Li Tianxiao

Analysis of the Effects of Different Snow Cover Mulches on Spatio-temporal Variationsof Farmland Soil Moisture

Abstract. We investigated the influence of snow cover on soil moisture in a seasonally frozen area in northern China. To do this, we performed a field test during one freeze-thaw cycle with four treatments of the test area: bare land, normal snow cover, compacted snow cover, and thick snow cover. Soil moisture depth, liquid moisture depth, frost depth, temperature, solar radiation, and other meteorological data were measured to obtain a comprehensive analysis. One-way ANOVA with Duncan‘s multiple ranges test was used to evaluate significant differences between soil moisture among all four treatments. The results demonstrated that the different snow cover treatments led to significantly different levels of soil moisture. Soil moisture accumulation area appeared obvious temporal and spatial distribution differences. However, snow cover effectively inhibited large magnitude temporal and spatial variations of the soil liquid moisture content. The feedback adjustment capability of the total soil moisture content showed that shallow profiles were more affected by different snow cover treatments than deep profiles. The compacted snow treatment was most effective for conserving soil moisture in shallow soil and improving the liquid moisture content of deep soil.

Application of Principal Component Analysis in Evaluating Influence Factors of Evaporation in Northern Cold Area

There are many meteorological factors affecting evaporation, which are not only considered comprehensively, but also their influence degree respectively. The contribution of each factor to principle component can be reflected by the coefficient of each factor in principal component equation, and then the main factor can be determined. Taking Chahayang irrigation area in Heilongjiang province for example, the data of influence factors from May to September in 2007 such as temperature, relative humidity, wind speed, vapor pressure and sunshine is analyzed with Principal Component Analysis (PCA for short). The results show that the change of evaporation is the result of the combined effect of numerous metrological factors which interact with each other, but when the temperature is kept unchanged, the average sunshine turns out to be the main factor.

Notice of Retraction Application of Principal Component Analysis in Analyzing Main Influence Factors of Increasing Grain Yield in Sanjiang Plain

In order to solve the problem of multiple correlation between area influence factors of increasing grain yield, taking Hongxinglong Bureau of Sanjiang Plain for example, principal component analysis is adopted to analyze these six main factors such as grain planting area, grain yield per hectare, effective irrigation area, fertilizer input, total power of agricultural machinery and farmland area of drought and flood. The results show that grain yield per hectare, effective irrigation area, fertilizer input and agriculture machinery total power are the key factors of increasing grain yield and it can provide scientific basis for making grain development strategy of Sanjiang Plain and construct grain security system of China.