Article
Meteorology & Atmospheric Sciences
Di Ma, Budong Qian, Haiting Gu, Zhilin Sun, Yue-Ping Xu
Summary: Assessing climate change impacts on streamflow and sediment processes is crucial for sustainable watershed management. A study on the upstream Mekong River Basin showed temperature and precipitation increases, along with projected streamflow and sediment load changes, but with inconsistent sediment load predictions. The use of multi-model ensembles is highlighted for climate change impact studies.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2021)
Article
Environmental Sciences
Kun Xie, Hua Chen, Yunfeng Qiu, Jong-Suk Kim, Sun-Kwon Yoon, Yunfa Lin, Bingyi Liu, Jun Wang, Jie Chen, Shengwen Zhang
Summary: This study predicted and assessed the impacts of land-use change and climate change on streamflow, sediment, and total phosphorus loads using the SWAT model. Future land-use change had a negligible impact, while climate change was likely to amplify streamflow and sediment and reduce total phosphorus loads. The combined impact of land-use and climate change was greater than the sum of individual impacts, especially for total phosphorus loads.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2021)
Article
Environmental Sciences
Li-Chi Chiang, Ci-Jyun Liao, Chih-Mei Lu, Yung-Chieh Wang
Summary: Climate change contributes to more intense and frequent extreme rainfall events in Taiwan, leading to severe erosion and landslides on steep hillslopes. The modified SWAT-Twn model effectively simulated sediment transport in the Zhuoshui River basin, outperforming the official SWAT model in terms of sediment load simulations. The study also highlighted the importance of considering landslide area variations in sediment yield predictions for watershed management.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2021)
Article
Chemistry, Multidisciplinary
Nageswara Reddy Nagireddy, Venkata Reddy Keesara, Gundapuneni Venkata Rao, Venkataramana Sridhar, Raghavan Srinivasan
Summary: Climate change is having a significant impact on water quality and quantity in the Nagavali and Vamsadhara watersheds in India. Future climate projections indicate increased rainfall and soil erosion in these watersheds, which will negatively affect agricultural lands and reservoir capacity. It is therefore crucial to implement soil and water management practices to reduce sediment loadings and mitigate these negative impacts.
APPLIED SCIENCES-BASEL
(2023)
Article
Green & Sustainable Science & Technology
Changzheng Chen, Rong Gan, Dongmei Feng, Feng Yang, Qiting Zuo
Summary: Assessing the impacts of climate change on hydrologic systems is crucial for water resources management and ecological protection. This study develops a workflow that integrates different calculation methods and models to evaluate the uncertainties in future runoff projections. The results show potential increases in monthly and annual runoff, with evapotranspiration calculation methods and climate models being the main sources of uncertainty.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Water Resources
Sedighe Nikkhoo Amiri, Mojtaba Khoshravesh, Reza Norooz Valashedi
Summary: Climate change is a significant factor affecting water supply in semi-arid and arid areas such as Iran. This research investigates the impact of climate change and upstream land use on the Tajan River in northern Iran. The study shows that peak streamflow will increase by 4% and 5.7%, while average annual discharges will decrease by 16% and 16.5% from 2016 to 2066 under different climate scenarios. Furthermore, different land use change scenarios lead to an increase in average annual streamflow by 8.5-15.8%. It is concluded that downstream water users should implement strategies to cope with the changing climate and water scarcity.
APPLIED WATER SCIENCE
(2023)
Article
Environmental Sciences
Muhammad Touseef, Lihua Chen, Hang Chen, Hamza Farooq Gabriel, Wenzhe Yang, Ammara Mubeen
Summary: This study combines remote sensing and CMIP6 data with hydrological modeling to investigate the impact of climate change on hydrological parameters. Future changes in precipitation and streamflow were projected in the Hongshui River basin, and it was found that climate change contributes 11% to streamflow variability.
Article
Geosciences, Multidisciplinary
S. Sreedevi, T. I. Eldho, T. Jayasankar
Summary: This study evaluates the impacts of land use/land cover and climate change on hydrology and soil erosion processes in a humid tropical region in India. Using the SHETRAN model, the researchers compare past land use maps and climate data with future climate scenarios. The results show that land use, climate variability, and combined effects have different influences on streamflow and sediment load. The projections from a general circulation model indicate an increase in temperature, precipitation, streamflow, and sediment load in the future. The SHETRAN model proves to be effective in assessing the impact of climate change on hydrology and sediment yield, providing valuable insights for future river basin management.
Article
Engineering, Civil
Baoxu Zhao, Huimin Lei, Dawen Yang, Shuyu Yang, Jerasorn Santisirisomboon
Summary: This study investigates the hydrological effects of deforestation in the Upper Chao Phraya River basin, a tropical monsoon region in Thailand. The findings suggest that deforestation contributes to increased annual streamflow, baseflow, and sediment load. The impact of deforestation varies depending on the specific sub-basin and the type of hydrological change. Climate change and forest cover reduction both play a role in affecting the hydrological and sedimentary changes observed in the region.
JOURNAL OF HYDROLOGY
(2022)
Article
Green & Sustainable Science & Technology
Jimin Lee, Minji Park, Joong-Hyuk Min, Eun Hye Na
Summary: Changes in land use and climate can affect the surface runoff and baseflow of streamflow. This study aims to improve predictions of streamflow using the SWAT model by applying the alpha factor estimated using BFLOW for calibration, and to evaluate the impacts of land use and climate changes on streamflow and baseflow. The results show that the alpha factor estimated using BFLOW improves the prediction accuracy of streamflow and baseflow in the SWAT model. Additionally, changes in land use have led to differences in the seasonal characteristics of streamflow and baseflow in the study area.
Article
Water Resources
Dessalegn Worku Ayalew, Tirusew Asefa, Mamaru Ayalew Moges, Sileshie Mesfin Leyew
Summary: Scientific findings suggest that in the future, the streamflow of Ribb River will decrease annually and monthly due to increasing temperatures and reduced rainfall. The study reveals that the changes in streamflow exhibit temporal and spatial patterns, with a significant reduction observed in June across different scenarios.
JOURNAL OF WATER AND CLIMATE CHANGE
(2022)
Article
Geosciences, Multidisciplinary
Chaoyue Li, Haiyan Fang
Summary: The study reveals that in the future, the temperature in Southeast Asia will increase and annual precipitation will decrease, especially in the Mun River Basin after 2020. Projections suggest that streamflow in the Mun River Basin will gradually increase over the following decades, particularly during the wet season months.
Article
Engineering, Civil
Swati Maurya, Prashant K. K. Srivastava, Lu Zhuo, Aradhana Yaduvanshi, R. K. Mall
Summary: Climate change significantly affects the hydrological regime, and the integration of climate models with physical based models is crucial for accurate measurement of surface water changes. The study found that the INMCM-4 and MRI-CGCM3 models, as well as their ensemble mean, performed well in predicting rainfall and temperature in the Mahi River basin, India. The findings indicate that there will be an increase in average annual streamflow in the near future.
WATER RESOURCES MANAGEMENT
(2023)
Article
Environmental Sciences
Susan Borchardt, Woonsup Choi
Summary: The number of high-capacity wells in Wisconsin has increased, causing concerns about their impact on groundwater levels and streamflow. This study uses simulation models to demonstrate the combined effects of climate change and groundwater withdrawal on the state's water resources. The models predict that future increases in precipitation will lead to higher groundwater recharge and streamflow, but higher temperatures will result in deficits in both streamflow and groundwater recharge, exacerbating the impacts of climate change. The study also highlights the significant decrease in groundwater levels due to climate and increased withdrawal rates from high-capacity wells.
ENVIRONMENTAL EARTH SCIENCES
(2023)
Article
Environmental Sciences
R. Visweshwaran, R. A. A. J. Ramsankaran, T. Eldho, Manoj Kumar Jha
Summary: This study assesses the impact of climate change on hydrological variables in the Bharathapuzha river basin in southern India. Five global circulation models were used to simulate future scenarios, and the SWAT hydrological model was employed for continuous simulation. The results indicate that rainfall, evapotranspiration, soil moisture, and surface runoff are projected to increase in the future.
Article
Remote Sensing
Xuecao Li, Yuyu Zhou, Peng Gong
Summary: This study proposes a conceptual model to characterize the spatial sprawl pattern of urban clusters using Zipf's law and 30-year time series of global urban extent data. The study reveals different sprawl patterns at different scales, with small urban clusters growing slightly faster than large clusters globally. It also finds that Asia and Africa show equilibrium patterns of sprawl, while other continents mostly exhibit diffuse patterns. The study provides insights into urban development pathways and contributes to the development of future urban growth models.
REMOTE SENSING LETTERS
(2023)
Article
Engineering, Civil
Jiye Lee, Ather Abbas, Gregory W. McCarty, Xuesong Zhang, Sangchul Lee, Kyung Hwa Cho
JOURNAL OF HYDROLOGY
(2023)
Article
Urban Studies
Wanru He, Xuecao Li, Yuyu Zhou, Xiaoping Liu, Peng Gong, Tengyun Hu, Peiyi Yin, Jianxi Huang, Jianyu Yang, Shuangxi Miao, Xi Wang, Tinghai Wu
Summary: Cellular automata (CA) based models are widely used in urban sprawl modeling for sustainable urban planning. However, most existing urban CA models only consider abrupt conversion, ignoring the difference in urbanization levels among grids and the gradual increase in urban densities. In this study, we proposed an impervious surface area (ISA) based urban CA model that can simulate urban fractional change within each grid. The model was implemented in Beijing and evaluated through comparison and scenario analyses. Results showed that the ISA-based urban CA model captures the dynamics of urban sprawl better than the traditional urban CA model and has great potential in supporting sustainable urban development.
Article
Agronomy
Tongxi Hu, Xuesong Zhang, Gil Bohrer, Yanlan Liu, Yuyu Zhou, Jay Martin, Yang Li, Kaiguang Zhao
Summary: Statistical crop modeling is crucial for understanding the impact of climate on crop yields. The choice of models is important, as linear regression is interpretable but lacks predictive power, while machine learning is highly predictive but often lacks interpretability. In this study, a Bayesian ensemble model (BM) was developed to explore historical crop yield data and predict future yields, providing both interpretability and high predictive power. BM incorporates many models via Bayesian model averaging, fits complex functions, and quantifies model uncertainty.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Environmental Sciences
Long Li, Wenfeng Zhan, Weimin Ju, Josep Penuelas, Zaichun Zhu, Shushi Peng, Xiaolin Zhu, Zihan Liu, Yuyu Zhou, Jiufeng Li, Jiameng Lai, Fan Huang, Gaofei Yin, Yongshuo Fu, Manchun Li, Chao Yu
Summary: Urban vegetation is influenced by complex urban environments. The study reveals that greenness trends decrease from urban cores to urban new towns, and brownish trends are observed in urban fringes. These results highlight the joint influence of biogeochemical drivers and land-cover changes on the urban-rural gradient in vegetation trends, providing insights into future global vegetation change.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Sijal Dangol, Xuesong Zhang, Xin-Zhong Liang, Martha Anderson, Wade Crow, Sangchul Lee, Glenn E. Moglen, Gregory W. McCarty
Summary: This study calibrated the Soil and Water Assessment Tool (SWAT) model using streamflow data and remotely sensed hydrologic variables. The results show that adding remotely sensed ET and soil moisture to streamflow for calibration can impact the sensitive parameters of the model, but it does not necessarily improve its performance. Using remote sensing data alone leads to a deterioration in model performance. Different choices of remote sensing data for calibration also result in noticeable differences in simulated hydrologic processes. The comparison between SWAT and SWAT-Carbon models under different calibration setups reveals significant differences in their performance.
Article
Multidisciplinary Sciences
Han Qiu, Xuesong Zhang, Anni Yang, Kimberly P. Wickland, Edward G. Stets, Min Chen
Summary: River networks are crucial for the global carbon cycle. This study provides important data on the riverine load of particulate organic carbon (POC) and dissolved organic carbon (DOC) across the Conterminous United States (CONUS) and estimates net gain or net loss of POC and DOC in watersheds using river network connectivity information.
Article
Agronomy
Songhan Wang, Alessandro Cescatti, Yongguang Zhang, Yuyu Zhou, Lian Song, Ji Li
Summary: By analyzing high spatial resolution satellite solar-induced chlorophyll fluorescence (SIF) data from 160 mega-cities worldwide, we investigated the impact of urbanization on vegetation primary productivity and its drivers. The results showed that SIF enhancements resulting from indirect urbanization impact offset approximately 47% of SIF reductions caused by land cover change. Atmospheric CO2, air temperature, radiation, and atmospheric nitrogen dioxide (NO2) were identified as the main drivers of enhanced SIF in urban areas. Our findings demonstrate a dominant and global enhancement of vegetation photosynthesis in urban conditions, providing insights into the specific contribution of climatic and environmental factors.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Environmental Sciences
Molly E. Brown, Catherine Mitchell, Meghan Halabisky, Benjamin Gustafson, Helga do Rosario Gomes, Joaquim Goes, Xuesong Zhang, Anthony D. Campbell, Benjamin Poulter
Summary: This article investigates stakeholders of wet carbon (WC) ecosystems and analyzes the gaps between scientific understanding and information needs. The study reveals that stakeholder interest in WC systems is primarily determined by its significance for local policy, economics, or ecology. To bridge the gap between stakeholders and available WC data, improved communication of data availability and uncertainty, capacity building, engagement between stakeholder groups, and data continuity are needed.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Jia Hu, Yuyu Zhou, Yingbao Yang, Gang Chen, Wei Chen, Mohamad Hejazi
Summary: This study used the SOLWEIG model and remote sensing data to generate hourly heat exposure maps in three US cities during heat wave and non-heat wave days. The study found high heat exposure in urban downtown areas due to low building height and limited shading effect. Heat exposure during heat waves was increased by 6°C to 10°C compared to non-heat wave conditions, and hot cities had higher heat exposure than warm cities. Sky view factor was the most important factor influencing heat exposure, while the role of impervious surface and trees varied among cities.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Multidisciplinary Sciences
Chenghao Wang, Jiyun Song, Dachuan Shi, Janet L. Reyna, Henry Horsey, Sarah Feron, Yuyu Zhou, Zutao Ouyang, Ying Li, Robert B. Jackson
Summary: Climate, technologies, and socio-economic changes will influence future building energy use in cities. A study on 277 U.S. urban areas shows that climate change results in heterogeneous changes in energy use intensity (EUI) among urban areas, with population and power sector changes being the primary factors driving city-scale building energy use changes. Considering intercity heterogeneity is crucial when developing sustainable and resilient urban energy systems.
NATURE COMMUNICATIONS
(2023)
Article
Geochemistry & Geophysics
Hanzeyu Xu, Yuyu Zhou, Yuchun Wei, Houcai Guo, Xiao Li
Summary: Relative radiometric normalization (RRN) is an effective method for enhancing radiometric consistency among multitemporal satellite images. In this study, we propose a multirule-based RRN method that identifies spectral- and spatial-invariant pseudo-invariant features (PIFs) and uses partial least-squares (PLS) regression to model RRN, resulting in improved radiometric consistency between reference-target image pairs. Our method outperforms six other RRN methods and shows potential for generating more comparable bitemporal multisensor images.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Geosciences, Multidisciplinary
Wanru He, Xuecao Li, Yuyu Zhou, Zitong Shi, Guojiang Yu, Tengyun Hu, Yixuan Wang, Jianxi Huang, Tiecheng Bai, Zhongchang Sun, Xiaoping Liu, Peng Gong
Summary: This study developed a dataset of global urban fractional changes, which can support quantitative analysis of urbanization-induced ecological and environmental change at a fine scale.
EARTH SYSTEM SCIENCE DATA
(2023)
Article
Engineering, Electrical & Electronic
Hanzeyu Xu, Yuyu Zhou, Yuchun Wei, Chong Liu, Xiao Li, Wei Chen
Summary: In this study, a novel RRN method was proposed to enhance the radiometric consistency of Landsat time-series images by trend-based PIFs identification, PIFs optimization, and combined RRN modeling. The experimental results showed that the proposed method achieved good performance in model precision and radiance consistency improvement, outperforming seven commonly used RRN methods.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Computer Science, Interdisciplinary Applications
Sijal Dangol, Xuesong Zhang, Xin-Zhong Liang, Elena Blanc-Betes
Summary: In this study, the SWAT model was enhanced by integrating grass growth algorithms from the DAYCENT model, resulting in the SWAT-GRASSM model which showed improved simulation of switchgrass biomass yield and LAI seasonal development. SWAT-GRASSM also provided a more realistic representation of root development, crucial for biomass and nutrient allocation between aboveground and belowground pools, enhancing the credibility of environmental impact assessments for perennial grasses grown for bioenergy production.
ENVIRONMENTAL MODELLING & SOFTWARE
(2023)
