scholarly journals Exploring the rainfall data from satellites to monitor rainfall induced landslides – A case study

2020 ◽  
Vol 66 (4) ◽  
pp. 887-894
Author(s):  
Manoj Kumar Thakur ◽  
Srinivas Desamsetti ◽  
A. Naga Rajesh ◽  
K. Koteswara Rao ◽  
M.S. Narayanan ◽  
...  
Keyword(s):  
Author(s):  
Binoy B Nair ◽  
S Silamparasu ◽  
R Mohnish ◽  
T S Deepak ◽  
M Rahul

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Jaber Almedeij

This study examines the spatial and temporal variability of monthly total rainfall data obtained from weather stations located in the urban areas of Kuwait. The rainfall data are analyzed by considering statistics on a seasonal basis and by means of periodogram technique to reveal the periods responsible for the variable pattern. The results demonstrate similarity implying that a point estimate of rainfall data can be considered spatially representative over the urban areas of Kuwait. A sinusoidal model triggering the influence of the detected periods is developed accordingly for the time duration from January 1965 to December 2009. The model is capable of describing the rainfall data with some discrepancies between the actual and calculated values resulting from hidden periods that have not been taken into account. This finding suggests that the ability to construct a more reliable model would require a wider range of historical data to detect the other periods affecting the rainfall pattern.


2020 ◽  
Vol 10 (5) ◽  
pp. 413
Author(s):  
Reena Hansa Seebocus ◽  
Michel Roddy Lollchund ◽  
Miloud Bessafi
Keyword(s):  

2019 ◽  
Vol 3 (1) ◽  
pp. 355 ◽  
Author(s):  
Duong Du Bui ◽  
Duc Minh Tran ◽  
Huong Thi Vu ◽  
Nuong Thi Bui

Water security is under severe pressures from human interventions and climate change in all over the world and improved water forecast is essential for water management. HYPE is a semi-distributed hydrographic model, running on Windows or Linux operating systems. The code of the model is written by the Fortran programming language and open source as Lesser GNU Public License. HYPE has been becoming a widely used tool in the forecasting of transboundary flows. However, the application of HYPE encounters many difficulties in processing input data and serving the construction, calibration, and validation of the model. This article introduces the development of the V-HYPE tool that helps a couple of global rainfall data and HYPE model for operational use. V-HYPE allows developing a user-friendly interface and setting parameters of the HYPE model as well as evaluating errors and transforming and visually displaying the results of the model. Besides, the V-HYPE has the ability to show related maps (i.e. sub-basins, river network, lake, and dams, etc), set up input data, automatically download global rainfall data, and visually display results on WebGIS. V-HYPE also can generate bulletins supporting for operational water resources warning and forecasting works in Vietnam. The utilities of this tool are demonstrated in the case study of Serepok river basin.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.


Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 349 ◽  
Author(s):  
Mohamed Salem Nashwan ◽  
Shamsuddin Shahid ◽  
Xiaojun Wang

This study assessed the uncertainty in the spatial pattern of rainfall trends in six widely used monthly gridded rainfall datasets for 1979–2010. Bangladesh is considered as the case study area where changes in rainfall are the highest concern due to global warming-induced climate change. The evaluation was based on the ability of the gridded data to estimate the spatial patterns of the magnitude and significance of annual and seasonal rainfall trends estimated using Mann–Kendall (MK) and modified MK (mMK) tests at 34 gauges. A set of statistical indices including Kling–Gupta efficiency, modified index of agreement (md), skill score (SS), and Jaccard similarity index (JSI) were used. The results showed a large variation in the spatial patterns of rainfall trends obtained using different gridded datasets. Global Precipitation Climatology Centre (GPCC) data was found to be the most suitable rainfall data for the assessment of annual and seasonal rainfall trends in Bangladesh which showed a JSI, md, and SS of 22%, 0.61, and 0.73, respectively, when compared with the observed annual trend. Assessment of long-term trend in rainfall (1901–2017) using mMK test revealed no change in annual rainfall and changes in seasonal rainfall only at a few grid points in Bangladesh over the last century.


Author(s):  
G Arvind ◽  
P Ashok Kumar ◽  
S Girish Karthi ◽  
C R Suribabu

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