Articles | Volume 24, issue 3
https://doi.org/10.5194/hess-24-1347-2020
© Author(s) 2020. 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-24-1347-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Mar 2020
Research article |
| 23 Mar 2020
| 23 Mar 2020
Dynamics of hydrological-model parameters: mechanisms, problems and solutions
Tian Lan
School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Kairong Lin
CORRESPONDING AUTHOR
School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Guangdong Engineering Technology Research Center of Water Security
Regulation and Control for Southern China, Guangzhou, 510275, China
School of Civil Engineering, Sun Yat-sen University, Guangzhou,
510275, China
Chong-Yu Xu
Department of Geosciences, University of Oslo, P.O. Box 1047 Blindern, 0316 Oslo, Norway
Xuezhi Tan
School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Guangdong Engineering Technology Research Center of Water Security
Regulation and Control for Southern China, Guangzhou, 510275, China
School of Civil Engineering, Sun Yat-sen University, Guangzhou,
510275, China
Xiaohong Chen
School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
Guangdong Engineering Technology Research Center of Water Security
Regulation and Control for Southern China, Guangzhou, 510275, China
School of Civil Engineering, Sun Yat-sen University, Guangzhou,
510275, China
Related authors
Tian Lan, Kairong Lin, Chong-Yu Xu, Zhiyong Liu, and Huayang Cai
Hydrol. Earth Syst. Sci., 24, 5859–5874, https://doi.org/10.5194/hess-24-5859-2020, https://doi.org/10.5194/hess-24-5859-2020, 2020
Tian Lan, Kairong Lin, Xuezhi Tan, Chong-Yu Xu, and Xiaohong Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-301, https://doi.org/10.5194/hess-2019-301, 2019
Manuscript not accepted for further review
Short summary
Short summary
A calibration scheme was developed for the dynamics of hydrological model parameters. Furthermore, a novel tool was designed to assess the reliability of the dynamized parameter set. The tool evaluates the convergence processes for global optimization algorithms using violin plots (ECP-VP). The results showed that the developed calibration scheme overcame the salient issues for poor model performance. Besides, the ECP-VP tool effectively assessed the reliability of the dynamic parameter set.
Tongtiegang Zhao, Zexin Chen, Yu Tian, and Xiaohong Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-83, https://doi.org/10.5194/hess-2024-83, 2024
Preprint under review for HESS
Short summary
Short summary
The local performance plays a critical part in practical applications of global streamflow reanalysis. This paper develops a decomposition approach to facilitating evaluations at different timescales. It is found that the reanalysis tends to be more effective in characterizing seasonal, annual and multi-annual features than daily, weekly and monthly features. The local performance is shown to be primarily influenced by precipitation seasonality, longitude, mean precipitation and mean slope.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Gokturk
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-68, https://doi.org/10.5194/hess-2024-68, 2024
Preprint under review for HESS
Short summary
Short summary
We compared extreme precipitations in Norway from convection-permitting models at 3 km resolution (HCLIM3) and regional climate model at 12 km (HCLIM12) and show that the HCLIM3 is more accurate than HCLIM12 in predicting the intense rainfalls that can lead to floods, especially at local scales. This is more clear in hourly extremes than daily. Our research suggests using more detailed climate models could improve forecasts, helping the local society brace for the impacts of extreme weather.
Jinghua Xiong, Shenglian Guo, Abhishek, Jiabo Yin, Chongyu Xu, Jun Wang, and Jing Guo
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-265, https://doi.org/10.5194/hess-2023-265, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
Temporal variability and spatial heterogeneity of climate systems challenge the accurate estimation of probable maximum precipitation (PMP) in China. We use high-resolution precipitation data and climate models to explore the variability, trends, and shifts of PMP under climate change. Validated with multi-source estimations, our observations and simulations show significant spatiotemporal divergence of PMP over country, which is projected to amplify in future due to land-atmosphere coupling.
Danielle M. Barna, Kolbjørn Engeland, Thomas Kneib, Thordis L. Thorarinsdottir, and Chong-Yu Xu
EGUsphere, https://doi.org/10.5194/egusphere-2023-2335, https://doi.org/10.5194/egusphere-2023-2335, 2023
Preprint archived
Short summary
Short summary
Estimating flood quantiles at data-scarce sites often involves single-duration regression models. However, floodplain management and reservoir design, for example, need estimates at several durations, posing challenges. Our flexible generalized additive model (GAM) enhances accuracy and explanation, revealing that single-duration models may underperform elsewhere, emphasizing the need for adaptable approaches.
Pengxiang Wang, Zuhao Zhou, Jiajia Liu, Chongyu Xu, Kang Wang, Yangli Liu, Jia Li, Yuqing Li, Yangwen Jia, and Hao Wang
Hydrol. Earth Syst. Sci., 27, 2681–2701, https://doi.org/10.5194/hess-27-2681-2023, https://doi.org/10.5194/hess-27-2681-2023, 2023
Short summary
Short summary
Considering the impact of the special geological and climatic conditions of the Qinghai–Tibet Plateau on the hydrological cycle, this study established the WEP-QTP hydrological model. The snow cover and gravel layers affected the temporal and spatial changes in frozen soil and improved the regulation of groundwater on the flow process. Ignoring he influence of special underlying surface conditions has a great impact on the hydrological forecast and water resource utilization in this area.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-106, https://doi.org/10.5194/hess-2023-106, 2023
Revised manuscript under review for HESS
Short summary
Short summary
Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (HUP) with the Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method to reduce inflow forecasting uncertainty of the Three Gorges reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Shanlin Tong, Weiguang Wang, Jie Chen, Chong-Yu Xu, Hisashi Sato, and Guoqing Wang
Geosci. Model Dev., 15, 7075–7098, https://doi.org/10.5194/gmd-15-7075-2022, https://doi.org/10.5194/gmd-15-7075-2022, 2022
Short summary
Short summary
Plant carbon storage potential is central to moderate atmospheric CO2 concentration buildup and mitigation of climate change. There is an ongoing debate about the main driver of carbon storage. To reconcile this discrepancy, we use SEIB-DGVM to investigate the trend and response mechanism of carbon stock fractions among water limitation regions. Results show that the impact of CO2 and temperature on carbon stock depends on water limitation, offering a new perspective on carbon–water coupling.
Tongtiegang Zhao, Haoling Chen, Yu Tian, Denghua Yan, Weixin Xu, Huayang Cai, Jiabiao Wang, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 26, 4233–4249, https://doi.org/10.5194/hess-26-4233-2022, https://doi.org/10.5194/hess-26-4233-2022, 2022
Short summary
Short summary
This paper develops a novel set operations of coefficients of determination (SOCD) method to explicitly quantify the overlapping and differing information for GCM forecasts and ENSO teleconnection. Specifically, the intersection operation of the coefficient of determination derives the overlapping information for GCM forecasts and the Niño3.4 index, and then the difference operation determines the differing information in GCM forecasts (Niño3.4 index) from the Niño3.4 index (GCM forecasts).
Tongtiegang Zhao, Haoling Chen, Quanxi Shao, Tongbi Tu, Yu Tian, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 25, 5717–5732, https://doi.org/10.5194/hess-25-5717-2021, https://doi.org/10.5194/hess-25-5717-2021, 2021
Short summary
Short summary
This paper develops a novel approach to attributing correlation skill of dynamical GCM forecasts to statistical El Niño–Southern Oscillation (ENSO) teleconnection using the coefficient of determination. Three cases of attribution are effectively facilitated, which are significantly positive anomaly correlation attributable to positive ENSO teleconnection, attributable to negative ENSO teleconnection and not attributable to ENSO teleconnection.
Pengxiang Wang, Zuhao Zhou, Jiajia Liu, Chongyu Xu, Kang Wang, Yangli Liu, Jia Li, Yuqing Li, Yangwen Jia, and Hao Wang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-538, https://doi.org/10.5194/hess-2021-538, 2021
Manuscript not accepted for further review
Short summary
Short summary
Combining the geological characteristics of the thin soil layer on the thick gravel layer and the climate characteristics of the long-term snow cover of the Qinghai-Tibet Plateau, the WEP-QTP hydrological model was constructed by dividing a single soil structure into soil and gravel. In contrast to the general cold area, the special environment of the Qinghai–Tibet Plateau affects the hydrothermal transport process, which can not be ignored in hydrological forecast and water resource assessment.
Qifen Yuan, Thordis L. Thorarinsdottir, Stein Beldring, Wai Kwok Wong, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 25, 5259–5275, https://doi.org/10.5194/hess-25-5259-2021, https://doi.org/10.5194/hess-25-5259-2021, 2021
Short summary
Short summary
Localized impacts of changing precipitation patterns on surface hydrology are often assessed at a high spatial resolution. Here we introduce a stochastic method that efficiently generates gridded daily precipitation in a future climate. The method works out a stochastic model that can describe a high-resolution data product in a reference period and form a realistic precipitation generator under a projected future climate. A case study of nine catchments in Norway shows that it works well.
Hailong Wang, Kai Duan, Bingjun Liu, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 25, 4741–4758, https://doi.org/10.5194/hess-25-4741-2021, https://doi.org/10.5194/hess-25-4741-2021, 2021
Short summary
Short summary
Using remote sensing and reanalysis data, we examined the relationships between vegetation development and water resource availability in a humid subtropical basin. We found overall increases in total water storage and surface greenness and vegetation production, and the changes were particularly profound in cropland-dominated regions. Correlation analysis implies water availability leads the variations in greenness and production, and irrigation may improve production during dry periods.
Jun Li, Zhaoli Wang, Xushu Wu, Jakob Zscheischler, Shenglian Guo, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 25, 1587–1601, https://doi.org/10.5194/hess-25-1587-2021, https://doi.org/10.5194/hess-25-1587-2021, 2021
Short summary
Short summary
We introduce a daily-scale index, termed the standardized compound drought and heat index (SCDHI), to measure the key features of compound dry-hot conditions. SCDHI can not only monitor the long-term compound dry-hot events, but can also capture such events at sub-monthly scale and reflect the related vegetation activity impacts. The index can provide a new tool to quantify sub-monthly characteristics of compound dry-hot events, which are vital for releasing early and timely warning.
Tian Lan, Kairong Lin, Chong-Yu Xu, Zhiyong Liu, and Huayang Cai
Hydrol. Earth Syst. Sci., 24, 5859–5874, https://doi.org/10.5194/hess-24-5859-2020, https://doi.org/10.5194/hess-24-5859-2020, 2020
Zhengke Pan, Pan Liu, Chong-Yu Xu, Lei Cheng, Jing Tian, Shujie Cheng, and Kang Xie
Hydrol. Earth Syst. Sci., 24, 4369–4387, https://doi.org/10.5194/hess-24-4369-2020, https://doi.org/10.5194/hess-24-4369-2020, 2020
Short summary
Short summary
This study aims to identify the response of catchment water storage capacity (CWSC) to meteorological drought by examining the changes of hydrological-model parameters after drought events. This study improves our understanding of possible changes in the CWSC induced by a prolonged meteorological drought, which will help improve our ability to simulate the hydrological system under climate change.
Wenyan Qi, Jie Chen, Lu Li, Chong-yu Xu, Jingjing Li, Yiheng Xiang, and Shaobo Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-127, https://doi.org/10.5194/hess-2020-127, 2020
Manuscript not accepted for further review
Short summary
Short summary
Global hydrological models (GHMs) play important roles in global water resources estimation and it is difficult to obtain parameter values for GHMs. A framework is developed for building GHMs based on parameter regionalization of catchment scale conceptual hydrological models. Four different GHMs established based on this framework can produce reliable streamflow simulations. Over all, it can be used with any conceptual hydrological model even though uncertainty exists in using different models.
Shaokun He, Shenglian Guo, Chong-Yu Xu, Kebing Chen, Zhen Liao, Lele Deng, Huanhuan Ba, and Dimitri Solomatine
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-586, https://doi.org/10.5194/hess-2019-586, 2020
Manuscript not accepted for further review
Short summary
Short summary
Aiming at cascade impoundment operation, we develop a classification-aggregation-decomposition method to overcome the
curse of dimensionalityand inflow stochasticity problem. It is tested with a mixed 30-reservoir system in China. The results show that our method can provide lots of schemes to refer to different flood event scenarios. The best scheme outperforms the conventional operating rule, as it increases impoundment efficiency and hydropower generation while flood control risk is less.
Tongtiegang Zhao, Wei Zhang, Yongyong Zhang, Zhiyong Liu, and Xiaohong Chen
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
Désirée Treichler, Andreas Kääb, Nadine Salzmann, and Chong-Yu Xu
The Cryosphere, 13, 2977–3005, https://doi.org/10.5194/tc-13-2977-2019, https://doi.org/10.5194/tc-13-2977-2019, 2019
Short summary
Short summary
Glacier growth such as that found on the Tibetan Plateau (TP) is counterintuitive in a warming world. Climate models and meteorological data are conflicting about the reasons for this glacier anomaly. We quantify the glacier changes in High Mountain Asia using satellite laser altimetry as well as the growth of over 1300 inland lakes on the TP. Our study suggests that increased summer precipitation is likely the largest contributor to the recently observed increases in glacier and lake masses.
Bin Xiong, Lihua Xiong, Jun Xia, Chong-Yu Xu, Cong Jiang, and Tao Du
Hydrol. Earth Syst. Sci., 23, 4453–4470, https://doi.org/10.5194/hess-23-4453-2019, https://doi.org/10.5194/hess-23-4453-2019, 2019
Short summary
Short summary
We develop a new indicator of reservoir effects, called the rainfall–reservoir composite index (RRCI). RRCI, coupled with the effects of static reservoir capacity and scheduling-related multivariate rainfall, has a better performance than the previous indicator in terms of explaining the variation in the downstream floods affected by reservoir operation. A covariate-based flood frequency analysis using RRCI can provide more reliable downstream flood risk estimation.
Hui-Min Wang, Jie Chen, Chong-Yu Xu, Hua Chen, Shenglian Guo, Ping Xie, and Xiangquan Li
Hydrol. Earth Syst. Sci., 23, 4033–4050, https://doi.org/10.5194/hess-23-4033-2019, https://doi.org/10.5194/hess-23-4033-2019, 2019
Short summary
Short summary
When using large ensembles of global climate models in hydrological impact studies, there are pragmatic questions on whether it is necessary to weight climate models and how to weight them. We use eight methods to weight climate models straightforwardly, based on their performances in hydrological simulations, and investigate the influences of the assigned weights. This study concludes that using bias correction and equal weighting is likely viable and sufficient for hydrological impact studies.
Tian Lan, Kairong Lin, Xuezhi Tan, Chong-Yu Xu, and Xiaohong Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-301, https://doi.org/10.5194/hess-2019-301, 2019
Manuscript not accepted for further review
Short summary
Short summary
A calibration scheme was developed for the dynamics of hydrological model parameters. Furthermore, a novel tool was designed to assess the reliability of the dynamized parameter set. The tool evaluates the convergence processes for global optimization algorithms using violin plots (ECP-VP). The results showed that the developed calibration scheme overcame the salient issues for poor model performance. Besides, the ECP-VP tool effectively assessed the reliability of the dynamic parameter set.
Cong Jiang, Lihua Xiong, Lei Yan, Jianfan Dong, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 23, 1683–1704, https://doi.org/10.5194/hess-23-1683-2019, https://doi.org/10.5194/hess-23-1683-2019, 2019
Short summary
Short summary
We present the methods addressing the multivariate hydrologic design applied to the engineering practice under nonstationary conditions. A dynamic C-vine copula allowing for both time-varying marginal distributions and a time-varying dependence structure is developed to capture the nonstationarities of multivariate flood distribution. Then, the multivariate hydrologic design under nonstationary conditions is estimated through specifying the design criterion by average annual reliability.
Lu Li, Mingxi Shen, Yukun Hou, Chong-Yu Xu, Arthur F. Lutz, Jie Chen, Sharad K. Jain, Jingjing Li, and Hua Chen
Hydrol. Earth Syst. Sci., 23, 1483–1503, https://doi.org/10.5194/hess-23-1483-2019, https://doi.org/10.5194/hess-23-1483-2019, 2019
Short summary
Short summary
The study used an integrated glacio-hydrological model for the hydrological projections of the Himalayan Beas basin under climate change. It is very likely that the upper Beas basin will get warmer and wetter in the future. This loss in glacier area will result in a reduction in glacier discharge, while the future changes in total discharge are uncertain. The uncertainty in future hydrological change is not only from GCMs, but also from the bias-correction methods and hydrological modeling.
Pan Hu, Qiang Zhang, Chong-Yu Xu, Shao Sun, and Jiayi Fang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-73, https://doi.org/10.5194/hess-2019-73, 2019
Preprint withdrawn
Short summary
Short summary
China is the country highly sensitive to flood disasters. Here we investigated flood disasters and relevant driving factors using meteorological disaster records s and also hourly rainfall data. We used the GeoDetector method to analyze potential driving factors behind flood disasters. We found increased rainstorm-induced flood disasters and increase in flood disaster frequency. Meanwhile, reduced flood-related death rates imply enhanced flood-mitigation infrastructure and facilities.
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Proc. IAHS, 380, 3–8, https://doi.org/10.5194/piahs-380-3-2018, https://doi.org/10.5194/piahs-380-3-2018, 2018
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Hydrol. Earth Syst. Sci., 22, 5735–5739, https://doi.org/10.5194/hess-22-5735-2018, https://doi.org/10.5194/hess-22-5735-2018, 2018
Xinjun Tu, Yiliang Du, Vijay P. Singh, Xiaohong Chen, Kairong Lin, and Haiou Wu
Hydrol. Earth Syst. Sci., 22, 5175–5189, https://doi.org/10.5194/hess-22-5175-2018, https://doi.org/10.5194/hess-22-5175-2018, 2018
Short summary
Short summary
For given frequencies of precipitation of a large region, design water demands of irrigation of the entire region among three methods, i.e., equalized frequency, typical year and most-likely weight function, slightly differed, but their alterations in sub-regions were complicated. A design procedure using the most-likely weight function in association with a high-dimensional copula, which built a linkage between regional frequency and sub-regional frequency of precipitation, is recommended.
Hong Li, Jan Erik Haugen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 22, 5097–5110, https://doi.org/10.5194/hess-22-5097-2018, https://doi.org/10.5194/hess-22-5097-2018, 2018
Short summary
Short summary
Precipitation is a key in the water system and glacier fate in the Great Himalayas region. We examine four datasets of available types in the Western Himalayas and they show very large differences. The differences depend much on the data source and are particularly large in monsoon seasons and high-elevation areas. All the datasets show a trend to wetter summer and drier winter and this trend reveals a tendency towards a high-flow seasonality and an unfavorable condition for glaciers.
Hui-Min Wang, Jie Chen, Alex J. Cannon, Chong-Yu Xu, and Hua Chen
Hydrol. Earth Syst. Sci., 22, 3739–3759, https://doi.org/10.5194/hess-22-3739-2018, https://doi.org/10.5194/hess-22-3739-2018, 2018
Short summary
Short summary
Facing a growing number of climate models, many selection methods were proposed to select subsets in the field of climate simulation, but the transferability of their performances to hydrological impacts remains doubtful. We investigate the transferability of climate simulation uncertainty to hydrological impacts using two selection methods, and conclude that envelope-based selection of about 10 climate simulations based on properly chosen climate variables is suggested for impact studies.
Bin Xiong, Lihua Xiong, Jie Chen, Chong-Yu Xu, and Lingqi Li
Hydrol. Earth Syst. Sci., 22, 1525–1542, https://doi.org/10.5194/hess-22-1525-2018, https://doi.org/10.5194/hess-22-1525-2018, 2018
Short summary
Short summary
In changing environments, extreme low-flow events are expected to increase. Frequency analysis of low-flow events considering the impacts of changing environments has attracted increasing attention. This study developed a frequency analysis framework by applying 11 indices to trace the main causes of the change in the annual extreme low-flow events of the Weihe River. We showed that the fluctuation in annual low-flow series was affected by climate, streamflow recession and irrigation area.
Diana Fuentes-Andino, Keith Beven, Sven Halldin, Chong-Yu Xu, José Eduardo Reynolds, and Giuliano Di Baldassarre
Hydrol. Earth Syst. Sci., 21, 3597–3618, https://doi.org/10.5194/hess-21-3597-2017, https://doi.org/10.5194/hess-21-3597-2017, 2017
Short summary
Short summary
Reproduction of past floods requires information on discharge and flood extent, commonly unavailable or uncertain during extreme events. We explored the possibility of reproducing an extreme flood disaster using rainfall and post-event hydrometric information by combining a rainfall-runoff and hydraulic modelling tool within an uncertainty analysis framework. Considering the uncertainty in post–event data, it was possible to reasonably reproduce the extreme event.
Sharad K. Jain, Sanjay K. Jain, Neha Jain, and Chong-Yu Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-100, https://doi.org/10.5194/hess-2017-100, 2017
Manuscript not accepted for further review
Lingqi Li, Lihua Xiong, Chong-Yu Xu, Shenglian Guo, and Pan Liu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-619, https://doi.org/10.5194/hess-2016-619, 2016
Revised manuscript not accepted
Short summary
Short summary
The study offers insights into future design floods that are inferred with both AM and POT samplings under nonstationarity caused by changing climate. Future design floods in nonstationarity context are usually (lower than) but not necessarily more different from stationary estimates. AM-based projection is more sensitive to climate change than POT estimates. The over-dispersion in POT arrival rate leads to the invalidation of Poisson assumption that the misuse may induce overestimated floods.
J. E. Reynolds, S. Halldin, C. Y. Xu, J. Seibert, and A. Kauffeldt
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-7437-2015, https://doi.org/10.5194/hessd-12-7437-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
In this study it was found that time-scale dependencies of hydrological model parameters are a result of the numerical method used in the model rather than a real time-scale-data dependence. This study further indicates that as soon as sub-daily driving data can be secured, flood forecasting in watersheds with sub-daily concentration times is possible with model parameter values inferred from long time series of daily data, as long as an appropriate numerical method is used.
A. Kauffeldt, S. Halldin, A. Rodhe, C.-Y. Xu, and I. K. Westerberg
Hydrol. Earth Syst. Sci., 17, 2845–2857, https://doi.org/10.5194/hess-17-2845-2013, https://doi.org/10.5194/hess-17-2845-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China
A network approach for multiscale catchment classification using traits
Multi-model approach in a variable spatial framework for streamflow simulation
Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake
Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins
Empirical stream thermal sensitivity cluster on the landscape according to geology and climate
Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia
On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow
Toward interpretable LSTM-based modeling of hydrological systems
Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model
What controls the tail behaviour of flood series: rainfall or runoff generation?
Seasonal prediction of end-of-dry-season watershed behavior in a highly interconnected alluvial watershed in northern California
Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau
Leveraging gauge networks and strategic discharge measurements to aid the development of continuous streamflow records
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration
Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings
Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+
On understanding mountainous carbonate basins of the Mediterranean using parsimonious modeling solutions
Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations
Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes
Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling
Modelling flood frequency and magnitude in a glacially conditioned, heterogeneous landscape: testing the importance of land cover and land use
Enhancing LSTM-based streamflow prediction with a spatially distributed approach
Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land
Altitudinal Control of Isotopic Composition and Application in Understanding Hydrologic Processes in the mid Merced River Catchment, Sierra Nevada, California, USA
Modelling the regional sensitivity of snowmelt, soil moisture, and streamflow generation to climate over the Canadian Prairies using a basin classification approach
To what extent does river routing matter in hydrological modeling?
Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins
An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
airGRteaching: an open-source tool for teaching hydrological modeling with R
To What Extent Do Extreme Storm Events Change Future Flood Hazards?
Stable water isotopes and tritium tracers tell the same tale: no evidence for underestimation of catchment transit times inferred by stable isotopes in StorAge Selection (SAS)-function models
Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation
Changes in Mediterranean flood processes and seasonality
Can the combining of wetlands with reservoir operation reduce the risk of future floods and droughts?
Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado
When best is the enemy of good – critical evaluation of performance criteria in hydrological models
The suitability of differentiable, physics-informed machine learning hydrologic models for ungauged regions and climate change impact assessment
Producing reliable hydrologic scenarios from raw climate model outputs without resorting to meteorological observations
Afforestation impacts on terrestrial hydrology insignificant compared to climate change in Great Britain
Using normalised difference infrared index patterns to constrain semi-distributed rainfall–runoff models in tropical nested catchments
Revisiting the hydrological basis of the Budyko framework with the principle of hydrologically similar groups
Reconstructing five decades of sediment export from two glacierized high-alpine catchments in Tyrol, Austria, using nonparametric regression
Water and energy budgets over hydrological basins on short and long timescales
Hydrological response to climate change and human activities in the Three-River Source Region
Incorporating experimentally derived streamflow contributions into model parameterization to improve discharge prediction
Machine-learning- and deep-learning-based streamflow prediction in a hilly catchment for future scenarios using CMIP6 GCM data
River hydraulic modeling with ICESat-2 land and water surface elevation
Hydrological modeling using the Soil and Water Assessment Tool in urban and peri-urban environments: the case of Kifisos experimental subbasin (Athens, Greece)
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
Short summary
Short summary
Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
Short summary
Short summary
We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
Short summary
Short summary
Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
Short summary
Short summary
We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
Short summary
Short summary
Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
Short summary
Short summary
This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
Short summary
Short summary
To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
Short summary
Short summary
Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
Short summary
Short summary
Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
Short summary
Short summary
Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
Short summary
Short summary
In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
Short summary
Short summary
In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
Short summary
Short summary
This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
Short summary
Short summary
Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
Short summary
Short summary
We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
Short summary
Short summary
Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
Short summary
Short summary
How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Salam A. Abbas, Ryan T. Bailey, Jeremy T. White, Jeffrey G. Arnold, Michael J. White, Natalja Čerkasova, and Jungang Gao
Hydrol. Earth Syst. Sci., 28, 21–48, https://doi.org/10.5194/hess-28-21-2024, https://doi.org/10.5194/hess-28-21-2024, 2024
Short summary
Short summary
Research highlights.
1. Implemented groundwater module (gwflow) into SWAT+ for four watersheds with different unique hydrologic features across the United States.
2. Presented methods for sensitivity analysis, uncertainty analysis and parameter estimation for coupled models.
3. Sensitivity analysis for streamflow and groundwater head conducted using Morris method.
4. Uncertainty analysis and parameter estimation performed using an iterative ensemble smoother within the PEST framework.
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
Short summary
Short summary
We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
Short summary
Short summary
Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Léo C. P. Martin, Sebastian Westermann, Michele Magni, Fanny Brun, Joel Fiddes, Yanbin Lei, Philip Kraaijenbrink, Tamara Mathys, Moritz Langer, Simon Allen, and Walter W. Immerzeel
Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, https://doi.org/10.5194/hess-27-4409-2023, 2023
Short summary
Short summary
Across the Tibetan Plateau, many large lakes have been changing level during the last decades as a response to climate change. In high-mountain environments, water fluxes from the land to the lakes are linked to the ground temperature of the land and to the energy fluxes between the ground and the atmosphere, which are modified by climate change. With a numerical model, we test how these water and energy fluxes have changed over the last decades and how they influence the lake level variations.
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023, https://doi.org/10.5194/hess-27-4385-2023, 2023
Short summary
Short summary
Dynamical systems are used by many agencies worldwide to produce seasonal streamflow forecasts, which are critical for decision-making. Such systems rely on hydrology models, which contain parameters that are typically estimated using a target performance metric (i.e., objective function). This study explores the effects of this decision across mountainous basins in Chile, illustrating tradeoffs between seasonal forecast quality and the models' capability to simulate streamflow characteristics.
Pamela E. Tetford and Joseph R. Desloges
Hydrol. Earth Syst. Sci., 27, 3977–3998, https://doi.org/10.5194/hess-27-3977-2023, https://doi.org/10.5194/hess-27-3977-2023, 2023
Short summary
Short summary
An efficient regional flood frequency model relates drainage area to discharge, with a major assumption of similar basin conditions. In a landscape with variable glacial deposits and land use, we characterize varying hydrological function using 28 explanatory variables. We demonstrate that (1) a heterogeneous landscape requires objective model selection criteria to optimize the fit of flow data, and (2) incorporating land use as a predictor variable improves the drainage area to discharge model.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-237, https://doi.org/10.5194/hess-2023-237, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
It is challenging to incorporate the spatial distribution information of input variables when implementing LSTM models for streamflow prediction. This paper presents a novel hybrid modeling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise in predicting streamflow at large ungauged basin.
Ana Ramos Oliveira, Tiago Brito Ramos, Lígia Pinto, and Ramiro Neves
Hydrol. Earth Syst. Sci., 27, 3875–3893, https://doi.org/10.5194/hess-27-3875-2023, https://doi.org/10.5194/hess-27-3875-2023, 2023
Short summary
Short summary
This paper intends to demonstrate the adequacy of a hybrid solution to overcome the difficulties related to the incorporation of human behavior when modeling hydrological processes. Two models were implemented, one to estimate the outflow of a reservoir and the other to simulate the hydrological processes of the watershed. With both models feeding each other, results show that the proposed approach significantly improved the streamflow estimation downstream of the reservoir.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-230, https://doi.org/10.5194/hess-2023-230, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of water falls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow-rain transition (2,000–2,500m) and very vulnerable to shift in the snow-rain ratio.
Zhihua He, Kevin Shook, Christopher Spence, John W. Pomeroy, and Colin Whitfield
Hydrol. Earth Syst. Sci., 27, 3525–3546, https://doi.org/10.5194/hess-27-3525-2023, https://doi.org/10.5194/hess-27-3525-2023, 2023
Short summary
Short summary
This study evaluated the impacts of climate change on snowmelt, soil moisture, and streamflow over the Canadian Prairies. The entire prairie region was divided into seven basin types. We found strong variations of hydrological sensitivity to precipitation and temperature changes in different land covers and basins, which suggests that different water management and adaptation methods are needed to address enhanced water stress due to expected climate change in different regions of the prairies.
Nicolás Cortés-Salazar, Nicolás Vásquez, Naoki Mizukami, Pablo A. Mendoza, and Ximena Vargas
Hydrol. Earth Syst. Sci., 27, 3505–3524, https://doi.org/10.5194/hess-27-3505-2023, https://doi.org/10.5194/hess-27-3505-2023, 2023
Short summary
Short summary
This paper shows how important river models can be for water resource applications that involve hydrological models and, in particular, parameter calibration. To this end, we conduct numerical experiments in a pilot basin using a combination of hydrologic model simulations obtained from a large sample of parameter sets and different routing methods. We find that routing can affect streamflow simulations, even at monthly time steps; the choice of parameters; and relevant streamflow metrics.
Dung Trung Vu, Thanh Duc Dang, Francesca Pianosi, and Stefano Galelli
Hydrol. Earth Syst. Sci., 27, 3485–3504, https://doi.org/10.5194/hess-27-3485-2023, https://doi.org/10.5194/hess-27-3485-2023, 2023
Short summary
Short summary
The calibration of hydrological models over extensive spatial domains is often challenged by the lack of data on river discharge and the operations of hydraulic infrastructures. Here, we use satellite data to address the lack of data that could unintentionally bias the calibration process. Our study is underpinned by a computational framework that quantifies this bias and provides a safe approach to the calibration of models in poorly gauged and heavily regulated basins.
Francesco Fatone, Bartosz Szeląg, Przemysław Kowal, Arthur McGarity, Adam Kiczko, Grzegorz Wałek, Ewa Wojciechowska, Michał Stachura, and Nicolas Caradot
Hydrol. Earth Syst. Sci., 27, 3329–3349, https://doi.org/10.5194/hess-27-3329-2023, https://doi.org/10.5194/hess-27-3329-2023, 2023
Short summary
Short summary
A novel methodology for the development of a stormwater network performance simulator including advanced risk assessment was proposed. The applied tool enables the analysis of the influence of spatial variability in catchment and stormwater network characteristics on the relation between (SWMM) model parameters and specific flood volume, as an alternative approach to mechanistic models. The proposed method can be used at the stage of catchment model development and spatial planning management.
Olivier Delaigue, Pierre Brigode, Guillaume Thirel, and Laurent Coron
Hydrol. Earth Syst. Sci., 27, 3293–3327, https://doi.org/10.5194/hess-27-3293-2023, https://doi.org/10.5194/hess-27-3293-2023, 2023
Short summary
Short summary
Teaching hydrological modeling is an important, but difficult, matter. It requires appropriate tools and teaching material. In this article, we present the airGRteaching package, which is an open-source software tool relying on widely used hydrological models. This tool proposes an interface and numerous hydrological modeling exercises representing a wide range of hydrological applications. We show how this tool can be applied to simple but real-life cases.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
EGUsphere, https://doi.org/10.5194/egusphere-2023-1969, https://doi.org/10.5194/egusphere-2023-1969, 2023
Short summary
Short summary
Due to climate change, flooding is expected to become more frequent globally in the coming decades. Locally, storm-induced channel geometry changes can drastically affect flood hazards, yet rivers are mostly treated as static elements in flood studies. This study tried to gain an understanding of the effects of major storm events on future flood hazards, promoting a framework for incorporating channel conveyance adjustments into flood hazard assessment.
Siyuan Wang, Markus Hrachowitz, Gerrit Schoups, and Christine Stumpp
Hydrol. Earth Syst. Sci., 27, 3083–3114, https://doi.org/10.5194/hess-27-3083-2023, https://doi.org/10.5194/hess-27-3083-2023, 2023
Short summary
Short summary
This study shows that previously reported underestimations of water ages are most likely not due to the use of seasonally variable tracers. Rather, these underestimations can be largely attributed to the choices of model approaches which rely on assumptions not frequently met in catchment hydrology. We therefore strongly advocate avoiding the use of this model type in combination with seasonally variable tracers and instead adopting StorAge Selection (SAS)-based or comparable model formulations.
Arianna Borriero, Rohini Kumar, Tam V. Nguyen, Jan H. Fleckenstein, and Stefanie R. Lutz
Hydrol. Earth Syst. Sci., 27, 2989–3004, https://doi.org/10.5194/hess-27-2989-2023, https://doi.org/10.5194/hess-27-2989-2023, 2023
Short summary
Short summary
We analyzed the uncertainty of the water transit time distribution (TTD) arising from model input (interpolated tracer data) and structure (StorAge Selection, SAS, functions). We found that uncertainty was mainly associated with temporal interpolation, choice of SAS function, nonspatial interpolation, and low-flow conditions. It is important to characterize the specific uncertainty sources and their combined effects on TTD, as this has relevant implications for both water quantity and quality.
Yves Tramblay, Patrick Arnaud, Guillaume Artigue, Michel Lang, Emmanuel Paquet, Luc Neppel, and Eric Sauquet
Hydrol. Earth Syst. Sci., 27, 2973–2987, https://doi.org/10.5194/hess-27-2973-2023, https://doi.org/10.5194/hess-27-2973-2023, 2023
Short summary
Short summary
Mediterranean floods are causing major damage, and recent studies have shown that, despite the increase in intense rainfall, there has been no increase in river floods. This study reveals that the seasonality of floods changed in the Mediterranean Basin during 1959–2021. There was also an increased frequency of floods linked to short episodes of intense rain, associated with a decrease in soil moisture. These changes need to be taken into consideration to adapt flood warning systems.
Yanfeng Wu, Jingxuan Sun, Boting Hu, Y. Jun Xu, Alain N. Rousseau, and Guangxin Zhang
Hydrol. Earth Syst. Sci., 27, 2725–2745, https://doi.org/10.5194/hess-27-2725-2023, https://doi.org/10.5194/hess-27-2725-2023, 2023
Short summary
Short summary
Reservoirs and wetlands are important regulators of watershed hydrology, which should be considered when projecting floods and droughts. We first coupled wetlands and reservoir operations into a semi-spatially-explicit hydrological model and then applied it in a case study involving a large river basin in northeast China. We found that, overall, the risk of future floods and droughts will increase further even under the combined influence of reservoirs and wetlands.
Peishi Jiang, Pin Shuai, Alexander Sun, Maruti K. Mudunuru, and Xingyuan Chen
Hydrol. Earth Syst. Sci., 27, 2621–2644, https://doi.org/10.5194/hess-27-2621-2023, https://doi.org/10.5194/hess-27-2621-2023, 2023
Short summary
Short summary
We developed a novel deep learning approach to estimate the parameters of a computationally expensive hydrological model on only a few hundred realizations. Our approach leverages the knowledge obtained by data-driven analysis to guide the design of the deep learning model used for parameter estimation. We demonstrate this approach by calibrating a state-of-the-art hydrological model against streamflow and evapotranspiration observations at a snow-dominated watershed in Colorado.
Guillaume Cinkus, Naomi Mazzilli, Hervé Jourde, Andreas Wunsch, Tanja Liesch, Nataša Ravbar, Zhao Chen, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 27, 2397–2411, https://doi.org/10.5194/hess-27-2397-2023, https://doi.org/10.5194/hess-27-2397-2023, 2023
Short summary
Short summary
The Kling–Gupta Efficiency (KGE) is a performance criterion extensively used to evaluate hydrological models. We conduct a critical study on the KGE and its variant to examine counterbalancing errors. Results show that, when assessing a simulation, concurrent over- and underestimation of discharge can lead to an overall higher criterion score without an associated increase in model relevance. We suggest that one carefully choose performance criteria and use scaling factors.
Dapeng Feng, Hylke Beck, Kathryn Lawson, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 27, 2357–2373, https://doi.org/10.5194/hess-27-2357-2023, https://doi.org/10.5194/hess-27-2357-2023, 2023
Short summary
Short summary
Powerful hybrid models (called δ or delta models) embrace the fundamental learning capability of AI and can also explain the physical processes. Here we test their performance when applied to regions not in the training data. δ models rivaled the accuracy of state-of-the-art AI models under the data-dense scenario and even surpassed them for the data-sparse one. They generalize well due to the physical structure included. δ models could be ideal candidates for global hydrologic assessment.
Simon Ricard, Philippe Lucas-Picher, Antoine Thiboult, and François Anctil
Hydrol. Earth Syst. Sci., 27, 2375–2395, https://doi.org/10.5194/hess-27-2375-2023, https://doi.org/10.5194/hess-27-2375-2023, 2023
Short summary
Short summary
A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations. Results confirm that the proposed workflow produces equivalent projections of the seasonal mean flows in comparison to a conventional hydroclimatic modelling approach. The proposed approach supports the participation of end-users in interpreting the impact of climate change on water resources.
Marcus Edmund Henry Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-138, https://doi.org/10.5194/hess-2023-138, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
Afforestation has been proposed internationally, but the hydrological implications of such large increases in spatial extent of woodland are not fully understood. In this study we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Nutchanart Sriwongsitanon, Wasana Jandang, James Williams, Thienchart Suwawong, Ekkarin Maekan, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 2149–2171, https://doi.org/10.5194/hess-27-2149-2023, https://doi.org/10.5194/hess-27-2149-2023, 2023
Short summary
Short summary
We developed predictive semi-distributed rainfall–runoff models for nested sub-catchments in the upper Ping basin, which yielded better or similar performance compared to calibrated lumped models. The normalised difference infrared index proves to be an effective proxy for distributed root zone moisture capacity over sub-catchments and is well correlated with the percentage of evergreen forest. In validation, soil moisture simulations appeared to be highly correlated with the soil wetness index.
Yuchan Chen, Xiuzhi Chen, Meimei Xue, Chuanxun Yang, Wei Zheng, Jun Cao, Wenting Yan, and Wenping Yuan
Hydrol. Earth Syst. Sci., 27, 1929–1943, https://doi.org/10.5194/hess-27-1929-2023, https://doi.org/10.5194/hess-27-1929-2023, 2023
Short summary
Short summary
This study addresses the quantification and estimation of the watershed-characteristic-related parameter (Pw) in the Budyko framework with the principle of hydrologically similar groups. The results show that Pw is closely related to soil moisture and fractional vegetation cover, and the relationship varies across specific hydrologic similarity groups. The overall satisfactory performance of the Pw estimation model improves the applicability of the Budyko framework for global runoff estimation.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, Christoph Mayer, and Axel Bronstert
Hydrol. Earth Syst. Sci., 27, 1841–1863, https://doi.org/10.5194/hess-27-1841-2023, https://doi.org/10.5194/hess-27-1841-2023, 2023
Short summary
Short summary
We present a suitable method to reconstruct sediment export from decadal records of hydroclimatic predictors (discharge, precipitation, temperature) and shorter suspended sediment measurements. This lets us fill the knowledge gap on how sediment export from glacierized high-alpine areas has responded to climate change. We find positive trends in sediment export from the two investigated nested catchments with step-like increases around 1981 which are linked to crucial changes in glacier melt.
Samantha Petch, Bo Dong, Tristan Quaife, Robert P. King, and Keith Haines
Hydrol. Earth Syst. Sci., 27, 1723–1744, https://doi.org/10.5194/hess-27-1723-2023, https://doi.org/10.5194/hess-27-1723-2023, 2023
Short summary
Short summary
Gravitational measurements of water storage from GRACE (Gravity Recovery and Climate Experiment) can improve understanding of the water budget. We produce flux estimates over large river catchments based on observations that close the monthly water budget and ensure consistency with GRACE on short and long timescales. We use energy data to provide additional constraints and balance the long-term energy budget. These flux estimates are important for evaluating climate models.
Ting Su, Chiyuan Miao, Qingyun Duan, Jiaojiao Gou, Xiaoying Guo, and Xi Zhao
Hydrol. Earth Syst. Sci., 27, 1477–1492, https://doi.org/10.5194/hess-27-1477-2023, https://doi.org/10.5194/hess-27-1477-2023, 2023
Short summary
Short summary
The Three-River Source Region (TRSR) plays an extremely important role in water resources security and ecological and environmental protection in China and even all of Southeast Asia. This study used the variable infiltration capacity (VIC) land surface hydrologic model linked with the degree-day factor algorithm to simulate the runoff change in the TRSR. These results will help to guide current and future regulation and management of water resources in the TRSR.
Andreas Hartmann, Jean-Lionel Payeur-Poirier, and Luisa Hopp
Hydrol. Earth Syst. Sci., 27, 1325–1341, https://doi.org/10.5194/hess-27-1325-2023, https://doi.org/10.5194/hess-27-1325-2023, 2023
Short summary
Short summary
We advance our understanding of including information derived from environmental tracers into hydrological modeling. We present a simple approach that integrates streamflow observations and tracer-derived streamflow contributions for model parameter estimation. We consider multiple observed streamflow components and their variation over time to quantify the impact of their inclusion for streamflow prediction at the catchment scale.
Dharmaveer Singh, Manu Vardhan, Rakesh Sahu, Debrupa Chatterjee, Pankaj Chauhan, and Shiyin Liu
Hydrol. Earth Syst. Sci., 27, 1047–1075, https://doi.org/10.5194/hess-27-1047-2023, https://doi.org/10.5194/hess-27-1047-2023, 2023
Short summary
Short summary
This study examines, for the first time, the potential of various machine learning models in streamflow prediction over the Sutlej River basin (rainfall-dominated zone) in western Himalaya during the period 2041–2070 (2050s) and 2071–2100 (2080s) and its relationship to climate variability. The mean ensemble of the model results shows that the mean annual streamflow of the Sutlej River is expected to rise between the 2050s and 2080s by 0.79 to 1.43 % for SSP585 and by 0.87 to 1.10 % for SSP245.
Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Ranndal, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 27, 1011–1032, https://doi.org/10.5194/hess-27-1011-2023, https://doi.org/10.5194/hess-27-1011-2023, 2023
Short summary
Short summary
This paper uses remote sensing data from ICESat-2 to calibrate a 1D hydraulic model. With the model, we can make estimations of discharge and water surface elevation, which are important indicators in flooding risk assessment. ICESat-2 data give an added value, thanks to the 0.7 m resolution, which allows the measurement of narrow river streams. In addition, ICESat-2 provides measurements on the river dry portion geometry that can be included in the model.
Evgenia Koltsida, Nikos Mamassis, and Andreas Kallioras
Hydrol. Earth Syst. Sci., 27, 917–931, https://doi.org/10.5194/hess-27-917-2023, https://doi.org/10.5194/hess-27-917-2023, 2023
Short summary
Short summary
Daily and hourly rainfall observations were inputted to a Soil and Water Assessment Tool (SWAT) hydrological model to investigate the impacts of rainfall temporal resolution on a discharge simulation. Results indicated that groundwater flow parameters were more sensitive to daily time intervals, and channel routing parameters were more influential for hourly time intervals. This study suggests that the SWAT model appears to be a reliable tool to predict discharge in a mixed-land-use basin.
Cited articles
Aldrich, J.: R. A. Fisher and the making of maximum likelihood 1912–1922,
Statist. Sci., 12, 162–176, https://doi.org/10.1214/ss/1030037906, 1997.
Arora, S. and Singh, S.: The firefly optimization algorithm: convergence
analysis and parameter selection, Int. J. Comput. Appl., 69, 48–52, https://doi.org/10.5120/11826-7528, 2013.
Arsenault, R., Poulin, A., Côté, P., and Brissette, F.: Comparison of Stochastic Optimization Algorithms in Hydrological Model Calibration, J. Hydrol. Eng., 19, 1374–1384, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000938, 2014.
Azad, S. K. J. S. and Optimization, M.: Monitored convergence curve: a new
framework for metaheuristic structural optimization algorithms, Struct. Multidiscip. O., 60, 481–499, https://doi.org/10.1007/s00158-019-02219-5, 2019.
Bárdossy, A.: Calibration of hydrological model parameters for ungauged
catchments, Hydrol. Earth Syst. Sci., 11, 703–710, https://doi.org/10.5194/hess-11-703-2007, 2007.
Bárdossy, A. and Singh, S. K.: Robust estimation of hydrological model
parameters, Hydrol. Earth Syst. Sci., 12, 1273–1283,
https://doi.org/10.5194/hess-12-1273-2008, 2008.
Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, https://doi.org/10.1002/hyp.3360060305, 1992.
Brigode, P., Oudin, L., and Perrin, C.: Hydrological model parameter instability: A source of additional uncertainty in estimating the hydrological impacts of climate change?, J. Hydrol., 476, 410–425,
https://doi.org/10.1016/j.jhydrol.2012.11.012, 2013.
Chen, Y., Chen, X. W., Xu, C. Y., Zhang, M. F., Liu, M. B., and Gao, L.:
Toward improved calibration of SWAT using season-based multi-objective
optimization: A case study in the Jinjiang basin in southeastern China, Water Resour. Manage,, 32, 1193–1207, https://doi.org/10.1007/s11269-017-1862-8, 2017.
Cheng, L., Yaeger, M., Viglione, A., Coopersmith, E., Ye, S., and Sivapalan,
M.: Exploring the physical controls of regional patterns of flow duration
curves – Part 1: Insights from statistical analyses, Hydrol. Earth Syst. Sci., 16, 4435–4446, https://doi.org/10.5194/hess-16-4435-2012, 2012.
Choi, H. T. and Beven, K.: Multi-period and multi-criteria model conditioning to reduce prediction uncertainty in an application of TOPMODEL within the GLUE framework, J. Hydrol., 332, 316–336, https://doi.org/10.1016/j.jhydrol.2006.07.012, 2007.
Cibin, R., Sudheer, K. P., and Chaubey, I.: Sensitivity and identifiability of stream flow generation parameters of the SWAT model, Hydrol. Process., 24,
1133–1148, https://doi.org/10.1002/hyp.7568, 2010.
CMDC: One Hour of Precipotation and Hour Temperature datasets during 1980–1990 on China Meteorological Data Service Center (CMDC), available at: https://data.cma.cn/en/?r=data/online&t=6 (last access: 20 March 2020), 2019.
Cooper, V. A., Nguyen, V. T. V., and Nicell, J. A.: Evaluation of global
optimization methods for conceptual rainfall-runoff model calibration, Water
Sci. Technol., 36, 53–60, https://doi.org/10.1016/S0273-1223(97)00461-7, 1997.
Coopersmith, E., Yaeger, M. A., Ye, S., Cheng, L., and Sivapalan, M.: Exploring the physical controls of regional patterns of flow duration curves
– Part 3: A catchment classification system based on regime curve indicators, Hydrol. Earth Syst. Sci., 16, 4467–4482, https://doi.org/10.5194/hess-16-4467-2012, 2012.
Coron, L., Andreassian, V., Perrin, C., Bourqui, M., and Hendrickx, F.: On
the lack of robustness of hydrologic models regarding water balance simulation: a diagnostic approach applied to three models of increasing
complexity on 20 mountainous catchments, Hydrol. Earth Syst. Sci., 18, 727–746, https://doi.org/10.5194/hess-18-727-2014, 2014.
Dakhlaoui, H., Ruelland, D., Tramblay, Y., and Bargaoui, Z.: Evaluating the
robustness of conceptual rainfall-runoff models under climate variability in
northern Tunisia, J. Hydrol., 550, 201–217, https://doi.org/10.1016/j.jhydrol.2017.04.032, 2017.
Delorit, J., Ortuya, E. C. G., and Block, P.: Evaluation of model-based seasonal streamflow and water allocation forecasts for the Elqui Valley,
Chile, Hydrol. Earth Syst. Sci., 21, 4711–4725, https://doi.org/10.5194/hess-21-4711-2017, 2017.
Deng, C., Liu, P., Guo, S. L., Li, Z. J., and Wang, D. B.: Identification of
hydrological model parameter variation using ensemble Kalman filter, Hydrol.
Earth Syst. Sci., 20, 4949–4961, https://doi.org/10.5194/hess-20-4949-2016, 2016.
Deng, C., Liu, P., Wang, D. B., and Wang, W. G.: Temporal variation and scaling of parameters for a monthly hydrologic model, J. Hydrol., 558, 290–300, https://doi.org/10.1016/j.jhydrol.2018.01.049, 2018.
Derrac, J., García, S., Hui, S., Suganthan, P. N., and Herrera, F.:
Analyzing convergence performance of evolutionary algorithms: A statistical
approach, Inform. Sci., 289, 41–58, https://doi.org/10.1016/j.ins.2014.06.009, 2014.
de Vos, N. J., Rientjes, T. H. M., and Gupta, H. V.: Diagnostic evaluation of conceptual rainfall-runoff models using temporal clustering, Hydrol. Process., 24, 2840–2850, https://doi.org/10.1002/hyp.7698, 2010.
Duan, Q., Sorooshian, S., and Gupta, V.: Effective and efficient global
optimization for conceptual rainfall-runoff models, Water Resour. Res., 28, 1015–1031, https://doi.org/10.1029/91WR02985, 1992.
Duan, Q., Sorooshian, S., and Gupta, V. K.: Optimal use of the SCE-UA global
optimization method for calibrating watershed models, J. Hydrol., 158, 265–284, 1994.
Duan, Q. Y., Gupta, V. K., and Sorooshian, S.: Shuffled Complex Evolution
Approach for Effective and Efficient Global Minimization, J. Optimiz. Theor. Appl., 76, 501–521, https://doi.org/10.1007/Bf00939380, 1993.
Fang, J. Y., Song, Y. C., Liu, H. Y., and Piao, S. L.: Vegetation-climate
relationship and its application in the division of vegetation zone in China, Acta Bot. Sin., 44, 1105–1122, 2002.
Fenicia, F., Kavetski, D., Savenije, H. H. G., Clark, M. P., Schoups, G., Pfister, L., and Freer, J.: Catchment properties, function, and conceptual model representation: is there a correspondence?, Hydrol. Process., 28, 2451–2467, https://doi.org/10.1002/hyp.9726, 2014.
Fenicia, F., Kavetski, D., Reichert, P., and Albert, C.: Signature-Domain
Calibration of Hydrological Models Using Approximate Bayesian Computation:
Empirical Analysis of Fundamental Properties, Water Resour. Res., 54,
3958–3987, https://doi.org/10.1002/2017wr021616, 2018.
Forrest, T. J. A. S.: Fitness Distance Correlation as a Measure of Problem
Difficulty for Genetic Algorithms, in: Proceedings of the Sixth International
Conference on Genetic Algorithms, 15–19 July 1995,
University of Pittsburgh, Pittsburgh, PA 15260, United States, 184–192, 1995.
Fowler, K., Coxon, G., Freer, J., Peel, M., Wagener, T., Western, A., Woods, R., and Zhang, L.: Simulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement, Water Resour. Res., 54, 9812–9832, https://doi.org/10.1029/2018wr023989, 2018.
Freer, J., Beven, K., and Peters, N.: Multivariate seasonal period model
rejection within the generalised likelihood uncertainty estimation procedure, in: Calibration of watershed models, 69–87, https://agupubs.onlinelibrary.wiley.com/doi/10.1029/WS006p0069 (last access: 11 March 2020), 2003.
Gharari, S., Hrachowitz, M., Fenicia, F., and Savenije, H. H. G.: An approach to identify time consistent model parameters: sub-period calibration, Hydrol. Earth Syst. Sci., 17, 149–161, https://doi.org/10.5194/hess-17-149-2013, 2013.
Gibbs, M. S., Maier, H. R., and Dandy, G. C.: Applying fitness landscape
measures to water distribution optimization problems, in: Hydroinformatics,
World Scientific Publishing Company, Singapore, 795–802, 2004.
Golmohammadi, G., Rudra, R., Dickinson, T., Goel, P., and Veliz, M.: Predicting the temporal variation of flow contributing areas using SWAT, J. Hydrol., 547, 375–386, https://doi.org/10.1016/j.jhydrol.2017.02.008, 2017.
Gomez, J.: Stochastic global optimization algorithms: A systematic formal
approach, Inform. Sci., 472, 53–76, https://doi.org/10.1016/j.ins.2018.09.021, 2019.
Guntner, A., Uhlenbrook, S., Seibert, J., and Leibundgut, C.: Multi-criterial validation of TOPMODEL in a mountainous catchment, Hydrol. Process., 13, 1603–1620, https://doi.org/10.1002/(sici)1099-1085(19990815)13:11<1603::aid-hyp830>3.3.co;2-b, 1999.
Guo, D., Johnson, F., and Marshall, L.: Assessing the Potential Robustness of Conceptual Rainfall-Runoff Models Under a Changing Climate, Water Resour. Res., 54, 5030–5049, https://doi.org/10.1029/2018WR022636, 2018.
Gupta, H. V., Sorooshian, S., and Yapo, P. O.: Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information, Water Resour. Res., 34, 751–763, https://doi.org/10.1029/97WR03495, 1998.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Guse, B., Pfannerstill, M., Strauch, M., Reusser, D. E., Ludtke, S., Volk, M., Gupta, H., and Fohrer, N.: On characterizing the temporal dominance
patterns of model parameters and processes, Hydrol. Process., 30, 2255–2270,
https://doi.org/10.1002/hyp.10764, 2016.
Hanne, T. J. J. O. H.: Global Multiobjective Optimization Using Evolutionary
Algorithms, J. Heuristics, 6, 347–360, https://doi.org/10.1023/a:1009630531634, 2000.
Harik, G., Cantú-Paz, E., Goldberg, D. E., and Miller, B. L.: The
Gambler's Ruin Problem, Genetic Algorithms, and the Sizing of Populations,
7, 231-253, 10.1162/evco.1999.7.3.231, 1999.
Herman, J. D., Reed, P. M., and Wagener, T.: Time-varying sensitivity analysis clarifies the effects of watershed model formulation on model behavior, Water Resour. Res., 49, 1400–1414, https://doi.org/10.1002/wrcr.20124, 2013.
Hintze, J. L. and Nelson, R. D.: Violin plots: a box plot-density trace
synergism, Am. Statist., 52, 181–184, https://doi.org/10.2307/2685478, 1998.
Höge, M., Wöhling, T., and Nowak, W.: A primer for model selection:
The decisive role of model complexity, Water Resour. Res., 54, 1688–1715, 2018.
Huang, G. H.: Model identifiability, Wiley StatsRef: Statistics Reference
Online, available at: https://onlinelibrary.wiley.com/doi/abs/10.1002/9781118445112.stat06411.pub2
(last access: 2016), 2005.
Hublart, P., Ruelland, D., De Cortázar-Atauri, L. G., Gascoin, S., Lhermitte, S., and Ibacache, A.: Reliability of lumped hydrological modeling
in a semi-arid mountainous catchment facing water-use changes, Hydrol. Earth
Syst. Sci., 20, 3691–3717, https://doi.org/10.5194/hess-20-3691-2016, 2016.
Kim, D. and Kaluarachchi, J.: Predicting streamflows in snowmelt-driven watersheds using the flow duration curve method, Hydrol. Earth Syst. Sci., 18, 1679–1693, https://doi.org/10.5194/hess-18-1679-2014, 2014.
Kim, K. B. and Han, D.: Exploration of sub-annual calibration schemes of
hydrological models, Hydrol. Res., 48, 1014–1031, https://doi.org/10.2166/nh.2016.296,
2017.
Kim, K. B., Kwon, H.-H., and Han, D.: Hydrological modelling under climate
change considering nonstationarity and seasonal effects, Hydrol. Res., 47, nh2015103, https://doi.org/10.2166/nh.2015.103, 2015.
Kiptala, J. K., Mul, M. L., Mohamed, Y. A., and van der Zaag, P.: Modelling
stream flow and quantifying blue water using a modified STREAM model for a
heterogeneous, highly utilized and data-scarce river basin in Africa, Hydrol.
Earth Syst. Sci., 18, 2287–2303, https://doi.org/10.5194/hess-18-2287-2014, 2014.
Klemeš, V.: Operational testing of hydrological simulation models, Hydrolog. Sci. J., 31, 13–24, 1986.
Klotz, D., Herrnegger, M., and Schulz, K.: Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models, Water Resour. Res., 53, 9402–9423, https://doi.org/10.1002/2017wr021253, 2017.
Laloy, E. and Vrugt, J. A.: High-dimensional posterior exploration of hydrologic models using multiple-try DREAM(ZS) and high-performance computing, Water Resour. Res., 48, W01526, https://doi.org/10.1029/2011wr010608, 2012.
Lan, T., Lin, K. R., Liu, Z. Y., He, Y. H., Xu, C. Y., Zhang, H. B., and
Chen, X. H.: A Clustering Preprocessing Framework for the Subannual Calibration of a Hydrological Model Considering Climate-Land Surface
Variations, Water Resour. Res., 54, 10034–10052, https://doi.org/10.1029/2018wr023160, 2018.
Lin, K., Zhang, Q., and Chen, X.: An evaluation of impacts of DEM resolution and parameter correlation on TOPMODEL modeling uncertainty, J. Hydrol., 394, 370–383, https://doi.org/10.1016/j.jhydrol.2010.09.012, 2010.
Liu, Z. Y., Zhou, P., Chen, X. Z., and Guan, Y. H.: A multivariate conditional model for streamflow prediction and spatial precipitation refinement, J. Geophys. Res.-Atmos., 120, 10116–110129, https://doi.org/10.1002/2015JD02378, 2015.
Liu, Z. Y., Cheng, L. Y., Hao, Z. C., Li, J. J., Thorstensen, A., and Gao, H. K.: A framework for exploring joint effects of conditional factors on compound floods, Water Resour. Res., 54, 2681–2696, https://doi.org/10.1002/2017WR021662, 2018.
Luo, J. M., Wang, E. L., Shen, S. H., Zheng, H. X., and Zhang, Y. Q.: Effects of conditional parameterization on performance of rainfall-runoff model regarding hydrologic non-stationarity, Hydrol. Process., 26, 3953–3961,
https://doi.org/10.1002/hyp.8420, 2012.
Madsen, H.: Automatic calibration of a conceptual rainfall–runoff model
using multiple objectives, J. Hydrol., 235, 276–288,
https://doi.org/10.1016/S0022-1694(00)00279-1, 2000.
Maier, H. R., Kapelan, Z., Kasprzyk, J., Kollat, J., Matott, L. S., Cunha, M. C., Dandy, G. C., Gibbs, M. S., Keedwell, E., Marchi, A., Ostfeld, A., Savic, D., Solomatine, D. P., Vrugt, J. A., Zecchin, A. C., Minsker, B. S., Barbour, E. J., Kuczera, G., Pasha, F., Castelletti, A., Giuliani, M., and Reed, P. M.: Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions, Environ. Modell. Softw., 62, 271–299, 2014.
Me, W., Abell, J. M., and Hamilton, D. P.: Effects of hydrologic conditions on SWAT model performance and parameter sensitivity for a small, mixed land
use catchment in New Zealand, Hydrol. Earth Syst. Sci., 19, 4127–4147,
https://doi.org/10.5194/hess-19-4127-2015, 2015.
Merz, R., Parajka, J., and Bloschl, G.: Time stability of catchment model
parameters: Implications for climate impact analyses, Water Resour. Res., 47, W02531, https://doi.org/10.1029/2010wr009505, 2011.
Michalewicz, Z. and Schoenauer, M.: Evolutionary Algorithms for Constrained
Parameter Optimization Problems, Evol. Comput., 4, 1–32, https://doi.org/10.1162/evco.1996.4.1.1, 1996.
Moore, R. J.: The probability-distributed principle and runoff production at
point and basin scales, Hydrol. Sci. J., 30, 273–297,
https://doi.org/10.1080/02626668509490989, 1985.
Motavita, D. F., Chow, R., Guthke, A., and Nowak, W.: The comprehensive differential split-sample test: A stress-test for hydrological model robustness under climate variability, J. Hydrol., 573, 501–515,
https://doi.org/10.1016/j.jhydrol.2019.03.054, 2019.
NASA: Global digital elevation model (GDEM) with a cell size of 30×30 m on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), available at:
https://asterweb.jpl.nasa.gov/gdem.asp (last access: 20 March 2020), 2019.
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.
Nijzink, R. C., Samaniego, L., Mai, J., Kumar, R., Thober, S., Zink, M.,
Schäfer, D., Savenije, H. H. G., and Hrachowitz, M.: The importance of
topography-controlled sub-grid process heterogeneity and semi-quantitative
prior constraints in distributed hydrological models, Hydrol. Earth Syst. Sci., 20, 1151–1176, https://doi.org/10.5194/hess-20-1151-2016, 2016.
Omran, M. G. H. and Mahdavi, M.: Global-best harmony search, Appl. Math. Comput., 198, 643–656, https://doi.org/10.1016/j.amc.2007.09.004, 2008.
Osuch, M., Wawrzyniak, T., and Nawrot, A.: Diagnosis of the hydrology of a small Arctic permafrost catchment using HBV conceptual rainfall-runoff model,
Hydrol. Res., 50, 459–478, 2019.
Ouyang, Y., Xu, D., Leininger, T. D., and Zhang, N.: A system dynamic model to estimate hydrological processes and water use in a eucalypt plantation, Ecol. Eng., 86, 290–299, https://doi.org/10.1016/j.ecoleng.2015.11.008, 2016.
Pande, S. and Moayeri, M.: Hydrological Interpretation of a Statistical
Measure of Basin Complexity, Water Resour. Res., 54, 7403–7416,
https://doi.org/10.1029/2018WR022675, 2018.
Pathiraja, S., Marshall, L., Sharma, A., and Moradkhani, H.: Hydrologic modeling in dynamic catchments: A data assimilation approach, Water Resour. Res., 52, 3350–3372, https://doi.org/10.1002/2015wr017192, 2016.
Pathiraja, S., Anghileri, D., Burlando, P., Sharma, A., Marshall, L., and
Moradkhani, H.: Time-varying parameter models for catchments with land use
change: the importance of model structure, Hydrol. Earth Syst. Sci., 22,
2903–2919, https://doi.org/10.5194/hess-22-2903-2018, 2018.
Pfannerstill, M., Guse, B., and Fohrer, N.: Smart low flow signature metrics
for an improved overall performance evaluation of hydrological models, J. Hydrol., 510, 447–458, https://doi.org/10.1016/j.jhydrol.2013.12.044, 2014.
Pfannerstill, M., Guse, B., Reusser, D., and Fohrer, N.: Process verification of a hydrological model using a temporal parameter sensitivity analysis, Hydrol. Earth Syst. Sci., 19, 4365–4376, https://doi.org/10.5194/hess-19-4365-2015, 2015.
Piel, F. B., Patil, A. P., Howes, R. E., Nyangiri, O. A., Gething, P. W.,
Williams, T. N., Weatherall, D. J., and Hay, S. I.: Global distribution of
the sickle cell gene and geographical confirmation of the malaria hypothesis, Nat. Commun., 1, 104, https://doi.org/10.1038/ncomms1104, 2010.
Piotrowski, A. P., Napiorkowski, M. J., Napiorkowski, J. J., and Rowinski, P. M.: Swarm Intelligence and Evolutionary Algorithms: Performance versus speed, Inform. Sci., 384, 34–85, https://doi.org/10.1016/j.ins.2016.12.028, 2017.
Pool, S., Viviroli, D., and Seibert, J.: Prediction of hydrographs and
flow-duration curves in almost ungauged catchments: Which runoff measurements are most informative for model calibration?, J. Hydrol., 554, 613–622, https://doi.org/10.1016/j.jhydrol.2017.09.037, 2017.
Pugliese, A., Castellarin, A., and Brath, A.: Geostatistical prediction of
flow–duration curves in an index-flow framework, Hydrol. Earth Syst. Sci., 18, 3801–3816, https://doi.org/10.5194/hess-18-3801-2014, 2014.
Rahnamay Naeini, M., Yang, T., Sadegh, M., AghaKouchak, A., Hsu, K.-L., Sorooshian, S., Duan, Q., and Lei, X.: Shuffled Complex-Self Adaptive Hybrid
EvoLution (SC-SAHEL) optimization framework, Environ. Model. Softw., 104,
215–235, https://doi.org/10.1016/j.envsoft.2018.03.019, 2018.
Sarhadi, A., Burn, D. H., Concepción Ausín, M., and Wiper, M. P.:
Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula, Water Resour. Res., 52, 2327–2349, https://doi.org/10.1002/2015wr018525, 2016.
Sarrazin, F., Pianosi, F., and Wagener, T.: Global Sensitivity Analysis of
environmental models: Convergence and validation, Environ. Model. Softw., 79,
135–152, https://doi.org/10.1016/j.envsoft.2016.02.005, 2016.
Sivakumar, B.: Dominant processes concept in hydrology: moving forward, Hydrol. Process., 18, 2349–2353, https://doi.org/10.1002/hyp.5606, 2004.
Sorooshian, S., Duan, Q., and Gupta, V. K.: Calibration of rainfall-runoff
models: Application of global optimization to the Sacramento Soil Moisture
Accounting Model, Water Resour. Res., 29, 1185–1194, https://doi.org/10.1029/92wr02617, 1993.
Storn, R. and Price, K.: Differential Evolution – A Simple and Efficient
Heuristic for global Optimization over Continuous Spaces, J. Global Optimiz., 11, 341–359, https://doi.org/10.1023/a:1008202821328, 1997.
Sun, J., Wu, X., Palade, V., Fang, W., Lai, C.-H., and Xu, W.: Convergence
analysis and improvements of quantum-behaved particle swarm optimization,
Inform. Sci., 193, 81–103, https://doi.org/10.1016/j.ins.2012.01.005, 2012.
Todorovic, A. and Plavsic, J.: The role of conceptual hydrologic model calibration in climate change impact on water resources assessment, J. Water Clim. Change, 7, 16–28, https://doi.org/10.2166/wcc.2015.086, 2015.
Tongal, H. and Booij, M. J.: Simulation and forecasting of streamflows using machine learning models coupled with base flow separation, J. Hydrol., 564, 266–282, https://doi.org/10.1016/j.jhydrol.2018.07.004, 2018.
Turner, S. W. D., Bennett, J. C., Robertson, D. E., and Galelli, S.: Complex
relationship between seasonal streamflow forecast skill and value in reservoir operations, Hydrol. Earth Syst. Sci., 21, 4841–4859,
https://doi.org/10.5194/hess-21-4841-2017, 2017.
van Griensven, A., Meixner, T., Grunwald, S., Bishop, T., Diluzio, M., and
Srinivasan, R.: A global sensitivity analysis tool for the parameters of
multi-variable catchment models, J. Hydrol., 324, 10–23,
https://doi.org/10.1016/j.jhydrol.2005.09.008, 2006.
Vormoor, K., Heistermann, M., Bronstert, A., and Lawrence, D.: Hydrological
model parameter (in)stability – “crash testing” the HBV model under contrasting flood seasonality conditions, Hydrolog. Sci. J., 63, 991–1007, https://doi.org/10.1080/02626667.2018.1466056, 2018.
Vrugt, J. A. and Beven, K. J.: Embracing equifinality with efficiency: Limits of Acceptability sampling using the DREAM (LOA) algorithm, J. Hydrol., 559, 954–971, https://doi.org/10.1016/j.jhydrol.2018.02.026, 2018.
Vrugt, J. A., Bouten, W., Gupta, H. V., and Sorooshian, S.: Toward improved
identifiability of hydrologic model parameters: The information content of
experimental data, Water Resour. Res., 38, 48-41–48-13, https://doi.org/10.1029/2001WR001118, 2002.
Vrugt, J. A., Diks, C. G. H., Gupta, H. V., Bouten, W., and Verstraten, J. M.: Improved treatment of uncertainty in hydrologic modeling: Combining the
strengths of global optimization and data assimilation, Water Resour. Res., 41, W01017, https://doi.org/10.1029/2004wr003059, 2005.
Wagener, T. and Kollat, J.: Numerical and visual evaluation of hydrological and environmental models using the Monte Carlo analysis toolbox, Environ.
Model. Softw., 22, 1021–1033, https://doi.org/10.1016/j.envsoft.2006.06.017, 2007.
Wagener, T., Boyle, D. P., Lees, M. J., Wheater, H. S., Gupta, H. V., and
Sorooshian, S.: A framework for development and application of hydrological
models, Hydrol. Earth Syst. Sci., 5, 13–26, https://doi.org/10.5194/hess-5-13-2001, 2001.
Wagener, T., McIntyre, N., Lees, M. J., Wheater, H. S., and Gupta, H. V.:
Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic
identifiability analysis, Hydrol. Process., 17, 455–476, https://doi.org/10.1002/hyp.1135, 2003.
Wang, S., Huang, G. H., Baetz, B. W., and Ancell, B. C.: Towards robust
quantification and reduction of uncertainty in hydrologic predictions:
Integration of particle Markov chain Monte Carlo and factorial polynomial chaos expansion, J. Hydrol., 548, 484–497, https://doi.org/10.1016/j.jhydrol.2017.03.027, 2017a.
Wang, S., Huang, G. H., Baetz, B. W., Cai, X. M., Ancell, B. C., and Fan, Y. R.: Examining dynamic interactions among experimental factors influencing
hydrologic data assimilation with the ensemble Kalman filter, J. Hydrol., 554, 743–757, https://doi.org/10.1016/j.jhydrol.2017.09.052, 2017b.
Wang, S., Ancell, B., Huang, G., and Baetz, B.: Improving Robustness of
Hydrologic Ensemble Predictions Through Probabilistic Pre-and Post-Processing in Sequential Data Assimilation, Water Resour. Res., 54, 2129–2151, 2018.
Weinberger, E. J. B. C.: Correlated and uncorrelated fitness landscapes and
how to tell the difference, Biol. Cyber., 63, 325–336, https://doi.org/10.1007/bf00202749, 1990.
Weise, T.: Global optimization algorithms-theory and application, Self-Published, second edition, available at: http://www.it-weise.de/projects/book.pdf (last access: 20 March 2020), 2009.
Westra, S., Thyer, M., Leonard, M., Kavetski, D., and Lambert, M.: A strategy for diagnosing and interpreting hydrological model nonstationarity, Water Resour. Res., 50, 5090–5113, 2014.
Wi, S., Yang, Y. C. E., Steinschneider, S., Khalil, A., and Brown, C. M.:
Calibration approaches for distributed hydrologic models in poorly gaged
basins: implication for streamflow projections under climate change, Hydrol.
Earth Syst. Sci., 19, 857–876, https://doi.org/10.5194/hess-19-857-2015, 2015.
Xiong, B., Xiong, L., Chen, J., Xu, C.-Y., and Li, L.: Multiple causes of
nonstationarity in the Weihe annual low-flow series, Hydrol. Earth Syst. Sci., 22, 1525–1542, https://doi.org/10.5194/hess-22-1525-2018, 2018.
Xiong, M., Liu, P., Cheng, L., Deng, C., Gui, Z., Zhang, X., and Liu, Y.:
Identifying time-varying hydrological model parameters to improve simulation
efficiency by the ensemble Kalman filter: A joint assimilation of streamflow
and actual evapotranspiration, J. Hydrol., 568, 758–768,
https://doi.org/10.1016/j.jhydrol.2018.11.038, 2019.
Yadav, M., Wagener, T., and Gupta, H.: Regionalization of constraints on
expected watershed response behavior for improved predictions in ungauged basins, Adv. Water Resour., 30, 1756–1774, https://doi.org/10.1016/j.advwatres.2007.01.005, 2007.
Yiu-Wing, L. and Yuping, W.: An orthogonal genetic algorithm with quantization for global numerical optimization, IEEE T. Evol. Comput., 5,
41–53, https://doi.org/10.1109/4235.910464, 2001.
Zecchin, A. C., Simpson, A. R., Maier, H. R., Marchi, A., and Nixon, J. B.:
Improved understanding of the searching behavior of ant colony optimization
algorithms applied to the water distribution design problem, Water Resour. Res., 48, W09505,
https://doi.org/10.1029/2011wr011652, 2012.
Zhang, D. J., Chen, X. W., Yao, H. X., and Lin, B. Q.: Improved calibration
scheme of SWAT by separating wet and dry seasons, Ecol. Model., 301, 54–61,
https://doi.org/10.1016/j.ecolmodel.2015.01.018, 2015.
Zhang, H., Huang, G. H., Wang, D. L., and Zhang, X. D.: Multi-period
calibration of a semi-distributed hydrological model based on hydroclimatic
clustering, Adv. Water Resour., 34, 1292–1303, https://doi.org/10.1016/j.advwatres.2011.06.005, 2011.
Zhang, X., Srinivasan, R., Zhao, K., and Liew, M. V.: Evaluation of global
optimization algorithms for parameter calibration of a computationally
intensive hydrologic model, Hydrol. Process., 23, 430–441,
https://doi.org/10.1002/hyp.7152, 2009.
Zhang, Y., Hao, Z., Xu, C.-Y., and Lai, X.: Response of melt water and rainfall runoff to climate change and their roles in controlling streamflow changes of the two upstream basins over the Tibetan Plateau, Hydrol. Res., nh2019075, https://doi.org/10.2166/nh.2019.075, 2019.
Zhao, B., Dai, H., Han, D., and Rong, G.: The sub-annual calibration of hydrological models considering climatic intra-annual variations, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-396, 2017.
Zheng, F., Zecchin, A. C., Newman, J. P., Maier, H. R., and Dandy, G. C.: An
Adaptive Convergence-Trajectory Controlled Ant Colony Optimization Algorithm
With Application to Water Distribution System Design Problems, IEEE T. Evol.
Comput., 21, 773–791, https://doi.org/10.1109/TEVC.2017.2682899, 2017.
