Hannes Müller Schmied, Taikan Oki, Yadu Pokhrel, Murugesu Sivapalan, Tara J. Troy, Albert I. J. M. van Dijk, Tim van Emmerik, Marjolein H. J. Van Huijgevoort, Henny A. J. Van Lanen, Charles J. Vörösmarty, Niko Wanders, and Howard Wheater
Hydrol. Earth Syst. Sci., 21, 4169–4193, https://doi.org/10.5194/hess-21-4169-2017, https://doi.org/10.5194/hess-21-4169-2017, 2017
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Rapidly increasing population and human activities have altered terrestrial water fluxes on an unprecedented scale. Awareness of potential water scarcity led to first global water resource assessments; however, few hydrological models considered the interaction between terrestrial water fluxes and human activities. Our contribution highlights the importance of human activities transforming the Earth's water cycle, and how hydrological models can include such influences in an integrated manner.
Niko Wanders, Anne F. Van Loon, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-512, https://doi.org/10.5194/hess-2017-512, 2017
Revised manuscript has not been submitted
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This paper investigates the similarities between frequently used drought indicators and how they should be used for global drought monitoring. We find that drought indicators that should monitor drought in the same hydrological domain show high discrepancy in their anomalies and thus drought detection. This shows that the current ways of monitoring drought events is not sufficient to fully capture the complexity of drought events and monitor the socio-economic impact of these large-scale events.
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017, https://doi.org/10.5194/hess-21-3879-2017, 2017
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We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
Emmy E. Stigter, Niko Wanders, Tuomo M. Saloranta, Joseph M. Shea, Marc F. P. Bierkens, and Walter W. Immerzeel
The Cryosphere, 11, 1647–1664, https://doi.org/10.5194/tc-11-1647-2017, https://doi.org/10.5194/tc-11-1647-2017, 2017
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
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The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Hylke E. Beck, Albert I. J. M. van Dijk, Ad de Roo, Emanuel Dutra, Gabriel Fink, Rene Orth, and Jaap Schellekens
Hydrol. Earth Syst. Sci., 21, 2881–2903, https://doi.org/10.5194/hess-21-2881-2017, https://doi.org/10.5194/hess-21-2881-2017, 2017
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Runoff measurements for 966 catchments around the globe were used to assess the quality of the daily runoff estimates of 10 hydrological models run as part of tier-1 of the eartH2Observe project. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
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Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
Di Tian, Eric F. Wood, and Xing Yuan
Hydrol. Earth Syst. Sci., 21, 1477–1490, https://doi.org/10.5194/hess-21-1477-2017, https://doi.org/10.5194/hess-21-1477-2017, 2017
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This study evaluated dynamic climate model sub-seasonal forecasts for important precipitation and temperature indices over the contiguous United States. The presence of active Madden-Julian Oscillation (MJO) events improved weekly mean precipitation forecast skill over most regions. Sub-seasonal forecast indices calculated from the daily forecast showed higher skill than temporally downscaled forecasts, suggesting the usefulness of the daily forecast for sub-seasonal hydrological forecasting.
Michael Marshall, Michael Norton-Griffiths, Harvey Herr, Richard Lamprey, Justin Sheffield, Tor Vagen, and Joseph Okotto-Okotto
Earth Syst. Dynam., 8, 55–73, https://doi.org/10.5194/esd-8-55-2017, https://doi.org/10.5194/esd-8-55-2017, 2017
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The transition of land from one cover type to another can adversely affect the Earth system. A growing body of research aims to map these transitions in space and time to better understand the impacts. Here we develop a statistical model that is parameterized by socio-ecological geospatial data and extensive aerial/ground surveys to visualize and interpret these transitions on an annual basis for 30 years in Kenya. Future work will use this method to project land suitability across Africa.
Hylke E. Beck, Albert I. J. M. van Dijk, Vincenzo Levizzani, Jaap Schellekens, Diego G. Miralles, Brecht Martens, and Ad de Roo
Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, https://doi.org/10.5194/hess-21-589-2017, 2017
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MSWEP (Multi-Source Weighted-Ensemble Precipitation) is a new global terrestrial precipitation dataset with a high 3-hourly temporal and 0.25° spatial resolution. The dataset is unique in that it takes advantage of a wide range of data sources, including gauge, satellite, and reanalysis data, to obtain the best possible precipitation estimates at global scale. The dataset outperforms existing gauge-adjusted precipitation datasets.
John Musau, Sopan Patil, Justin Sheffield, and Michael Marshall
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-502, https://doi.org/10.5194/hess-2016-502, 2016
Manuscript not accepted for further review
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An assessment of vegetation-climate relations over East Africa is presented. LAI trends in Southern Ethiopia through Central Kenya into Central Tanzania show persistent decrease. Precipitation exerts widespread positive forcing on vegetation. North Uganda shows high LAI increase. Positive vegetation feedback on precipitation is dominant while a stronger negative forcing on Tmin is shown. Vegetation-climate interactions show strong spatial dependence. Land cover types influence the interractions.
Anne F. Van Loon, Kerstin Stahl, Giuliano Di Baldassarre, Julian Clark, Sally Rangecroft, Niko Wanders, Tom Gleeson, Albert I. J. M. Van Dijk, Lena M. Tallaksen, Jamie Hannaford, Remko Uijlenhoet, Adriaan J. Teuling, David M. Hannah, Justin Sheffield, Mark Svoboda, Boud Verbeiren, Thorsten Wagener, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, https://doi.org/10.5194/hess-20-3631-2016, 2016
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In the Anthropocene, drought cannot be viewed as a natural hazard independent of people. Drought can be alleviated or made worse by human activities and drought impacts are dependent on a myriad of factors. In this paper, we identify research gaps and suggest a framework that will allow us to adequately analyse and manage drought in the Anthropocene. We need to focus on attribution of drought to different drivers, linking drought to its impacts, and feedbacks between drought and society.
Bart van den Hurk, Hyungjun Kim, Gerhard Krinner, Sonia I. Seneviratne, Chris Derksen, Taikan Oki, Hervé Douville, Jeanne Colin, Agnès Ducharne, Frederique Cheruy, Nicholas Viovy, Michael J. Puma, Yoshihide Wada, Weiping Li, Binghao Jia, Andrea Alessandri, Dave M. Lawrence, Graham P. Weedon, Richard Ellis, Stefan Hagemann, Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, and Justin Sheffield
Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, https://doi.org/10.5194/gmd-9-2809-2016, 2016
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This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
Patricia López López, Niko Wanders, Jaap Schellekens, Luigi J. Renzullo, Edwin H. Sutanudjaja, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci., 20, 3059–3076, https://doi.org/10.5194/hess-20-3059-2016, https://doi.org/10.5194/hess-20-3059-2016, 2016
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We perform a joint assimilation experiment of high-resolution satellite soil moisture and discharge observations in the Murrumbidgee River basin with a large-scale hydrological model. Additionally, we study the impact of high- and low-resolution meteorological forcing on the model performance. We show that the assimilation of high-resolution satellite soil moisture and discharge observations has a significant impact on discharge simulations and can bring them closer to locally calibrated models.
Wolfgang Buermann, Claudie Beaulieu, Bikash Parida, David Medvigy, George J. Collatz, Justin Sheffield, and Jorge L. Sarmiento
Biogeosciences, 13, 1597–1607, https://doi.org/10.5194/bg-13-1597-2016, https://doi.org/10.5194/bg-13-1597-2016, 2016
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Recent analyses of the global carbon budget found a substantial increase in the land sink in the late 1980s whose origin remains unknown. Consistent with this shift, we find that plant growth increased in the late 1980s especially in Eurasia and northern Africa. There, climatic constraints on plant growth have eased possibly due to linked climate modes in the North Atlantic. Better understanding of North Atlantic climate may be essential for more credible projections of the land carbon sink.
D. G. Miralles, C. Jiménez, M. Jung, D. Michel, A. Ershadi, M. F. McCabe, M. Hirschi, B. Martens, A. J. Dolman, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, https://doi.org/10.5194/hess-20-823-2016, 2016
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The WACMOS-ET project aims to advance the development of land evaporation estimates on global and regional scales. Evaluation of current evaporation data sets on the global scale showed that they manifest large dissimilarities during conditions of water stress and drought and deficiencies in the way evaporation is partitioned into several components. Different models perform better under different conditions, highlighting the potential for considering biome- or climate-specific model ensembles.
D. Michel, C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
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In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
S. Sadri, J. Kam, and J. Sheffield
Hydrol. Earth Syst. Sci., 20, 633–649, https://doi.org/10.5194/hess-20-633-2016, https://doi.org/10.5194/hess-20-633-2016, 2016
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Low flows are a critical part of the river flow regime but little is known about how they are changing in response to human influences and climate. We analyzed low flow records across the eastern US and identified sites that were minimally influenced by human activities. We found a general increasing trend in low flows across the northeast and decreasing trend across the southeast that are likely driven by changes in climate. The results have implications for how we manage our water resources.
M. F. McCabe, A. Ershadi, C. Jimenez, D. G. Miralles, D. Michel, and E. F. Wood
Geosci. Model Dev., 9, 283–305, https://doi.org/10.5194/gmd-9-283-2016, https://doi.org/10.5194/gmd-9-283-2016, 2016
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In an effort to develop a global terrestrial evaporation product, four models were forced using both a tower and grid-based data set. Comparisons against flux-tower observations from different biome and land cover types show considerable inter-model variability and sensitivity to forcing type. Results suggest that no single model is able to capture expected flux patterns and response. It is suggested that a multi-model ensemble is likely to provide a more stable long-term flux estimate.
W. W. Immerzeel, N. Wanders, A. F. Lutz, J. M. Shea, and M. F. P. Bierkens
Hydrol. Earth Syst. Sci., 19, 4673–4687, https://doi.org/10.5194/hess-19-4673-2015, https://doi.org/10.5194/hess-19-4673-2015, 2015
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The water resources of the upper Indus river basin (UIB) are important for millions of people, yet little is known about the rain and snow fall in the high-altitude regions because of the inaccessibility, the climatic complexity and the lack of observations. In this study we use mass balance of glaciers to reconstruct the amount of precipitation in the UIB and we conclude that this amount is much higher than previously thought.
W. Zhan, M. Pan, N. Wanders, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 4275–4291, https://doi.org/10.5194/hess-19-4275-2015, https://doi.org/10.5194/hess-19-4275-2015, 2015
T. J. Troy, M. Konar, V. Srinivasan, and S. Thompson
Hydrol. Earth Syst. Sci., 19, 3667–3679, https://doi.org/10.5194/hess-19-3667-2015, https://doi.org/10.5194/hess-19-3667-2015, 2015
N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015, https://doi.org/10.5194/hess-19-3239-2015, 2015
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Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.
N. Wanders and H. A. J. Van Lanen
Nat. Hazards Earth Syst. Sci., 15, 487–504, https://doi.org/10.5194/nhess-15-487-2015, https://doi.org/10.5194/nhess-15-487-2015, 2015
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In this study a conceptual hydrological model was forced by three general circulation models for the SRES A2 emission scenario and compared to the WATCH Forcing data set. Hydrological drought characteristics (duration and severity) were calculated on a global scale. It was found that both drought duration and severity will increase in multiple regions, which will lead to a higher impact of drought events, which urges water resources managers to timely design pro-active measures.
J. Elliott, C. Müller, D. Deryng, J. Chryssanthacopoulos, K. J. Boote, M. Büchner, I. Foster, M. Glotter, J. Heinke, T. Iizumi, R. C. Izaurralde, N. D. Mueller, D. K. Ray, C. Rosenzweig, A. C. Ruane, and J. Sheffield
Geosci. Model Dev., 8, 261–277, https://doi.org/10.5194/gmd-8-261-2015, https://doi.org/10.5194/gmd-8-261-2015, 2015
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We present and describe the Global Gridded Crop Model Intercomparison (GGCMI) project, an ongoing international effort to 1) validate global models of crop productivity, 2) improve models through detailed analysis of processes, and 3) assess the impacts of climate change on agriculture and food security. We present analysis of data inputs for the project, detailed protocols for conducting and evaluating simulation outputs, and example results.
N. Wanders, Y. Wada, and H. A. J. Van Lanen
Earth Syst. Dynam., 6, 1–15, https://doi.org/10.5194/esd-6-1-2015, https://doi.org/10.5194/esd-6-1-2015, 2015
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This study shows the impact of a changing climate on hydrological drought. The study illustrates that an alternative drought identification that considers adaptation to an altered hydrological regime has a substantial influence on the way in which drought impact is calculated. The obtained results show that an adaptive threshold approach is the way forward to study the impact of climate change on the identification and characterization of hydrological drought events.
K. Guan, S. P. Good, K. K. Caylor, H. Sato, E. F. Wood, and H. Li
Biogeosciences, 11, 6939–6954, https://doi.org/10.5194/bg-11-6939-2014, https://doi.org/10.5194/bg-11-6939-2014, 2014
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Climate change is expected to modify the way that rainfall arrives, namely the frequency and intensity of rainfall events and rainy season length. Yet, the quantification of the impact of these possible rainfall changes across large biomes is lacking. Our study fills this gap by developing a new modeling framework, applying it to continental Africa. We show that African ecosystems are highly sensitive to these rainfall variabilities, with esp. large sensitivity to changes in rainy season length.
N. Wanders, D. Karssenberg, A. de Roo, S. M. de Jong, and M. F. P. Bierkens
Hydrol. Earth Syst. Sci., 18, 2343–2357, https://doi.org/10.5194/hess-18-2343-2014, https://doi.org/10.5194/hess-18-2343-2014, 2014
S. Manfreda, L. Brocca, T. Moramarco, F. Melone, and J. Sheffield
Hydrol. Earth Syst. Sci., 18, 1199–1212, https://doi.org/10.5194/hess-18-1199-2014, https://doi.org/10.5194/hess-18-1199-2014, 2014
M. Pan and E. F. Wood
Hydrol. Earth Syst. Sci., 17, 4577–4588, https://doi.org/10.5194/hess-17-4577-2013, https://doi.org/10.5194/hess-17-4577-2013, 2013
M. Konar and K. K. Caylor
Hydrol. Earth Syst. Sci., 17, 3969–3982, https://doi.org/10.5194/hess-17-3969-2013, https://doi.org/10.5194/hess-17-3969-2013, 2013
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
M. Konar, Z. Hussein, N. Hanasaki, D. L. Mauzerall, and I. Rodriguez-Iturbe
Hydrol. Earth Syst. Sci., 17, 3219–3234, https://doi.org/10.5194/hess-17-3219-2013, https://doi.org/10.5194/hess-17-3219-2013, 2013
S. Shukla, J. Sheffield, E. F. Wood, and D. P. Lettenmaier
Hydrol. Earth Syst. Sci., 17, 2781–2796, https://doi.org/10.5194/hess-17-2781-2013, https://doi.org/10.5194/hess-17-2781-2013, 2013
H. A. J. Van Lanen, N. Wanders, L. M. Tallaksen, and A. F. Van Loon
Hydrol. Earth Syst. Sci., 17, 1715–1732, https://doi.org/10.5194/hess-17-1715-2013, https://doi.org/10.5194/hess-17-1715-2013, 2013
Related subject area
Subject: Water Resources Management | Techniques and Approaches: Modelling approaches
Spatially explicit assessment of water stress and potential mitigating solutions in a large water-limited basin: the Yellow River basin in China
A scalable and modular reservoir implementation for large-scale integrated hydrologic simulations
The interprovincial green water flow in China and its teleconnected effects on the social economy
Modeling hydropower operations at the scale of a power grid: a demand-based approach
Determining the threshold of issuing flash flood warnings based on people's response process simulation
Modeling water balance components of conifer species using the Noah-MP model in an eastern Mediterranean ecosystem
Assessment of upscaling methodologies for daily crop transpiration using sap flows and two-source energy balance models in almonds under different water statuses and production systems
Making a case for power-sensitive water modelling: a literature review
Developing water supply reservoir operating rules for large-scale hydrological modelling
An investigation of anthropogenic influences on hydrologic connectivity using model stress tests
The H2Ours game to explore water use, resources and sustainability: connecting issues in two landscapes in Indonesia
Drainage assessment of irrigation districts: on the precision and accuracy of four parsimonious models
Impact of reservoir evaporation on future water availability in north-eastern Brazil: a multi-scenario assessment
How economically and environmentally viable are multiple dams in the upper Cauvery Basin, India? A hydro-economic analysis using a landscape-based hydrological model
Leveraging a novel hybrid ensemble and optimal interpolation approach for enhanced streamflow and flood prediction
Value of seasonal flow forecasts for enhancing reservoir operation and drought management in South Korea
Optimising Ensemble Streamflow Predictions with Bias-Correction and Data Assimilation Techniques
Extracting Spatiotemporal Flood Information from News Texts Using Machine Learning for a National Dataset in China
Can adaptations of crop and soil management prevent yield losses during water scarcity? – A modelling study
A generalised ecohydrological landscape classification for assessing ecosystem risk in Australia due to an altering water regime
Process-based three-layer synergistic optimal-allocation model for complex water resource systems considering reclaimed water
Joint optimal operation of the South-to-North Water Diversion Project considering the evenness of water deficit
Employing the generalized Pareto distribution to analyze extreme rainfall events on consecutive rainy days in Thailand's Chi watershed: implications for flood management
How to account for irrigation withdrawals in a watershed model
Inferring reservoir filling strategies under limited-data-availability conditions using hydrological modeling and Earth observations: the case of the Grand Ethiopian Renaissance Dam (GERD)
Evaluating an Earth system model from a water user perspective
The precision of satellite-based net irrigation quantification in the Indus and Ganges basins
Developing a Bayesian network model for understanding river catchment resilience under future change scenarios
Quantifying the trade-offs in re-operating dams for the environment in the Lower Volta River
Dynamically coupling system dynamics and SWAT+ models using Tinamït: application of modular tools for coupled human–water system models
Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes
Cooperation in a transboundary river basin: a large-scale socio-hydrological model of the Eastern Nile
Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts
An improved model of shade-affected stream temperature in Soil & Water Assessment Tool
Seasonal forecasting of snow resources at Alpine sites
Operationalizing equity in multipurpose water systems
Evaluation of a new observationally based channel parameterization for the National Water Model
High-resolution drought simulations and comparison to soil moisture observations in Germany
Cooperation under conflict: participatory hydrological modeling for science policy dialogues for the Aculeo Lake
Socio-hydrological modeling of the tradeoff between flood control and hydropower provided by the Columbia River Treaty
Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP
A system dynamic model to quantify the impacts of water resources allocation on water–energy–food–society (WEFS) nexus
Net irrigation requirement under different climate scenarios using AquaCrop over Europe
The role of multi-criteria decision analysis in a transdisciplinary process: co-developing a flood forecasting system in western Africa
Unfolding the relationship between seasonal forecast skill and value in hydropower production: a global analysis
Drought impact links to meteorological drought indicators and predictability in Spain
Opportunities for seasonal forecasting to support water management outside the tropics
Probabilistic modelling of the inherent field-level pesticide pollution risk in a small drinking water catchment using spatial Bayesian belief networks
Are maps of nitrate reduction in groundwater altered by climate and land use changes?
Historical simulation of maize water footprints with a new global gridded crop model ACEA
Weibin Zhang, Xining Zhao, Xuerui Gao, Wei Liang, Junyi Li, and Baoqing Zhang
Hydrol. Earth Syst. Sci., 29, 507–524, https://doi.org/10.5194/hess-29-507-2025, https://doi.org/10.5194/hess-29-507-2025, 2025
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The Yellow River basin shows worsening water stress indicators (WSIs) over 1965‒2020. Water withdrawal is the main factor driving WSI before 2000, balanced by water availability. Local water yield and upstream flows are key drivers of sub-basin water availability. Water demand is expected to rise by 6.5 % in the 2030s, creating an 8.36 km³ surface water deficit. Enhanced irrigation efficiency can cut this deficit by 25 %, maintaining the stress level but worsening it for 44.9% of the population.
Benjamin D. West, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 29, 245–259, https://doi.org/10.5194/hess-29-245-2025, https://doi.org/10.5194/hess-29-245-2025, 2025
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This article describes the addition of reservoirs to the hydrologic model ParFlow. ParFlow is particularly good at helping us understand some of the broader drivers behind different parts of the water cycle. By having reservoirs in such a model, we hope to be able to better understand both our impacts on the environment and how to adjust our management of reservoirs to changing conditions.
Shan Sang, Yan Li, Chengcheng Hou, Shuangshuang Zi, and Huiqing Lin
Hydrol. Earth Syst. Sci., 29, 67–84, https://doi.org/10.5194/hess-29-67-2025, https://doi.org/10.5194/hess-29-67-2025, 2025
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Green water exchanges between each province in China form an interconnected flow network and have substantial socioeconomic values. Green water flow and its teleconnected socioeconomic effects should be considered in water resource management in addition to blue water.
Laure Baratgin, Jan Polcher, Patrice Dumas, and Philippe Quirion
Hydrol. Earth Syst. Sci., 28, 5479–5509, https://doi.org/10.5194/hess-28-5479-2024, https://doi.org/10.5194/hess-28-5479-2024, 2024
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Hydrological modeling is valuable for estimating the potential impact of climate change on hydropower generation. This study presents a comprehensive approach to modeling the management of hydroelectric reservoirs in hydrological models. The total power grid demand for hydropower is distributed to the various power plants to compute their release. The method is tested on the French national power grid, and it is demonstrated that it successfully reproduces the observed behavior of reservoirs.
Ruikang Zhang, Dedi Liu, Lihua Xiong, Jie Chen, Hua Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 28, 5229–5247, https://doi.org/10.5194/hess-28-5229-2024, https://doi.org/10.5194/hess-28-5229-2024, 2024
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Flash flood warnings cannot be effective without people’s responses to them. We propose a method to determine the threshold of issuing warnings based on a people’s response process simulation. The results show that adjusting the warning threshold according to people’s tolerance levels to the failed warnings can improve warning effectiveness, but the prerequisite is to increase forecasting accuracy and decrease forecasting variance.
Mohsen Amini Fasakhodi, Hakan Djuma, Ioannis Sofokleous, Marinos Eliades, and Adriana Bruggeman
Hydrol. Earth Syst. Sci., 28, 5209–5227, https://doi.org/10.5194/hess-28-5209-2024, https://doi.org/10.5194/hess-28-5209-2024, 2024
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This study examined the water use of pine and cypress trees in a semiarid Mediterranean forest environment. We applied a widely used land surface model (Noah-MP) to simulate the water balance of the ecosystem. We found good modeling results for soil moisture. However, the model underestimated the transpiration of the trees during the dry summer months. These findings indicate that more research is needed to improve the modeling of ecosystem responses to climate and land use change.
Manuel Quintanilla-Albornoz, Xavier Miarnau, Ana Pelechá, Héctor Nieto, and Joaquim Bellvert
Hydrol. Earth Syst. Sci., 28, 4797–4818, https://doi.org/10.5194/hess-28-4797-2024, https://doi.org/10.5194/hess-28-4797-2024, 2024
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Remote sensing can be a helpful tool for monitoring crop transpiration (T) for agricultural water management. Since remote sensing provides instantaneous data, upscaling techniques are required to estimate T on a daily scale. This study assesses optimal image acquisition times and four upscaling approaches to estimate daily T. The results indicate that the main errors derive from measurement time and water stress levels, which can be mitigated by choosing a proper upscaling approach.
Rozemarijn ter Horst, Rossella Alba, Jeroen Vos, Maria Rusca, Jonatan Godinez-Madrigal, Lucie V. Babel, Gert Jan Veldwisch, Jean-Philippe Venot, Bruno Bonté, David W. Walker, and Tobias Krueger
Hydrol. Earth Syst. Sci., 28, 4157–4186, https://doi.org/10.5194/hess-28-4157-2024, https://doi.org/10.5194/hess-28-4157-2024, 2024
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The exact power of models often remains hidden, especially when neutrality is claimed. Our review of 61 scientific articles shows that in the scientific literature little attention is given to the power of water models to influence development processes and outcomes. However, there is a lot to learn from those who are openly reflexive. Based on lessons from the review, we call for power-sensitive modelling, which means that people are critical about how models are made and with what effects.
Saskia Salwey, Gemma Coxon, Francesca Pianosi, Rosanna Lane, Chris Hutton, Michael Bliss Singer, Hilary McMillan, and Jim Freer
Hydrol. Earth Syst. Sci., 28, 4203–4218, https://doi.org/10.5194/hess-28-4203-2024, https://doi.org/10.5194/hess-28-4203-2024, 2024
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Reservoirs are essential for water resource management and can significantly impact downstream flow. However, representing reservoirs in hydrological models can be challenging, particularly across large scales. We design a new and simple method for simulating river flow downstream of water supply reservoirs using only open-access data. We demonstrate the approach in 264 reservoir catchments across Great Britain, where we can significantly improve the simulation of reservoir-impacted flow.
Amelie Herzog, Jost Hellwig, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 28, 4065–4083, https://doi.org/10.5194/hess-28-4065-2024, https://doi.org/10.5194/hess-28-4065-2024, 2024
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Surface water–groundwater interaction can vary along a river. This study used a groundwater model that reproduced relative observed longitudinal and vertical connectivity patterns in the river network to assess the system's response to imposed stress tests. For the case study, imposed groundwater abstraction appears to influence connectivity relatively more than altered recharge, but a quantification of absolute exchange flows will require further model improvements.
Lisa Tanika, Rika Ratna Sari, Arief Lukman Hakim, Meine van Noordwijk, Marielos Peña-Claros, Beria Leimona, Edi Purwanto, and Erika N. Speelman
Hydrol. Earth Syst. Sci., 28, 3807–3835, https://doi.org/10.5194/hess-28-3807-2024, https://doi.org/10.5194/hess-28-3807-2024, 2024
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The H2Ours game is designed to facilitate knowledge transfer and sharing among stakeholders to trigger commitment and collaborative action to restore hydrological conditions. The adaptability of the H2Ours game was proven in two different landscapes: groundwater recharge in upper to middle sub-watersheds with (over)use of water in the lowland zone and a peatland with drainage, rewetting, oil palm conversion and fire as issues. The game evaluation shows that the H2Ours game meets its purpose.
Pierre Laluet, Luis Olivera-Guerra, Víctor Altés, Vincent Rivalland, Alexis Jeantet, Julien Tournebize, Omar Cenobio-Cruz, Anaïs Barella-Ortiz, Pere Quintana-Seguí, Josep Maria Villar, and Olivier Merlin
Hydrol. Earth Syst. Sci., 28, 3695–3716, https://doi.org/10.5194/hess-28-3695-2024, https://doi.org/10.5194/hess-28-3695-2024, 2024
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Monitoring agricultural drainage flow in irrigated areas is key to water and soil management. In this paper, four simple drainage models are evaluated on two irrigated sub-basins where drainage flow is measured daily. The evaluation of their precision shows that they simulate drainage very well when calibrated with drainage data and that one of them is slightly better. The evaluation of their accuracy shows that only one model can provide rough drainage estimates without calibration data.
Gláuber Pontes Rodrigues, Arlena Brosinsky, Ítalo Sampaio Rodrigues, George Leite Mamede, and José Carlos de Araújo
Hydrol. Earth Syst. Sci., 28, 3243–3260, https://doi.org/10.5194/hess-28-3243-2024, https://doi.org/10.5194/hess-28-3243-2024, 2024
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The research focuses on a 4-million-inhabitant tropical region supplied by a network of open-water reservoirs where the dry season lasts for 8 months (Jun−Dec). We analysed the impact of four climate change scenarios on the evaporation rate and the associated availability (water yield distributed per year). The worst-case scenario shows that by the end of the century (2071−2099), the evaporation rate in the dry season could increase by 6 %, which would reduce stored water by about 80 %.
Anjana Ekka, Yong Jiang, Saket Pande, and Pieter van der Zaag
Hydrol. Earth Syst. Sci., 28, 3219–3241, https://doi.org/10.5194/hess-28-3219-2024, https://doi.org/10.5194/hess-28-3219-2024, 2024
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For the first time, we analyse the economic and ecological performance of existing multiple big reservoirs on a daily timescale for a major river basin (upper Cauvery) in India, where pre-intervention data were not available but where there are increasing calls for such assessments. Results show that smaller reservoirs on smaller streams that maximize the economic value of stored water are better for the basin economy and the environment. The approach can help to prioritize dam removals.
Mohamad El Gharamti, Arezoo Rafieeinasab, and James L. McCreight
Hydrol. Earth Syst. Sci., 28, 3133–3159, https://doi.org/10.5194/hess-28-3133-2024, https://doi.org/10.5194/hess-28-3133-2024, 2024
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This study introduces a hybrid data assimilation scheme for precise streamflow predictions during intense rainfall and hurricanes. Tested in real events, it outperforms traditional methods by up to 50 %, utilizing ensemble and climatological background covariances. The adaptive algorithm ensures reliability with a small ensemble, offering improved forecasts up to 18 h in advance, marking a significant advancement in flood prediction capabilities.
Yongshin Lee, Andres Peñuela, Francesca Pianosi, and Miguel Angel Rico-Ramirez
EGUsphere, https://doi.org/10.5194/egusphere-2024-1985, https://doi.org/10.5194/egusphere-2024-1985, 2024
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This study assesses the value of Seasonal Flow Forecasts (SFFs) in informing decision-making for drought management in South Korea and introduces a novel method for assessing value benchmarked against historical operations. Our results show the importance of considering flow forecast uncertainty in reservoir operations. But the difference in value between SFFs and Ensemble Streamflow Prediction is negligible. The method for selecting a compromise release schedule is a key control of the value.
Maliko Tanguy, Michael Eastman, Amulya Chevuturi, Eugene Magee, Elizabeth Cooper, Robert H. B. Johnson, Katie Facer-Childs, and Jamie Hannaford
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-179, https://doi.org/10.5194/hess-2024-179, 2024
Revised manuscript accepted for HESS
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Our research compares two techniques, Bias-Correction (BC) and Data Assimilation (DA), for improving river flow forecasts across 316 UK catchments. BC, which corrects errors post-simulation, showed broad improvements, while DA, adjusting model states pre-forecast, excelled in specific conditions like snowmelt and high base flows. Each method's unique strengths suit different scenarios. These insights can enhance forecasting systems, offering reliable and user-friendly hydrological predictions.
Shengnan Fu, David M. Schultz, Heng Lyu, Zhonghua Zheng, and Chi Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-146, https://doi.org/10.5194/hess-2024-146, 2024
Revised manuscript accepted for HESS
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To address the lack of county-level flood dataset in China, we used machine learning techniques to accurately identify flood events and locations from news reports. This dataset offers crucial insights into the spatiotemporal distribution of urban flooding from 2000 to 2022, highlighting increases in flood occurrences and identifying key vulnerable areas. These findings are vital for enhancing urban planning in China, aiming to mitigate the impact of future floods.
Malve Heinz, Maria Eliza Turek, Bettina Schaefli, Andreas Keiser, and Annelie Holzkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-1201, https://doi.org/10.5194/egusphere-2024-1201, 2024
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Potato farmers in Switzerland are facing drier conditions and water restrictions. We explored how improving soil health and planting early maturing potato varieties might help to adapt. Using a computer model, we simulated potato yields and irrigation water needs under water scarcity. Our results show that earlier maturing potato varieties reduce the reliance on irrigation but result in lower yields. However, improving soil health can significantly reduce yield losses.
Alexander Herr, Linda E. Merrin, Patrick J. Mitchell, Anthony P. O'Grady, Kate L. Holland, Richard E. Mount, David A. Post, Chris R. Pavey, and Ashley D. Sparrow
Hydrol. Earth Syst. Sci., 28, 1957–1979, https://doi.org/10.5194/hess-28-1957-2024, https://doi.org/10.5194/hess-28-1957-2024, 2024
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We develop an ecohydrological classification for regions with limited hydrological records. It provides causal links of landscape features and their water requirement. The classification is an essential framework for modelling the impact of future coal resource developments via water on the features. A rule set combines diverse data with prioritisation, resulting in a transparent, repeatable and adjustable approach. We show examples of linking ecohydrology with environmental impacts.
Jing Liu, Yue-Ping Xu, Wei Zhang, Shiwu Wang, and Siwei Chen
Hydrol. Earth Syst. Sci., 28, 1325–1350, https://doi.org/10.5194/hess-28-1325-2024, https://doi.org/10.5194/hess-28-1325-2024, 2024
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Applying optimal water allocation models to simultaneously enable economic benefits, water preferences, and environmental demands at different decision levels, timescales, and regions is a challenge. In this study, a process-based three-layer synergistic optimal-allocation model (PTSOA) is established to achieve these goals. Reused, reclaimed water is also coupled to capture environmentally friendly solutions. Network analysis was introduced to reduce competition among different stakeholders.
Bing-Yi Zhou, Guo-Hua Fang, Xin Li, Jian Zhou, and Hua-Yu Zhong
Hydrol. Earth Syst. Sci., 28, 817–832, https://doi.org/10.5194/hess-28-817-2024, https://doi.org/10.5194/hess-28-817-2024, 2024
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The current unreasonable inter-basin water transfer operation leads to the problem of spatial and temporal imbalances in water allocation. This paper defines a water deficit evenness index and incorporates it into a joint optimization model for the Jiangsu section of the South-to-North Water Diversion Project considering ecology and economy. At the same time, the lake storage capacity performs well, and the water transfer efficiency of the river is significantly improved.
Tossapol Phoophiwfa, Prapawan Chomphuwiset, Thanawan Prahadchai, Jeong-Soo Park, Arthit Apichottanakul, Watchara Theppang, and Piyapatr Busababodhin
Hydrol. Earth Syst. Sci., 28, 801–816, https://doi.org/10.5194/hess-28-801-2024, https://doi.org/10.5194/hess-28-801-2024, 2024
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This study examines the impact of extreme rainfall events on flood risk management in Thailand's Chi watershed. By analyzing historical data, we identified regions, notably Udon Thani and Chaiyaphum, with a high risk of flash flooding. To aid in flood risk assessment, visual maps were created. The study underscores the importance of preparing for extreme rainfall events, particularly in the context of climate change, to effectively mitigate potential flood damage.
Elisabeth Brochet, Youen Grusson, Sabine Sauvage, Ludovic Lhuissier, and Valérie Demarez
Hydrol. Earth Syst. Sci., 28, 49–64, https://doi.org/10.5194/hess-28-49-2024, https://doi.org/10.5194/hess-28-49-2024, 2024
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This study aims to take into account irrigation withdrawals in a watershed model. The model we used combines agriculture and hydrological modeling. Two different crop models were compared, the first based on air temperature and the second based on Sentinel-2 satellite data. Results show that including remote sensing data leads to better emergence dates. Both methods allow us to simulate the daily irrigation withdrawals and downstream flow with a good accuracy, especially during low-flow periods.
Awad M. Ali, Lieke A. Melsen, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 27, 4057–4086, https://doi.org/10.5194/hess-27-4057-2023, https://doi.org/10.5194/hess-27-4057-2023, 2023
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Using a new approach based on a combination of modeling and Earth observation, useful information about the filling of the Grand Ethiopian Renaissance Dam can be obtained with limited data and proper rainfall selection. While the monthly streamflow into Sudan has decreased significantly (1.2 × 109–5 × 109 m3) with respect to the non-dam scenario, the negative impact has been masked due to higher-than-average rainfall. We reveal that the dam will need 3–5 more years to complete filling.
Mari R. Tye, Ming Ge, Jadwiga H. Richter, Ethan D. Gutmann, Allyson Rugg, Cindy L. Bruyère, Sue Ellen Haupt, Flavio Lehner, Rachel McCrary, Andrew J. Newman, and Andrew Wood
EGUsphere, https://doi.org/10.5194/egusphere-2023-2326, https://doi.org/10.5194/egusphere-2023-2326, 2023
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There is a perceived mismatch between the spatial scales that global climate models can produce data and that needed for water management decisions. However, poor communication of specific metrics relevant to local decisions is also a problem. We identified a potential set of water use decision metrics to assess their credibility in the Community Earth System Model v2 (CESM2). CESM2 can reliably reproduce many of these metrics and shows potential to support long-range water resource decisions.
Søren J. Kragh, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 27, 2463–2478, https://doi.org/10.5194/hess-27-2463-2023, https://doi.org/10.5194/hess-27-2463-2023, 2023
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This study investigates the precision of irrigation estimates from a global hotspot of unsustainable irrigation practice, the Indus and Ganges basins. We show that irrigation water use can be estimated with high precision by comparing satellite and rainfed hydrological model estimates of evapotranspiration. We believe that our work can support sustainable water resource management, as it addresses the uncertainty of a key component of the water balance that remains challenging to quantify.
Kerr J. Adams, Christopher A. J. Macleod, Marc J. Metzger, Nicola Melville, Rachel C. Helliwell, Jim Pritchard, and Miriam Glendell
Hydrol. Earth Syst. Sci., 27, 2205–2225, https://doi.org/10.5194/hess-27-2205-2023, https://doi.org/10.5194/hess-27-2205-2023, 2023
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We applied participatory methods to create a hybrid equation-based Bayesian network (BN) model to increase stakeholder understanding of catchment-scale resilience to the impacts of both climatic and socio-economic stressors to a 2050 time horizon. Our holistic systems-thinking approach enabled stakeholders to gain new perspectives on how future scenarios may influence their specific sectors and how their sector impacted other sectors and environmental conditions within the catchment system.
Afua Owusu, Jazmin Zatarain Salazar, Marloes Mul, Pieter van der Zaag, and Jill Slinger
Hydrol. Earth Syst. Sci., 27, 2001–2017, https://doi.org/10.5194/hess-27-2001-2023, https://doi.org/10.5194/hess-27-2001-2023, 2023
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The construction of two dams in the Lower Volta River, Ghana, adversely affected downstream riverine ecosystems and communities. In contrast, Ghana has enjoyed vast economic benefits from the dams. Herein lies the challenge; there exists a trade-off between water for river ecosystems and water for anthropogenic water demands such hydropower. In this study, we quantify these trade-offs and show that there is room for providing environmental flows under current and future climatic conditions.
Joel Z. Harms, Julien J. Malard-Adam, Jan F. Adamowski, Ashutosh Sharma, and Albert Nkwasa
Hydrol. Earth Syst. Sci., 27, 1683–1693, https://doi.org/10.5194/hess-27-1683-2023, https://doi.org/10.5194/hess-27-1683-2023, 2023
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To facilitate the meaningful participation of stakeholders in water management, model choice is crucial. We show how system dynamics models (SDMs), which are very visual and stakeholder-friendly, can be automatically combined with physically based hydrological models that may be more appropriate for modelling the water processes of a human–water system. This allows building participatory SDMs with stakeholders and delegating hydrological components to an external hydrological model.
Erhu Du, Feng Wu, Hao Jiang, Naliang Guo, Yong Tian, and Chunmiao Zheng
Hydrol. Earth Syst. Sci., 27, 1607–1626, https://doi.org/10.5194/hess-27-1607-2023, https://doi.org/10.5194/hess-27-1607-2023, 2023
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This study develops an integrated socio-hydrological modeling framework that can simulate the entire flood management processes, including flood inundation, flood management policies, public responses, and evacuation activities. The model is able to holistically examine flood evacuation performance under the joint impacts of hydrological conditions, management policies (i.e., shelter location distribution), and human behaviors (i.e., evacuation preparation time and route-searching strategy).
Mohammad Ghoreishi, Amin Elshorbagy, Saman Razavi, Günter Blöschl, Murugesu Sivapalan, and Ahmed Abdelkader
Hydrol. Earth Syst. Sci., 27, 1201–1219, https://doi.org/10.5194/hess-27-1201-2023, https://doi.org/10.5194/hess-27-1201-2023, 2023
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The study proposes a quantitative model of the willingness to cooperate in the Eastern Nile River basin. Our results suggest that the 2008 food crisis may account for Sudan recovering its willingness to cooperate with Ethiopia. Long-term lack of trust among the riparian countries may have reduced basin-wide cooperation. The model can be used to explore the effects of changes in future dam operations and other management decisions on the emergence of basin cooperation.
Richard Laugesen, Mark Thyer, David McInerney, and Dmitri Kavetski
Hydrol. Earth Syst. Sci., 27, 873–893, https://doi.org/10.5194/hess-27-873-2023, https://doi.org/10.5194/hess-27-873-2023, 2023
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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
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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
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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
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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
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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
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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
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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
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Equitable sharing of benefits is key to successful cooperation in transboundary water resource management. However, external changes can shift the split of benefits and shifts in the preferences regarding how an actor’s benefits compare to the other’s benefits. To understand how these changes can impact the robustness of cooperative agreements, we develop a socio-hydrological system dynamics model of the benefit sharing provision of the Columbia River Treaty and assess a series of scenarios.
Sara Modanesi, Christian Massari, Michel Bechtold, Hans Lievens, Angelica Tarpanelli, Luca Brocca, Luca Zappa, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 4685–4706, https://doi.org/10.5194/hess-26-4685-2022, https://doi.org/10.5194/hess-26-4685-2022, 2022
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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
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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
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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
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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
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To fully realize the potential of seasonal streamflow forecasts in the hydropower industry, we need to understand the relationship between reservoir design specifications, forecast skill, and value. Here, we rely on realistic forecasts and simulated hydropower operations for 753 dams worldwide to unfold such relationship. Our analysis shows how forecast skill affects hydropower production, what type of dams are most likely to benefit from seasonal forecasts, and where these dams are located.
Herminia Torelló-Sentelles and Christian L. E. Franzke
Hydrol. Earth Syst. Sci., 26, 1821–1844, https://doi.org/10.5194/hess-26-1821-2022, https://doi.org/10.5194/hess-26-1821-2022, 2022
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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
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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
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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
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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
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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.
Cited articles
Adegoke, J. O. and Carleton, A. M.: Relations between Soil Moisture and
Satellite Vegetation Indices in the U.S. Corn Belt, J. Hydrometeorol., 3, 395–405, https://doi.org/10.1175/1525-7541(2002)003<0395:rbsmas>2.0.co;2, 2002. a
Aghighi, H., Azadbakht, M., Ashourloo, D., Shahrabi, H. S., and Radiom, S.: Machine Learning Regression Techniques for the Silage Maize Yield Prediction Using Time-Series Images of Landsat 8 OLI, IEEE J. Sel. Top. Appl., 11, 4563–4577, https://doi.org/10.1109/jstars.2018.2823361, 2018. a
Archer, K. J. and Kimes, R. V.: Empirical characterization of random forest variable importance measures, Comput. Stat. Data An., 52, 2249–2260, https://doi.org/10.1016/j.csda.2007.08.015, 2008. a, b
Azzari, G., Jain, M., and Lobell, D. B.: Towards fine resolution global maps of crop yields: Testing multiple methods and satellites in three countries, Remote Sens. Environ., 202, 129–141, https://doi.org/10.1016/j.rse.2017.04.014, 2017. a, b
Baccini, A., Friedl, M. A., Woodcock, C. E., and Warbington, R.: Forest biomass estimation over regional scales using multisource data, Geophys. Res. Lett., 31, L10501, https://doi.org/10.1029/2004gl019782, 2004. a
Bachmair, S., Svensson, C., Hannaford, J., Barker, L. J., and Stahl, K.: A quantitative analysis to objectively appraise drought indicators and model drought impacts, Hydrol. Earth Syst. Sci., 20, 2589–2609, https://doi.org/10.5194/hess-20-2589-2016, 2016. a
Bank, T. W.: Global Risk Data Platform: Gross Domestic Product. United Nations Environment Programme, available at: http://preview.grid.unep.ch/ (last access: 10 June 2019), 2012. a
Beck, H. E., Pan, M., Miralles, D. G., Reichle, R. H., Dorigo, W. A., Hahn,
S., Sheffield, J., Karthikeyan, L., Balsamo, G., Parinussa, R. M., van Dijk,
A. I. J. M., Du, J., Kimball, J. S., Vergopolan, N., and Wood, E. F.:
Evaluation of 18 satellite- and model-based soil moisture products using in
situ measurements from 826 sensors, Hydrol. Earth Syst. Sci., 25, 17–40,
https://doi.org/10.5194/hess-25-17-2021, 2021. a
Berg, A., Findell, K., Lintner, B., Giannini, A., Seneviratne, S. I., van den Hurk, B., Lorenz, R., Pitman, A., Hagemann, S., Meier, A., Cheruy, F., Ducharne, A., Malyshev, S., and Milly, P. C. D.: Land–atmosphere feedbacks amplify aridity increase over land under global warming, Nat. Clim. Change, 6, 869–874, https://doi.org/10.1038/nclimate3029, 2016. a
Beza, E., Silva, J. V., Kooistra, L., and Reidsma, P.: Review of yield gap explaining factors and opportunities for alternative data collection approaches, Eur. J. Agron., 82, 206–222, https://doi.org/10.1016/j.eja.2016.06.016, 2017. a
Bierkens, M. F. P., Bell, V. A., Burek, P., Chaney, N., Condon, L. E., David, C. H., de Roo, A., Döll, P., Drost, N., Famiglietti, J. S., Flörke, M., Gochis, D. J., Houser, P., Hut, R., Keune, J., Kollet, S., Maxwell, R. M., Reager, J. T., Samaniego, L., Sudicky, E., Sutanudjaja, E. H., van de Giesen, N., Winsemius, H., and Wood, E. F.: Hyper-resolution global hydrological modelling: what is next?, Hydrol. Process., 29, 310–320, https://doi.org/10.1002/hyp.10391, 2014. a
Borras, L., Westgate, M. E., and Oteguie, M. E.: Control of kernel weight and kernel water relations by Post-flowering Source–sink ratio in maize, Ann. Bot.-London, 91, 857–867, https://doi.org/10.1093/aob/mcg090, 2003. a
Bourgoin, C., Blanc, L., Bailly, J.-S., Cornu, G., Berenguer, E., Oszwald, J., Tritsch, I., Laurent, F., Hasan, A., Sist, P., and Gond, V.: The Potential of Multisource Remote Sensing for Mapping the Biomass of a Degraded Amazonian Forest, Forests, 9, 303, https://doi.org/10.3390/f9060303, 2018. a
Breiman, L.: Random Forests, Mach. Learn., 45, 261–277, https://doi.org/10.1023/a:1017934522171, 2001. a, b
Cai, X., Pan, M., Chaney, N. W., Colliander, A., Misra, S., Cosh, M. H., Crow, W. T., Jackson, T. J., and Wood, E. F.: Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model, Water Resour. Res., 53, 3013–3028, https://doi.org/10.1002/2016wr019967, 2017. a
Chaney, N. W., Metcalfe, P., and Wood, E. F.: HydroBlocks: a field-scale resolving land surface model for application over continental extents, Hydrol. Process., 30, 3543–3559, https://doi.org/10.1002/hyp.10891, 2016. a, b, c
Chaney, N. W., Van Huijgevoort, M. H. J., Shevliakova, E., Malyshev, S., Milly, P. C. D., Gauthier, P. P. G., and Sulman, B. N.: Harnessing big data to rethink land heterogeneity in Earth system models, Hydrol. Earth Syst. Sci., 22, 3311–3330, https://doi.org/10.5194/hess-22-3311-2018, 2018. a, b
Chen, J., Jönsson, P., Tamura, M., Gu, Z., Matsushita, B., and Eklundh, L.: A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter, Remote Sens. Environ., 91, 332–344, https://doi.org/10.1016/j.rse.2004.03.014, 2004. a
Chen, Y., Lu, D., Moran, E., Batistella, M., Dutra, L. V., Sanches, I. D., da Silva, R. F. B., Huang, J., Luiz, A. J. B., and de Oliveira, M. A. F.: Mapping croplands, cropping patterns, and crop types using MODIS time-series data, Int. J. Appl. Earth Obs., 69, 133–147, https://doi.org/10.1016/j.jag.2018.03.005, 2018. a
Chlingaryan, A., Sukkarieh, S., and Whelan, B.: Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review, Comput. Electron. Agr., 151, 61–69, https://doi.org/10.1016/j.compag.2018.05.012, 2018. a, b
CIESIN: Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 10, https://doi.org/10.7927/H4DZ068D, 2017. a
Crow, W. T., Kumar, S. V., and Bolten, J. D.: On the utility of land surface models for agricultural drought monitoring, Hydrol. Earth Syst. Sci., 16, 3451–3460, https://doi.org/10.5194/hess-16-3451-2012, 2012. a, b
Deines, J. M., Kendall, A. D., and Hyndman, D. W.: Annual Irrigation Dynamics in the U. S. Northern High Plains Derived from Landsat Satellite Data, Geophys. Res. Lett., 44, 9350–9360, https://doi.org/10.1002/2017gl074071, 2017. a
D'Odorico, P. and Bhattachan, A.: Hydrologic variability in dryland regions: impacts on ecosystem dynamics and food security, Philos. T R. Soc. B, 367, 3145–3157, https://doi.org/10.1098/rstb.2012.0016, 2012. a
Donaldson, D. and Storeygard, A.: The View from Above: Applications of Satellite Data in Economics, J. Econ. Perspect., 30, 171–198, https://doi.org/10.1257/jep.30.4.171, 2016. a
Economist: ARC's covenant, available at:
https://www.economist.com/finance-and-economics/2016/08/25/arcs-covenant
(last access: 10 June 2019), 2016. a
Enenkel, M., Farah, C., Hain, C., White, A., Anderson, M., You, L., Wagner, W., and Osgood, D.: What Rainfall Does Not Tell Us – Enhancing Financial Instruments with Satellite-Derived Soil Moisture and Evaporative Stress, Remote Sens.-Basel, 10, 1819, https://doi.org/10.3390/rs10111819, 2018. a
Estel, S., Kuemmerle, T., Levers, C., Baumann, M., and Hostert, P.: Mapping cropland-use intensity across Europe using MODIS NDVI time series, Environ. Res. Lett., 11, 024015, https://doi.org/10.1088/1748-9326/11/2/024015, 2016. a
Estes, L. D., Bradley, B. A., Beukes, H., Hole, D. G., Lau, M., Oppenheimer, M. G., Schulze, R., Tadross, M. A., and Turner, W. R.: Comparing mechanistic and empirical model projections of crop suitability and productivity: implications for ecological forecasting, Global Ecol. Biogeogr., 22, 1007–1018, https://doi.org/10.1111/geb.12034, 2013. a
Famiglietti, J. S., Ryu, D., Berg, A. A., Rodell, M., and Jackson, T. J.: Field observations of soil moisture variability across scales, Water Resour. Res., 44, W01423, https://doi.org/10.1029/2006wr005804, 2008. a
FAO: 2015–2016 El Niño Early action and response for agriculture, food
security and nutrition (Update 6), available at: http://www.fao.org/fileadmin/user_upload/emergencies/docs/FAOEl%20NinoReportMarch2016.pdf (last access: 18 May 2020), 2016a. a
FAO: 2015–2016 El Niño Early action and response for agriculture, food
security and nutrition (Update 10), available at:
http://www.fao.org/3/a-i6049e.pdf (last access: 18 May 2020), 2016b. a
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S., Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf, D.: The Shuttle Radar Topography Mission, Rev. Geophys., 45, RG2004, https://doi.org/10.1029/2005rg000183, 2007. a, b
Fick, S. E. and Hijmans, R. J.: WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas, Int. J. Climatol., 37, 4302–4315, https://doi.org/10.1002/joc.5086, 2017. a
Folberth, C., Baklanov, A., Balkovič, J., Skalský, R., Khabarov, N., and Obersteiner, M.: Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning, Agr. Forest Meteorol., 264, 1–15, https://doi.org/10.1016/j.agrformet.2018.09.021, 2019. a, b
Franz, T. E., Pokal, S., Gibson, J. P., Zhou, Y., Gholizadeh, H., Tenorio, F. A., Rudnick, D., Heeren, D., McCabe, M., Ziliani, M., Jin, Z., Guan, K., Pan, M., Gates, J., and Wardlow, B.: The role of topography, soil, and remotely sensed vegetation condition towards predicting crop yield, Field Crop. Res., 252, 107788, https://doi.org/10.1016/j.fcr.2020.107788, 2020. a, b
Funk, C. and Budde, M. E.: Phenologically-tuned MODIS NDVI-based production anomaly estimates for Zimbabwe, Remote Sens. Environ., 113, 115–125, https://doi.org/10.1016/j.rse.2008.08.015, 2009. a
Gourlay, S., Kilic, T., and Lobell, D. B.: A new spin on an old debate: Errors in farmer-reported production and their implications for inverse scale – Productivity relationship in Uganda, J. Dev. Econ., 141, 102376, https://doi.org/10.1016/j.jdeveco.2019.102376, 2019. a, b
Gregorutti, B., Michel, B., and Saint-Pierre, P.: Correlation and variable importance in random forests, Stat. Comput., 27, 659–678, https://doi.org/10.1007/s11222-016-9646-1, 2016. a
Gu, Y., Wylie, B. K., Howard, D. M., Phuyal, K. P., and Ji, L.: NDVI saturation adjustment: A new approach for improving cropland performance estimates in the Greater Platte River Basin, USA, Ecol. Indic., 30, 1–6, https://doi.org/10.1016/j.ecolind.2013.01.041, 2013. a
Guilpart, N., Grassini, P., van Wart, J., Yang, H., van Ittersum, M. K., van Bussel, L. G. J., Wolf, J., Claessens, L., Leenaars, J. G. B., and Cassman, K. G.: Rooting for food security in Sub-Saharan Africa, Environ. Res. Lett., 12, 114036, https://doi.org/10.1088/1748-9326/aa9003, 2017. a
Hao, Z. and Singh, V. P.: Drought characterization from a multivariate perspective: A review, J. Hydrol., 527, 668–678, https://doi.org/10.1016/j.jhydrol.2015.05.031, 2015. a
Harrison, L., Michaelsen, J., Funk, C., and Husak, G.: Effects of temperature changes on maize production in Mozambique, Clim. Res., 46, 211–222, https://doi.org/10.3354/cr00979, 2011. a
Hatfield, J. L. and Prueger, J. H.: Temperature extremes: Effect on plant
growth and development, Weather Clim. Extrem., 10, 4–10,
https://doi.org/10.1016/j.wace.2015.08.001, 2015. a
Hengl, T., Mendes de Jesus, J., Heuvelink, G. B. M., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M. N., Geng, X., Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A., Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., Mantel, S., and Kempen, B.: SoilGrids250m: Global gridded soil information based on machine learning, PLOS ONE, 12, e0169748, https://doi.org/10.1371/journal.pone.0169748, 2017. a, b
Jain, S.: An empirical economic assessment of impacts of climate change on agriculture in Zambia, The World Bank, https://doi.org/10.1596/1813-9450-4291, 2007. a
Jayne, T., Chamberlin, J., Traub, L., Sitko, N., Muyanga, M., Yeboah, F. K., Anseeuw, W., Chapoto, A., Wineman, A., Nkonde, C., and Kachule, R.: Africa's changing farm size distribution patterns: the rise of medium-scale farms, Agr. Econ., 47, 197–214, https://doi.org/10.1111/agec.12308, 2016. a, b
Jeong, J. H., Resop, J. P., Mueller, N. D., Fleisher, D. H., Yun, K., Butler, E. E., Timlin, D. J., Shim, K.-M., Gerber, J. S., Reddy, V. R., and Kim, S.-H.: Random Forests for Global and Regional Crop Yield Predictions, PLOS ONE, 11, e0156571, https://doi.org/10.1371/journal.pone.0156571, 2016. a
Jin, Z., Azzari, G., Burke, M., Aston, S., and Lobell, D.: Mapping Smallholder Yield Heterogeneity at Multiple Scales in Eastern Africa, Remote Sens.-Basel, 9, 931, https://doi.org/10.3390/rs9090931, 2017. a
Johnson, D. M.: A comprehensive assessment of the correlations between field crop yields and commonly used MODIS products, Int. J. Appl. Earth Obs., 52, 65–81, https://doi.org/10.1016/j.jag.2016.05.010, 2016. a
Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., Wilkens, P. W., Singh, U., Gijsman, A. J., and Ritchie, J. T.: The DSSAT cropping system model, Eur. J. Agron., 18, 235–265, https://doi.org/10.1016/S1161-0301(02)00107-7, 2003. a
Karthikeyan, L., Pan, M., Wanders, N., Kumar, D. N., and Wood, E. F.: Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons, Adv. Water Resour., 109, 236–252, https://doi.org/10.1016/j.advwatres.2017.09.010, 2017. a
Karthikeyan, L., Chawla, I., and Mishra, A. K.: A review of remote sensing applications in agriculture for food security: Crop growth and yield, irrigation, and crop losses, J. Hydrol., 586, 124905, https://doi.org/10.1016/j.jhydrol.2020.124905, 2020. a, b, c
Keating, B. A., Carberry, P. S., Hammer, G. L., Probert, M. E., Robertson, M. J., Holzworth, D., Huth, N. I., Hargreaves, J. N. G., Meinke, H., Hochman, Z., McLean, G., Verburg, K., Snow, V., Dimes, J. P., Silburn, M., Wang, E., Brown, S., Bristow, K. L., Asseng, S., Chapman, S., McCown, R. L., Freebairn, D. M., and Smith, C. J.: An overview of APSIM, a model designed for farming systems simulation, Eur. J. Agron., 18, 267–288, https://doi.org/10.1016/S1161-0301(02)00108-9, 2003. a
Khanal, S., Fulton, J., Klopfenstein, A., Douridas, N., and Shearer, S.: Integration of high resolution remotely sensed data and machine learning techniques for spatial prediction of soil properties and corn yield, Comput. Electron. Agr., 153, 213–225, https://doi.org/10.1016/j.compag.2018.07.016, 2018. a
Kintisch, E.: How a “Godzilla” El Nino shook up weather forecasts, Science, 352, 1501–1502, https://doi.org/10.1126/science.352.6293.1501, 2016. a, b
Koster, R. D., Walker, G. K., Collatz, G. J., and Thornton, P. E.: Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake, J. Climate, 27, 5632–5652, https://doi.org/10.1175/jcli-d-13-00477.1, 2014. a
Kristjanson, P., Neufeldt, H., Gassner, A., Mango, J., Kyazze, F. B., Desta, S., Sayula, G., Thiede, B., Förch, W., Thornton, P. K., and Coe, R.: Are food insecure smallholder households making changes in their farming practices? Evidence from East Africa, Food Secur., 4, 381–397, https://doi.org/10.1007/s12571-012-0194-z, 2012. a
Lehmann, C. E. R. and Parr, C. L.: Tropical grassy biomes: linking ecology, human use and conservation, Philos. T R. Soc B, 371, 20160329, https://doi.org/10.1098/rstb.2016.0329, 2016. a
Lobell, D. B.: The use of satellite data for crop yield gap analysis, Field Crop. Res., 143, 56–64, https://doi.org/10.1016/j.fcr.2012.08.008, 2013. a
Lobell, D. B. and Burke, M. B.: On the use of statistical models to predict crop yield responses to climate change, Agr. Forest Meteorol., 150, 1443–1452, https://doi.org/10.1016/j.agrformet.2010.07.008, 2010. a
Lobell, D. B. and Field, C. B.: Global scale climate–crop yield relationships and the impacts of recent warming, Environ. Res. Lett., 2, 014002, https://doi.org/10.1088/1748-9326/2/1/014002, 2007. a
Lobell, D. B., Ortiz-Monasterio, J. I., and Falcon, W. P.: Yield uncertainty at the field scale evaluated with multi-year satellite data, Agr. Syst., 92, 76–90, https://doi.org/10.1016/j.agsy.2006.02.010, 2007. a, b
Lobell, D. B., Hammer, G. L., McLean, G., Messina, C., Roberts, M. J., and Schlenker, W.: The critical role of extreme heat for maize production in the United States, Nat. Clim. Change, 3, 497–501, https://doi.org/10.1038/nclimate1832, 2013. a
Luo, Q.: Temperature thresholds and crop production: a review, Climatic Change, 109, 583–598, https://doi.org/10.1007/s10584-011-0028-6, 2011. a
Maggio, G., Sitko, N. J., and Ignaciuk, A.: Cropping system diversification in Eastern and Southern Africa: Identifying policy options to enhance
productivity and build resilience, FAO Agricultural Development Economics Working Paper 18-05, FAO, Rome, https://doi.org/10.22004/ag.econ.288953, 2018. a
Mason, N. M. and Myers, R. J.: The effects of the Food Reserve Agency on maize market prices in Zambia, Agr. Econ., 44, 203–216, https://doi.org/10.1111/agec.12004, 2013. a
McNaughton, K. and Jarvis, P.: Effects of spatial scale on stomatal control of transpiration, Agr. Forest Meteorol., 54, 279–302, https://doi.org/10.1016/0168-1923(91)90010-n, 1991. a
Mueller, N. D., Gerber, J. S., Johnston, M., Ray, D. K., Ramankutty, N., and Foley, J. A.: Closing yield gaps through nutrient and water management, Nature, 490, 254–257, https://doi.org/10.1038/nature11420, 2012. a
Mulenga, B. P., Wineman, A., and Sitko, N. J.: Climate Trends and Farmers' Perceptions of Climate Change in Zambia, Environ. Manage., 59, 291–306, https://doi.org/10.1007/s00267-016-0780-5, 2016. a
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: A state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2021-82, in review, 2021. a, b
Ng'ombe, J. N.: Technical efficiency of smallholder maize production in Zambia: a stochastic meta-frontier approach, Agrekon, 56, 347–365, https://doi.org/10.1080/03031853.2017.1409127, 2017. a
Niu, G.-Y., Yang, Z.-L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., and Xia, Y.: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements, J. Geophys. Res., 116, D12109, https://doi.org/10.1029/2010jd015139, 2011. a
Paliwal, A. and Jain, M.: The Accuracy of Self-Reported Crop Yield Estimates and Their Ability to Train Remote Sensing Algorithms, Front. Sustain. Food Syst., 4, 25–35, https://doi.org/10.3389/fsufs.2020.00025, 2020. a, b
Peichl, M., Thober, S., Meyer, V., and Samaniego, L.: The effect of soil moisture anomalies on maize yield in Germany, Nat. Hazards Earth Syst. Sci., 18, 889–906, https://doi.org/10.5194/nhess-18-889-2018, 2018. a
Petersen, L.: Real-Time Prediction of Crop Yields From MODIS Relative Vegetation Health: A Continent-Wide Analysis of Africa, Remote Sens.-Basel, 10, 1726, https://doi.org/10.3390/rs10111726, 2018. a
Sadri, S., Pan, M., Wada, Y., Vergopolan, N., Sheffield, J., Famiglietti, J. S., Kerr, Y., and Wood, E.: A global near-real-time soil moisture index monitor for food security using integrated SMOS and SMAP, Remote Sens. Environ., 246, 111864, https://doi.org/10.1016/j.rse.2020.111864, 2020. a
Saxton, K. E. and Rawls, W. J.: Soil Water Characteristic Estimates by Texture and Organic Matter for Hydrologic Solutions, Soil Sci. Soc. Am. J., 70, 1569, https://doi.org/10.2136/sssaj2005.0117, 2006. a
Scanlon, T. M., Caylor, K. K., Manfreda, S., Levin, S. A., and Rodriguez-Iturbe, I.: Dynamic response of grass cover to rainfall variability: implications for the function and persistence of savanna ecosystems, Adv. Water Resour., 28, 291–302, https://doi.org/10.1016/j.advwatres.2004.10.014, 2005. a
Schauberger, B., Archontoulis, S., Arneth, A., Balkovic, J., Ciais, P.,
Deryng, D., Elliott, J., Folberth, C., Khabarov, N., Müller, C.,
Pugh, T. A. M., Rolinski, S., Schaphoff, S., Schmid, E., Wang, X.,
Schlenker, W., and Frieler, K.: Consistent negative response of US crops to
high temperatures in observations and crop models, Nat. Commun., 8, 13931, https://doi.org/10.1038/ncomms13931, 2017. a
Searchinger, T. D., Estes, L., Thornton, P. K., Beringer, T., Notenbaert, A., Rubenstein, D., Heimlich, R., Licker, R., and Herrero, M.: High carbon and biodiversity costs from converting Africa's wet savannahs to cropland, Nat. Clim. Change, 5, 481–486, https://doi.org/10.1038/nclimate2584, 2015. a
Sheffield, J.: A simulated soil moisture based drought analysis for the United States, J. Geophys. Res., 109, D24108, https://doi.org/10.1029/2004jd005182, 2004. a
Steward, P. R., Dougill, A. J., Thierfelder, C., Pittelkow, C. M., Stringer, L. C., Kudzala, M., and Shackelford, G. E.: The adaptive capacity of maize-based conservation agriculture systems to climate stress in tropical and subtropical environments: A meta-regression of yields, Agr. Ecosyst. Environ., 251, 194–202, https://doi.org/10.1016/j.agee.2017.09.019, 2018. a
Sutanto, S. J., van der Weert, M., Wanders, N., Blauhut, V., and Van Lanen, H. A. J.: Moving from drought hazard to impact forecasts, Nat. Commun., 10, 1–7, https://doi.org/10.1038/s41467-019-12840-z, 2019. a, b
Thomas, E., Jordan, E., Linden, K., Mogesse, B., Hailu, T., Jirma, H., Thomson, P., Koehler, J., and Collins, G.: Reducing drought emergencies in the Horn of Africa, Sci. Total Environ., 727, 138772, https://doi.org/10.1016/j.scitotenv.2020.138772, 2020. a
Troy, T. J., Kipgen, C., and Pal, I.: The impact of climate extremes and irrigation on US crop yields, Environ. Res. Lett., 10, 054013, https://doi.org/10.1088/1748-9326/10/5/054013, 2015. a
Van Loon, A. F., Gleeson, T., Clark, J., Van Dijk, A. I. J. M., Stahl, K., Hannaford, J., Di Baldassarre, G., Teuling, A. J., Tallaksen, L. M., Uijlenhoet, R., Hannah, D. M., Sheffield, J., Svoboda, M., Verbeiren, B., Wagener, T., Rangecroft, S., Wanders, N., and Van Lanen, H. A. J.: Drought in the Anthropocene, Nat. Geosci., 9, 89–91, https://doi.org/10.1038/ngeo2646, 2016. a
Vergopolan, N., Chaney, N. W., Beck, H. E., Pan, M., Sheffield, J., Chan, S., and Wood, E. F.: Combining hyper-resolution land surface modeling with SMAP brightness temperatures to obtain 30-m soil moisture estimates, Remote Sens. Environ., 242, 111740, https://doi.org/10.1016/j.rse.2020.111740, 2020. a, b, c
Waldman, K. B., Vergopolan, N., Attari, S. Z., Sheffield, J., Estes, L. D., Caylor, K. K., and Evans, T. P.: Cognitive Biases about Climate Variability in Smallholder Farming Systems in Zambia, Weather Clim. Soc., 11, 369–383, https://doi.org/10.1175/wcas-d-18-0050.1, 2019. a
Wanders, N., Bachas, A., He, X. G., Huang, H., Koppa, A., Mekonnen, Z. T., Pagán, B. R., Peng, L. Q., Vergopolan, N., Wang, K. J., Xiao, M., Zhan, S., Lettenmaier, D. P., and Wood, E. F.: Forecasting the Hydroclimatic Signature of the 2015/16 El Niño Event on the Western United States, J. Hydrometeorol., 18, 177–186, https://doi.org/10.1175/jhm-d-16-0230.1, 2017. a
Williams, C. A., Reichstein, M., Buchmann, N., Baldocchi, D., Beer, C., Schwalm, C., Wohlfahrt, G., Hasler, N., Bernhofer, C., Foken, T., Papale, D., Schymanski, S., and Schaefer, K.: Climate and vegetation controls on the surface water balance: Synthesis of evapotranspiration measured across a global network of flux towers, Water Resour. Res., 48, W06523, https://doi.org/10.1029/2011wr011586, 2012.
a
Wood, E. F., Roundy, J. K., Troy, T. J., van Beek, L. P. H., Bierkens, M. F. P., Blyth, E., de Roo, A., Döll, P., Ek, M., Famiglietti, J., Gochis, D., van de Giesen, N., Houser, P., Jaffé, P. R., Kollet, S., Lehner, B., Lettenmaier, D. P., Peters-Lidard, C., Sivapalan, M., Sheffield, J., Wade, A., and Whitehead, P.: Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water, Water Resour. Res., 47, W05301, https://doi.org/10.1029/2010wr010090, 2011. a
Wylie, B. K., Pastick, N. J., Picotte, J. J., and Deering, C.: Geospatial data mining for digital raster mapping, GISci. Remote Sens., 56, 406–429, https://doi.org/10.1080/15481603.2018.1517445, 2019. a, b
Xia, Y., Ek, M. B., Peters-Lidard, C. D., Mocko, D., Svoboda, M., Sheffield, J., and Wood, E. F.: Application of USDM statistics in NLDAS-2: Optimal blended NLDAS drought index over the continental United States, J. Geophys. Res.-Atmos., 119, 2947–2965, https://doi.org/10.1002/2013jd020994, 2014. a
Zargar, A., Sadiq, R., Naser, B., and Khan, F. I.: A review of drought indices, Environ. Rev., 19, 333–349, https://doi.org/10.1139/a11-013, 2011. a
Zhao, Y., Vergopolan, N., Baylis, K., Blekking, J., Caylor, K., Evans, T., Giroux, S., Sheffield, J., and Estes, L.: Comparing empirical and survey-based yield forecasts in a dryland agro-ecosystem, Agr. Forest Meteorol., 262, 147–156, https://doi.org/10.1016/j.agrformet.2018.06.024, 2018. a, b, c
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.
Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or...
