Impact of Time Resolution of Rainfall Measurement on Erosivity Factor in Arid Region of India: RESEARCH PAPER - Machiwal, Deepesh; Priyabrata Santra; H.M. Meena; Akath Singh (Annals of Arid Zone, 2025)
Rainfall erosivity is considered as a vital factor in computing soil loss through erosion prediction models such as original and derived versions of the universal soil loss equation model. The accurate estimates of the rainfall erosivity require high-resolution rainfall measurements, which are still not widely available for many parts of the world. In this study, a set of conversion factors was developed to adjust rainfall erosivity estimates derived from rainfall data recorded at various temporal resolutions to those based on 1 min interval rainfall measurements. For the first time in the western arid region of India, 1 min interval rainfall data for two years (2020 and 2024) were utilized to compute the total kinetic energy (E), maximum 30 minute rainfall intensity (I30), and rainfall erosivity factor (R-factor) for individual rainfall events using the EI30 index method. Results of the study indicated that I30 values were severe for 5% to 10% of the total rainy storms, and high to very high for 75% to 80% storms. It is further revealed that as rainfall measurement interval decreases, the peaks of I30 are easily captured, which ultimately leads to enhanced erosive energy of the rainfall. The conversion factors obtained for the arid region in this study are relatively less as compared to that reported for humid and semi-arid regions in earlier studies. Also, underestimations of the E are evidenced on increasing the time interval from 5 min to 60 min with relative error within -10% whereas, the R-factors showed -4.5, -8.0, -9.6, -5.8 and -96.7% underestimations at 5, 15, 30 and 60 min and 24 h, respectively. The relationships developed for computing the precise and accurate E, I30 and R-factors for high-resolution (1 min) data based on coarser data at different time intervals (5 min, 15 min, 30 min, 60 min and 24 h) can be used adequately as the estimations involves a strong interactions confirmed among the factors.