Seasonal Cropland Trends and Their Nexus with Agrometeorological Parameters in the Indus River Plain

Abstract

The fine-scale insights of existing cropland trends and their nexus with agrometeorological parameters are of paramount importance in assessing future food security risks and analyzing adaptation options under climate change. This study has analyzed the seasonal cropland trends in the Indus River Plain (IRP), using multi-year remote sensing data. A combination of Sen’s slope estimator and Mann–Kendall test was used to quantify the existing cropland trends. A correlation analysis between enhanced vegetation index (EVI) and 9 agrometeorological parameters, derived from reanalysis and remote sensing data, was conducted to study the region’s cropland-climate nexus. The seasonal trend analysis revealed that more than 50% of cropland in IRP improved significantly from the year 2003 to 2018. The lower reaches of the IRP had the highest fraction of cropland, showing a significant decreasing trend during the study period. The nexus analysis showed a strong correlation of EVI with the evaporative stress index (ESI) during the water-stressed crop season. Simultaneously, it exhibited substantial nexus of EVI with actual evapotranspiration (AET) during high soil moisture crop season. Temperature and solar radiation had a negative linkage with EVI response. In contrast, a positive correlation of rainfall with EVI trends was spatially limited to the IRP’s upstream areas. The relative humidity had a spatially broad positive correlation with EVI compare to other direct climatic parameters. The study concluded that positive and sustainable growth in IRP croplands could be achieved through effective agriculture policies to address spatiotemporal AET anomalies.

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

“…The results revealed significant positive trends of the NDVI at seasonal temporal scale and spatially at basin as well as grid scale. Previous investigations on vegetation dynamics covering parts of our study area identified comparable greening trends (Chen et al, 2019;Lamchin et al, 2018;Sarmah et al, 2018;Zhou and Ismaeel, 2020). Our results additionally reveal spatial patterns of seasonal trends and trends differentiated by land cover and land use classes at basin scale until the end of 2020.…”

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

“…The results revealed significant positive trends for the NDVI at annual and seasonal temporal scale as well as spatially at basin and grid scale. Previous investigations on vegetation trends covering parts of the investigated study area identified comparable greening trends (Chen et al, 2019;Lamchin et al, 2018;Sarmah et al, 2018;Zhou and Ismaeel, 2020). Based on the multi-faceted trend analyses of this study, it was shown that irrigated and rainfed croplands significantly contributed to vegetation greening (Table 3).…”

Trend Analysis of Climatic Parameters Using Geographical Information Systems: A Case Study of Sivas Province (1982-2021)

“…One widely used method for trend analysis is the Mann-Kendall (MK) test, which is a nonparametric statistical test that assesses the presence of monotonic trends in time series data (Zheng et al, 2021). This test has been applied in various studies to analyze trends in different climatic and hydrological variables, including yield losses, streamflow, climatic records, snowpack accumulation, cropland trends, precipitation, groundwater levels, and evapotranspiration (Helsel and Frans, 2006;New et al, 2006;Harpold et al, 2012;Shephard et al, 2014;Yeh et al, 2015;Palizdan et al, 2017;Chang et al, 2018;Djaman et al, 2018;Ali et al, 2019;Fang et al, 2019;Tayyab et al, 2019;Mirdashtvan and Mohseni Saravi, 2020;Patakamuri et al, 2020;Avino et al, 2021;Hu et al, 2021;Zheng et al, 2021;Zhou and Ismaeel, 2021;Nkiaka, 2022;Paudel et al, 2022).…”