Remote sensing-based spatiotemporal assessment of agricultural drought and its impact on crop yields in Punjab, Pakistan - Ghani Rahman; Samavia Khalid; Sana Arshad; Muhammad Farhan Ul Moazzam; Hyun-Han Kwon (Scientific Reports)
Abstract Long-term meteorological droughts disrupt hydrological balances and lead to agricultural droughts that affect crop yield. This study uses remote sensing techniques to analyze agricultural droughts in Punjab, Pakistan, over two decades. From MODIS satellite data, three drought indices, such as vegetation condition index (VCI), temperature condition index (TCI), and vegetation health index (VHI), were generated to identify drought years and assess agricultural impacts during the rabi and kharif cropping seasons from 2001 to 2020. Standardized Yield Residual Series (SYRS) and Standardized Drought Residual Series (SDRS) were used to evaluate the impact of agriculture droughts on rabi crops (wheat, barley, gram) and kharif crops (sugarcane, rice, maize, cotton) and to compute Crop Drought Resilience (CDR). Results showed that Punjab experienced extreme to mild droughts from 2001 to 2018, notably in 2002 and 2008, with yield losses of 39% for rice, 34% for sugarcane, and 25% for wheat. The Mann-Kendall (MK) test indicated a significant (p < 0.001) upward trend in VHI for both cropping seasons, with trend breakpoints in 2009 and 2010. Stepwise linear regression found VHI was most predictive for gram yield (R2 = 0.49), while VCI was most predictive for sugarcane (R2 = 0.56) and rice (R2 = 0.29). Polynomial regression demonstrated that SYRSgram is highly influenced by all drought indices, especially SDRSVHI (R2 = 0.49), followed by SDRSVCI (R2 = 0.44) and SDRSTCI (R2 = 0.28). SYRSsugarcane and SYRSrice crops were primarily affected by SDRSVCI, with correlation coefficients of R2 = 0.62 for sugarcane and R2 = 0.33 for rice. This study concludes that gram, sugarcane, and wheat exhibit high to moderate non-resilience under extreme drought conditions, highlighting the vulnerability of these crops to climate variability. These findings are essential for developing targeted adaptation strategies to mitigate yield loss and ensure sustainable agriculture.