Article
Engineering, Civil
Garett Pignotti, Melba Crawford, Eunjin Han, Mark R. Williams, Indrajeet Chaubey
Summary: In this study, the effects of data assimilation on water quality and crop yield predictions were evaluated using the Soil and Water Assessment Tool (SWAT). The results showed that data assimilation significantly impacted these predictions.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Ankita Pradhan, Akhilesh S. Nair, J. Indu, Olga Makarieva, Nataliia Nesterova
Summary: This study examines the potential for satellite soil moisture assimilation to enhance land surface model seasonal dynamics using blended soil moisture data from microwave satellites. The Ensemble Kalman Filter method is used to integrate soil moisture data across the Iya River Basin in Russia. The results show that assimilation can reduce the dry bias in Noah LSM, especially in the northern regions of the Iya Basin.
Article
Environmental Sciences
Mehrad Bayat, Hosein Alizadeh, Barat Mojaradi
Summary: This paper introduces the application of multivariate data assimilation (DA) to the SWAT model (DA-SWAT) and discusses the limitations of existing integrated approaches. A new approach is proposed that allows the perfect integration of SWAT with any desired DA algorithm. The results show that multivariate assimilation improves the accuracy of SCF (Streamflow) estimation and mitigates the equifinality problem.
WATER RESOURCES RESEARCH
(2022)
Article
Engineering, Civil
A. K. Nayak, B. Biswal, K. P. Sudheer
Summary: Soil moisture data assimilation (SMDA) has been widely used in hydrological research to enhance streamflow prediction. Different conceptual hydrological model structures have varying impacts on the SMDA process, with the GR4J model performing best and the DB model performing worst in this study. Improvements in model performance were observed for some basins, but deterioration was also noted for others during assimilation.
JOURNAL OF HYDROLOGY
(2021)
Article
Geosciences, Multidisciplinary
Keighobad Jafarzadegan, Peyman Abbaszadeh, Hamid Moradkhani
Summary: Real-time probabilistic flood inundation mapping is crucial for flood risk warning and decision-making, and traditional flood hazard maps cannot accurately represent the actual dynamics of flooding rivers. Introducing data assimilation techniques is an effective way to improve the accuracy and reliability of flood inundation mapping.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2021)
Article
Engineering, Electrical & Electronic
Rolf H. Reichle, Sara Q. Zhang, Qing Liu, Clara S. Draper, Jana Kolassa, Ricardo Todling
Summary: The assimilation of L-band brightness temperature from the SMAP mission in the GEOS weakly coupled land-atmosphere data assimilation system improved the correlation between surface and root-zone soil moisture, reduced the root-mean-square error of soil moisture, and lowered the RMSE of specific humidity and maximum temperature compared to ADAS estimates. The introduction of SMAP Tb analysis has a positive impact on the modeled land-atmosphere coupling.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Environmental Sciences
Ching Pui Hung, Bernd Schalge, Gabriele Baroni, Harry Vereecken, Harrie-Jan Hendricks Franssen
Summary: Integrated terrestrial system models predict the coupled water, energy and biogeochemical cycles. Data assimilation can reduce uncertainties by improving the representation of soil moisture, groundwater level, and other variables in the model. This study used a virtual reality simulation to mimic a river catchment in Germany and assimilated soil moisture and groundwater level data to improve the model's performance.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Khaled Mohammed, Robert Leconte, Melanie Trudel
Summary: Soil moisture modeling is important for various applications, and assimilating soil moisture observations can improve the model performance. This study examines the impact of spatial and temporal data gaps on soil moisture modeling and streamflow modeling. The results indicate that the absence of root-zone soil moisture estimates from satellite data has the greatest impact on modeling performance. Temporal and horizontal spatial gaps in satellite data also have an impact, but to a lesser extent. Real-data experiments using the SMAP product improve soil moisture modeling in the upper soil layers, but not as much in the bottom soil layer. Assimilating observations also improves streamflow modeling in synthetic experiments, but not in real-data experiments.
Article
Engineering, Civil
Yakun Wang, Liangsheng Shi, Tianfang Xu, Qiuru Zhang, Ming Ye, Yuanyuan Zha
Summary: This paper presents a nonparametric sequential data assimilation scheme, Kalman-GP, based on Gaussian process modeling and EnKF filtering equations, which effectively reconstructs soil moisture dynamics in the absence of a physical model. The Kalman-GP outperforms traditional EnKF with a physical model and exhibits a good tradeoff between effectiveness and efficiency, making it a promising alternative in areas with limited hydrogeological data.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Civil
Jun Qin, Jiaxin Tian, Kun Yang, Hui Lu, Xin Li, Ling Yao, Jiancheng Shi
Summary: Soil moisture plays a critical role in land surface energy and water cycles and is considered an essential climate variable. Microwave remote sensing offers the potential to estimate soil moisture in real-time on a large scale. In this study, a dual-cycle assimilation algorithm is proposed to correct bias in satellite soil moisture products. Numerical experiments show that the presented algorithm outperforms existing correction schemes.
JOURNAL OF HYDROLOGY
(2022)
Article
Meteorology & Atmospheric Sciences
Weijing Chen, Chunlin Huang, Zong-Liang Yang, Ying Zhang
Summary: This study establishes a multisource remote sensing data assimilation framework to improve the accuracy of soil moisture estimation over the Tibetan Plateau. The integration of multiple satellite data sources with a land surface model shows promising results in estimating soil moisture, especially in shallow soil layers. The assimilation experiments demonstrated advantages in improving soil moisture and temperature simulation compared to default parameters.
JOURNAL OF HYDROMETEOROLOGY
(2021)
Article
Engineering, Civil
Chengde Yang, Min Xu, Shichang Kang, Congsheng Fu, Didi Hu
Summary: This study proposes a hybrid modeling framework that combines the SWAT+ model considering glacial hydrological processes with Gated Recurrent Unit neural networks to simulate and forecast streamflow in glacial river basins. The results indicate that the hybrid model outperforms both the traditional hydrological model and the deep learning model in terms of simulation and prediction accuracy.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Chuxuan Li, Guo Yu, Jiali Wang, Daniel E. Horton
Summary: This study improves the representation of hydrologic processes in the Weather Research and Forecasting Hydrological modeling system (WRF-Hydro) by using soil parameter estimates from the Soil Survey Geographic (SSURGO) database and the probability mapping of SSURGO (POLARIS). The WRF-Hydro simulations with POLARIS-adjusted soil parameters show increased correlation coefficients (r), reduced biases, and increased Kling-Gupta Efficiencies (KGEs) for soil moisture at seven observing stations. The fidelity of WRF-Hydro streamflow also improves, with better capture of peak flow events, increased correlation coefficients (r) across nine stream gages, and an increase in mean KGE from 0.12 to 0.66 at seven out of nine gages. The pre-calibration parameter estimate approach used in this study can greatly enhance model performance and reduce calibration efforts and computational costs.
WATER RESOURCES RESEARCH
(2023)
Article
Meteorology & Atmospheric Sciences
Avinash N. Parde, Sachin D. Ghude, Ashish Sharma, Narendra G. Dhangar, Gaurav Govardhan, Sandeep Wagh, R. K. Jenamani, Prakash Pithani, Fei Chen, M. Rajeevan, Dev Niyogi
Summary: The present study emphasizes the role of high-resolution land data assimilation in improving the prediction of radiation fog and near-surface meteorological variables. The performance of the Weather Research and Forecasting (WRF) model coupled with the High-Resolution Land Data Assimilation System (HRLDAS) is evaluated for a dense fog event in Delhi, India. The study finds that the combination of HRLDAS and Pleim-Xiu land-surface parameterizations significantly improves the accuracy of predicting micro-meteorological variables and Turbulent Kinetic Energy (TKE) during the fog event.
ATMOSPHERIC RESEARCH
(2022)
Article
Water Resources
Jose Martinez-Fernandez, Eugenio Molina-Navarro, Angel Gonzalez-Zamora, Alejandro Sanchez-Gomez, Laura Almendra-Martin
Summary: This study assessed the SWAT soil moisture in the Henares River Basin under Mediterranean conditions for the first time. Modeling and remote sensing products were used as references, and the evaluation results showed satisfactory performances. The findings indicate that producing reliable SWAT soil moisture databases can increase the availability of suitable soil moisture series worldwide.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2023)
Article
Water Resources
Md Mominul Haque, Ousmane Seidou, Abdolmajid Mohammadian, Abdouramane Gado Djibo
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2020)
Article
Engineering, Environmental
S. Ansari, C. D. Rennie, S. P. Clark, O. Seidou
Summary: This study introduces a novel algorithm called IceMaskNet for automatic river ice detection and characterization from aerial imagery, which can classify river ice into six different classes with high accuracy. The algorithm has been tested on data collected from the Dauphin River in Manitoba, Canada, demonstrating promising results for potential applications in the field of ice processes research.
COLD REGIONS SCIENCE AND TECHNOLOGY
(2021)
Article
Geosciences, Multidisciplinary
Md Mominul Haque, Ousmane Seidou, Abdolmajid Mohammadian, B. A. Khalidou
Summary: The Inner Niger Delta is a complex hydraulic system where flood dynamics and water connectivity are crucial for ecosystem services and economic activities. Existing hydrodynamic models may have inaccuracies, so improving prediction methods is essential to enhance accuracy in simulating flood dynamics and connectivity.
JOURNAL OF AFRICAN EARTH SCIENCES
(2021)
Article
Engineering, Civil
Ousmane Seidou, Claudia Ringler, Spela Kalcic, Luca Ferrini, Traore Abdou Ramani, Abdou Guero
Summary: The countries sharing the Niger River face challenges of poor access to clean water, energy, and food security, with the Niger River Basin Authority aiming to advance progress in these areas while reducing environmental degradation. A mixed-methods approach was developed to engage basin countries in qualitatively ranking projects to meet various goals and prioritize activities for investors.
WATER INTERNATIONAL
(2021)
Article
Water Resources
M. Noteboom, O. Seidou, D. R. Lapen
Summary: The study showed that streamflow and sediment loads were not sensitive to forest loss, but continuing deforestation at the current rate would increase nitrate, total nitrogen, and total phosphorus loads by 2032. Reforestation scenarios were effective in reducing total nitrogen concentrations below water quality guidelines with the help of vegetated filter strips, but further improvements are needed to achieve water quality guidelines for total phosphorus concentrations.
WATER QUALITY RESEARCH JOURNAL
(2021)
Article
Engineering, Civil
A. Morabbi, A. Bouziane, O. Seidou, N. Habitou, D. Ouazar, T. B. M. J. Ouarda, C. Charron, M. D. Hasnaoui, M. Benrhanem, K. Sittichok
Summary: Hydrologic regionalization involves regrouping stations and catchments based on a similarity measure, to extract a robust signal for describing the hydrology of a region. However, existing methods often overlook the non-linear and non-stationary nature of hydrometeorological variables. This study introduces a novel similarity measure based on changepoint locations in hydrological time series, applied to the Tensift watershed in Morocco, with coherence of detected regions verified using wavelet coherence.
JOURNAL OF HYDROLOGY
(2022)
Article
Water Resources
Baba-Serges Zango, Ousmane Seidou, Majid Sartaj, Nader Nakhaei, Kelly Stiles
Summary: This study focused on the Carp river watershed in Ottawa, Ontario, and found that the impacts of climate change and urbanization on water quantity and quality vary greatly depending on spatial scale and geographic location. Globally, by 2050, average annual discharge is expected to increase between 6.75% and 9.34%, while changes in nitrogen and phosphorus loads will vary between -1.20% and 24.84%, and 19.15% and 23.81%, respectively.
JOURNAL OF WATER AND CLIMATE CHANGE
(2022)
Article
Environmental Sciences
Sara Karam, Ousmane Seidou, Nidhi Nagabhatla, Duminda Perera, Raphael M. Tshimanga
Summary: The Congo River Basin, the second-largest river basin in the world, is at risk of worsening extreme climatic events such as floods and droughts due to climate change. Future rainfall-induced flash floods and drought regimes in the basin are projected to increase or decrease in different regions.
Correction
Environmental Sciences
Sara Karam, Ousmane Seidou, Nidhi Nagabhatla, Duminda Perera, Raphael M. Tshimanga
Article
Environmental Sciences
Ketvara Sittichok, Jutithep Vongphet, Ousmane Seidou
Summary: Expected changes in temperature, rainfall, water yield, and surface runoff dynamics in the Phetchaburi River Basin, Thailand were estimated using outputs from five regional climate models under RCP 8.5. The models predicted higher temperatures in the future, with disagreements in projected precipitations for the short term but pointing to an overall increase in rainfall in the long term. Surface runoff/ water yield showed a significant increase in the long-term following the same trend as rainfall.
ASIAN JOURNAL OF WATER ENVIRONMENT AND POLLUTION
(2022)
Article
Engineering, Civil
Fahad Alzahrani, Ousmane Seidou, Abdullah Alodah
Summary: Climate change will impact hydrological variables worldwide, potentially leading to more extreme events and failures in hydraulic infrastructure. In urban infrastructure planning and management, it is important to account for changes in extreme sub-daily precipitation, specifically by developing intensity-duration-frequency (IDF) curves that accurately represent future climate conditions. The study critically assessed existing algorithms for developing IDF curves and proposed new and improved versions that provide better inputs for adaptation assessments.
WATER RESOURCES MANAGEMENT
(2022)
Article
Environmental Sciences
S. Ansari, C. D. Rennie, E. C. Jamieson, O. Seidou, S. P. Clark
Summary: Streamflow data plays a crucial role in hydrologic and hydraulic research, modeling, and design studies. The use of close range non-contact sensing techniques, such as image velocimetry, for streamflow measurement is a novel but not fully matured technique. This study introduces RivQNet, a novel and accurate river velocimetry scheme that utilizes artificial intelligence to process close-range non-contact water surface images. The presented method is validated and compared with conventional optical flow methodologies, showing accurate and dense spatial distributions of surface velocities.
WATER RESOURCES RESEARCH
(2023)
Article
Meteorology & Atmospheric Sciences
Taesam Lee, Taha B. M. J. Ouarda, Ousmane Seidou
Summary: The objective of this study is to compare techniques for forecasting low-frequency climate oscillation indices, with a focus on the Great Lakes system. Various time series models, including ARMA, DLM, GARCH, and NSOR, were tested for predicting the monthly ENSO and PDO indices, which have significant teleconnections with the NBS of the Great Lakes system. The aim is to forecast future water levels, ice extent, and temperature for planning and decision making. Results indicate that the DLM and GARCH models outperform others for forecasting the monthly ENSO index, while the traditional ARMA model shows good agreement with observed values for the monthly PDO index within a short lead time.
THEORETICAL AND APPLIED CLIMATOLOGY
(2023)
Article
Water Resources
Fahad Alzahrani, Ousmane Seidou, Abdullah Alodah
Summary: This paper proposes a simple steady-state stochastic disaggregation model that generates wet/dry day occurrence using a binomial distribution and precipitation intensity using an exponential distribution. Comparing with other temporal disaggregation methods, the proposed method performed well when resampling the observed extreme precipitation.
JOURNAL OF WATER AND CLIMATE CHANGE
(2023)
Article
Green & Sustainable Science & Technology
Sara Karam, Baba-Serges Zango, Ousmane Seidou, Duminda Perera, Nidhi Nagabhatla, Raphael M. Tshimanga
Summary: Surface water resources are crucial for human activities, but global warming is expected to affect their availability, quality, and distribution. Planning and adaptation to the potential impacts of climate change are important for communities.
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)
