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Analysing the Potential Impact of Climate Change on the Hydrological Regime of the Upper Benue River Basin (North Cameroon)
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作者 Elisabeth Dassou Fita Auguste Ombolo +4 位作者 Thierry C. Fotso-Nguemo Daniel Bogno Saïdou Augustin Daïka Steven Chouto Felix Abbo Mbele 《Journal of Water Resource and Protection》 CAS 2024年第8期569-583,共15页
In this study, we analyse the climate variability in the Upper Benue basin and assess its potential impact on the hydrology regime under two different greenhouse gas emission scenarios. The hydrological regime of the ... In this study, we analyse the climate variability in the Upper Benue basin and assess its potential impact on the hydrology regime under two different greenhouse gas emission scenarios. The hydrological regime of the basin is more vulnerable to climate variability, especially precipitation and temperature. Observed hydroclimatic data (1950-2015) was analysed using a statistical approach. The potential impact of future climate change on the hydrological regime is quantified using the GR2M model and two climate models: HadGEM2-ES and MIROC5 from CMIP5 under RCP 4.5 and RCP 8.5 greenhouse gas emission scenarios. The main result shows that precipitation varies significantly according to the geographical location and time in the Upper Benue basin. The trend analysis of climatic parameters shows a decrease in annual average precipitation across the study area at a rate of -0.568 mm/year which represents about 37 mm/year over the time 1950-2015 compared to the 1961-1990 reference period. An increase of 0.7°C in mean temperature and 14% of PET are also observed according to the same reference period. The two climate models predict a warming of the basin of about 2°C for both RCP 4.5 and 8.5 scenarios and an increase in precipitation between 1% and 10% between 2015 and 2100. Similarly, the average annual flow is projected to increase by about +2% to +10% in the future for both RCP 4.5 and 8.5 scenarios between 2015 and 2100. Therefore, it is primordial to develop adaptation and mitigation measures to manage efficiently the availability of water resources. 展开更多
关键词 Climate Variability hydrological Modelling Climate Models Upper Benue Basin Northern Cameroon
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Integrated Hydrological Modeling of the Godavari River Basin in Maharashtra Using the SWAT Model: Streamflow Simulation and Analysis
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作者 Pallavi Saraf Dattatray Gangaram Regulwar 《Journal of Water Resource and Protection》 CAS 2024年第1期17-26,共10页
Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in M... Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in Maharashtra using the Soil and Water Assessment Tool (SWAT). SWAT is a process-based hydrological model used to predict water balance components, sediment levels, and nutrient contamination. In this research, we used integrated remote sensing and GIS data, including Digital Elevation Models (DEM), land use and land cover (LULC) maps, soil maps, and observed precipitation and temperature data, as input for developing the SWAT model to assess surface runoff in this large river basin. The Godavari River Basin under study was divided into 25 sub-basins, comprising 151 hydrological response units categorized by unique land cover, soil, and slope characteristics using the SWAT model. The model was calibrated and validated against observed runoff data for two time periods: 2003-2006 and 2007-2010 respectively. Model performance was assessed using the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). The results show the effectiveness of the SWAT2012 model, with R2 value of 0.84 during calibration and 0.86 during validation. NSE values also ranged from 0.84 during calibration to 0.85 during validation. These findings enhance our understanding of surface runoff dynamics in the Godavari River Basin under study and highlight the suit-ability of the SWAT model for this region. 展开更多
关键词 Soil and Water Assessment Tool (SWAT) Streamflow hydrological Modeling RAINFALL RUNOFF
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Hierarchical multihead self-attention for time-series-based fault diagnosis
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作者 Chengtian Wang Hongbo Shi +1 位作者 Bing Song Yang Tao 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2024年第6期104-117,共14页
Fault diagnosis is important for maintaining the safety and effectiveness of chemical process.Considering the multivariate,nonlinear,and dynamic characteristic of chemical process,many time-series-based data-driven fa... Fault diagnosis is important for maintaining the safety and effectiveness of chemical process.Considering the multivariate,nonlinear,and dynamic characteristic of chemical process,many time-series-based data-driven fault diagnosis methods have been developed in recent years.However,the existing methods have the problem of long-term dependency and are difficult to train due to the sequential way of training.To overcome these problems,a novel fault diagnosis method based on time-series and the hierarchical multihead self-attention(HMSAN)is proposed for chemical process.First,a sliding window strategy is adopted to construct the normalized time-series dataset.Second,the HMSAN is developed to extract the time-relevant features from the time-series process data.It improves the basic self-attention model in both width and depth.With the multihead structure,the HMSAN can pay attention to different aspects of the complicated chemical process and obtain the global dynamic features.However,the multiple heads in parallel lead to redundant information,which cannot improve the diagnosis performance.With the hierarchical structure,the redundant information is reduced and the deep local time-related features are further extracted.Besides,a novel many-to-one training strategy is introduced for HMSAN to simplify the training procedure and capture the long-term dependency.Finally,the effectiveness of the proposed method is demonstrated by two chemical cases.The experimental results show that the proposed method achieves a great performance on time-series industrial data and outperforms the state-of-the-art approaches. 展开更多
关键词 Self-attention mechanism Deep learning Chemical process time-series Fault diagnosis
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Modeling urban redevelopment:A novel approach using time-series remote sensing data and machine learning
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作者 Li Lin Liping Di +6 位作者 Chen Zhang Liying Guo Haoteng Zhao Didarul Islam Hui Li Ziao Liu Gavin Middleton 《Geography and Sustainability》 CSCD 2024年第2期211-219,共9页
Accurate mapping and timely monitoring of urban redevelopment are pivotal for urban studies and decisionmakers to foster sustainable urban development.Traditional mapping methods heavily depend on field surveys and su... Accurate mapping and timely monitoring of urban redevelopment are pivotal for urban studies and decisionmakers to foster sustainable urban development.Traditional mapping methods heavily depend on field surveys and subjective questionnaires,yielding less objective,reliable,and timely data.Recent advancements in Geographic Information Systems(GIS)and remote-sensing technologies have improved the identification and mapping of urban redevelopment through quantitative analysis using satellite-based observations.Nonetheless,challenges persist,particularly concerning accuracy and significant temporal delays.This study introduces a novel approach to modeling urban redevelopment,leveraging machine learning algorithms and remote-sensing data.This methodology can facilitate the accurate and timely identification of urban redevelopment activities.The study’s machine learning model can analyze time-series remote-sensing data to identify spatio-temporal and spectral patterns related to urban redevelopment.The model is thoroughly evaluated,and the results indicate that it can accurately capture the time-series patterns of urban redevelopment.This research’s findings are useful for evaluating urban demographic and economic changes,informing policymaking and urban planning,and contributing to sustainable urban development.The model can also serve as a foundation for future research on early-stage urban redevelopment detection and evaluation of the causes and impacts of urban redevelopment. 展开更多
关键词 Urban redevelopment Urban sustainability Remote sensing time-series analysis Machine learning
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Missing Value Imputation for Radar-Derived Time-Series Tracks of Aerial Targets Based on Improved Self-Attention-Based Network
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作者 Zihao Song Yan Zhou +2 位作者 Wei Cheng Futai Liang Chenhao Zhang 《Computers, Materials & Continua》 SCIE EI 2024年第3期3349-3376,共28页
The frequent missing values in radar-derived time-series tracks of aerial targets(RTT-AT)lead to significant challenges in subsequent data-driven tasks.However,the majority of imputation research focuses on random mis... The frequent missing values in radar-derived time-series tracks of aerial targets(RTT-AT)lead to significant challenges in subsequent data-driven tasks.However,the majority of imputation research focuses on random missing(RM)that differs significantly from common missing patterns of RTT-AT.The method for solving the RM may experience performance degradation or failure when applied to RTT-AT imputation.Conventional autoregressive deep learning methods are prone to error accumulation and long-term dependency loss.In this paper,a non-autoregressive imputation model that addresses the issue of missing value imputation for two common missing patterns in RTT-AT is proposed.Our model consists of two probabilistic sparse diagonal masking self-attention(PSDMSA)units and a weight fusion unit.It learns missing values by combining the representations outputted by the two units,aiming to minimize the difference between the missing values and their actual values.The PSDMSA units effectively capture temporal dependencies and attribute correlations between time steps,improving imputation quality.The weight fusion unit automatically updates the weights of the output representations from the two units to obtain a more accurate final representation.The experimental results indicate that,despite varying missing rates in the two missing patterns,our model consistently outperforms other methods in imputation performance and exhibits a low frequency of deviations in estimates for specific missing entries.Compared to the state-of-the-art autoregressive deep learning imputation model Bidirectional Recurrent Imputation for Time Series(BRITS),our proposed model reduces mean absolute error(MAE)by 31%~50%.Additionally,the model attains a training speed that is 4 to 8 times faster when compared to both BRITS and a standard Transformer model when trained on the same dataset.Finally,the findings from the ablation experiments demonstrate that the PSDMSA,the weight fusion unit,cascade network design,and imputation loss enhance imputation performance and confirm the efficacy of our design. 展开更多
关键词 Missing value imputation time-series tracks probabilistic sparsity diagonal masking self-attention weight fusion
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Initiatives to clarify mechanisms of hydrological evolution in human-influenced Yellow River Basin 被引量:2
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作者 Li-liang Ren Shan-shui Yuan +6 位作者 Xiao-li Yang Shan-hu Jiang Gui-bao Li Qiu-an Zhu Xiu-qin Fang Yi Liu Yi-qi Yan 《Water Science and Engineering》 EI CAS CSCD 2023年第2期117-121,共5页
Significant changes in water cycle elements/processes have created serious challenges to regional sustainability and high-quality development in the Yellow River Basin in China.It is necessary to investigate the impac... Significant changes in water cycle elements/processes have created serious challenges to regional sustainability and high-quality development in the Yellow River Basin in China.It is necessary to investigate the impacts of climate change and human activities on hydrological evolution and disaster risk from a holistic perspective of the basin.This study developed initiatives to clarify the mechanisms of hydrological evolution in the human-influenced Yellow River Basin.The proposed research method includes:(1)a tool to simulate multiple factors and a multi-scale water cycle using a grid-based spatiotemporal coupling approach,and(2)a new algorithm to separate the responses of the water cycle to climate change and human impacts,and de-couple the eco-environmental effects using artificial intelligence techniques.With this research framework,key breakthroughs are expected to be made in the understanding of the impacts of land cover change on the water cycle and blue/green water redirection.The outcomes of this research project are expected to provide theoretical support for ecological protection and water governance in the basin. 展开更多
关键词 Climate change Human activities hydrological evolution Runoff change Yellow River Basin
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Effect of sand-fixing vegetation on the hydrological regulation function of sand dunes and its practical significance 被引量:2
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作者 Alamusa SU Yuhang +2 位作者 YIN Jiawang ZHOU Quanlai WANG Yongcui 《Journal of Arid Land》 SCIE CSCD 2023年第1期52-62,共11页
Soil water content is a key controlling factor for vegetation restoration in sand dunes.The deep seepage and lateral migration of water in dunes affect the recharge process of deep soil water and groundwater in sand d... Soil water content is a key controlling factor for vegetation restoration in sand dunes.The deep seepage and lateral migration of water in dunes affect the recharge process of deep soil water and groundwater in sand dune ecosystems.To determine the influence of vegetation on the hydrological regulation function of sand dunes,we examined the deep seepage and lateral migration of dune water with different vegetation coverages during the growing season in the Horqin Sandy Land,China.The results showed that the deep seepage and lateral migration of water decreased with the increase in vegetation coverage on the dunes.The accumulated deep seepage water of mobile dunes(vegetation coverage<5%)and dunes with vegetation coverage of 18.03%,27.12%,and 50.65%accounted for 56.53%,51.82%,18.98%,and 0.26%,respectively,of the rainfall in the same period.The accumulated lateral migration of water in these dunes accounted for 12.39%,6.33%,2.23%,and 7.61%of the rainfall in the same period.The direction and position of the dune slope affected the soil water deep seepage and lateral migration process.The amounts of deep seepage and lateral migration of water on the windward slope were lower than those on the leeward slope.The amounts of deep seepage and lateral migration of water showed a decreasing trend from the bottom to the middle and to the top of the dune slope.According to the above results,during the construction of sand-control projects in sandy regions,we suggest that a certain area of mobile dunes(>13.75%)should be retained as a water resource reservoir to maintain the water balance of artificial fixed dune ecosystems.These findings provide reliable evidence for the accurate assessment of water resources within the sand dune ecosystem and guide the construction of desertification control projects. 展开更多
关键词 vegetation coverage hydrological regulation soil water deep seepage sand dune water balance desertification control
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Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China 被引量:1
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作者 Jianguo LIU Zong-Liang YANG +4 位作者 Binghao JIA Longhuan WANG Ping WANG Zhenghui XIE Chunxiang SHI 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2023年第2期235-250,共16页
In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent t... In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were conducted.Six simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against observations.The results show that the meteorological forcing is the most important factor governing output.Beyond that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the LSM.The Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight basins.It increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD simulations.This study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes. 展开更多
关键词 hydrological simulations land surface model meteorological forcing land surface parameters UNCERTAINTY
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Hydrological Processes in a Small Research Watershed under Forest Coverage in the Coast of Chiapas, Mexico 被引量:1
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作者 Juan Alberto Rodríguez-Morales Romeo de Jesús Barrios-Calderón +1 位作者 Jorge Reyes-Reyes Dorian de Jesús Pimienta-de la Torre 《Journal of Geoscience and Environment Protection》 2023年第3期104-114,共11页
In the hydrological watershed, some natural processes take place in which the interaction of water, soil, climate and vegetation favors the capture of water. The present study aimed to evaluate preliminary information... In the hydrological watershed, some natural processes take place in which the interaction of water, soil, climate and vegetation favors the capture of water. The present study aimed to evaluate preliminary information regarding the hydrological response and the water balance in a small research watershed with tropical forest cover (15°01'44''N and 92°13'55''W, 471 m, 2.3 has). Events of precipitation, direct runoff, infiltration rate and baseflow were performed. The amount, duration and intensity of rainfall events were recorded with the use of a pluviograph. Surface runoff was quantified with an established gauging station, an H-type gauging device and a horizontal mechanical gauging limnograph. Runoff base flow was measured at the gauging station using the volume-time method. Infiltration was measured using a triple ring infiltrometer, taking two measurements in the upper part and two in the lower part of the microbasin. Evapotranspiration was measured with the amount of rainfall entering and runoff leaving the watershed. In the study period, annual rainfall of 4417.6 mm distributed over 181 events were recorded;about 70% of the storms showed lower intensities at 20 mm·h<sup>-1</sup>. The total runoff was 345.8 mm caused by half of the rainfall events, which represents 7.8% of the total rain;77% of runoff events showed lower sheets of 5 mm and an average specific rate of 20.7 L·s<sup>-1</sup>·ha<sup>-1</sup> with a maximum of 113.6 L·s<sup>-1</sup>·ha<sup>-1</sup>. Three runoff events were greater than 20.1 mm and caused the 22.5% of the total runoff depth in the study period showing the equilibrium conditions in the hydrological response of the forest. Water outputs like baseflow was 669.5 mm. In this way, 90% of the rainfall is infiltrated every year in the micro-watershed, which shows the importance of the plant cover in the hydrological regulation and the groundwater recharge. 展开更多
关键词 hydrological Response Tropical Forest Runoff-Rain Ratio Water Balance Groundwater Recharge
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Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study 被引量:1
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作者 Ting Hu Zhao-Yuan Xu +2 位作者 Jian Wang Yao Su Bing-Bing Guo 《World Journal of Psychiatry》 SCIE 2023年第12期1061-1078,共18页
BACKGROUND The literature has discussed the relationship between environmental factors and depressive disorders;however,the results are inconsistent in different studies and regions,as are the interaction effects betw... BACKGROUND The literature has discussed the relationship between environmental factors and depressive disorders;however,the results are inconsistent in different studies and regions,as are the interaction effects between environmental factors.We hypo-thesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity.AIM To investigate the effects of meteorological factors and air pollution on depressive disorders,including their lagged effects and interactions.METHODS The samples were obtained from a class 3 hospital in Harbin,China.Daily hos-pital admission data for depressive disorders from January 1,2015 to December 31,2022 were obtained.Meteorological and air pollution data were also collected during the same period.Generalized additive models with quasi-Poisson regre-ssion were used for time-series modeling to measure the non-linear and delayed effects of environmental factors.We further incorporated each pair of environ-mental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders.RESULTS Data for 2922 d were included in the study,with no missing values.The total number of depressive admissions was 83905.Medium to high correlations existed between environmental factors.Air temperature(AT)and wind speed(WS)significantly affected the number of admissions for depression.An extremely low temperature(-29.0℃)at lag 0 caused a 53%[relative risk(RR)=1.53,95%confidence interval(CI):1.23-1.89]increase in daily hospital admissions relative to the median temperature.Extremely low WSs(0.4 m/s)at lag 7 increased the number of admissions by 58%(RR=1.58,95%CI:1.07-2.31).In contrast,atmospheric pressure and relative humidity had smaller effects.Among the six air pollutants considered in the time-series model,nitrogen dioxide(NO_(2))was the only pollutant that showed significant effects over non-cumulative,cumulative,immediate,and lagged conditions.The cumulative effect of NO_(2) at lag 7 was 0.47%(RR=1.0047,95%CI:1.0024-1.0071).Interaction effects were found between AT and the five air pollutants,atmospheric temperature and the four air pollutants,WS and sulfur dioxide.CONCLUSION Meteorological factors and the air pollutant NO_(2) affect daily hospital admissions for depressive disorders,and interactions exist between meteorological factors and ambient air pollution. 展开更多
关键词 Mental health Depressive disorder Hospital admissions Meteorological factors Air pollution time-series
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Graph Construction Method for GNN-Based Multivariate Time-Series Forecasting
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作者 Wonyong Chung Jaeuk Moon +1 位作者 Dongjun Kim Eenjun Hwang 《Computers, Materials & Continua》 SCIE EI 2023年第6期5817-5836,共20页
Multivariate time-series forecasting(MTSF)plays an important role in diverse real-world applications.To achieve better accuracy in MTSF,time-series patterns in each variable and interrelationship patterns between vari... Multivariate time-series forecasting(MTSF)plays an important role in diverse real-world applications.To achieve better accuracy in MTSF,time-series patterns in each variable and interrelationship patterns between variables should be considered together.Recently,graph neural networks(GNNs)has gained much attention as they can learn both patterns using a graph.For accurate forecasting through GNN,a well-defined graph is required.However,existing GNNs have limitations in reflecting the spectral similarity and time delay between nodes,and consider all nodes with the same weight when constructing graph.In this paper,we propose a novel graph construction method that solves aforementioned limitations.We first calculate the Fourier transform-based spectral similarity and then update this similarity to reflect the time delay.Then,we weight each node according to the number of edge connections to get the final graph and utilize it to train the GNN model.Through experiments on various datasets,we demonstrated that the proposed method enhanced the performance of GNN-based MTSF models,and the proposed forecasting model achieve of up to 18.1%predictive performance improvement over the state-of-the-art model. 展开更多
关键词 Deep learning graph neural network multivariate time-series forecasting
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Intensity Estimation of Extreme Meteorological and Hydrological Factors Induced by Tropical Cyclones Affecting Hong Kong
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作者 TAO Shanshan HUA Yunfei DONG Sheng 《Journal of Ocean University of China》 SCIE CAS CSCD 2023年第2期313-323,共11页
Hong Kong is often affected by tropical cyclones.The Hong Kong observatory issues warning signals based on the impact of tropical cyclones on the region.The joint frequency analysis of tropical cyclones in Hong Kong c... Hong Kong is often affected by tropical cyclones.The Hong Kong observatory issues warning signals based on the impact of tropical cyclones on the region.The joint frequency analysis of tropical cyclones in Hong Kong can provide a scientific basis for disaster reduction and prevention and post-disaster reconstruction of tropical cyclones.First,the maximum hourly mean wind speed(W),warning signal duration(D),maximum sea level(L),and total rainfall(R)of each tropical cyclone that affected Hong Kong from 1985 to 2019 are selected and fitted using the Gumbel,Weibull,Pearson type 3,and lognormal distributions.Then,bivariate copula functions,such as the Clayton,Frank,Gumbel-Hougaard,and Gaussian copulas,are applied to construct the joint probability models of W,D,L,and R,respectively.The joint return periods of W and D and those of L and R are defined as the meteorological and hydrological intensities of tropical cyclones,respectively.The results show that the joint return periods are good indicators of the comprehensive effect of the meteorological and hydrological intensities of tropical cyclones.No necessary correlation between meteorological and hydrological intensities of tropical cyclones exists.The meteorological and hydrological intensities of tropical cyclones show an upward trend in recent years. 展开更多
关键词 tropical cyclone warning signal meteorological intensity hydrological intensity copula
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Dimensioning Urban Drainage Systems in Housing Subdivisions in the Amazon Using Different Hydrological Models
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作者 Caio Emanuel da Silva Pacheco Taís Silva Sousa +1 位作者 Elizandra Perez Araújo Alan Cavalcanti da Cunha 《Journal of Geoscience and Environment Protection》 2023年第11期151-170,共20页
Hydrological studies for sizing urban drainage systems in the Amazon have often been neglected and little investigated for rainwater projects. This research evaluated alternative hydrological models used in sizing urb... Hydrological studies for sizing urban drainage systems in the Amazon have often been neglected and little investigated for rainwater projects. This research evaluated alternative hydrological models used in sizing urban drainage network projects in subdivisions with subsidized houses in the Amazonian region in Brazil. Statistical tests of these models were performed for both original and alternative scenarios. The methodological steps we conducted as follows: 1) evaluate the dimensioning of infrastructure project networks, considering two case studies contemplated by the Calha Norte Program (CNP) in the state of Amapá;2) test the statistical significance of the dimensioning of network diameters (α < 0.05), considering a) benchmark project (MD or M1) approved by the Ministry of Defense;b) determination of concentration time (C<sub>t</sub>) and rainfall intensity-duration-frequency (IDF) relationships, as well as estimating diameters using alternative models. The results indicated a significant influence on the diameters of the projected rainfall networks (p < 0.05), suggesting that alternative models predicted more unfavorable flow peaks than the original model. We conclude that the benchmarking model underestimated the diameter of the project compared to alternative models, which means the optimized C<sub>t</sub> parameter significantly impacts dimensioning estimates in rainwater projects in these Amazonian municipalities. This suggests that underestimated parameters in MD may cause inefficiency in the stormwater system projects in future similar scenarios. 展开更多
关键词 hydrological Studies Concentration Time Calha Norte Program Amapá
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Sentinel-1 In SAR observations and time-series analysis of co-and postseismic deformation mechanisms of the 2021 Mw 5.8 Bandar Ganaveh Earthquake,Southern Iran
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作者 Reza SABER Veysel ISIK +1 位作者 Ayse CAGLAYAN Marjan TOURANI 《Journal of Mountain Science》 SCIE CSCD 2023年第4期911-927,共17页
In the past two decades,because of the significant increase in the availability of differential interferometry from synthetic aperture radar and GPS data,spaceborne geodesy has been widely employed to determine the co... In the past two decades,because of the significant increase in the availability of differential interferometry from synthetic aperture radar and GPS data,spaceborne geodesy has been widely employed to determine the co-seismic displacement field of earthquakes.On April 18,2021,a moderate earthquake(Mw 5.8)occurred east of Bandar Ganaveh,southern Iran,followed by intensive seismic activity and aftershocks of various magnitudes.We use two-pass D-InSAR and Small Baseline Inversion techniques via the LiCSBAS suite to study the coseismic displacement and monitor the four-month post-seismic deformation of the Bandar Ganaveh earthquake,as well as constrain the fault geometry of the co-seismic faulting mechanism during the seismic sequence.Analyses show that the co-and postseismic deformation are distributed in relatively shallow depths along with an NW-SE striking and NE dipping complex reverse/thrust fault branches of the Zagros Mountain Front Fault,complying with the main trend of the Zagros structures.The average cumulative displacements were obtained from-137.5 to+113.3 mm/yr in the SW and NE blocks of the Mountain Front Fault,respectively.The received maximum uplift amount is approximately consistent with the overall orogen-normal shortening component of the Arabian-Eurasian convergence in the Zagros region.No surface ruptures were associated with the seismic source;therefore,we propose a shallow blind thrust/reverse fault(depth~10 km)connected to the deeper basal decollement fault within a complex tectonic zone,emphasizing the thin-skinned tectonics. 展开更多
关键词 Sentinel‑1 InSAR time-series Neotectonic reactivation Seismogenic fault Bandar Ganaveh earthquakes Zagros Fold-Thrust Belt Arabian-Eurasian collision
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Generating Time-Series Data Using Generative Adversarial Networks for Mobility Demand Prediction
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作者 Subhajit Chatterjee Yung-Cheol Byun 《Computers, Materials & Continua》 SCIE EI 2023年第3期5507-5525,共19页
The increasing penetration rate of electric kickboard vehicles has been popularized and promoted primarily because of its clean and efficient features.Electric kickboards are gradually growing in popularity in tourist... The increasing penetration rate of electric kickboard vehicles has been popularized and promoted primarily because of its clean and efficient features.Electric kickboards are gradually growing in popularity in tourist and education-centric localities.In the upcoming arrival of electric kickboard vehicles,deploying a customer rental service is essential.Due to its freefloating nature,the shared electric kickboard is a common and practical means of transportation.Relocation plans for shared electric kickboards are required to increase the quality of service,and forecasting demand for their use in a specific region is crucial.Predicting demand accurately with small data is troublesome.Extensive data is necessary for training machine learning algorithms for effective prediction.Data generation is a method for expanding the amount of data that will be further accessible for training.In this work,we proposed a model that takes time-series customers’electric kickboard demand data as input,pre-processes it,and generates synthetic data according to the original data distribution using generative adversarial networks(GAN).The electric kickboard mobility demand prediction error was reduced when we combined synthetic data with the original data.We proposed Tabular-GAN-Modified-WGAN-GP for generating synthetic data for better prediction results.We modified The Wasserstein GAN-gradient penalty(GP)with the RMSprop optimizer and then employed Spectral Normalization(SN)to improve training stability and faster convergence.Finally,we applied a regression-based blending ensemble technique that can help us to improve performance of demand prediction.We used various evaluation criteria and visual representations to compare our proposed model’s performance.Synthetic data generated by our suggested GAN model is also evaluated.The TGAN-Modified-WGAN-GP model mitigates the overfitting and mode collapse problem,and it also converges faster than previous GAN models for synthetic data creation.The presented model’s performance is compared to existing ensemble and baseline models.The experimental findings imply that combining synthetic and actual data can significantly reduce prediction error rates in the mean absolute percentage error(MAPE)of 4.476 and increase prediction accuracy. 展开更多
关键词 Machine learning generative adversarial networks electric vehicle time-series TGAN WGAN-GP blend model demand prediction regression
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Anthropogenic activity,hydrological regime,and light level jointly influence temporal patterns in biosonar activity of the Yangtze finless porpoise at the junction of the Yangtze River and Poyang Lake,China
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作者 Peng-Xiang Duan Zhi-Tao Wang +4 位作者 Tomonari Akamatsu Nick Tregenza Guang-Yu Li Ke-Xiong Wang Ding Wang 《Zoological Research》 SCIE CSCD 2023年第5期919-931,共13页
Under increasing anthropogenic pressure,species with a previously contiguous distribution across their ranges have been reduced to small fragmented populations.The critically endangered Yangtze finless porpoise(Neopho... Under increasing anthropogenic pressure,species with a previously contiguous distribution across their ranges have been reduced to small fragmented populations.The critically endangered Yangtze finless porpoise(Neophocaena asiaeorientalis asiaeorientalis),once commonly observed in the Yangtze River-Poyang Lake junction,is now rarely seen in the river-lake corridor.In this study,static passive acoustic monitoring techniques were used to detect the biosonar activities of the Yangtze finless porpoise in this unique corridor.Generalized linear models were used to examine the correlation between these activities and anthropogenic impacts from the COVID-19 pandemic lockdown and boat navigation,as well as environmental variables,including hydrological conditions and light levels.Over approximately three consecutive years of monitoring(2020–2022),porpoise biosonar was detected during 93%of logged days,indicating the key role of the corridor for finless porpoise conservation.In addition,porpoise clicks were recorded in 3.80%of minutes,while feeding correlated buzzes were detected in 1.23%of minutes,suggesting the potential existence of localized,small-scale migration.Furthermore,both anthropogenic and environmental variables were significantly correlated with the diel,lunar,monthly,seasonal,and annual variations in porpoise biosonar activities.During the pandemic lockdown period,porpoise sonar detection showed a significant increase.Furthermore,a significant negative correlation was identified between the detection of porpoise click trains and buzzes and boat traffic intensity.In addition to water level and flux,daylight and moonlight exhibited significant correlations with porpoise biosonar activities,with markedly higher detections at night and quarter moon periods.Ensuring the spatiotemporal reduction of anthropogenic activities,implementing vessel speed restrictions(e.g.,during porpoise migration and feeding),and maintaining local natural hydrological regimes are critical factors for sustaining porpoise population viability. 展开更多
关键词 Yangtze finless porpoises Yangtze River Poyang Lake Pandemic lockdown Boat traffic hydrological regime Light level
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Artificial Intelligence Technique in Hydrological Forecasts Supporting for Water Resources Management of a Large River Basin in Vietnam
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作者 Truong Van Anh 《Open Journal of Modern Hydrology》 2023年第4期246-258,共13页
Hydrological forecasting plays an important role in water resource management, supporting socio-economic development and managing water-related risks in river basins. There are many flow forecasting techniques that ha... Hydrological forecasting plays an important role in water resource management, supporting socio-economic development and managing water-related risks in river basins. There are many flow forecasting techniques that have been developed several centuries ago, ranging from physical models, physics-based models, conceptual models, and data-driven models. Recently, Artificial Intelligence (AI) has become an advanced technique applied as an effective data-driven model in hydrological forecasting. The main advantage of these models is that they give results with compatible accuracy, and require short computation time, thus increasing forecasting time and reducing human and financial effort. This study evaluates the applicability of machine learning and deep learning in Hanoi water level forecasting where it is controlled for flood management and water supply in the Red River Delta, Vietnam. Accordingly, SANN (machine learning algorithm) and LSTM (deep learning algorithm) were tested and compared with a Physics-Based Model (PBM) for the Red River Delta. The results show that SANN and LSTM give high accuracy. The R-squared coefficient is greater than 0.8, the mean squared error (MSE) is less than 20 cm, the correlation coefficient of the forecast hydrology is greater than 0.9 and the level of assurance of the forecast plan ranges from 80% to 90% in both cases. In addition, the calculation time is much reduced compared to the requirement of PBM, which is its limitation in hydrological forecasting for large river basins such as the Red River in Vietnam. Therefore, SANN and LSTM are expected to help increase lead time, thereby supporting water resource management for sustainable development and management of water-related risks in the Red River Delta. 展开更多
关键词 hydrological Forecast Water Resources Management Machine Learning Deep Learning Red River Basin
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Recent advances in hydrology studies under changing permafrost on the Qinghai-Xizang Plateau
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作者 Lu Zhou YuZhong Yang +1 位作者 DanDan Zhang HeLin Yao 《Research in Cold and Arid Regions》 CSCD 2024年第4期159-169,共11页
Due to the great influences of both climate warming and human activities,permafrost on the Qinghai-Xizang Plateau(QXP)has been undergoing considerable degradation.Continuous degradation of plateau permafrost dramatica... Due to the great influences of both climate warming and human activities,permafrost on the Qinghai-Xizang Plateau(QXP)has been undergoing considerable degradation.Continuous degradation of plateau permafrost dramatically modifies the regional water cycle and hydrological processes,affecting the hydrogeological conditions,and ground hydrothermal status in cold regions.Permafrost thawing impacts the ecological environment,engineering facilities,and carbon storage functions,releasing some major greenhouse gases and exacerbating climate change.Despite the utilization of advanced research methodologies to investigate the changing hydrological processes and the corresponding influencing factors in permafrost regions,there still exist knowledge gaps in multivariate data,quantitative analysis of permafrost degradation's impact on various water bodies,and systematic hydrological modeling on the QXP.This review summarizes the main research methods in permafrost hydrology and elaborates on the impacts of permafrost degradation on regional precipitation distribution patterns,changes in surface runoff,expansion of thermokarst lakes/ponds,and groundwater dynamics on the QXP.Then,we discuss the current inadequacies and future research priorities,including multiple methods,observation data,and spatial and temporal scales,to provide a reference for a comprehensive analysis of the hydrological and environmental effects of permafrost degradation on the QXP under a warming climate. 展开更多
关键词 Qinghai-Xizang Plateau Permafrost degradation hydrological processes
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Hydrologic Response to Future Climate Change in the Dulong-Irra-waddy River Basin Based on Coupled Model Intercomparison Project 6
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作者 XU Ziyue MA Kai +1 位作者 YUAN Xu HE Daming 《Chinese Geographical Science》 SCIE CSCD 2024年第2期294-310,共17页
Within the context of the Belt and Road Initiative(BRI)and the China-Myanmar Economic Corridor(CMEC),the Dulong-Ir-rawaddy(Ayeyarwady)River,an international river among China,India and Myanmar,plays a significant role... Within the context of the Belt and Road Initiative(BRI)and the China-Myanmar Economic Corridor(CMEC),the Dulong-Ir-rawaddy(Ayeyarwady)River,an international river among China,India and Myanmar,plays a significant role as both a valuable hydro-power resource and an essential ecological passageway.However,the water resources and security exhibit a high degree of vulnerabil-ity to climate change impacts.This research evaluates climate impacts on the hydrology of the Dulong-Irrawaddy River Basin(DIRB)by using a physical-based hydrologic model.We crafted future climate scenarios using the three latest global climate models(GCMs)from Coupled Model Intercomparison Project 6(CMIP6)under two shared socioeconomic pathways(SSP2-4.5 and SSP5-8.5)for the near(2025-2049),mid(2050-2074),and far future(2075-2099).The regional model using MIKE SHE based on historical hydrologic processes was developed to further project future streamflow,demonstrating reliable performance in streamflow simulations with a val-idation Nash-Sutcliffe Efficiency(NSE)of 0.72.Results showed that climate change projections showed increases in the annual precip-itation and potential evapotranspiration(PET),with precipitation increasing by 11.3%and 26.1%,and PET increasing by 3.2%and 4.9%,respectively,by the end of the century under SSP2-4.5 and SSP5-8.5.These changes are projected to result in increased annual streamflow at all stations,notably at the basin’s outlet(Pyay station)compared to the baseline period(with an increase of 16.1%and 37.0%at the end of the 21st century under SSP2-4.5 and SSP5-8.5,respectively).Seasonal analysis for Pyay station forecasts an in-crease in dry-season streamflow by 31.3%-48.9%and 22.5%-76.3%under SSP2-4.5 and SSP5-8.5,respectively,and an increase in wet-season streamflow by 5.8%-12.6%and 2.8%-33.3%,respectively.Moreover,the magnitude and frequency of flood events are pre-dicted to escalate,potentially impacting hydropower production and food security significantly.This research outlines the hydrological response to future climate change during the 21st century and offers a scientific basis for the water resource management strategies by decision-makers. 展开更多
关键词 climate change hydrologic response Coupled Model Intercomparison Project 6(CMIP6) MIKE SHE(Système hydrologique Europeén) Dulong-Irrawaddy River Basin
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Hydrological Process Factors Analysis of Heihe River Mountain Basin Based on GIS 被引量:8
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作者 黄清华 杨永国 陈玉华 《Agricultural Science & Technology》 CAS 2010年第3期147-150,共4页
Hydrological process factors are a reflection of the physical mechanism of basin hydrology,which can provide important basis for the use and protection of water resources.Taking Heihe River Mountain Basin as the study... Hydrological process factors are a reflection of the physical mechanism of basin hydrology,which can provide important basis for the use and protection of water resources.Taking Heihe River Mountain Basin as the study area,the hydrological simulation was made based on SWAT-GIS integrated model platform.The calculation methods of hydrological process factors using SWAT model were described based on the simulation results of runoff from 1990 to 2000.Hydrological process factors in the study area were analyzed by using GIS technology.The spatial and temporal characteristics of precipitation,runoff,infiltration,evapotranspiration and snowmelt in the basin were calculated and analyzed. 展开更多
关键词 GIS hydrological process factors SWAT Heihe River Basin
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