Articles | Volume 28, issue 5
https://doi.org/10.5194/hess-28-1147-2024
© Author(s) 2024. 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-28-1147-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Mar 2024
Research article |
| 07 Mar 2024
| 07 Mar 2024
A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze–Atbara Basin
Mohammed Abdallah
The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, Jiangsu, 210024, China
College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
The Hydraulics Research Station, P.O. Box 318, Wad Madani, Republic of the Sudan
The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, Jiangsu, 210024, China
College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
Yangtze Institute for Conservation and Development, Hohai University, Nanjing, Jiangsu, 210024, China
China Meteorological Administration Hydro-Meteorology Key Laboratory, Hohai University, Nanjing, Jiangsu, 210024, China
Key Laboratory of Water Big Data Technology of Ministry of Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
Lijun Chao
The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, Jiangsu, 210024, China
College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
China Meteorological Administration Hydro-Meteorology Key Laboratory, Hohai University, Nanjing, Jiangsu, 210024, China
Abubaker Omer
Moon Soul Graduate School of Future Strategy, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
Khalid Hassaballah
IGAD Climate Prediction and Applications Center (ICPAC), Nairobi, Kenya
Kidane Welde Reda
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Tigray Agricultural Research Institute, Mekele, Ethiopia
Linxin Liu
The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, Jiangsu, 210024, China
College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
Tolossa Lemma Tola
The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, Jiangsu, 210024, China
College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
Omar M. Nour
The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, Jiangsu, 210024, China
College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, 210024, China
The Hydraulics Research Station, P.O. Box 318, Wad Madani, Republic of the Sudan
Related authors
No articles found.
Jin Feng, Ke Zhang, Lijun Chao, Huijie Zhan, and Yunping Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-137, https://doi.org/10.5194/essd-2025-137, 2025
Revised manuscript under review for ESSD
Short summary
Short summary
Understanding how soil moisture affects evapotranspiration (ET) is essential for improving ET estimates. However, many global ET datasets overlook soil moisture constraints, causing large uncertainties. In this study, we developed an improved model that better captures the influence of soil moisture on vegetation and soil evaporation. Our model significantly improves ET estimation accuracy and provides a new long-term global ET dataset to support water cycle and climate research.
Nan Wu, Ke Zhang, Amir Naghibi, Hossein Hashemi, Zhongrui Ning, and Jerker Jarsjö
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-401, https://doi.org/10.5194/hess-2024-401, 2025
Revised manuscript under review for HESS
Short summary
Short summary
This study explores how snow dynamics and hydropower reservoirs shape monthly runoff in the Yalong River basin, China. Using 15 years of data and a extended Budyko framework, we found that snow accumulation and melt dominate runoff in high-altitude areas, while reservoirs increasingly influence lower elevations. These factors reduce runoff seasonality at the basin outlet, emphasizing how climate change and human activity alter water availability in cold, mountainous regions.
Jiefan Niu, Ke Zhang, Xi Li, and Hongjun Bao
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-304, https://doi.org/10.5194/hess-2024-304, 2024
Preprint under review for HESS
Short summary
Short summary
This study developed a new method for classifying catchments, combining machine learning techniques with climate and landscape data. By analyzing catchments across China, we identified six climate regions and 35 unique catchment types, each with distinct streamflow patterns. This classification method improves hydrological predictions, especially in areas lacking direct data.
Nan Wu, Ke Zhang, Amir Naghibi, Hossein Hashemi, Zhongrui Ning, Qinuo Zhang, Xuejun Yi, Haijun Wang, Wei Liu, Wei Gao, and Jerker Jarsjö
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-324, https://doi.org/10.5194/hess-2024-324, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
The hydrology of cold regions in the human population is poorly understood due to complex motion and limited data, hindering streamflow analysis. Using existing models, we compared runoff from an extended model with snowmelt and frozen ground, validating its reliability and integration. This study focuses on the effects of snowmelt and frozen ground on runoff, affecting precipitation type, surface-groundwater partitioning, and evapotranspiration.
Ileen N. Streefkerk, Jeroen C. J. H. Aerts, Jens de Bruijn, Khalid Hassaballah, Rhoda Odongo, Teun Schrieks, Oliver Wasonga, and Anne F. Van Loon
EGUsphere, https://doi.org/10.5194/egusphere-2024-2382, https://doi.org/10.5194/egusphere-2024-2382, 2024
Short summary
Short summary
In East Africa are conflict over water and vegetation prominent. On top of that, water abstraction of commercial farms are increasing the competition of water. Therefore, this study has developed a model which can investigate what the influence is of these farming activities on the water balance of the region and people's livelihood activities in times of dry periods. We do that by ‘replacing’ the farms in the model, and see what the effect would be if there were communities or forests instead.
Anne F. Van Loon, Sarra Kchouk, Alessia Matanó, Faranak Tootoonchi, Camila Alvarez-Garreton, Khalid E. A. Hassaballah, Minchao Wu, Marthe L. K. Wens, Anastasiya Shyrokaya, Elena Ridolfi, Riccardo Biella, Viorica Nagavciuc, Marlies H. Barendrecht, Ana Bastos, Louise Cavalcante, Franciska T. de Vries, Margaret Garcia, Johanna Mård, Ileen N. Streefkerk, Claudia Teutschbein, Roshanak Tootoonchi, Ruben Weesie, Valentin Aich, Juan P. Boisier, Giuliano Di Baldassarre, Yiheng Du, Mauricio Galleguillos, René Garreaud, Monica Ionita, Sina Khatami, Johanna K. L. Koehler, Charles H. Luce, Shreedhar Maskey, Heidi D. Mendoza, Moses N. Mwangi, Ilias G. Pechlivanidis, Germano G. Ribeiro Neto, Tirthankar Roy, Robert Stefanski, Patricia Trambauer, Elizabeth A. Koebele, Giulia Vico, and Micha Werner
Nat. Hazards Earth Syst. Sci., 24, 3173–3205, https://doi.org/10.5194/nhess-24-3173-2024, https://doi.org/10.5194/nhess-24-3173-2024, 2024
Short summary
Short summary
Drought is a creeping phenomenon but is often still analysed and managed like an isolated event, without taking into account what happened before and after. Here, we review the literature and analyse five cases to discuss how droughts and their impacts develop over time. We find that the responses of hydrological, ecological, and social systems can be classified into four types and that the systems interact. We provide suggestions for further research and monitoring, modelling, and management.
Guoding Chen, Ke Zhang, Sheng Wang, Yi Xia, and Lijun Chao
Geosci. Model Dev., 16, 2915–2937, https://doi.org/10.5194/gmd-16-2915-2023, https://doi.org/10.5194/gmd-16-2915-2023, 2023
Short summary
Short summary
In this study, we developed a novel modeling system called iHydroSlide3D v1.0 by coupling a modified a 3D landslide model with a distributed hydrology model. The model is able to apply flexibly different simulating resolutions for hydrological and slope stability submodules and gain a high computational efficiency through parallel computation. The test results in the Yuehe River basin, China, show a good predicative capability for cascading flood–landslide events.
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
Short summary
Short summary
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.
Marcos Longo, Ryan G. Knox, David M. Medvigy, Naomi M. Levine, Michael C. Dietze, Yeonjoo Kim, Abigail L. S. Swann, Ke Zhang, Christine R. Rollinson, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4309–4346, https://doi.org/10.5194/gmd-12-4309-2019, https://doi.org/10.5194/gmd-12-4309-2019, 2019
Short summary
Short summary
Our paper describes the Ecosystem Demography model. This computer program calculates how plants and ground exchange heat, water, and carbon with the air, and how plants grow, reproduce and die in different climates. Most models simplify forests to an average big tree. We consider that tall, deep-rooted trees get more light and water than small plants, and that some plants can with shade and drought. This diversity helps us to better explain how plants live and interact with the atmosphere.
Marcos Longo, Ryan G. Knox, Naomi M. Levine, Abigail L. S. Swann, David M. Medvigy, Michael C. Dietze, Yeonjoo Kim, Ke Zhang, Damien Bonal, Benoit Burban, Plínio B. Camargo, Matthew N. Hayek, Scott R. Saleska, Rodrigo da Silva, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4347–4374, https://doi.org/10.5194/gmd-12-4347-2019, https://doi.org/10.5194/gmd-12-4347-2019, 2019
Short summary
Short summary
The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates. To test if our calculations were reasonable, we compared our results with field and satellite measurements. Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air. However, it must improve the tree growth rates and how fast dead plants decompose.
Yingchun Huang, András Bárdossy, and Ke Zhang
Hydrol. Earth Syst. Sci., 23, 2647–2663, https://doi.org/10.5194/hess-23-2647-2019, https://doi.org/10.5194/hess-23-2647-2019, 2019
Short summary
Short summary
This study investigates whether higher temporal and spatial resolution of rainfall can lead to improved model performance. Four rainfall datasets were used to drive lumped and distributed HBV models to simulate daily discharges. Results show that a higher temporal resolution of rainfall improves the model performance if the station density is high. A combination of observed high temporal resolution observations with disaggregated daily rainfall leads to further improvement of the tested models.
Ke Zhang, Sheng Wang, Hongjun Bao, and Xiaomeng Zhao
Nat. Hazards Earth Syst. Sci., 19, 93–105, https://doi.org/10.5194/nhess-19-93-2019, https://doi.org/10.5194/nhess-19-93-2019, 2019
Short summary
Short summary
We investigated the spatiotemporal characteristics of landslide and debris flow hazards in Shaanxi Province and quantified the relationships between the occurrence rates of the two hazards and their influencing factors, including antecedent rainfall amount, rainfall duration, rainfall intensity, terrain slope, land cover type and soil type. Rainfall amount, duration, and intensity and slope are the dominant factors controlling slope stability across this region.
Matthieu Guimberteau, Philippe Ciais, Agnès Ducharne, Juan Pablo Boisier, Ana Paula Dutra Aguiar, Hester Biemans, Hannes De Deurwaerder, David Galbraith, Bart Kruijt, Fanny Langerwisch, German Poveda, Anja Rammig, Daniel Andres Rodriguez, Graciela Tejada, Kirsten Thonicke, Celso Von Randow, Rita C. S. Von Randow, Ke Zhang, and Hans Verbeeck
Hydrol. Earth Syst. Sci., 21, 1455–1475, https://doi.org/10.5194/hess-21-1455-2017, https://doi.org/10.5194/hess-21-1455-2017, 2017
Ke Zhang, Xianwu Xue, Yang Hong, Jonathan J. Gourley, Ning Lu, Zhanming Wan, Zhen Hong, and Rick Wooten
Hydrol. Earth Syst. Sci., 20, 5035–5048, https://doi.org/10.5194/hess-20-5035-2016, https://doi.org/10.5194/hess-20-5035-2016, 2016
Short summary
Short summary
We developed a new approach to couple a distributed hydrological model, CREST, to a geotechnical landslide model, TRIGRS, to simulate both flood- and rainfall-triggered landslide hazards. By implementing more sophisticated and realistic representations of hydrological processes in the coupled model system, it shows better performance than the standalone landslide model in the case study. It highlights the important physical connection between rainfall, hydrological processes and slope stability.
Amir K. Basheer, Haishen Lu, Abubaker Omer, Abubaker B. Ali, and Abdeldime M. S. Abdelgader
Hydrol. Earth Syst. Sci., 20, 1331–1353, https://doi.org/10.5194/hess-20-1331-2016, https://doi.org/10.5194/hess-20-1331-2016, 2016
Short summary
Short summary
We assess the impact of future climate change on Dinder River streamflow (Sudan), and infer its relative possible effects on the Dinder National Park (DNP) ecosystem habitats. Four GCMs from CMIP5 and two statistical downscaling approaches combined with SWAT were used. Climate over the basin will become warmer and wetter and streamflow will likely increase; accordingly, the ecosystems in the DNP will be affected positively and promote the ecological restoration of the flora and fauna habitats.
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
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
Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Francesco Marra, Efrat Morin, Nadav Peleg, Yiwen Mei, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 21, 2389–2404, https://doi.org/10.5194/hess-21-2389-2017, https://doi.org/10.5194/hess-21-2389-2017, 2017
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Cited articles
Aas, K., Czado, C., Frigessi, A., and Bakken, H.: Pair-copula constructions of multiple dependence, Insurance, 44, 182–198, https://doi.org/10.1016/j.insmatheco.2007.02.001, 2009.
Abdalla, E. M. H., Pons, V., Stovin, V., De-Ville, S., Fassman-Beck, E., Alfredsen, K., and Muthanna, T. M.: Evaluating different machine learning methods to simulate runoff from extensive green roofs, Hydrol. Earth Syst. Sci., 25, 5917–5935, https://doi.org/10.5194/hess-25-5917-2021, 2021.
Abdallah, M.: A D-vine copula-based quantile regression towards merging satellite precipitation products over a rugged topography: A case study at the upper Tekeze Atbara Basin of the Nile Basin, HydroShare [data set], http://www.hydroshare.org/resource/d0d9140845144d73ac578d865411a10a (last access: 25 February 2024), 2024.
Abdallah, M., Mohammadi, B., Zaroug, M. A. H., Omer, A., Cheraghalizadeh, M., Eldow, M. E. E., and Duan, Z.: Reference evapotranspiration estimation in hyper-arid regions via D-vine copula based-quantile regression and comparison with empirical approaches and machine learning models, J. Hydrol.: Reg. Stud., 44, 101259, https://doi.org/10.1016/j.ejrh.2022.101259, 2022.
Abebe, S. A., Qin, T. L., Yan, D. H., Gelaw, E. B., Workneh, H. T., Kun, W., Liu, S. S., and Dong, B. O.: Spatial and Temporal Evaluation of the Latest High-Resolution Precipitation Products over the Upper Blue Nile River Basin, Ethiopia, Water, 12, 20, https://doi.org/10.3390/w12113072, 2020.
Alfieri, L., Pappenberger, F., Wetterhall, F., Haiden, T., Richardson, D., and Salamon, P.: Evaluation of ensemble streamflow predictions in Europe, J. Hydrol., 517, 913–922, https://doi.org/10.1016/j.jhydrol.2014.06.035, 2014.
Amjad, M., Yilmaz, M. T., Yucel, I., and Yilmaz, K. K.: Performance evaluation of satellite- and model-based precipitation products over varying climate and complex topography, J. Hydrol., 584, 124707, https://doi.org/10.1016/j.jhydrol.2020.124707, 2020.
Baez-Villanueva, O. M., Zambrano-Bigiarini, M., Beck, H. E., McNamara, I., Ribbe, L., Nauditt, A., Birkel, C., Verbist, K., Giraldo-Osorio, J. D., and Thinh, N. X.: RF-MEP: A novel Random Forest method for merging gridded precipitation products and ground-based measurements, Remote Sens. Environ., 239, 111606, https://doi.org/10.1016/j.rse.2019.111606, 2020.
Barrett, E. C. and Martin, D. W.: Use of satellite data in rainfall monitoring, Academic Press, ISBN 0120796805, https://cir.nii.ac.jp/crid/1130000793777022720 (last access: 25 February 2024), 1981.
Belete, M., Deng, J. S., Wang, K., Zhou, M. M., Zhu, E. Y., Shifaw, E., and Bayissa, Y.: Evaluation of satellite rainfall products for modeling water yield over the source region of Blue Nile Basin, Sci. Total Environ., 708, 134834, https://doi.org/10.1016/j.scitotenv.2019.134834, 2020.
Bhuiyan, M. A. E., Nikolopoulos, E. I., Anagnostou, E. N., Quintana-Seguí, P., and Barella-Ortiz, A.: A nonparametric statistical technique for combining global precipitation datasets: Development and hydrological evaluation over the Iberian Peninsula, Hydrol. Earth Syst. Sci., 22, 1371–1389, https://doi.org/10.5194/hess-22-1371-2018, 2018.
Bhuiyan, M. A. E., Nikolopoulos, E. I., and Anagnostou, E. N.: Machine learning–based blending of satellite and reanalysis precipitation datasets: A multiregional tropical complex terrain evaluation, J. Hydrometeorol., 20, 2147–2161, https://doi.org/10.1175/JHM-D-19-0073.1, 2019.
Blocken, B., Poesen, J., and Carmeliet, J.: Impact of wind on the spatial distribution of rain over micro-scale topography: numerical modelling and experimental verification, Hydrol. Process., 20, 345–368, https://doi.org/10.1002/hyp.5865, 2006.
Bouyé, E. and Salmon, M.: Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets, Eur. J. Finance, 15, 721–750, https://doi.org/10.1080/13518470902853491, 2009.
Chao, L. J., Zhang, K., Li, Z. J., Zhu, Y. L., Wang, J. F., and Yu, Z. B.: Geographically weighted regression based methods for merging satellite and gauge precipitation, J. Hydrol., 558, 275–289, https://doi.org/10.1016/j.jhydrol.2018.01.042, 2018.
Chao, L. J., Zhang, K., Wang, J. F., Feng, J., and Zhang, M. J.: A Comprehensive Evaluation of Five Evapotranspiration Datasets Based on Ground and GRACE Satellite Observations: Implications for Improvement of Evapotranspiration Retrieval Algorithm, Remote Sens., 13, 2414, https://doi.org/10.3390/rs13122414, 2021.
Chen, L. and Guo, S.: Copulas and its application in hydrology and water resources, Springer, ISBN 978-981-13-0573-3, https://doi.org/10.1007/978-981-13-0574-0, 2019.
Chen, Y., Sharma, S., Zhou, X., Yang, K., Li, X., Niu, X., Hu, X., and Khadka, N.: Spatial performance of multiple reanalysis precipitation datasets on the southern slope of central Himalaya, Atmos. Res., 250, 105365, https://doi.org/10.1016/j.atmosres.2020.105365, 2021.
Chen, Y. Y., Huang, J. F., Sheng, S. X., Mansaray, L. R., Liu, Z. X., Wu, H. Y., and Wang, X. Z.: A new downscaling-integration framework for high-resolution monthly precipitation estimates: Combining rain gauge observations, satellite-derived precipitation data and geographical ancillary data, Remote Sens. Environ., 214, 154–172, https://doi.org/10.1016/j.rse.2018.05.021, 2018.
CHRS: PERSIANN, https://chrsdata.eng.uci.edu/ (last access: 25 February 2024), 2024.
Diem, J. E., Hartter, J., Ryan, S. J., and Palace, M. W.: Validation of satellite rainfall products for western Uganda, Journal of Hydrometeorology, 15, 2030–2038, https://doi.org/10.1175/JHM-D-13-0193.1, 2014.
Din, S. U., Al-Dousari, A., Ramdan, A., and Al Ghadban, A.: Site-specific precipitation estimate from TRMM data using bilinear weighted interpolation technique: An example from Kuwait, J. Arid Environ., 72, 1320–1328, https://doi.org/10.1016/j.jaridenv.2007.12.013, 2008.
Dinku, T., Ceccato, P., Grover-Kopec, E., Lemma, M., Connor, S. J., and Ropelewski, C. F.: Validation of satellite rainfall products over East Africa's complex topography, Int. J. Remote Sens., 28, 1503–1526, https://doi.org/10.1080/01431160600954688, 2007.
Dinku, T., Chidzambwa, S., Ceccato, P., Connor, S. J., and Ropelewski, C. F.: Validation of high-resolution satellite rainfall products over complex terrain, Int. J. Remote Sens., 29, 4097–4110, https://doi.org/10.1080/01431160701772526, 2008.
Dinku, T., Ceccato, P., and Connor, S. J.: Challenges of satellite rainfall estimation over mountainous and arid parts of east Africa, Int. J. Remote Sens., 32, 5965–5979, https://doi.org/10.1080/01431161.2010.499381, 2011.
Duan, Q. and Phillips, T. J.: Bayesian estimation of local signal and noise in multimodel simulations of climate change, J. Geophys. Res.-Atmos., 115, D18123, https://doi.org/10.1029/2009JD013654, 2010.
Duan, Q. Y., Ajami, N. K., Gao, X. G., and Sorooshian, S.: Multi-model ensemble hydrologic prediction using Bayesian model averaging, Adv. Water Resour., 30, 1371–1386, https://doi.org/10.1016/j.advwatres.2006.11.014, 2007.
Fenta, A. A., Yasuda, H., Shimizu, K., Ibaraki, Y., Haregeweyn, N., Kawai, T., Belay, A. S., Sultan, D., and Ebabu, K.: Evaluation of satellite rainfall estimates over the Lake Tana basin at the source region of the Blue Nile River, Atmos. Res., 212, 43–53, https://doi.org/10.1016/j.atmosres.2018.05.009, 2018.
Gebremedhin, M. A., Lubczynski, M. W., Maathuis, B. P., and Teka, D.: Novel approach to integrate daily satellite rainfall with in-situ rainfall, Upper Tekeze Basin, Ethiopia, Atmos. Res., 248, 105135, https://doi.org/10.1016/j.atmosres.2020.105135, 2021.
Gebremicael, T. G., Mohamed, Y. A., van der Zaag, P., Gebremedhin, A., Gebremeskel, G., Yazew, E., and Kifle, M.: Evaluation of multiple satellite rainfall products over the rugged topography of the Tekeze-Atbara basin in Ethiopia, Int. J. Remote Sens., 40, 4326–4345, https://doi.org/10.1080/01431161.2018.1562585, 2019.
Gebremicael, T. G., Deitch, M. J., Gancel, H. N., Croteau, A. C., Haile, G. G., Beyene, A. N., and Kumar, L.: Satellite-based rainfall estimates evaluation using a parsimonious hydrological model in the complex climate and topography of the Nile River Catchments, Atmos. Res., 266, 105939, https://doi.org/10.1016/j.atmosres.2021.105939, 2022.
Genest, C. and MacKay, R.J.,: Fonctions de repartition an dimensions et leurs marges, Can. J. Stat., 8, 229–231, https://doi.org/10.2307/3314660, 1959.
GLEAM: Method Global Land Evaporation Amsterdam Model, https://www.gleam.eu/ (last access: 25 February 2024), 2024.
Haile, A. T., Rientjes, T., Gieske, A., and Gebremichael, M.: Rainfall Variability over Mountainous and Adjacent Lake Areas: The Case of Lake Tana Basin at the Source of the Blue Nile River, J. Appl. Meteorol. Clim., 48, 1696–1717, https://doi.org/10.1175/2009jamc2092.1, 2009.
Haile, A. T., Habib, E., and Rientjes, T.: Evaluation of the climate prediction center (CPC) morphing technique (CMORPH) rainfall product on hourly time scales over the source of the Blue Nile River, Hydrol. Process., 27, 1829–1839, https://doi.org/10.1002/hyp.9330, 2013.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023.
Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D., Kojima, M., Oki, R., Nakamura, K., and Iguchi, T.: The Global Precipitation Measurement Mission, B. Am. Meteorol. Soc., 95, 701–722, https://doi.org/10.1175/bams-d-13-00164.1, 2014.
Hsu, K. L., Gao, X. G., Sorooshian, S., and Gupta, H. V.: Precipitation estimation from remotely sensed information using artificial neural networks, J. Appl. Meteorol., 36, 1176–1190, https://doi.org/10.1175/1520-0450(1997)036<1176:Pefrsi>2.0.Co;2, 1997.
Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K., Joyce, R., Xie, P. and Yoo, S. H.: NASA global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG), p. 30, https://gpm.nasa.gov/sites/default/files/2020-05/IMERG_ATBD_V06.3.pdf (last access: 24 February 2024), 2015.
Jennifer, A., David, M., Adrian, E. R., and Chris, V.: Bayesian model averaging: a tutorial, Stat. Sci., 14, 382–417, 1999.
Joyce, R. J., Janowiak, J. E., Arkin, P. A., and Xie, P. P.: CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution, J. Hydrometeorol., 5, 487–503, https://doi.org/10.1175/1525-7541(2004)005<0487:Camtpg>2.0.Co;2, 2004.
Kidd, C. and Huffman, G.: Global precipitation measurement, Meteorol. Appl., 18, 334–353, https://doi.org/10.1002/met.284, 2011.
Kidd, C., Becker, A., Huffman, G. J., Muller, C. L., Joe, P., Skofronick-Jackson, G., and Kirschbaum, D. B.: So, how much of the Earth's surface is covered by rain gauges?, B. Am. Meteorol. Soc., 98, 69–78, https://doi.org/10.1175/BAMS-D-14-00283.1, 2017.
Kimani, M. W., Hoedjes, J. C. B., and Su, Z. B.: An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa, Remote Sens., 9, 21, https://doi.org/10.3390/rs9050430, 2017.
Koenker, R. and Bassett, G.: Regression Quantiles, Econometrica, 46, 33–50, https://doi.org/10.2307/1913643, 1978.
Koenker, R. and Ng, P.: Inequality Constrained Quantile Regression. Sankhyā, 67, 418–440, 2005.
Koenker, R., Portnoy, S., Ng, P. T., Zeileis, A., Grosjean, P., and Ripley, B. D.: Package `quantreg', CRAN [code], https://cran.r-project.org/web/packages/quantreg/ (last access: 25 February 2024), 2018.
Kolluru, V., Kolluru, S., Wagle, N., and Acharya, T. D.: Secondary Precipitation Estimate Merging Using Machine Learning: Development and Evaluation over Krishna River Basin, India, Remote Sens., 12, 23, https://doi.org/10.3390/rs12183013, 2020.
Kraus, D. and Czado, C.: D-vine copula based quantile regression, Comput. Stat. Data Anal., 110, 1–18, https://doi.org/10.1016/j.csda.2016.12.009, 2017.
Kumar, A., Ramsankaran, R., Brocca, L., and Munoz-Arriola, F.: A Machine Learning Approach for Improving Near-Real-Time Satellite-Based Rainfall Estimates by Integrating Soil Moisture, Remote Sens., 11, 20, https://doi.org/10.3390/rs11192221, 2019.
Kumar, A., Ramsankaran, R., Brocca, L., and Muñoz-Arriola, F.: A simple machine learning approach to model real-time streamflow using satellite inputs: Demonstration in a data scarce catchment, J. Hydrol., 595, 126046, https://doi.org/10.1016/j.jhydrol.2021.126046, 2021.
Kurowicka, D. and Cooke, R. M.: Distribution-free continuous Bayesian belief, in: Modern statistical and mathematical methods in reliability, 10, World Scientific, p. 309. https://doi.org/10.1142/9789812703378_0022, 2005.
Li, Z., Yang, D. W., Gao, B., Jiao, Y., Hong, Y., and Xu, T.: Multiscale Hydrologic Applications of the Latest Satellite Precipitation Products in the Yangtze River Basin using a Distributed Hydrologic Model, J. Hydrometeorol., 16, 407–426, https://doi.org/10.1175/jhm-d-14-0105.1, 2015.
Lu, X., Tang, G., Wang, X., Liu, Y., Jia, L., Xie, G., Li, S., and Zhang, Y.: Correcting GPM IMERG precipitation data over the Tianshan Mountains in China, J. Hydrol., 575, 1239–1252, https://doi.org/10.1016/j.jhydrol.2019.06.019, 2019.
Ma, Y. Z., Zhang, Y. S., Yang, D. Q., and Bin Farhan, S.: Precipitation bias variability versus various gauges under different climatic conditions over the Third Pole Environment (TPE) region, Int. J. Climatol., 35, 1201–1211, https://doi.org/10.1002/joc.4045, 2015.
Ma, Y. Z., Yang, Y., Han, Z. Y., Tang, G. Q., Maguire, L., Chu, Z. G., and Hong, Y.: Comprehensive evaluation of Ensemble Multi-Satellite Precipitation Dataset using the Dynamic Bayesian Model Averaging scheme over the Tibetan plateau, J. Hydrol., 556, 634–644, https://doi.org/10.1016/j.jhydrol.2017.11.050, 2018.
Maidment, R. I., Grimes, D., Allan, R. P., Tarnavsky, E., Stringer, M., Hewison, T., Roebeling, R., and Black, E.: The 30 year TAMSAT African Rainfall Climatology And Time series (TARCAT) data set, J. Geophys. Res.-Atmos., 119, 10619–10644, https://doi.org/10.1002/2014jd021927, 2014.
Maidment, R. I., Grimes, D., Black, E., Tarnavsky, E., Young, M., Greatrex, H., Allan, R. P., Stein, T., Nkonde, E., Senkunda, S., and Alcantara, E. M. U.: Data Descriptor: A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa, Sci. Data, 4, 17, https://doi.org/10.1038/sdata.2017.63, 2017.
Manz, B., Buytaert, W., Zulkafli, Z., Lavado, W., Willems, B., Robles, L. A., and Rodríguez-Sánchez, J. P.: High-resolution satellite-gauge merged precipitation climatologies of the Tropical Andes, J. Geophys. Res.-Atmos., 121, 1190–1207, https://doi.org/10.1002/2015JD023788, 2016.
Mastrantonas, N., Bhattacharya, B., Shibuo, Y., Rasmy, M., Espinoza-Davalos, G., and Solomatine, D.: Evaluating the Benefits of Merging Near-Real-Time Satellite Precipitation Products: A Case Study in the Kinu Basin Region, Japan, J. Hydrometeorol., 20, 1213–1233, https://doi.org/10.1175/jhm-d-18-0190.1, 2019.
Moazami, S., Golian, S., Kavianpour, M. R., and Hong, Y.: Uncertainty analysis of bias from satellite rainfall estimates using copula method, Atmos. Res., 137, 145–166, https://doi.org/10.1016/j.atmosres.2013.08.016, 2014.
Mohammadi, B. and Aghashariatmadari, Z.: Estimation of solar radiation using neighboring stations through hybrid support vector regression boosted by Krill Herd algorithm, Arab. J. Geosci., 13, 16, https://doi.org/10.1007/s12517-020-05355-1, 2020.
Muhammad, W., Yang, H. B., Lei, H. M., Muhammad, A., and Yang, D. W.: Improving the Regional Applicability of Satellite Precipitation Products by Ensemble Algorithm, Remote Sens., 10, 19, https://doi.org/10.3390/rs10040577, 2018.
Nagler, T.: vinereg: D-Vine Quantile Regression, R package version 0.10.0, https://tnagler.github.io/vinereg/, GitHub [code], (last access: 25 February 2024), 2024.
NASA: GES DISC, https://disc.gsfc.nasa.gov/ (last access: 25 February 2024), 2024.
NASA Shuttle Radar Topography Mission – SRTM: Shuttle Radar Topography Mission (SRTM) Global, OpenTopography [data set], https://doi.org/10.5069/G9445JDF, 2013.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual models part I – A discussion of principles, J. Hydrol., 10, 282–290, https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
Nelsen, R. B.: An Introduction to Copulas, in: Springer Series in Statistics, Springer, ISBN 13:978-0387-28659-4, https://doi.org/10.1007/0-387-28678-0, 2005.
Nguyen, G. V., Le, X. H., Van, L. N., Jung, S., Yeon, M., and Lee, G.: Application of Random Forest Algorithm for Merging Multiple Satellite Precipitation Products across South Korea, Remote Sens., 13, 17, https://doi.org/10.3390/rs13204033, 2021.
Nguyen, H. H., Cho, S., Jeong, J., and Choi, M.: A D-vine copula quantile regression approach for soil moisture retrieval from dual polarimetric SAR Sentinel-1 over vegetated terrains, Remote Sens. Environ., 255, 112283, https://doi.org/10.1016/j.rse.2021.112283, 2021.
Niemierko, R., Toppel, J., and Trankler, T.: A D-vine copula quantile regression approach for the prediction of residential heating energy consumption based on historical data, Appl. Energy, 233, 691–708, https://doi.org/10.1016/j.apenergy.2018.10.025, 2019.
NOAA: Index of /data/cmorph-high-resolution-global-precipitation-estimates, NOAA [data set], https://www.ncei.noaa.gov/data/cmorph-high-resolution-global-precipitation-estimates/ (last access: 25 February 2024), 2024.
Parzen, E.: On estimation of a probability density function and mode, Ann. Math. Stat., 33, 1065–1076, 1962.
Pham, M. T., Vernieuwe, H., Baets, B. D., Willems, P., and Verhoest, N. E. C.: Stochastic simulation of precipitation-consistent daily reference evapotranspiration using vine copulas, Stoch. Environ. Res. Risk A., 30, 2197–2214, https://doi.org/10.1007/s00477-015-1181-7, 2016.
Pradhan, B., Jebur, M. N., Shafri, H. Z. M., and Tehrany, M. S.: Data fusion technique using wavelet transform and Taguchi methods for automatic landslide detection from airborne laser scanning data and quickbird satellite imagery, IEEE T. Geosci. Remote, 54, 1610–1622, https://doi.org/10.1109/TGRS.2015.2484325, 2015.
Qi, W., Zhang, C., Fu, G. T., Sweetapple, C., and Liu, Y. L.: Impact of robustness of hydrological model parameters on flood prediction uncertainty, J. Flood Risk Manage., 12, e12488, https://doi.org/10.1111/jfr3.12488, 2019.
Raftery, A. E., Gneiting, T., Balabdaoui, F., and Polakowski, M.: Using Bayesian model averaging to calibrate forecast ensembles, Mon. Weather Rev., 133, 1155—1174, https://doi.org/10.1175/mwr2906.1, 2005a.
Raftery, A. E., Painter, I. S., and Volinsky, C. T.: BMA: an R package for Bayesian model averaging, The Newsletter of the R Project Volume, CRAN [code], https://cran.r-project.org/web/packages/BMA (last access: 25 February 2024), 2005b.
Rahman, H. L. R., Shang, S. H., Shahid, M., Wen, Y. Q., and Khan, Z.: Application of a Dynamic Clustered Bayesian Model Averaging (DCBA) Algorithm for Merging Multisatellite Precipitation Products over Pakistan, J. Hydrometeorol., 21, 17–37, https://doi.org/10.1175/jhm-d-19-0087.1, 2020.
Rahman, K. U., Shang, S. H., Shahid, M., and Li, J.: Developing an Ensemble Precipitation Algorithm from Satellite Products and Its Topographical and Seasonal Evaluations Over Pakistan, Remote Sens., 10, 23, https://doi.org/10.3390/rs10111835, 2018.
Rahman, K. U., Shang, S. H., Shahid, M., and Wen, Y. Q.: An Appraisal of Dynamic Bayesian Model Averaging-based Merged Multi-Satellite Precipitation Datasets Over Complex Topography and the Diverse Climate of Pakistan, Remote Sens., 12, 30, hhttps://doi.org/10.3390/rs12010010, 2020a.
Rahman, K. U., Shang, S. H., Shahid, M., and Wen, Y. Q.: Hydrological evaluation of merged satellite precipitation datasets for streamflow simulation using SWAT: A case study of Potohar Plateau, Pakistan, J. Hydrol., 587, 125040, https://doi.org/10.1016/j.jhydrol.2020.125040, 2020b.
Rahman, K. U., Shang, S. H., Shahid, M., Wen, Y. Q., and Khan, A. J.: Development of a novel Weighted Average Least Squares-based ensemble multi-satellite precipitation dataset and its comprehensive evaluation over Pakistan, Atmos. Res., 246, 18, https://doi.org/10.1016/j.atmosres.2020.105133, 2020c.
Rahman, K. U., Shang, S. H., and Zohaib, M.: Assessment of Merged Satellite Precipitation Datasets in Monitoring Meteorological Drought over Pakistan, Remote Sens., 13, 37, https://doi.org/10.3390/rs13091662, 2021.
Reda, K. W., Liu, X. C., Tang, Q. H., and Gebremicael, T. G.: Evaluation of Global Gridded Precipitation and Temperature Datasets against Gauged Observations over the Upper Tekeze River Basin, Ethiopia, J. Meteorol. Res., 35, 673–689, https://doi.org/10.1007/s13351-021-0199-7, 2021.
Reda, K. W., Liu, X. C., Haile, G. G., Sun, S. A., and Tang, Q. H.: Hydrological evaluation of satellite and reanalysis-based rainfall estimates over the Upper Tekeze Basin, Ethiopia, Hydrol. Res., 53, 584–604, https://doi.org/10.2166/nh.2022.131, 2022.
Sen Gupta, A. and Tarboton, D. G.: A tool for downscaling weather data from large-grid reanalysis products to finer spatial scales for distributed hydrological applications, Environ. Model. Softw., 84, 50–69, https://doi.org/10.1016/j.envsoft.2016.06.014, 2016.
Sharifi, E., Saghafian, B., and Steinacker, R.: Copula-based stochastic uncertainty analysis of satellite precipitation products, J. Hydrol., 570, 739–754, https://doi.org/10.1016/j.jhydrol.2019.01.035, 2019.
Shen, Y., Xiong, A. Y., Hong, Y., Yu, J. J., Pan, Y., Chen, Z. Q., and Saharia, M.: Uncertainty analysis of five satellite-based precipitation products and evaluation of three optimally merged multi-algorithm products over the Tibetan Plateau, Int. J. Remote Sens., 35, 6843–6858, https://doi.org/10.1080/01431161.2014.960612, 2014.
Shi, Y., Chen, C., Chen, J., Mohammadi, B., Cheraghalizadeh, M., Abdallah, M., Mert Katipoğlu, O., Li, H., and Duan, Z.: Evaluation of the RF-MEP Method for Merging Multiple Gridded Precipitation Products in the Chongqing City, China, Remote Sens., 15, 4230, https://doi.org/10.3390/rs15174230, 2023.
Sun, R. C., Yuan, H. L., Liu, X. L., and Jiang, X. M.: Evaluation of the latest satellite-gauge precipitation products and their hydrologic applications over the Huaihe River basin, J. Hydrol., 536, 302–319, https://doi.org/10.1016/j.jhydrol.2016.02.054, 2016.
Sun, R. C., Yuan, H. L., and Yang, Y. Z.: Using multiple satellite-gauge merged precipitation products ensemble for hydrologic uncertainty analysis over the Huaihe River basin, J. Hydrol., 566, 406–420, https://doi.org/10.1016/j.jhydrol.2018.09.024, 2018.
Tan, J., Huffman, G. J., Bolvin, D. T., and Nelkin, E. J.: IMERG V06: Changes to the Morphing Algorithm, J. Atmos. Ocean. Tech., 36, 2471–2482, https://doi.org/10.1175/jtech-d-19-0114.1, 2019.
The National Meteorological Agency: Meteorological Station Information, http://www.ethiomet.gov.et/ (last access: 24 February 2024), 2016.
Ulloa, J., Ballari, D., Campozano, L., and Samaniego, E.: Two-Step Downscaling of Trmm 3b43 V7 Precipitation in Contrasting Climatic Regions With Sparse Monitoring: The Case of Ecuador in Tropical South America, Remote Sens., 9, 23, https://doi.org/10.3390/rs9070758, 2017.
University of Reading: TAMSAT, http://www.tamsat.org.uk/data (last access: 25 February 2024), 2024.
Viste, E. and Sorteberg, A.: Moisture transport into the Ethiopian highlands, Int. J. Climatol., 33, 249–263, https://doi.org/10.1002/joc.3409, 2013.
Wang, S., Zhang, K., Chao, L. J., Li, D. H., Tian, X., Bao, H. J., Chen, G. D., and Xia, Y.: Exploring the utility of radar and satellite-sensed precipitation and their dynamic bias correction for integrated prediction of flood and landslide hazards, J. Hydrol., 603, 126964, https://doi.org/10.1016/j.jhydrol.2021.126964, 2021.
WMO: Guide to hydrological practices: data aquisition and processing, analysis, forecasting and other applications, http://www.innovativehydrology.com/WMO-No.168-1994.pdf (last access: 24 February 2024), 1994.
Worqlul, A. W., Yen, H., Collick, A. S., Tilahun, S. A., Langan, S., and Steenhuis, T. S.: Evaluation of CFSR, TMPA 3B42 and ground-based rainfall data as input for hydrological models, in data-scarce regions: The upper Blue Nile Basin, Ethiopia, Catena, 152, 242–251, https://doi.org/10.1016/j.catena.2017.01.019, 2017.
Wu, H., Zhang, X., Liang, S., Yang, H., and Zhou, G.: Estimation of clear-sky land surface longwave radiation from MODIS data products by merging multiple models, J. Geophys. Res.-Atmos., 117, D22107, https://doi.org/10.1029/2012JD017567, 2012.
Wu, H., Yang, Q., Liu, J., and Wang, G.: A spatiotemporal deep fusion model for merging satellite and gauge precipitation in China, J. Hydrol., 584, 124664, https://doi.org/10.1016/j.jhydrol.2020.124664, 2020.
Wu, T., Bai, J., and Han, H.: Short-Term Agricultural Drought Prediction based on D-vine copula quantile regression in snow-free unfrozen surface area, China, Geocarto Int., 37, 9320–9338, https://doi.org/10.1080/10106049.2021.2017015, 2022.
Xiao, S., Xia, J., and Zou, L.: Evaluation of multi-satellite precipitation products and their ability in capturing the characteristics of extreme climate events over the Yangtze River Basin, China, Water, 12, 1179, https://doi.org/10.3390/w12041179, 2020.
Yong, B., Ren, L. L., Hong, Y., Wang, J. H., Gourley, J. J., Jiang, S. H., Chen, X., and Wang, W.: Hydrologic evaluation of Multisatellite Precipitation Analysis standard precipitation products in basins beyond its inclined latitude band: A case study in Laohahe basin, China, Water Resour. Res., 46, W07542, https://doi.org/10.1029/2009wr008965, 2010.
Young, M. P., Williams, C. J. R., Chiu, J. C., Maidment, R. I., and Chen, S.-H.: Investigation of discrepancies in satellite rainfall estimates over Ethiopia, J. Hydrometeorol., 15, 2347–2369, https://doi.org/10.1175/JHM-D-13-0111.1, 2014.
Yumnam, K., Guntu, R. K., Rathinasamy, M., and Agarwal, A.: Quantile-based Bayesian Model Averaging approach towards merging of precipitation products, J. Hydrol., 604, 127206, https://doi.org/10.1016/j.jhydrol.2021.127206, 2022.
Zhang, K., Xue, X. W., Hong, Y., Gourley, J. J., Lu, N., Wan, Z. M., Hong, Z., and Wooten, R.: iCRESTRIGRS: a coupled modeling system for cascading flood-landslide disaster forecasting, Hydrol. Earth Syst. Sci., 20, 5035–5048, https://doi.org/10.5194/hess-20-5035-2016, 2016.
Zubieta, R., Getirana, A., Espinoza, J. C., Lavado-Casimiro, W., and Aragon, L.: Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset, Hydrol. Earth Syst. Sci., 21, 3543–3555, https://doi.org/10.5194/hess-21-3543-2017, 2017.
Short summary
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.
A D-vine copula-based quantile regression (DVQR) model is used to merge satellite precipitation...
