Efficient detection of ephemeral gully trajectories using topographic index-based approach: Calibration-free for large-scale applications

In agricultural landscapes, the use of topographic index (TI) models has been common to predict the presence and extent of ephemeral gullies (EGs). However, these models face two significant challenges: (1) the accurate prediction of EGs relies heavily on a critical threshold (CT) value, which is difficult to determine optimally using existing strategies, and (2) the calibration of TI models limits their applicability on a larger scale. To address these limitations, the current study proposes two methods: (1) the division of the study area into zones based on key factors influencing gully formation, reducing the need for TI model calibration, and (2) a pixel-based binary classification approach coupled with a precision performance metric to identify the calibrated CT value within a watershed. The performance of seven TI models for predicting EG length was evaluated using local validation within zones and transferred validation between zones. Local validation demonstrated that among the TI models, modified stream power index (MSPI), stream power index (SPI), and compound topographic index (CTI), in descending order, yielded the most accurate predictions for EG length. Furthermore, the decrease in accuracy observed in the transferred MSPI model compared to the local MSPI model supported the study's hypothesis that dividing a large-scale area into distinct zones with varying topographic and climatic characteristics enables the determination of a CT value specific to each zone. Soil loss rates due to EGs ranged from 0.36 to 1 kg/m2 yr, aligning with findings from similar global studies. These findings offer valuable insight that can be integrated into comprehensive watershed and soil erosion models.