Risk assessment of maize drought disaster in southwest China using the Environmental Policy Integrated Climate model

The East Asian monsoon has a tremendous impact on agricultural production in China. An assessment of the risk of drought disaster in maize-producing regions is therefore important in ensuring a reduction in such disasters and an increase in food security. A risk assessment model, EPIC（Environmental Policy Integrated Climate） model, for maize drought disasters based on the Erosion Productivity Impact Calculator crop model is proposed for areas with the topographic characteristics of the mountainous karst region in southwest China. This region has one of the highest levels of environmental degradation in China. The results showed that the hazard risk level for the maize zone of southwest China is generally high. Most hazard index values were between 0.4 and 0.5,accounting for 47.32% of total study area. However,the risk level for drought loss was low. Most of the loss rate was ＆lt;0.1, accounting for 96.24% of the total study area. The three high-risk areas were mainlydistributed in the parallel ridge–valley areas in the east of Sichuan Province, the West Mountain area of Guizhou Province, and the south of Yunnan Province.These results provide a scientific basis and support for the reduction of agricultural drought disasters and an increase in food security in the southwest China maize zone.

Effects of Optimized Root Water Uptake Parameterization Schemes on Water and Heat Flux Simulation in a Maize Agroecosystem

As root water uptake（RWU）is an important link in the water and heat exchange between plants and ambient air,improving its parameterization is key to enhancing the performance of land surface model simulations.Although different types of RWU functions have been adopted in land surface models,there is no evidence as to which scheme most applicable to maize farmland ecosystems.Based on the 2007–09 data collected at the farmland ecosystem field station in Jinzhou,the RWU function in the Common Land Model（Co LM）was optimized with scheme options in light of factors determining whether roots absorb water from a certain soil layer（W_x）and whether the baseline cumulative root efficiency required for maximum plant transpiration（W_c）is reached.The sensibility of the parameters of the optimization scheme was investigated,and then the effects of the optimized RWU function on water and heat flux simulation were evaluated.The results indicate that the model simulation was not sensitive to W_x but was significantly impacted by W_c.With the original model,soil humidity was somewhat underestimated for precipitation-free days;soil temperature was simulated with obvious interannual and seasonal differences and remarkable underestimations for the maize late-growth stage;and sensible and latent heat fluxes were overestimated and underestimated,respectively,for years with relatively less precipitation,and both were simulated with high accuracy for years with relatively more precipitation.The optimized RWU process resulted in a significant improvement of Co LM’s performance in simulating soil humidity,temperature,sensible heat,and latent heat,for dry years.In conclusion,the optimized RWU scheme available for the Co LM model is applicable to the simulation of water and heat flux for maize farmland ecosystems in arid areas.