Rainfall interception using the revised Gash analytical model for Pinus sylvestris var. mongolica in a semi-humid region of NE China

Abstract

Rainfall loss by canopy interception comprises a substantial portion of the water budget in forested ecosystems, and accurately measuring and simulating this process is critical for the effective management of forest water resources. Pinus sylvestris var. mongolica is a main afforested species in northeastern China; however, little work has been carried out assessing the canopy interception loss of this plant species in semi-humid areas. Accordingly, a rainfall interception experiment was conducted for P. sylvestris plots in a semi-humid area of northeastern China from June to September 2019. The revised Gash analytical model was then applied to the canopy interception values, and its regional applicability was tested. During the experimental process, incident rainfall (P), throughfall (Tf), and stemflow events (Sf) were collected and measured, while meteorological data were simultaneously obtained on-site. The Penman (PM) equation and the Gash regression method were used to estimate evaporation rates (E) from the saturated canopy, and the Leyton constraint method was applied to obtain canopy storage capacity (S). Parameters such as E, S, stemflow partitioning coefficient (pt), and trunk storage capacity (St) were scaled to the canopy cover fraction per unit area (producing Ec, Sc, ptc, and Stc in the revised Gash analytical model, respectively) for use in the simulated rainfall interception. The proportions of measured canopy interception (I), Sf, and Tf accounted for 17.2 %, 6.0 %, and 76.8 % of P, respectively; whereas the Sc, ptc, and Stc were calculated as 1.60 mm, 0.067, and 0.21 mm, respectively, over the experimental period. The revised Gash analytical model with Ec varied from 0.37 to 0.93, and Ec/R varied from 0.62 to 1.55 (acquired via the PM equation), thus indicating its ability to accurately simulate P. sylvestris canopy interception. These findings can provide a theoretical foundation for understanding correlated ecological and hydrological processes, allowing land managers to predict the impacts of afforestation on water inputs for current and future rainfall scenarios in typical coniferous forests of semi-humid regions.