Global climate change,along with the rapid increase of the population,has put significant pressure on water security.A water reservoir is an effective solution for adjusting and ensuring water supply.In particular,the...Global climate change,along with the rapid increase of the population,has put significant pressure on water security.A water reservoir is an effective solution for adjusting and ensuring water supply.In particular,the reservoir water level is an essential physical indicator for the reservoirs.Forecasting the reservoir water level effectively assists the managers in making decisions and plans related to reservoir management policies.In recent years,deep learning models have been widely applied to solve forecasting problems.In this study,we propose a novel hybrid deep learning model namely the YOLOv9_ConvLSTM that integrates YOLOv9,ConvLSTM,and linear interpolation to predict reservoir water levels.It utilizes data from Sentinel-2 satellite images,generated from visible spectrum bands(Red-Blue-Green)to reconstruct true-color reservoir images.Adam is used as the optimization algorithm with the loss function being MSE(Mean Squared Error)to evaluate the model’s error during training.We implemented and validated the proposed model using Sentinel-2 satellite imagery for the An Khe reservoir in Vietnam.To assess its performance,we also conducted comparative experiments with other related models,including SegNet_ConvLSTM and UNet_ConvLSTM,on the same dataset.The model performances were validated using k-fold cross-validation and ANOVA analysis.The experimental results demonstrate that the YOLOv9_ConvLSTM model outperforms the compared models.It has been seen that the proposed approach serves as a valuable tool for reservoir water level forecasting using satellite imagery that contributes to effective water resource management.展开更多
Compared with traditional real-time forecasting,this paper proposes a Grey Markov Model(GMM) to forecast the maximum water levels at hydrological stations in the estuary area.The GMM combines the Grey System and Marko...Compared with traditional real-time forecasting,this paper proposes a Grey Markov Model(GMM) to forecast the maximum water levels at hydrological stations in the estuary area.The GMM combines the Grey System and Markov theory into a higher precision model.The GMM takes advantage of the Grey System to predict the trend values and uses the Markov theory to forecast fluctuation values,and thus gives forecast results involving two aspects of information.The procedure for forecasting annul maximum water levels with the GMM contains five main steps:1) establish the GM(1,1) model based on the data series;2) estimate the trend values;3) establish a Markov Model based on relative error series;4) modify the relative errors caused in step 2,and then obtain the relative errors of the second order estimation;5) compare the results with measured data and estimate the accuracy.The historical water level records(from 1960 to 1992) at Yuqiao Hydrological Station in the estuary area of the Haihe River near Tianjin,China are utilized to calibrate and verify the proposed model according to the above steps.Every 25 years' data are regarded as a hydro-sequence.Eight groups of simulated results show reasonable agreement between the predicted values and the measured data.The GMM is also applied to the 10 other hydrological stations in the same estuary.The forecast results for all of the hydrological stations are good or acceptable.The feasibility and effectiveness of this new forecasting model have been proved in this paper.展开更多
By using the durative rainstorm data in South China during May-early June in 2010,the forecast characteristics of K index and low level jet were analyzed.The results found that K2 had the good indication,advancement a...By using the durative rainstorm data in South China during May-early June in 2010,the forecast characteristics of K index and low level jet were analyzed.The results found that K2 had the good indication,advancement and relativity on the intensity and falling zone forecast of regional rainstorm in future 24 h,and the positive relative coefficient reached 0.987.The low level jet also had the same advancement and indication significance on the intensity and influence scope of regional rainstorm in 24 h in the future,and the relative coefficient reached above 0.8.K2 and the low level jet were selected as the main factors,and the basic conceptual model of rainstorm falling zone was established.The model has passed the computer program and realized the business automation.K2 provided the important basis for the forecast of rainstorm intensity and falling zone.展开更多
Stochastic modelling of hydrological time series with insufficient length and data gaps is a serious challenge since these problems significantly affect the reliability of statistical models predicting and forecasting...Stochastic modelling of hydrological time series with insufficient length and data gaps is a serious challenge since these problems significantly affect the reliability of statistical models predicting and forecasting skills.In this paper,we proposed a method for searching the seasonal autoregressive integrated moving average(SARIMA)model parameters to predict the behavior of groundwater time series affected by the issues mentioned.Based on the analysis of statistical indices,8 stations among 44 available within the Campania region(Italy)have been selected as the highest quality measurements.Different SARIMA models,with different autoregressive,moving average and differentiation orders had been used.By reviewing the criteria used to determine the consistency and goodness-of-fit of the model,it is revealed that the model with specific combination of parameters,SARIMA(0,1,3)(0,1,2)_(12),has a high R^(2) value,larger than 92%,for each of the 8 selected stations.The same model has also good performances for what concern the forecasting skills,with an average NSE of about 96%.Therefore,this study has the potential to provide a new horizon for the simulation and reconstruction of groundwater time series within the investigated area.展开更多
The rise of tidal level in tidal reaches induced by sea-level rise has a large impact on flood control and water supply for the regions around the estuary. This paper focuses on the variations of tidal level response ...The rise of tidal level in tidal reaches induced by sea-level rise has a large impact on flood control and water supply for the regions around the estuary. This paper focuses on the variations of tidal level response along the tidal reaches in the Yangtze Estuary, as well as the impacts of upstream discharge on tidal level response, due to the sea-level rise of the East China Sea. Based on the Topex/Poseidon altimeter data obtained during the period 1993-2005, a stochastic dynamic analysis was performed and a forecast model was run to predict the sea-level rise of the East China Sea. Two- dimensional hydrodynamic numerical models downscaling from the East China Sea to estuarine areas were implemented to analyze the rise of tidal level along the tidal reaches. In response to the sea-level rise, the tidal wave characteristics change slightly in nearshore areas outside the estuaries, involving the tidal range and the duration of flood and ebb tide. The results show that the rise of tidal level in the tidal reaches due to the sea-level rise has upstream decreasing trends. The step between the stations of Zhangjiagang and Shiyiwei divides the tidal reaches into two parts, in which the tidal level response declines slightly. The rise of tidal level is 1-2.5 mm/a in the upper part, and 4-6 mm/a in the lower part. The stations of Jiangyin and Yanglin, as an example of the upper part and the lower part respectively, are extracted to analyze the impacts of upstream discharge on tidal level response to the sea-level rise. The relation between the rise of tidal level and the upstream discharge can be fitted well with a quadratic fimction in the upper part. However, the relation is too complicated to be fitted in the lower part because of the tide dominance. For comparison purposes, hourly tidal level observations at the stations of Xuliujing and Yanglin during the period 1993-2009 are adopted. In order to uniform the influence of upstream discharge on tidal level for a certain day each year, the hourly tidal level observations are corrected by the correlation between the increment of tidal level and the increment of daily mean upstream discharge. The rise of annual mean tidal level is evaluated. The resulting rise of tidal level at the stations of Xuliujing and Yanglin is 3.0 mm/a and 6.6 mm/a respectively, close to the rise of 5 mm/a according to the proposed relation between the rise of tidal level and the upstream discharge.展开更多
基金funded by International School,Vietnam National University,Hanoi(VNU-IS)under project number CS.2023-10.
文摘Global climate change,along with the rapid increase of the population,has put significant pressure on water security.A water reservoir is an effective solution for adjusting and ensuring water supply.In particular,the reservoir water level is an essential physical indicator for the reservoirs.Forecasting the reservoir water level effectively assists the managers in making decisions and plans related to reservoir management policies.In recent years,deep learning models have been widely applied to solve forecasting problems.In this study,we propose a novel hybrid deep learning model namely the YOLOv9_ConvLSTM that integrates YOLOv9,ConvLSTM,and linear interpolation to predict reservoir water levels.It utilizes data from Sentinel-2 satellite images,generated from visible spectrum bands(Red-Blue-Green)to reconstruct true-color reservoir images.Adam is used as the optimization algorithm with the loss function being MSE(Mean Squared Error)to evaluate the model’s error during training.We implemented and validated the proposed model using Sentinel-2 satellite imagery for the An Khe reservoir in Vietnam.To assess its performance,we also conducted comparative experiments with other related models,including SegNet_ConvLSTM and UNet_ConvLSTM,on the same dataset.The model performances were validated using k-fold cross-validation and ANOVA analysis.The experimental results demonstrate that the YOLOv9_ConvLSTM model outperforms the compared models.It has been seen that the proposed approach serves as a valuable tool for reservoir water level forecasting using satellite imagery that contributes to effective water resource management.
基金supported by the National Natural Science Foundation of China (50879085)the Program for New Century Excellent Talents in University(NCET-07-0778)the Key Technology Research Project of Dynamic Environmental Flume for Ocean Monitoring Facilities (201005027-4)
文摘Compared with traditional real-time forecasting,this paper proposes a Grey Markov Model(GMM) to forecast the maximum water levels at hydrological stations in the estuary area.The GMM combines the Grey System and Markov theory into a higher precision model.The GMM takes advantage of the Grey System to predict the trend values and uses the Markov theory to forecast fluctuation values,and thus gives forecast results involving two aspects of information.The procedure for forecasting annul maximum water levels with the GMM contains five main steps:1) establish the GM(1,1) model based on the data series;2) estimate the trend values;3) establish a Markov Model based on relative error series;4) modify the relative errors caused in step 2,and then obtain the relative errors of the second order estimation;5) compare the results with measured data and estimate the accuracy.The historical water level records(from 1960 to 1992) at Yuqiao Hydrological Station in the estuary area of the Haihe River near Tianjin,China are utilized to calibrate and verify the proposed model according to the above steps.Every 25 years' data are regarded as a hydro-sequence.Eight groups of simulated results show reasonable agreement between the predicted values and the measured data.The GMM is also applied to the 10 other hydrological stations in the same estuary.The forecast results for all of the hydrological stations are good or acceptable.The feasibility and effectiveness of this new forecasting model have been proved in this paper.
文摘By using the durative rainstorm data in South China during May-early June in 2010,the forecast characteristics of K index and low level jet were analyzed.The results found that K2 had the good indication,advancement and relativity on the intensity and falling zone forecast of regional rainstorm in future 24 h,and the positive relative coefficient reached 0.987.The low level jet also had the same advancement and indication significance on the intensity and influence scope of regional rainstorm in 24 h in the future,and the relative coefficient reached above 0.8.K2 and the low level jet were selected as the main factors,and the basic conceptual model of rainstorm falling zone was established.The model has passed the computer program and realized the business automation.K2 provided the important basis for the forecast of rainstorm intensity and falling zone.
文摘Stochastic modelling of hydrological time series with insufficient length and data gaps is a serious challenge since these problems significantly affect the reliability of statistical models predicting and forecasting skills.In this paper,we proposed a method for searching the seasonal autoregressive integrated moving average(SARIMA)model parameters to predict the behavior of groundwater time series affected by the issues mentioned.Based on the analysis of statistical indices,8 stations among 44 available within the Campania region(Italy)have been selected as the highest quality measurements.Different SARIMA models,with different autoregressive,moving average and differentiation orders had been used.By reviewing the criteria used to determine the consistency and goodness-of-fit of the model,it is revealed that the model with specific combination of parameters,SARIMA(0,1,3)(0,1,2)_(12),has a high R^(2) value,larger than 92%,for each of the 8 selected stations.The same model has also good performances for what concern the forecasting skills,with an average NSE of about 96%.Therefore,this study has the potential to provide a new horizon for the simulation and reconstruction of groundwater time series within the investigated area.
基金supported by the State Key Development Program of Basic Research of China (Grant No. 2010CB429001)the Special Fund of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering (Grant No. 2009586812)the Priority Academic Program Development of Jiangsu Higher Education Institutions (Coastal Development Conservancy) (PAPD)
文摘The rise of tidal level in tidal reaches induced by sea-level rise has a large impact on flood control and water supply for the regions around the estuary. This paper focuses on the variations of tidal level response along the tidal reaches in the Yangtze Estuary, as well as the impacts of upstream discharge on tidal level response, due to the sea-level rise of the East China Sea. Based on the Topex/Poseidon altimeter data obtained during the period 1993-2005, a stochastic dynamic analysis was performed and a forecast model was run to predict the sea-level rise of the East China Sea. Two- dimensional hydrodynamic numerical models downscaling from the East China Sea to estuarine areas were implemented to analyze the rise of tidal level along the tidal reaches. In response to the sea-level rise, the tidal wave characteristics change slightly in nearshore areas outside the estuaries, involving the tidal range and the duration of flood and ebb tide. The results show that the rise of tidal level in the tidal reaches due to the sea-level rise has upstream decreasing trends. The step between the stations of Zhangjiagang and Shiyiwei divides the tidal reaches into two parts, in which the tidal level response declines slightly. The rise of tidal level is 1-2.5 mm/a in the upper part, and 4-6 mm/a in the lower part. The stations of Jiangyin and Yanglin, as an example of the upper part and the lower part respectively, are extracted to analyze the impacts of upstream discharge on tidal level response to the sea-level rise. The relation between the rise of tidal level and the upstream discharge can be fitted well with a quadratic fimction in the upper part. However, the relation is too complicated to be fitted in the lower part because of the tide dominance. For comparison purposes, hourly tidal level observations at the stations of Xuliujing and Yanglin during the period 1993-2009 are adopted. In order to uniform the influence of upstream discharge on tidal level for a certain day each year, the hourly tidal level observations are corrected by the correlation between the increment of tidal level and the increment of daily mean upstream discharge. The rise of annual mean tidal level is evaluated. The resulting rise of tidal level at the stations of Xuliujing and Yanglin is 3.0 mm/a and 6.6 mm/a respectively, close to the rise of 5 mm/a according to the proposed relation between the rise of tidal level and the upstream discharge.
