Digital Mapping Algorithms to Estimate Soil Salinity in Indira Gandhi Nahar Pariyojana (IGNP) Command Area of India
2022
Moharana, P. C. | Dharumarajan, S. | Kumar, Nirmal | Pradhan, U. K. | Jena, R. K. | Naitam, R. K. | Kumar, Sunil | Singh, R. S. | Meena, R. S. | Nogiya, M. | Meena, R. L. | Tailor, B. L.
In the present study, the distribution of salinity was investigated using digital soil mapping (DSM) algorithms in the 5 km buffer zone of both sides of the Indira Gandhi Nahar Pariyojana (IGNP) canal system of Suratgarh tehsil in Rajasthan. To achieve this goal, 64 soil samples were used with 21 environmental covariates and 3 DSM algorithms. The result from the study showed that the difference between the minimum and maximum EC is very high (35.55dS m ) in the different irrigation zone of the IGNPcanal system. The EC ranged from 0.50 to 36.05. Results indicated that the most important environmental covariates were annual precipitation, elevation and valley depth. Among the DSM algorithms, RF model showed the best performance in predicting EC at the regional level. Results 2 showed that the RF algorithm could predict EC with an R , RMSE and MAE of 0.701, 3.367 and 1.722, respectively. RF and QRF showed similar performance in predicting EC, while SVM showed lower efficiency than the other models in terms of 2 R and prediction errors. The salinity prediction map shows that the vulnerability to soil salinity is high in the Anupgarh branch of the canal, and low in the IGNP main and Bikaner canal area. Furthermore, the model developed in this study provides comprehensive guidance for the land planners and decision-makers to develop amicable strategies for the management of the IGNPcanal system.
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