The time domain approach, i.e. Autoregressive (AR) processes, of time series analysis is applied to the monsoon rainfall series of India and its two major regions, viz. North-West India and Central India. Since the or...The time domain approach, i.e. Autoregressive (AR) processes, of time series analysis is applied to the monsoon rainfall series of India and its two major regions, viz. North-West India and Central India. Since the original time series shows no modelable structure due to the presence of high interannual variability, a 3-point running filter is applied before exploring and fitting appropriate stochastic models. Out of several parsimonious models fitted, AR(3) is found to be most suitable. The usefulness of this fitted model is validted on an independent datum of 18 years and some skill has been noted. These models therefore can be used for low skill higher lead time forecasts of monsoon. Further the forecasts produced through such models can be combined with other forecasts to increase the skill of monsoon forecasts.展开更多
To evaluate the long-term effects of reforestation types on soil erosion on degraded land, vegetation and soil properties under conventional sloping farmland （CSF） and three different reforestation types including a...To evaluate the long-term effects of reforestation types on soil erosion on degraded land, vegetation and soil properties under conventional sloping farmland （CSF） and three different reforestation types including a Pinus massoniana secondary forest （PSF）, an Eucommia ulmoides artificial economic forest （EEF） and a natural succession type forest （NST）, were investigated at runoff plot scale over a six-year period in a red soil region of southern China. One hundred and thirty erosive rainfall events generating runoff in plots were grouped into four rainfall types by means of K-mean clustering method. Erosive rainfall type I is the dominant rainfall type. The amount of runoff and the soil loss under erosive rainfall type III were the most, followed by rain-fall type II, IV and I. Compared with CSF treatment, reforestation treatments decreased the average annual runoff depth and the soil loss by 25.5%–61.8% and 93.9%– 96.2% during the study period respectively. Meanwhile, runoff depth at PSF and EEF treatments was significantly lower than that in NST treatment, but no significant difference existed in soil erosion modulus among the three reforestation treatments. This is mainly due to the improved vegetation properties （i.e., vegetation coverage, biomass of above- and below-ground and litter-fall mass） and soil properties （i.e., bulk density, total porosity, infiltration rate and organic carbon content） in the three reforestation treatments compared to CSF treatment. The PSF and EEF are recommended as the preferred reforestation types to control runoff and soil erosion in the red soil region of southern China, with the NST potentially being used as an important supplement.展开更多
文摘The time domain approach, i.e. Autoregressive (AR) processes, of time series analysis is applied to the monsoon rainfall series of India and its two major regions, viz. North-West India and Central India. Since the original time series shows no modelable structure due to the presence of high interannual variability, a 3-point running filter is applied before exploring and fitting appropriate stochastic models. Out of several parsimonious models fitted, AR(3) is found to be most suitable. The usefulness of this fitted model is validted on an independent datum of 18 years and some skill has been noted. These models therefore can be used for low skill higher lead time forecasts of monsoon. Further the forecasts produced through such models can be combined with other forecasts to increase the skill of monsoon forecasts.
基金supported by the National Natural Science Foundation of China(No.30428028)the Innovation Group Project of the National Natural Science Foundation of China(No.40621061)
文摘To evaluate the long-term effects of reforestation types on soil erosion on degraded land, vegetation and soil properties under conventional sloping farmland （CSF） and three different reforestation types including a Pinus massoniana secondary forest （PSF）, an Eucommia ulmoides artificial economic forest （EEF） and a natural succession type forest （NST）, were investigated at runoff plot scale over a six-year period in a red soil region of southern China. One hundred and thirty erosive rainfall events generating runoff in plots were grouped into four rainfall types by means of K-mean clustering method. Erosive rainfall type I is the dominant rainfall type. The amount of runoff and the soil loss under erosive rainfall type III were the most, followed by rain-fall type II, IV and I. Compared with CSF treatment, reforestation treatments decreased the average annual runoff depth and the soil loss by 25.5%–61.8% and 93.9%– 96.2% during the study period respectively. Meanwhile, runoff depth at PSF and EEF treatments was significantly lower than that in NST treatment, but no significant difference existed in soil erosion modulus among the three reforestation treatments. This is mainly due to the improved vegetation properties （i.e., vegetation coverage, biomass of above- and below-ground and litter-fall mass） and soil properties （i.e., bulk density, total porosity, infiltration rate and organic carbon content） in the three reforestation treatments compared to CSF treatment. The PSF and EEF are recommended as the preferred reforestation types to control runoff and soil erosion in the red soil region of southern China, with the NST potentially being used as an important supplement.
