The Processes Of Vegetation Water Consumption And Its Influencing Factors In Small Watershed In The Northern Loess Plateau Of China

The nature ecological environment is very fragile in the northern loess plateau of china. Study on characteristics of vegetation water consumption and its influencing factors in a small watershed, will help to utilize water-soil resources and establish sustainable development ecosystem. In this study, in order to understand characteristics of different vegetations water consumption, the dynamics of soil moisture and water consumptions of vegetations on different land uses were analyzed. In addition, spatial variability of soil properties was investigated in a watershed on the Loess Plateau of China. The main conclusions of this study were as follows:(1) The results showed that the vertical change of soil moisture could be divided into three layers: weak absorbing layer, absorbing layer, and regulating layer. There were significant linear negative correlation between coefficient of variations and mean soil moisture, and significant linear positive correlation between extreme differences and mean soil moisture. The seasonal changes of soil water storage in different land uses were similar. In May and June the soil water storages were low, and in September and October were high. The total precipitation in the growing season was 421.5 mm in the year of 2009, which was sufficient for the growing of plants. The soil moisture was surplus for bare land, farm land, and shrub land in the end of growing season. The total precipitation was 364.7 mm in the year of 2010 which was 56.8 mm less than the year of 2009. In the end of growing season in 2010 the soil moisture was deficit. The orders of different land uses water consumptions in the year of 2009 were: wood land > grass land > shrub land > farm land > bare land. The orders of different land uses water consumptions in the year of 2010 were: grass land > shrub land > wood land > farm land > bare land.(2) The sites of LA17, LB13, and LC8 could represent the mean SWS of LA, LB, and LC subregions, respectively. The 3⁴ m SWS had higher time stabilities than other soil depths at LA and LB subregions. The time stability of SWS in LC subregion was obviously different from LA and LB subregions. The spearman rank correlation coefficients were small when the SWS varied greatly, but increased when the SWS remained more or less stable.(3) The change of vegetations height and stem diameter complied with"slow-quick-slow"curve during the different growing stages. The biomasses under PAM treatment were higher than straw mulch treatment and CK. The daily water consumption variations of the three types of vegetations were significantly affected by precipitation, indicating that evapotranspiration processes were controlled by the soil water moisture in the arid region. PAM and straw mulch could reduce the water consumption for bare land and three kinds of vegetations. PAM could increase the biomasses and improve soil properties; however straw mulch had no influence on them. There were significant correlation between the water consumption and meteorological factors on PAM treatment and CK, and no correlation on straw mulch treatment.(4) The classical statistics indicated that fractal dimension (D), pH, total porosity, and bulk density were weak variability, and ammonium nitrogen (NH₄^`+-N), extractable soil potassium (K), phosphorus (P), copper (Cu), zinc (Zn), ferrum (Fe), and manganese (Mn) were medium variability, while nitrate nitrogen (NO₃^--N) and soil hydraulic conductivity (KS) had strong variability. Soil properties were mainly correlated to land uses within the research area. The D values in the research area ranged from 1.37 to 2.66. There was a significant sigmoidal correlation between D values and the contents of clay, silt, and sand fractions. Geostatistical analyses showed that the spatial autocorrelation of all soil properties were strong. The ordinary kriging maps could provide useful information for the development and application of precision agriculture in wind-water erosion crisscross region on the Loess Plateau of China.(5) The performance of the principal components BP neural network model was well in simulating daily ET0 on the Loess Plateau. The simulation ability of principal components BP neural network model was better than tradition BP neural network model during the training stage for Yulin, Taiyuan, and Xi'an stations. The ET0 values simulated by three principal components BP neural network were consistent with the Penman-Monteith method (R2>0.95). It clearly demonstrated that high precision, simple structure and minimum error for the principal components BP neural network model in estimating ET0 compared to the tradition BP neural network model.