Articles | Volume 17, issue 7
https://doi.org/10.5194/hess-17-2859-2013
© Author(s) 2013. 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-17-2859-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
23 Jul 2013
Research article |
| 23 Jul 2013
Drought evolution characteristics and precipitation intensity changes during alternating dry–wet changes in the Huang–Huai–Hai River basin
D. H. Yan
State Key Laboratory of Simulation and Regulation of River Basin Water Cycle, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Water Resources Department, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
D. Wu
State Key Laboratory of Simulation and Regulation of River Basin Water Cycle, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Water Resources Department, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
R. Huang
State Key Laboratory of Simulation and Regulation of River Basin Water Cycle, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Water Resources Department, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
L. N. Wang
State Key Laboratory of Simulation and Regulation of River Basin Water Cycle, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Water Resources Department, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
G. Y. Yang
State Key Laboratory of Simulation and Regulation of River Basin Water Cycle, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
Water Resources Department, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, 100038, China
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Hydrol. Earth Syst. Sci., 24, 1–16, https://doi.org/10.5194/hess-24-1-2020, https://doi.org/10.5194/hess-24-1-2020, 2020
Guoxiao Wei, Xiaoying Zhang, Ming Ye, Ning Yue, and Fei Kan
Hydrol. Earth Syst. Sci., 23, 2877–2895, https://doi.org/10.5194/hess-23-2877-2019, https://doi.org/10.5194/hess-23-2877-2019, 2019
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Accurately evaluating evapotranspiration (ET) is a critical challenge in improving hydrological process modeling. Here we evaluated four ET models (PM, SW, PT–FC, and AA) under the Bayesian framework. Our results reveal that the SW model has the best performance. This is in part because the SW model captures the main physical mechanism in ET; the other part is that the key parameters, such as the extinction factor, could be well constrained with observation data.
Chongli Di, Tiejun Wang, Xiaohua Yang, and Siliang Li
Hydrol. Earth Syst. Sci., 22, 5069–5079, https://doi.org/10.5194/hess-22-5069-2018, https://doi.org/10.5194/hess-22-5069-2018, 2018
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The original Grassberger–Procaccia algorithm for complex analysis was modified by incorporating the normal-based K-means clustering technique and the RANSAC algorithm. The calculation accuracy of the proposed method was shown to outperform traditional algorithms. The proposed algorithm was used to diagnose climate system complexity in the Hai He basin. The spatial patterns of the complexity of precipitation and air temperature reflected the influence of the dominant climate system.
César Cisneros Vaca, Christiaan van der Tol, and Chandra Prasad Ghimire
Hydrol. Earth Syst. Sci., 22, 3701–3719, https://doi.org/10.5194/hess-22-3701-2018, https://doi.org/10.5194/hess-22-3701-2018, 2018
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The influence of long-term changes in canopy structure on rainfall interception loss was studied in a 55-year old forest. Interception loss was similar at the same site (38 %), when the forest was 29 years old. In the past, the forest was denser and had a higher storage capacity, but the evaporation rates were lower. We emphasize the importance of quantifying downward sensible heat flux and heat release from canopy biomass in tall forest in order to improve the quantification of evaporation.
Sojung Park, Seon Ki Park, Jeung Whan Lee, and Yunho Park
Hydrol. Earth Syst. Sci., 22, 3435–3452, https://doi.org/10.5194/hess-22-3435-2018, https://doi.org/10.5194/hess-22-3435-2018, 2018
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Understanding the precipitation characteristics is essential to design an optimal observation network. We studied the spatial and temporal characteristics of summertime precipitation systems in Korea via geostatistical analyses on the ground-based precipitation and satellite water vapor data. We found that, under a strict standard, an observation network with higher resolution is required in local areas with frequent heavy rainfalls, depending on directional features of precipitation systems.
Wenbin Liu, Fubao Sun, Yanzhong Li, Guoqing Zhang, Yan-Fang Sang, Wee Ho Lim, Jiahong Liu, Hong Wang, and Peng Bai
Hydrol. Earth Syst. Sci., 22, 351–371, https://doi.org/10.5194/hess-22-351-2018, https://doi.org/10.5194/hess-22-351-2018, 2018
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The dynamics of basin-scale water budgets over the Tibetan Plateau (TP) are not well understood nowadays due to the lack of hydro-climatic observations. In this study, we investigate seasonal cycles and trends of water budget components (e.g. precipitation P, evapotranspiration ET and runoff Q) in 18 TP river basins during the period 1982–2011 through the use of multi-source datasets (e.g. in situ observations, satellite retrievals, reanalysis outputs and land surface model simulations).
Harsh Beria, Trushnamayee Nanda, Deepak Singh Bisht, and Chandranath Chatterjee
Hydrol. Earth Syst. Sci., 21, 6117–6134, https://doi.org/10.5194/hess-21-6117-2017, https://doi.org/10.5194/hess-21-6117-2017, 2017
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High-quality satellite precipitation forcings have provided a viable alternative to hydrologic modeling in data-scarce regions. Ageing TRMM sensors have recently been upgraded to GPM, promising enhanced spatio-temporal resolutions. Statistical and hydrologic evaluation of GPM measurements across 86 Indian river basins revealed improved low rainfall estimates with reduced effects of climatology and topography.
James C. Bennett, Quan J. Wang, David E. Robertson, Andrew Schepen, Ming Li, and Kelvin Michael
Hydrol. Earth Syst. Sci., 21, 6007–6030, https://doi.org/10.5194/hess-21-6007-2017, https://doi.org/10.5194/hess-21-6007-2017, 2017
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We assess a new streamflow forecasting system in Australia. The system is designed to meet the need of water agencies for 12-month forecasts. The forecasts perform well in a wide range of rivers. Forecasts for shorter periods (up to 6 months) are generally informative. Forecasts sometimes did not perform well in a few very dry rivers. We test several techniques for improving streamflow forecasts in drylands, with mixed success.
Konrad Bogner, Katharina Liechti, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 21, 5493–5502, https://doi.org/10.5194/hess-21-5493-2017, https://doi.org/10.5194/hess-21-5493-2017, 2017
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The enhanced availability of many different weather prediction systems nowadays makes it very difficult for flood and water resource managers to choose the most reliable and accurate forecast. In order to circumvent this problem of choice, different approaches for combining this information have been applied at the Sihl River (CH) and the results have been verified. The outcome of this study highlights the importance of forecast combination in order to improve the quality of forecast systems.
Matthew B. Switanek, Peter A. Troch, Christopher L. Castro, Armin Leuprecht, Hsin-I Chang, Rajarshi Mukherjee, and Eleonora M. C. Demaria
Hydrol. Earth Syst. Sci., 21, 2649–2666, https://doi.org/10.5194/hess-21-2649-2017, https://doi.org/10.5194/hess-21-2649-2017, 2017
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The commonly used bias correction method called quantile mapping assumes a constant function of error correction values between modeled and observed distributions. Our article finds that this function cannot be assumed to be constant. We propose a new bias correction method, called scaled distribution mapping, that does not rely on this assumption. Furthermore, the proposed method more explicitly accounts for the frequency of rain days and the likelihood of individual events.
Tesfay G. Gebremicael, Yasir A. Mohamed, Pieter v. Zaag, and Eyasu Y. Hagos
Hydrol. Earth Syst. Sci., 21, 2127–2142, https://doi.org/10.5194/hess-21-2127-2017, https://doi.org/10.5194/hess-21-2127-2017, 2017
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This study was conducted to understand the spatio-temporal variations of streamflow in the Tekezē basin. Results showed rainfall over the basin did not significantly change. However, streamflow experienced high variabilities at seasonal and annual scales. Further studies are needed to verify hydrological changes by identifying the physical mechanisms behind those changes. Findings are useful as prerequisite for studying the effects of catchment management dynamics on the hydrological processes.
Louise Crochemore, Maria-Helena Ramos, Florian Pappenberger, and Charles Perrin
Hydrol. Earth Syst. Sci., 21, 1573–1591, https://doi.org/10.5194/hess-21-1573-2017, https://doi.org/10.5194/hess-21-1573-2017, 2017
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The use of general circulation model outputs for streamflow forecasting has developed in the last decade. In parallel, traditional streamflow forecasting is commonly based on historical data. This study investigates the impact of conditioning historical data based on circulation model precipitation forecasts on seasonal streamflow forecast quality. Results highlighted a trade-off between the sharpness and reliability of forecasts.
Louise Crochemore, Maria-Helena Ramos, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 20, 3601–3618, https://doi.org/10.5194/hess-20-3601-2016, https://doi.org/10.5194/hess-20-3601-2016, 2016
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This study investigates the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. Eight variants of bias correction approaches based on the linear scaling and the distribution mapping methods are applied to the precipitation forecasts prior to generating the streamflow forecasts. One of the main results of the study is that distribution mapping of daily values is successful in improving forecast reliability.
P. Froidevaux, J. Schwanbeck, R. Weingartner, C. Chevalier, and O. Martius
Hydrol. Earth Syst. Sci., 19, 3903–3924, https://doi.org/10.5194/hess-19-3903-2015, https://doi.org/10.5194/hess-19-3903-2015, 2015
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We investigate precipitation characteristics prior to 4000 annual floods in Switzerland since 1961. The floods were preceded by heavy precipitation, but in most catchments extreme precipitation occurred only during the last 3 days prior to the flood events. Precipitation sums for earlier time periods (like e.g. 4-14 days prior to floods) were mostly average and do not correlate with the return period of the floods.
G. H. Fang, J. Yang, Y. N. Chen, and C. Zammit
Hydrol. Earth Syst. Sci., 19, 2547–2559, https://doi.org/10.5194/hess-19-2547-2015, https://doi.org/10.5194/hess-19-2547-2015, 2015
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This study compares the effects of five precipitation and three temperature correction methods on precipitation, temperature, and streamflow through loosely coupling RCM (RegCM) and a distributed hydrological model (SWAT) in terms of frequency-based indices and time-series-based indices. The methodology and results can be used for other regions and other RCM and hydrologic models, and for impact studies of climate change on water resources at a regional scale.
M. S. Siam and E. A. B. Eltahir
Hydrol. Earth Syst. Sci., 19, 1181–1192, https://doi.org/10.5194/hess-19-1181-2015, https://doi.org/10.5194/hess-19-1181-2015, 2015
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This paper explains the different natural modes of interannual variability in the flow of the Nile River and also presents a new index based on the sea surface temperature (SST) over the southern Indian Ocean to forecast the flow of the Nile River. It also presents a new hybrid forecasting algorithm that can be used to predict the Nile flow based on indices of the SST in the eastern Pacific and southern Indian oceans.
D. Halwatura, A. M. Lechner, and S. Arnold
Hydrol. Earth Syst. Sci., 19, 1069–1091, https://doi.org/10.5194/hess-19-1069-2015, https://doi.org/10.5194/hess-19-1069-2015, 2015
G. Panthou, T. Vischel, T. Lebel, G. Quantin, and G. Molinié
Hydrol. Earth Syst. Sci., 18, 5093–5107, https://doi.org/10.5194/hess-18-5093-2014, https://doi.org/10.5194/hess-18-5093-2014, 2014
D. Masson and C. Frei
Hydrol. Earth Syst. Sci., 18, 4543–4563, https://doi.org/10.5194/hess-18-4543-2014, https://doi.org/10.5194/hess-18-4543-2014, 2014
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The question of how to utilize information from the physiography/topography in the spatial interpolation of rainfall is a long-standing discussion in the literature. In this study we test ideas that go beyond the approach in popular interpolation schemes today. The key message of our study is that these ideas can at best marginally improve interpolation accuracy, even in a region where a clear benefit would intuitively be expected.
A. Casanueva, C. Rodríguez-Puebla, M. D. Frías, and N. González-Reviriego
Hydrol. Earth Syst. Sci., 18, 709–725, https://doi.org/10.5194/hess-18-709-2014, https://doi.org/10.5194/hess-18-709-2014, 2014
F. Yusof, I. L. Kane, and Z. Yusop
Hydrol. Earth Syst. Sci., 17, 1311–1318, https://doi.org/10.5194/hess-17-1311-2013, https://doi.org/10.5194/hess-17-1311-2013, 2013
J. H. Lee, J. Timmermans, Z. Su, and M. Mancini
Hydrol. Earth Syst. Sci., 16, 4291–4302, https://doi.org/10.5194/hess-16-4291-2012, https://doi.org/10.5194/hess-16-4291-2012, 2012
L. Gudmundsson, J. B. Bremnes, J. E. Haugen, and T. Engen-Skaugen
Hydrol. Earth Syst. Sci., 16, 3383–3390, https://doi.org/10.5194/hess-16-3383-2012, https://doi.org/10.5194/hess-16-3383-2012, 2012
T. Bosshard, S. Kotlarski, T. Ewen, and C. Schär
Hydrol. Earth Syst. Sci., 15, 2777–2788, https://doi.org/10.5194/hess-15-2777-2011, https://doi.org/10.5194/hess-15-2777-2011, 2011
S. Nie, J. Zhu, and Y. Luo
Hydrol. Earth Syst. Sci., 15, 2437–2457, https://doi.org/10.5194/hess-15-2437-2011, https://doi.org/10.5194/hess-15-2437-2011, 2011
G. Ibarra-Berastegi, J. Saénz, A. Ezcurra, A. Elías, J. Diaz Argandoña, and I. Errasti
Hydrol. Earth Syst. Sci., 15, 1895–1907, https://doi.org/10.5194/hess-15-1895-2011, https://doi.org/10.5194/hess-15-1895-2011, 2011
R. Schiemann, R. Erdin, M. Willi, C. Frei, M. Berenguer, and D. Sempere-Torres
Hydrol. Earth Syst. Sci., 15, 1515–1536, https://doi.org/10.5194/hess-15-1515-2011, https://doi.org/10.5194/hess-15-1515-2011, 2011
A. Lü, S. Jia, W. Zhu, H. Yan, S. Duan, and Z. Yao
Hydrol. Earth Syst. Sci., 15, 1273–1281, https://doi.org/10.5194/hess-15-1273-2011, https://doi.org/10.5194/hess-15-1273-2011, 2011
G. Wang, A. J. Dolman, and A. Alessandri
Hydrol. Earth Syst. Sci., 15, 57–64, https://doi.org/10.5194/hess-15-57-2011, https://doi.org/10.5194/hess-15-57-2011, 2011
F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara
Hydrol. Earth Syst. Sci., 14, 951–964, https://doi.org/10.5194/hess-14-951-2010, https://doi.org/10.5194/hess-14-951-2010, 2010
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