Articles | Volume 21, issue 5
https://doi.org/10.5194/hess-21-2389-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-2389-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
09 May 2017
Research article |
| 09 May 2017
Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean
Francesco Marra
CORRESPONDING AUTHOR
Institute of Earth Sciences, Hebrew University of Jerusalem, 91904, Jerusalem, Israel
Efrat Morin
Institute of Earth Sciences, Hebrew University of Jerusalem, 91904, Jerusalem, Israel
Nadav Peleg
Institute of Environmental Engineering, Hydrology and Water Resources Management, ETH Zurich, Zurich, Switzerland
Yiwen Mei
Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT, USA
Emmanouil N. Anagnostou
Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT, USA
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Understanding air–sea heat exchange is vital for studying ocean dynamics. Eddy covariance measurements over the Gulf of Eilat revealed a 3.22 m yr-1 evaporation rate, which is inconsistent with bulk formulae estimations in stable atmospheric conditions, requiring bulk formulae to be revisited in these environments. The surface fluxes have a net cooling effect on the gulf water on an annual mean (-79 W m-2), balanced by a strong exchange flux between the Red Sea and the Gulf of Eilat.
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Mariam Khanam, Giulia Sofia, Wilmalis Rodriguez, Efthymios I. Nikolopoulos, Binghao Lu, Dongjin Song, and Emmanouil N. Anagnostou
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Revised manuscript accepted for NHESS
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This study comprehends and predicts the socioeconomic effects of floods in the High Mountain Asia (HMA) region. We proposed a machine-learning strategy for mapping flood damages. We predicted the Lifeyears Index (LYI), which quantifies the financial cost and loss of life caused by floods, using variables including climate, geomorphology, and population. The study's overall goal is to offer useful information on flood susceptibility and subsequent risk mapping in the HMA region.
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
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Short summary
Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Shalev Siman-Tov and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1079–1093, https://doi.org/10.5194/nhess-23-1079-2023, https://doi.org/10.5194/nhess-23-1079-2023, 2023
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Debris flows represent a threat to infrastructure and the population. In arid areas, they are observed when heavy rainfall hits steep slopes with sediments. Here, we use digital surface models and radar rainfall data to detect and characterize the triggering and non-triggering rainfall conditions. We find that rainfall intensity alone is insufficient to explain the triggering. We suggest that antecedent rainfall could represent a critical factor for debris flow triggering in arid regions.
Kang He, Qing Yang, Xinyi Shen, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 22, 2921–2927, https://doi.org/10.5194/nhess-22-2921-2022, https://doi.org/10.5194/nhess-22-2921-2022, 2022
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This study depicts the flood-affected areas in western Europe in July 2021 and particularly the agriculture land that was under flood inundation. The results indicate that the total inundated area over western Europe is about 1920 km2, of which 1320 km2 is in France. Around 64 % of the inundated area is agricultural land. We expect that the agricultural productivity in western Europe will have been severely impacted.
Michael Schirmer, Adam Winstral, Tobias Jonas, Paolo Burlando, and Nadav Peleg
The Cryosphere, 16, 3469–3488, https://doi.org/10.5194/tc-16-3469-2022, https://doi.org/10.5194/tc-16-3469-2022, 2022
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Rain is highly variable in time at a given location so that there can be both wet and dry climate periods. In this study, we quantify the effects of this natural climate variability and other sources of uncertainty on changes in flooding events due to rain on snow (ROS) caused by climate change. For ROS events with a significant contribution of snowmelt to runoff, the change due to climate was too small to draw firm conclusions about whether there are more ROS events of this important type.
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, and Yossi Matias
Hydrol. Earth Syst. Sci., 26, 4013–4032, https://doi.org/10.5194/hess-26-4013-2022, https://doi.org/10.5194/hess-26-4013-2022, 2022
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Early flood warnings are one of the most effective tools to save lives and goods. Machine learning (ML) models can improve flood prediction accuracy but their use in operational frameworks is limited. The paper presents a flood warning system, operational in India and Bangladesh, that uses ML models for forecasting river stage and flood inundation maps and discusses the models' performances. In 2021, more than 100 million flood alerts were sent to people near rivers over an area of 470 000 km2.
Assaf Hochman, Francesco Marra, Gabriele Messori, Joaquim G. Pinto, Shira Raveh-Rubin, Yizhak Yosef, and Georgios Zittis
Earth Syst. Dynam., 13, 749–777, https://doi.org/10.5194/esd-13-749-2022, https://doi.org/10.5194/esd-13-749-2022, 2022
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Gaining a complete understanding of extreme weather, from its physical drivers to its impacts on society, is important in supporting future risk reduction and adaptation measures. Here, we provide a review of the available scientific literature, knowledge gaps and key open questions in the study of extreme weather events over the vulnerable eastern Mediterranean region.
Francesco Marra, Moshe Armon, and Efrat Morin
Hydrol. Earth Syst. Sci., 26, 1439–1458, https://doi.org/10.5194/hess-26-1439-2022, https://doi.org/10.5194/hess-26-1439-2022, 2022
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We present a new method for quantifying the probability of occurrence of extreme rainfall using radar data, and we use it to examine coastal and orographic effects on extremes. We identify three regimes, directly related to precipitation physical processes, which respond differently to these forcings. The methods and results are of interest for researchers and practitioners using radar for the analysis of extremes, risk managers, water resources managers, and climate change impact studies.
Yoav Ben Dor, Francesco Marra, Moshe Armon, Yehouda Enzel, Achim Brauer, Markus Julius Schwab, and Efrat Morin
Clim. Past, 17, 2653–2677, https://doi.org/10.5194/cp-17-2653-2021, https://doi.org/10.5194/cp-17-2653-2021, 2021
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Laminated sediments from the deepest part of the Dead Sea unravel the hydrological response of the eastern Mediterranean to past climate changes. This study demonstrates the importance of geological archives in complementing modern hydrological measurements that do not fully capture natural hydroclimatic variability, which is crucial to configure for understanding the impact of climate change on the hydrological cycle in subtropical regions.
Yair Rinat, Francesco Marra, Moshe Armon, Asher Metzger, Yoav Levi, Pavel Khain, Elyakom Vadislavsky, Marcelo Rosensaft, and Efrat Morin
Nat. Hazards Earth Syst. Sci., 21, 917–939, https://doi.org/10.5194/nhess-21-917-2021, https://doi.org/10.5194/nhess-21-917-2021, 2021
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Flash floods are among the most devastating and lethal natural hazards worldwide. The study of such events is important as flash floods are poorly understood and documented processes, especially in deserts. A small portion of the studied basin (1 %–20 %) experienced extreme rainfall intensities resulting in local flash floods of high magnitudes. Flash floods started and reached their peak within tens of minutes. Forecasts poorly predicted the flash floods mostly due to location inaccuracy.
Mariam Khanam, Giulia Sofia, Marika Koukoula, Rehenuma Lazin, Efthymios I. Nikolopoulos, Xinyi Shen, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 21, 587–605, https://doi.org/10.5194/nhess-21-587-2021, https://doi.org/10.5194/nhess-21-587-2021, 2021
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Compound extremes correspond to events with multiple concurrent or consecutive drivers, leading to substantial impacts such as infrastructure failure. In many risk assessment and design applications, however, multihazard scenario events are ignored. In this paper, we present a general framework to investigate current and future climate compound-event flood impact on coastal critical infrastructures such as power grid substations.
Diego Cerrai, Qing Yang, Xinyi Shen, Marika Koukoula, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 20, 1463–1468, https://doi.org/10.5194/nhess-20-1463-2020, https://doi.org/10.5194/nhess-20-1463-2020, 2020
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On 1 September 2019 Hurricane Dorian made landfall on Great Abaco, unleashing unprecedented destruction on the northern Bahamas. Dorian was characterized by extreme winds, extensive coastal flooding, and impressive precipitation. We studied the event through images acquired by the synthetic aperture radars (SARs) mounted on European Space Agency satellites to derive flooding maps showing the extent of the devastation. We found that the flooded area in the Bahamas was at least 3000 km2.
Moshe Armon, Francesco Marra, Yehouda Enzel, Dorita Rostkier-Edelstein, and Efrat Morin
Hydrol. Earth Syst. Sci., 24, 1227–1249, https://doi.org/10.5194/hess-24-1227-2020, https://doi.org/10.5194/hess-24-1227-2020, 2020
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Heavy precipitation events (HPEs), occurring around the globe, lead to natural hazards as well as to water resource recharge. Rainfall patterns during HPEs vary from one case to another and govern their effect. Thus, correct prediction of these patterns is crucial for coping with HPEs. However, the ability of weather models to generate such patterns is unclear. Here, we characterise rainfall patterns during HPEs based on weather radar data and evaluate weather model simulations of these events.
Nadav Peleg, Chris Skinner, Simone Fatichi, and Peter Molnar
Earth Surf. Dynam., 8, 17–36, https://doi.org/10.5194/esurf-8-17-2020, https://doi.org/10.5194/esurf-8-17-2020, 2020
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Extreme rainfall is expected to intensify with increasing temperatures, which will likely affect rainfall spatial structure. The spatial variability of rainfall can affect streamflow and sediment transport volumes and peaks. The sensitivity of the hydro-morphological response to changes in the structure of heavy rainfall was investigated. It was found that the morphological components are more sensitive to changes in rainfall spatial structure in comparison to the hydrological components.
Davide Zoccatelli, Francesco Marra, Moshe Armon, Yair Rinat, James A. Smith, and Efrat Morin
Hydrol. Earth Syst. Sci., 23, 2665–2678, https://doi.org/10.5194/hess-23-2665-2019, https://doi.org/10.5194/hess-23-2665-2019, 2019
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This study presents a comparison of flood properties over multiple Mediterranean and desert catchments. While in Mediterranean areas floods are related to rainfall amount, in deserts we observed a strong connection with the characteristics of the more intense part of storms. Because of the different mechanisms involved, despite having significantly shorter and more localized storms, deserts are able to produce floods with a magnitude comparable to Mediterranean areas.
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Jan Polcher, Clément Albergel, Emanuel Dutra, Gabriel Fink, Alberto Martínez-de la Torre, and Simon Munier
Hydrol. Earth Syst. Sci., 23, 1973–1994, https://doi.org/10.5194/hess-23-1973-2019, https://doi.org/10.5194/hess-23-1973-2019, 2019
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This study investigates the propagation of precipitation uncertainty, and its interaction with hydrologic modeling, in global water resource reanalysis. Analysis is based on ensemble hydrologic simulations for a period of 11 years based on six global hydrologic models and five precipitation datasets. Results show that uncertainties in the model simulations are attributed to both uncertainty in precipitation forcing and the model structure.
William Amponsah, Pierre-Alain Ayral, Brice Boudevillain, Christophe Bouvier, Isabelle Braud, Pascal Brunet, Guy Delrieu, Jean-François Didon-Lescot, Eric Gaume, Laurent Lebouc, Lorenzo Marchi, Francesco Marra, Efrat Morin, Guillaume Nord, Olivier Payrastre, Davide Zoccatelli, and Marco Borga
Earth Syst. Sci. Data, 10, 1783–1794, https://doi.org/10.5194/essd-10-1783-2018, https://doi.org/10.5194/essd-10-1783-2018, 2018
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The EuroMedeFF database comprises 49 events that occurred in France, Israel, Germany, Slovenia, Romania, and Italy. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the verification of flash flood hydrological models and for hydro-meteorological forecast systems. It provides, moreover, a sample of rainfall and flood discharge extremes in different climates.
Efthymios I. Nikolopoulos, Elisa Destro, Md Abul Ehsan Bhuiyan, Marco Borga, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 18, 2331–2343, https://doi.org/10.5194/nhess-18-2331-2018, https://doi.org/10.5194/nhess-18-2331-2018, 2018
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Debris flows, following wildfires, constitute a significant threat to downstream populations and infrastructure. Therefore, developing measures to reduce the vulnerability of local communities to debris flows is of paramount importance. This work proposes a new model for predicting post-fire debris flow occurrence on a regional scale and demonstrates that the proposed model has notably higher skill than the currently used approaches.
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Pere Quintana-Seguí, and Anaïs Barella-Ortiz
Hydrol. Earth Syst. Sci., 22, 1371–1389, https://doi.org/10.5194/hess-22-1371-2018, https://doi.org/10.5194/hess-22-1371-2018, 2018
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This study investigates the use of a nonparametric model for combining multiple global precipitation datasets and characterizing estimation uncertainty. Inputs to the model included three satellite precipitation products, an atmospheric reanalysis precipitation dataset, satellite-derived near-surface daily soil moisture data, and terrain elevation. We evaluated the technique based on high-resolution reference precipitation data and further used generated ensembles to force a hydrological model.
Idit Belachsen, Francesco Marra, Nadav Peleg, and Efrat Morin
Hydrol. Earth Syst. Sci., 21, 5165–5180, https://doi.org/10.5194/hess-21-5165-2017, https://doi.org/10.5194/hess-21-5165-2017, 2017
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Spatiotemporal rainfall patterns in arid environments are not well-known. We derived properties of convective rain cells over the arid Dead Sea region from a long-term radar archive. We found differences in cell properties between synoptic systems and between flash-flood and non-flash-flood events. Large flash floods are associated with slow rain cells, directed downstream with the main catchment axis. Results from this work can be used for hydrological models and stochastic storm simulations.
Francesco Marra, Elisa Destro, Efthymios I. Nikolopoulos, Davide Zoccatelli, Jean Dominique Creutin, Fausto Guzzetti, and Marco Borga
Hydrol. Earth Syst. Sci., 21, 4525–4532, https://doi.org/10.5194/hess-21-4525-2017, https://doi.org/10.5194/hess-21-4525-2017, 2017
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Previous studies have reported a systematic underestimation of debris flow occurrence thresholds, due to the use of sparse networks in non-stationary rain fields. We analysed high-resolution radar data to show that spatially aggregated estimates (e.g. satellite data) largely reduce this issue, in light of a reduced estimation variance. Our findings are transferable to other situations in which lower envelope curves are used to predict point-like events in the presence of non-stationary fields.
Yiwen Mei, Xinyi Shen, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 21, 2277–2299, https://doi.org/10.5194/hess-21-2277-2017, https://doi.org/10.5194/hess-21-2277-2017, 2017
Nadav Peleg, Frank Blumensaat, Peter Molnar, Simone Fatichi, and Paolo Burlando
Hydrol. Earth Syst. Sci., 21, 1559–1572, https://doi.org/10.5194/hess-21-1559-2017, https://doi.org/10.5194/hess-21-1559-2017, 2017
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We investigated the relative contribution of the spatial versus climatic rainfall variability for flow peaks by applying an advanced stochastic rainfall generator to simulate rainfall for a small urban catchment and simulate flow dynamics in the sewer system. We found that the main contribution to the total flow variability originates from the natural climate variability. The contribution of spatial rainfall variability to the total flow variability was found to increase with return periods.
N. Peleg, E. Shamir, K. P. Georgakakos, and E. Morin
Hydrol. Earth Syst. Sci., 19, 567–581, https://doi.org/10.5194/hess-19-567-2015, https://doi.org/10.5194/hess-19-567-2015, 2015
H. Seyyedi, E. N. Anagnostou, E. Beighley, and J. McCollum
Hydrol. Earth Syst. Sci., 18, 5077–5091, https://doi.org/10.5194/hess-18-5077-2014, https://doi.org/10.5194/hess-18-5077-2014, 2014
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The paper presents a methodology for using global precipitation products from satellite remote sensing to error-correct and downscale global atmospheric reanalysis precipitation data sets. It is shown that streamflow simulations from the satellite-adjusted precipitation reanalysis give similar statistics to the ones derived by high-resolution ground-based radar rainfall data sets. This approach can be applied globally to derive improved flood frequency maps over data-poor areas.
N. Peleg, M. Ben-Asher, and E. Morin
Hydrol. Earth Syst. Sci., 17, 2195–2208, https://doi.org/10.5194/hess-17-2195-2013, https://doi.org/10.5194/hess-17-2195-2013, 2013
E. Picciotti, F. S. Marzano, E. N. Anagnostou, J. Kalogiros, Y. Fessas, A. Volpi, V. Cazac, R. Pace, G. Cinque, L. Bernardini, K. De Sanctis, S. Di Fabio, M. Montopoli, M. N. Anagnostou, A. Telleschi, E. Dimitriou, and J. Stella
Nat. Hazards Earth Syst. Sci., 13, 1229–1241, https://doi.org/10.5194/nhess-13-1229-2013, https://doi.org/10.5194/nhess-13-1229-2013, 2013
E. Shamir, L. Ben-Moshe, A. Ronen, T. Grodek, Y. Enzel, K. P. Georgakakos, and E. Morin
Hydrol. Earth Syst. Sci., 17, 1021–1034, https://doi.org/10.5194/hess-17-1021-2013, https://doi.org/10.5194/hess-17-1021-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Remote Sensing and GIS
Evaluation of remote sensing and reanalysis based precipitation products for agro-hydrological studies in semi-arid tropics of Tamil Nadu
Extent of gross underestimation of precipitation in India
A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze–Atbara Basin
Improved soil evaporation remote sensing retrieval algorithms and associated uncertainty analysis on the Tibetan Plateau
SMPD: a soil moisture-based precipitation downscaling method for high-resolution daily satellite precipitation estimation
Evaluating the accuracy of gridded water resources reanalysis and evapotranspiration products for assessing water security in poorly gauged basins
Attribution of global evapotranspiration trends based on the Budyko framework
The influence of vegetation water dynamics on the ASCAT backscatter–incidence angle relationship in the Amazon
Extrapolating continuous vegetation water content to understand sub-daily backscatter variations
Comprehensive evaluation of satellite-based and reanalysis soil moisture products using in situ observations over China
Variations in surface roughness of heterogeneous surfaces in the Nagqu area of the Tibetan Plateau
Evapotranspiration in the Amazon: spatial patterns, seasonality, and recent trends in observations, reanalysis, and climate models
The benefit of brightness temperature assimilation for the SMAP Level-4 surface and root-zone soil moisture analysis
Evaluation of the dual-polarization weather radar quantitative precipitation estimation using long-term datasets
Validation of SMAP L2 passive-only soil moisture products using upscaled in situ measurements collected in Twente, the Netherlands
Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa
Data-driven estimates of evapotranspiration and its controls in the Congo Basin
Ability of an Australian reanalysis dataset to characterise sub-daily precipitation
A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products
Evaluation of soil moisture from CCAM-CABLE simulation, satellite-based models estimates and satellite observations: a case study of Skukuza and Malopeni flux towers
Statistical characteristics of raindrop size distribution during rainy seasons in the Beijing urban area and implications for radar rainfall estimation
An evaluation of daily precipitation from a regional atmospheric reanalysis over Australia
Performance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River basin
The El Niño event of 2015–2016: climate anomalies and their impact on groundwater resources in East and Southern Africa
Consistency of satellite-based precipitation products in space and over time compared with gauge observations and snow- hydrological modelling in the Lake Titicaca region
Using phase lags to evaluate model biases in simulating the diurnal cycle of evapotranspiration: a case study in Luxembourg
Integrating multiple satellite observations into a coherent dataset to monitor the full water cycle – application to the Mediterranean region
An improved perspective in the spatial representation of soil moisture: potential added value of SMOS disaggregated 1 km resolution “all weather” product
Temporal- and spatial-scale and positional effects on rain erosivity derived from point-scale and contiguous rain data
The PERSIANN family of global satellite precipitation data: a review and evaluation of products
Exploring seasonal and regional relationships between the Evaporative Stress Index and surface weather and soil moisture anomalies across the United States
Development of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United States
Evaluation of multiple climate data sources for managing environmental resources in East Africa
Precipitation downscaling using a probability-matching approach and geostationary infrared data: an evaluation over six climate regions
Regional co-variability of spatial and temporal soil moisture–precipitation coupling in North Africa: an observational perspective
Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US
Regional frequency analysis of extreme rainfall in Belgium based on radar estimates
An assessment of the performance of global rainfall estimates without ground-based observations
Water–food–energy nexus with changing agricultural scenarios in India during recent decades
The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France
Reservoir storage and hydrologic responses to droughts in the Paraná River basin, south-eastern Brazil
Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels
Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau
Evaluation of soil moisture downscaling using a simple thermal-based proxy – the REMEDHUS network (Spain) example
The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat
Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002–2012)
Scoping a field experiment: error diagnostics of TRMM precipitation radar estimates in complex terrain as a basis for IPHEx2014
Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in Ethiopia
Downscaling of seasonal soil moisture forecasts using satellite data
Long term soil moisture mapping over the Tibetan plateau using Special Sensor Microwave/Imager
Aatralarasi Saravanan, Daniel Karthe, Selvaprakash Ramalingam, and Niels Schütze
EGUsphere, https://doi.org/10.5194/egusphere-2024-2369, https://doi.org/10.5194/egusphere-2024-2369, 2024
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In water-scarce regions, precipitation is a highly variable and essential resource for crop production. Developing countries like India have an uneven distribution of rain gauges, so reliance on satellite and reanalysis-based precipitation products is critical for their prudent management. Hence, the study statistically evaluated different precipitation products against the station data for water-scarce regions in Tamil Nadu and found that ERA5-Land performed the best, followed by MSWEP.
Gopi Goteti and James Famiglietti
Hydrol. Earth Syst. Sci., 28, 3435–3455, https://doi.org/10.5194/hess-28-3435-2024, https://doi.org/10.5194/hess-28-3435-2024, 2024
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Underestimation of precipitation (UoP) in India is a substantial issue not just within gauge-based precipitation datasets but also within state-of-the-art satellite and reanalysis-based datasets. UoP is prevalent across most river basins of India, including those that have experienced catastrophic flooding in the recent past. This paper highlights not only a major limitation of existing precipitation products for India but also other data-related obstacles faced by the research community.
Mohammed Abdallah, Ke Zhang, Lijun Chao, Abubaker Omer, Khalid Hassaballah, Kidane Welde Reda, Linxin Liu, Tolossa Lemma Tola, and Omar M. Nour
Hydrol. Earth Syst. Sci., 28, 1147–1172, https://doi.org/10.5194/hess-28-1147-2024, https://doi.org/10.5194/hess-28-1147-2024, 2024
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A D-vine copula-based quantile regression (DVQR) model is used to merge satellite precipitation products. The performance of the DVQR model is compared with the simple model average and one-outlier-removed average methods. The nonlinear DVQR model outperforms the quantile-regression-based multivariate linear and Bayesian model averaging methods.
Jin Feng, Ke Zhang, Huijie Zhan, and Lijun Chao
Hydrol. Earth Syst. Sci., 27, 363–383, https://doi.org/10.5194/hess-27-363-2023, https://doi.org/10.5194/hess-27-363-2023, 2023
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Here we improved a satellite-driven evaporation algorithm by introducing the modified versions of the two constraint schemes. The two moisture constraint schemes largely improved the evaporation estimation on two barren-dominated basins of the Tibetan Plateau. Investigation of moisture constraint uncertainty showed that high-quality soil moisture can optimally represent moisture, and more accessible precipitation data generally help improve the estimation of barren evaporation.
Kunlong He, Wei Zhao, Luca Brocca, and Pere Quintana-Seguí
Hydrol. Earth Syst. Sci., 27, 169–190, https://doi.org/10.5194/hess-27-169-2023, https://doi.org/10.5194/hess-27-169-2023, 2023
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In this study, we developed a soil moisture-based precipitation downscaling (SMPD) method for spatially downscaling the GPM daily precipitation product by exploiting the connection between surface soil moisture and precipitation according to the soil water balance equation. Based on this physical method, the spatial resolution of the daily precipitation product was downscaled to 1 km and the SMPD method shows good potential for the development of the high-resolution precipitation product.
Elias Nkiaka, Robert G. Bryant, Joshua Ntajal, and Eliézer I. Biao
Hydrol. Earth Syst. Sci., 26, 5899–5916, https://doi.org/10.5194/hess-26-5899-2022, https://doi.org/10.5194/hess-26-5899-2022, 2022
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Achieving water security in poorly gauged regions is hindered by a lack of in situ hydrometeorological data. In this study, we validated nine existing gridded water resource reanalyses and eight evapotranspiration products in eight representative gauged basins in Central–West Africa. Our results show the strengths and and weaknesses of the existing products and that these products can be used to assess water security in ungauged basins. However, it is imperative to validate these products.
Shijie Li, Guojie Wang, Chenxia Zhu, Jiao Lu, Waheed Ullah, Daniel Fiifi Tawia Hagan, Giri Kattel, and Jian Peng
Hydrol. Earth Syst. Sci., 26, 3691–3707, https://doi.org/10.5194/hess-26-3691-2022, https://doi.org/10.5194/hess-26-3691-2022, 2022
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We found that the precipitation variability dominantly controls global evapotranspiration (ET) in dry climates, while the net radiation has substantial control over ET in the tropical regions, and vapor pressure deficit (VPD) impacts ET trends in boreal mid-latitude climate. The critical role of VPD in controlling ET trends is particularly emphasized due to its influence in controlling the carbon–water–energy cycle.
Ashwini Petchiappan, Susan C. Steele-Dunne, Mariette Vreugdenhil, Sebastian Hahn, Wolfgang Wagner, and Rafael Oliveira
Hydrol. Earth Syst. Sci., 26, 2997–3019, https://doi.org/10.5194/hess-26-2997-2022, https://doi.org/10.5194/hess-26-2997-2022, 2022
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This study investigates spatial and temporal patterns in the incidence angle dependence of backscatter from the ASCAT C-band scatterometer and relates those to precipitation, humidity, and radiation data and GRACE equivalent water thickness in ecoregions in the Amazon. The results show that the ASCAT data record offers a unique perspective on vegetation water dynamics exhibiting sensitivity to moisture availability and demand and phenological change at interannual, seasonal, and diurnal scales.
Paul C. Vermunt, Susan C. Steele-Dunne, Saeed Khabbazan, Jasmeet Judge, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 26, 1223–1241, https://doi.org/10.5194/hess-26-1223-2022, https://doi.org/10.5194/hess-26-1223-2022, 2022
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This study investigates the use of hydrometeorological sensors to reconstruct variations in internal vegetation water content of corn and relates these variations to the sub-daily behaviour of polarimetric L-band backscatter. The results show significant sensitivity of backscatter to the daily cycles of vegetation water content and dew, particularly on dry days and for vertical and cross-polarizations, which demonstrates the potential for using radar for studies on vegetation water dynamics.
Xiaolu Ling, Ying Huang, Weidong Guo, Yixin Wang, Chaorong Chen, Bo Qiu, Jun Ge, Kai Qin, Yong Xue, and Jian Peng
Hydrol. Earth Syst. Sci., 25, 4209–4229, https://doi.org/10.5194/hess-25-4209-2021, https://doi.org/10.5194/hess-25-4209-2021, 2021
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Soil moisture (SM) plays a critical role in the water and energy cycles of the Earth system, for which a long-term SM product with high quality is urgently needed. In situ observations are generally treated as the true value to systematically evaluate five SM products, including one remote sensing product and four reanalysis data sets during 1981–2013. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.
Maoshan Li, Xiaoran Liu, Lei Shu, Shucheng Yin, Lingzhi Wang, Wei Fu, Yaoming Ma, Yaoxian Yang, and Fanglin Sun
Hydrol. Earth Syst. Sci., 25, 2915–2930, https://doi.org/10.5194/hess-25-2915-2021, https://doi.org/10.5194/hess-25-2915-2021, 2021
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In this study, using MODIS satellite data and site atmospheric turbulence observation data in the Nagqu area of the northern Tibetan Plateau, with the Massman-retrieved model and a single height observation to determine aerodynamic surface roughness, temporal and spatial variation characteristics of the surface roughness were analyzed. The result is feasible, and it can be applied to improve the model parameters of the land surface model and the accuracy of model simulation in future work.
Jessica C. A. Baker, Luis Garcia-Carreras, Manuel Gloor, John H. Marsham, Wolfgang Buermann, Humberto R. da Rocha, Antonio D. Nobre, Alessandro Carioca de Araujo, and Dominick V. Spracklen
Hydrol. Earth Syst. Sci., 25, 2279–2300, https://doi.org/10.5194/hess-25-2279-2021, https://doi.org/10.5194/hess-25-2279-2021, 2021
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Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to measure over large areas. In this study, we compare spatial patterns, seasonality, and recent trends in Amazon ET from a water-budget analysis with estimates from satellites, reanalysis, and global climate models. We find large differences between products, showing that many widely used datasets and climate models may not provide a reliable representation of this crucial variable over the Amazon.
Jianxiu Qiu, Jianzhi Dong, Wade T. Crow, Xiaohu Zhang, Rolf H. Reichle, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 1569–1586, https://doi.org/10.5194/hess-25-1569-2021, https://doi.org/10.5194/hess-25-1569-2021, 2021
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The SMAP L4 dataset has been extensively used in hydrological applications. We innovatively use a machine learning method to analyze how the efficiency of the L4 data assimilation (DA) system is determined. It shows that DA efficiency is mainly related to Tb innovation, followed by error in precipitation forcing and microwave soil roughness. Since the L4 system can effectively filter out precipitation error, future development should focus on correctly specifying the SSM–RZSM coupling strength.
Tanel Voormansik, Roberto Cremonini, Piia Post, and Dmitri Moisseev
Hydrol. Earth Syst. Sci., 25, 1245–1258, https://doi.org/10.5194/hess-25-1245-2021, https://doi.org/10.5194/hess-25-1245-2021, 2021
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A long set of operational polarimetric weather radar rainfall accumulations from Estonia and Italy are generated and investigated. Results show that the combined product of specific differential phase and horizontal reflectivity yields the best results when compared to rain gauge measurements. The specific differential-phase-based product overestimates weak precipitation, and the horizontal-reflectivity-based product underestimates heavy rainfall in all analysed accumulation periods.
Rogier van der Velde, Andreas Colliander, Michiel Pezij, Harm-Jan F. Benninga, Rajat Bindlish, Steven K. Chan, Thomas J. Jackson, Dimmie M. D. Hendriks, Denie C. M. Augustijn, and Zhongbo Su
Hydrol. Earth Syst. Sci., 25, 473–495, https://doi.org/10.5194/hess-25-473-2021, https://doi.org/10.5194/hess-25-473-2021, 2021
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NASA’s SMAP satellite provides estimates of the amount of water in the soil. With measurements from a network of 20 monitoring stations, the accuracy of these estimates has been studied for a 4-year period. We found an agreement between satellite and in situ estimates in line with the mission requirements once the large mismatches associated with rapidly changing water contents, e.g. soil freezing and rainfall, are excluded.
Moctar Dembélé, Bettina Schaefli, Nick van de Giesen, and Grégoire Mariéthoz
Hydrol. Earth Syst. Sci., 24, 5379–5406, https://doi.org/10.5194/hess-24-5379-2020, https://doi.org/10.5194/hess-24-5379-2020, 2020
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This study evaluates 102 combinations of rainfall and temperature datasets from satellite and reanalysis sources as input to a fully distributed hydrological model. The model is recalibrated for each input dataset, and the outputs are evaluated with streamflow, evaporation, soil moisture and terrestrial water storage data. Results show that no single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes.
Michael W. Burnett, Gregory R. Quetin, and Alexandra G. Konings
Hydrol. Earth Syst. Sci., 24, 4189–4211, https://doi.org/10.5194/hess-24-4189-2020, https://doi.org/10.5194/hess-24-4189-2020, 2020
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Water that evaporates from Africa's tropical forests provides rainfall throughout the continent. However, there are few sources of meteorological data in central Africa, so we use observations from satellites to estimate evaporation from the Congo Basin at different times of the year. We find that existing evaporation estimates in tropical Africa do not accurately capture seasonal variations in evaporation and that fluctuations in soil moisture and solar radiation drive evaporation rates.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 24, 2951–2962, https://doi.org/10.5194/hess-24-2951-2020, https://doi.org/10.5194/hess-24-2951-2020, 2020
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BARRA is a high-resolution reanalysis dataset over the Oceania region. This study evaluates the performance of sub-daily BARRA precipitation at point and spatial scales over Australia. We find that the dataset reproduces some of the sub-daily characteristics of precipitation well, although it exhibits some spatial displacement errors, and it performs better in temperate than in tropical regions. The product is well suited to complement other estimates derived from remote sensing and rain gauges.
Christian Massari, Luca Brocca, Thierry Pellarin, Gab Abramowitz, Paolo Filippucci, Luca Ciabatta, Viviana Maggioni, Yann Kerr, and Diego Fernandez Prieto
Hydrol. Earth Syst. Sci., 24, 2687–2710, https://doi.org/10.5194/hess-24-2687-2020, https://doi.org/10.5194/hess-24-2687-2020, 2020
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Rain gauges are unevenly spaced around the world with extremely low gauge density over places like Africa and South America. Here, water-related problems like floods, drought and famine are particularly severe and able to cause fatalities, migration and diseases. We have developed a rainfall dataset that exploits the synergies between rainfall and soil moisture to provide accurate rainfall observations which can be used to face these problems.
Floyd Vukosi Khosa, Mohau Jacob Mateyisi, Martina Reynita van der Merwe, Gregor Timothy Feig, Francois Alwyn Engelbrecht, and Michael John Savage
Hydrol. Earth Syst. Sci., 24, 1587–1609, https://doi.org/10.5194/hess-24-1587-2020, https://doi.org/10.5194/hess-24-1587-2020, 2020
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The paper evaluates soil moisture outputs from three structurally distinct models against in situ data. Our goal is to find how representative the model outputs are for site and region. This is a question of interest as some of the models have a specific regional focus on their inceptions. Much focus is placed on how the models capture the soil moisture signal. We find that there is agreement on seasonal patterns between the models and observations with a tolerable level of model uncertainty.
Yu Ma, Guangheng Ni, Chandrasekar V. Chandra, Fuqiang Tian, and Haonan Chen
Hydrol. Earth Syst. Sci., 23, 4153–4170, https://doi.org/10.5194/hess-23-4153-2019, https://doi.org/10.5194/hess-23-4153-2019, 2019
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Raindrop size distribution (DSD) information is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation. This study extensively investigates the DSD characteristics during rainy seasons in the Beijing urban area using 5-year DSD observations from a Parsivel2 disdrometer. The statistical distributions of DSD parameters are examined and the polarimetric radar rainfall algorithms are derived to support the ongoing development of an X-band radar network.
Suwash Chandra Acharya, Rory Nathan, Quan J. Wang, Chun-Hsu Su, and Nathan Eizenberg
Hydrol. Earth Syst. Sci., 23, 3387–3403, https://doi.org/10.5194/hess-23-3387-2019, https://doi.org/10.5194/hess-23-3387-2019, 2019
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BARRA is a novel regional reanalysis for Australia. Our research demonstrates that it is able to characterize a rich spatial variation in daily precipitation behaviour. In addition, its ability to represent large rainfalls is valuable for the analysis of extremes. It is a useful complement to existing precipitation datasets for Australia, especially in sparsely gauged regions.
Webster Gumindoga, Tom H. M. Rientjes, Alemseged Tamiru Haile, Hodson Makurira, and Paolo Reggiani
Hydrol. Earth Syst. Sci., 23, 2915–2938, https://doi.org/10.5194/hess-23-2915-2019, https://doi.org/10.5194/hess-23-2915-2019, 2019
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We evaluate the influence of elevation and distance from large-scale open water bodies on bias for CMORPH satellite rainfall in the Zambezi basin. Effects of distance > 10 km from water bodies are minimal, whereas the effects at shorter distances are indicated but are not conclusive for lack of rain gauges. Taylor diagrams show station elevation influencing CMORPH performance. The
spatio-temporaland newly developed
elevation zonebias schemes proved more effective in removing CMORPH bias.
Seshagiri Rao Kolusu, Mohammad Shamsudduha, Martin C. Todd, Richard G. Taylor, David Seddon, Japhet J. Kashaigili, Girma Y. Ebrahim, Mark O. Cuthbert, James P. R. Sorensen, Karen G. Villholth, Alan M. MacDonald, and Dave A. MacLeod
Hydrol. Earth Syst. Sci., 23, 1751–1762, https://doi.org/10.5194/hess-23-1751-2019, https://doi.org/10.5194/hess-23-1751-2019, 2019
Frédéric Satgé, Denis Ruelland, Marie-Paule Bonnet, Jorge Molina, and Ramiro Pillco
Hydrol. Earth Syst. Sci., 23, 595–619, https://doi.org/10.5194/hess-23-595-2019, https://doi.org/10.5194/hess-23-595-2019, 2019
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This paper assesses the potential of satellite precipitation estimates (SPEs) for precipitation measurement and hydrological and snow modelling. A total of 12 SPEs is considered to provide a global overview of available SPE accuracy for users interested in such datasets. Results show that, over poorly monitored regions, SPEs represent a very efficient alternative to traditional precipitation gauges to follow precipitation in time and space and for hydrological and snow modelling.
Maik Renner, Claire Brenner, Kaniska Mallick, Hans-Dieter Wizemann, Luigi Conte, Ivonne Trebs, Jianhui Wei, Volker Wulfmeyer, Karsten Schulz, and Axel Kleidon
Hydrol. Earth Syst. Sci., 23, 515–535, https://doi.org/10.5194/hess-23-515-2019, https://doi.org/10.5194/hess-23-515-2019, 2019
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We estimate the phase lag of surface states and heat fluxes to incoming solar radiation at the sub-daily timescale. While evapotranspiration reveals a minor phase lag, the vapor pressure deficit used as input by Penman–Monteith approaches shows a large phase lag. The surface-to-air temperature gradient used by energy balance residual approaches shows a small phase shift in agreement with the sensible heat flux and thus explains the better correlation of these models at the sub-daily timescale.
Victor Pellet, Filipe Aires, Simon Munier, Diego Fernández Prieto, Gabriel Jordá, Wouter Arnoud Dorigo, Jan Polcher, and Luca Brocca
Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019, https://doi.org/10.5194/hess-23-465-2019, 2019
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This study is an effort for a better understanding and quantification of the water cycle and related processes in the Mediterranean region, by dealing with satellite products and their uncertainties. The aims of the paper are 3-fold: (1) developing methods with hydrological constraints to integrate all the datasets, (2) giving the full picture of the Mediterranean WC, and (3) building a model-independent database that can evaluate the numerous regional climate models (RCMs) for this region.
Samiro Khodayar, Amparo Coll, and Ernesto Lopez-Baeza
Hydrol. Earth Syst. Sci., 23, 255–275, https://doi.org/10.5194/hess-23-255-2019, https://doi.org/10.5194/hess-23-255-2019, 2019
Franziska K. Fischer, Tanja Winterrath, and Karl Auerswald
Hydrol. Earth Syst. Sci., 22, 6505–6518, https://doi.org/10.5194/hess-22-6505-2018, https://doi.org/10.5194/hess-22-6505-2018, 2018
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The potential of rain to cause soil erosion by runoff is called rain erosivity. Rain erosivity is highly variable in space and time even over distances of less than 1 km. Contiguously measured radar rain data depict for the first time this spatio-temporal variation, but scaling factors are required to account for differences in spatial and temporal resolution compared to rain gauge data. These scaling factors were obtained from more than 2 million erosive events.
Phu Nguyen, Mohammed Ombadi, Soroosh Sorooshian, Kuolin Hsu, Amir AghaKouchak, Dan Braithwaite, Hamed Ashouri, and Andrea Rose Thorstensen
Hydrol. Earth Syst. Sci., 22, 5801–5816, https://doi.org/10.5194/hess-22-5801-2018, https://doi.org/10.5194/hess-22-5801-2018, 2018
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The goal of this article is to first provide an overview of the available PERSIANN precipitation retrieval algorithms and their differences. We evaluate the products over CONUS at different spatial and temporal scales using CPC data. Daily scale is the finest temporal scale used for the evaluation over CONUS. We provide a comparison of the available products at a quasi-global scale. We highlight the strengths and limitations of the PERSIANN products.
Jason A. Otkin, Yafang Zhong, David Lorenz, Martha C. Anderson, and Christopher Hain
Hydrol. Earth Syst. Sci., 22, 5373–5386, https://doi.org/10.5194/hess-22-5373-2018, https://doi.org/10.5194/hess-22-5373-2018, 2018
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Correlation analyses were used to explore relationships between the Evaporative Stress Index (ESI) – which depicts anomalies in evapotranspiration (ET) – and various land and atmospheric variables that impact ET. The results revealed that the ESI is more strongly correlated to anomalies in soil moisture and near-surface vapor pressure deficit than to precipitation and temperature anomalies. Large regional and seasonal dependencies in the strengths of the correlations were also observed.
Vikalp Mishra, James F. Cruise, Christopher R. Hain, John R. Mecikalski, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 22, 4935–4957, https://doi.org/10.5194/hess-22-4935-2018, https://doi.org/10.5194/hess-22-4935-2018, 2018
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Multiple satellite observations can be used for surface and subsurface soil moisture estimations. In this study, satellite observations along with a mathematical model were used to distribute and develop multiyear soil moisture profiles over the southeastern US. Such remotely sensed profiles become particularly useful at large spatiotemporal scales, can be a significant tool in data-scarce regions of the world, can complement various land and crop models, and can act as drought indicators etc.
Solomon Hailu Gebrechorkos, Stephan Hülsmann, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 22, 4547–4564, https://doi.org/10.5194/hess-22-4547-2018, https://doi.org/10.5194/hess-22-4547-2018, 2018
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In Africa field-based meteorological data are scarce; therefore global data sources based on remote sensing and climate models are often used as alternatives. To assess their suitability for a large and topographically complex area in East Africa, we evaluated multiple climate data products with available ground station data at multiple timescales over 21 regions. The comprehensive evaluation resulted in identification of preferential data sources to be used for climate and hydrological studies.
Ruifang Guo, Yuanbo Liu, Han Zhou, and Yaqiao Zhu
Hydrol. Earth Syst. Sci., 22, 3685–3699, https://doi.org/10.5194/hess-22-3685-2018, https://doi.org/10.5194/hess-22-3685-2018, 2018
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Existing satellite products are often insufficient for use in small-scale (< 10 km) hydrological and meteorological studies. We propose a new approach based on the cumulative distribution of frequency to downscale satellite precipitation products with geostationary (GEO) data. This paper uses CMORPH and FY2-E GEO data to examine the approach in six different climate regions. The downscaled precipitation performed better for convective systems.
Irina Y. Petrova, Chiel C. van Heerwaarden, Cathy Hohenegger, and Françoise Guichard
Hydrol. Earth Syst. Sci., 22, 3275–3294, https://doi.org/10.5194/hess-22-3275-2018, https://doi.org/10.5194/hess-22-3275-2018, 2018
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In North Africa rain storms can be as vital as they are devastating. The present study uses multi-year satellite data to better understand how and where soil moisture conditions affect development of rainfall in the area. Our results reveal two major regions in the southwest and southeast, where drier soils show higher potential to cause rainfall development. This knowledge is essential for the hydrological sector, and can be further used by models to improve prediction of rainfall and droughts.
Nishan Bhattarai, Kaniska Mallick, Nathaniel A. Brunsell, Ge Sun, and Meha Jain
Hydrol. Earth Syst. Sci., 22, 2311–2341, https://doi.org/10.5194/hess-22-2311-2018, https://doi.org/10.5194/hess-22-2311-2018, 2018
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We report the first ever regional-scale implementation of the Surface Temperature Initiated Closure (STIC1.2) model for mapping evapotranspiration (ET) using MODIS land surface and gridded climate datasets to overcome the existing uncertainties in aerodynamic temperature and conductance estimation in global ET models. Validation and intercomparison with SEBS and MOD16 products across an aridity gradient in the US manifested better ET mapping potential of STIC1.2 in different climates and biomes.
Edouard Goudenhoofdt, Laurent Delobbe, and Patrick Willems
Hydrol. Earth Syst. Sci., 21, 5385–5399, https://doi.org/10.5194/hess-21-5385-2017, https://doi.org/10.5194/hess-21-5385-2017, 2017
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Knowing the characteristics of extreme precipitation is useful for flood management applications like sewer system design. The potential of a 12-year high-quality weather radar precipitation dataset is investigated by comparison with rain gauges. Despite known limitations, a good agreement is found between the radar and the rain gauges. Using the radar data allow us to reduce the uncertainty of the extreme value analysis, especially for short duration extremes related to thunderstorms.
Christian Massari, Wade Crow, and Luca Brocca
Hydrol. Earth Syst. Sci., 21, 4347–4361, https://doi.org/10.5194/hess-21-4347-2017, https://doi.org/10.5194/hess-21-4347-2017, 2017
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The paper explores a method for the assessment of the performance of global rainfall estimates without relying on ground-based observations. Thanks to this method, different global correlation maps are obtained (for the first time without relying on a benchmark dataset) for some of the most used globally available rainfall products. This is central for hydroclimatic studies within data-scarce regions, where ground observations are scarce to evaluate the relative quality of a rainfall product
Beas Barik, Subimal Ghosh, A. Saheer Sahana, Amey Pathak, and Muddu Sekhar
Hydrol. Earth Syst. Sci., 21, 3041–3060, https://doi.org/10.5194/hess-21-3041-2017, https://doi.org/10.5194/hess-21-3041-2017, 2017
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The article summarises changing patterns of the water-food-energy nexus in India during recent decades. The work first analyses satellite data of water storage with a validation using the observed well data. Northern India shows a declining trend of water storage and western-central India shows an increasing trend of the same. Major droughts result in a drop in water storage which is not recovered due to uncontrolled ground water irrigation for agricultural activities even in good monsoon years.
David Fairbairn, Alina Lavinia Barbu, Adrien Napoly, Clément Albergel, Jean-François Mahfouf, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 2015–2033, https://doi.org/10.5194/hess-21-2015-2017, https://doi.org/10.5194/hess-21-2015-2017, 2017
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This study assesses the impact on river discharge simulations over France of assimilating ASCAT-derived surface soil moisture (SSM) and leaf area index (LAI) observations into the ISBA land surface model. Wintertime LAI has a notable impact on river discharge. SSM assimilation degrades river discharge simulations. This is caused by limitations in the simplified versions of the Kalman filter and ISBA model used in this study. Implementing an observation operator for ASCAT is needed.
Davi de C. D. Melo, Bridget R. Scanlon, Zizhan Zhang, Edson Wendland, and Lei Yin
Hydrol. Earth Syst. Sci., 20, 4673–4688, https://doi.org/10.5194/hess-20-4673-2016, https://doi.org/10.5194/hess-20-4673-2016, 2016
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Drought propagation from rainfall deficits to reservoir depletion was studied based on remote sensing, monitoring and modelling data. Regional droughts were shown by widespread depletion in total water storage that reduced soil moisture storage and runoff, greatly reducing reservoir storage. The multidisciplinary approach to drought assessment shows the linkages between meteorological and hydrological droughts that are essential for managing water resources subjected to climate extremes.
Zhi Qing Peng, Xiaozhou Xin, Jin Jun Jiao, Ti Zhou, and Qinhuo Liu
Hydrol. Earth Syst. Sci., 20, 4409–4438, https://doi.org/10.5194/hess-20-4409-2016, https://doi.org/10.5194/hess-20-4409-2016, 2016
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A remote sensing algorithm named temperature sharpening and flux aggregation (TSFA) was applied to HJ-1B satellite data to estimate evapotranspiration over heterogeneous surface considering landscape and statistical effects on mixed pixels. Footprint validation results showed TSFA was more accurate and less uncertain than other two upscaling methods. Additional analysis and comparison showed TSFA can capture land surface heterogeneities and integrate the effect of landscapes within mixed pixels.
Jian Peng, Alexander Loew, Xuelong Chen, Yaoming Ma, and Zhongbo Su
Hydrol. Earth Syst. Sci., 20, 3167–3182, https://doi.org/10.5194/hess-20-3167-2016, https://doi.org/10.5194/hess-20-3167-2016, 2016
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The Tibetan Plateau plays a major role in regional and global climate. The knowledge of latent heat flux can help to better describe the complex interactions between land and atmosphere. The purpose of this paper is to provide a detailed cross-comparison of existing latent heat flux products over the TP. The results highlight the recently developed latent heat product – High Resolution Land Surface Parameters from Space (HOLAPS).
J. Peng, J. Niesel, and A. Loew
Hydrol. Earth Syst. Sci., 19, 4765–4782, https://doi.org/10.5194/hess-19-4765-2015, https://doi.org/10.5194/hess-19-4765-2015, 2015
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This paper gives a comprehensive evaluation of a simple newly developed downscaling scheme using in situ measurements from REMEDHUS network, a first cross-comparison of the performance of the downscaled soil moisture from MODIS and MSG SEVIRI, an evaluation of the performance of the downscaled soil moisture at different spatial resolutions, and an exploration of the influence of LST, vegetation index, terrain, clouds, and land cover heterogeneity on the performance of VTCI.
G. Boulet, B. Mougenot, J.-P. Lhomme, P. Fanise, Z. Lili-Chabaane, A. Olioso, M. Bahir, V. Rivalland, L. Jarlan, O. Merlin, B. Coudert, S. Er-Raki, and J.-P. Lagouarde
Hydrol. Earth Syst. Sci., 19, 4653–4672, https://doi.org/10.5194/hess-19-4653-2015, https://doi.org/10.5194/hess-19-4653-2015, 2015
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The paper presents a new model (SPARSE) to estimate total evapotranspiration as well as its components (evaporation and transpiration) from remote-sensing data in the thermal infra-red domain. The limits of computing two unknowns (evaporation and transpiration) out of one piece of information (one surface temperature) are assessed theoretically. The model performance in retrieving the components as well as the water stress is assessed for two wheat crops (one irrigated and one rainfed).
O. P. Prat and B. R. Nelson
Hydrol. Earth Syst. Sci., 19, 2037–2056, https://doi.org/10.5194/hess-19-2037-2015, https://doi.org/10.5194/hess-19-2037-2015, 2015
Y. Duan, A. M. Wilson, and A. P. Barros
Hydrol. Earth Syst. Sci., 19, 1501–1520, https://doi.org/10.5194/hess-19-1501-2015, https://doi.org/10.5194/hess-19-1501-2015, 2015
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A diagnostic analysis of the space-time structure of error in quantitative precipitation estimates (QPEs) from the precipitation radar on the Tropical Rainfall Measurement Mission satellite is presented here in preparation for the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014. A high-density raingauge network over the southern Appalachians allows for direct comparison between ground-based measurements and satellite-based QPE (PR 2A25 Version 7 with 5 years of data 2008-2013).
A. W. Worqlul, B. Maathuis, A. A. Adem, S. S. Demissie, S. Langan, and T. S. Steenhuis
Hydrol. Earth Syst. Sci., 18, 4871–4881, https://doi.org/10.5194/hess-18-4871-2014, https://doi.org/10.5194/hess-18-4871-2014, 2014
S. Schneider, A. Jann, and T. Schellander-Gorgas
Hydrol. Earth Syst. Sci., 18, 2899–2905, https://doi.org/10.5194/hess-18-2899-2014, https://doi.org/10.5194/hess-18-2899-2014, 2014
R. van der Velde, M. S. Salama, T. Pellarin, M. Ofwono, Y. Ma, and Z. Su
Hydrol. Earth Syst. Sci., 18, 1323–1337, https://doi.org/10.5194/hess-18-1323-2014, https://doi.org/10.5194/hess-18-1323-2014, 2014
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Short summary
Rainfall frequency analyses from radar and satellite estimates over the eastern Mediterranean are compared examining different climatic conditions. Correlation between radar and satellite results is high for frequent events and decreases with return period. The uncertainty related to record length is larger for drier climates. The agreement between different sensors instills confidence on their use for rainfall frequency analysis in ungauged areas of the Earth.
Rainfall frequency analyses from radar and satellite estimates over the eastern Mediterranean...
