Article
Engineering, Civil
Karen Gabriels, Patrick Willems, Jos Van Orshoven
Summary: A computationally efficient, raster-based and spatially-explicit RR-model was conceptualized to address the limitations of spatially distributed hydrological models for iterative spatial optimization analyses. Through implementation of AMC correction and re-infiltration, several model configurations achieved adequate performances for such analyses, with the most effective configuration showing promising results in three catchments.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
Moritz Feigl, Stephan Thober, Robert Schweppe, Mathew Herrnegger, Luis Samaniego, Karsten Schulz
Summary: Parameter estimation is a challenging task in large-scale distributed modeling. This study presents the first large-scale application of automatic parameter transfer function (TF) estimation for a complex hydrological model. By relating model parameters to catchment/landscape characteristics, it reduces the number of parameters and enables the transfer of hydrological model parameters in time and space. The results show that using automatic TF estimation can achieve high performance in ungauged basins.
WATER RESOURCES RESEARCH
(2022)
Article
Engineering, Civil
Chulsang Yoo, Eunsaem Cho, Wooyoung Na, Minseok Kang, Munseok Lee
Summary: This study proposes a method to consider high-rise buildings in rainfall-runoff analysis of urban basins. The research uses a model based on shot noise process to evaluate the roles of building rooftops and walls in runoff. Results show that building walls contribute significantly to increased runoff volume and peak flow compared to rooftops. Experimental and simulation results demonstrate the importance of building walls, especially in high wind speed conditions.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Civil
Han Yang, Lihua Xiong, Dedi Liu, Lei Cheng, Jie Chen
Summary: This study assimilated multiple remote-sensed PSM data into a high spatial resolution distributed hydrological model, generating high-resolution PSM estimations which were found to be more accurate than both the original remote-sensed PSM data and the model-simulated PSM. The assimilation of the SMAP PSM dataset into the model showed potential for improving streamflow simulations for the studied catchments.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
Vimal Chandra Sharma, Satish Kumar Regonda
Summary: The study discusses the importance of selecting an appropriate model spatial resolution in rainfall-runoff modeling for streamflow estimation, comparing the advantages and limitations of lumped modeling, distributed modeling, and semi-distributed modeling, with a focus on streamflow estimation at customized locations within river basins.
Article
Environmental Sciences
Sotirios Moustakas, Patrick Willems
Summary: There are various hydrological models available, with many using physically based formulations that require a substantial amount of spatial data. A new top-down approach for distributed rainfall-runoff modelling has been developed to combine accuracy and simplicity by deriving a distributed model with uniform parameters from a calibrated lumped conceptual model. The approach has shown improved performance in capturing internal catchment dynamics compared to the base model, although further improvements are needed for reliable results.
Article
Geosciences, Multidisciplinary
Yang Wang, Hassan A. Karimi
Summary: Rainfall-runoff modeling is an important tool for flood forecast and water management. This study compared the performance of LSTM models with different look-back windows and found that rainfall data with spatial information improves the performance of the models. Additionally, using spatially distributed rainfall data can reduce the difference between regional and individual LSTM models.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Green & Sustainable Science & Technology
Yan Zhou, Zhongmin Liang, Binquan Li, Yixin Huang, Kai Wang, Yiming Hu
Summary: This study introduces a new statistical rainfall-runoff model (SRR) that combines exponential difference distribution (EDD) and stochastic differential equation to deal with rainfall spatial variability and flow routing. The results suggest that the SRR model outperforms traditional models in describing rainfall spatial variability and simulation accuracy.
Article
Computer Science, Interdisciplinary Applications
Andreas Buttinger-Kreuzhuber, Artem Konev, Zsolt Horvath, Daniel Cornel, Ingo Schwerdorf, Guenter Bloeschl, Juergen Waser
Summary: This paper presents an integrated modeling framework for accurate predictions of flood hazard from heavy rainfalls. By integrating complementary models and utilizing GPU acceleration, the accuracy and simulation time of the model are improved. The framework is validated and tested in various scenarios, showing significant acceleration and the ability to simulate a large urban area in real-time.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Engineering, Civil
Shilei Chen, Lihua Xiong, Ling Zeng, Jong-Suk Kim, Quan Zhang, Cong Jiang
Summary: Runoff movement in karst catchments is complex, and distributed models are crucial for accurate simulation. Models considering karst landform and topographic index show improved accuracy in rainfall-runoff simulation in large-scale karst catchments.
JOURNAL OF HYDROLOGY
(2022)
Article
Geosciences, Multidisciplinary
Jerom P. M. Aerts, Rolf W. Hut, Nick C. van de Giesen, Niels Drost, Willem J. van Verseveld, Albrecht H. Weerts, Pieter Hazenberg
Summary: This study investigates the spatial scaling in distributed hydrological modelling and evaluates the streamflow estimates at different spatial resolutions. The results show that finer spatial resolution does not necessarily improve the accuracy of streamflow estimates. Although there are statistical differences among the three model instances, the conclusion is inconclusive due to high uncertainties in the sampling. The results also indicate significant differences between model instances, providing research directions for studying the changes in flux and state partitioning in hyper-resolution hydrological modelling.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Engineering, Civil
Afshin Jahanshahi, Lieke A. Melsen, Sopan D. Patil, Erfan Goharian
Summary: The study found that transferring parameters using the temporal mode yields the best results in simulating streamflow in ungauged catchments, with model performance in arid regions being inferior to humid regions. Parameter uncertainties are associated with all parameters, with model transferability being controlled by aridity and catchment elevation.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
Tianfang Xu, Qianqiu Longyang, Conor Tyson, Ruijie Zeng, Bethany T. Neilson
Summary: This study presents a hybrid modeling approach that combines a physically based snow model with a deep learning karst model to predict streamflow in mountainous karst watersheds. The approach is tested on a watershed in northern Utah and shows high accuracy in simulating streamflow. The deep learning model captures the spatiotemporal recharge and discharge patterns and provides valuable insights into hydrologic responses influenced by complex surface and subsurface properties.
WATER RESOURCES RESEARCH
(2022)
Article
Engineering, Civil
Andrew Watson, Sven Kralisch, Jared van Rooyen, Jodie Miller
Summary: In rural settings, groundwater is often the most utilised freshwater resource and river seepage plays an important role in recharging alluvial groundwater systems. A study developed a river seepage component for a rainfall/runoff model, which showed that by accounting for seepage, observed low flows were well simulated. However, uncertainties in precipitation data and quality, as well as changes in station density, impacted the simulation results.
JOURNAL OF HYDROLOGY
(2021)
Article
Geography, Physical
Simon J. Walker, Albert I. J. M. van Dijk, Scott N. Wilkinson, Peter B. Hairsine
Summary: This study evaluated the variability of gully head drainage area estimates using different methods and found that estimates were more variable in divergent flow conditions. It was concluded that a finer resolution DEM and a multiple-direction flow routing algorithm achieve the most realistic drainage area estimates in low-relief landscapes. The study also indicated the impact of different hydrologic enforcement methods on threshold analysis.
EARTH SURFACE PROCESSES AND LANDFORMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Tomohiro Tanaka, Yasuto Tachikawa, Yutaka Ichikawa, Kazuaki Yorozu
ENVIRONMENTAL MODELLING & SOFTWARE
(2019)
Article
Meteorology & Atmospheric Sciences
Patinya Hanittinan, Yasuto Tachikawa, Teerawat Ram-Indra
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2020)
Article
Engineering, Civil
Tomohiro Tanaka, Keiko Kiyohara, Yasuto Tachikawa
JOURNAL OF HYDROLOGY
(2020)
Article
Environmental Sciences
Y. K. Kim, S. M. Kim, Y. Tachikawa
WATER RESOURCES RESEARCH
(2020)
Article
Environmental Sciences
Bing-Chen Jhong, Yasuto Tachikawa, Tomohiro Tanaka, Parmeshwar Udmale, Ching-Pin Tung
Article
Environmental Sciences
Tomohiro Tanaka, Keita Kobayashi, Yasuto Tachikawa
Summary: This study used big data of annual maximum hourly flow from a large climate simulation database to investigate flood risk among all the 109 class-A river basins in Japan, predicting an increase in simultaneous flood risk in the future climate. The research concluded that the combination of large ensemble climate simulation data with informatics technology is a powerful approach for simultaneous flood risk analysis.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
Article
Meteorology & Atmospheric Sciences
Nobuhito Mori, Tetsuya Takemi, Yasuto Tachikawa, Hirokazu Tatano, Tomoya Shimura, Tomohiro Tanaka, Toshimi Fujimi, Yukari Osakada, Adrean Webb, Eiichi Nakakita
Summary: Climate change driven by global warming is expected to have significant impacts on natural disasters in East Asia. Numerical simulation of climate phenomena and weather hazards on local scales is important for assessing the future impacts of climate change on regional natural hazards.
WEATHER AND CLIMATE EXTREMES
(2021)
Article
Water Resources
Thatkiat Meema, Yasuto Tachikawa, Yutaka Ichikawa, Kazuaki Yorozu
Summary: This study assesses the sensitivity of Nam Ngum 1 reservoir operation to water resource uncertainty driven by climate change and upstream cascade dam development. Results show that these factors will impact the inflow and energy production of the reservoir. The study suggests that hydropower operation should be adapted to the effects of climate change.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2021)
Article
Water Resources
Thatkiat Meema, Yasuto Tachikawa, Yutaka Ichikawa, Kazuaki Yorozu
Summary: This study focused on forecasting river flows and optimizing dam release in the Nan River Basin in Thailand using a distributed hydrological model with ensemble weather forecasting. The research found that utilizing ensemble forecasts with dynamic programming led to more efficient real-time reservoir optimization compared to using historical data. The results provide valuable insights for water resource management in the region and can potentially be applied to other basins as well.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2021)
Article
Water Resources
Yutaka Ichikawa, Hyunuk An, Yasuto Tachikawa
Summary: This study proposed a method to examine the capability of physically-based rainfall-runoff models to simulate hillslope water dynamics using a depth-discharge constitutive equation. Results showed that the targeted constitutive equation could represent depth-discharge relationship on hillslopes and had potential in determining parameters from the internal structure of hillslope water dynamics.
HYDROLOGICAL RESEARCH LETTERS
(2021)
Article
Water Resources
Thatkiat Meema, Yasuto Tachikawa
HYDROLOGICAL RESEARCH LETTERS
(2020)
Article
Water Resources
Luis Chero, Yasuto Tachikawa
HYDROLOGICAL RESEARCH LETTERS
(2020)
Article
Water Resources
Tomohiro Tanaka, Yasuto Tachikawa, Yutaka Ichikawa, Kazuaki Yorozu
HYDROLOGICAL RESEARCH LETTERS
(2018)
Article
Water Resources
Sunmin Kim, Yasuto Tachikawa, Eiichi Nakakita
HYDROLOGICAL RESEARCH LETTERS
(2017)
Article
Meteorology & Atmospheric Sciences
Ryo Mizuta, Akihiko Murata, Masayoshi Ishii, Hideo Shiogama, Kenshi Hibino, Nobuhito Mori, Osamu Arakawa, Yukiko Imada, Kohei Yoshida, Toshinori Aoyagi, Hiroaki Kawase, Masato Mori, Yasuko Okada, Tomoya Shimura, Toshiharu Nagatomo, Mikiko Ikeda, Hirokazu Endo, Masaya Nosaka, Miki Arai, Chiharu Takahashi, Kenji Tanaka, Tetsuya Takemi, Yasuto Tachikawa, Khujanazarov Temur, Youichi Kamae, Masahiro Watanabe, Hidetaka Sasaki, Akio Kitoh, Izuru Takayabu, Eiichi Nakakita, Masahide Kimoto
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
(2017)