Satellite-based assessment of drought and its impact on vegetation in Nepal | |
| Author | Shrestha, Sichu |
| Call Number | AIT Thesis no.RS-23-08 |
| Subject(s) | Droughts--Nepal Drought forecasting--Nepal Plants--Drought tolerance--Nepal Environmental monitoring--Nepal |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Abstract | Historical drought analysis helps to understand the evolution of drought on a temporal and spatial scale and helps to determine real time risk. Detailed spatial-temporal drought analysis considering severity, duration and intensity of drought event and its return period have not been done in Nepal. Additionally, the time lag in drought occurrence and changes in vegetation have not been studied in Nepal. Thus, this study aimed to assess drought and its impact on vegetation in Nepal. Satellite/ reanalysis based monthly gridded precipitation dataset: CHIRPS V2.0, MSWEP V2.2, PERSIANN-CCS-CDR and ERA5 Land average data were evaluated using RMSE, CC, MBE, PBIAS, RSR and NSE with observed ground-based meteorological station data. CHIRPS V2.0 identified to be best among datasets was corrected for bias using linear scaling with Thiessen polygon method and then used for SPI computation (1,3,6,9,12-months). The severity, duration and intensity of drought was determined using run theory statistics. The bivariate drought return period map of duration and severity was determined using empirical copula and the magnitude of drought intensity trend was determined using Sen's slope estimator which was weighted overlayed to determine drought prone areas for I) short duration and low severity drought event and 2) long duration and high severity drought event at province level. Finally, to understand the response of vegetation to drought in multiple time scales, correlation analysis of the indicator (MODIS based LAI, GPP, NDVI and NDWD anomaly was performed in relation to SPI (1, 3,6,9,12-months) for 8 vegetation cover types. The result showed change in indicators was more correlated (overall average correlation coefficient(r) 4 to7) to short- and medium-term drought in early spring months. The anomalous decrease in precipitation was more linearly related with anomalous decrease in GPP and NDWI (meanr=6) followed by NDVI and LAI (mean r=5) while the correlation value decreased with increase in elevation ranges in Nepal. The average maximum correlation observed at the lag of 1 month was low (corrclation coefficient=0.2 to 0.3). Thus, this study suggests further study on lag analysis considering multiple vegetation influencing factors. |
| Year | 2023 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing and Geographic Information Systems (RS) |
| Chairperson(s) | Sarawut Ninsawat; |
| Examination Committee(s) | Babel, Mukand S.;Shrestha, Sangam; |
| Scholarship Donor(s) | His Majesty the King's Scholarship (Thailand); |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2023 |