Hazard at weather scale for extreme rainfall forecast reduces uncertainty

2021 ◽  
Vol 14 ◽  
pp. 100106
Author(s):  
Shrabani S. Tripathy ◽  
Subhankar Karmakar ◽  
Subimal Ghosh
Keyword(s):  
Extreme Rainfall ◽  
Rainfall Forecast

scholarly journals The Development of a Quantitative Precipitation Forecast Correction Technique Based on Machine Learning for Hydrological Applications

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 111 ◽  
Author(s):  
Chul-Min Ko ◽  
Yeong Yun Jeong ◽  
Young-Mi Lee ◽  
Byung-Sik Kim
Keyword(s):  
Machine Learning ◽  
Heavy Rainfall ◽  
Extreme Rainfall ◽  
Machine Learning Techniques ◽  
Precipitation Forecast ◽  
Machine Learning Technique ◽  
Rainfall Forecast ◽  
Quantitative Precipitation Forecast ◽  
Correction Technique ◽  
Learning Technique

This study aimed to enhance the accuracy of extreme rainfall forecast, using a machine learning technique for forecasting hydrological impact. In this study, machine learning with XGBoost technique was applied for correcting the quantitative precipitation forecast (QPF) provided by the Korea Meteorological Administration (KMA) to develop a hydrological quantitative precipitation forecast (HQPF) for flood inundation modeling. The performance of machine learning techniques for HQPF production was evaluated with a focus on two cases: one for heavy rainfall events in Seoul and the other for heavy rainfall accompanied by Typhoon Kong-rey (1825). This study calculated the well-known statistical metrics to compare the error derived from QPF-based rainfall and HQPF-based rainfall against the observational data from the four sites. For the heavy rainfall case in Seoul, the mean absolute errors (MAE) of the four sites, i.e., Nowon, Jungnang, Dobong, and Gangnam, were 18.6 mm/3 h, 19.4 mm/3 h, 48.7 mm/3 h, and 19.1 mm/3 h for QPF and 13.6 mm/3 h, 14.2 mm/3 h, 33.3 mm/3 h, and 12.0 mm/3 h for HQPF, respectively. These results clearly indicate that the machine learning technique is able to improve the forecasting performance for localized rainfall. In addition, the HQPF-based rainfall shows better performance in capturing the peak rainfall amount and spatial pattern. Therefore, it is considered that the HQPF can be helpful to improve the accuracy of intense rainfall forecast, which is subsequently beneficial for forecasting floods and their hydrological impacts.

scholarly journals Improving the extreme rainfall forecast of Typhoon Morakot (2009) by assimilating radar data from Taiwan Island and mainland China

2017 ◽  
Vol 31 (4) ◽  
pp. 747-766 ◽  
Author(s):  
Xuwei Bao ◽  
Dan Wu ◽  
Xiaotu Lei ◽  
Leiming Ma ◽  
Dongliang Wang ◽  
...  
Keyword(s):  
Mainland China ◽  
Extreme Rainfall ◽  
Radar Data ◽  
Typhoon Morakot ◽  
Rainfall Forecast ◽  
Taiwan Island

scholarly journals Extreme Flooding in Alexandria: Can Anticipatory Flood Management be a Solution?

10.29007/wvth ◽  
2018 ◽  
Author(s):  
Biswa Bhattacharya ◽  
Chris Zevenbergen ◽  
Adele Young ◽  
Mohanasundar Radhakrishnan
Keyword(s):  
Heavy Rainfall ◽  
Extreme Event ◽  
Meteorological Data ◽  
Extreme Rainfall ◽  
Flood Management ◽  
Landsat 8 ◽  
Flood Water ◽  
Rainfall Forecast ◽  
Extreme Flooding ◽  
The City

Alexandria experienced heavy rainfall in October 2015 resulting in wide spread flooding, huge damages and seven deaths. This paper presents the analysis of the hydro- meteorological data to characterise the extremity of the event. The flood map of the city and its adjoining area prepared with LANDSAT-8 satellite images shows the extent of flooding. The analysis with the rainfall forecast from the ECMWF clearly demonstrated that the extreme event could have been predicted days ahead. It is proposed to implement Anticipatory Flood Management in Alexandria (AFMA), which will allow using the extreme rainfall forecast to start pumping out water from Lake Maryot and Airport Lake before the event starts. This will enable extra storage space to accommodate some of the flood water from subsequent rain. An analysis of the October flood showed that 50% of the flood water due to the heavy rainfall could have been stored in the lakes had the AFMA been implemented. The study shows that the existing data allows us to implement AFMA to reduce flood consequences and pave the way to critically decide upon additional mitigation infrastructure. The recommendation of this study is currently being implemented.

The Influence of Geographical Factors on Extreme Rainfalls in Lampung Province

2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly
Keyword(s):  
Geographical Location ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Design Flood ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Ungauged Basin ◽  
Flood Discharge ◽  
Design Rainfall ◽  
Geographical Factors

Many people in Indonesia calculate design rainfall before calculating the design flooddischarge. The design rainfall with a certain return period will eventually be convertedinto a design flood discharge by combining it with the characteristics of the watershed.However, the lack of a network of rainfall recording stations makes many areas that arenot hydrologically measured (ungauged basin), so it is quite difficult to know thecharacteristics of rain in the area concerned. This study aims to analyze thecharacteristics of design rainfall in Lampung Province. The focus of the analysis is toinvestigate whether geographical factors influence the design rainfall that occurs in theparticular area. The data used in this study is daily rainfall data from 15 rainfallrecording stations spread in Lampung Province. The method of frequency analysis usedin this study is the Gumbel method. The research shows that the geographical location ofan area does not have significant effect on extreme rainfall events. The effect of risingearth temperatures due to natural exploitation by humans tends to be stronger as a causeof extreme events such as extreme rainfall.Keywords: Influence, geographical, factors, extreme, rainfall.

Trend of Extreme Precipitations Indices in West-central Côte d’Ivoire: Case of the Lobo Watershed

2020 ◽  
Vol 5 (10) ◽  
pp. 1281-1287
Author(s):  
F. B. Allechy ◽  
M. Youan Ta ◽  
V. H. N’Guessan Bi ◽  
F. A. Yapi ◽  
A. B. Koné ◽  
...  
Keyword(s):  
Cote D'ivoire ◽  
Côte D’Ivoire ◽  
Crop Yields ◽  
Extreme Rainfall ◽  
Cote D’Ivoire ◽  
West Central ◽  
Côte D'ivoire ◽  
Northern Half ◽  
Agricultural Potential ◽  
Annual Total

The Lobo watershed located in the west-central part of Côte d'Ivoire is an area with high agricultural potential, influenced by climate variations and changes that reduce crop yields. The objective of this study is to analyse trends in ETCCDI extreme rainfall indices from rainfall data from 1984 to 2013 using ClimPACT2 software. This study shows that the trend of the indices: number of consecutive wet days (CWD), number of rainy days (R1mm) and the cumulative annual total rainfall (PRCPTOT) is decreasing. On the other hand, the number of consecutive dry days (CDD) is on the rise. In general, the whole basin has experienced a decrease in rainfall as well as wet sequences and an increase in dry sequences. These different trends observed in this study are more pronounced in the northern half of the watershed.

Economic Impact of Sugarcane Variety CO-86032 on Farmers Economy in Maharashtra

2020 ◽  
pp. 354-359
Keyword(s):  
Economic Impact ◽  
Production Technology ◽  
Economic Benefit ◽  
Extreme Rainfall ◽  
Sugar Recovery ◽  
Sugarcane Variety ◽  
Public Research ◽  
Productivity Improvement ◽  
Farming Community ◽  
The Government

The area under sugarcane in Maharashtra state was found to be more stable and consistent rather than production and productivity. It may be due to the F & RP of sugarcane. In the year 1996, MPKV, Rahuri released a promising variety of sugarcane viz., Co-86032 which is very famous in farming community due to its hardiness, sugar recovery (percent) and resistance to the extreme rainfall as well as deficit rainfall. The total economic worthiness of university released sugarcane variety Co-86032(production technology) over other competing varieties of sugarcane in the Maharashtra was `51449.14per ha. The sugarcane growers in Maharashtra state earned net economic benefit of `11059.40 crores from improved sugarcane variety Co-86032. Therefore, it is suggested that the Government should allocate substantial funds to public research in sugarcane for productivity improvement.

Effects of extreme rainfall and drought events on grassland ecosystems

2014 ◽  
Vol 38 (9) ◽  
pp. 1008-1018 ◽  
Author(s):  
ZHANG Bin ◽  
◽  
ZHU Jian-Jun ◽  
LIU Hua-Min ◽  
and PAN Qing-Min
Keyword(s):  
Extreme Rainfall ◽  
Grassland Ecosystems

ACCURACY EVALUATION OF PREDICTING TIMES OF ISSUES OF THE TRAIN OPERATION CONTROL USING RAINFALL FORECAST INFORMATION

2019 ◽  
Vol 75 (2) ◽  
pp. I_121-I_126
Author(s):  
Yohei NAKABUCHI ◽  
Hiroto SUZUKI ◽  
Chiho KIMPARA ◽  
Satoru ENDO ◽  
Eiichi NAKAKITA
Keyword(s):  
Accuracy Evaluation ◽  
Rainfall Forecast ◽  
Train Operation ◽  
Operation Control
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