Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM(1,1) model

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guantlng reservoir inlet and outlet （China）. The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What＇s more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.

Methane emissions from rice fields under continuous straw return in the middle-lower reaches of the Yangtze River

A three-year experiment was conducted in the middle-lower reaches of the Yangtze River in China to study the influence of continuous wheat straw return during the rice season and continuous rice straw return in wheat on methane （CH 4 ） emissions from rice fields in which, the rice-wheat rotation system is the most dominant planting pattern. The field experiment was initiated in October 2009 and has continued since the wheat-growing season of that year. The analyses for the present study were conducted in the second （2011） and third （2012） rice growing seasons. Four treatments, namely, the continuous return of wheat straw and rice straw in every season （WR）, of rice straw but no wheat straw return （R）, of wheat straw but no rice straw return （W） and a control with no straw return （CK）, were laid out in a randomized split-plot design. The total seasonal CH 4 emissions ranged from 107.4 to 491.7 kg/ha （2011） and 160.3 to 909.6 kg/ha （2012）. The increase in CH 4 emissions for treatments WR and W were 289% and 230% in the second year and 185% and 225% in the third year, respectively, in relation to CK. We observed less methane emissions in the treatment R than in CK by 14%-43%, but not statistically significant. Treatment R could increase rice productivity while no more CH 4 emission occurs. The difference in the total CH 4 emissions mainly related to a difference in the methane flux rate during the first 30-35 days after transplant in the rice growing season, which was caused by the amount of dissolved oxygen in paddy water and the amount of reducible soil materials.