Numerical simulation of flow and bed morphology in the case of dam break floods with vegetation effect

The purpose of this study is to establish a depth-averaged 2-D hydrodynamic and sediment transport model for the dambreak flows with vegetation effect. The generalized shallow water equations are solved using an explicit finite volume method with unstructured quadtree rectangular grid, and in the hydrodynamic model, a Harten-Lax-Van Leer（HLL） approximate Riemann solver is used to calculate the intercell flux for capturing the dry-to-wet moving boundary. The sediment transport and bed variation equations in a coupled fashion are calculated by including the bed variation and the variable flow density in the flow continuity and momentum equations. The drag force of vegetation is modeled as the sink terms in the momentum equations. The developed model is tested against lab experiments of the dam-break flows over a fix bed and a movable bed in vegetated and non-vegetated channels. The results are compared with experimental data, and good agreement is obtained. It is shown that the reduced velocity under vegetated conditions leads to a decrease of the peak discharge and a rise of the water level of rivers and also an enhancement of the sediment deposition.

Soil erosion differences in paired grassland and forestland catchments on the Chinese Loess Plateau

In this study,two adjacent gauged catchments on the Chinese Loess Plateau were selected,in which one catchment was afforested and one was restored with natural vegetation in 1954.The distributions of soil erosion rates were estimated between 2010 and 2020 with a high spatial resolution of 2 m in the paired catchments based on the Revised Universal Soil Loss Equation model(RUSLE)and Geographic Information Systems(GIS).The results showed that the simulated soil erosion rates in 2010-2020 averaged 12.58 and 8.56 t ha^(-1)a^(-1)for the grassland and forestland catchment,respectively.Moreover,areas with high soil erosion rates(>80t ha^(-1)a^(-1))were mainly distributed in the topography with steep slope gradients(>45°).Comparisons between simulated soil erosion rates and observed annual sediment loads indicated that the simulation results of the grassland catchment were lower than the observed values,while it was reversed in the forestland catchment.We conclude that the RUSLE model cannot simulate the gravity erosion induced by extreme rainfall events.For the forestland catchment,insufficient streamflow and dense vegetation coverage are crucial factors resulting in hindering the movement of sediments.

Estimation of Shallow Landslide Susceptibility Incorporating the Impacts of Vegetation on Slope Stability

This study aimed to develop a physical-based approach for predicting the spatial likelihood of shallow landslides at the regional scale in a transition zone with extreme topography.Shallow landslide susceptibility study in an area with diverse vegetation types as well as distinctive geographic factors(such as steep terrain,fractured rocks,and joints)that dominate the occurrence of shallow landslides is challenging.This article presents a novel methodology for comprehensively assessing shallow landslide susceptibility,taking into account both the positive and negative impacts of plants.This includes considering the positive efects of vegetation canopy interception and plant root reinforcement,as well as the negative efects of plant gravity loading and preferential fow of root systems.This approach was applied to simulate the regional-scale shallow landslide susceptibility in the Dadu River Basin,a transition zone with rapidly changing terrain,uplifting from the Sichuan Plain to the Qinghai–Tibet Plateau.The research fndings suggest that:(1)The proposed methodology is efective and capable of assessing shallow landslide susceptibility in the study area;(2)the proposed model performs better than the traditional pseudo-static analysis method(TPSA)model,with 9.93%higher accuracy and 5.59%higher area under the curve;and(3)when the ratio of vegetation weight loads to unstable soil mass weight is high,an increase in vegetation biomass tends to be advantageous for slope stability.The study also mapped the spatial distribution of shallow landslide susceptibility in the study area,which can be used in disaster prevention,mitigation,and risk management.

Evaluating alternative hypotheses behind biodiversity and multifunctionality relationships in the forests of Northeastern China

Background:The importance of biodiversity in maintaining multiple ecosystem functions has been widely accepted.However,the specific mechanisms affecting biodiversity and ecosystem multifunctionality(BEMF)relationships in forests are largely unknown.This is particularly evident for the macroscale of a large forested landscape.Methods:Based on 412 one-tenth hectare field plots distributed over forested areas across northeastern China,we evaluated three alternative hypotheses explaining the relationships between BEMF,namely:niche complementarity,mass ratio,and vegetation quantity effect.We used Rao's quadratic entropy and community weighted mean trait values to quantify forest“biodiversity”.These two variables represent two complementary aspects of functional properties,which are in line with niche complementary and mass ratio effects,respectively.Results:Ecosystem multifunctionality was negatively associated with the community weighted mean values of acquisitive traits(a proxy of mass ratio effect).Rao's quadratic entropy(a proxy of niche complementarity)had no relationship with ecosystem multifunctionality.Higher stand biomass greatly increased ecosystem multifunctionality,which is in line with the vegetation quantity effect.Our results confirm that in the temperate forests of northeastern China,the relationship of BEMF was primarily affected by vegetation quantity,followed by mass ratio effects.Conclusions:The results of this study contribute to a better understanding of the main drivers of ecosystem multifunctionality in forest ecosystems.The results of this study provide additional evidence to support the vegetation quantity and mass ratio hypotheses in forest ecosystems.

Effects of Dynamic Vegetation on Global Climate Simulation Using the NCEP GFS and SSiB4/TRIFFID

Two global experiments were carried out to investigate the effects of dynamic vegetation processes on numerical climate simulations from 1948 to 2008.The NCEP Global Forecast System(GFS)was coupled with a biophysical model,the Simplified Simple Biosphere Model(SSi B)version 2(GFS/SSi B2),and it was also coupled with a biophysical and dynamic vegetation model,SSi B version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics(TRIFFID)(GFS/SSi B4/TRIFFID).The effects of dynamic vegetation processes on the simulation of precipitation,near-surface temperature,and the surface energy budget were identified on monthly and annual scales by assessing the GFS/SSi B4/TRIFFID and GFS/SSi B2 results against the satellite-derived leaf area index(LAI)and albedo and the observed land surface temperature and precipitation.The results show that compared with the GFS/SSiB2 model,the temporal correlation coefficients between the globally averaged monthly simulated LAI and the Global Inventory Monitoring and Modeling System(GIMMS)/Global Land Surface Satellite(GLASS)LAI in the GFS/SSi B4/TRIFFID simulation increased from 0.31/0.29(SSiB2)to 0.47/0.46(SSiB4).The correlation coefficients between the simulated and observed monthly mean near-surface air temperature increased from 0.50(Africa),0.35(Southeast Asia),and 0.39(South America)to 0.56,0.41,and 0.44,respectively.The correlation coefficients between the simulated and observed monthly mean precipitation increased from 0.19(Africa),0.22(South Asia),and 0.22(East Asia)to 0.25,0.27,and 0.28,respectively.The greatest improvement occurred over arid and semiarid areas.The spatiotemporal variability and changes in vegetation and ground surface albedo modeled by the GFS with a dynamic vegetation model were more consistent with the observations.The dynamic vegetation processes contributed to the surface energy and water balance and in turn,improved the annual variations in the simulated regional temperature and precipitation.The dynamic vegetation processes had the greatest influence on the spatiotemporal changes in the latent heat flux.This study shows that dynamic vegetation processes in earth system models significantly improve simulations of the climate mean status.