scholarly journals Daily GRACE gravity field solutions track major flood events in the Ganges–Brahmaputra Delta

2018 ◽  
Vol 22 (5) ◽  
pp. 2867-2880 ◽  
Author(s):  
Ben T. Gouweleeuw ◽  
Andreas Kvas ◽  
Christian Gruber ◽  
Animesh K. Gain ◽  
Thorsten Mayer-Gürr ◽  
...  
Keyword(s):  
Gravity Field ◽  
River Runoff ◽  
Large Scale ◽  
High Volume ◽  
Temporal Variations ◽  
Flood Events ◽  
Satellite Mission ◽  
Flood Level ◽  
Flood Monitoring ◽  
The Ganges

Abstract. Two daily gravity field solutions based on observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are evaluated against daily river runoff data for major flood events in the Ganges–Brahmaputra Delta (GBD) in 2004 and 2007. The trends over periods of a few days of the daily GRACE data reflect temporal variations in daily river runoff during major flood events. This is especially true for the larger flood in 2007, which featured two distinct periods of critical flood level exceedance in the Brahmaputra River. This first hydrological evaluation of daily GRACE gravity field solutions based on a Kalman filter approach confirms their potential for gravity-based large-scale flood monitoring. This particularly applies to short-lived, high-volume floods, as they occur in the GBD with a 4–5-year return period. The release of daily GRACE gravity field solutions in near-real time may enable flood monitoring for large events.

scholarly journals Daily GRACE gravity field solutions track major flood events in the Ganges-Brahmaputra Delta

2017 ◽  
Author(s):  
Ben T. Gouweleeuw ◽  
Andreas Kvas ◽  
Christian Grüber ◽  
Animesh K. Gain ◽  
Thorsten Mayer-Gürr ◽  
...  
Keyword(s):  
Gravity Field ◽  
River Runoff ◽  
Large Scale ◽  
High Volume ◽  
Temporal Variations ◽  
Flood Events ◽  
Satellite Mission ◽  
Flood Level ◽  
Flood Monitoring ◽  
The Ganges

Abstract. Two daily gravity field solutions based on observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are evaluated against daily river runoff data for major flood events in the Ganges-Brahmaputra Delta (GBD) in 2004 and 2007. The trends over periods of a few days of the daily GRACE data reflect temporal variations in daily river runoff during major flood events. This is especially true for the larger flood in 2007, which featured two distinct periods of critical flood level exceedance in the Brahmaputra River. This first hydrological evaluation of daily GRACE gravity field solutions based on a Kalman filter approach confirms their potential for gravity-based large-scale flood monitoring. This particularly applies to short-lived, high-volume floods, as they occur in the GBD with a 4–5 year return period. The release of daily GRACE gravity field solutions in near real-time may enable flood monitoring for large events.

scholarly journals Applicability of GRACE and GRACE-FO for monitoring water mass changes of the Aral Sea and the Caspian Sea

2020 ◽  
Vol 26 (2) ◽  
pp. 443-453
Author(s):  
Lorant Földváry ◽  
Victor Statov ◽  
Nizamatdin Mamutov
Keyword(s):  
Gravity Field ◽  
Caspian Sea ◽  
Large Scale ◽  
Aral Sea ◽  
Water Volume ◽  
Satellite Mission ◽  
The Caspian Sea ◽  
Gravity Fields ◽  
Range Rate ◽  
Sea Area

The GRACE gravity satellite mission has provided monthly gravity field solutions for about 15 years enabling a unique opportunity to monitor large scale mass variation processes. By the end of the GRACE, the GRACE-FO mission was launched in order to continue the time series of monthly gravity fields. The two missions are similar in most aspects apart from the improved intersatellite range rate measurements, which is performed with lasers in addition to microwaves. An obvious demand for the geoscientific applications of the monthly gravity field models is to understand the consistency of the models provided by the two missions. This study provides a case-study related consistency investigation of GRACE and GRACE-FO monthly solutions for the Aral Sea region. As the closeness of the Caspian Sea may influence the monthly mass variations of the Aral Sea, it has also been involved in the investigations. According to the results, GRACE-FO models seem to continue the mass variations of the GRACE period properly, therefore their use jointly with GRACE is suggested. Based on the justified characteristics of the gravity anomaly by water volume variations in the case of the Aral Sea, GRACE models for the period March–June 2017 are suggested to be neglected. Though the correlation between water volume and monthly gravity field variations is convincing in the case of the Aral Sea, no such a correlation for the Caspian Sea could have been detected, which suggests to be the consequence of other mass varying processes, may be related to the seismicity of the Caspian Sea area.

scholarly journals Temporal Gravity Signals in Reprocessed GOCE Gravitational Gradients

2020 ◽  
Vol 12 (21) ◽  
pp. 3483
Author(s):  
Betty Heller ◽  
Frank Siegismund ◽  
Roland Pail ◽  
Thomas Gruber ◽  
Roger Haagmans
Keyword(s):  
Gravity Field ◽  
Ocean Circulation ◽  
Signal To Noise Ratio ◽  
Spatial Scales ◽  
Low Frequency ◽  
Temporal Variations ◽  
Normal Equation ◽  
Frequency Noise ◽  
Satellite Mission ◽  
Gravitational Gradients

The reprocessing of the satellite gravitational gradiometry (SGG) data from the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite mission in 2018/2019 considerably reduced the low-frequency noise in the data, leading to reduced noise amplitudes in derived gravity field models at large spatial scales, at which temporal variations of the Earth’s gravity field have their highest amplitudes. This is the motivation to test the reprocessed GOCE SGG data for their ability to resolve time-variable gravity signals. For the gravity field processing, we apply and compare a spherical harmonics (SH) approach and a mass concentration (mascon) approach. Although their global signal-to-noise ratio is <1, SH GOCE SGG-only models resolve the strong regional signals of glacier melting in Greenland and Antarctica, and the 2011 moment magnitude 9.0 earthquake in Japan, providing an estimation of gravity variations independent of Gravity Recovery and Climate Experiment (GRACE) data. The benefit of combined GRACE/GOCE SGG models is evaluated based on the ice mass trend signals in Greenland and Antarctica. While no signal contribution from GOCE SGG data additional to the GRACE models could be observed, we show that the incorporation of GOCE SGG data numerically stabilizes the related normal equation systems.

scholarly journals Gravity field of Sarmatia according to satellite data (model EIGEN-6S2) and its interpretation

2021 ◽  
Vol 43 (3) ◽  
pp. 47-63
Author(s):  
O. A. Chornaya ◽  
T. P. Yegorova
Keyword(s):  
Gravity Field ◽  
Satellite Data ◽  
Large Scale ◽  
Donets Basin ◽  
Field Pattern ◽  
Satellite Mission ◽  
The Caspian Sea ◽  
Tectonic Zone ◽  
The North ◽  
Free Air

The paper presents a brief overview of satellite observations of the CHAMP, GRACE and GOCE missions to study the Earth’s global gravity field, and the used mathematical apparatus in the form of an expansion of the geopotential in spherical harmonics. The application of satellite data in various fields of Earth Sciences is considered. As a basic global model of the Earth’s gravity field based on satellite data we used the EIGEN-6S2 model [Rudenko et al, 2014] that combines satellite mission data GRACE and GOCE, and also uses satellite data of LAGEOUS laser ranging.  On its basis, the gravity field of Sarmatia was analyzed using the Free Air anomalies, Bouguer anomalies, the second radial derivative of the geopotential and the geoid heights. The geological units of Sarmatia and its surroundings are most clearly manifested in the Free Air anomalies and in the distribution of the second derivative of the geopotential, showing differences in the gravity field pattern of the Ukrainian Shield, the Voronezh Massif, and the Pripyat-Dnieper-Donets basin (PDDB) with characteristic anomalies of the general northwest strike. The continuation of the PDDB in a southeastern direction through the Karpinsky Swell to the northern part of the Caspian Sea confirms the existence of an extended ancient tectonic zone of the Sarmato-Turanian lineament. The geoid within Sarmatia shows in general a regional west-east gradient change from +40 m in the west to -10 m in the east. Such large-scale geoid changes are determined by the Sarmatia position between two global geoid anomalies — the maximum of the North Atlantic and the minimum of the Indian Ocean.

scholarly journals Extreme Floods in the Eastern Part of Europe: Large-Scale Drivers and Associated Impacts

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1122
Author(s):  
Monica Ionita ◽  
Viorica Nagavciuc
Keyword(s):  
Water Vapor ◽  
Heavy Rainfall ◽  
Large Scale ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Flood Events ◽  
Rainfall Events ◽  
Catchment Areas ◽  
Large Scale Atmospheric Circulation ◽  
Heavy Rainfall Events

The role of the large-scale atmospheric circulation in producing heavy rainfall events and floods in the eastern part of Europe, with a special focus on the Siret and Prut catchment areas (Romania), is analyzed in this study. Moreover, a detailed analysis of the socio-economic impacts of the most extreme flood events (e.g., July 2008, June–July 2010, and June 2020) is given. Analysis of the largest flood events indicates that the flood peaks have been preceded up to 6 days in advance by intrusions of high Potential Vorticity (PV) anomalies toward the southeastern part of Europe, persistent cut-off lows over the analyzed region, and increased water vapor transport over the catchment areas of Siret and Prut Rivers. The vertically integrated water vapor transport prior to the flood peak exceeds 300 kg m−1 s−1, leading to heavy rainfall events. We also show that the implementation of the Flood Management Plan in Romania had positive results during the 2020 flood event compared with the other flood events, when the authorities took several precaution measurements that mitigated in a better way the socio-economic impact and risks of the flood event. The results presented in this study offer new insights regarding the importance of large-scale atmospheric circulation and water vapor transport as drivers of extreme flooding in the eastern part of Europe and could lead to a better flood forecast and flood risk management.

scholarly journals An Accurate Reconstruction of CMB E Mode Signal over Large Angular Scales using Prior Information of CMB Covariance Matrix in ILC Algorithm

2020 ◽  
Author(s):  
Ujjal Purkayastha ◽  
Vipin Sudevan ◽  
Rajib Saha
Keyword(s):  
Power Spectrum ◽  
Linear Combination ◽  
Covariance Matrix ◽  
Large Scale ◽  
Prior Information ◽  
Future Generation ◽  
Temperature Anisotropy ◽  
Satellite Mission ◽  
Angular Power Spectrum ◽  
Accurate Reconstruction

Abstract Recently, the internal-linear-combination (ILC) method was investigated extensively in the context of reconstruction of Cosmic Microwave Background (CMB) temperature anisotropy signal using observations obtained by WMAP and Planck satellite missions. In this article, we, for the first time, apply the ILC method to reconstruct the large scale CMB E mode polarization signal, which could probe the ionization history, using simulated observations of 15 frequency CMB polarization maps of future generation Cosmic Origin Explorer (COrE) satellite mission. We find that the clean power spectra, from the usual ILC, are strongly biased due to non zero CMB-foregrounds chance correlations. In order to address the issues of bias and errors we extend and improve the usual ILC method for CMB E mode reconstruction by incorporating prior information of theoretical E mode angular power spectrum while estimating the weights for linear combination of input maps (Sudevan & Saha 2018b). Using the E mode covariance matrix effectively suppresses the CMB-foreground chance correlation power leading to an accurate reconstruction of cleaned CMB E mode map and its angular power spectrum. We compare the performance of the usual ILC and the new method over large angular scales and show that the later produces significantly statistically improved results than the former. The new E mode CMB angular power spectrum contains neither any significant negative bias at the low multipoles nor any positive foreground bias at relatively higher mutlipoles. The error estimates of the cleaned spectrum agree very well with the cosmic variance induced error.

scholarly journals Enhancement of Detecting Permanent Water and Temporary Water in Flood Disasters by Fusing Sentinel-1 and Sentinel-2 Imagery Using Deep Learning Algorithms: Demonstration of Sen1Floods11 Benchmark Datasets

2021 ◽  
Vol 13 (11) ◽  
pp. 2220
Author(s):  
Yanbing Bai ◽  
Wenqi Wu ◽  
Zhengxin Yang ◽  
Jinze Yu ◽  
Bo Zhao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
Large Scale ◽  
Learning Algorithms ◽  
Flood Events ◽  
Test Set ◽  
Source Data ◽  
Flood Disasters ◽  
Temporary Water ◽  
Sentinel 2

Identifying permanent water and temporary water in flood disasters efficiently has mainly relied on change detection method from multi-temporal remote sensing imageries, but estimating the water type in flood disaster events from only post-flood remote sensing imageries still remains challenging. Research progress in recent years has demonstrated the excellent potential of multi-source data fusion and deep learning algorithms in improving flood detection, while this field has only been studied initially due to the lack of large-scale labelled remote sensing images of flood events. Here, we present new deep learning algorithms and a multi-source data fusion driven flood inundation mapping approach by leveraging a large-scale publicly available Sen1Flood11 dataset consisting of roughly 4831 labelled Sentinel-1 SAR and Sentinel-2 optical imagery gathered from flood events worldwide in recent years. Specifically, we proposed an automatic segmentation method for surface water, permanent water, and temporary water identification, and all tasks share the same convolutional neural network architecture. We utilize focal loss to deal with the class (water/non-water) imbalance problem. Thorough ablation experiments and analysis confirmed the effectiveness of various proposed designs. In comparison experiments, the method proposed in this paper is superior to other classical models. Our model achieves a mean Intersection over Union (mIoU) of 52.99%, Intersection over Union (IoU) of 52.30%, and Overall Accuracy (OA) of 92.81% on the Sen1Flood11 test set. On the Sen1Flood11 Bolivia test set, our model also achieves very high mIoU (47.88%), IoU (76.74%), and OA (95.59%) and shows good generalization ability.

scholarly journals 1068. Large-Scale Migration and the Changing Viral Hepatitis Prevalences in North America: A modeling approach

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S563-S563
Author(s):  
Kenneth A Valles ◽  
Lewis R Roberts
Keyword(s):  
United States ◽  
Viral Hepatitis ◽  
Large Scale ◽  
Country Of Origin ◽  
Human Movement ◽  
High Volume ◽  
The United States ◽  
The Philippines ◽  
Outcome Data ◽  
Treatment Programs

Abstract Background Infection by hepatitis B and C viruses causes inflammation of the liver and can lead to cirrhosis, liver failure, and hepatocellular carcinoma. The WHO’s ambition to eliminate viral hepatitis by 2030 requires strategies specific to the dynamic disease profiles each nation faces. Large-scale human movement from high-prevalence nations to the United States and Canada have altered the disease landscape, likely warranting adjustments to present elimination approaches. However, the nature and magnitude of the new disease burden remains unknown. This study aims to generate a modeled estimate of recent HBV and HCV prevalence changes to the United States and Canada due to migration. Methods Total migrant populations from 2010-2019 were obtained from United Nations Migrant Stock database. Country-of-origin HBV and HCV prevalences were obtained for the select 40 country-of-origin nations from the Polaris Observatory and systematic reviews. A standard pivot table was used to evaluate the disease contribution from and to each nation. Disease progression estimates were generated using the American Association for the Study of the Liver guidelines and outcome data. Results Between 2010 and 2019, 7,676,937 documented migrants arrived in US and Canada from the selected high-volume nations. Primary migrant source regions were East Asia and Latin America. Combined, an estimated 878,995 migrants were HBV positive, and 226,428 HCV positive. The majority of both migrants (6,477,506) and new viral hepatitis cases (HBV=840,315 and HCV=215,359) were found in the United States. The largest source of HBV cases stemmed from the Philippines, and HCV cases from El Salvador. Conclusion Massive human movement has significantly changed HBV and HCV disease burdens in both the US and Canada over the past decade and the long-term outcomes of cirrhosis and HCC are also expected to increase. These increases are likely to disproportionally impact individuals of the migrant and refugee communities and screening and treatment programs must be strategically adjusted in order to reduce morbidity, mortality, and healthcare expenses. Disclosures All Authors: No reported disclosures

scholarly journals Study on the High-Speed Milling Performance of High-Volume Fraction SiCp/Al Composites

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4143
Author(s):  
Youzheng Cui ◽  
Shenrou Gao ◽  
Fengjuan Wang ◽  
Qingming Hu ◽  
Cheng Xu ◽  
...  
Keyword(s):  
High Speed ◽  
Large Scale ◽  
Volume Fraction ◽  
Simulation Analysis ◽  
Cutting Temperature ◽  
High Volume ◽  
Cutting Parameters ◽  
High Volume Fraction ◽  
High Wear Resistance ◽  
Element Analysis

Compared with other materials, high-volume fraction aluminum-based silicon carbide composites (hereinafter referred to as SiCp/Al) have many advantages, including high strength, small change in the expansion coefficient due to temperature, high wear resistance, high corrosion resistance, high fatigue resistance, low density, good dimensional stability, and thermal conductivity. SiCp/Al composites have been widely used in aerospace, ordnance, transportation service, precision instruments, and in many other fields. In this study, the ABAQUS/explicit large-scale finite element analysis platform was used to simulate the milling process of SiCp/Al composites. By changing the parameters of the tool angle, milling depth, and milling speed, the influence of these parameters on the cutting force, cutting temperature, cutting stress, and cutting chips was studied. Optimization of the parameters was based on the above change rules to obtain the best processing combination of parameters. Then, the causes of surface machining defects, such as deep pits, shallow pits, and bulges, were simulated and discussed. Finally, the best cutting parameters obtained through simulation analysis was the tool rake angle γ0 = 5°, tool clearance angle α0 = 5°, corner radius r = 0.4 mm, milling depth ap = 50 mm, and milling speed vc= 300 m/min. The optimal combination of milling parameters provides a theoretical basis for subsequent cutting.

scholarly journals A pan-African medium-range ensemble flood forecast system

2015 ◽  
Vol 19 (8) ◽  
pp. 3365-3385 ◽  
Author(s):  
V. Thiemig ◽  
B. Bisselink ◽  
F. Pappenberger ◽  
J. Thielen
Keyword(s):  
Large Scale ◽  
Practical Implication ◽  
River Basins ◽  
Flood Forecasting ◽  
Small Scale ◽  
Flood Forecast ◽  
Flood Events ◽  
Forecast System ◽  
Pan African ◽  
Forecasting System

Abstract. The African Flood Forecasting System (AFFS) is a probabilistic flood forecast system for medium- to large-scale African river basins, with lead times of up to 15 days. The key components are the hydrological model LISFLOOD, the African GIS database, the meteorological ensemble predictions by the ECMWF (European Centre for Medium-Ranged Weather Forecasts) and critical hydrological thresholds. In this paper, the predictive capability is investigated in a hindcast mode, by reproducing hydrological predictions for the year 2003 when important floods were observed. Results were verified by ground measurements of 36 sub-catchments as well as by reports of various flood archives. Results showed that AFFS detected around 70 % of the reported flood events correctly. In particular, the system showed good performance in predicting riverine flood events of long duration (> 1 week) and large affected areas (> 10 000 km2) well in advance, whereas AFFS showed limitations for small-scale and short duration flood events. The case study for the flood event in March 2003 in the Sabi Basin (Zimbabwe) illustrated the good performance of AFFS in forecasting timing and severity of the floods, gave an example of the clear and concise output products, and showed that the system is capable of producing flood warnings even in ungauged river basins. Hence, from a technical perspective, AFFS shows a large potential as an operational pan-African flood forecasting system, although issues related to the practical implication will still need to be investigated.

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