scholarly journals Wavelet transform analysis of reference crop evapotranspiration during the growing season in three typical regions of Inner Mongolia, China

2017 ◽  
Vol 8 (3) ◽  
pp. 474-483
Author(s):  
Ruiping Li ◽  
Haibin Shi ◽  
Chunxia Zou ◽  
Shouzhong Hu
Keyword(s):  
Inner Mongolia ◽  
Potential Evapotranspiration ◽  
Central Area ◽  
Growing Season ◽  
Geographic Region ◽  
Wave Period ◽  
Eastern Area ◽  
Western Area ◽  
Data Driven Approach ◽  
Inner Mongolia Autonomous Region

Management and scheduling of irrigation water requires consideration of evapotranspiration, one of the most important hydrological variables. This study investigates the variations in the daily potential evapotranspiration (ET0), and its aerodynamic (ETa) and radiometric (ETr) components in three areas (western, central and eastern) of the Inner Mongolia Autonomous Region (IMAR) during the growing season (April–September, 2007). In this study, a data-driven approach was followed, and the wavelet transformation analysis method was used to investigate the evapotranspiration characteristics of a relatively large geographic region. The results show that there are close correlations in the variations of ET0 with those of ETa and ETr. For the western area of the IMAR, the timing of the largest ETa is 1 month earlier and its wave period is 10 days shorter than those of ET0 and ETr. For the central area, the wave period of ETa is 20 days shorter, and the timing of the largest ETa is approximately 1 month earlier than those of ET0 and ETr. For the eastern area, there are two large fluctuations in ETa, and they occur 1 month earlier than those of ET0.

scholarly journals Sustainability Governance in China: An Analysis of Regional Ecological Efficiency

2019 ◽  
Vol 11 (7) ◽  
pp. 1958 ◽  
Author(s):  
Xiangxiang Sun ◽  
Lawrence Loh
Keyword(s):  
Inner Mongolia ◽  
Central Area ◽  
Ecological Environment ◽  
Chinese Government ◽  
Data Envelopment ◽  
Ecological Efficiency ◽  
Eastern Area ◽  
Sulfur Dioxide Emissions ◽  
Sustainability Governance ◽  
Ecological Governance

The Chinese government is committed to sustainability governance to alleviate the shortage of energy and the imbalance between ecological environment and economic development. This paper evaluates and analyzes the sustainability governance performance of China. A bootstrap data envelopment analysis (DEA) is proposed to evaluate sustainability governance performance of 30 provinces based on ecological efficiency in China from 1998 to 2015. The results indicate that the ecological efficiency of China significantly improved as a whole, which is related to the decline in sulfur dioxide emissions. Among these provinces, Jiangsu, Liaoning, and Inner Mongolia exhibited the highest values, while Gansu, Chongqing, and Sichuan had the lowest values. The 30 provinces were divided into four sub-areas. The average ecological efficiency of the eastern area was the highest, followed by the northeast area. Compared to the east area, northeast area, and central area, we find that west area obviously falls behind. As such, the results provide helpful guidance to improve ecological governance performance.

scholarly journals NDVI-Based Vegetation Change in Inner Mongolia from 1982 to 2006 and Its Relationship to Climate at the Biome Scale

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Linghui Guo ◽  
Shaohong Wu ◽  
Dongsheng Zhao ◽  
Yunhe Yin ◽  
Guoyong Leng ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Inner Mongolia ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Potential Evapotranspiration ◽  
Vegetation Type ◽  
Growing Season ◽  
Desert Steppe

Based on the normalized difference vegetation index (NDVI), we analyzed vegetation change of the six major biomes across Inner Mongolia at the growing season and the monthly timescales and estimated their responses to climate change between 1982 and 2006. To reduce disturbance associated with land use change, those pixels affected by land use change from the 1980s to 2000s were excluded. At the growing season scale, the NDVI increased weakly in the natural ecosystems, but strongly in cropland. Interannual variations in the growing season NDVI for forest was positively linked with potential evapotranspiration and temperature, but negatively correlated with precipitation. In contrast, it was positively correlated with precipitation, but negatively related to potential evapotranspiration for other natural biomes, particularly for desert steppe. Although monthly NDVI trends were characterized as heterogeneous, corresponding to monthly variations in climate change among biome types, warming-related NDVI at the beginning of the growing season was the main contributor to the NDVI increase during the growing season for forest, meadow steppe, and typical steppe, but it constrained the NDVI increase for desert steppe, desert, and crop. Significant one-month lagged correlations between monthly NDVI and climate variables were found, but the correlation characteristics varied greatly depending on vegetation type.

scholarly journals Regional Differences in the Spatial Characteristics and Dynamic Convergence of Environmental Efficiency in China

2020 ◽  
Vol 12 (18) ◽  
pp. 7423 ◽  
Author(s):  
Shichun Xu ◽  
Yiwen Li ◽  
Yuan Tao ◽  
Yan Wang ◽  
Yunfan Li
Keyword(s):  
Economic Growth ◽  
Regional Differences ◽  
Central Area ◽  
State Level ◽  
Environmental Efficiency ◽  
Data Envelopment ◽  
Eastern Area ◽  
Western Area ◽  
The Difference ◽  
Surrounding Areas

This study uses the undesirable output and super-efficiency slacks-based measure combined with window (WIN-US-SBM) data envelopment analysis (DEA) to evaluate the environmental efficiency (EE) in 30 Chinese provinces, from 2005 to 2016, explores regional differences in the EE, and uses the dynamic spatial Durbin model (DSDM) to analyze regional differences in effects of important factors on the convergence of EE. It reveals that EE in the eastern area is higher than EE in the central and western areas, and a positive spatial autocorrelation exists in the interregional EE. The difference in provincial EE gradually narrows over time and tends to converge to its own steady-state level. Economic growth reduces EE for the central and western areas and improves efficiency for the eastern area; economic growth from surrounding areas indirectly promotes local EE for the eastern area. Foreign direct investment (FDI) promotes EE in the eastern and central areas, and FDI in the adjacent areas has a positive effect on local EE for the eastern area. Export reduces EE for all areas, and export in surrounding areas indirectly promotes local EE for the central area. Industrialization reduces EE in the western area, and industrialization in the surrounding areas increases local EE for the eastern area. Energy efficiency promotes EE for the central area, urbanization increases EE for the central area, and urbanization of the surrounding areas reduces local EE for the eastern area.

Granger Causality Test between Oil Consumption and Gross Domestic Product of China Based on the Provincial Panel Data Analysis

2012 ◽  
Vol 209-211 ◽  
pp. 1643-1646
Author(s):  
Yan Hong Li
Keyword(s):  
Energy Consumption ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Central Area ◽  
Granger Causality Test ◽  
Oil Consumption ◽  
Causality Test ◽  
Eastern Area ◽  
Western Area ◽  
Heterogeneous Panel

This paper, based on the Provincial Panel Data of 30 provinces during 1995~2010 period, applies the panel unit root, heterogeneous panel co-integration and panel based error correction models to re-investigate co-movement and the causality between oil consumption and GDP. The results show that there is one-way directional causality from energy consumption to GDP in the western area, and one-way causality from GDP to energy consumption in the central area, while no causality between energy consumption and GDP exists in the eastern area.

scholarly journals A Spatiotemporal Convolutional Gated Recurrent Unit Network for Mean Wave Period Field Forecasting

2021 ◽  
Vol 9 (4) ◽  
pp. 383
Author(s):  
Ting Yu ◽  
Jichao Wang
Keyword(s):  
Lead Time ◽  
Wave Period ◽  
Data Driven ◽  
Lead Times ◽  
Proposed Model ◽  
Data Driven Approach ◽  
Mean Wave Period ◽  
Scattering Index ◽  
Gated Recurrent Unit ◽  
Methods Numerical

Mean wave period (MWP) is one of the key parameters affecting the design of marine facilities. Currently, there are two main methods, numerical and data-driven methods, for forecasting wave parameters, of which the latter are widely used. However, few studies have focused on MWP forecasting, and even fewer have investigated it with spatial and temporal information. In this study, correlations between ocean dynamic parameters are explored to obtain appropriate input features, significant wave height (SWH) and MWP. Subsequently, a data-driven approach, the convolution gated recurrent unit (Conv-GRU) model with spatiotemporal characteristics, is utilized to field forecast MWP with 1, 3, 6, 12, and 24-h lead times in the South China Sea. Six points at different locations and six consecutive moments at every 12-h intervals are selected to study the forecasting ability of the proposed model. The Conv-GRU model has a better performance than the single gated recurrent unit (GRU) model in terms of root mean square error (RMSE), the scattering index (SI), Bias, and the Pearson’s correlation coefficient (R). With the lead time increasing, the forecast effect shows a decreasing trend, specifically, the experiment displays a relatively smooth forecast curve and presents a great advantage in the short-term forecast of the MWP field in the Conv-GRU model, where the RMSE is 0.121 m for 1-h lead time.

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