Spatiotemporal variation of potential evapotranspiration and meteorological drought based on multi-source data in Nepal

Abstract

Quantifying the spatiotemporal dynamic of potential evapotranspiration (PET) in topographically complex country are often limited by the scarcity and difficulty in obtaining ground-based measured climate data. Remote sensing products have multiple advantage, which allows rapid acquisition of information and status over large areas and long time series. This study compared and explored the spatiotemporal variation of PET across Nepal using three widely-used remote sensing and reanalysis data PET products (CRU_PET, MODIS_PET and PML_PET), and PET estimation using Hargreaves-Samani method based on CHIRTS datasets. On the basis of this, the spatiotemporal dynamic at seasonal and annual level and the periodical change of PET and meteorological aridity index AI (precipitation P/PET) were identified using Mann-Kendall test and Morlet Wavelet method. These PET products showed general spatial consistency over most areas in Nepal with higher PET in the south and less in the north. However, great differences were also found in PET values for four different products. Compared with the three remote sensing and reanalysis data products, CHIRTS_PET performs better in Nepal. The AI based on CHIRTS_PET showed an insignificant increasing (wetting) trend in the western and southern regions, while an insignificant decreasing (drying) trend in the central and northeastern region, which is generally consistent with the spatial pattern of precipitation. In the western and southern regions, the positive impact of increasing precipitation on AI masked the negative effect of increasing PET, and thus making this region getting humid. However, in the central and northeastern region, the increase in PET aggravates the impact of reduced precipitation on the drying trend. Our investigation have broad implications for sustainable water resources management under climate change in a topographically complex country like Nepal.

Keywords

• Potential Evapotranspiration (PET)
• Multi-Source PET Data
• Meteorological Aridity Index (AI)
• Precipitation
• Nepal