Trends and Anomalies of Rainfall and Rice Productivity across Four Agro-climatic Zones of Bihar, India
DOI:
https://doi.org/10.52151/jae2025624.1962Keywords:
innovative trend analysis, Mann-Kendall test, productivity anomaly index, rainfall anomaly index, Sen’s slope estimatorAbstract
Understanding rainfall variability is crucial for effective water resource management and agricultural planning. This study analyzed annual and monsoon rainfall trends across four representative stations of from four different agro-climatic zones (ACZs) of Bihar, namely, Patna, Purnia, Samastipur, and Bhagalpur, using non-parametric Mann–Kendall (MK) test with Sen’s slope estimator and the Innovative Trend Analysis (ITA). Results from both ITA and MK tests revealed predominantly decreasing monsoon rainfall trends at Patna and Purnia, while Samastipur and Bhagalpur exhibited weak increasing trend. For annual rainfall, MK test for all the four stations showed an increasing trend, with Samastipur (Z = 1.35, p = 0.15) showing the strongest upward tendency. However, none of the observed trends were statistically significant (p > 0.05), indicating considerable inter-annual variability and the absence of a consistent rainfall pattern across Bihar. Though results of MK and ITA differed for some stations, but results of Mann-Kendall test and Sen’s slope estimator were found to be in agreement for all the four stations both annually as well as during monsoon season. Rice productivity across the four agro-climatic zones showed a significant positive trend (p < 0.05), with the highest yield (1608 kg ha⁻¹) recorded in ACZ-IIIB (Purnia). The analysis of Rainfall Anomaly Index (RAI) and Productivity Anomaly Index (PAI) revealed that a negative RAI coexisted with a positive PAI, indicating that agricultural productivity was not solely dictated by precipitation deficits. This suggests that factors like rainfall distribution pattern, improved cultivar, effective water management, or other agronomic management practices mitigated the impact of reduced rainfall, highlighting complex adaptive capacities. Further, spatially heterogeneous rainfall patterns have potential implications for regional water management and agricultural productivity under changing climate conditions.
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