Added value of online satellite data transmission for flood forecasting: warning systems in medium-size catchments

2009 ◽  
Vol 59 (1) ◽  
pp. 23-29 ◽  
Author(s):  
C. Ruch ◽  
H. Stadler
Keyword(s):  
Satellite Communication ◽  
Flood Forecasting ◽  
Added Value ◽  
Medium Size ◽  
Warning Systems ◽  
Online Data ◽  
Concentration Time ◽  
Forecasting System ◽  
Information Chain ◽  
Leo Satellite

The present paper deals with the implementation of online data transferred via LEO satellite communication in a flood forecasting system. Although the project is ongoing, it is already recognised that the information chain: “measurement—transmission—forecast—alert” can be shortened, i.e., the flood danger can be more rapidly communicated to the population at risk. This gain is particularly valuable for medium size catchments where the concentration time (basin time of response to rainfall) is short.

scholarly journals Flood inundation simulations based on GSMaP satellite rainfall data in Jakarta, Indonesia

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Bambang Adhi Priyambodoho ◽  
Shuichi Kure ◽  
Ryuusei Yagi ◽  
Nurul Fajar Januriyadi
Keyword(s):  
Real Time ◽  
Storm Surges ◽  
Flood Forecasting ◽  
Rainfall Data ◽  
Observation Data ◽  
Flood Inundation ◽  
Rainfall Runoff ◽  
Concentration Time ◽  
Forecasting System ◽  
Hourly Observation

AbstractJakarta is the capital of Indonesia and is considered one of the most vulnerable cities to climate-related disasters, including flooding, sea-level rise, and storm surges. Therefore, the development of a flood-forecasting system for Jakarta is crucial. However, the accurate prediction of flooding in Jakarta is challenging because of the short flood concentration time in highly urbanized basins and the shortage of rainfall data in poorly gauged areas. The aim of this study is to simulate recent flood inundation using global satellite mapping of precipitation (GSMaP) products. The GSMaP products (NRT and Gauge V7) were evaluated and compared with hourly observation data from five ground stations in the Ciliwung River Basin. In addition, a rainfall-runoff and flood inundation model was applied to the target basin. The results of the analysis showed that the GSMaP Gauge data were more accurate than the GSMaP NRT data. However, the GSMaP Gauge cannot be used to provide real-time rainfall data and is, therefore, inadequate for real-time flood forecasting. We conclude that the GSMaP Gauge is suitable for replicating past flood events, but it is challenging to use the GSMaP NRT for real-time flood forecasting in Jakarta.

Flood Inundation Simulations based on GSMaP Satellite Rainfall Data in Jakarta, Indonesia

2020 ◽  
Author(s):  
Bambang Adhi Priyambodoho ◽  
Shuichi Kure ◽  
Ryuusei Yagi ◽  
Nurul Fajar Januriyadi
Keyword(s):  
Real Time ◽  
Flood Forecasting ◽  
Rainfall Data ◽  
Observation Data ◽  
Flood Inundation ◽  
Rainfall Runoff ◽  
Flood Events ◽  
Concentration Time ◽  
Gauge Data ◽  
Forecasting System

Abstract Jakarta is the capital of Indonesia and is considered as one of the most vulnerable cities to climate-related disasters, including flooding, sea-level rise, and storm surge, in the world. Therefore, the development of a flood-forecasting system for Jakarta is crucial. However, the accurate prediction of flooding in Jakarta is challenging because of the rapid flood-concentration time in highly urbanized basins and the shortage of rainfall data in poorly gauged areas. The aim of this study is to simulate flood inundation that occurred in recent years using global satellite mapping of precipitation (GSMaP) products. The GSMaP products (NRT and Gauge V7) were evaluated and compared with the observation data obtained hourly from five ground stations in the Ciliwung River Basin. In addition, a rainfall-runoff and flood inundation model were applied to the target basin. The results of the analysis showed that the GSMaP Gauge data were more accurate than the GSMaP NRT data. However, the GSMaP Gauge could not be used to provide real-time rainfall data and is, therefore, inadequate for real-time flood forecasting. We conclude that the GSMaP Gauge is suitable for replicating past flood events, but it is challenging to use the GSMaP NRT for real-time flood forecasting in Jakarta.

scholarly journals Single-Satellite Integrated Navigation Algorithm Based on Broadband LEO Constellation Communication Links

2021 ◽  
Vol 13 (4) ◽  
pp. 703
Author(s):  
Lvyang Ye ◽  
Yikang Yang ◽  
Xiaolun Jing ◽  
Jiangang Ma ◽  
Lingyu Deng ◽  
...  
Keyword(s):  
Real Time ◽  
Satellite Communication ◽  
The State ◽  
Earth Orbit ◽  
Integrated Navigation ◽  
Location Services ◽  
The Real ◽  
Navigation Algorithm ◽  
Communication Links ◽  
Leo Satellite

With the rapid development of satellite technology and the need to satisfy the increasing demand for location-based services, in challenging environments such as indoors, forests, and canyons, there is an urgent need to improve the position accuracy in these environments. However, traditional algorithms obtain the position solution through time redundancy in exchange for spatial redundancy, and they require continuous observations that cannot satisfy the real-time location services. In addition, they must also consider the clock bias between the satellite and receiver. Therefore, in this paper, we provide a single-satellite integrated navigation algorithm based on the elimination of clock bias for broadband low earth orbit (LEO) satellite communication links. First, we derive the principle of LEO satellite communication link clock bias elimination; then, we give the principle and process of the algorithm. Next, we model and analyze the error of the system. Subsequently, based on the unscented Kalman filter (UKF), we model the state vector and observation vector of our algorithm and give the state and observation equations. Finally, for different scenarios, we conduct qualitative and quantitative analysis through simulations, and the results show that, whether in an altimeter scenario or non-altimeter scenario, the performance indicators of our algorithm are significantly better than the inertial navigation system (INS), which can effectively overcome the divergence problem of INS; compared with the medium earth orbit (MEO) constellation, the navigation trajectory under the LEO constellation is closer to the real trajectory of the aircraft; and compared with the traditional algorithm, the accuracy of each item is improved by more than 95%. These results show that our algorithm not only significantly improves the position error, but also effectively suppresses the divergence of INS. The algorithm is more robust and can satisfy the requirements of cm-level real-time location services in challenging environments.

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.

Development of a Real-Time Flood Forecasting System by Hydraulic Flood Routing

2001 ◽  
Author(s):  
Joo Heon Lee ◽  
Do Hun Lee ◽  
Sang Man Jeong ◽  
Eun Tae Lee
Keyword(s):  
Real Time ◽  
Flood Forecasting ◽  
Flood Routing ◽  
Forecasting System
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