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Interception loss (I) can remove substantial portions of water from forested watersheds, Thus, I prediction models are crucial if we are to balance human and ecosystem water needs under a shifting climate. This is particularly true for arid/semiarid regions that rely on afforestation efforts for economic or agricultural needs, yet very few of these regions have selected, applied and validated an I prediction model. This study applied/evaluated the reformulated Gash I model to a data set of 54 storms using 50 manual throughfall (TF) observations per site, for two stands of common afforestation tree species in semiarid Northern Iran: Pinus eldarica (Eldar pine) and Cupressus arizonica (Arizona cypress). The reformulated Gash model has rarely been evaluated in semiarid forest stands of these common species. Each species intercepted substantial rainfall during commonly experienced storm conditions up to 56% (C. arizonica) and 65% (P. eldarica). Mean TF was modestly higher under C. arizonica (76%) than P. eldarica (73%). However, water storage (S) was nearly double for P. eldarica compared to C. arizonica (1.2-0.7 mm, respectively). Canopy structural differences also altered the gap fraction (p) for P. eldarica (0.38) in relation to C. arizonica (0.49). Modeling error was low (-1.3% vs. -2.6% for P. eldarica and C. arizonica, respectively), generally underestimating On the whole, the validated model performed better for C. arizonica than P. eldarica stands, likely as a result of influence from canopy structural functions not parameterized by the model (e.g., P. eldarica’s higher LAI, horizontal leaves/branches, high crown length, and rougher bark) which directly alter S, p, and TF parameters, or indirectly influence the ratio of mean evaporation rate from the wet canopy (mm h(-1)) to the mean rainfall intensity (mm h(-1)) ((E) over bar/(R) over bar) by sheltering intercepted rain water from boundary layer meteorological conditions. It is, therefore, suggested that future work seek to parameterize these canopy parameters. Since I reduces the quantity of water for infiltration and recharge, I estimates and prediction tools are of great value to semiarid and arid regions undergoing afforestation because the model allows land managers to predict impacts of afforestation on water inputs for current and future rainfall scenarios. (C) 2014 Elsevier B.V. All rights reserved.