Articles | Volume 15, issue 17
https://doi.org/10.5194/gmd-15-6581-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-6581-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
01 Sep 2022
Model description paper |
| 01 Sep 2022
A physically based distributed karst hydrological model (QMG model-V1.0) for flood simulations
Chongqing Jinfo Mountain Karst Ecosystem National Observation and
Research Station, Chongqing Key Laboratory of Karst Environment, School of
Geographical Sciences, Southwest University, Chongqing 400715, China
Daoxian Yuan
Chongqing Jinfo Mountain Karst Ecosystem National Observation and
Research Station, Chongqing Key Laboratory of Karst Environment, School of
Geographical Sciences, Southwest University, Chongqing 400715, China
Key Laboratory of Karst Dynamics, MNR & Guangxi, Institute of Karst
Geology, Chinese Academy of Geological Sciences, Guilin 541004, China
Fuxi Zhang
College of Engineering Science and Technology, Shanghai Ocean
University, Shanghai Engineering Research Center of Marine Renewable Energy
201306, China
Jiao Liu
Chongqing Municipal Hydrological Monitoring Station, Chongqing 401120,
China
Mingguo Ma
Chongqing Jinfo Mountain Karst Ecosystem National Observation and
Research Station, Chongqing Key Laboratory of Karst Environment, School of
Geographical Sciences, Southwest University, Chongqing 400715, China
Related authors
Ji Li, Daoxian Yuan, Aihua Hong, Yongjun Jiang, Jiao Liu, and Yangbo Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-285, https://doi.org/10.5194/hess-2019-285, 2019
Preprint withdrawn
Short summary
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There is often a lack of effective precipitation in karst areas. In this study, two weather models, the WRF QPF and the PERSIANN-CCS QPEs are used,compared and revised to obtain reliable rainfall results for a karst basin. After that,coupling the two weather model with a new fully distributed and physical hydrological model, the Karst-Liuxihe model in flood simulations and forecasting in a typical karst watershed. This coupling model works well and can be extended to other karst basins.
Ji Li, Daoxian Yuan, Jiao Liu, Yongjun Jiang, Yangbo Chen, Kuo Lin Hsu, and Soroosh Sorooshian
Hydrol. Earth Syst. Sci., 23, 1505–1532, https://doi.org/10.5194/hess-23-1505-2019, https://doi.org/10.5194/hess-23-1505-2019, 2019
Short summary
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There are no long-term reasonable rainfall data to build a hydrological model in karst river basins to a large extent. In this paper, the PERSIANN-CCS QPEs are employed to estimate the precipitation data as an attempt in the Liujiang karst river basin, 58 270 km2, China. An improved method is proposed to revise the results of the PERSIANN-CCS QPEs. The post-processed PERSIANN-CCS QPE with a distributed hydrological model, the Liuxihe model, has a better performance in karst flood forecasting.
Ji Li, Yangbo Chen, Huanyu Wang, Jianming Qin, Jie Li, and Sen Chiao
Hydrol. Earth Syst. Sci., 21, 1279–1294, https://doi.org/10.5194/hess-21-1279-2017, https://doi.org/10.5194/hess-21-1279-2017, 2017
Short summary
Short summary
Quantitative precipitation forecast produced by the WRF model has a similar pattern to that estimated by rain gauges in a southern China large watershed, hydrological model parameters should be optimized with QPF produced by WRF, and simulating floods by coupling the WRF QPF with a distributed hydrological model provides a good reference for large watershed flood warning and could benefit the flood management communities due to its longer lead time.
Yangbo Chen, Ji Li, Huanyu Wang, Jianming Qin, and Liming Dong
Hydrol. Earth Syst. Sci., 21, 735–749, https://doi.org/10.5194/hess-21-735-2017, https://doi.org/10.5194/hess-21-735-2017, 2017
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The distributed hydrological model has not yet been applied in large watershed flood forecasting due to some limitations. By proposing a method for estimating channel cross section size with remote sensing data, employing the PSO algorithm optimize model parameters and running the model on high-performance supercomputer with parallel computation technique, this article successfully applied the Liuxihe model in a larger watershed flood forecasting in southern China at high resolution.
Y. Chen, J. Li, and H. Xu
Hydrol. Earth Syst. Sci., 20, 375–392, https://doi.org/10.5194/hess-20-375-2016, https://doi.org/10.5194/hess-20-375-2016, 2016
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Parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. A method for parameter optimization with particle swam optimization (PSO) algorithm has been proposed for physically based distributed hydrological model in catchment flood forecasting and validated in southern China. It has found that the appropriate particle number and maximum evolution number of PSO algorithm are 20 and 30 respectively.
Debing Kong, Guicai Ning, Shigong Wang, Jing Cong, Ming Luo, Xiang Ni, and Mingguo Ma
Atmos. Chem. Phys., 21, 14493–14505, https://doi.org/10.5194/acp-21-14493-2021, https://doi.org/10.5194/acp-21-14493-2021, 2021
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This study provides the first attempt to examine the diurnal cycles of day-to-day temperature change and reveals their impacts on air quality forecasting in mountain-basin areas. Three different diurnal cycles of the preceding day-to-day temperature change are identified and exhibit notably distinct effects on the air quality evolutions. The mechanisms of the identified diurnal cycles' effects on air quality are also revealed, which exhibit promising potential for air quality forecasting.
Chao-Jun Chen, Dao-Xian Yuan, Jun-Yun Li, Xian-Feng Wang, Hai Cheng, You-Feng Ning, R. Lawrence Edwards, Yao Wu, Si-Ya Xiao, Yu-Zhen Xu, Yang-Yang Huang, Hai-Ying Qiu, Jian Zhang, Ming-Qiang Liang, and Ting-Yong Li
Clim. Past Discuss., https://doi.org/10.5194/cp-2021-20, https://doi.org/10.5194/cp-2021-20, 2021
Manuscript not accepted for further review
Tao Che, Xin Li, Shaomin Liu, Hongyi Li, Ziwei Xu, Junlei Tan, Yang Zhang, Zhiguo Ren, Lin Xiao, Jie Deng, Rui Jin, Mingguo Ma, Jian Wang, and Xiaofan Yang
Earth Syst. Sci. Data, 11, 1483–1499, https://doi.org/10.5194/essd-11-1483-2019, https://doi.org/10.5194/essd-11-1483-2019, 2019
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The paper presents a suite of datasets consisting of long-term hydrometeorological, snow cover and frozen ground data for investigating watershed science and functions from an integrated, distributed and multiscale observation network in the upper reaches of the Heihe River Basin in China. These data are expected to serve as a testing platform to provide accurate forcing data and validate and evaluate remote-sensing products and hydrological models in cold regions for a broader community.
Ji Li, Daoxian Yuan, Aihua Hong, Yongjun Jiang, Jiao Liu, and Yangbo Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-285, https://doi.org/10.5194/hess-2019-285, 2019
Preprint withdrawn
Short summary
Short summary
There is often a lack of effective precipitation in karst areas. In this study, two weather models, the WRF QPF and the PERSIANN-CCS QPEs are used,compared and revised to obtain reliable rainfall results for a karst basin. After that,coupling the two weather model with a new fully distributed and physical hydrological model, the Karst-Liuxihe model in flood simulations and forecasting in a typical karst watershed. This coupling model works well and can be extended to other karst basins.
Ji Li, Daoxian Yuan, Jiao Liu, Yongjun Jiang, Yangbo Chen, Kuo Lin Hsu, and Soroosh Sorooshian
Hydrol. Earth Syst. Sci., 23, 1505–1532, https://doi.org/10.5194/hess-23-1505-2019, https://doi.org/10.5194/hess-23-1505-2019, 2019
Short summary
Short summary
There are no long-term reasonable rainfall data to build a hydrological model in karst river basins to a large extent. In this paper, the PERSIANN-CCS QPEs are employed to estimate the precipitation data as an attempt in the Liujiang karst river basin, 58 270 km2, China. An improved method is proposed to revise the results of the PERSIANN-CCS QPEs. The post-processed PERSIANN-CCS QPE with a distributed hydrological model, the Liuxihe model, has a better performance in karst flood forecasting.
Ji Li, Yangbo Chen, Huanyu Wang, Jianming Qin, Jie Li, and Sen Chiao
Hydrol. Earth Syst. Sci., 21, 1279–1294, https://doi.org/10.5194/hess-21-1279-2017, https://doi.org/10.5194/hess-21-1279-2017, 2017
Short summary
Short summary
Quantitative precipitation forecast produced by the WRF model has a similar pattern to that estimated by rain gauges in a southern China large watershed, hydrological model parameters should be optimized with QPF produced by WRF, and simulating floods by coupling the WRF QPF with a distributed hydrological model provides a good reference for large watershed flood warning and could benefit the flood management communities due to its longer lead time.
Yangbo Chen, Ji Li, Huanyu Wang, Jianming Qin, and Liming Dong
Hydrol. Earth Syst. Sci., 21, 735–749, https://doi.org/10.5194/hess-21-735-2017, https://doi.org/10.5194/hess-21-735-2017, 2017
Short summary
Short summary
The distributed hydrological model has not yet been applied in large watershed flood forecasting due to some limitations. By proposing a method for estimating channel cross section size with remote sensing data, employing the PSO algorithm optimize model parameters and running the model on high-performance supercomputer with parallel computation technique, this article successfully applied the Liuxihe model in a larger watershed flood forecasting in southern China at high resolution.
Y. Chen, J. Li, and H. Xu
Hydrol. Earth Syst. Sci., 20, 375–392, https://doi.org/10.5194/hess-20-375-2016, https://doi.org/10.5194/hess-20-375-2016, 2016
Short summary
Short summary
Parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. A method for parameter optimization with particle swam optimization (PSO) algorithm has been proposed for physically based distributed hydrological model in catchment flood forecasting and validated in southern China. It has found that the appropriate particle number and maximum evolution number of PSO algorithm are 20 and 30 respectively.
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Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
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Stefania Camici, Gabriele Giuliani, Luca Brocca, Christian Massari, Angelica Tarpanelli, Hassan Hashemi Farahani, Nico Sneeuw, Marco Restano, and Jérôme Benveniste
Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, https://doi.org/10.5194/gmd-15-6935-2022, 2022
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This paper presents an innovative approach, STREAM (SaTellite-based Runoff Evaluation And Mapping), to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and terrestrial total water storage anomalies. Potentially useful for multiple operational and scientific applications, the added value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities, and their interactions on the land.
Luca Trotter, Wouter J. M. Knoben, Keirnan J. A. Fowler, Margarita Saft, and Murray C. Peel
Geosci. Model Dev., 15, 6359–6369, https://doi.org/10.5194/gmd-15-6359-2022, https://doi.org/10.5194/gmd-15-6359-2022, 2022
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Zhi Li, Shang Gao, Mengye Chen, Jonathan Gourley, Naoki Mizukami, and Yang Hong
Geosci. Model Dev., 15, 6181–6196, https://doi.org/10.5194/gmd-15-6181-2022, https://doi.org/10.5194/gmd-15-6181-2022, 2022
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Operational streamflow prediction at a continental scale is critical for national water resources management. However, limited computational resources often impede such processes, with streamflow routing being one of the most time-consuming parts. This study presents a recent development of a hydrologic system that incorporates a vector-based routing scheme with a lake module that markedly speeds up streamflow prediction. Moreover, accuracy is improved and flood false alarms are mitigated.
Suyeon Choi and Yeonjoo Kim
Geosci. Model Dev., 15, 5967–5985, https://doi.org/10.5194/gmd-15-5967-2022, https://doi.org/10.5194/gmd-15-5967-2022, 2022
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Here we present the cGAN-based precipitation nowcasting model, named Rad-cGAN, trained to predict a radar reflectivity map with a lead time of 10 min. Rad-cGAN showed superior performance at a lead time of up to 90 min compared with the reference models. Furthermore, we demonstrate the successful implementation of the transfer learning strategies using pre-trained Rad-cGAN to develop the models for different dam domains.
Rolf Hut, Niels Drost, Nick van de Giesen, Ben van Werkhoven, Banafsheh Abdollahi, Jerom Aerts, Thomas Albers, Fakhereh Alidoost, Bouwe Andela, Jaro Camphuijsen, Yifat Dzigan, Ronald van Haren, Eric Hutton, Peter Kalverla, Maarten van Meersbergen, Gijs van den Oord, Inti Pelupessy, Stef Smeets, Stefan Verhoeven, Martine de Vos, and Berend Weel
Geosci. Model Dev., 15, 5371–5390, https://doi.org/10.5194/gmd-15-5371-2022, https://doi.org/10.5194/gmd-15-5371-2022, 2022
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With the eWaterCycle platform, we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both open science and FAIR science. The eWatercyle platform gives easy access to well-known hydrological models, big datasets and example experiments. Using eWaterCycle hydrologists can easily compare the results from different models, couple models and do more complex hydrological computational research.
Hsi-Kai Chou, Ana Maria Heuminski de Avila, and Michaela Bray
Geosci. Model Dev., 15, 5233–5240, https://doi.org/10.5194/gmd-15-5233-2022, https://doi.org/10.5194/gmd-15-5233-2022, 2022
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Land surface models allow us to understand and investigate the cause and effect of environmental process changes. Therefore, this type of model is increasingly used for hydrological assessments. Here we explore the possibility of this approach using a case study in the Atibaia River basin, which serves as a major water supply for the metropolitan regions of Campinas and São Paulo, Brazil. We evaluated the model performance and use the model to simulate the basin hydrology.
Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
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Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Verena Bessenbacher, Sonia Isabelle Seneviratne, and Lukas Gudmundsson
Geosci. Model Dev., 15, 4569–4596, https://doi.org/10.5194/gmd-15-4569-2022, https://doi.org/10.5194/gmd-15-4569-2022, 2022
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Earth observations have many missing values. They are often filled using information from spatial and temporal contexts that mostly ignore information from related observed variables. We propose the gap-filling method CLIMFILL that additionally uses information from related variables. We test CLIMFILL using gap-free reanalysis data of variables related to soil–moisture climate interactions. CLIMFILL creates estimates for the missing values that recover the original dependence structure.
Anthony Bernus and Catherine Ottlé
Geosci. Model Dev., 15, 4275–4295, https://doi.org/10.5194/gmd-15-4275-2022, https://doi.org/10.5194/gmd-15-4275-2022, 2022
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The lake model FLake was coupled to the ORCHIDEE land surface model to simulate lake energy balance at global scale with a multi-tile approach. Several simulations were performed with various atmospheric reanalyses and different lake depth parameterizations. The simulated lake surface temperature showed good agreement with observations (RMSEs of the order of 3 °C). We showed the large impact of the atmospheric forcing on lake temperature. We highlighted systematic errors on ice cover phenology.
Inne Vanderkelen, Shervan Gharari, Naoki Mizukami, Martyn P. Clark, David M. Lawrence, Sean Swenson, Yadu Pokhrel, Naota Hanasaki, Ann van Griensven, and Wim Thiery
Geosci. Model Dev., 15, 4163–4192, https://doi.org/10.5194/gmd-15-4163-2022, https://doi.org/10.5194/gmd-15-4163-2022, 2022
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Human-controlled reservoirs have a large influence on the global water cycle. However, dam operations are rarely represented in Earth system models. We implement and evaluate a widely used reservoir parametrization in a global river-routing model. Using observations of individual reservoirs, the reservoir scheme outperforms the natural lake scheme. However, both schemes show a similar performance due to biases in runoff timing and magnitude when using simulated runoff.
Jiming Jin, Lei Wang, Jie Yang, Bingcheng Si, and Guo-Yue Niu
Geosci. Model Dev., 15, 3405–3416, https://doi.org/10.5194/gmd-15-3405-2022, https://doi.org/10.5194/gmd-15-3405-2022, 2022
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This study aimed to improve runoff simulations and explore deep soil hydrological processes for a highly varying soil depth and complex terrain watershed in the Loess Plateau, China. The actual soil depths and river channels were incorporated into the model to better simulate the runoff in this watershed. The soil evaporation scheme was modified to better describe the evaporation processes. Our results showed that the model significantly improved the runoff simulations.
Sebastian Müller, Lennart Schüler, Alraune Zech, and Falk Heße
Geosci. Model Dev., 15, 3161–3182, https://doi.org/10.5194/gmd-15-3161-2022, https://doi.org/10.5194/gmd-15-3161-2022, 2022
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The GSTools package provides a Python-based platform for geoostatistical applications. Salient features of GSTools are its random field generation, its kriging capabilities and its versatile covariance model. It is furthermore integrated with other Python packages, like PyKrige, ogs5py or scikit-gstat, and provides interfaces to meshio and PyVista. Four presented workflows showcase the abilities of GSTools.
Ather Abbas, Laurie Boithias, Yakov Pachepsky, Kyunghyun Kim, Jong Ahn Chun, and Kyung Hwa Cho
Geosci. Model Dev., 15, 3021–3039, https://doi.org/10.5194/gmd-15-3021-2022, https://doi.org/10.5194/gmd-15-3021-2022, 2022
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The field of artificial intelligence has shown promising results in a wide variety of fields including hydrological modeling. However, developing and testing hydrological models with artificial intelligence techniques require expertise from diverse fields. In this study, we developed an open-source framework based upon the python programming language to simplify the process of the development of hydrological models of time series data using machine learning.
Yunxiang Chen, Jie Bao, Yilin Fang, William A. Perkins, Huiying Ren, Xuehang Song, Zhuoran Duan, Zhangshuan Hou, Xiaoliang He, and Timothy D. Scheibe
Geosci. Model Dev., 15, 2917–2947, https://doi.org/10.5194/gmd-15-2917-2022, https://doi.org/10.5194/gmd-15-2917-2022, 2022
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Climate change affects river discharge variations that alter streamflow. By integrating multi-type survey data with a computational fluid dynamics tool, OpenFOAM, we show a workflow that enables accurate and efficient streamflow modeling at 30 km and 5-year scales. The model accuracy for water stage and depth average velocity is −16–9 cm and 0.71–0.83 in terms of mean error and correlation coefficients. This accuracy indicates the model's reliability for evaluating climate impact on rivers.
Marcela Silva, Ashley M. Matheny, Valentijn R. N. Pauwels, Dimetre Triadis, Justine E. Missik, Gil Bohrer, and Edoardo Daly
Geosci. Model Dev., 15, 2619–2634, https://doi.org/10.5194/gmd-15-2619-2022, https://doi.org/10.5194/gmd-15-2619-2022, 2022
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Our study introduces FETCH3, a ready-to-use, open-access model that simulates the water fluxes across the soil, roots, and stem. To test the model capabilities, we tested it against exact solutions and a case study. The model presented considerably small errors when compared to the exact solutions and was able to correctly represent transpiration patterns when compared to experimental data. The results show that FETCH3 can correctly simulate above- and below-ground water transport.
Mayra Ishikawa, Wendy Gonzalez, Orides Golyjeswski, Gabriela Sales, J. Andreza Rigotti, Tobias Bleninger, Michael Mannich, and Andreas Lorke
Geosci. Model Dev., 15, 2197–2220, https://doi.org/10.5194/gmd-15-2197-2022, https://doi.org/10.5194/gmd-15-2197-2022, 2022
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Reservoir hydrodynamics is often described in numerical models differing in dimensionality. 1D and 2D models assume homogeneity along the unresolved dimension. We compare the performance of models with 1 to 3 dimensions. All models presented reasonable results for seasonal temperature dynamics. Neglecting longitudinal transport resulted in the largest deviations in temperature. Flow velocity could only be reproduced by the 3D model. Results support the selection of models and their assessment.
Sandra Hellmers and Peter Fröhle
Geosci. Model Dev., 15, 1061–1077, https://doi.org/10.5194/gmd-15-1061-2022, https://doi.org/10.5194/gmd-15-1061-2022, 2022
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A hydrological method to compute backwater effects in surface water streams and on adjacent lowlands caused by mostly complex flow control systems is presented. It enables transfer of discharges to water levels and calculation of backwater volume routing along streams and lowland areas by balancing water level slopes. The developed, implemented and evaluated method extends the application range of hydrological models significantly for flood-routing simulation in backwater-affected catchments.
Mathias Bavay, Michael Reisecker, Thomas Egger, and Daniela Korhammer
Geosci. Model Dev., 15, 365–378, https://doi.org/10.5194/gmd-15-365-2022, https://doi.org/10.5194/gmd-15-365-2022, 2022
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Most users struggle with the configuration of numerical models. This can be improved by relying on a GUI, but this requires a significant investment and a specific skill set and does not fit with the daily duties of model developers, leading to major maintenance burdens. Inishell generates a GUI on the fly based on an XML description of the required configuration elements, making maintenance very simple. This concept has been shown to work very well in our context.
Vladimir Mirlas, Yaakov Anker, Asher Aizenkod, and Naftali Goldshleger
Geosci. Model Dev., 15, 129–143, https://doi.org/10.5194/gmd-15-129-2022, https://doi.org/10.5194/gmd-15-129-2022, 2022
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Salinization owing to irrigation water quality causes soil degradation and soil fertility reduction that with poor drainage conditions impede plant development and manifest in economic damage. This study provided a soil salting process evaluation procedure through a combination of soil salinity monitoring, field experiments, remote sensing, and unsaturated soil profile saline water movement modeling. The modeling results validated the soil salinization danger from using brackish irrigation.
Niccolò Tubini and Riccardo Rigon
Geosci. Model Dev., 15, 75–104, https://doi.org/10.5194/gmd-15-75-2022, https://doi.org/10.5194/gmd-15-75-2022, 2022
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This paper presents WHETGEO and its 1D deployment: a new physically based model simulating the water and energy budgets in a soil column. WHETGEO-1D is intended to be the first building block of a new customisable land-surface model that is integrated with process-based hydrology. WHETGEO is developed as an open-source code and is fully integrated into the GEOframe/OMS3 system, allowing the use of the many ancillary tools it provides.
Tobias Stacke and Stefan Hagemann
Geosci. Model Dev., 14, 7795–7816, https://doi.org/10.5194/gmd-14-7795-2021, https://doi.org/10.5194/gmd-14-7795-2021, 2021
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HydroPy is a new version of an established global hydrology model. It was rewritten from scratch and adapted to a modern object-oriented infrastructure to facilitate its future development and application. With this study, we provide a thorough documentation and evaluation of our new model. At the same time, we open our code base and publish the model's source code in a public software repository. In this way, we aim to contribute to increasing transparency and reproducibility in science.
Emilie Rouzies, Claire Lauvernet, Bruno Sudret, and Arthur Vidard
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-425, https://doi.org/10.5194/gmd-2021-425, 2021
Revised manuscript accepted for GMD
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Water and pesticide transfer models are complex and should be simplified to be used in decision support. Indeed, these models simulate many spatial processes in interaction, involving a large number of parameters. Sensitivity analysis allows selecting the most influential input parameters but it has to be adapted to spatial modelling. This study will (i) identify relevant methods that can be transposed to any hydrological and water quality models, (ii) improve the fate of pesticides knowledge.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, https://doi.org/10.5194/gmd-14-7545-2021, 2021
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Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
model evaluation).
Marco Toffolon, Luca Cortese, and Damien Bouffard
Geosci. Model Dev., 14, 7527–7543, https://doi.org/10.5194/gmd-14-7527-2021, https://doi.org/10.5194/gmd-14-7527-2021, 2021
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The time when lakes freeze varies considerably from year to year. A common way to predict it is to use negative degree days, i.e., the sum of air temperatures below 0 °C, a proxy for the heat lost to the atmosphere. Here, we show that this is insufficient as the mixing of the surface layer induced by wind tends to delay the formation of ice. To do so, we developed a minimal model based on a simplified energy balance, which can be used both for large-scale analyses and short-term predictions.
Marco De Lucia, Michael Kühn, Alexander Lindemann, Max Lübke, and Bettina Schnor
Geosci. Model Dev., 14, 7391–7409, https://doi.org/10.5194/gmd-14-7391-2021, https://doi.org/10.5194/gmd-14-7391-2021, 2021
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POET is a parallel reactive transport simulator which implements a mechanism to store and reuse previous results of geochemical simulations through distributed hash tables. POET parallelizes chemistry using a master/worker design with noncontiguous grid partitions to maximize its efficiency and load balance on shared-memory machines and compute clusters.
Mary M. F. O'Neill, Danielle T. Tijerina, Laura E. Condon, and Reed M. Maxwell
Geosci. Model Dev., 14, 7223–7254, https://doi.org/10.5194/gmd-14-7223-2021, https://doi.org/10.5194/gmd-14-7223-2021, 2021
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Modeling the hydrologic cycle at high resolution and at large spatial scales is an incredible opportunity and challenge for hydrologists. In this paper, we present the results of a high-resolution hydrologic simulation configured over the contiguous United States. We discuss simulated water fluxes through groundwater, soil, plants, and over land, and we compare model results to in situ observations and satellite products in order to build confidence and guide future model development.
Daniel Power, Miguel Angel Rico-Ramirez, Sharon Desilets, Darin Desilets, and Rafael Rosolem
Geosci. Model Dev., 14, 7287–7307, https://doi.org/10.5194/gmd-14-7287-2021, https://doi.org/10.5194/gmd-14-7287-2021, 2021
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Cosmic-ray neutron sensors estimate root-zone soil moisture at sub-kilometre scales. There are national-scale networks of these sensors across the globe; however, methods for converting neutron signals to soil moisture values are inconsistent. This paper describes our open-source Python tool that processes raw sensor data into soil moisture estimates. The aim is to allow a user to ensure they have a harmonized data set, along with informative metadata, to facilitate both research and teaching.
Marco Dal Molin, Dmitri Kavetski, and Fabrizio Fenicia
Geosci. Model Dev., 14, 7047–7072, https://doi.org/10.5194/gmd-14-7047-2021, https://doi.org/10.5194/gmd-14-7047-2021, 2021
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This paper introduces SuperflexPy, an open-source Python framework for building flexible conceptual hydrological models. SuperflexPy is available as open-source code and can be used by the hydrological community to investigate improved process representations, for model comparison, and for operational work.
E. Andrés Quichimbo, Michael Bliss Singer, Katerina Michaelides, Daniel E. J. Hobley, Rafael Rosolem, and Mark O. Cuthbert
Geosci. Model Dev., 14, 6893–6917, https://doi.org/10.5194/gmd-14-6893-2021, https://doi.org/10.5194/gmd-14-6893-2021, 2021
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Understanding and quantifying water partitioning in dryland regions are of key importance to anticipate the future impacts of climate change in water resources and dryland ecosystems. Here, we have developed a simple hydrological model (DRYP) that incorporates the key processes of water partitioning in drylands. DRYP is a modular, versatile, and parsimonious model that can be used to anticipate and plan for climatic and anthropogenic changes to water fluxes and storage in dryland regions.
Nathaniel W. Chaney, Laura Torres-Rojas, Noemi Vergopolan, and Colby K. Fisher
Geosci. Model Dev., 14, 6813–6832, https://doi.org/10.5194/gmd-14-6813-2021, https://doi.org/10.5194/gmd-14-6813-2021, 2021
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Although there have been significant advances in river routing and sub-grid heterogeneity (i.e., tiling) schemes in Earth system models over the past decades, there has yet to be a concerted effort to couple these two concepts. This paper aims to bridge this gap through the development of a two-way coupling between tiling schemes and river networks in the HydroBlocks land surface model. The scheme is implemented and tested over a 1 arc degree domain in Oklahoma, United States.
Dejian Zhang, Bingqing Lin, Jiefeng Wu, and Qiaoying Lin
Geosci. Model Dev., 14, 5915–5925, https://doi.org/10.5194/gmd-14-5915-2021, https://doi.org/10.5194/gmd-14-5915-2021, 2021
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GP-SWAT is a two-layer model parallelization tool for a SWAT model based on the graph-parallel Pregel algorithm. It can be employed to perform both individual and iterative model parallelization, endowing it with a range of possible applications and great flexibility in maximizing performance. As a flexible and scalable tool, it can run in diverse environments, ranging from a commodity computer with a Microsoft Windows, Mac or Linux OS to a Spark cluster consisting of a large number of nodes.
Daisuke Tokuda, Hyungjun Kim, Dai Yamazaki, and Taikan Oki
Geosci. Model Dev., 14, 5669–5693, https://doi.org/10.5194/gmd-14-5669-2021, https://doi.org/10.5194/gmd-14-5669-2021, 2021
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We developed TCHOIR, a hydrologic simulation framework, to solve fluvial- and thermodynamics of the river–lake continuum. This provides an algorithm for upscaling high-resolution topography as well, which enables the representation of those interactions at the global scale. Validation against in situ and satellite observations shows that the coupled mode outperforms river- or lake-only modes. TCHOIR will contribute to elucidating the role of surface hydrology in Earth’s energy and water cycle.
Marko Kallio, Joseph H. A. Guillaume, Vili Virkki, Matti Kummu, and Kirsi Virrantaus
Geosci. Model Dev., 14, 5155–5181, https://doi.org/10.5194/gmd-14-5155-2021, https://doi.org/10.5194/gmd-14-5155-2021, 2021
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Different runoff and streamflow products are freely available but may come with unsuitable spatial units. On the other hand, starting a new modelling exercise may require considerable resources. Hydrostreamer improves the usability of existing runoff products, allowing runoff and streamflow estimates at the desired spatial units with minimal data requirements and intuitive workflow. The case study shows that Hydrostreamer performs well compared to benchmark products and observation data.
Cited articles
Abbott, M. B., Bathurst, J. C., Cunge, J. A., O'Connell, P. E., and
Rasmussen, J.: An Introduction to the European HydrologicSystem-System
Hydrologue Europeen, `SHE', a: History and Philosophy of a Physically-based,
Distributed Modelling System, J. Hydrol., 87, 45–59, 1986a.
Abbott, M. B., Bathurst, J. C., Cunge, J. A., O'Connell, P. E., and
Rasmussen, J.: An Introduction to the European Hydrologic System-System
Hydrologue Europeen, `SHE', b: Structure of a Physically based, distributed
modeling System, J. Hydrol., 87, 61–77, 1986b.
Ambroise, B., Beven, K., and Freer, J.: Toward a generalization of the
TOPMODEL concepts: Topographic indices of hydrologic similarity, Water
Resour. Res., 32, 2135–2145, 1996.
Atkinson, T. C.: Diffuse flow and conduit flow in limestone terrain in the
Mendip Hills, Somerset (Great Britain), J. Hydrol., 35, 93–110, https://doi.org/10.1016/0022-1694(77)90079-8,
1977.
Berry, R. A., Saurel, R., and Lemetayer, O.: The discrete equation method
(DEM) for fully compressible, two-phase flows in ducts of spatially varying
cross-section, Nucl. Eng. Design, 240, 3797–3818, 2010.
Beven, K., and Binley, A.: The future of distributed models: Model
calibration and uncertainty prediction, Hydrol. Process., 6, 279–298,
2006.
Birk, S., Geyer, T., Liedl, R., and Sauter, M.: Process-based interpretation
of tracer tests in carbonate aquifers, Ground Water, 43, 381–388, 2005.
Bittner, D., Parente, M. T., Mattis, S., Wohlmuth, B., and Chiogna, G.:
Identifying relevant hydrological and catchment properties in active
subspaces: An inference study of a lumped karst aquifer model, Adv.
Water Resour., 135, 550–560,
https://doi.org/10.1016/j.advwatres.2019.103472, 2020.
Blansett, K. L.: Flow, water quality, and SWMM model analysis for five urban
karst basins, PhD thesis, The Pennsylvania State University,
USA, https://www.doc88.com/p-0753138375298.html (last access: 29 March 2016), 2011.
Blansett, K. L. and Hamlett, J. M.: Challenges of Stormwater Modeling for
Urbanized Karst Basins. Pittsburgh, Pennsylvania, an ASABE Meeting
Presentation, Paper Number 1009274, https://doi.org/10.13031/2013.29840, 2010.
Bonacci, O., Ljubenkov, I., and Roje-Bonacci, T.: Karst flash floods: an example from the Dinaric karst (Croatia), Nat. Hazards Earth Syst. Sci., 6, 195–203, https://doi.org/10.5194/nhess-6-195-2006, 2006.
Chang, Y. and Liu, L.: A review of hydrological models in karst areas,
Engineering investigation, 43, 37–44, 2015.
Chang, Y., Hartmann, A., Liu, L., Jiang, G., and Wu, J.: Identifying more
realistic model structures by electrical conductivity observations of the
karst spring, Water Resour. Res., 57, e28587, https://doi.org/10.1029/2020WR028587, 2021.
Chen, Y.: Distributed Hydrological Models. Springer Berlin Heidelberg,
Berlin, Germany,
https://doi.org/10.1007/978-3-642-40457-3_23-1, 2018.
Chen, Y. B., Ren, Q. W., Huang, F. H., Xu, H. J., and Cluckie, I.: Liuxihe model and its modeling to river basin flood, J. Hydrol. Eng., 16, 33–50, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000286, 2010.
Chen, Y., Li, J., Wang, H., Qin, J., and Dong, L.: Large-watershed flood forecasting with high-resolution distributed hydrological model, Hydrol. Earth Syst. Sci., 21, 735–749, https://doi.org/10.5194/hess-21-735-2017, 2017.
Dewandel, B., Lachassagne, P., Bakalowicz, M., Weng, P., and Malki, A. A.:
Evaluation of aquifer thickness by analysing recession hydrographs.
Application to the Oman ophiolite hard-rock aquifer, J. Hydrol.,
274, 248–269, 2003.
Doummar, J., Sauter, M., and Geyer, T.: Simulation of flow processes in a
large scale karst system with an integrated catchment model (MIKE SHE) –
identification of relevant parameters influencing spring discharge, J. Hydrol., 426–427, 112–123, 2012.
Epting, J., Page, R. M., and Auckenthaler, A.: Process-based monitoring and
modeling of Karst springs – Linking intrinsic to specific vulnerability,
Sci. Total Environ., 625, 403–415, 2018.
Fleury, P., Plagnes, V., and Bakalowicz, M.: Modelling of the functioning of
karst aquifers with a reservoir model: Application to Fontaine de Vaucluse
(South of France), J. Hydrol., 345, 38–49,
https://doi.org/10.1016/j.jhydrol.2007.07.014, 2007b.
Gang, L., Tong, F. G., and Bin, T.: A Finite Element Model for Simulating
Surface Runoff and Unsaturated Seepage Flow in the Shallow Subsurface,
Hydrol. Process., 6, 102–120, https://doi.org/10.1002/hyp.13564, 2019.
Gautama, R. S., Notosiswoyo, S., Zen, M. T., and Kusumayudha, S. B.:
Mathematical model of fractal conduits flow mechanics in the gunungsewu
karst area, yogyakarta special region, indonesia, Int. J.
Hydrol. Sci. Technol., 1, 1, https://doi.org/10.1504/IJHST.2021.10035255, 2021.
Geyer, T., Birk, S., Liedl, R., and Sauter, M.: Quantification of temporal
distribution of recharge in karst systems from spring hydrographs, J. Hydrol., 348, 452–463, 2008.
Gou, P. F., Jiang, Y. J., Hu, Z. Y., Pu, J. B., and Yang, P. H.: A study of the
variations in hydrology and hydrochemistry under the condition of a storm in
a typical karst subterranean stream, Hydrogeol. Eng.
Geol., 37, 20–25, 2010.
Guila, J. F., Samper, J., Belén, B., Paloma, G., and Montenegro, L.:
Reactive transport model of gypsum karstification in physically and
chemically heterogeneous fractured media, Energies, 15, 1–29, 2022.
Gutierrez, F.: Hazards associated with karst, in:
Geomorphological Hazards and Disaster Prevention, edited by: Alcantara, I. and
Goudie, A., Cambridge University
Press,
Cambridge, 161–175, 2010.
Gutierrez, F., Parise, M., D' Waele, J., and Jourde, H.: A review on natural
and human-induced geohazards and impacts in karst, Earth Sci. Rev., 138, 61–88,
2014.
Hartmann, A.: Experiences in calibrating and evaluating lumped karst
hydrological models, Geological Society, London, Special Publications, 466, 331–340, https://doi.org/10.1144/sp466.18, 2018.
Hartmann, A. and Baker, A.: Progress in the hydrologic simulation of time
variant of karst systems-Exemplified at a karst spring in Southern Spain,
Adv. Water Resour., 54, 149–160, 2013.
Hartmann, A. and Baker, A.: Modelling karst vadose zone hydrology and its
relevance for paleoclimate reconstruction, Earth-Sci. Rev., 172,
178–192, 2017.
Hartmann, A., Goldscheider, N., Wagener, T., Lange, J., and Weiler, M.:
Karst water resources in a changing world: Review of hydrological modeling
approaches, Rev. Geophys., 52, 218–242, https://doi.org/10.1002/2013RG000443, 2014.
Jamal, M. S. and Awotunde, A. A.: Darcy model with optimized permeability
distribution (dmopd) approach for simulating two-phase flow in karst
reservoirs, J. Petrol. Explor. Prod. Technol., 12, 191–205, https://doi.org/10.1007/S13202-021-01385-X,
2022.
Jourde, H., Roesch, A., Guinot, V., and Bailly-Comte, V.: Dynamics and
contribution of
karst groundwater to surface flow during Mediterranean flood, Environ. Geol.
51,
725–730, 2007.
Jourde, H., Lafare, A., Mazzilli, N., Belaud, G., Neppel, L., Doerfliger,
N., and Cernesson, F.: Flash flood mitigation as a positive consequence of
anthropogenic forcings on the
groundwater resource in a karst catchment, Environ. Earth Sci., 71,
573–583, 2014.
Jukić, D. and Denić-Jukić, V.: Groundwater balance estimation
in karst by using a conceptual rainfall–runoff model, J. Hydrol.,
373, 302–315, https://doi.org/10.1016/j.jhydrol.2009.04.035, 2009.
Kong, F. Z. and Rui, X. F.: Hydrological similarity of catchments based on
topography, Geogr. Res., 6, 709–715, 2003.
Kovács, A. and Perrochet, P.: A quantitative approach to spring
hydrograph decomposition, J. Hydrol., 352, 16–29,
https://doi.org/10.1016/j.jhydrol.2007.12.009, 2008.
Kovács, A. and Sauter, M.: Modelling karst hydrodynamics, Frontiers of Karst Research, 26, 13–26, 2008.
Kraller, G., Warscher, M., Strasser, U., Kunstmann, H., and Franz, H.:
Distributed hydrological modeling and model adaption in high alpine karst at
regional scale (berchtesgaden alps, germany), Springer International
Publishing Switzerland,
https://doi.org/10.1007/978-3-319-06139-9_8, 2014.
Krzysztofowicz, R.: Probabilistic flood forecast: Exact and approximate
predictive distributions, J. Hydrol., 517, 643–651, 2014.
Krzysztofowicz, R. and Kelly, K.: Hydrologic uncertainty processor for
probabilistic river stage forecasting, Water Resour. Res.,
36, 3265–3277, 2000.
Kurtulus, B. and Razack, M.: Evaluation of the ability of an artificial
neural network model to simulate the input-output responses of a large
karstic aquifer: the la rochefoucauld aquifer (charente, france),
Hydrogeol. J., 15, 241–254, 2007.
Ladouche, B., Marechal, J. C., and Dorfliger, N.: Semi-distributed lumped
model of a karst system under active management, J. Hydrol.,
509, 215–230, 2014.
Li, J.: QMG model-V1.0, Zenodo, https://doi.org/10.5281/zenodo.4964701, 2021a.
Li, J.: dotNetFx40_Full_x86_x64, Zenodo, https://doi.org/10.5281/zenodo.4964697, 2021b.
Li, J.: User guide for QMG model-VI.0, Zenodo, https://doi.org/10.5281/zenodo.4964754, 2021c.
Li, J.: QMG model-V1.0 code (v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.4964709, 2021d.
Li, J.: Simulated data and modelling data package includes the DEM data, land use type and soil type data, Zenodo [data set], https://doi.org/10.5281/zenodo.4964727, 2021e.
Li, J., Yuan, D., Liu, J., Jiang, Y., Chen, Y., Hsu, K. L., and Sorooshian, S.: Predicting floods in a large karst river basin by coupling PERSIANN-CCS QPEs with a physically based distributed hydrological model, Hydrol. Earth Syst. Sci., 23, 1505–1532, https://doi.org/10.5194/hess-23-1505-2019, 2019.
Li, J., Hong, A., Yuan, D., Jiang, Y., Deng, S., Cao, C., and Liu, J.: A new
distributed karst-tunnel hydrological model and tunnel hydrological effect
simulations, J. Hydrol., 593, 125639,
https://doi.org/10.1016/j.jhydrol.2020.125639, 2020.
Li, J., Hong, A., Yuan, D., Jiang, Y., Zhang, Y., Deng, S., Cao, C., Liu, J.,
and Chen, Y.: Elaborate Simulations and Forecasting of the Effects of
Urbanization on Karst Flood Events Using the Improved Karst-Liuxihe
Model, CATENA, 197, 104990, https://doi.org/10.1016/j.catena.2020.104990, 2021.
Liedl, R., Sauter, M., Huckinghaus, D., Clemens, T., and Teutsch, G.:
Simulation of the development of karst aquifers using a coupled continuum
pipe flow model, Water Resour. Res., 39, 50–57, 2003.
Liu, X., Jiang, Y. J., Ye, M. Y., Yang, P. H., Hu, Z. Y., and Li, Y. Q.: Study on
hydrologic regime of underground river in typical karst valley – A case study
on the Qingmuguan subterranean stream in Chongqing, Carsologica Sinica,
28, 149–154, 2009.
Lu, D. B., Shi, Z. T., Gu, S. X., and Zeng, J. J.: Application of
Hydrological Model in the Karst Area, Water-saving irrigation, 11, 31–34,
2013.
Martinotti, M. E., Pisano, L., Marchesini, I., Rossi, M., Peruccacci, S., Brunetti, M. T., Melillo, M., Amoruso, G., Loiacono, P., Vennari, C., Vessia, G., Trabace, M., Parise, M., and Guzzetti, F.: Landslides, floods and sinkholes in a karst environment: the 1–6 September 2014 Gargano event, southern Italy, Nat. Hazards Earth Syst. Sci., 17, 467–480, https://doi.org/10.5194/nhess-17-467-2017, 2017.
Masciopinto, C., Passarella, G., Caputo, M. C., Masciale, R., and Carlo, L. D.:
Hydrogeological models of water flow and pollutant transport in karstic and
fractured reservoirs, Water Resour. Res., 57, https://doi.org/10.1029/2021WR029969, 2021.
Meng, H. H. and Wang, N. C.: Advances in the study of hydrological models in
karst basin, Prog. Geogr., 29, 1311–1318, 2010.
Meng, H. H., Wang, N. C., Su, W. C., and Huo, Y.: Modeling and application of
karst semi-distributed hydrological model based on sinkholes, Scientia
Geographica Sinica, 5, 550–554, https://doi.org/10.3969/j.issn.1000-0690.2009.04.014, 2009.
Pan, H. Y.: Hydrological model and application in karst watersheds, China
University of Geosciences, PhD thesis, Wuhan, China, 2014.
Parise, M.: Hazards in karst, Proceedings Int. Conf. “Sustainability of the
karst environment. Dinaric karst and other karst regions”, IHP-Unesco,
Series on Groundwater, 2, 155–162, 2010.
Peterson, E. W. and Wicks, C. M.: Assessing the importance of conduit
geometry and physical parameters in karst systems using the storm water
management model (SWMM), J. Hydrol., 329, 294–305, 2006.
Peterson, J. R. and Hamlett, J. M.: Hydrologic calibration of the SWAT model
in a basin containing fragipan soils, J. Am. Water
Resour. As., 34, tb00952.x, https://doi.org/10.1111/j.1752-1688.1998, 1998.
Petrie, R., Denvil, S., Ames, S., Levavasseur, G., Fiore, S., Allen, C., Antonio, F., Berger, K., Bretonnière, P.-A., Cinquini, L., Dart, E., Dwarakanath, P., Druken, K., Evans, B., Franchistéguy, L., Gardoll, S., Gerbier, E., Greenslade, M., Hassell, D., Iwi, A., Juckes, M., Kindermann, S., Lacinski, L., Mirto, M., Nasser, A. B., Nassisi, P., Nienhouse, E., Nikonov, S., Nuzzo, A., Richards, C., Ridzwan, S., Rixen, M., Serradell, K., Snow, K., Stephens, A., Stockhause, M., Vahlenkamp, H., and Wagner, R.: Coordinating an operational data distribution network for CMIP6 data, Geosci. Model Dev., 14, 629–644, https://doi.org/10.5194/gmd-14-629-2021, 2021.
Qin, J. G. and Jiang, Y.P.: A review of numerical simulation methods for CFP
pipeline flow, Groundwater, 3, 98–100, 2014.
Reimann, T. and Hill, M. E.: Modflow-cfp: a new conduit flow process
for modflow–2005, Ground Water, 47, 321–325,
https://doi.org/10.1111/j.1745-6584.2009.00561.x, 2009.
Shoemaker, W. B., Cunningham, K. J., and Kuniansky, E. L.: Effects of
turbulence on hydraulic heads and parameter sensitivities in preferential
groundwater flow layers, Water Resour. Res., 44, 34–50, https://doi.org/10.1029/2007WR006601, 2008.
Suo, L. T., Wan, J. W., and Lu, X. W.: Improvement and application of TOPMODEL
in karst region, Carsologica Sinica, 26, 67–70, 2007.
Teixeiraparente, M., Bittner, D., Mattis, S. A., Chiogna, G., and Wohlmuth,
B.: Bayesian calibration and sensitivity analysis for a karst aquifer model
using active subspaces, Water Resour. Res., 55, 342–356, https://doi.org/10.1029/2019WR024739, 2019.
White, W. B.: Karst hydrology: recent developments and open questions, Eng.
Geol., 65, 85–105, 2002.
Williams, P. W.: The role of the epikarst in karst and cave hydrogeology: a
review, Int. J. Speleol., 37, 1–10, 2008.
Williams, P. W.: Book Review: Methods in Karst Hydrogeology,
Goldscheider, N. and Drew, D., Hydrogeol. J., 17, 1025–1025, 2009.
Yang, P. H., Luo, J. Y., Peng, W., Xia, K. S., and Lin, Y. S.: Application of
online technique in tracer test-A case in Qingmuguan subterranean river
system, Chongqing, China, Carsologica Sinica, 27, 215–220, 2008.
Yu, D., Yin, J., Wilby, R. L., Stuart, N. L., Jeroen, C., Lin, N., Liu, M.,
Yuan, H., Chen, J., Christel, P., Guan, M., Avinoam, B., Charlie, W. D.,
Tang, X., Yu, L., and Xu, S.: Disruption of emergency response to vulnerable
populations during floods, Nat. Sustain., 3, 728–736,
https://doi.org/10.1038/s41893-020-0516-7, 2020.
Yu, Q., Yang., P. H., Yu, Z. L., Chen, X. B., and Wu, H.: Dominant factors
controlling hydrochemical variationg of karst underground river in different
period, Qingmuguan, Chongqing, Carsologica Sinica, 35, 134–143, 2016.
Zhang, H.: Characterization of a multi-layer karst aquifer through analysis
of tidal fluctuation, J. Hydrol., 601, 126677, https://doi.org/10.1016/j.jhydrol.2021.126677, 2021.
Zhang, Q.: Assesment on the intrinsic vulnerability of karst groundwater
source in the Qingmuguan karst valley, Carsologica Sinica, 31, 67–73,
2012.
Zhu, C. and Li, Y.: Long-Term Hydrological Impacts of Land Use/Land
Cover Change From 1984 to 2010 in the Little River Basin, Tennessee,
International Soil and Water Conservation Research, 2, 11–21, 2014.
Short summary
A new karst hydrological model (the QMG model) is developed to simulate and predict the floods in karst trough valley basins. Unlike the complex structure and parameters of current karst groundwater models, this model has a simple double-layered structure with few parameters and decreases the demand for modeling data in karst areas. The flood simulation results based on the QMG model of the Qingmuguan karst trough valley basin are satisfactory, indicating the suitability of the model simulation.
A new karst hydrological model (the QMG model) is developed to simulate and predict the floods...
