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
Increase in demand of electrical power for different purposes in Iraq leads increase towards to power plant system such as thermal power plant. Any thermal power plant requires water for processing, cooling, oilfields...Increase in demand of electrical power for different purposes in Iraq leads increase towards to power plant system such as thermal power plant. Any thermal power plant requires water for processing, cooling, oilfields, boiler feed and other miscellaneous uses including domestic requirements. The main parameter to measure the efficiency of thermal power plant is the availability of water and technology employed. Therefore, the thermal power plants like A1-Anbar thermal power station is built on the Euphrates River bank in the city of Ramadi in the middle part of Iraq. Depending on the field measurements and pervious measurements, the computation of river water level for different frequency periods was achieved to determine the inundation area of the plant and the required height of power plant intakes. The problems of intake operation include low flow rate of the river at intake that resulting low water level （minimum flow rate was recorded 107 m^3/s with water level 47.8 m）, and annual sediments at intake that may be caused operation off. Therefore, any design for the intake or operation must consider the above problems. The study referred to the discharge for full operation is about 300 m^3/s and water level is 51.3 m to satisfy these requirements. The study suggested two solutions for this problem, first by using the groins and the second by building two weirs.展开更多
The North China Plain(NCP)is the political and cultural center of China,including the metropolises of Beijing and Tianjin,the province of Hebei,and parts of Henan and Shandong provinces.Adopted from previous hydrologi...The North China Plain(NCP)is the political and cultural center of China,including the metropolises of Beijing and Tianjin,the province of Hebei,and parts of Henan and Shandong provinces.Adopted from previous hydrological studies,the NCP is bounded by the Taihang Mountains in the west and the Yellow River in the south,with an area of approximately 140,000 km2,hosting a population of 350 million[1](Fig.1a).展开更多
Dear Editor,The use of global navigation satellite system(GNSS)technologies to study the hydrological cycle has gained increasing attention.Current research pri-marily spans two domains:GNSS hydrogeodesy and GNSS remo...Dear Editor,The use of global navigation satellite system(GNSS)technologies to study the hydrological cycle has gained increasing attention.Current research pri-marily spans two domains:GNSS hydrogeodesy and GNSS remote sensing.However,these areas remain fragmented within hydrology-related fields.展开更多
Large-scale surface soil moisture data are critical for hydrological and climatic studies at large regional scales.The accuracy of large-scale soil moisture retrieval relying solely on physical models is constrained b...Large-scale surface soil moisture data are critical for hydrological and climatic studies at large regional scales.The accuracy of large-scale soil moisture retrieval relying solely on physical models is constrained by model complexity and inaccurate parameters.Nowadays,machine learning models are widely used,but their excellent retrieval performance depends heavily on extensive accurate labeled data and faces criticism for lacking physical interpretability.Using in situ data as labeled data can enhance the accuracy of retrieval models.However,current soil moisture sites are predominantly concentrated in some key regions,and it is challenging to perform high-quality soil moisture retrieval in regions where sites are sparse.Facing the above challenges,this study proposed a fusion model utilizing limited in situ data to achieve high-accuracy soil moisture retrieval on a large regional scale.Based on the SMAP SCA-V algorithm,the retrieval model employed a differentiable modeling approach,integrating physical models like theτ-ωmodel,the Q-H model,the Fresnel equation,and the Mironov mixing dielectric model with the neural networks.This integration ensured model accuracy and improved generalization,achieving highaccuracy soil moisture retrieval across China at a 1-km resolution with labeled data from a limited number of sites.The differentiable retrieval model demonstrated strong performance in the Shandian River Basin and Naqu study areas,with R of 0.906 and 0.927,respectively,and attained an R of 0.925 and an ubRMSE of 0.035 m^(3)·m^(-3) in the overall evaluation.In the comparative analysis with the SMAP product,the differentiable retrieval model demonstrated comparable spatial distribution characteristics and effectively captured the temporal trends of soil moisture variation.The differentiable retrieval model creates the conditions for high-accuracy soil moisture retrievals in countries and regions with a small number of soil moisture monitoring sites or publicly available in situ data.展开更多
文摘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.
文摘Increase in demand of electrical power for different purposes in Iraq leads increase towards to power plant system such as thermal power plant. Any thermal power plant requires water for processing, cooling, oilfields, boiler feed and other miscellaneous uses including domestic requirements. The main parameter to measure the efficiency of thermal power plant is the availability of water and technology employed. Therefore, the thermal power plants like A1-Anbar thermal power station is built on the Euphrates River bank in the city of Ramadi in the middle part of Iraq. Depending on the field measurements and pervious measurements, the computation of river water level for different frequency periods was achieved to determine the inundation area of the plant and the required height of power plant intakes. The problems of intake operation include low flow rate of the river at intake that resulting low water level （minimum flow rate was recorded 107 m^3/s with water level 47.8 m）, and annual sediments at intake that may be caused operation off. Therefore, any design for the intake or operation must consider the above problems. The study referred to the discharge for full operation is about 300 m^3/s and water level is 51.3 m to satisfy these requirements. The study suggested two solutions for this problem, first by using the groins and the second by building two weirs.
基金supported by the China Geological Survey:Program of National Land Subsidence Mapping with Satellite SAR Interferometry(DD20230440)the National Natural Science Foundation of China(42374019 and 42071397)。
文摘The North China Plain(NCP)is the political and cultural center of China,including the metropolises of Beijing and Tianjin,the province of Hebei,and parts of Henan and Shandong provinces.Adopted from previous hydrological studies,the NCP is bounded by the Taihang Mountains in the west and the Yellow River in the south,with an area of approximately 140,000 km2,hosting a population of 350 million[1](Fig.1a).
基金jointly supported by the National Natural Science Foundation of China(NSFC)projects(grant no.42471511)the Beijing Nova Program(grant nos.20230484327 and 20240484540)+2 种基金the Hunan Provincial Natural Science Foundation project(grant no.2024JJ9186)the Fundamental Research Funds for the Central Universities,Peking Universitysupported by 1311 DFG under SFB 1502/1-2022(project number 450058266).
文摘Dear Editor,The use of global navigation satellite system(GNSS)technologies to study the hydrological cycle has gained increasing attention.Current research pri-marily spans two domains:GNSS hydrogeodesy and GNSS remote sensing.However,these areas remain fragmented within hydrology-related fields.
基金supported in part by the National Key Research and Development Program of China under grant 2022YFB3903403.
文摘Large-scale surface soil moisture data are critical for hydrological and climatic studies at large regional scales.The accuracy of large-scale soil moisture retrieval relying solely on physical models is constrained by model complexity and inaccurate parameters.Nowadays,machine learning models are widely used,but their excellent retrieval performance depends heavily on extensive accurate labeled data and faces criticism for lacking physical interpretability.Using in situ data as labeled data can enhance the accuracy of retrieval models.However,current soil moisture sites are predominantly concentrated in some key regions,and it is challenging to perform high-quality soil moisture retrieval in regions where sites are sparse.Facing the above challenges,this study proposed a fusion model utilizing limited in situ data to achieve high-accuracy soil moisture retrieval on a large regional scale.Based on the SMAP SCA-V algorithm,the retrieval model employed a differentiable modeling approach,integrating physical models like theτ-ωmodel,the Q-H model,the Fresnel equation,and the Mironov mixing dielectric model with the neural networks.This integration ensured model accuracy and improved generalization,achieving highaccuracy soil moisture retrieval across China at a 1-km resolution with labeled data from a limited number of sites.The differentiable retrieval model demonstrated strong performance in the Shandian River Basin and Naqu study areas,with R of 0.906 and 0.927,respectively,and attained an R of 0.925 and an ubRMSE of 0.035 m^(3)·m^(-3) in the overall evaluation.In the comparative analysis with the SMAP product,the differentiable retrieval model demonstrated comparable spatial distribution characteristics and effectively captured the temporal trends of soil moisture variation.The differentiable retrieval model creates the conditions for high-accuracy soil moisture retrievals in countries and regions with a small number of soil moisture monitoring sites or publicly available in situ data.
