Interpreting Irrigation Decisions: Explainable AI Using SHAP and LIME in Agricultural Water Management Models

The study show that SHAP gives more robust, theoretically motivated explanations, especially in modeling higher-order feature interactions whereas LIME is faster and offer localizing to instances, and present a new hybrid explanation framework, which borrows the virtues of both methods to increase transparency and trust.