See the published version of this preprint at Environmental Systems Research.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Abebe Senamaw
aBahir Dar University, College of Agriculture and Environmental Sciences, Bahir Dar, Ethiopia
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
Geographic Information System (GIS) and Remote Sensing play an important role for near real time monitoring of drought condition over large areas. The objective of this study was to assess spatial and temporal variation of agricultural and metrological drought using temporal image of eMODIS NDVI based vegetation condition index (VCI) and standard precipitation index (SPI). To validate the strength of drought indices correlation analysis was made between VCI and crop yield anomaly as well as SPI and crop yield anomaly. The results revealed that the year 2009 and 2015 were drought years while the 2001 and 2007 were wet years. There was also a good correlation between NDVI and rainfall (r=0.71), VCI and crop yield anomaly (0.72), SPI and crop yield anomaly (0.74). Frequency of metrological and agricultural drought was compiled by using historical drought intensity map.
Result
The result shows that there was complex and local scale variation in frequency of drought events in the study period. There was also no year without drought in many parts of the study area. Combined drought risk map also showed that 8%, 56%, 35% and 8% of study area were vulnerable to very severe, severe and moderate drought condition respectively.
Conclusion
In conclusion, the study area is highly vulnerable to agricultural and meteorological drought. Thus besides mapping drought vulnerable areas, integrating socioeconomic data for better understand other vulnerable factors were recommended.
Keywords
Drought, eMODIS NDVI, Geographic Information System, Remote Sensing, Standardized Precipitation index, Waghimra Zone
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Loading...
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Environmental Systems Research.
Version 1
Posted 17 Sep, 2020
No community comments so far
Editorial decision: Major Revision
On 24 Oct, 2020
Reviewer #3 agreed
On 20 Oct, 2020
Review #3 received
Received 20 Oct, 2020
Review #2 received
Received 20 Oct, 2020
Review #1 received
Received 09 Oct, 2020
Reviewer #2 agreed
On 22 Sep, 2020
Reviewers invited
Invitations sent on 19 Sep, 2020
Reviewer #1 agreed
On 19 Sep, 2020
Editor assigned
On 15 Sep, 2020
Submission checks complete
On 14 Sep, 2020
Editor invited
On 14 Sep, 2020
First submitted
On 03 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Environmental Engineering
Learn more about our company.
See the published version of this preprint at Environmental Systems Research.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Abebe Senamaw
aBahir Dar University, College of Agriculture and Environmental Sciences, Bahir Dar, Ethiopia
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Environmental Systems Research.
Version 1
Posted 17 Sep, 2020
No community comments so far
Editorial decision: Major Revision
On 24 Oct, 2020
Reviewer #3 agreed
On 20 Oct, 2020
Review #3 received
Received 20 Oct, 2020
Review #2 received
Received 20 Oct, 2020
Review #1 received
Received 09 Oct, 2020
Reviewer #2 agreed
On 22 Sep, 2020
Reviewers invited
Invitations sent on 19 Sep, 2020
Reviewer #1 agreed
On 19 Sep, 2020
Editor assigned
On 15 Sep, 2020
Submission checks complete
On 14 Sep, 2020
Editor invited
On 14 Sep, 2020
First submitted
On 03 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Environmental Engineering
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Environmental Systems Research.
Background
Geographic Information System (GIS) and Remote Sensing play an important role for near real time monitoring of drought condition over large areas. The objective of this study was to assess spatial and temporal variation of agricultural and metrological drought using temporal image of eMODIS NDVI based vegetation condition index (VCI) and standard precipitation index (SPI). To validate the strength of drought indices correlation analysis was made between VCI and crop yield anomaly as well as SPI and crop yield anomaly. The results revealed that the year 2009 and 2015 were drought years while the 2001 and 2007 were wet years. There was also a good correlation between NDVI and rainfall (r=0.71), VCI and crop yield anomaly (0.72), SPI and crop yield anomaly (0.74). Frequency of metrological and agricultural drought was compiled by using historical drought intensity map.
Result
The result shows that there was complex and local scale variation in frequency of drought events in the study period. There was also no year without drought in many parts of the study area. Combined drought risk map also showed that 8%, 56%, 35% and 8% of study area were vulnerable to very severe, severe and moderate drought condition respectively.
Conclusion
In conclusion, the study area is highly vulnerable to agricultural and meteorological drought. Thus besides mapping drought vulnerable areas, integrating socioeconomic data for better understand other vulnerable factors were recommended.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Loading...