Article
Geosciences, Multidisciplinary
Hetal P. Dabhi, Mathias W. Rotach, Michael Oberguggenberger
Summary: For climate change impact assessment, high-resolution and spatiotemporally consistent precipitation data are essential. This study proposes a stochastic weather generator that incorporates elevation dependence for a mountainous region. The model is able to generate realistic precipitation fields with good spatial and temporal variability. However, it underestimates inter-annual variability in autumn and winter.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2023)
Article
Meteorology & Atmospheric Sciences
Nasser Najibi, Sudarshana Mukhopadhyay, Scott Steinschneider
Summary: Weather regime based stochastic weather generators (WR-SWGs) are proposed as a tool to better understand vulnerability to climate change, distinguishing and simulating different types of climate change with varying degrees of uncertainty. A novel framework is proposed to identify representative WRs based on performance over a broad geographic area and applied to a case study in California. Findings suggest that a small number of WRs identified using Hidden Markov Models (HMMs) perform best, with agreement between the number of WRs selected based on performance and regimes identified using metastability analysis. Future research could explore expanding this framework for additional design parameters and spatial scales.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2021)
Article
Environmental Sciences
Antonio-Juan Collados-Lara, Eulogio Pardo-Iguzquiza, David Pulido-Velazquez
Summary: This study introduces a novel methodology to assess the impact of climate change on snow cover areas in alpine systems, focusing on the Sierra Nevada in southern Spain. The findings suggest significant reductions in snow cover area over the next few decades, with potential implications equivalent to a 400-meter elevation shift in snow distribution.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Engineering, Civil
Samaneh Sohrabi, Francois P. Brissette, Richard Arsenault
Summary: This study aims to improve long-term streamflow forecasts by conditioning parameters of a stochastic weather generator on large-scale climate indices. Results show significant correlation between temperatures and large-scale climate indices, while precipitation is weakly related. The length of the time window has a considerable impact on the prediction ability of linear models, with short duration windows performing better for precipitation models and longer windows for temperature models.
JOURNAL OF HYDROLOGY
(2021)
Article
Multidisciplinary Sciences
Stephen G. Hesterberg, Kendal Jackson, Susan S. Bell
Summary: This study finds that the transition from salt marsh to mangrove is linked to the transition from oyster reef to mangrove through the spread of mangrove propagules. The transition is influenced by climate change as well as other non-climate factors. If the supply of propagules keeps up with predicted warming, subtropical estuaries will begin to transform by 2070. Measures such as restoring oyster reefs or removing mangrove seedlings could help slow down the impacts of climate change.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Meteorology & Atmospheric Sciences
Xunchang (John) Zhang, Phillip R. R. Busteed, Jie Chen, Lifeng Yuan
Summary: This study compares two weather generator-based tools in simulating daily precipitation extremes and evaluates the response of surface runoff and soil loss to generated precipitation under different cropping and tillage systems. The results show that all data sources are capable of providing information on future storm intensification and it is recommended to use as many members as possible in model screening. There are no discernable differences between storm intensification options with each tool due to weaker signals of storm intensification projected for the study site. Simulated soil loss and surface runoff rates with one tool (GPCC) are significantly greater than those with the other tool (SYNTOR) due to the generation of more frequent and heavier storms by GPCC.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2023)
Article
Water Resources
Wenxian Guo, Huan Yang, Yinchu Ma, Fengtian Hong, Hongxiang Wang
Summary: This study focuses on the change in hydrothermal regime and its ecological response in the upper reach of the Yangtze River basin in China. A framework is proposed to quantify the impact of climate change and reservoirs on hydrothermal variability and fish reproduction. The results show that hydrothermal tends to be uniform after the mutation, with reservoirs playing a dominant role. Climate change is the main factor for river warming on an annual scale, while reservoirs act as heat sources in autumn and winter and as cold sources in other seasons. The reservoirs also significantly affect hydrothermal in the nonflood season, especially in March and December. They have delayed the spawning time for Coreius guichenoti and Myxocyprinus asiaticus but increased the duration of Myxocyprinus asiaticus.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2022)
Article
Engineering, Civil
Jose George, P. Athira
Summary: The study proposes a multi-stage statistical downscaling method for regional rainfall, combining the strengths of RVM models and weather generators. The methodology captures the occurrence and distribution characteristics of regional observed rainfall and its non-stationarity based on regional climatic phenomena.
WATER RESOURCES MANAGEMENT
(2023)
Article
Ecology
Adam Pepi, Marcel Holyoak, Richard Karban
Summary: The study reveals a regime shift from shorter to longer period oscillations in the dynamics of a moth species in California, along with changes in regional precipitation dynamics. Simulations support the hypothesis that shifting precipitation dynamics led to changes in moth dynamics, possibly due to stochastic resonance. The observed shift in climate dynamics and its interaction with endogenous dynamics highlight the challenge of predicting future population dynamics.
Article
Engineering, Civil
Qifen Yuan, Thordis L. Thorarinsdottir, Stein Beldring, Wai Kwok Wong, Chong-Yu Xu
Summary: Hydrological impact assessments are increasingly being conducted at fine spatial and temporal resolutions to better understand local-scale changes in a future climate. The internal variability of local climate can be a major source of uncertainty for hydrological projections, in addition to model and scenario uncertainties. This paper presents a methodology for assessing the local-scale internal variability in catchment-scale hydrological models, using stochastic weather generators and a statistical hypothesis test. The results show significant changes in runoff regimes and indicate that temperature and precipitation are the main sources of variability in different seasons.
JOURNAL OF HYDROLOGY
(2023)
Article
Meteorology & Atmospheric Sciences
Sarah Wilson Kemsley, Timothy J. Osborn, Stephen R. Dorling, Craig Wallace
Summary: By combining a stochastic precipitation generator with pattern scaling, the limitations of climate models can be overcome to study future climate and the risk of extreme weather events.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2023)
Article
Engineering, Civil
Yue Zhang, Ying Wang, Yu Chen, Yingjun Xu, Guoming Zhang, Qigen Lin, Rihong Luo
Summary: This study projected an increase in flash flood occurrence in the future for the Nanshan Scenic Zone in China, with all 13 selected global climate models showing a unanimous increase. The findings suggest that adaptation and risk reduction measures should be taken by flood managers and stakeholders in the NSZ, as the peak tourist season coincides with months seeing the largest increase in flash flood occurrence.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
Simon Michael Papalexiou, Francesco Serinaldi, Martyn P. Clark
Summary: This study proposes a methodological advancement in the CoSMoS framework for large-domain simulations. It demonstrates the feasibility of the proposed method by simulating 40 years of daily precipitation records from 1,000 gauging stations in the Mississippi River basin. Further improvements, such as incorporating non-Gaussian processes and using advection and nonstationary spatiotemporal correlation functions, are suggested.
WATER RESOURCES RESEARCH
(2023)
Article
Environmental Sciences
Sylvie Parey, Joel Gailhard
Summary: This paper proposes a simulation-based approach to estimate the impact of climate change on low flow situations. The approach generates a large sample of river flow time series using a bivariate generator of temperature and rainfall and analyzes the sample statistically. The method shows promising results in studying historical low flow situations and future climate projections, but further improvements are possible. The findings are important for understanding the impact of climate change on local low flow situations.
Article
Meteorology & Atmospheric Sciences
Bandar S. AlMutairi, Mitchell J. Small, Iris Grossmann
Summary: Improved seasonal precipitation forecasts can enable more effective water resource management decisions in various sectors. This study develops a statistical approach that utilizes Coupled General Climate Models (CGCMs) to enhance the quality of seasonal precipitation forecasts by incorporating El Nino-Southern Oscillation (ENSO) information. Results show the potential to narrow the uncertainty of seasonal precipitation forecasts by considering CGCMs ENSO cycle information, with greater predictability in the late part of the wet season.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2023)
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)