To obtain high-precision precipitation simulation results, different types of rainfall events in the Ili Region are simulated by using the Weather Research and Forecasting (WRF) model with different physical parameterization schemes. According to the spatiotemporal distribution of rainfall evenness, six rainfall events in the Ili Region are divided into four types. Six microphysical parameterization (MP) schemes, five planetary boundary layer (PBL) schemes, and five cumulus (CU) schemes are combined into 14 parameterization members to simulate the rainfall events. It is worth noting that the simulation result sequence of the WRF model (from best to worst) is as follows: type I (events 3 and 5) > type II (events 1 and 6) > type III (event 2) > type IV (event 4). This finding would imply that the WRF model has the best performance for rainfall events with even spatiotemporal distributions, while it is hard to achieve good simulation results for rainfall events with highly uneven spatial and temporal distributions. The results suggest that no single combination of parameterization members provides the best performance for all rainfall events. According to the overall scheme rankings, d, n, and j are the optimal parameterization combination members that accurately describe the spatiotemporal characteristics of the six rainfall events. The study provides guidance for the selection of the physical parameters for the accurate simulation of different types of rainfall events in the arid region of northwestern China.

The acquisition vegetation phenology information by using time series of satellite data is an important aspect of the application of remote sensing and climate change research . Based on the MODOS NDVI time series of images in 2000-2010, Dynamic threshold method and GIS tools were used to extract the vegetation phenology parameters of Qinling Mountains in 2000-2010 , the accuracy of remote sensing phenology results was verified combined with the measured phenological data, And analyzed the characteristis of phenological variation and the relationship between temperature changes and the phenology of Qinling region,and quantified the extent of temperature change on vegetation phenology in a macro scale. Calculated :the trend of vegetation phenology variation based on the NDVI and the results of phenological data are consistent. Results show that NDVI has good revealed effect on vegetation phenology; From 2000 to 2010,it ahead of 1.8 days at the beginning period of vegetation phenology and late back 1.2 days at the end period ; The start phenology NDVI was generally greater than the late phenology on spatial distribution; The effective temperatures and the temperature in spring, growing period had a maximum influence on NDVI at beginning phenology period,the temperatures in summer and autumn had greater impact on the final NDVI .

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Wetland ecological systems have recently suffered varying degrees of damage, significantly threatening wetland waterfowls and their living spaces. Considering Mai Po-Deep Bay Wetland as an example, the current study analyzed 14 independent variables that are closely related to ardeidae waterfowls. The actual data on ardeidae waterfowls in January 2003 were used as induced variables in a logistic regression model. Nine variable factors, including land use, normalized difference vegetation index, gradient, rainfall, TM4 vein, TM3 vein, road density, road distance, and habitat density, were obtained via screening. The precision of the model reached 0.743 via Nagelkerke R2 inspection with better fitting. The model result was used for the fast clustering for suitability classification of habitat. Classification result shows a good agreement with the actual data on ardeidae waterfowls within the same period, and the precision reached 77.4%. Finally, all variable factor data in January 2009 were collected to perform time-scale inspection on the regression equation. Moreover, the fitting precision with actual data on ardeidae waterfowls within the same period reached 75.8%. Therefore, the proposed model has better universality.