Large-scale rain-fed to paddy farmland conversion modified land-surface thermal properties in Cold China

Sci Total Environ. 2020 Jun 20:722:137917. doi: 10.1016/j.scitotenv.2020.137917. Epub 2020 Mar 13.

Abstract

The recent acute evolution of cropland structure in Cold China could lead to rapid rice paddy expansion, potentially altering land-surface thermal processes and influencing climate. To address the issue, this study investigated the changes in cropland type, land-surface temperature (LST) and heat fluxes in the agricultural region of Cold China during 2000-2015 based on time-series of land-use data and MODIS LST product, using the split-window algorithms (SWA) model and the pixel component arranging and component algorithm (PCACA). The investigation revealed large-scale land transformation from rain-fed farmland to paddy field in Cold China during 2000-2015. Compared to the rain-fed farmland, lower LST was observed in paddy field throughout crop growing seasons, with the highest LST threshold found in June (7.17 ± 1.05 °C) and the lowest value found in August (1.04 ± 0.35 °C). The cooling effect of paddy-field ranged from 0.59 ± 0.06 °C, 0.77 ± 0.07 °C, and 1.08 ± 0.08 °C for the low-, medium-, and high-density paddies, respectively. Compared to other months, stronger cooling effect was found in May and June. Further analysis showed the conversion of a rain-fed farmland to paddy field reduced the sensible heat flux and soil heat flux by 52.94 W/m2 and 15.26 W/m2, respectively, while increased the latent heat flux and net radiation by 115.66 W/m2 and 47.34 W/m2, respectively. The findings from this study indicated the changes in cropland structure and management regime (e.g., irrigation) could profoundly modify land-surface thermal processes and local/regional climate, interfering the signals from global warming. Therefore, instrumental climate data that collected from areas experienced large-scale conversion between rain-fed and paddy farmland should be carefully screened and corrected to prevent land-use induced biases.

Keywords: Cold China; Land use change; Remote sensing; Surface thermal environment.