The Pearl River Estuary(PRE)is one of China’s busiest shipping hubs and fishery production centers,as well as a region with abundant island tourism and wind energy resources,which calls for accurate short-term wind f...The Pearl River Estuary(PRE)is one of China’s busiest shipping hubs and fishery production centers,as well as a region with abundant island tourism and wind energy resources,which calls for accurate short-term wind forecasts.First,this study evaluated three operational numerical models,i.e.,ECMWF-EC,NCEP-GFS,and CMA-GD,for their ability to predict short-term wind speed over the PRE against in-situ observations during 2018-2021.Overall,ECMWF-EC out-performs other models with an average RMSE of 2.24 m s^(-1)and R of 0.57,but the NCEP-GFS performs better in the case of strong winds.Then,various bias correction and multi-model ensemble(MME)methods are used to perform the deterministic post-processing using a local and lead-specific scheme.Two-factor model output statistics(MOS2)is the optimal bias correction method for reducing(increasing)the overall RMSE(R)to 1.62(0.70)m s^(-1),demonstrating the benefits of considering both initial and lead-specific information.Intercomparison of MME results reveals that Multiple linear regression(MLR)presents superior skills,followed by random forest(RF),but it is slightly inferior to MOS2,particularly for the first few forecasting hours.Furthermore,the incorporation of additional features in MLR reduces the overall RMSE to 1.53 m s^(-1)and increases R to 0.74.Similarly,RF presents comparable results,and both outperform MOS2 in terms of correcting their deficiencies at the first few lead hours and limiting the error growth rate.Despite the satisfactory skill of deterministic post-processing techniques,they are unable to achieve a balanced performance between mean and extreme statistics.This highlights the necessity for further development of probabilistic forecasts.展开更多
Freezing and thawing indices are not only of great significance for permafrost research but also are important indicators of the effects of climate change.However,to date,research on ground-surface freezing and thawin...Freezing and thawing indices are not only of great significance for permafrost research but also are important indicators of the effects of climate change.However,to date,research on ground-surface freezing and thawing indices and their relationship with air indices is limited.Based on daily air and ground-surface temperatures collected from 11 meteorological stations in the source region of the Yellow River,the freezing and thawing indices were calculated,and their spatial distribution and trends were analyzed.The air-freezing index(AFI),air-thawing index(ATI),ground surface-freezing index(GFI),ground surface-thawing index(GTI),air thawing-freezing index ratio(Na)and surface ground thawing-freezing index ratio(Ng)were 1554.64,1153.93,1.55,2484.85,850.57℃-days and 3.44,respectively.Altitude affected the spatial distribution of the freezing and thawing indices.As the altitude increased,the freezing indices gradually increased,and the thawing indices and thawing-freezing index ratio decreased.From 1980 to 2014,the AFI and GFI decreased at rates of 8.61 and 11.06℃-days a^(-1),the ATI and GTI increased at 9.65 and 14.53℃-days a^(-1),and Na and Ng significantly increased at 0.21 and 0.79 decade^(-1).Changes in the freezing and thawing indices were associated with increases in the air and ground-surface temperatures.The rates of change of the ground surface freezing and thawing indices were faster than the air ones because the rate of increase of the groundsurface temperature was faster than that of the air and the difference between the ground surface and air increased.The change point of the time series of freezing and thawing indices occurred in 2000–2001.After 2000–2001,the AFI and GFI were lower than before the change point,and the changing trend was lower.The ATI,GTI,Na and Ng during 2001–2014 were higher,with faster rates than before.In addition,the annual thawing indices composed a greater proportion of the mean annual air temperature and mean annual ground surface temperature than the annual freezing indices.This study provides the necessary basis for research on and prediction of permafrost changes,especially changes in the depth of the active permafrost layer,climate change,and possible evolution of the ecological environment over the source region of the Yellow River on the Qinghai-Tibet Plateau.展开更多
Based on analyzing the limitations of the commonly used back-propagation neural network （BPNN）, a wavelet neural network （WNN） is adopted as the nonlinear river channel flood forecasting method replacing the BPNN....Based on analyzing the limitations of the commonly used back-propagation neural network （BPNN）, a wavelet neural network （WNN） is adopted as the nonlinear river channel flood forecasting method replacing the BPNN. The WNN has the characteristics of fast convergence and improved capability of nonlinear approximation. For the purpose of adapting the timevarying characteristics of flood routing, the WNN is coupled with an AR real-time correction model. The AR model is utilized to calculate the forecast error. The coefficients of the AR real-time correction model are dynamically updated by an adaptive fading factor recursive least square（RLS） method. The application of the flood forecasting method in the cross section of Xijiang River at Gaoyao shows its effectiveness.展开更多
Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon...Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon emissions in the Yangtze River Delta(YRD)through path analysis,and to forecast carbon emissions in the YRD from the baseline scenario,factor regulation scenario and integrated scenario to reach the peak.The results show that:(1)Jiangsu's high carbon emission pattern is the main reason for the YRD hindering the synergistic regulation of carbon emissions.(2)Human factors,institutional factors and economic growth factors can all contribute to carbon emissions in the YRD region,while technological and industrial factors can generally suppress carbon emissions in the YRD region.(3)Under the capital regulation scenario,the YRD region has the highest level of carbon emission synergy,with Jiangsu reaching its peak five years earlier.Under the balanced regulation scenario,the YRD region as a whole,Jiangsu,Zhejiang and Anhui reach the peak as scheduled.展开更多
A combination of the rainfall-runoff module of the Xin’anjiang model, the Muskingum routing method, the water stage simulating hydrologic method, the diffusion wave nonlinear water stage method, and the real-time err...A combination of the rainfall-runoff module of the Xin’anjiang model, the Muskingum routing method, the water stage simulating hydrologic method, the diffusion wave nonlinear water stage method, and the real-time error correction method is applied to the real-time flood forecasting and regulation of the Huai River with flood diversion and retarding areas. The Xin’anjiang model is used to forecast the flood discharge hydrograph of the upstream and tributary. The flood routing of the main channel and flood diversion areas is based on the Muskingum method. The water stage of the downstream boundary condition is calculated with the water stage simulating hydrologic method and the water stages of each cross section are calculated from downstream to upstream with the diffusion wave nonlinear water stage method. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The faded-memory forgetting factor least square of error series is used as the real-time error correction method for forecasting discharge and water stage. As an example, the combined models were applied to flood forecasting and regulation of the upper reaches of the Huai River above Lutaizi during the 2007 flood season. The forecast achieves a high accuracy and the results show that the combined models provide a scientific way of flood forecasting and regulation for a complex watershed with flood diversion and retarding areas.展开更多
In this study, a 47-day regional climate simulation of the heavy rainfall in the Yangtze-Huai River Basin during the summer of 2003 was conducted using the Weather Research and Forecast （WRY） model. The simulation r...In this study, a 47-day regional climate simulation of the heavy rainfall in the Yangtze-Huai River Basin during the summer of 2003 was conducted using the Weather Research and Forecast （WRY） model. The simulation reproduces reasonably well the evolution of the rainfall during the study period＇s three successive rainy phases, especially the frequent heavy rainfall events occurring in the Huai River Basin. The model captures the major rainfall peak observed by the monitoring stations in the morning. Another peak appears later than that shown by the observations. In addition, the simulation realistically captures not only the evolution of the low-level winds but also the characteristics of their diurnal variation. The strong southwesterly （low-level jet, LLJ） wind speed increases beginning in the early evening and reaches a peak in the morning; it then gradually decreases until the afternoon. The intense LLJ forms a strong convergent circulation pattern in the early morning along the Yangtze-Huai River Basin. This pattern partly explains the rainfall peak observed at this time. This study furnishes a basis for the further analysis of the mechanisms of evolution of the LLJ and for the further study of the interactions between the LLJ and rainfall.展开更多
The research of coupling WRF （Weather Research and Forecasting Model） with a land surface model is enhanced to explore the interaction of the atmosphere and land surface; however, regional applicability of WRF model...The research of coupling WRF （Weather Research and Forecasting Model） with a land surface model is enhanced to explore the interaction of the atmosphere and land surface; however, regional applicability of WRF model is questioned. In order to do the validation of WRF model on simulating forcing data for the Heihe River Basin, daily meteorological observation data from 15 stations of CMA （China Meteorological Administration） and hourly meteorological observation data from seven sites of WATER （Watershed Airborne Telemetry Experimental Research） are used to compare with WRF simulations, with a time range of a whole year for 2008. Results show that the average MBE （Mean Bias Error） of daily 2-m surface temperature, surface pressure, 2-m relative humidity and 10-m wind speed were -0.19 ℃, -4.49 hPa, 4.08% and 0.92 m/s, the average RMSE （Root Mean Square Error） of them were 2.11 ℃, 5.37 hPa, 9.55% and 1.73 m/s, and the average R （correlation coefficient） of them were 0.99, 0.98, 0.80 and 0.55, respectively. The average MBE of hourly 2-m surface temperature, surface pressure, 2-m relative humidity, 10-m wind speed, downward shortwave radiation and downward longwave were-0.16 ℃,-6.62 hPa,-5.14%, 0.26 m/s, 33.0 W/m^2 and-6.44 W/m^2, the average RMSE of them were 2.62 ℃, 17.10 hPa, 20.71%, 2.46 m/s, 152.9 W/m^2 and 53.5 W/m^2, and the average R of them were 0.96, 0.97, 0.70, 0.26, 0.91 and 0.60, respectively. Thus, the following conclusions were obtained： （1） regardless of daily or hourly validation, WRF model simulations of 2-m surface temperature, surface pressure and relative humidity are more reliable, especially for 2-m surface air temperature and surface pressure, the values of MBE were small and R were more than 0.96; （2） the WRF simulating downward shortwave radiation was relatively good, the average R between WRF simulation and hourly observation data was above 0.9, and the average R of downward longwave radiation was 0.6; （3） both wind speed and rainfall simulated from WRF model did not agree well with observation data.展开更多
River ice is a natural phenomenon in cold regions, influenced by meteorology, geomorphology, and hydraulic conditions. River ice processes involve complex interactions between hydrodynamic, mechanical, and thermal pro...River ice is a natural phenomenon in cold regions, influenced by meteorology, geomorphology, and hydraulic conditions. River ice processes involve complex interactions between hydrodynamic, mechanical, and thermal processes, and they are also influenced by weather and hydrologic conditions. Because natural rivers are serpentine, with bends, narrows, and straight reaches, the commonly-used one-dimensional river ice models and two-dimensional models based on the rectangular Cartesian coordinates are incapable of simulating the physical phenomena accurately. In order to accurately simulate the complicated river geometry and overcome the difficulties of numerical simulation resulting from both complex boundaries and differences between length and width scales, a two-dimensional river ice numerical model based on a boundary-fitted coordinate transformation method was developed. The presented model considers the influence of the frazil ice accumulation under ice cover and the shape of the leading edge of ice cover during the freezing process. The model is capable of determining the velocity field, the distribution of water temperature, the concentration distribution of frazil ice, the transport of floating ice, the progression, stability, and thawing of ice cover, and the transport, accumulation, and erosion of ice under ice cover. A MacCormack scheme was used to solve the equations numerically. The model was validated with field observations from the Hequ Reach of the Yellow River. Comparison of simulation results with field data indicates that the model is capable of simulating the river ice process with high accuracy.展开更多
Taking the nonlinear nature of runoff system into account,and combining auto-regression method and multi-regression method,a Nonlinear Mixed Regression Model (NMR) was established to analyze the impact of temperature ...Taking the nonlinear nature of runoff system into account,and combining auto-regression method and multi-regression method,a Nonlinear Mixed Regression Model (NMR) was established to analyze the impact of temperature and precipitation changes on annual river runoff process. The model was calibrated and verified by using BP neural network with observed meteorological and runoff data from Daiying Hydrological Station in the Chaohe River of Hebei Province in 1956–2000. Compared with auto-regression model,linear multi-regression model and linear mixed regression model,NMR can improve forecasting precision remarkably. Therefore,the simulation of climate change scenarios was carried out by NMR. The results show that the nonlinear mixed regression model can simulate annual river runoff well.展开更多
Changes in ground surface thermal regimes play a vital role in surface and subsurface hydrology, ecosystem diversity and productivity, and global thermal, water and carbon budgets as well as climate change. Estimating...Changes in ground surface thermal regimes play a vital role in surface and subsurface hydrology, ecosystem diversity and productivity, and global thermal, water and carbon budgets as well as climate change. Estimating spring, summer, autumn and winter air temperatures and mean annual air temperature（MAAT） from 1960 through 2008 over the Heihe River Basin reveals a statistically significant trend of 0.31 °C/decade, 0.28 °C/decade, 0.37 °C/decade, 0.50 °C/decade, and 0.37 °C /decade, respectively. The averaged time series of mean annual ground surface temperature（MAGST） and maximum annual ground surface temperature（MaxAGST） for 1972–2006 over the basin indicates a statistically significant trend of 0.58 °C/decade and 1.27 °C/decade, respectively. The minimum annual ground surface temperature（MinAGST） in the same period remains unchanged as a whole. Estimating surface freezing/thawing index as well as the ratio of freezing index to thawing index（RFT） in the period between 1959 and 2006 over the basin indicates a statistically significant trend of-42.5 °C-day/decade, 85.4 °C-day/decade and-0.018/decade, respectively.展开更多
The active-layer soils overlying the permafrost are the most thermodynamically active zone of rock or soil and play important roles in the earth-atmosphere energy system. The processes of thawing and freezing and thei...The active-layer soils overlying the permafrost are the most thermodynamically active zone of rock or soil and play important roles in the earth-atmosphere energy system. The processes of thawing and freezing and their associated complex hydrothermal coupling can significantly affect variation in mean annual temperatures and the formation of ground ice in permafrost regions. Using soil-temperature and-moisture data obtained from the active layer between September 2011 and October 2014 in the permafrost region of the Nanweng'he River in the Da Xing'anling Mountains, the freeze-thaw characteristics of the permafrost were studied. Based on analysis of ground-temperature variation and hydrothermal transport characteristics, the thawing and freezing processes of the active layer were divided into three stages:(1) autumn-winter freezing,(2) winter freeze-up, and(3) spring-summer thawing. Variations in the soil temperature and moisture were analyzed during each stage of the freeze-thaw process, and the effects of the soil moisture and ground vegetation on the freeze-thaw are discussed in this paper. The study's results show that thawing in the active layer was unidirectional, while the ground freezing was bidirectional(upward from the bottom of the active layer and downward from the ground surface).During the annual freeze-thaw cycle, the migration of soil moisture had different characteristics at different stages. In general, during a freezing-thawing cycle, the soil-water molecules migrate downward, i.e., soil moisture transports from the entire active layer to the upper limit of the permafrost. In the meantime, freeze-thaw in the active layer can be significantly affected by the soil-moisture content and vegetation.展开更多
Detecting near-surface soil freeze-thaw cycles in high-altitude cold regions is important for understanding the Earth＇s surface system, but such studies are rare. In this study, we detected the spatial-temporal varia...Detecting near-surface soil freeze-thaw cycles in high-altitude cold regions is important for understanding the Earth＇s surface system, but such studies are rare. In this study, we detected the spatial-temporal variations in near-surface soil freeze-thaw cycles in the source region of the Yellow River（SRYR） during the period 2002–2011 based on data from the Advanced Microwave Scanning Radiometer for the Earth Observing System（AMSR-E）. Moreover, the trends of onset dates and durations of the soil freeze-thaw cycles under different stages were also analyzed. Results showed that the thresholds of daytime and nighttime brightness temperatures of the freeze-thaw algorithm for the SRYR were 257.59 and 261.28 K, respectively. At the spatial scale, the daily frozen surface（DFS） area and the daily surface freeze-thaw cycle surface（DFTS） area decreased by 0.08% and 0.25%, respectively, and the daily thawed surface（DTS） area increased by 0.36%. At the temporal scale, the dates of the onset of thawing and complete thawing advanced by 3.10（±1.4） and 2.46（±1.4） days, respectively; and the dates of the onset of freezing and complete freezing were delayed by 0.9（±1.4） and 1.6（±1.1） days, respectively. The duration of thawing increased by 0.72（±0.21） day/a and the duration of freezing decreased by 0.52（±0.26） day/a. In conclusion, increases in the annual minimum temperature and winter air temperature are the main factors for the advanced thawing and delayed freezing and for the increase in the duration of thawing and the decrease in the duration of freezing in the SRYR.展开更多
The combined effects of global warming and the urban heat islands exacerbate the risk of urban heat stress. It is crucial to implement effective cooling measures in urban areas to improve the comfort of the thermal en...The combined effects of global warming and the urban heat islands exacerbate the risk of urban heat stress. It is crucial to implement effective cooling measures in urban areas to improve the comfort of the thermal environment. In this study, the Weather Research and Forecasting Model(WRF), coupled with a single-layer Urban Canopy Model(UCM), was used to study the impact of heat mitigation strategies. In addition, a 5-km resolution land-cover dataset for China(ChinaLC), which is based on satellite remote sensing data, was adjusted and used, and 18 groups of numerical experiments were designed, to increase the albedo and vegetation fraction of roof/ground parameters. The experiments were conducted for four heatwave events that occurred in the summer of 2013 in the Yangtze River Delta urban agglomeration of China. The simulated results demonstrated that, for the single roof/ground schemes, the mitigation effects were directly proportional to the albedo and greening. Among all the experimental schemes, the superposed schemes presented better cooling effects. For the ground greening scheme, with similar net radiation flux and latent heat flux, its storage heat was lower than that of the roof greening scheme, resulting in more energy flux into the atmosphere, and its daytime cooling effect was not as good as that of the roof greening scheme. In terms of human thermal comfort(HTC), the improvement achieved by the ground greening scheme was better than any other single roof/ground schemes, because the increase in the relative humidity was small. The comprehensive evaluation of the mitigation effects of different schemes on the thermal environment presented in this paper provides a theoretical basis for improving the urban environment through rational urban planning and construction.展开更多
Channel roughness is considered as the most sensitive parameter in development of hydraulic models for flood forecasting and flood inundation mapping. Hence, it is essential to calibrate the channel roughness coeffici...Channel roughness is considered as the most sensitive parameter in development of hydraulic models for flood forecasting and flood inundation mapping. Hence, it is essential to calibrate the channel roughness coefficient (Mannnig’s “n” value) for various river reaches through simulation of floods. In the present study it is attempted to calibrate and validate Mannnig’s “n” value using HEC-RAS for Mahanadi Riverin Odisha (India). For calibration of Mannnig’s “n” value, the floods for the years 2001 and 2003 have been considered. The calibrated model, in terms of channel roughness, has been used to simulate the flood for year2006 inthe same river reach. The performance of the calibrated and validated HEC-RAS based model has been tested using Nash and Sutcliffe efficiency. It is concluded from the simulation study that optimum Mannnig’s “n” value that can be used effectively for Khairmal to Barmul reach of Mahanadi Riveris 0.029. It is also verified that the peak flood discharge and time to reach peak value computed using Mannnig’s “n” of 0.029 showed only an error of 5.42% as compared with the observed flood data of year 2006.展开更多
基金Science and Technology Research Project of Guangdong Meteorological Service(GRMC2021M19,GRMC2022Q16,GRMC2023M29)。
文摘The Pearl River Estuary(PRE)is one of China’s busiest shipping hubs and fishery production centers,as well as a region with abundant island tourism and wind energy resources,which calls for accurate short-term wind forecasts.First,this study evaluated three operational numerical models,i.e.,ECMWF-EC,NCEP-GFS,and CMA-GD,for their ability to predict short-term wind speed over the PRE against in-situ observations during 2018-2021.Overall,ECMWF-EC out-performs other models with an average RMSE of 2.24 m s^(-1)and R of 0.57,but the NCEP-GFS performs better in the case of strong winds.Then,various bias correction and multi-model ensemble(MME)methods are used to perform the deterministic post-processing using a local and lead-specific scheme.Two-factor model output statistics(MOS2)is the optimal bias correction method for reducing(increasing)the overall RMSE(R)to 1.62(0.70)m s^(-1),demonstrating the benefits of considering both initial and lead-specific information.Intercomparison of MME results reveals that Multiple linear regression(MLR)presents superior skills,followed by random forest(RF),but it is slightly inferior to MOS2,particularly for the first few forecasting hours.Furthermore,the incorporation of additional features in MLR reduces the overall RMSE to 1.53 m s^(-1)and increases R to 0.74.Similarly,RF presents comparable results,and both outperform MOS2 in terms of correcting their deficiencies at the first few lead hours and limiting the error growth rate.Despite the satisfactory skill of deterministic post-processing techniques,they are unable to achieve a balanced performance between mean and extreme statistics.This highlights the necessity for further development of probabilistic forecasts.
基金funded by the National Science and Technology Support Plan(2015BAD07B02)
文摘Freezing and thawing indices are not only of great significance for permafrost research but also are important indicators of the effects of climate change.However,to date,research on ground-surface freezing and thawing indices and their relationship with air indices is limited.Based on daily air and ground-surface temperatures collected from 11 meteorological stations in the source region of the Yellow River,the freezing and thawing indices were calculated,and their spatial distribution and trends were analyzed.The air-freezing index(AFI),air-thawing index(ATI),ground surface-freezing index(GFI),ground surface-thawing index(GTI),air thawing-freezing index ratio(Na)and surface ground thawing-freezing index ratio(Ng)were 1554.64,1153.93,1.55,2484.85,850.57℃-days and 3.44,respectively.Altitude affected the spatial distribution of the freezing and thawing indices.As the altitude increased,the freezing indices gradually increased,and the thawing indices and thawing-freezing index ratio decreased.From 1980 to 2014,the AFI and GFI decreased at rates of 8.61 and 11.06℃-days a^(-1),the ATI and GTI increased at 9.65 and 14.53℃-days a^(-1),and Na and Ng significantly increased at 0.21 and 0.79 decade^(-1).Changes in the freezing and thawing indices were associated with increases in the air and ground-surface temperatures.The rates of change of the ground surface freezing and thawing indices were faster than the air ones because the rate of increase of the groundsurface temperature was faster than that of the air and the difference between the ground surface and air increased.The change point of the time series of freezing and thawing indices occurred in 2000–2001.After 2000–2001,the AFI and GFI were lower than before the change point,and the changing trend was lower.The ATI,GTI,Na and Ng during 2001–2014 were higher,with faster rates than before.In addition,the annual thawing indices composed a greater proportion of the mean annual air temperature and mean annual ground surface temperature than the annual freezing indices.This study provides the necessary basis for research on and prediction of permafrost changes,especially changes in the depth of the active permafrost layer,climate change,and possible evolution of the ecological environment over the source region of the Yellow River on the Qinghai-Tibet Plateau.
基金The National Natural Science Foundation of China(No.50479017).
文摘Based on analyzing the limitations of the commonly used back-propagation neural network （BPNN）, a wavelet neural network （WNN） is adopted as the nonlinear river channel flood forecasting method replacing the BPNN. The WNN has the characteristics of fast convergence and improved capability of nonlinear approximation. For the purpose of adapting the timevarying characteristics of flood routing, the WNN is coupled with an AR real-time correction model. The AR model is utilized to calculate the forecast error. The coefficients of the AR real-time correction model are dynamically updated by an adaptive fading factor recursive least square（RLS） method. The application of the flood forecasting method in the cross section of Xijiang River at Gaoyao shows its effectiveness.
文摘Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon emissions in the Yangtze River Delta(YRD)through path analysis,and to forecast carbon emissions in the YRD from the baseline scenario,factor regulation scenario and integrated scenario to reach the peak.The results show that:(1)Jiangsu's high carbon emission pattern is the main reason for the YRD hindering the synergistic regulation of carbon emissions.(2)Human factors,institutional factors and economic growth factors can all contribute to carbon emissions in the YRD region,while technological and industrial factors can generally suppress carbon emissions in the YRD region.(3)Under the capital regulation scenario,the YRD region has the highest level of carbon emission synergy,with Jiangsu reaching its peak five years earlier.Under the balanced regulation scenario,the YRD region as a whole,Jiangsu,Zhejiang and Anhui reach the peak as scheduled.
基金supported by the National Natural Science Foundation of China (Grant No 50479017)the Program for Changjiang Scholars and Innovative Research Teams in Universities (Grant No IRT071)
文摘A combination of the rainfall-runoff module of the Xin’anjiang model, the Muskingum routing method, the water stage simulating hydrologic method, the diffusion wave nonlinear water stage method, and the real-time error correction method is applied to the real-time flood forecasting and regulation of the Huai River with flood diversion and retarding areas. The Xin’anjiang model is used to forecast the flood discharge hydrograph of the upstream and tributary. The flood routing of the main channel and flood diversion areas is based on the Muskingum method. The water stage of the downstream boundary condition is calculated with the water stage simulating hydrologic method and the water stages of each cross section are calculated from downstream to upstream with the diffusion wave nonlinear water stage method. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The faded-memory forgetting factor least square of error series is used as the real-time error correction method for forecasting discharge and water stage. As an example, the combined models were applied to flood forecasting and regulation of the upper reaches of the Huai River above Lutaizi during the 2007 flood season. The forecast achieves a high accuracy and the results show that the combined models provide a scientific way of flood forecasting and regulation for a complex watershed with flood diversion and retarding areas.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX2-YW-Q11-04)the National High Technology Research and Development Program of China (863 Program, Grant No. 2010AA012304)+2 种基金the National Natural Science Foundation of China (Grant No. 40905049)the LASG State Key Laboratory special fundthe LASG free exploration fund
文摘In this study, a 47-day regional climate simulation of the heavy rainfall in the Yangtze-Huai River Basin during the summer of 2003 was conducted using the Weather Research and Forecast （WRY） model. The simulation reproduces reasonably well the evolution of the rainfall during the study period＇s three successive rainy phases, especially the frequent heavy rainfall events occurring in the Huai River Basin. The model captures the major rainfall peak observed by the monitoring stations in the morning. Another peak appears later than that shown by the observations. In addition, the simulation realistically captures not only the evolution of the low-level winds but also the characteristics of their diurnal variation. The strong southwesterly （low-level jet, LLJ） wind speed increases beginning in the early evening and reaches a peak in the morning; it then gradually decreases until the afternoon. The intense LLJ forms a strong convergent circulation pattern in the early morning along the Yangtze-Huai River Basin. This pattern partly explains the rainfall peak observed at this time. This study furnishes a basis for the further analysis of the mechanisms of evolution of the LLJ and for the further study of the interactions between the LLJ and rainfall.
基金supported by grant from the National High Technology Research and Development Program (863) of China (Grant No.2009AA122104)grants from the National Natural Science Foundation of China (No.40901202, No.40925004)+1 种基金supported by the CAS Action Plan for West Development Program (Grant No.KZCX2-XB2-09)Chinese State Key Basic Research Project (Grant No.2007CB714400)
文摘The research of coupling WRF （Weather Research and Forecasting Model） with a land surface model is enhanced to explore the interaction of the atmosphere and land surface; however, regional applicability of WRF model is questioned. In order to do the validation of WRF model on simulating forcing data for the Heihe River Basin, daily meteorological observation data from 15 stations of CMA （China Meteorological Administration） and hourly meteorological observation data from seven sites of WATER （Watershed Airborne Telemetry Experimental Research） are used to compare with WRF simulations, with a time range of a whole year for 2008. Results show that the average MBE （Mean Bias Error） of daily 2-m surface temperature, surface pressure, 2-m relative humidity and 10-m wind speed were -0.19 ℃, -4.49 hPa, 4.08% and 0.92 m/s, the average RMSE （Root Mean Square Error） of them were 2.11 ℃, 5.37 hPa, 9.55% and 1.73 m/s, and the average R （correlation coefficient） of them were 0.99, 0.98, 0.80 and 0.55, respectively. The average MBE of hourly 2-m surface temperature, surface pressure, 2-m relative humidity, 10-m wind speed, downward shortwave radiation and downward longwave were-0.16 ℃,-6.62 hPa,-5.14%, 0.26 m/s, 33.0 W/m^2 and-6.44 W/m^2, the average RMSE of them were 2.62 ℃, 17.10 hPa, 20.71%, 2.46 m/s, 152.9 W/m^2 and 53.5 W/m^2, and the average R of them were 0.96, 0.97, 0.70, 0.26, 0.91 and 0.60, respectively. Thus, the following conclusions were obtained： （1） regardless of daily or hourly validation, WRF model simulations of 2-m surface temperature, surface pressure and relative humidity are more reliable, especially for 2-m surface air temperature and surface pressure, the values of MBE were small and R were more than 0.96; （2） the WRF simulating downward shortwave radiation was relatively good, the average R between WRF simulation and hourly observation data was above 0.9, and the average R of downward longwave radiation was 0.6; （3） both wind speed and rainfall simulated from WRF model did not agree well with observation data.
基金supported by the National Natural Science Foundation of China(Grant No.50579030)
文摘River ice is a natural phenomenon in cold regions, influenced by meteorology, geomorphology, and hydraulic conditions. River ice processes involve complex interactions between hydrodynamic, mechanical, and thermal processes, and they are also influenced by weather and hydrologic conditions. Because natural rivers are serpentine, with bends, narrows, and straight reaches, the commonly-used one-dimensional river ice models and two-dimensional models based on the rectangular Cartesian coordinates are incapable of simulating the physical phenomena accurately. In order to accurately simulate the complicated river geometry and overcome the difficulties of numerical simulation resulting from both complex boundaries and differences between length and width scales, a two-dimensional river ice numerical model based on a boundary-fitted coordinate transformation method was developed. The presented model considers the influence of the frazil ice accumulation under ice cover and the shape of the leading edge of ice cover during the freezing process. The model is capable of determining the velocity field, the distribution of water temperature, the concentration distribution of frazil ice, the transport of floating ice, the progression, stability, and thawing of ice cover, and the transport, accumulation, and erosion of ice under ice cover. A MacCormack scheme was used to solve the equations numerically. The model was validated with field observations from the Hequ Reach of the Yellow River. Comparison of simulation results with field data indicates that the model is capable of simulating the river ice process with high accuracy.
基金Under the auspices of National Natural Science Foundation of China (No. 50809004)
文摘Taking the nonlinear nature of runoff system into account,and combining auto-regression method and multi-regression method,a Nonlinear Mixed Regression Model (NMR) was established to analyze the impact of temperature and precipitation changes on annual river runoff process. The model was calibrated and verified by using BP neural network with observed meteorological and runoff data from Daiying Hydrological Station in the Chaohe River of Hebei Province in 1956–2000. Compared with auto-regression model,linear multi-regression model and linear mixed regression model,NMR can improve forecasting precision remarkably. Therefore,the simulation of climate change scenarios was carried out by NMR. The results show that the nonlinear mixed regression model can simulate annual river runoff well.
基金supported by the Chinese Academy of Sciences Key Research Program (No. KZZD-EW-13)the Natural Science Foundation of China (Nos. 91025013, 91325202)+1 种基金the State Key Laboratory of Frozen Soil Engineering (No. SKLFSE-ZY-06), CASthe Major Research Plan of the National Natural Science Foundation of China (No. 2013CBA01802)
文摘Changes in ground surface thermal regimes play a vital role in surface and subsurface hydrology, ecosystem diversity and productivity, and global thermal, water and carbon budgets as well as climate change. Estimating spring, summer, autumn and winter air temperatures and mean annual air temperature（MAAT） from 1960 through 2008 over the Heihe River Basin reveals a statistically significant trend of 0.31 °C/decade, 0.28 °C/decade, 0.37 °C/decade, 0.50 °C/decade, and 0.37 °C /decade, respectively. The averaged time series of mean annual ground surface temperature（MAGST） and maximum annual ground surface temperature（MaxAGST） for 1972–2006 over the basin indicates a statistically significant trend of 0.58 °C/decade and 1.27 °C/decade, respectively. The minimum annual ground surface temperature（MinAGST） in the same period remains unchanged as a whole. Estimating surface freezing/thawing index as well as the ratio of freezing index to thawing index（RFT） in the period between 1959 and 2006 over the basin indicates a statistically significant trend of-42.5 °C-day/decade, 85.4 °C-day/decade and-0.018/decade, respectively.
基金supported by the National Natural Science Foundation of China(Grant No.41401081)the State Key Laboratory of Frozen Soils Engineering(Grant Nos.SKLFSE-ZT-41,SKLFSE-ZT-20and SKLFSE-ZT-12)
文摘The active-layer soils overlying the permafrost are the most thermodynamically active zone of rock or soil and play important roles in the earth-atmosphere energy system. The processes of thawing and freezing and their associated complex hydrothermal coupling can significantly affect variation in mean annual temperatures and the formation of ground ice in permafrost regions. Using soil-temperature and-moisture data obtained from the active layer between September 2011 and October 2014 in the permafrost region of the Nanweng'he River in the Da Xing'anling Mountains, the freeze-thaw characteristics of the permafrost were studied. Based on analysis of ground-temperature variation and hydrothermal transport characteristics, the thawing and freezing processes of the active layer were divided into three stages:(1) autumn-winter freezing,(2) winter freeze-up, and(3) spring-summer thawing. Variations in the soil temperature and moisture were analyzed during each stage of the freeze-thaw process, and the effects of the soil moisture and ground vegetation on the freeze-thaw are discussed in this paper. The study's results show that thawing in the active layer was unidirectional, while the ground freezing was bidirectional(upward from the bottom of the active layer and downward from the ground surface).During the annual freeze-thaw cycle, the migration of soil moisture had different characteristics at different stages. In general, during a freezing-thawing cycle, the soil-water molecules migrate downward, i.e., soil moisture transports from the entire active layer to the upper limit of the permafrost. In the meantime, freeze-thaw in the active layer can be significantly affected by the soil-moisture content and vegetation.
基金supported by the National Science and Technology Support Plan of China (2015BAD07B02)
文摘Detecting near-surface soil freeze-thaw cycles in high-altitude cold regions is important for understanding the Earth＇s surface system, but such studies are rare. In this study, we detected the spatial-temporal variations in near-surface soil freeze-thaw cycles in the source region of the Yellow River（SRYR） during the period 2002–2011 based on data from the Advanced Microwave Scanning Radiometer for the Earth Observing System（AMSR-E）. Moreover, the trends of onset dates and durations of the soil freeze-thaw cycles under different stages were also analyzed. Results showed that the thresholds of daytime and nighttime brightness temperatures of the freeze-thaw algorithm for the SRYR were 257.59 and 261.28 K, respectively. At the spatial scale, the daily frozen surface（DFS） area and the daily surface freeze-thaw cycle surface（DFTS） area decreased by 0.08% and 0.25%, respectively, and the daily thawed surface（DTS） area increased by 0.36%. At the temporal scale, the dates of the onset of thawing and complete thawing advanced by 3.10（±1.4） and 2.46（±1.4） days, respectively; and the dates of the onset of freezing and complete freezing were delayed by 0.9（±1.4） and 1.6（±1.1） days, respectively. The duration of thawing increased by 0.72（±0.21） day/a and the duration of freezing decreased by 0.52（±0.26） day/a. In conclusion, increases in the annual minimum temperature and winter air temperature are the main factors for the advanced thawing and delayed freezing and for the increase in the duration of thawing and the decrease in the duration of freezing in the SRYR.
基金Supported by the National Natural Science Foundation of China (42021004 and 42175032)。
文摘The combined effects of global warming and the urban heat islands exacerbate the risk of urban heat stress. It is crucial to implement effective cooling measures in urban areas to improve the comfort of the thermal environment. In this study, the Weather Research and Forecasting Model(WRF), coupled with a single-layer Urban Canopy Model(UCM), was used to study the impact of heat mitigation strategies. In addition, a 5-km resolution land-cover dataset for China(ChinaLC), which is based on satellite remote sensing data, was adjusted and used, and 18 groups of numerical experiments were designed, to increase the albedo and vegetation fraction of roof/ground parameters. The experiments were conducted for four heatwave events that occurred in the summer of 2013 in the Yangtze River Delta urban agglomeration of China. The simulated results demonstrated that, for the single roof/ground schemes, the mitigation effects were directly proportional to the albedo and greening. Among all the experimental schemes, the superposed schemes presented better cooling effects. For the ground greening scheme, with similar net radiation flux and latent heat flux, its storage heat was lower than that of the roof greening scheme, resulting in more energy flux into the atmosphere, and its daytime cooling effect was not as good as that of the roof greening scheme. In terms of human thermal comfort(HTC), the improvement achieved by the ground greening scheme was better than any other single roof/ground schemes, because the increase in the relative humidity was small. The comprehensive evaluation of the mitigation effects of different schemes on the thermal environment presented in this paper provides a theoretical basis for improving the urban environment through rational urban planning and construction.
文摘Channel roughness is considered as the most sensitive parameter in development of hydraulic models for flood forecasting and flood inundation mapping. Hence, it is essential to calibrate the channel roughness coefficient (Mannnig’s “n” value) for various river reaches through simulation of floods. In the present study it is attempted to calibrate and validate Mannnig’s “n” value using HEC-RAS for Mahanadi Riverin Odisha (India). For calibration of Mannnig’s “n” value, the floods for the years 2001 and 2003 have been considered. The calibrated model, in terms of channel roughness, has been used to simulate the flood for year2006 inthe same river reach. The performance of the calibrated and validated HEC-RAS based model has been tested using Nash and Sutcliffe efficiency. It is concluded from the simulation study that optimum Mannnig’s “n” value that can be used effectively for Khairmal to Barmul reach of Mahanadi Riveris 0.029. It is also verified that the peak flood discharge and time to reach peak value computed using Mannnig’s “n” of 0.029 showed only an error of 5.42% as compared with the observed flood data of year 2006.
