Effects of Irrigation on Soil and Wheat Yield under Drought Conditions in Sichuan

In order to study the effective water-saving cultivation of wheat in Sichuan under drought conditions to reduce grain loss,the effects of different irrigation methods（ natural rainfall,artificial irrigation,and infiltrating irrigation） on soil physical characteristics and main agronomic characters and yield of wheat were analyzed. The results showed that different irrigation treatments at different growth stages had different effects on soil physical characteristics and agronomic characters of wheat. At the seedling and jointing stage,there were small differences between the treatments in soil compactness,soil bulk density,and soil water content. At the flowering and maturation stage,different irrigation treatments had great impacts on soil compactness,soil bulk density,soil water content,and agronomic characters of wheat. In the hilly areas of Sichuan Basin,infiltrating irrigation at the jointing stage was the best,and wheat yield increased significantly,2 113. 46 kg/hm^2 higher than that in the control.

Soil-nitrogen net mineralization increased after nearly six years of continuous nitrogen additions in a subtropical bamboo ecosystem

In order to understand the effects of increasing atmospheric nitrogen （N） deposition on the subtropical bamboo ecosystem, a nearly six-year field experiment was conducted in a Pleioblastus amarus plantation in the rainy region of SW China, near the western edge of Sichuan Basin. Four N treatment levels---control （no N added）, low- N （50 kg N ha-1 a-l）, medium-N （150 kg N ha-1 a-l）, and high-N （300 kg N ha-1 a-1）--were applied monthly in the P. amarus plantation starting in November 2007. In June 2012, we collected intact soil cores in the bamboo plantation and conducted a 30-day laboratory incubation experiment. The results showed that the soil N net miner- alization rate was 0.96 4- 0.10 mg N kg-1 day-1, under control treatment. N additions stimulated the soil N net mineralization, and the high-N treatment significantly increased the soil N net mineralization rate compared with the control. Moreover, the soil N net mineralization rate was significantly and positively correlated with the fine root biomass, the soil microbial biomass nitrogen content and the soil initial inorganic N content, respectively,whereas it was negatively correlated with the soil pH value. There were no significant relationships between the soil N net mineralization rate and the soil total nitrogen （TN） content and the soil total organic carbon content and the soil C/N ratio and the soil microbial biomass carbon con- tent, respectively. These results suggest that N additions would improve the mineral N availability in the topsoil of the P. amarus plantation through the effects of N additions on soil chemical and physical characteristics and fine-root biomass.

Landform classification using soil data and remote sensing in northern Ordos Plateau of China

Landform classification is commonly done using topographic altitude only. However practice indicates that locations at a same altitude may have distinctly different landforms, depending on characteristics of soils underneath those locations. The objectives of this study were to： 1） develop a landform classification approach that is based on both altitude and soil characteristic; and 2） use this approach to determine landforms within a watershed located in northern Ordos Plateau of China. Using data collected at 134 out of 200 sampling sites, this study determined that D10 （the diameter of soil particles 10% finer by weight） and long-term average soil moisture acquired in 2010, which can be estimated at reasonable accuracy from remote sensing imagery, can be used to represent soil characteristics of the study watershed. Also, the sampling data revealed that this watershed consists of nine classes of landforms, namely mobile dune （MD）, mobile semi-mobile dune （SMD）, rolling fixed semi-fixed dune （RFD）, flat sandy land （FD）, grassy sandy land （GS）, bedrock （BR）, flat sandy bedrock （FSB）, valley agricultural land （VA）, and swamp and salt lake （SW）. A set of logistic regression equations were derived using data collected at the 134 sampling sites and verified using data at the remaining 66 sites. The verification indicated that these equations have moderate classification accuracy （Kappa coefficients K 〉 43%）. The results revealed that the dominant classes in the study watershed are FD （36.3%）, BR （27.0%）, and MD （23.5%）, while the other six types of landforms （i.e., SMD, RFD, GS, FSB, VA, and SW） in combination account for 13.2%. Further, the landforms determined in this study were compared with the classes presented by a geologically-based classification map. The comparison indicated that the geologically-based classification could not identify multiple landforms within a class that are dependent upon soil characteristics.