Kailun Jin

Evapotranspiration (ET) research is rare but is essential for understanding the impacts of climate change and forest management on water resource in Nepal. This study assessed eight global remote sensing-based ET products including GLASS, GLEAM, PMLv2, REA, PEW, ETmonitor, SSEBop and SEBAL, and an ecohydrolgical model, WaSSI using locally constructed 12 watershed-scale water balance datasets. Additionally, the Budyko framework was employed to constrain ET estimates. We found serious water imbalance issues in the hydrometeorological records for medium-sized basins where measured streamflow exceeded precipitation (P) and ET/P values substantively deviated from the theoretical Budyko curve. The accuracy of the remote sensing ET products varies at selected watersheds with large elevation gradients. We found considerable modeling errors with ET overestimated, especially in high elevations among these remote sensing products. Nationally, the eight remote sensing models do not agree on the temporal trends for annual ET over the past two decades. We identified potential causes to the large errors of the ET products: 1) meteorological input data used to drive the potential ET model and ET model, 2) model algorithms causing overestimates of ET at high elevations, and 3) underestimation of precipitation and overestimation of leaf area index at high elevations. We estimated mean annual ET for High Himalya, High Mountain, Middle Mountain, Low Mountain, Terai Plain as 257 mm, 544 mm, 764 mm, 844 mm and 892 mm, respectively. This study underscores the importance of ground measuring and integrated modeling of water balances in constraining remotely estimated ET in the Himalya region.

Evapotranspiration (ET) research is rare but is essential for understanding the impacts of climate change and forest management on water resource in Nepal. This study assessed eight global remote sensing-based ET products including GLASS, GLEAM, PMLv2, REA, PEW, ETmonitor, SSEBop and SEBAL, and an ecohydrolgical model, WaSSI using locally constructed 12 watershed-scale water balance datasets. Additionally, the Budyko framework was employed to constrain ET estimates. We found serious water imbalance issues in the hydrometeorological records for medium-sized basins where measured streamflow exceeded precipitation (P) and ET/P values substantively deviated from the theoretical Budyko curve. The accuracy of the remote sensing ET products varies at selected watersheds with large elevation gradients. We found considerable modeling errors with ET overestimated, especially in high elevations among these remote sensing products. Nationally, the eight remote sensing models do not agree on the temporal trends for annual ET over the past two decades. We identified potential causes to the large errors of the ET products: 1) meteorological input data used to drive the potential ET model and ET model, 2) model algorithms causing overestimates of ET at high elevations, and 3) underestimation of precipitation and overestimation of leaf area index at high elevations. We estimated mean annual ET for High Himalya, High Mountain, Middle Mountain, Low Mountain, Terai Plain as 257 mm, 544 mm, 764 mm, 844 mm and 892 mm, respectively. This study underscores the importance of ground measuring and integrated modeling of water balances in constraining remotely estimated ET in the Himalya region.

Evapotranspiration (ET) research is rare but is essential for understanding the impacts of climate change and forest management on water resource in Nepal. This study assessed eight global remote sensing-based ET products including GLASS, GLEAM, PMLv2, REA, PEW, ETmonitor, SSEBop and SEBAL, and an ecohydrolgical model, WaSSI using locally constructed 12 watershed-scale water balance datasets. Additionally, the Budyko framework was employed to constrain ET estimates. We found serious water imbalance issues in the hydrometeorological records for medium-sized basins where measured streamflow exceeded precipitation (P) and ET/P values substantively deviated from the theoretical Budyko curve. The accuracy of the remote sensing ET products varies at selected watersheds with large elevation gradients. We found considerable modeling errors with ET overestimated, especially in high elevations among these remote sensing products. Nationally, the eight remote sensing models do not agree on the temporal trends for annual ET over the past two decades. We identified potential causes to the large errors of the ET products: 1) meteorological input data used to drive the potential ET model and ET model, 2) model algorithms causing overestimates of ET at high elevations, and 3) underestimation of precipitation and overestimation of leaf area index at high elevations. We estimated mean annual ET for High Himalya, High Mountain, Middle Mountain, Low Mountain, Terai Plain as 257 mm, 544 mm, 764 mm, 844 mm and 892 mm, respectively. This study underscores the importance of ground measuring and integrated modeling of water balances in constraining remotely estimated ET in the Himalya region.

Potential evapotranspiration (PET), as an indicator of atmospheric evaporative demand, is a critical hydrological and meteorological factor to reflect regional and global hydrological cycles and environmental change. Understanding these nuanced responses of PET to environmental changes is important for agricultural production and water demand estimation. This study rigorously evaluated fluctuations in PET using the Penman–Monteith model over a 50-year span from 1970 to 2020 in the Sichuan–Chongqing region, an area notably susceptible to climate change. The changing characteristics of PET and local meteorological factors were detected by integrating the Mann–Kendall method and Pettitt test. Furthermore, the contribution and sensitivity of key meteorological variables to the observed variation in PET were also thoroughly investigated. Breakpoint analysis revealed that abrupt changes appeared in 1996 for annual PET. The detrending method indicated that substantial decreases in net radiation and wind speed (p < 0.01) were responsible for the decrease in annual PET from 1970 to 1996. Marked increases in minimum temperature and wind speed were the driving forces behind the uptick in annual PET in 1997–2020. At seasonal scales, wind speed and net radiation predominantly influenced PET in 1970–1996 in general. However, from 1997 to 2020, the factors controlling PET fluctuations displayed considerable seasonal variation. Sensitivity analysis showed that W_s and T_min were the second-most sensitive factors. By exploring the impacts of PET changes and shifts, attention must be paid when allocating water resources reasonably under the background of ongoing climate change and likelihood of future drought.

Studying the impact of vegetation dynamics on hydrological processes is essential for environmental management to reduce ecological environment risk and develop sustainable water management strategies under global warming. This case study simulated the responses of streamflow to vegetation cover degradation under climate variations in the Xilin River Basin in a semi-arid steppe of northern China. The snowmelt and river ice melting processes in the Soil and Water Assessment Tool (SWAT) were improved to estimate the changes in streamflow under multiple scenarios. Results showed that the improved SWAT simulations matched well to the measured monthly streamflow for both calibration (determination coefficient R2 = 0.75 and Nash–Sutcliffe ENS = 0.67) and validation periods (R2 = 0.74 and ENS = 0.68). Simulations of vegetation change revealed that obvious changes occurred in streamflow through conversion between high and low vegetation covers. The reductions in vegetation cover can elevate streamflow in both rainfall and snowmelt season, but the effects are most pronounced during the rainfall seasons (i.e., the growing seasons) and in drier years. These findings highlight the importance of vegetation degradation on modifying the hydrological partitioning in a semi-arid steppe basin. We conclude that in a particular climate zone, vegetation cover change is one of the important contributing factors to streamflow variations. Increases in streamflow in water-limited regions will likely reduce the effective water content of soil, which in turn leads to further degradation risk in vegetation. Therefore, vegetation cover management is one of the most effective and sustainable methods of improving water resources in water-constrained regions.