An Analysis of Long-Term Rainfall Trends and Variability in the Uttarakhand Himalaya Using Google Earth Engine

This paper analyses the spatio-temporal trends and variability in annual, seasonal, and monthly rainfall with corresponding rainy days in Bhilangana river basin, Uttarakhand Himalaya, based on stations and two gridded products. Station-based monthly rainfall and rainy days data were obtained from th...

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Main Authors: Abhishek Banerjee, Ruishan Chen, Michael E. Meadows, R.B. Singh, Suraj Mal, Dhritiraj Sengupta
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/4/709
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language English
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author Abhishek Banerjee
Ruishan Chen
Michael E. Meadows
R.B. Singh
Suraj Mal
Dhritiraj Sengupta
spellingShingle Abhishek Banerjee
Ruishan Chen
Michael E. Meadows
R.B. Singh
Suraj Mal
Dhritiraj Sengupta
An Analysis of Long-Term Rainfall Trends and Variability in the Uttarakhand Himalaya Using Google Earth Engine
Remote Sensing
rainfall variability
chirps
persiann-cdr
non-parametric tests
google earth engine
himalaya
author_facet Abhishek Banerjee
Ruishan Chen
Michael E. Meadows
R.B. Singh
Suraj Mal
Dhritiraj Sengupta
author_sort Abhishek Banerjee
title An Analysis of Long-Term Rainfall Trends and Variability in the Uttarakhand Himalaya Using Google Earth Engine
title_short An Analysis of Long-Term Rainfall Trends and Variability in the Uttarakhand Himalaya Using Google Earth Engine
title_full An Analysis of Long-Term Rainfall Trends and Variability in the Uttarakhand Himalaya Using Google Earth Engine
title_fullStr An Analysis of Long-Term Rainfall Trends and Variability in the Uttarakhand Himalaya Using Google Earth Engine
title_full_unstemmed An Analysis of Long-Term Rainfall Trends and Variability in the Uttarakhand Himalaya Using Google Earth Engine
title_sort analysis of long-term rainfall trends and variability in the uttarakhand himalaya using google earth engine
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-02-01
description This paper analyses the spatio-temporal trends and variability in annual, seasonal, and monthly rainfall with corresponding rainy days in Bhilangana river basin, Uttarakhand Himalaya, based on stations and two gridded products. Station-based monthly rainfall and rainy days data were obtained from the India Meteorological Department (IMD) for the period from 1983 to 2008 and applied, along with two daily rainfall gridded products to establish temporal changes and spatial associations in the study area. Due to the lack of more recent ground station rainfall measurements for the basin, gridded data were then used to establish monthly rainfall spatio-temporal trends for the period 2009 to 2018. The study shows all surface observatories in the catchment experienced an annual decreasing trend in rainfall over the 1983 to 2008 period, averaging 15.75 mm per decade. Analysis of at the monthly and seasonal trend showed reduced rainfall for August and during monsoon season as a whole (10.13 and 11.38 mm per decade, respectively); maximum changes were observed in both monsoon and winter months. Gridded rainfall data were obtained from the Climate Hazard Infrared Group Precipitation Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). By combining the big data analytical potential of Google Earth Engine (GEE), we compare spatial patterns and temporal trends in observational and modelled precipitation and demonstrate that remote sensing products can reliably be used in inaccessible areas where observational data are scarce and/or temporally incomplete. CHIRPS reanalysis data indicate that there are in fact three significantly distinct annual rainfall periods in the basin, viz. phase 1: 1983 to 1997 (relatively high annual rainfall); phase 2: 1998 to 2008 (drought); phase 3: 2009 to 2018 (return to relatively high annual rainfall again). By comparison, PERSIANN-CDR data show reduced annual and winter precipitation, but no significant changes during the monsoon and pre-monsoon seasons from 1983 to 2008. The major conclusions of this study are that rainfall modelled using CHIRPS corresponds well with the observational record in confirming the decreased annual and seasonal rainfall, averaging 10.9 and 7.9 mm per decade respectively between 1983 and 2008, although there is a trend (albeit not statistically significant) to higher rainfall after the marked dry period between 1998 and 2008. Long-term variability in rainfall in the Bhilangana river basin has had critical impacts on the environment arising from water scarcity in this mountainous region.
topic rainfall variability
chirps
persiann-cdr
non-parametric tests
google earth engine
himalaya
url https://www.mdpi.com/2072-4292/12/4/709
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spelling doaj-a2e35f8f4bc84146805582f51831c0482020-11-25T00:37:16ZengMDPI AGRemote Sensing2072-42922020-02-0112470910.3390/rs12040709rs12040709An Analysis of Long-Term Rainfall Trends and Variability in the Uttarakhand Himalaya Using Google Earth EngineAbhishek Banerjee0Ruishan Chen1Michael E. Meadows2R.B. Singh3Suraj Mal4Dhritiraj Sengupta5Key Laboratory of Geographic Information Science, Ministry of Education, and School of Geographical Science, Institute of Eco-Chongming, East China Normal University, 500 Dongchuan Road, Shanghai 200241, ChinaKey Laboratory of Geographic Information Science, Ministry of Education, and School of Geographical Science, Institute of Eco-Chongming, East China Normal University, 500 Dongchuan Road, Shanghai 200241, ChinaKey Laboratory of Geographic Information Science, Ministry of Education, and School of Geographical Science, Institute of Eco-Chongming, East China Normal University, 500 Dongchuan Road, Shanghai 200241, ChinaDepartment of Geography, Delhi School of Economics, University of Delhi, New Delhi 110007, IndiaDepartment of Geography, Shaheed Bhagat Singh College, University of Delhi, New Delhi 110017, IndiaKey Laboratory of Geographic Information Science, Ministry of Education, and School of Geographical Science, Institute of Eco-Chongming, East China Normal University, 500 Dongchuan Road, Shanghai 200241, ChinaThis paper analyses the spatio-temporal trends and variability in annual, seasonal, and monthly rainfall with corresponding rainy days in Bhilangana river basin, Uttarakhand Himalaya, based on stations and two gridded products. Station-based monthly rainfall and rainy days data were obtained from the India Meteorological Department (IMD) for the period from 1983 to 2008 and applied, along with two daily rainfall gridded products to establish temporal changes and spatial associations in the study area. Due to the lack of more recent ground station rainfall measurements for the basin, gridded data were then used to establish monthly rainfall spatio-temporal trends for the period 2009 to 2018. The study shows all surface observatories in the catchment experienced an annual decreasing trend in rainfall over the 1983 to 2008 period, averaging 15.75 mm per decade. Analysis of at the monthly and seasonal trend showed reduced rainfall for August and during monsoon season as a whole (10.13 and 11.38 mm per decade, respectively); maximum changes were observed in both monsoon and winter months. Gridded rainfall data were obtained from the Climate Hazard Infrared Group Precipitation Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). By combining the big data analytical potential of Google Earth Engine (GEE), we compare spatial patterns and temporal trends in observational and modelled precipitation and demonstrate that remote sensing products can reliably be used in inaccessible areas where observational data are scarce and/or temporally incomplete. CHIRPS reanalysis data indicate that there are in fact three significantly distinct annual rainfall periods in the basin, viz. phase 1: 1983 to 1997 (relatively high annual rainfall); phase 2: 1998 to 2008 (drought); phase 3: 2009 to 2018 (return to relatively high annual rainfall again). By comparison, PERSIANN-CDR data show reduced annual and winter precipitation, but no significant changes during the monsoon and pre-monsoon seasons from 1983 to 2008. The major conclusions of this study are that rainfall modelled using CHIRPS corresponds well with the observational record in confirming the decreased annual and seasonal rainfall, averaging 10.9 and 7.9 mm per decade respectively between 1983 and 2008, although there is a trend (albeit not statistically significant) to higher rainfall after the marked dry period between 1998 and 2008. Long-term variability in rainfall in the Bhilangana river basin has had critical impacts on the environment arising from water scarcity in this mountainous region.https://www.mdpi.com/2072-4292/12/4/709rainfall variabilitychirpspersiann-cdrnon-parametric testsgoogle earth enginehimalaya