Articles | Volume 29, issue 22
https://doi.org/10.5194/hess-29-6715-2025
© 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-29-6715-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Torrential rainfall in Valencia, Spain, recorded by personal weather stations preceding and during the 29 October 2024 floods
Department of Water Management, Delft University of Technology, the Netherlands
Markus Hrachowitz
Department of Water Management, Delft University of Technology, the Netherlands
Remko Uijlenhoet
Department of Water Management, Delft University of Technology, the Netherlands
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Hydrol. Earth Syst. Sci., 29, 4585–4606, https://doi.org/10.5194/hess-29-4585-2025, https://doi.org/10.5194/hess-29-4585-2025, 2025
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Rain gauge networks from personal weather stations (PWSs) have a network density 100 times higher than dedicated rain gauge networks in the Netherlands. However, PWSs are prone to several sources of error, as they are generally not installed and maintained according to international guidelines. This study systematically quantifies and describes the uncertainties arising from PWS rainfall estimates. In particular, the focus is on the highest rainfall accumulations.
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Severe weather such as hail, lightning, and heavy rainfall can be hazardous to humans and property. Dual-polarization weather radars provide crucial information to forecast these events by detecting precipitation types. This study analyses the importance of dual-polarization data for predicting severe weather for 60 min using an existing deep learning model. The results indicate that including these variables improves the accuracy of predicting heavy rainfall and lightning.
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Hydrol. Earth Syst. Sci., 29, 6589–6606, https://doi.org/10.5194/hess-29-6589-2025, https://doi.org/10.5194/hess-29-6589-2025, 2025
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Commercial microwave links (CMLs), part of mobile phone networks, transmit comparable signals as instruments specially designed to estimate evaporation. Therefore, we investigate if CMLs could be used to estimate evaporation, even though they have not been designed for this purpose. Our results illustrate the potential of using CMLs to estimate evaporation, especially given their global coverage, but also outline some major drawbacks, often a consequence of unfavourable design choices for CMLs.
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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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This study explores the use the signal attenuation of cellular communication networks, combined with machine learning approaches, to observe fog events. We use the McFly software package that selects the most appropriate machine leaning technique (out of ~20 available techniques) based on small samples of the input datasets. This approach is developed for a microwave link over Wageningen in The Netherlands, while in a second part of the paper the approach is upscaled to the whole country.
Luuk D. van der Valk, Oscar K. Hartogensis, Miriam Coenders-Gerrits, Rolf W. Hut, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 18, 6143–6165, https://doi.org/10.5194/amt-18-6143-2025, https://doi.org/10.5194/amt-18-6143-2025, 2025
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Commercial microwave links (CMLs), part of mobile phone networks, transmit comparable signals to instruments specially designed to estimate evaporation. Therefore, we investigate if CMLs could be used to estimate evaporation, even though they have not been designed for this purpose. Our results illustrate the potential for using CMLs to estimate evaporation, especially given their global coverage, but also outline some major drawbacks, often a consequence of unfavourable design choices for CMLs.
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Hatice Türk, Christine Stumpp, Markus Hrachowitz, Karsten Schulz, Peter Strauss, Günter Blöschl, and Michael Stockinger
Hydrol. Earth Syst. Sci., 29, 3935–3956, https://doi.org/10.5194/hess-29-3935-2025, https://doi.org/10.5194/hess-29-3935-2025, 2025
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Using advances in transit time estimation and tracer data, we tested if fast-flow transit times are controlled solely by soil moisture or if they are also controlled by precipitation intensity. We used soil-moisture-dependent and precipitation-intensity-conditional transfer functions. We showed that a significant portion of event water bypasses the soil matrix through fast flow paths (overland flow, tile drains, preferential-flow paths) in dry soil conditions for both low- and high-intensity precipitation.
Magali Ponds, Sarah Hanus, Harry Zekollari, Marie-Claire ten Veldhuis, Gerrit Schoups, Roland Kaitna, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 3545–3568, https://doi.org/10.5194/hess-29-3545-2025, https://doi.org/10.5194/hess-29-3545-2025, 2025
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This research examines how future climate changes impact root zone storage, a key hydrological model parameter. Root zone storage – the soil water accessible to plants – adapts to climate but is often kept constant in models. We estimated climate-adapted storage in six Austrian Alps catchments. While storage increased, streamflow projections showed minimal change, which suggests that dynamic root zone representation is less critical in humid regions but warrants further study in arid areas.
Xuan Chen, Job Augustijn van der Werf, Arjan Droste, Miriam Coenders-Gerrits, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 29, 3447–3480, https://doi.org/10.5194/hess-29-3447-2025, https://doi.org/10.5194/hess-29-3447-2025, 2025
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The review highlights the need to integrate urban land surface and hydrological models to better predict and manage compound climate events in cities. We find that inadequate representation of water surfaces, hydraulic systems and detailed building representations are key areas for improvement in future models. Coupled models show promise but face challenges at regional and neighbourhood scales. Interdisciplinary communication is crucial to enhance urban hydrometeorological simulations.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-2597, https://doi.org/10.5194/egusphere-2025-2597, 2025
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This study shows that stream flow isotope data (δ2H) were inadequate for distinguishing preferential groundwater flow. Large passive groundwater storage dampened δ2H variations, obscuring signals of fast groundwater flow and complicating the estimation of older water fractions in the streams. Further, weekly-resolution δ2H sampling yielded deceptively high model performance, highlighting the need for complementary and groundwater-level data to improve catchment-scale transit-time estimates.
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In lowland catchments, flood severity is determined by both the amount of rain and how wet the soil is prior to the rain event. We investigated the trade-off between these two factors and how this affects peaks in the river discharge, for both the current and future climate. We found that with climate change floods will increase in winter and spring, but decease in fall. The total number and severity of floods will increase. This can help water managers to design climate robust water management.
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025, https://doi.org/10.5194/hess-29-1703-2025, 2025
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The quantification of precipitation into evaporation and runoff is vital for water resources management. The Budyko framework, based on aridity and evaporative indices of a catchment, can be an ideal tool for that. However, recent research highlights deviations of catchments from the expected evaporative index, casting doubt on its reliability. This study quantifies deviations of 2387 catchments, finding them minor and predictable. Integrating these into predictions upholds the framework's efficacy.
Wouter R. Berghuijs, Ross A. Woods, Bailey J. Anderson, Anna Luisa Hemshorn de Sánchez, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1319–1333, https://doi.org/10.5194/hess-29-1319-2025, https://doi.org/10.5194/hess-29-1319-2025, 2025
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Water balances of catchments will often strongly depend on their state in the recent past, but such memory effects may persist at annual timescales. We use global data sets to show that annual memory is typically absent in precipitation but strong in terrestrial water stores and also present in evaporation and streamflow (including low flows and floods). Our experiments show that hysteretic models provide behaviour that is consistent with these observed memory behaviours.
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Hydrol. Earth Syst. Sci., 29, 127–158, https://doi.org/10.5194/hess-29-127-2025, https://doi.org/10.5194/hess-29-127-2025, 2025
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Abbas El Hachem, Jochen Seidel, Tess O'Hara, Roberto Villalobos Herrera, Aart Overeem, Remko Uijlenhoet, András Bárdossy, and Lotte de Vos
Hydrol. Earth Syst. Sci., 28, 4715–4731, https://doi.org/10.5194/hess-28-4715-2024, https://doi.org/10.5194/hess-28-4715-2024, 2024
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This study presents an overview of open-source quality control (QC) algorithms for rainfall data from personal weather stations (PWSs). The methodology and usability along technical and operational guidelines for using every QC algorithm are presented. All three QC algorithms are available for users to explore in the OpenSense sandbox. They were applied in a case study using PWS data from the Amsterdam region in the Netherlands. The results highlight the necessity for data quality control.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
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This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Hongkai Gao, Markus Hrachowitz, Lan Wang-Erlandsson, Fabrizio Fenicia, Qiaojuan Xi, Jianyang Xia, Wei Shao, Ge Sun, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 4477–4499, https://doi.org/10.5194/hess-28-4477-2024, https://doi.org/10.5194/hess-28-4477-2024, 2024
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The concept of the root zone is widely used but lacks a precise definition. Its importance in Earth system science is not well elaborated upon. Here, we clarified its definition with several similar terms to bridge the multi-disciplinary gap. We underscore the key role of the root zone in the Earth system, which links the biosphere, hydrosphere, lithosphere, atmosphere, and anthroposphere. To better represent the root zone, we advocate for a paradigm shift towards ecosystem-centred modelling.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
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Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Athanasios Tsiokanos, Martine Rutten, Ruud J. van der Ent, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 28, 3327–3345, https://doi.org/10.5194/hess-28-3327-2024, https://doi.org/10.5194/hess-28-3327-2024, 2024
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We focus on past high-flow events to find flood drivers in the Geul. We also explore flood drivers’ trends across various timescales and develop a new method to detect the main direction of a trend. Our results show that extreme 24 h precipitation alone is typically insufficient to cause floods. The combination of extreme rainfall and wet initial conditions determines the chance of flooding. Precipitation that leads to floods increases in winter, whereas no consistent trends are found in summer.
Fransje van Oorschot, Ruud J. van der Ent, Andrea Alessandri, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 2313–2328, https://doi.org/10.5194/hess-28-2313-2024, https://doi.org/10.5194/hess-28-2313-2024, 2024
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Vegetation plays a crucial role in regulating the water cycle by transporting water from the subsurface to the atmosphere via roots; this transport depends on the extent of the root system. In this study, we quantified the effect of irrigation on roots at a global scale. Our results emphasize the importance of accounting for irrigation in estimating the vegetation root extent, which is essential to adequately represent the water cycle in hydrological and climate models.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024, https://doi.org/10.5194/amt-17-2811-2024, 2024
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Microwave links, often part of mobile phone networks, can be used to measure rainfall along the link path by determining the signal loss caused by rainfall. We use high-frequency data of multiple microwave links to recreate commonly used sampling strategies. For time intervals up to 1 min, the influence of sampling strategies on estimated rainfall intensities is relatively little, while for intervals longer than 5–15 min, the sampling strategy can have significant influences on the estimates.
Louise J. Schreyers, Tim H. M. van Emmerik, Thanh-Khiet L. Bui, Khoa L. van Thi, Bart Vermeulen, Hong-Q. Nguyen, Nicholas Wallerstein, Remko Uijlenhoet, and Martine van der Ploeg
Hydrol. Earth Syst. Sci., 28, 589–610, https://doi.org/10.5194/hess-28-589-2024, https://doi.org/10.5194/hess-28-589-2024, 2024
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River plastic emissions into the ocean are of global concern, but the transfer dynamics between fresh water and the marine environment remain poorly understood. We developed a simple Eulerian approach to estimate the net and total plastic transport in tidal rivers. Applied to the Saigon River, Vietnam, we found that net plastic transport amounted to less than one-third of total transport, highlighting the need to better integrate tidal dynamics in plastic transport and emission models.
Nathalie Rombeek, Jussi Leinonen, and Ulrich Hamann
Nat. Hazards Earth Syst. Sci., 24, 133–144, https://doi.org/10.5194/nhess-24-133-2024, https://doi.org/10.5194/nhess-24-133-2024, 2024
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Severe weather such as hail, lightning, and heavy rainfall can be hazardous to humans and property. Dual-polarization weather radars provide crucial information to forecast these events by detecting precipitation types. This study analyses the importance of dual-polarization data for predicting severe weather for 60 min using an existing deep learning model. The results indicate that including these variables improves the accuracy of predicting heavy rainfall and lightning.
Linda Bogerd, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 247–259, https://doi.org/10.5194/amt-17-247-2024, https://doi.org/10.5194/amt-17-247-2024, 2024
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Algorithms merge satellite radiometer data from various frequency channels, each tied to a different footprint size. We studied the uncertainty associated with sampling (over the Netherlands using 4 years of data) as precipitation is highly variable in space and time by simulating ground-based data as satellite footprints. Though sampling affects precipitation estimates, it doesn’t explain all discrepancies. Overall, uncertainties in the algorithm seem more influential than how data is sampled.
Bich Ngoc Tran, Johannes van der Kwast, Solomon Seyoum, Remko Uijlenhoet, Graham Jewitt, and Marloes Mul
Hydrol. Earth Syst. Sci., 27, 4505–4528, https://doi.org/10.5194/hess-27-4505-2023, https://doi.org/10.5194/hess-27-4505-2023, 2023
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Satellite data are increasingly used to estimate evapotranspiration (ET) or the amount of water moving from plants, soils, and water bodies into the atmosphere over large areas. Uncertainties from various sources affect the accuracy of these calculations. This study reviews the methods to assess the uncertainties of such ET estimations. It provides specific recommendations for a comprehensive assessment that assists in the potential uses of these data for research, monitoring, and management.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, Emanuele Di Carlo, Franco Catalano, Souhail Boussetta, Gianpaolo Balsamo, and Andrea Alessandri
Earth Syst. Dynam., 14, 1239–1259, https://doi.org/10.5194/esd-14-1239-2023, https://doi.org/10.5194/esd-14-1239-2023, 2023
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Vegetation largely controls land hydrology by transporting water from the subsurface to the atmosphere through roots and is highly variable in space and time. However, current land surface models have limitations in capturing this variability at a global scale, limiting accurate modeling of land hydrology. We found that satellite-based vegetation variability considerably improved modeled land hydrology and therefore has potential to improve climate predictions of, for example, droughts.
Siyuan Wang, Markus Hrachowitz, Gerrit Schoups, and Christine Stumpp
Hydrol. Earth Syst. Sci., 27, 3083–3114, https://doi.org/10.5194/hess-27-3083-2023, https://doi.org/10.5194/hess-27-3083-2023, 2023
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This study shows that previously reported underestimations of water ages are most likely not due to the use of seasonally variable tracers. Rather, these underestimations can be largely attributed to the choices of model approaches which rely on assumptions not frequently met in catchment hydrology. We therefore strongly advocate avoiding the use of this model type in combination with seasonally variable tracers and instead adopting StorAge Selection (SAS)-based or comparable model formulations.
Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 5971–5986, https://doi.org/10.5194/hess-26-5971-2022, https://doi.org/10.5194/hess-26-5971-2022, 2022
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We test whether coupling a global glacier model (GloGEM) with a global hydrological model (PCR-GLOBWB 2) leads to a more realistic glacier representation and to improved basin runoff simulations across 25 large-scale basins. The coupling does lead to improved glacier representation, mainly by accounting for glacier flow and net glacier mass loss, and to improved basin runoff simulations, mostly in strongly glacier-influenced basins, which is where the coupling has the most impact.
Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, Jaap Schellekens, Frederiek Sperna Weiland, Markus Hrachowitz, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 22, 3641–3661, https://doi.org/10.5194/nhess-22-3641-2022, https://doi.org/10.5194/nhess-22-3641-2022, 2022
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This study compared gauge-based and satellite-based precipitation products. Similarly, satellite- and hydrological model-derived soil moisture was compared to in situ soil moisture and used in landslide hazard assessment and warning. The results reveal the cumulative 3 d rainfall from the NASA-GPM to be the most effective landslide trigger. The modelled antecedent soil moisture in the root zone was the most informative hydrological variable for landslide hazard assessment and warning in Rwanda.
Femke A. Jansen, Remko Uijlenhoet, Cor M. J. Jacobs, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 26, 2875–2898, https://doi.org/10.5194/hess-26-2875-2022, https://doi.org/10.5194/hess-26-2875-2022, 2022
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We studied the controls on open water evaporation with a focus on Lake IJssel, the Netherlands, by analysing eddy covariance observations over two summer periods at two locations at the borders of the lake. Wind speed and the vertical vapour pressure gradient can explain most of the variation in observed evaporation, which is in agreement with Dalton's model. We argue that the distinct characteristics of inland waterbodies need to be taken into account when parameterizing their evaporation.
Judith Uwihirwe, Markus Hrachowitz, and Thom Bogaard
Nat. Hazards Earth Syst. Sci., 22, 1723–1742, https://doi.org/10.5194/nhess-22-1723-2022, https://doi.org/10.5194/nhess-22-1723-2022, 2022
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This research tested the value of regional groundwater level information to improve landslide predictions with empirical models based on the concept of threshold levels. In contrast to precipitation-based thresholds, the results indicated that relying on threshold models exclusively defined using hydrological variables such as groundwater levels can lead to improved landslide predictions due to their implicit consideration of long-term antecedent conditions until the day of landslide occurrence.
Elisa Ragno, Markus Hrachowitz, and Oswaldo Morales-Nápoles
Hydrol. Earth Syst. Sci., 26, 1695–1711, https://doi.org/10.5194/hess-26-1695-2022, https://doi.org/10.5194/hess-26-1695-2022, 2022
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We explore the ability of non-parametric Bayesian networks to reproduce maximum daily discharge in a given month in a catchment when the remaining hydro-meteorological and catchment attributes are known. We show that a saturated network evaluated in an individual catchment can reproduce statistical characteristics of discharge in about ~ 40 % of the cases, while challenges remain when a saturated network considering all the catchments together is evaluated.
Laurène J. E. Bouaziz, Emma E. Aalbers, Albrecht H. Weerts, Mark Hegnauer, Hendrik Buiteveld, Rita Lammersen, Jasper Stam, Eric Sprokkereef, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 26, 1295–1318, https://doi.org/10.5194/hess-26-1295-2022, https://doi.org/10.5194/hess-26-1295-2022, 2022
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Assuming stationarity of hydrological systems is no longer appropriate when considering land use and climate change. We tested the sensitivity of hydrological predictions to changes in model parameters that reflect ecosystem adaptation to climate and potential land use change. We estimated a 34 % increase in the root zone storage parameter under +2 K global warming, resulting in up to 15 % less streamflow in autumn, due to 14 % higher summer evaporation, compared to a stationary system.
Wagner Wolff, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 15, 485–502, https://doi.org/10.5194/amt-15-485-2022, https://doi.org/10.5194/amt-15-485-2022, 2022
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The existing infrastructure for cellular communication is promising for ground-based rainfall remote sensing. Rain-induced signal attenuation is used in dedicated algorithms for retrieving rainfall depth along commercial microwave links (CMLs) between cell phone towers. This processing is a source of many uncertainties about input data, algorithm structures, parameters, CML network, and local climate. Application of a stochastic optimization method leads to improved CML rainfall estimates.
Markus Hrachowitz, Michael Stockinger, Miriam Coenders-Gerrits, Ruud van der Ent, Heye Bogena, Andreas Lücke, and Christine Stumpp
Hydrol. Earth Syst. Sci., 25, 4887–4915, https://doi.org/10.5194/hess-25-4887-2021, https://doi.org/10.5194/hess-25-4887-2021, 2021
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Deforestation affects how catchments store and release water. Here we found that deforestation in the study catchment led to a 20 % increase in mean runoff, while reducing the vegetation-accessible water storage from about 258 to 101 mm. As a consequence, fractions of young water in the stream increased by up to 25 % during wet periods. This implies that water and solutes are more rapidly routed to the stream, which can, after contamination, lead to increased contaminant peak concentrations.
Ruben Imhoff, Claudia Brauer, Klaas-Jan van Heeringen, Hidde Leijnse, Aart Overeem, Albrecht Weerts, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 25, 4061–4080, https://doi.org/10.5194/hess-25-4061-2021, https://doi.org/10.5194/hess-25-4061-2021, 2021
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Significant biases in real-time radar rainfall products limit the use for hydrometeorological forecasting. We introduce CARROTS (Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting), a set of fixed bias reduction factors to correct radar rainfall products and to benchmark other correction algorithms. When tested for 12 Dutch basins, estimated rainfall and simulated discharges with CARROTS generally outperform those using the operational mean field bias adjustments.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, and Andrea Alessandri
Earth Syst. Dynam., 12, 725–743, https://doi.org/10.5194/esd-12-725-2021, https://doi.org/10.5194/esd-12-725-2021, 2021
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The roots of vegetation largely control the Earth's water cycle by transporting water from the subsurface to the atmosphere but are not adequately represented in land surface models, causing uncertainties in modeled water fluxes. We replaced the root parameters in an existing model with more realistic ones that account for a climate control on root development and found improved timing of modeled river discharge. Further extension of our approach could improve modeled water fluxes globally.
Sarah Hanus, Markus Hrachowitz, Harry Zekollari, Gerrit Schoups, Miren Vizcaino, and Roland Kaitna
Hydrol. Earth Syst. Sci., 25, 3429–3453, https://doi.org/10.5194/hess-25-3429-2021, https://doi.org/10.5194/hess-25-3429-2021, 2021
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This study investigates the effects of climate change on runoff patterns in six Alpine catchments in Austria at the end of the 21st century. Our results indicate a substantial shift to earlier occurrences in annual maximum and minimum flows in high-elevation catchments. Magnitudes of annual extremes are projected to increase under a moderate emission scenario in all catchments. Changes are generally more pronounced for high-elevation catchments.
Simone Gelsinari, Valentijn R. N. Pauwels, Edoardo Daly, Jos van Dam, Remko Uijlenhoet, Nicholas Fewster-Young, and Rebecca Doble
Hydrol. Earth Syst. Sci., 25, 2261–2277, https://doi.org/10.5194/hess-25-2261-2021, https://doi.org/10.5194/hess-25-2261-2021, 2021
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Estimates of recharge to groundwater are often driven by biophysical processes occurring in the soil column and, particularly in remote areas, are also always affected by uncertainty. Using data assimilation techniques to merge remotely sensed observations with outputs of numerical models is one way to reduce this uncertainty. Here, we show the benefits of using such a technique with satellite evapotranspiration rates and coupled hydrogeological models applied to a semi-arid site in Australia.
Artemis Roodari, Markus Hrachowitz, Farzad Hassanpour, and Mostafa Yaghoobzadeh
Hydrol. Earth Syst. Sci., 25, 1943–1967, https://doi.org/10.5194/hess-25-1943-2021, https://doi.org/10.5194/hess-25-1943-2021, 2021
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In a combined data analysis and modeling study in the transboundary Helmand River basin, we analyzed spatial patterns of drought and changes therein based on the drought indices as well as on absolute water deficits. Overall the results illustrate that flow deficits and the associated droughts clearly reflect the dynamic interplay between temporally varying regional differences in hydro-meteorological variables together with subtle and temporally varying effects linked to human intervention.
Laurène J. E. Bouaziz, Fabrizio Fenicia, Guillaume Thirel, Tanja de Boer-Euser, Joost Buitink, Claudia C. Brauer, Jan De Niel, Benjamin J. Dewals, Gilles Drogue, Benjamin Grelier, Lieke A. Melsen, Sotirios Moustakas, Jiri Nossent, Fernando Pereira, Eric Sprokkereef, Jasper Stam, Albrecht H. Weerts, Patrick Willems, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 1069–1095, https://doi.org/10.5194/hess-25-1069-2021, https://doi.org/10.5194/hess-25-1069-2021, 2021
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We quantify the differences in internal states and fluxes of 12 process-based models with similar streamflow performance and assess their plausibility using remotely sensed estimates of evaporation, snow cover, soil moisture and total storage anomalies. The dissimilarities in internal process representation imply that these models cannot all simultaneously be close to reality. Therefore, we invite modelers to evaluate their models using multiple variables and to rely on multi-model studies.
Petra Hulsman, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 957–982, https://doi.org/10.5194/hess-25-957-2021, https://doi.org/10.5194/hess-25-957-2021, 2021
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Satellite observations have increasingly been used for model calibration, while model structural developments largely rely on discharge data. For large river basins, this often results in poor representations of system internal processes. This study explores the combined use of satellite-based evaporation and total water storage data for model structural improvement and spatial–temporal model calibration for a large, semi-arid and data-scarce river system.
Jolijn van Engelenburg, Erik van Slobbe, Adriaan J. Teuling, Remko Uijlenhoet, and Petra Hellegers
Drink. Water Eng. Sci., 14, 1–43, https://doi.org/10.5194/dwes-14-1-2021, https://doi.org/10.5194/dwes-14-1-2021, 2021
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This study analysed the impact of extreme weather events, water quality deterioration, and a growing drinking water demand on the sustainability of drinking water supply in the Netherlands. The results of the case studies were compared to sustainability issues for drinking water supply that are experienced worldwide. This resulted in a set of sustainability characteristics describing drinking water supply on a local scale in terms of hydrological, technical, and socio-economic characteristics.
Ralf Loritz, Markus Hrachowitz, Malte Neuper, and Erwin Zehe
Hydrol. Earth Syst. Sci., 25, 147–167, https://doi.org/10.5194/hess-25-147-2021, https://doi.org/10.5194/hess-25-147-2021, 2021
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This study investigates the role and value of distributed rainfall in the runoff generation of a mesoscale catchment. We compare the performance of different hydrological models at different periods and show that a distributed model driven by distributed rainfall yields improved performances only during certain periods. We then step beyond this finding and develop a spatially adaptive model that is capable of dynamically adjusting its spatial model structure in time.
Cited articles
AEMET: Informe sobre el episodio meteorológico de precipitaciones torrenciales y persistentes ocasionadas por una DANA el día 29 de octubre de 2024, https://www.aemet.es/en/conocermas/recursos_en_linea/publicaciones_y_estudios/estudios/detalles/dana_oct_24_prelim (last access: November 2024), 2024a. a
Bárdossy, A. and Anwar, F.: Why do our rainfall–runoff models keep underestimating the peak flows?, Hydrol. Earth Syst. Sci., 27, 1987–2000, https://doi.org/10.5194/hess-27-1987-2023, 2023. a
Bárdossy, A., Seidel, J., and El Hachem, A.: The use of personal weather station observations to improve precipitation estimation and interpolation, Hydrol. Earth Syst. Sci., 25, 583–601, https://doi.org/10.5194/hess-25-583-2021, 2021. a, b
Brauer, C. C., Teuling, A. J., Overeem, A., van der Velde, Y., Hazenberg, P., Warmerdam, P. M. M., and Uijlenhoet, R.: Anatomy of extraordinary rainfall and flash flood in a Dutch lowland catchment, Hydrol. Earth Syst. Sci., 15, 1991–2005, https://doi.org/10.5194/hess-15-1991-2011, 2011. a
Camarasa-Belmonte, A. and Soriano-García, J.: Flood risk assessment and mapping in peri-urban Mediterranean environments using hydrogeomorphology. Application to ephemeral streams in the Valencia region (eastern Spain), Landscape Urban Plan., 104, 189–200, https://doi.org/10.1016/j.landurbplan.2011.10.009, 2012. a
Cecinati, F., Moreno-Ródenas, A. M., Rico-Ramirez, M. A., Ten Veldhuis, M.-C., and Langeveld, J. G.: Considering rain gauge uncertainty using kriging for uncertain data, Atmosphere, 9, 446, https://doi.org/10.3390/atmos9110446, 2018. a
Chazarra-Bernabé, A., Lorenzo Mariño, B., Belinchón Martín, F., Moreno García, J. V., and Romero Fresneda, R.: Mapas climáticos de España (1981–2020) y ETo (1996–2020), https://doi.org/10.31978/666-24-007-4, 2024. a, b
Copernicus Land Monitoring Service: EU-Hydro – River Network Database, European Environment Agency [data set], https://doi.org/10.2909/393359a7-7ebd-4a52-80ac-1a18d5f3db9c, 2019. a
Cornes, R. C., van der Schrier, G., van den Besselaar, E. J. M., and Jones, P. D.: An Ensemble Version of the E-OBS Temperature and Precipitation Data Sets, J. Geophys. Res.-Atmos., 123, 9391–9409, https://doi.org/10.1029/2017JD028200, 2018. a
Delhomme, J. P.: Kriging in the hydrosciences, Adv. Water Resour., 1, 251–266, https://doi.org/10.1016/0309-1708(78)90039-8, 1978. a
de Vos, L., Leijnse, H., Overeem, A., and Uijlenhoet, R.: The potential of urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam, Hydrol. Earth Syst. Sci., 21, 765–777, https://doi.org/10.5194/hess-21-765-2017, 2017. a, b, c
de Vos, L. W., Leijnse, H., Overeem, A., and Uijlenhoet, R.: Quality control for crowdsourced personal weather stations to enable operational rainfall monitoring, Geophys. Res. Lett., 46, 8820–8829, https://doi.org/10.1029/2019GL083731, 2019. a, b
do Nascimento, T. V. M., Rudlang, J., Höge, M., van der Ent, R., Chappon, M., Seibert, J., Hrachowitz, M., and Fenicia, F.: EStreams: An Integrated Dataset and Catalogue of Streamflow, Hydro-Climatic Variables and Landscape Descriptors for Europe (1.0), Zenodo [data set], https://doi.org/10.5281/zenodo.13154470, 2024. a, b, c, d, e
Efron, B. and Tibshirani, R. J.: An Introduction to the Bootstrap, 1st edn., Chapman and Hall/CRC, https://doi.org/10.1201/9780429246593, 1994. a
Egozcue, J. and Ramis, C.: Bayesian hazard analysis of heavy precipitation in eastern Spain, Int. J. Climatol., 21, 1263–1279, https://doi.org/10.1002/joc.688, 2001. a
European Space Agency: Copernicus Global Digital Elevation Model, distributed by OpenTopography [data set], https://doi.org/10.5069/G9028PQB, 2024. a
Faranda, D., Alvarez-Castro, M. C., Ginesta, M., Coppola, E., and Pons, F. M. E.: Heavy precipitations in October 2024 South-Eastern Spain DANA mostly strengthened by human-driven climate change, https://doi.org/10.5281/zenodo.14052042, 2024. a, b
Ferreira, R. N.: Cut-off lows and extreme precipitation in eastern Spain: Current and future climate, Atmosphere, 12, 835, https://doi.org/10.3390/atmos12070835, 2021. a
Gaume, E., Bain, V., Bernardara, P., Newinger, O., Barbuc, M., Bateman, A., Blaškovičová, L., Blöschl, G., Borga, M., Dumitrescu, A., Daliakopoulos, I., Garcia, J., Irimescu, A., Kohnova, S., Koutroulis, A., Marchi, L., Matreata, S., Medina, V., Preciso, E., Sempere-Torres, D., Stancalie, G., Szolgay, J., Tsanis, I., Velasco, D., and Viglione, A.: A compilation of data on European flash floods, J. Hydrol., 367, 70–78, https://doi.org/10.1016/j.jhydrol.2008.12.028, 2009. a
Germann, U., Galli, G., Boscacci, M., and Bolliger, M.: Radar precipitation measurement in a mountainous region, Q. J. Roy. Meteor. Soc., 132, 1669–1692, https://doi.org/10.1256/qj.05.190, 2006. a
Gochis, D., Schumacher, R., Friedrich, K., Doesken, N., Kelsch,M., Sun, J., Ikeda, K., Lindsey, D., Wood, A., Dolan, B., Matrosov, S., Newman, A., Mahoney, K., Rutledge, S., Johnson, R., Kucera, P., Kennedy, P., Sempere-Torres, D., Steiner, M., Roberts, R., Wilson, J., Yu, W., Chandrasekar, V., Rasmussen, R., Anderson, A., and Brown, B.: The great Colorado flood of September 2013, B. Am. Meteorol. Soc., 96, 1461–1487, https://doi.org/10.1175/BAMS-D-13-00241.1, 2015. a
González Hidalgo, J., De Luis, M., Raventós, J., and Sánchez, J.: Daily rainfall trend in the Valencia Region of Spain, Theor. Appl. Climatol., 75, 117–130, https://doi.org/10.1007/s00704-002-0718-0, 2003. a
Goudenhoofdt, E. and Delobbe, L.: Evaluation of radar-gauge merging methods for quantitative precipitation estimates, Hydrol. Earth Syst. Sci., 13, 195–203, https://doi.org/10.5194/hess-13-195-2009, 2009. a
Graf, M., El Hachem, A., Eisele, M., Seidel, J., Chwala, C., Kunstmann, H., and Bárdossy, A.: Rainfall estimates from opportunistic sensors in Germany across spatio-temporal scales, J. Hydrol.: Reg. Stud., 37, 100883, https://doi.org/10.1016/j.ejrh.2021.100883, 2021. a
Horton, R. E.: The Role of infiltration in the hydrologic cycle, Eos, Transactions American Geophysical Union, 14, 446–460, https://doi.org/10.1029/TR014i001p00446, 1933. a
Hrachowitz, M. and Weiler, M.: Uncertainty of Precipitation Estimates Caused by Sparse Gauging Networks in a Small, Mountainous Watershed, J. Hydrol. Eng., 16, 460–471, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000331, 2011. a
Humphrey, M., Istok, J., Lee, J., Hevesi, J., and Flint, A.: A new method for automated dynamic calibration of tipping-bucket rain gauges, J. Atmos. Ocean. Tech., 14, 1513–1519, https://doi.org/10.1175/1520-0426(1997)014%3C1513:ANMFAD%3E2.0.CO;2, 1997. a
Jenkinson, A. F.: The frequency distribution of the annual maximum (or minimum) values of meteorological elements, Q. J. Roy. Meteor. Soc., 81, 158–171, 1955. a
Klein Tank, A. M. G., Wijngaard, J. B., Können, G. P., Böhm, R., Demarée, G., Gocheva, A., Mileta, M., Pashiardis, S., Hejkrlik, L., Kern-Hansen, C., Heino, R., Bessemoulin, P., Müller-Westermeier, G., Tzanakou, M., Szalai, S., Pálsdóttir, T., Fitzgerald, D., Rubin, S., Capaldo, M., Maugeri, M., Leitass, A., Bukantis, A., Aberfeld, R., van Engelen, A.F.V., Forland, E., Mietus, M., Coelho, F., Mares, C., Razuvaev, V., Nieplova, E., Cegnar, T., Antonio López, J., Dahlström, B., Moberg, A., Kirchhofer, W., Ceylan, A., Pachaliuk, O., Alexander, L. V., and Petrovic, P.: Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment, Int. J. Climatol., 22, 1441–1453, https://doi.org/10.1002/joc.773, 2002. a
Krajewski, W. F., Villarini, G., and Smith, J. A.: Radar-rainfall uncertainties: Where are we after thirty years of effort?, B. Am. Meteorol. Soc., 91, 87–94, https://doi.org/10.1175/2009BAMS2747.1, 2010. a
Krüger, R., Karrasch, P., and Eltner, A.: Calibrating low-cost rain gauge sensors for their applications in Internet of Things (IoT) infrastructures to densify environmental monitoring networks, Geosci. Instrum. Method. Data Syst., 13, 163–176, https://doi.org/10.5194/gi-13-163-2024, 2024. a
Lazoglou, G. and Anagnostopoulou, C.: An overview of statistical methods for studying the extreme rainfalls in Mediterranean, in: Proceedings, vol. 1, MDPI, 681 https://doi.org/10.3390/ecas2017-04132, 2017. a
Lebel, T., Bastin, G., Obled, C., and Creutin, J.: On the accuracy of areal rainfall estimation: a case study, Water Resour. Res., 23, 2123–2134, https://doi.org/10.1029/WR023i011p02123, 1987. a, b
Lehner, B. and Grill, G.: Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems, Hydrol. Process., 27, 2171–2186, https://doi.org/10.1002/hyp.9740, 2013. a, b
Llasat, M. C.: Spain's flash floods reveal a desperate need for improved mitigation efforts, Nature, 635, 787, https://doi.org/10.1038/d41586-024-03825-0, 2024. a
Marchi, L., Borga, M., Preciso, E., and Gaume, E.: Characterisation of selected extreme flash floods in Europe and implications for flood risk management, J. Hydrol., 394, 118–133, https://doi.org/10.1016/j.jhydrol.2010.07.017, 2010. a
Marsalek, J.: Calibration of the tipping-bucket raingage, J. Hydrol., 53, 343–354, https://doi.org/10.1016/0022-1694(81)90010-X, 1981. a
Miglietta, M. M. and Regano, A.: An observational and numerical study of a flash-flood event over south-eastern Italy, Nat. Hazards Earth Syst. Sci., 8, 1417–1430, https://doi.org/10.5194/nhess-8-1417-2008, 2008. a
Morin, E., Enzel, Y., Shamir, U., and Garti, R.: The characteristic time scale for basin hydrological response using radar data, J. Hydrol., 252, 85–99, https://doi.org/10.1016/S0022-1694(01)00451-6, 2001. a
Nielsen, J., van de Beek, C., Thorndahl, S., Olsson, J., Andersen, C., Andersson, J., Rasmussen, M., and Nielsen, J.: Merging weather radar data and opportunistic rainfall sensor data to enhance rainfall estimates, Atmos. Res., 300, 107228, https://doi.org/10.1016/j.atmosres.2024.107228, 2024. a
Niemczynowicz, J.: The dynamic calibration of tipping-bucket raingauges, Hydrol. Res., 17, 203–214, https://doi.org/10.2166/nh.1986.0013, 1986. a
Ochoa-Rodriguez, S., Wang, L.-P., Willems, P., and Onof, C.: A review of radar-rain gauge data merging methods and their potential for urban hydrological applications, Water Resour. Res., 55, 6356–6391, https://doi.org/10.1029/2018WR023332, 2019. a
Overeem, A., Buishand, T. A., Holleman, I., and Uijlenhoet, R.: Extreme value modeling of areal rainfall from weather radar, Water Resources Research, 46, https://doi.org/10.1029/2009WR008517, 2010. a
Overeem, A., Leijnse, H., van der Schrier, G., van den Besselaar, E., Garcia-Marti, I., and de Vos, L. W.: Merging with crowdsourced rain gauge data improves pan-European radar precipitation estimates, Hydrol. Earth Syst. Sci., 28, 649–668, https://doi.org/10.5194/hess-28-649-2024, 2024. a, b, c, d
Pastor, F., Gómez, I., and Estrela, M. J.: Numerical study of the October 2007 flash flood in the Valencia region (Eastern Spain): the role of orography, Nat. Hazards Earth Syst. Sci., 10, 1331–1345, https://doi.org/10.5194/nhess-10-1331-2010, 2010. a, b
Pellarin, T., Delrieu, G., Saulnier, G.-M., Andrieu, H., Vignal, B., and Creutin, J.-D.: Hydrologic Visibility of Weather Radar Systems Operating in Mountainous Regions: Case Study for the Ardèche Catchment (France), J. Hydrometeorol., 3, 539–555, https://doi.org/10.1175/1525-7541(2002)003<0539:HVOWRS>2.0.CO;2, 2002. a
Peñarrocha, D., Estrela, M. J., and Millán, M.: Classification of daily rainfall patterns in a Mediterranean area with extreme intensity levels: the Valencia region, Int. J. Climatol., 22, 677–695, https://doi.org/10.1002/joc.747, 2002. a
Portugués Mollà, I.: Management of the Turia River in Valencia (Spain): The Recent History of an Unfinished Metamorphosis, in: Urban and Metropolitan Rivers: Geomorphology, Planning and Perception, 155–171, Springer, https://doi.org/10.1007/978-3-031-62641-8_9, 2024. a
Romero, R., Guijarro, J., Ramis, C., and Alonso, S.: A 30-year (1964–1993) daily rainfall data base for the Spanish Mediterranean regions: First exploratory study, Int. J. Climatol., 18, 541–560, https://doi.org/10.1002/(SICI)1097-0088(199804)18:5<541::AID-JOC270>3.0.CO;2-N, 1998. a
Ruiz, J. M., Carmona, P., and Pérez Cueva, A.: Flood frequency and seasonality of the Jucar and Turia Mediterranean rivers (Spain) during the “Little Ice Age”, Méditerranée, Revue géographique des pays méditerranéens/Journal of Mediterranean geography, 121–130, https://doi.org/10.4000/mediterranee.7208, 2014. a
Sawada, Y., Kanai, R., and Kotani, H.: Impact of cry wolf effects on social preparedness and the efficiency of flood early warning systems, Hydrol. Earth Syst. Sci., 26, 4265–4278, https://doi.org/10.5194/hess-26-4265-2022, 2022. a
Schilling, W.: Rainfall data for urban hydrology: what do we need?, Atmos. Res., 27, 5–21, https://doi.org/10.1016/0169-8095(91)90003-F, 1991. a
Van de Beek, C., Leijnse, H., Torfs, P., and Uijlenhoet, R.: Climatology of daily rainfall semi-variance in The Netherlands, Hydrology and Earth System Sciences, 15, 171–183, https://doi.org/10.1016/j.advwatres.2012.03.023, 2011. a
Villarini, G. and Krajewski, W. F.: Review of the different sources of uncertainty in single polarization radar-based estimates of rainfall, Surv. Geophys., 31, 107–129, https://doi.org/10.1007/s10712-009-9079-x, 2010. a
Wang, L.-P., Ochoa-Rodríguez, S., Van Assel, J., Pina, R. D., Pessemier, M., Kroll, S., Willems, P., and Onof, C.: Enhancement of radar rainfall estimates for urban hydrology through optical flow temporal interpolation and Bayesian gauge-based adjustment, J. Hydrol., 531, 408–426, https://doi.org/10.1016/j.jhydrol.2015.05.049, 2015. a
Short summary
On 29 October 2024 Valencia (Spain) was struck by torrential rainfall, triggering devastating floods in this area. In this study, we quantify and describe the spatial and temporal structure of this rainfall event using personal weather stations (PWSs). These PWSs provide near real-time observations at a temporal resolution of ~5 min. This study shows the potential of PWSs for real-time rainfall monitoring and potentially flood early warning systems by complementing dedicated rain gauge networks.
On 29 October 2024 Valencia (Spain) was struck by torrential rainfall, triggering devastating...