Dynamic simulation and prediction of ecological footprint in Liaohe River Basin based on ARIMA model
Author(s): WANG Geng, WANG Jiali, SU Bailing
Pages: 632-638
Year: 2013 Issue: 4
Journal: Ecology and Environment Sciences
Keyword: ARIMA model; Liaohe River Basin; Emergy; Ecological carrying capacity; Ecological footprint;
Abstract: In this work, Based on emergy analysis and the theory of ecological footprint, the emergy-ecological footprint model was established by the coefficient of energy conversion and emergy density. The ecological carrying capacity and ecological footprint in Liaohe River basin from 2001 to 2010 were calculated via this model. The calculation of ecological carrying capacity includes the carrying capacity of natural ecological and local products output. The carrying capacity of natural ecological mainly refers to the carrying capacity of renewable resources, and the carrying capacity of local product output mainly includes the carrying capacity of biological resources and industrial products output. The calculation of the ecological footprint includes consumption footprint and pollution footprint. The consumption footprint consists of the footprint of biological resources consumption, energy consumption and water consumption, and the pollution footprint mainly calculates the load of natural ecosystems brought by exhaust gas and waste water. The results showed that the growth speed of the per capita ecological footprint was greater than one of the ecological carrying capacity. So the ecological deficit occurred in retained years except for the slight ecological surplus in 2001 and 2009. Based on the results of the emergy-ecological footprint model, the autoregressive integrated moving average (ARIMA) model by EViews was introduced to stimulate the dynamic evolution trend in the research region during decade years. Firstly, the stationarity of time series was inspected by Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root model. The diagram of the autocorrelation function and the partial autocorrelation function of the sequence were analyzed, and the order time of autoregressive (AR) and moving average (MA) were initially identified. Then the model parameters were diagnosed and estimated according to R-squared (R2), Akanke’s Information Criterion (AIC) and Schwarz Criterion (SC). The best simulation model was determined. Secondly, the evolution trend of the ecological carrying capacity and ecological footprint in Liaohe River basin from 2011 to 2015 was predicted via the ARIMA model. The results show that the per capita ecological footprint will present a significant growth in the next five years. The per capita ecological footprint will be up to 7.3878 hm2 in 2015, and this value will be 2.16 times than that of 2001. While the per capital ecological carrying capacity may present a downward trend after 2011. The value will be up to -4.167 67 hm2 in 2015 and this will be about 10 times than that of 2005. Thus the situation of unsustainable development will become worse due to expanding ecological deficit. Finally, the eco-security countermeasures of Liaohe River basin were emphasized. The results of model calculation were basically consistent with the field research, and can truly reflect the situation of sustainable development in the Liaohe River basin. The results predicted by ARMIA model stimulation can provide a reference for future watershed development and construction.
Pages: 632-638
Year: 2013 Issue: 4
Journal: Ecology and Environment Sciences
Keyword: ARIMA model; Liaohe River Basin; Emergy; Ecological carrying capacity; Ecological footprint;
Abstract: In this work, Based on emergy analysis and the theory of ecological footprint, the emergy-ecological footprint model was established by the coefficient of energy conversion and emergy density. The ecological carrying capacity and ecological footprint in Liaohe River basin from 2001 to 2010 were calculated via this model. The calculation of ecological carrying capacity includes the carrying capacity of natural ecological and local products output. The carrying capacity of natural ecological mainly refers to the carrying capacity of renewable resources, and the carrying capacity of local product output mainly includes the carrying capacity of biological resources and industrial products output. The calculation of the ecological footprint includes consumption footprint and pollution footprint. The consumption footprint consists of the footprint of biological resources consumption, energy consumption and water consumption, and the pollution footprint mainly calculates the load of natural ecosystems brought by exhaust gas and waste water. The results showed that the growth speed of the per capita ecological footprint was greater than one of the ecological carrying capacity. So the ecological deficit occurred in retained years except for the slight ecological surplus in 2001 and 2009. Based on the results of the emergy-ecological footprint model, the autoregressive integrated moving average (ARIMA) model by EViews was introduced to stimulate the dynamic evolution trend in the research region during decade years. Firstly, the stationarity of time series was inspected by Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root model. The diagram of the autocorrelation function and the partial autocorrelation function of the sequence were analyzed, and the order time of autoregressive (AR) and moving average (MA) were initially identified. Then the model parameters were diagnosed and estimated according to R-squared (R2), Akanke’s Information Criterion (AIC) and Schwarz Criterion (SC). The best simulation model was determined. Secondly, the evolution trend of the ecological carrying capacity and ecological footprint in Liaohe River basin from 2011 to 2015 was predicted via the ARIMA model. The results show that the per capita ecological footprint will present a significant growth in the next five years. The per capita ecological footprint will be up to 7.3878 hm2 in 2015, and this value will be 2.16 times than that of 2001. While the per capital ecological carrying capacity may present a downward trend after 2011. The value will be up to -4.167 67 hm2 in 2015 and this will be about 10 times than that of 2005. Thus the situation of unsustainable development will become worse due to expanding ecological deficit. Finally, the eco-security countermeasures of Liaohe River basin were emphasized. The results of model calculation were basically consistent with the field research, and can truly reflect the situation of sustainable development in the Liaohe River basin. The results predicted by ARMIA model stimulation can provide a reference for future watershed development and construction.
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