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
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
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
Jeonghyeon Choi, Ungtae Kim, Sangdan Kim
Summary: This study investigated the applicability of Satellite-Remote Sensed Data (SRSD) as a source for model calibration in ungauged basins. The results showed that the model calibrated with leaf area index (LAI) had the most robust performance in predicting streamflow. The findings suggest that SRSD can be a valuable tool for water resource planning and management in basins with limited or no observed data.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
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
Plant Sciences
Junyi Liu, Xianpeng Hou, Shuaiming Chen, Yanhua Mu, Hai Huang, Hengbin Wang, Zhe Liu, Shaoming Li, Xiaodong Zhang, Yuanyuan Zhao, Jianxi Huang
Summary: This study demonstrates the successful application of a crop model and remote sensing data assimilation method for growth monitoring and yield estimation of maize inbred lines.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Environmental Sciences
Jeonghyeon Choi, Jeongeun Won, Okjeong Lee, Sangdan Kim
Summary: This study explores the potential of using global root zone soil moisture based on satellite observation to calibrate hydrological models for predicting stream flow in ungauged basins. The results show that this approach is promising as it provides impressive predictive performance, particularly in dry years, and significantly improves the model's performance under low flow conditions compared to traditional regionalization methods. The uncertainty of the model calibrated using soil moisture data is similar to that using observed stream flow data, indicating more robust outputs, and overall stream flow predictions are also better.
Article
Environmental Sciences
Wade T. Crow, Jianzhi Dong, Rolf H. Reichle
Summary: This study demonstrates the importance of the rank correlation between surface soil moisture and storm-scale runoff in calibrating streamflow estimates in ungauged basins. A new calibration approach based on L4_SM has been successfully developed to identify LSM configurations with high rank correlation with observed runoff coefficients.
WATER RESOURCES RESEARCH
(2022)
Article
Meteorology & Atmospheric Sciences
Zdenko Heyvaert, Samuel Scherrer, Michel Bechtold, Alexander Gruber, Wouter Dorigo, Sujay Kumar, Gabrielle De Lannoy
Summary: In this study, the combination of active-passive ESA Climate Change Initiative soil moisture product with the Noah-MP land surface model is evaluated over Europe. The impact of different design choices on the performance of the data assimilation system is explored. The choice of observation errors, observation bias correction method, and atmospheric reanalysis dataset all affect the skill improvements.
JOURNAL OF HYDROMETEOROLOGY
(2023)
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
Chen Zhang, Siyu Cai, Juxiu Tong, Weihong Liao, Pingping Zhang
Summary: This study focused on flood monitoring and forecasting in the Chaohe River Basin, utilizing data assimilation to improve the accuracy of runoff predictions by merging satellite-based soil moisture data and runoff data.
Article
Environmental Sciences
Zhenzhou Ding, Haishen Lu, Naveed Ahmed, Yonghua Zhu, Qiqi Gou, Xiaoyi Wang, En Liu, Haiting Xu, Ying Pan, Mingyue Sun
Summary: This study assimilates soil moisture data from the China Land Data Assimilation System (CLDAS) into the MISDc hydrological model using the ensemble Kalman filter. The results show that the assimilation improves the simulation ability of the model, especially for high flows, but deteriorates the simulation for low flows. Overall, data assimilation has a positive impact on the runoff simulation ability of the model.
Article
Engineering, Electrical & Electronic
Jiaxin Tian, Hui Lu, Kun Yang, Jun Qin, Long Zhao, Yaozhi Jiang, Pengfei Shi, Xiaogang Ma, Jianhong Zhou
Summary: Soil moisture plays a vital role in the global terrestrial water, energy, and carbon cycles. This article develops a novel land surface temperature assimilation scheme, which improves soil moisture estimation accuracy by linking simulated ensembles of soil moisture with remote sensing land surface temperature.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
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
D. De Santis, D. Biondi, W. T. Crow, S. Camici, S. Modanesi, L. Brocca, C. Massari
Summary: This study conducted a data assimilation experiment on a large number of European catchments to assess the impact of satellite soil moisture assimilation on streamflow simulations. The results showed that the assimilation of satellite data provided limited improvements, with greater enhancements observed in catchments with poor model performance and inaccurate precipitation estimates. Factors such as the accuracy of remote sensing products and structural limitations in hydrological models were found to be significant drivers of assimilation efficiency.
WATER RESOURCES RESEARCH
(2021)
Article
Environmental Sciences
Kai Wu, Dongryeol Ryu, Wolfgang Wagner, Zhongmin Hu
Summary: This study aims to advance the use of Triple Collocation Analysis (TCA) for characterizing errors in remotely sensed soil moisture data, particularly focusing on the impact of rescaling techniques and the validation of TCA-based time-variant errors. The findings suggest that different selection of rescaling techniques significantly affects the accuracy of TCA error estimates. The optimal combination strategy is to apply TCA to soil moisture anomalies and rescale errors using coefficients derived from the TCA model. The study highlights the importance of accurate characterization of errors for hydrometeorological applications.
REMOTE SENSING OF ENVIRONMENT
(2023)
Editorial Material
Environmental Sciences
Timothy Dube, Munyaradzi D. D. Shekede, Christian Massari
Summary: In line with UN SDG 6, this special issue aimed to gather articles from scientists around the world on the use of remote sensing technologies to assess and monitor freshwater resources and ensure water security. The issue attracted 13 peer-reviewed articles, with most of them coming from China. Satellite datasets, ranging from coarse to medium spatial resolution, were used in the studies, along with big data processing techniques. The special issue highlighted knowledge gaps in big data image processing techniques and computing processes for water resource assessment and monitoring.
Article
Environmental Sciences
Mohammad Reza Eini, Christian Massari, Mikolaj Piniewski
Summary: Satellite-based observations of soil moisture, leaf area index, precipitation, and evapotranspiration are used in agrohydrological modeling. This study utilized the Climate Change Initiative Soil Moisture dataset adjusted based on Soil Water Index for agro-hydrological modeling in a transboundary river basin. The results showed that incorporating satellite-based soil moisture in the calibration process improved the accuracy and consistency of agro-hydrological modeling.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Environmental Sciences
Mark Edwin Tupas, Florian Roth, Bernhard Bauer-Marschallinger, Wolfgang Wagner
Summary: With the help of Sentinel-1 mission, the study compared four change detection models and found that the Bayes change detection model performed the best in terms of mapping accuracy due to its scalable classification rules and least sensitivity to parameter choices.
Review
Environmental Sciences
Sonali McDermid, Mallika Nocco, Patricia Lawston-Parker, Jessica Keune, Yadu Pokhrel, Meha Jain, Jonas Jaegermeyr, Luca Brocca, Christian Massari, Andrew D. Jones, Pouya Vahmani, Wim Thiery, Yi Yao, Andrew Bell, Liang Chen, Wouter Dorigo, Naota Hanasaki, Scott Jasechko, Min-Hui Lo, Rezaul Mahmood, Vimal Mishra, Nathaniel D. Mueller, Dev Niyogi, Sam S. Rabin, Lindsey Sloat, Yoshihide Wada, Luca Zappa, Fei Chen, Benjamin I. Cook, Hyungjun Kim, Danica Lombardozzi, Jan Polcher, Dongryeol Ryu, Joe Santanello, Yusuke Satoh, Sonia Seneviratne, Deepti Singh, Tokuta Yokohata
Summary: Irrigation accounts for a large majority of global freshwater withdrawals and consumptive water use, causing significant impacts on the Earth system. This Review provides a summary of how irrigation currently affects key components of the Earth system. It is estimated that over 3.6 million km(2) of land is currently being irrigated, with hot spots in the US High Plains, California Central Valley, Indo-Gangetic Basin, and northern China. Process-based models estimate that around 2,700 +/- 540 km(3) of irrigation water is withdrawn globally each year, and this is broadly consistent with reported values from countries, despite uncertainties.
NATURE REVIEWS EARTH & ENVIRONMENT
(2023)
Article
Engineering, Civil
Christian Massari, Victor Pellet, Yves Tramblay, Wade T. Crow, Gaby J. Grundemann, Tristian Hascoetf, Daniele Penna, Sara Modanesi, Luca Brocca, Stefania Camici, Francesco Marra
Summary: This study investigates the control of pre-storm conditions on runoff coefficients in European basins. The results indicate that precipitation has a relatively good explanatory power for stormflow volumes, but not for peak discharge. The correlation between pre-storm conditions and runoff coefficients varies among different basin types, which is crucial for flood forecasting and model calibration.
JOURNAL OF HYDROLOGY
(2023)
Article
Chemistry, Analytical
Claudio Navacchi, Senmao Cao, Bernhard Bauer-Marschallinger, Paul Snoeij, David Small, Wolfgang Wagner
Summary: Radiometric Terrain Corrected (RTC) gamma nought backscatter has become the standard for analysis-ready SAR data. However, processing large SAR datasets requires substantial computing resources.
Correction
Environmental Sciences
Sonali McDermid, Mallika Nocco, Patricia Lawston-Parker, Jessica Keune, Yadu Pokhrel, Meha Jain, Jonas Jagermeyr, Luca Brocca, Christian Massari, Andrew D. Jones, Pouya Vahmani, Wim Thiery, Yi Yao, Andrew Bell, Liang Chen, Wouter Dorigo, Naota Hanasaki, Scott Jasechko, Min-Hui Lo, Rezaul Mahmood, Vimal Mishra, Nathaniel D. Mueller, Dev Niyogi, Sam S. Rabin, Lindsey Sloat, Yoshihide Wada, Luca Zappa, Fei Chen, Benjamin I. Cook, Hyungjun Kim, Danica Lombardozzi, Jan Polcher, Dongryeol Ryu, Joe Santanello, Yusuke Satoh, Sonia Seneviratne, Deepti Singh, Tokuta Yokohata
NATURE REVIEWS EARTH & ENVIRONMENT
(2023)
Article
Geosciences, Multidisciplinary
Jacopo Dari, Luca Brocca, Sara Modanesi, Christian Massari, Angelica Tarpanelli, Silvia Barbetta, Raphael Quast, Mariette Vreugdenhil, Vahid Freeman, Anais Barella-Ortiz, Pere Quintana-Segui, David Bretreger, Espen Volden
Summary: Irrigation water use is a major source of freshwater consumption by humans. This study presents the first regional-scale and high-resolution irrigation water datasets obtained from satellite observations, providing detailed information on irrigation dynamics. The results demonstrate satisfactory performance of the satellite-derived irrigation products in most areas.
EARTH SYSTEM SCIENCE DATA
(2023)
Article
Environmental Sciences
Hyunglok Kim, Wade Crow, Xiaojun Li, Wolfgang Wagner, Sebastian Hahn, Venkataraman Lakshmi
Summary: This article discusses the importance of quantifying the accuracy of satellite-based soil moisture data and the limitations of existing statistical methods. It then fills the spatial gaps in TCA results using machine learning and provides spatially complete error maps for satellite-based soil moisture data products. Additionally, SHAP values are used to examine the impact of various environmental conditions on the quality of satellite-based soil moisture retrievals.
REMOTE SENSING OF ENVIRONMENT
(2023)
Proceedings Paper
Automation & Control Systems
Domenico De Santis, Concetta D'Amato, Paulina Bartkowiak, Shima Azimi, Mariapina Castelli, Riccardo Rigon, Christian Massari
Summary: This study evaluates several remotely-sensed ET datasets and finds that some of them demonstrate remarkable ability and potential to describe evapotranspiration. Despite differences in spatial scales, the remotely-sensed data generally agree with the measured fluxes.
2022 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR AGRICULTURE AND FORESTRY (METROAGRIFOR)
(2022)
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)
