Articles | Volume 29, issue 8
https://doi.org/10.5194/hess-29-1981-2025
© Author(s) 2025. 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-29-1981-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note
| 
22 Apr 2025
Technical note |
| 22 Apr 2025
| 22 Apr 2025
Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis
Fabián Lema
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
Advanced Mining Technology Center, Universidad de Chile, Santiago, Chile
Nicolás A. Vásquez
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
Naoki Mizukami
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
Mauricio Zambrano-Bigiarini
Department of Civil Engineering, Universidad de La Frontera, Temuco, Chile
Center for Climate and Resilience Research, Universidad de Chile, Santiago, Chile
Ximena Vargas
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
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David R. Casson, Guoqiang Tang, Nicolás Vásquez, Andrew W. Wood, and Martyn P. Clark
The Cryosphere, 20, 5895–5940, https://doi.org/10.5194/tc-20-5895-2026, https://doi.org/10.5194/tc-20-5895-2026, 2026
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Improving mountain snow prediction requires better representation of meteorological uncertainty. This study generates meteorological ensembles accounting for topography, gauge undercatch, and large-scale atmospheric patterns. Driving a physics-based snow model calibrated using a Large Sample Emulator with these ensembles propagates forcing uncertainty into snow accumulation and melt, producing probablistic estimates for data assimilation and hydrological forecasting.
Millie C. Spencer, Alfonso Fernandez, Emma Tyrrell, Robert Clasing, Enrique Muñoz, Pablo A. Mendoza, Jorge Berkhoff, and Noah P. Molotch
The Cryosphere, 20, 5559–5583, https://doi.org/10.5194/tc-20-5559-2026, https://doi.org/10.5194/tc-20-5559-2026, 2026
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Mountain glaciers are important freshwater reservoirs. Quantifying their loss is essential for forecasting water availability. While glacier retreat is well studied in many regions, glacier loss on the Nevados de Chillán volcanic complex in south-central Chile remains uncertain. Using satellite and drone images, we find all 28 glaciers on Nevados de Chillán lost volume over the past 7 decades, with melt rates accelerating markedly since 2000.
Alexis Caro, Javier Medina, Freddy Saavedra, Fernando Gimeno, Jorge Huenante, Mariano Masiokas, Cristian Orrego, Ana Hernández, James McPhee, Pierre Pitte, Sebastián Krogh, David Farías-Barahona, Nevenka Bulovic, Iñigo Irarrázaval, Shelley MacDonell, Mauricio Zambrano-Bigiarini, and Carlos Romero
Earth Syst. Sci. Data, 18, 7097–7123, https://doi.org/10.5194/essd-18-7097-2026, https://doi.org/10.5194/essd-18-7097-2026, 2026
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Snowpack dynamics in the Southern Andes remain poorly quantified due to sparse and inconsistent in situ data, limiting hydrological modeling. We compile and quality-control daily snow depth observations from 81 stations (21–54° S, 2010–2024). The resulting dataset improves the Physical Consistency Index (up to 95 %) despite reduced data availability, reveals a north–south increase in snow depth but no consistent positive relationship with elevation across river basins.
Jerónimo Sota, Pablo A. Mendoza, and Miguel Lagos-Zúñiga
EGUsphere, https://doi.org/10.5194/egusphere-2026-4067, https://doi.org/10.5194/egusphere-2026-4067, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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Despite snowmelt runoff from mountainous domains is a vital water source, river flows months ahead remain difficult to predict. This study tested several ways to improve dynamical forecasts across 21 Andean basins using nearly four decades of past data. Results show that some configurations improve forecasts only at specific times or in certain basins, while others can reduce accuracy. The results can help water managers choose more reliable forecasting tools for decision making.
Matthias Cuntz, Stephan Thober, Anne Verhoef, Yijian Zeng, Aaron Boone, Agnès Ducharne, Sujan Koirala, David M. Lawrence, Philipp de Vrese, Carsten Montzka, Sonia I. Seneviratne, Harry Vereecken, Dani Or, Salma Tafasca, Naoki Mizukami, Rich Ellis, Patrick C. McGuire, and Lukas Gudmundsson
EGUsphere, https://doi.org/10.5194/egusphere-2026-4223, https://doi.org/10.5194/egusphere-2026-4223, 2026
Preprint archived
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Land surface models (LSMs) are essential tools to analyze future climate change. Here we pushed state-of-the-art LSMs out of their comfort zone revealing hidden connections between processes encoded into the models. The LSMs reacted differently due to complex, sometimes counter-intuitive interactions of different water fluxes. We identified surface runoff and soil evaporation as the two main reasons behind model differences, which should be improved by using more mechanistic descriptions.
Chayan Roychoudhury, Rajesh Kumar, Cenlin He, William Y. Y. Cheng, Kirpa Ram, Naoki Mizukami, and Avelino F. Arellano
Earth Syst. Sci. Data, 18, 5209–5257, https://doi.org/10.5194/essd-18-5209-2026, https://doi.org/10.5194/essd-18-5209-2026, 2026
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Snow and ice in the high mountains of Asia feed rivers supplying water to over a billion people, but airborne soot and dust darken the snow and speed up melting. We built a 17-year record of these conditions by blending satellite observations with a complex model that simulates weather, air pollution, land, and snow as one connected system. The record agrees well with independent measurements and traces soot on the glaciers to its regional sources, helping assess risks to Asia's water supply.
Cyril Thébault, Wouter J. M. Knoben, Nans Addor, Andrew J. Newman, Diana Spieler, Nicolás A. Vásquez, Yalan Song, Gaby J. Gründemann, Shaun Carney, Mukesh Kumar, Katie van Werkhoven, Chaopeng Shen, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 30, 3945–3977, https://doi.org/10.5194/hess-30-3945-2026, https://doi.org/10.5194/hess-30-3945-2026, 2026
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Reliable river flow prediction guide water supply planning and flood protection. We tested whether selecting or combining multiple models improves accuracy compared with a single model. 78 models were used and tested in 559 river basins across the United States. A carefully chosen single model nearly matched more complex multi-model approaches, while combining models gave slightly higher accuracy and lower uncertainty. However, no approach worked best everywhere.
Matías Moreno, Pablo Mendoza, Eduardo Muñoz-Castro, Mauricio Zambrano-Bigiarini, and Alonso Pizarro
EGUsphere, https://doi.org/10.5194/egusphere-2026-2912, https://doi.org/10.5194/egusphere-2026-2912, 2026
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We developed a new method called SPEAK to better evaluate how well hydrological models reproduce spatial patterns such as evapotranspiration across different regions. We tested it in 99 Chilean catchments with different climates and terrain types. Compared with existing methods, SPEAK more accurately represented spatial patterns and was less affected by map resolution or catchment characteristics. This could help improve water resource modelling and planning across diverse local conditions.
Nicolás A. Vásquez, Pablo A. Mendoza, Wouter Knoben, Martyn Clark, Tricia Stadnyk, and Naoki Mizukami
EGUsphere, https://doi.org/10.5194/egusphere-2026-1363, https://doi.org/10.5194/egusphere-2026-1363, 2026
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Although distributed hydrological models are often calibrated using only streamflow data, this practice may provide unrealistic representations of the water cycle. We show that, while streamflow annual cycles can be reasonably simulated, the seasonality of other key variables - such as evapotranspiration, soil moisture, and snow cover - may be severely misrepresented. Our results highlight the need to assess seasonal patterns of variables beyond streamflow when calibrating hydrological models.
Daniel A. Núñez-Ibarra, Mauricio Zambrano-Bigiarini, and Mauricio Galleguillos
Hydrol. Earth Syst. Sci., 30, 1813–1847, https://doi.org/10.5194/hess-30-1813-2026, https://doi.org/10.5194/hess-30-1813-2026, 2026
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Soil moisture plays a key role in how land and climate interact, yet it remains difficult to measure in remote or natural areas. This study compared four state-of-the-art soil moisture datasets against ground data from ten sites in Chile. Results show that some products perform better in humid areas, while others do better in dry regions. The work highlights which datasets are most reliable and suggests new ways to assess how well they track changes after precipitation events.
Eduardo Muñoz-Castro, Bailey J. Anderson, Paul C. Astagneau, Daniel L. Swain, Pablo A. Mendoza, and Manuela I. Brunner
Hydrol. Earth Syst. Sci., 30, 825–848, https://doi.org/10.5194/hess-30-825-2026, https://doi.org/10.5194/hess-30-825-2026, 2026
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Flood impacts can be enhanced when they occur after droughts, yet the effectiveness of hydrological models in simulating these events remains unclear. Here, we calibrated four conceptual hydrological models across 63 catchments in Chile and Switzerland to assess their ability to detect streamflow extremes and their transitions. We show that drought-to-flood transitions are generally poorly captured, especially in semi-arid high-mountain catchments than in humid low-elevation ones.
Cristóbal Soto-Escobar, Mauricio Zambrano-Bigiarini, Violeta Tolorza, and René Garreaud
Hydrol. Earth Syst. Sci., 30, 91–117, https://doi.org/10.5194/hess-30-91-2026, https://doi.org/10.5194/hess-30-91-2026, 2026
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This study assesses how spatial patterns, temporal trends, and record length in hourly precipitation data affect annual maximum intensities estimated with stationary and non-stationary models across a climatically and topographically diverse region. Comparing five gridded datasets, we find consistent spatial patterns but notable differences in intensities, with non-stationary estimates generally slightly lower.
René Garreaud, Juan Pablo Boisier, Camila Alvarez-Garreton, Duncan A. Christie, Tomás Carrasco-Escaff, Iván Vergara, Roberto O. Chávez, Paulina Aldunce, Pablo Camus, Manuel Suazo-Álvarez, Mariano Masiokas, Gabriel Castro, Ariel Muñoz, Mauricio Zambrano-Bigiarini, Rodrigo Fuster, and Lintsiee Godoy
Hydrol. Earth Syst. Sci., 29, 5347–5369, https://doi.org/10.5194/hess-29-5347-2025, https://doi.org/10.5194/hess-29-5347-2025, 2025
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This study focuses on hyperdroughts (HDs) in central Chile, defined as years with a regional rainfall deficit exceeding 75 %. Only five HDs occurred in the last century (1924, 1968, 1998, 2019, 2021), but they caused disproportionate environmental and social impacts. In some systems, the effects were larger than expected from those considering moderate droughts and dependent on the antecedent conditions. HDs have analogs from the remote past, and they are expected to increase in the near future.
Naoki Mizukami, Samar Minallah, Cenlin He, Chayan Roychoudhury, William Y.Y. Cheng, and Rajesh Kumar
EGUsphere, https://doi.org/10.5194/egusphere-2025-4586, https://doi.org/10.5194/egusphere-2025-4586, 2025
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We examined how air pollution particles that darken snow affect water resources in High Mountain Asia, a region that supplies rivers vital to millions of populations. Using computer models, we found that these particles cause snow to melt two weeks to a month earlier, shifting when water becomes available. This leads to more runoff at first but less later in the year, slightly reducing annual river flow. The findings highlight the need to link air pollution control with water management.
Mozhgan A. Farahani, Andrew W. Wood, Guoqiang Tang, and Naoki Mizukami
Hydrol. Earth Syst. Sci., 29, 4515–4537, https://doi.org/10.5194/hess-29-4515-2025, https://doi.org/10.5194/hess-29-4515-2025, 2025
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We present a new strategy to calibrate large-domain land/hydrology models over diverse regions. Using the Structure for Unifying Multiple Modeling Alternatives (SUMMA) and mizuRoute models, our approach integrates catchment attributes, parameters, and performance metrics to optimize streamflow simulations. Leveraging advances in machine learning for hydrology, we improve calibration and enable regionalization to ungauged basins, which is valuable for national-scale water security studies.
Sofía Segovia, Pablo A. Mendoza, Miguel Lagos-Zúñiga, Lucía Scaff, and Andreas Prein
EGUsphere, https://doi.org/10.5194/egusphere-2025-3061, https://doi.org/10.5194/egusphere-2025-3061, 2025
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High-resolution climate simulations can improve our understanding of precipitation and temperature patterns in regions with complex terrain. We evaluate a new climate dataset against in-situ observations, and its potencial for hydrological modeling. Results show that, despite some limitations in dry areas, high-resolution climate models can provide information of a quality comparable to that of observation-based products, supporting their use in water resources planning and decision-making.
Violeta Tolorza, Christian H. Mohr, Mauricio Zambrano-Bigiarini, Benjamín Sotomayor, Dagoberto Poblete-Caballero, Sebastien Carretier, Mauricio Galleguillos, and Oscar Seguel
Earth Surf. Dynam., 12, 841–861, https://doi.org/10.5194/esurf-12-841-2024, https://doi.org/10.5194/esurf-12-841-2024, 2024
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We calculated disturbances and landscape-lowering rates across various timescales in a ~ 406 km2 catchment in the Chilean Coastal Range. Intensive management of exotic tree plantations involves short rotational cycles (planting and harvesting by replanting clear-cuts) lasting 9–25 years, dense forestry road networks (increasing connectivity), and a recent increase in wildfires. Concurrently, persistent drought conditions and the high water demand of fast-growing trees reduce water availability.
Camila Alvarez-Garreton, Juan Pablo Boisier, René Garreaud, Javier González, Roberto Rondanelli, Eugenia Gayó, and Mauricio Zambrano-Bigiarini
Hydrol. Earth Syst. Sci., 28, 1605–1616, https://doi.org/10.5194/hess-28-1605-2024, https://doi.org/10.5194/hess-28-1605-2024, 2024
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This opinion paper reflects on the risks of overusing groundwater savings to supply permanent water use requirements. Using novel data recently developed for Chile, we reveal how groundwater is being overused, causing ecological and socioeconomic impacts and concealing a Day Zero
scenario. Our argument underscores the need for reformed water allocation rules and sustainable management, shifting from a perception of groundwater as an unlimited source to a finite and vital one.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Diego G. Miralles, Hylke E. Beck, Jonatan F. Siegmund, Camila Alvarez-Garreton, Koen Verbist, René Garreaud, Juan Pablo Boisier, and Mauricio Galleguillos
Hydrol. Earth Syst. Sci., 28, 1415–1439, https://doi.org/10.5194/hess-28-1415-2024, https://doi.org/10.5194/hess-28-1415-2024, 2024
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Various drought indices exist, but there is no consensus on which index to use to assess streamflow droughts. This study addresses meteorological, soil moisture, and snow indices along with their temporal scales to assess streamflow drought across hydrologically diverse catchments. Using data from 100 Chilean catchments, findings suggest that there is not a single drought index that can be used for all catchments and that snow-influenced areas require drought indices with larger temporal scales.
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023, https://doi.org/10.5194/hess-27-4385-2023, 2023
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Dynamical systems are used by many agencies worldwide to produce seasonal streamflow forecasts, which are critical for decision-making. Such systems rely on hydrology models, which contain parameters that are typically estimated using a target performance metric (i.e., objective function). This study explores the effects of this decision across mountainous basins in Chile, illustrating tradeoffs between seasonal forecast quality and the models' capability to simulate streamflow characteristics.
Nicolás Cortés-Salazar, Nicolás Vásquez, Naoki Mizukami, Pablo A. Mendoza, and Ximena Vargas
Hydrol. Earth Syst. Sci., 27, 3505–3524, https://doi.org/10.5194/hess-27-3505-2023, https://doi.org/10.5194/hess-27-3505-2023, 2023
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This paper shows how important river models can be for water resource applications that involve hydrological models and, in particular, parameter calibration. To this end, we conduct numerical experiments in a pilot basin using a combination of hydrologic model simulations obtained from a large sample of parameter sets and different routing methods. We find that routing can affect streamflow simulations, even at monthly time steps; the choice of parameters; and relevant streamflow metrics.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Zhi Li, Shang Gao, Mengye Chen, Jonathan Gourley, Naoki Mizukami, and Yang Hong
Geosci. Model Dev., 15, 6181–6196, https://doi.org/10.5194/gmd-15-6181-2022, https://doi.org/10.5194/gmd-15-6181-2022, 2022
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Operational streamflow prediction at a continental scale is critical for national water resources management. However, limited computational resources often impede such processes, with streamflow routing being one of the most time-consuming parts. This study presents a recent development of a hydrologic system that incorporates a vector-based routing scheme with a lake module that markedly speeds up streamflow prediction. Moreover, accuracy is improved and flood false alarms are mitigated.
Ulises M. Sepúlveda, Pablo A. Mendoza, Naoki Mizukami, and Andrew J. Newman
Hydrol. Earth Syst. Sci., 26, 3419–3445, https://doi.org/10.5194/hess-26-3419-2022, https://doi.org/10.5194/hess-26-3419-2022, 2022
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This paper characterizes parameter sensitivities across more than 5500 grid cells for a commonly used macroscale hydrological model, including a suite of eight performance metrics and 43 soil, vegetation and snow parameters. The results show that the model is highly overparameterized and, more importantly, help to provide guidance on the most relevant parameters for specific target processes across diverse climatic types.
Inne Vanderkelen, Shervan Gharari, Naoki Mizukami, Martyn P. Clark, David M. Lawrence, Sean Swenson, Yadu Pokhrel, Naota Hanasaki, Ann van Griensven, and Wim Thiery
Geosci. Model Dev., 15, 4163–4192, https://doi.org/10.5194/gmd-15-4163-2022, https://doi.org/10.5194/gmd-15-4163-2022, 2022
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Human-controlled reservoirs have a large influence on the global water cycle. However, dam operations are rarely represented in Earth system models. We implement and evaluate a widely used reservoir parametrization in a global river-routing model. Using observations of individual reservoirs, the reservoir scheme outperforms the natural lake scheme. However, both schemes show a similar performance due to biases in runoff timing and magnitude when using simulated runoff.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Pablo A. Mendoza, Ian McNamara, Hylke E. Beck, Joschka Thurner, Alexandra Nauditt, Lars Ribbe, and Nguyen Xuan Thinh
Hydrol. Earth Syst. Sci., 25, 5805–5837, https://doi.org/10.5194/hess-25-5805-2021, https://doi.org/10.5194/hess-25-5805-2021, 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.
Cited articles
Adeyeri, O. E., Zhou, W., Laux, P., Ndehedehe, C. E., Wang, X., Usman, M., and Akinsanola, A. A.: Multivariate Drought Monitoring, Propagation, and Projection Using Bias-Corrected General Circulation Models, Earth's Future, 11, 1–16, https://doi.org/10.1029/2022EF003303, 2023.
Almagro, A., Meira Neto, A. A., Vergopolan, N., Roy, T., Troch, P. A., and Oliveira, P. T. S.: The Drivers of Hydrologic Behavior in Brazil: Insights From a Catchment Classification, Water Resour. Res., 60, e2024WR037212, https://doi.org/10.1029/2024WR037212, 2024.
Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Puelma, C., Cortes, G., Garreaud, R., McPhee, J., and Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset, Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, 2018.
Andreadis, K. M., Clark, E. A., Wood, A. W., Hamlet, A. F., and Lettenmaier, D. P.: Twentieth-century drought in the conterminous United States, J. Hydrometeorol., 6, 985–1001, https://doi.org/10.1175/JHM450.1, 2005.
Apurv, T., Sivapalan, M., and Cai, X.: Understanding the Role of Climate Characteristics in Drought Propagation, Water Resour. Res., 53, 9304–9329, https://doi.org/10.1002/2017WR021445, 2017.
Bachmair, S., Kohn, I., and Stahl, K.: Exploring the link between drought indicators and impacts, Nat. Hazards Earth Syst. Sci., 15, 1381–1397, https://doi.org/10.5194/nhess-15-1381-2015, 2015.
Baez-Villanueva, O. M., Zambrano-Bigiarini, M., Miralles, D. G., Beck, H. E., Siegmund, J. F., Alvarez-Garreton, C., Verbist, K., Garreaud, R., Boisier, J. P., and Galleguillos, M.: On the timescale of drought indices for monitoring streamflow drought considering catchment hydrological regimes, Hydrol. Earth Syst. Sci., 28, 1415–1439, https://doi.org/10.5194/hess-28-1415-2024, 2024.
Barker, L. J., Hannaford, J., Chiverton, A., and Svensson, C.: From meteorological to hydrological drought using standardised indicators, Hydrol. Earth Syst. Sci., 20, 2483–2505, https://doi.org/10.5194/hess-20-2483-2016, 2016.
Bevacqua, A. G., Chaffe, P. L. B., Chagas, V. B. P., and AghaKouchak, A.: Spatial and temporal patterns of propagation from meteorological to hydrological droughts in Brazil, J. Hydrol., 603, 126902, https://doi.org/10.1016/j.jhydrol.2021.126902, 2021.
Bhardwaj, K., Shah, D., Aadhar, S., and Mishra, V.: Propagation of Meteorological to Hydrological Droughts in India, J. Geophys. Res.-Atmos., 125, e2020JD033455, https://doi.org/10.1029/2020JD033455, 2020.
Boisier, J. P., Alvarez-Garretón, C., Cepeda, J., Osses, A., Vásquez, N., and Rondanelli, R.: CR2MET: A high-resolution precipitation and temperature dataset for hydroclimatic research in Chile, Center for Climate and Resilience Research [data set], https://www.cr2.cl/datos-productos-grillados (last access: 1 April 2023), 2018.
Brunner, L., Pendergrass, A. G., Lehner, F., Merrifield, A. L., Lorenz, R., and Knutti, R.: Reduced global warming from CMIP6 projections when weighting models by performance and independence, Earth Syst. Dynam., 11, 995–1012, https://doi.org/10.5194/esd-11-995-2020, 2020.
Brunner, M. I. and Stahl, K.: Temporal hydrological drought clustering varies with climate and land-surface processes, Environ. Res. Lett., 18, 034011, https://doi.org/10.1088/1748-9326/acb8ca, 2023.
Brunner, M. I. and Tallaksen, L. M.: Proneness of European Catchments to Multiyear Streamflow Droughts, Water Resour. Res., 55, 8881–8894, https://doi.org/10.1029/2019WR025903, 2019.
Buitink, J., van Hateren, T. C., and Teuling, A. J.: Hydrological System Complexity Induces a Drought Frequency Paradox, Front. Water, 3, 1–12, https://doi.org/10.3389/frwa.2021.640976, 2021.
Carrão, H., Russo, S., Sepulcre, G., and Barbosa, P.: Agricultural Drought Assessment In Latin America Based On A Standardized Soil Moisture Index, ESA Living Planet Symposium, December, 9–13 September 2013, Edinburgh, UK, 2013.
Celia, M. A., Bouloutas, E. T., and Zarba, R. L.: A general mass-conservative numerical solution for the unsaturated flow equation, Water Resour. Res., 26, 1483–1496, https://doi.org/10.1029/WR026i007p01483, 1990.
Center for Climate and Resilience Research (CR2): Datos de caudales, Center for Climate and Resilience Research [data set], https://www.cr2.cl/datos-de-caudales/, last access: 15 April 2023.
Clark, M. P., Nijssen, B., Lundquist, J. D., Kavetski, D., Rupp, D. E., Woods, R. A., Freer, J. E., Gutmann, E. D., Wood, A. W., Brekke, L. D., Arnold, J. R., Gochis, D. J., and Rasmussen, R. M.: A unified approach for process-based hydrologic modeling: 1. Modeling concept, Water Resour. Res., 51, 2498–2514, https://doi.org/10.1002/2015WR017198, 2015a.
Clark, M. P., Nijssen, B., Lundquist, J. D., Kavetski, D., Rupp, D. E., Woods, R. A., Freer, J. E., Gutmann, E. D., Wood, A. W., Gochis, D. J., Rasmussen, R. M., Tarboton, D. G., Mahat, V., Flerchinger, G. N., and Marks, D. G.: A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies, Water Resour. Res., 51, 2515–2542, https://doi.org/10.1002/2015WR017200, 2015b.
Clark, M. P., Zolfaghari, R., Green, K. R., Trim, S., Knoben, W. J. M., Bennett, A., Nijssen, B., Ireson, A., and Spiteri, R. J.: The numerical implementation of land models: Problem formulation and laugh tests, J. Hydrometeorol., 22, 1627–1648, https://doi.org/10.1175/JHM-D-20-0175.1, 2021.
Cook, B. I., Smerdon, J. E., Seager, R., and Coats, S.: Global warming and 21st century drying, Clim. Dynam., 43, 2607–2627, https://doi.org/10.1007/s00382-014-2075-y, 2014.
Cook, B. I., Mankin, J. S., and Anchukaitis, K. J.: Climate Change and Drought: From Past to Future, Current Climate Change Reports, 4, 164–179, https://doi.org/10.1007/s40641-018-0093-2, 2018.
Cortés-Salazar, N., Vásquez, N., Mizukami, N., Mendoza, P. A., and Vargas, X.: To what extent does river routing matter in hydrological modeling?, Hydrol. Earth Syst. Sci., 27, 3505–3524, https://doi.org/10.5194/hess-27-3505-2023, 2023.
DGA: Actualización del Balance Hídrico Nacional, SIT no. 417, https://repositoriodirplan.mop.gob.cl/biblioteca/handle/20.500.12140/32653 (last access: 1 November 2023), 2017.
DGA: Deja sin efecto la resolución D.G.A. no. 1.674 (exenta), de 12 de junio de 2012, y establece criterios que determinan el carácter de severa sequía, de conformidad a lo dispuesto en el artículo 314 del código de aguas, https://www.bcn.cl/leychile/navegar?i=1177291 (last access: 4 May 2024), 2022.
Fowé, T., Yonaba, R., Mounirou, L. A., Ouédraogo, E., Ibrahim, B., Niang, D., Karambiri, H., and Yacouba, H.: From meteorological to hydrological drought: a case study using standardized indices in the Nakanbe River Basin, Burkina Faso, Natural Hazards, 119, 1941–1965, https://doi.org/10.1007/s11069-023-06194-5, 2023.
Friedl, M. and Sulla-Menashe, D.: MCD12C1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V006, distributed by NASA EOSDIS Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MCD12C1.006, 2015.
Fuentes, I., Padarian, J., and Vervoort, R. W.: Spatial and Temporal Global Patterns of Drought Propagation, Front. Environ. Sci., 10, 1–21, https://doi.org/10.3389/fenvs.2022.788248, 2022.
Garcia, F., Folton, N., and Oudin, L.: Which objective function to calibrate rainfall–runoff models for low-flow index simulations?, Hydrol. Sci. J., 62, 1149–1166, https://doi.org/10.1080/02626667.2017.1308511, 2017.
Garreaud, R. D., Alvarez-Garreton, C., Barichivich, J., Boisier, J. P., Christie, D., Galleguillos, M., LeQuesne, C., McPhee, J., and Zambrano-Bigiarini, M.: The 2010–2015 megadrought in central Chile: impacts on regional hydroclimate and vegetation, Hydrol. Earth Syst. Sci., 21, 6307–6327, https://doi.org/10.5194/hess-21-6307-2017, 2017.
Garreaud, R. D., Boisier, J. P. P., Rondanelli, R., Montecinos, A., Sepúlveda, H. H. H., and Veloso-Aguila, D.: The Central Chile Mega Drought (2010–2018): A climate dynamics perspective, Int. J. Climatol., 40, 1–19, https://doi.org/10.1002/joc.6219, 2019.
Gautam, S., Samantaray, A., Babbar-Sebens, M., and Ramadas, M.: Characterization and Propagation of Historical and Projected Droughts in the Umatilla River Basin, Oregon, USA, Adv. Atmos. Sci., 41, 247–262, https://doi.org/10.1007/s00376-023-2302-8, 2024.
Gobron, N., Belward, A., Pinty, B., and Knorr, W.: Monitoring biosphere vegetation 1998–2009, Geophys. Res. Lett., 37, 1–6, https://doi.org/10.1029/2010GL043870, 2010.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91, https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Hameed, M. M., Mohd Razali, S. F., Wan Mohtar, W. H. M., and Yaseen, Z. M.: Improving multi-month hydrological drought forecasting in a tropical region using hybridized extreme learning machine model with Beluga Whale Optimization algorithm, Stoch. Env. Res. Risk A., 37, 4963–4989, https://doi.org/10.1007/s00477-023-02548-4, 2023.
Haslinger, K., Koffler, D., Schöner, W., and Laaha, G.: Exploring the link between meteorological drought and streamflow: Effects of climate-catchment interaction, Water Resour. Res., 50, 2468–2487, https://doi.org/10.1002/2013WR015051, 2014.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hoffmann, D., Gallant, A. J. E., and Arblaster, J. M.: Uncertainties in Drought From Index and Data Selection, J. Geophys. Res.-Atmos., 125, 1–21, https://doi.org/10.1029/2019JD031946, 2020.
Hosking, J. R. M.: The Theory of Probability Weighted Moments, Research Report 840 RC12210, IBM Research Division, Yorktown Heights, New York, 160 pp., 1986.
Huang, S., Li, P., Huang, Q., Leng, G., Hou, B., and Ma, L.: The propagation from meteorological to hydrological drought and its potential influence factors, J. Hydrol., 547, 184–195, https://doi.org/10.1016/j.jhydrol.2017.01.041, 2017.
Iziomon, M. G., Mayer, H., and Matzarakis, A.: Downward atmospheric longwave irradiance under clear and cloudy skies: Measurement and parameterization, J. Atmos. Solar-Terr. Phy., 65, 1107–1116, https://doi.org/10.1016/j.jastp.2003.07.007, 2003.
Jarvis, P.: The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field, Philos. T. Roy. Soc. Lond. B, 273, 593–610, https://doi.org/10.1098/rstb.1976.0035, 1976.
Jordan, R.: A One-Dimensional Temperature Model for a Snow Cover, Cold Regions Research and Engineering Lab, U.S. Army Corps of Engineers, Hanover, N.H., Spec. Rept. 91-16, 1991.
Laimighofer, J. and Laaha, G.: How standard are standardized drought indices? Uncertainty components for the SPI & SPEI case, J. Hydrol., 613, 128385, https://doi.org/10.1016/j.jhydrol.2022.128385, 2022.
Lee, J., Kim, Y., and Wang, D.: Assessing the characteristics of recent drought events in South Korea using WRF-Hydro, J. Hydrol., 607, 127459, https://doi.org/10.1016/j.jhydrol.2022.127459, 2022.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99, 14415–14428, https://doi.org/10.1029/94jd00483, 1994.
Mahat, V. and Tarboton, D. G.: Canopy radiation transmission for an energy balance snowmelt model, Water Resour. Res., 48, 1–16, https://doi.org/10.1029/2011WR010438, 2012.
Mahat, V., Tarboton, D. G., and Molotch, N. P.: Testing above- and below-canopy representations of turbulent fluxes in an energy balance snowmelt model, Water Resour. Res., 49, 1107–1122, https://doi.org/10.1002/wrcr.20073, 2013.
Matott, L.: OSTRICH: an Optimization Software Tool, Documentation and User's Guide, Version 17.12.19., 2017.
McKee, T. B., Doesken, N. J., and Kleist, J.: The relationship of drought frequency and duration to time scales, in: Proceedings of the 8th Conference on Applied Climatology, California, 17–22 January 1993, vol. 17, 179–183, https://www.scirp.org/reference/ReferencesPapers?ReferenceID=2099290 (last access: 28 December 2023), 1993.
Mizukami, N., Clark, M. P., Sampson, K., Nijssen, B., Mao, Y., McMillan, H., Viger, R. J., Markstrom, S. L., Hay, L. E., Woods, R., Arnold, J. R., and Brekke, L. D.: mizuRoute version 1: a river network routing tool for a continental domain water resources applications, Geosci. Model Dev., 9, 2223–2238, https://doi.org/10.5194/gmd-9-2223-2016, 2016.
Mizukami, N., Clark, M. P., Gharari, S., Kluzek, E., Pan, M., Lin, P., Beck, H. E., and Yamazaki, D.: A Vector-Based River Routing Model for Earth System Models: Parallelization and Global Applications, J. Adv. Model. Earth Sy., 13, 1–20, https://doi.org/10.1029/2020MS002434, 2021.
Modarres, R.: Streamflow drought time series forecasting, Stoch. Env. Res. Risk A., 21, 223–233, https://doi.org/10.1007/s00477-006-0058-1, 2007.
Muñoz-Castro, E., Mendoza, P. A., Vásquez, N., and Vargas, X.: Exploring parameter (dis)agreement due to calibration metric selection in conceptual rainfall-runoff models, Hydrol. Sci. J., 68, 1754–1768, https://doi.org/10.1080/02626667.2023.2231434, 2023.
Muñoz Sabater, J.: ERA5-Land hourly data from 1950 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.e2161bac (last access: 12 November 2023), 2019.
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, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021.
Nash, J. and Sutcliffe, J.: River flow forecasting through conceptual models part I - A discussion of principles, J. Hydrol., 10, 282–290, https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
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.
Nkiaka, E., Nawaz, N. R., and Lovett, J. C.: Using standardized indicators to analyse dry/wet conditions and their application for monitoring drought/floods: a study in the Logone catchment, Lake Chad basin, Hydrol. Sci. J., 62, 2720–2736, https://doi.org/10.1080/02626667.2017.1409427, 2017.
Núñez, J., Rivera, D., Oyarzún, R., and Arumí, J. L.: On the use of Standardized Drought Indices under decadal climate variability: Critical assessment and drought policy implications, J. Hydrol., 517, 458–470, https://doi.org/10.1016/j.jhydrol.2014.05.038, 2014.
Odongo, R. A., De Moel, H., and Van Loon, A. F.: Propagation from meteorological to hydrological drought in the Horn of Africa using both standardized and threshold-based indices, Nat. Hazards Earth Syst. Sci., 23, 2365–2386, https://doi.org/10.5194/nhess-23-2365-2023, 2023.
Oertel, M., Meza, F. J., and Gironás, J.: Observed trends and relationships between ENSO and standardized hydrometeorological drought indices in central Chile, Hydrol. Process., 34, 159–174, https://doi.org/10.1002/hyp.13596, 2020.
Okumura, Y. M., DiNezio, P., and Deser, C.: Evolving Impacts of Multiyear La Niña Events on Atmospheric Circulation and U.S. Drought, Geophys. Res. Lett., 44, 11614–11623, https://doi.org/10.1002/2017GL075034, 2017.
Palmer, W.: Meteorological drought, US Weather Bureau, Research Paper 45, 58 pp., https://www.droughtmanagement.info/literature/USWB_Meteorological_Drought_1965.pdf (last access: 21 May 2024), 1965.
Peña-Gallardo, M., Vicente-Serrano, S. M., Hannaford, J., Lorenzo-Lacruz, J., Svoboda, M., Domínguez-Castro, F., Maneta, M., Tomas-Burguera, M., and Kenawy, A. El: Complex influences of meteorological drought time-scales on hydrological droughts in natural basins of the contiguous Unites States, J. Hydrol., 568, 611–625, https://doi.org/10.1016/j.jhydrol.2018.11.026, 2019.
Peters, A. J., Walter-Shea, E. A., Ji, L., Viña, A., Hayes, M., and Svoboda, M. D.: Drought monitoring with NDVI-based Standardized Vegetation Index, Photogramm. Eng. Remote, 68, 71–75, 2002.
Peters-Lidard, C. D., Mocko, D. M., Su, L., Lettenmaier, D. P., Gentine, P., and Barlage, M.: Advances in land surface models and indicators for drought monitoring and prediction, B. Am. Meteorol. Soc., 102, E1099–E1122, https://doi.org/10.1175/BAMS-D-20-0087.1, 2021.
Pokhrel, Y., Felfelani, F., Satoh, Y., Boulange, J., Burek, P., Gädeke, A., Gerten, D., Gosling, S. N., Grillakis, M., Gudmundsson, L., Hanasaki, N., Kim, H., Koutroulis, A., Liu, J., Papadimitriou, L., Schewe, J., Müller Schmied, H., Stacke, T., Telteu, C. E., Thiery, W., Veldkamp, T., Zhao, F., and Wada, Y.: Global terrestrial water storage and drought severity under climate change, Nat. Clim. Change, 11, 226–233, https://doi.org/10.1038/s41558-020-00972-w, 2021.
Rakovec, O., Kumar, R., Attinger, S., and Samaniego, L.: Improving the realism of hydrologic model functioning through multivariate parameter estimation, Water Resour. Res., 52, 7779–7792, https://doi.org/10.1002/2016WR019430, 2016.
Rakovec, O., Samaniego, L., Hari, V., Markonis, Y., Moravec, V., Thober, S., Hanel, M., and Kumar, R.: The 2018–2020 Multi-Year Drought Sets a New Benchmark in Europe, Earth's Future, 10, 1–11, https://doi.org/10.1029/2021EF002394, 2022.
Raupach, M. R.: Simplified expressions for vegetation roughness length and zero-plane displacement as functions of canopy height and area index, Bound.-Lay. Meteorol., 71, 211–216, https://doi.org/10.1007/BF00709229, 1994.
Rivera, J. A., Otta, S., Lauro, C., and Zazulie, N.: A Decade of Hydrological Drought in Central-Western Argentina, Front. Water, 3, 1–20, https://doi.org/10.3389/frwa.2021.640544, 2021.
Samaniego, L., Kumar, R., and Zink, M.: Implications of parameter uncertainty on soil moisture drought analysis in Germany, J. Hydrometeorol., 14, 47–68, https://doi.org/10.1175/JHM-D-12-075.1, 2013.
Sawicz, K., Wagener, T., Sivapalan, M., Troch, P. A., and Carrillo, G.: Catchment classification: empirical analysis of hydrologic similarity based on catchment function in the eastern USA, Hydrol. Earth Syst. Sci., 15, 2895–2911, https://doi.org/10.5194/hess-15-2895-2011, 2011.
Schumacher, D. L., Keune, J., Dirmeyer, P., and Miralles, D. G.: Drought self-propagation in drylands due to land–atmosphere feedbacks, Nat. Geosci., 15, 262–268, https://doi.org/10.1038/s41561-022-00912-7, 2022.
Seibert, M., Merz, B., and Apel, H.: Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods, Hydrol. Earth Syst. Sci., 21, 1611–1629, https://doi.org/10.5194/hess-21-1611-2017, 2017.
Sepulcre-Canto, G., Horion, S., Singleton, A., Carrao, H., and Vogt, J.: Development of a Combined Drought Indicator to detect agricultural drought in Europe, Nat. Hazards Earth Syst. Sci., 12, 3519–3531, https://doi.org/10.5194/nhess-12-3519-2012, 2012.
Sheffield, J. and Wood, E. F.: Characteristics of global and regional drought, 1950–2000: Analysis of soil moisture data from off-line simulation of the terrestrial hydrologic cycle, J. Geophys. Res. Atmospheres, 112, D17115, https://doi.org/10.1029/2006JD008288, 2007.
Shen, H., Tolson, B. A., and Mai, J.: Time to Update the Split‐Sample Approach in Hydrological Model Calibration, Water Resour. Res., 58, 1–26, https://doi.org/10.1029/2021wr031523, 2022.
Shukla, S. and Wood, A. W.: Use of a standardized runoff index for characterizing hydrologic drought, Geophys. Res. Lett., 35, 1–7, https://doi.org/10.1029/2007GL032487, 2008.
Stagge, J. H., Tallaksen, L. M., Gudmundsson, L., Van Loon, A. F., and Stahl, K.: Candidate Distributions for Climatological Drought Indices (SPI and SPEI), Int. J. Climatol., 35, 4027–4040, https://doi.org/10.1002/joc.4267, 2015.
Stahl, K., Vidal, J.-P., Hannaford, J., Tijdeman, E., Laaha, G., Gauster, T., and Tallaksen, L. M.: The challenges of hydrological drought definition, quantification and communication: an interdisciplinary perspective, Proc. IAHS, 383, 291–295, https://doi.org/10.5194/piahs-383-291-2020, 2020.
Steiger, N. J., Smerdon, J. E., Seager, R., Williams, A. P., and Varuolo-Clarke, A. M.: ENSO-driven coupled megadroughts in North and South America over the last millennium, Nat. Geosci., 14, 739–744, https://doi.org/10.1038/s41561-021-00819-9, 2021.
Sutanto, S. J. and Van Lanen, H. A. J.: Streamflow drought: implication of drought definitions and its application for drought forecasting, Hydrol. Earth Syst. Sci., 25, 3991–4023, https://doi.org/10.5194/hess-25-3991-2021, 2021.
Sutanto, S. J. and Van Lanen, H. A. J.: Catchment memory explains hydrological drought forecast performance, Sci. Rep., 12, 1–11, https://doi.org/10.1038/s41598-022-06553-5, 2022.
Svensson, C., Hannaford, J., and Prosdocimi, I.: Statistical distributions for monthly aggregations of precipitation and streamflow in drought indicator applications, Water Resour. Res., 53, 999–1018, https://doi.org/10.1002/2016WR019276, 2017.
Svoboda, M. and Fuchs, B.: Handbook of Drought Indicators and Indices, World Meteorological Organization (WMO) and Global Water Partnership (GWP), Integrated Drought Management Programme (IDMP), Integrated Drought Management Tools and Guidelines Series 2, Geneva, ISBN 978-92-63-11173-9, https://www.droughtmanagement.info/literature/GWP_Handbook_of_Drought_Indicators_and_Indices_2016.pdf (last access: 5 January 2025), 2016.
Svoboda, M., LeComte, D., Hayes, M., Heim, R., Gleason, K., Angel, J., Rippey, B., Tinker, R., Palecki, M., Stooksbury, D., Miskus, D., and Stephens, S.: THE DROUGHT MONITOR, B. Am. Meteorol. Soc., 83, 1181–1190, https://doi.org/10.1175/1520-0477-83.8.1181, 2002.
Tallaksen, L. M. and Van Lanen, H. A. J.: Hydrological Drought Processes and Estimation Methods for Streamflow and Groundwater. Developments in Water Science, 48, Elsevier Science B.V., 579 pp., http://europeandroughtcentre.com/resources/hydrological-drought-1st-edition/ (last access: 20 December 2023), 2004.
Teutschbein, C., Quesada Montano, B., Todorović, A., and Grabs, T.: Streamflow droughts in Sweden: Spatiotemporal patterns emerging from six decades of observations, J. Hydrol.: Regional Studies, 42, 101171, https://doi.org/10.1016/j.ejrh.2022.101171, 2022.
Thober, S., Kumar, R., Sheffield, J., Mai, J., Schäfer, D., and Samaniego, L.: Seasonal Soil Moisture Drought Prediction over Europe Using the North American Multi-Model Ensemble (NMME), J. Hydrometeorol., 16, 2329–2344, https://doi.org/10.1175/JHM-D-15-0053.1, 2015.
Thornthwaite, C. W.: An Approach Toward a Rational Classification of Climate, Geogr. Rev., 38, 55–94, 1948.
Tijdeman, E., Stahl, K., and Tallaksen, L. M.: Drought Characteristics Derived Based on the Standardized Streamflow Index: A Large Sample Comparison for Parametric and Nonparametric Methods, Water Resour. Res., 56, e2019WR026315, https://doi.org/10.1029/2019WR026315, 2020.
Tokarska, K. B., Stolpe, M. B., Sippel, S., Fischer, E. M., Smith, C. J., Lehner, F., and Knutti, R.: Past warming trend constrains future warming in CMIP6 models, Sci. Adv., 6, 1–14, https://doi.org/10.1126/sciadv.aaz9549, 2020.
Tolson, B. A. and Shoemaker, C. A.: Dynamically dimensioned search algorithm for computationally efficient watershed model calibration, Water Resour. Res., 43, 1–16, https://doi.org/10.1029/2005WR004723, 2007.
Trenberth, K. E., Dai, A., Van Der Schrier, G., Jones, P. D., Barichivich, J., Briffa, K. R., and Sheffield, J.: Global warming and changes in drought, Nat. Clim. Change, 4, 17–22, https://doi.org/10.1038/nclimate2067, 2014.
van der Knijff, J. M., Younis, J., and de Roo, A. P. J.: LISFLOOD: A GIS-based distributed model for river basin scale water balance and flood simulation, Int. J. Geogr. Inf. Sci., 24, 189–212, https://doi.org/10.1080/13658810802549154, 2010.
Van Loon, A.: Hydrological drought explained, Wiley Interdisciplinary Reviews: Water, 2, 359–392, https://doi.org/10.1002/WAT2.1085, 2015.
Van Loon, A. and Laaha, G.: Hydrological drought severity explained by climate and catchment characteristics, J. Hydrol., 526, 3–14, https://doi.org/10.1016/j.jhydrol.2014.10.059, 2015.
Van Loon, A. F. and Van Lanen, H. A. J.: A process-based typology of hydrological drought, Hydrol. Earth Syst. Sci., 16, 1915–1946, https://doi.org/10.5194/hess-16-1915-2012, 2012.
Van Loon, A., Tijdeman, E., Wanders, N., Van Lanen, H. A. J., Teuling, A. J., and Uijlenhoet, R.: How climate seasonality modifies drought duration and deficit, J. Geophys. Res., 119, 4640–4656, https://doi.org/10.1002/2013JD020383, 2014.
Vásquez, N., Cepeda, J., Gómez, T., Mendoza, P. A., Lagos, M., Boisier, J. P., Álvarez-Garretón, C., and Vargas, X.: Catchment- Scale Natural Water Balance in Chile, in: Water Resources of Chile. World Water Resources, edited by: Fernández, B. and Gironás, J., vol. 8, Springer, Cham, https://doi.org/10.1007/978-3-030-56901-3_9, 2021.
Vicente-Serrano, S. M., Beguería, S., and López-Moreno, J. I.: A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index, J. Climate, 23, 1696–1718, https://doi.org/10.1175/2009JCLI2909.1, 2010.
Vicente-Serrano, S. M., López-Moreno, J. I., Beguería, S., Lorenzo-Lacruz, J., Azorin-Molina, C., and Morán-Tejeda, E.: Accurate Computation of a Streamflow Drought Index, J. Hydrol. Eng., 17, 318–332, https://doi.org/10.1061/(asce)he.1943-5584.0000433, 2012.
Vicente-Serrano, S. M., Quiring, S. M., Peña-Gallardo, M., Yuan, S., and Domínguez-Castro, F.: A review of environmental droughts: Increased risk under global warming?, Earth-Sci. Rev., 201, 102953, https://doi.org/10.1016/j.earscirev.2019.102953, 2020.
Wan, W., Zhao, J., Li, H. Y., Mishra, A., Hejazi, M., Lu, H., Demissie, Y., and Wang, H.: A Holistic View of Water Management Impacts on Future Droughts: A Global Multimodel Analysis, J. Geophys. Res.-Atmos., 123, 5947–5972, https://doi.org/10.1029/2017JD027825, 2018.
Wanders, N., Wada, Y., and Van Lanen, H. A. J.: Global hydrological droughts in the 21st century under a changing hydrological regime, Earth Syst. Dynam., 6, 1–15, https://doi.org/10.5194/esd-6-1-2015, 2015.
Wang, F., Wang, Z., Yang, H., Di, D., Zhao, Y., Liang, Q., and Hussain, Z.: Comprehensive evaluation of hydrological drought and its relationships with meteorological drought in the Yellow River basin, China, J. Hydrol., 584, 124751, https://doi.org/10.1016/j.jhydrol.2020.124751, 2020.
Wilhite, D. A. and Pulwarty, R. S. (Eds.): Drought and Water Crises: integrating science, management and policy, 2nd edn., CRC Press, Boca Raton, https://doi.org/10.1201/b22009, 2017.
Wilhite, D. A. and Glantz, M. H.: Understanding the drought phenomenon: The role of definitions, Water Int., 10, 10, 111–120, https://doi.org/10.4324/9780429301735-2, 1985.
Wu, J., Chen, X., Yao, H., Gao, L., Chen, Y., and Liu, M.: Non-linear relationship of hydrological drought responding to meteorological drought and impact of a large reservoir, J. Hydrol., 551, 495–507, https://doi.org/10.1016/j.jhydrol.2017.06.029, 2017.
Wu, J., Chen, X., Yao, H., Liu, Z., and Zhang, D.: Hydrological Drought Instantaneous Propagation Speed Based on the Variable Motion Relationship of Speed-Time Process, Water Resour. Res., 54, 9549–9565, https://doi.org/10.1029/2018WR023120, 2018.
Wu, J., Yao, H., Chen, X., Wang, G., Bai, X., and Zhang, D.: A framework for assessing compound drought events from a drought propagation perspective, J. Hydrol., 604, 127228, https://doi.org/10.1016/j.jhydrol.2021.127228, 2022.
Yun, X., Tang, Q., Wang, J., Li, J., Li, Y., and Bao, H.: Reservoir operation affects propagation from meteorological to hydrological extremes in the Lancang-Mekong River Basin, Sci. Total Environ., 896, 165297, https://doi.org/10.1016/j.scitotenv.2023.165297, 2023.
Zhang, X., Hao, Z., Singh, V. P., Zhang, Y., Feng, S., Xu, Y., and Hao, F.: Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors, Sci. Total Environ., 838, 156021, https://doi.org/10.1016/j.scitotenv.2022.156021, 2022.
Zhu, Y., Wang, W., Singh, V. P., and Liu, Y.: Combined use of meteorological drought indices at multi-time scales for improving hydrological drought detection, Sci. Total Environ., 571, 1058–1068, https://doi.org/10.1016/j.scitotenv.2016.07.096, 2016.
Zink, M., Samaniego, L., Kumar, R., Thober, S., Mai, J., Schafer, D., and Marx, A.: The German drought monitor, Environ. Res. Lett., 11, 074002, https://doi.org/10.1088/1748-9326/11/7/074002, 2016.
Short summary
Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite the fact that they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what they truly reflect in terms of water cycle processes. Here, we used state-of-the-art hydrological models in Andean basins to examine drivers of SSI fluctuations. The results highlight the importance of careful selection of indices and timescales for accurate drought characterization and monitoring.
Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite the fact...
