During the Fifth Plenum of the 18th Central Committee of the Communist Party of China, the five development ideas of “innovation, coordination, green, open, and sharing” are proposed and will be implemented in the thirteenth Five-Year Plan. In the five ideas, innovation is regarded as the first driver to promote the development of economy, especially the theoretical innovation, institutional innovation, technological innovation and culture innovation. In the traditional industry base in Northeast China, innovation is undoubtedly the key point to solve the structural and institutional obstacles, enhance the development of energy and abilities, and explore new development mode. On the basis of exploring the relationship between innovation development and overall revitalization, this article analyzes the significance, implementation way, and countermeasures of innovation development for comprehensively revitalizing Northeast China. In the third part, the article proposes new ideas, new patterns and new mechanisms for comprehensively revitalizing northeast China. First, the article suggests that it is the most important policy to reconstruct the think-tank systems and build the first driver for industry development. Second, it proposes to implement the precision talent action plan and supply safeguard for comprehensively revitalizing northeast China. Third, it promotes action for stabling the agriculture yields and promoting the product quality, and further pushes the innovation of modern agricultural development. Fourth, it recommends implementing the innovation action for the whole industry chain, improving the productivity and increasing the production efficiency. Fifth, it puts forward to the perspective of taking the function zone to be the flat of innovation development environment and regional innovation carrier. On one hand, to realize the comprehensively revitalization northeast China, the central government should: 1) make breakthroughs in reform and innovation in important areas, including deepen reform of the administrative system, further streamline administration and delegate more power to lower-level governments; 2) usher in a new phase of Northeast China’s opening to the outside world and ensure its high standard performance; 3) advance agricultural modernization and rural reform and development; 4) use the innovation to support and lead economic structural improvement and upgrading. On the other hand, the Northeast China should make the most of the government's innovation and entrepreneurship drive to turn innovation into a major source of development, according to the document.
The state-owned enterprise has been playing an irreplaceable role in the regional industrial technological progress, structural transformation and economic growth. In the construction of state-owned enterprise innovation and development of regional economic growth effect theoretical model, through the construction of the innovation and development of state-owned enterprises and economic growth evaluation index system, based on Cointegration and VEC model, this article analyzes on the number of economic growth and the quality of the economy growth of state-owned enterprises in three provinces of the Northeast China. The empirical results indicate that there is a non synchronous relation between quality and quantity of state-owned enterprise innovation and development and regional economic growth in the three provinces of Northeast China and it is significantly different to their relationship in the whole China. From the view of the impact of innovation development on the quantity and quality of economic growth in state-owned enterprises, in the short term, the level of innovation promotes the economic growth quantity and quality of the three provinces in Northeast China, but in the long run, the growth in the quantity of the economy is based on the decline of the quality of the economy. In the three provinces of Northeast China, the impact of the level of innovation shows the difference. Whether in the whole country or in the provinces in Northeast China or not, the quantity and the quality of economic growth mutually promote each other. In the three provinces of Northeast China, the quantity of economic growth has more influence on the quality of economic growth. In terms of the relationship between quantity and quality of economic growth, firstly, the level of innovation development promotes economic growth by capital investment, and the quantity of growth is bound to bring about the improvement of economic quality. To be further, economic quality growth will bring a breakthrough in the quantity of economic growth. Therefore, the future economic growth should practice the social system, natural system and economic system to achieve a harmonious and sustainable economic development model.
Through analyzing the ecological system, the corresponding evaluation index system and ecological niche models have been constructed to evaluate the government intervention intense and marketization level of the three provinces in Northeast China and 34 cities at the prefectural level. Then the pattern and trend of "government functions play a leading role while market functions play a supporting role" is further analyzed. A significant conclusion drawn out of the article when having conducted quantitative analyses is that there generally exists the status quo with "the government playing a leading role while the market playing a supporting role" in the three provinces in Northeast China and such a fact is the most prominent in Heilongjiang Province but less and less prominent in Jilin Province and Liaoning Province in turn. There is a fact that the setup with “the government playing a leading role while the market playing a supportive role” has witnessed a number of fluctuations in various areas in Northeast China but the decreasing margin was the largest from 2003 to 2005. It is proved that the influence of the Strategy of Revitalizing Northeast China formulated in 2003 is rather less sustainable, and that the setup with "the government playing a leading role while the market playing a supporting role" has an obvious regional spillover effect in various prefectures and cities in Northeast China. Such a setup is more obviously distributed in those regions that are rather far away from key cities or ports on the coast, including North Heilongjiang and certain inland cities in both Liaoning and Jilin Provinces.
In order to find the impact of industrial transformation on the industrial pollution discharge and its spatial pattern, this article analyzes the dynamic coupling relationship between industrial growth and SO2 emission with the index of decoupling coefficients with industrial SO2 as the object and prefecture level city of as the unit. It was found that the industrial outputs of cities in Northeast China have really increased while its industrial SO2 emission decreased in 2005-2013. So, the revitalization of old industrial base in Northeast China could be seen as “green revitalization”. Then, the LMDI model was used to divide the decoupling coefficients into scale, industrial structure and technology upgrading effect. This article found that the scale effect expressed as growth of industrial output value has a positive driving impact on the growth of industrial SO2 emissions; industrial technology progress promotes the industrial SO2 emission reduction, and industrial structure's role varies from city to city. Mostly, the higher technology effect is concentrated in special industrial cities in the peripheral of mega city region while scale effect is concentrated in core mega city and coastal cities in Liaoning Province. Industrial transformation of Shenyang metropolitan area is significant and effective, where the development of equipment manufacture sector and decrease of ratio of high SO2-load sectors in total output had led into the reducing of SO2 emission. On the other side, in the cities around Bohai Sea of Liaoning Province and cities with wood processing and basic energy and raw material industries as regional pillar industry in Jilin and Heilongjiang provinces, the rising of ratio of energy and basic material sector to total industrial output has led to the growth of industrial SO2 emission. Finally, according to the main driving factors and limiting factors of SO2 emission reduction in different cities, this article puts forward policy recommendations to promote the green transformation in Northeast China.
In recent years, the economic development of Northeast China has come to the new normal state, the overall economic development has grown downward, and the phenomenon has become the focus concerned by researchers and the society. However, the development gap between cities is gradually expanding, and it has become a main barrier for Northeast China to achieve all-round well-off society. As such, this article builds a comprehensive evaluation index system for economic development level by three terms of economic base, economic growth and economic structure. Then the paper comprehensively studies the economic development, spatial differentiation and its evolution of Northeast China over its revitalized 10 years through factor analysis method and ESDA. The results are as follows: 1) Over the past 10 years, the economic development of Northeast China has obtained a certain degree of improvement. But the overall economic development level of Northeast China rises first and then decreases. 2) The economic development of Northeast China is spatially clustered, and the trend is strengthened over time. Meanwhile, the differences of cities on Northeast China are expanding. The northern area of Heilongjiang province is the weakest area of economic development level in Northeast China. 3) The economic development level of the cities whichareold industrial bases has been promoted at a certain degree, while that of the resource-based cities has been declined.The differences of economic development of the resource-based cities are more significant. Among the resource-based cities, the economic development level of the recessionary cities decline seriously, such as Yichun, Hegang, Shuangyashan, Qitaihe and Daxing’anling. At the same time, these cities only belong to the resource-based cities. 4) In terms of the economic development of Northeast China, it shows three kinds of patterns: the core-periphery mode with the core of four megacities, the agglomeration development pattern with the growth axis from Harbin to Dalian, and the mode with the economic development differences between the southern coastal cities to the northern border cities. The economic development of cities located in the axis from Harbin to Dalian or around the four major urban agglomerations is well. In order to impel the development of Northeast China, the government should lower the regional economic development well, and prevent further expanding of differences among these cities. When developing the cities belong to old industrial base constantly, the government should make the reasonable industrial transformation and increase policy support for the resource-based cities especially the recessionary cities, then gradually improve the ability of economic development. The northern are of Heilongjiang Province needs to get more support from the Central government, who should promote its economic development and prevent the gap with other cities to expand further.
China has entered the era of rapid outward direct investment (ODI) expansion. Recently, “the Belt and Road” strategy and the Northeast Asia Economic Integration have provided boarder opportunities for outward direct investment of Northeast China. Promoting ODI is not only a necessary stage for Northeast China to build all-round opening up economy, but also a developing chance for revitalization of Northeast China. With the provincial ODI data by captical and insititutions from 2003 to 2014, this article firstly analyzes the spatio-temporal pattern of Northeast Chinese ODI. Then we used the geographically weighted regression model to detect the crucial factors that influence the development of Northeast Chinese ODI as well as its changing trend. Based on previous analysis, several suggestions were proposed to facilitate Northeast Chinese ODI. The results are as follows: 1) Northeast Chinese embraced a rapid growth after the financial crisis in 2008, but faced with downward pressure recently. The divergence of provincial ODI enlarged quickly, especially after 2008 when ODI of Liaoning province promptly surpassed ODI of Heilongjiang province. 2) Firms in Northeast China tend to invest directly near their home, thus the largest host country of Northeast Chinese ODI is Russia. Korea Peninsula and Japan are also on the list of the most attractive destinations the most attractive destinations of Northeast Chinese ODI. 3) Resource-seeking ODI is typical in Northeast China. More than 40% Northeast Chinese firms invested abroad in forestry, farming and mining industries. And most Northeast Chinese ODI aims at market and trade service. 4) GDP, export and the level of economy nationalization had positive influence with Northeast Chinese ODI from 2003 to 2013. GDP and export had relatively less impact on ODI in Northeast China than in other regions, while the level of economy nationalization played more and more important role in the expansion of Northeast Chinese ODI. In contrast, the impact of technology on ODI was not so significant in Northeast China. The gap of supply and demand of resource turned to be the most critical factor of the development of Northeast Chinese ODI from 2003 to 2013. Financial environment was supportive for firms in Northeast China to invest directly abroad in 2003, but became backward or even adverse in 2013. In the end, based on the results, we proposed that firms in Northeast provinces should enhance cooperation when investing abroad, and take a spatially differentiated investing strategy to avoid vicious competition. Heilongjiang province may aim at the market in Russia and Mongolia, while Jilin province may focus on investing in Korea and Japan. Liaoning province should strengthen ODI in North America and Europe, as well as critical coutries along the Maritime Silk Road such as Singapore, India and Indonesia. Northest China should exploit the advantages of SOEs to promote private ODI. Local governments of Northest China should further implement effective financial policies to encourage technology-seeking ODI and promote reverse technology spillover.
Influenced by the development of knowledge economy and scientific technology, innovation-driven development is becoming an important strategy of economic development. The spatial patterns of innovation resources and its’ relation with economic development largely influence the economic development. Therefore, it is significant to explore the relationship between innovation resources and industry development. This article examines the relationship between innovation resources and industry development from both the spatial and industrial perspectives, using the methods of exploratory spatial data analysis and quadrant map approach. The results indicate that: both the innovation resources and industry development are under the state of agglomeration in space, while the degree of spatial agglomeration of different industrial sectors are quite different. The industrial sectors of automobile industry, general equipment manufacturing industry, special equipment manufacturing industry and medicine industry have relatively higher degree of spatial agglomeration than the others. Spatially, the counties and districts of Dalian, Shenyang, Changchun and Harbin belong to the over-innovation or under-innovation, especially the industrial sectors of automobile industry and general equipment manufacturing industry, while the spatial patterns of the relationship between innovation resources and industry development share the different characters.
Economic growth rate in northeast China has dropped suddenly in the latest two years, beyond a reasonable range. “New Northeast Phenomenon” has attracted widespread attention from academic community and policy-makers, the rejuvenation of northeast China has been one hot-debated national development issue. Expanding opening up and developing foreign trades, is not only an important part of the whole strategy of rejuvenation of northeast China, but the significant method to achieve the revitalization of northeast. To identify the trading partner, the key industrial fields and space carriers of foreign trade in Northeast China, is much importance to upgrading the foreign trade volume and level. Firstly, this article analyzes the overall trading volume and partners of Northeast China. Secondly, it studies the internal spatial pattern of foreign trade at provincial and prefecture levels, as well as commodity structures of foreign trade in Northeast China. Data sources include 2003-2014 Statistical Yearbook and Statistical Bulletin of three provinces in Northeast China, Chinese customs statistics in 2014. The results show that: 1) While trade volume with Southeast Asia and Middle East has grown, Japan, South Korea, Germany, the United States and Russia has remained the important trading partners for Northeast China. 2) The trading commodity are mostly raw materials, primary processed products and labor-intensive products, implying the commodity exported from northeast China as whole is low- value added . 3) Major cities and coastal port cities are the main spatial carriers of foreign trading in Northeast China. Additionally, the article put forwards the different development strategy for foreign trade according to the current situation and challenges.
Resources based industry (RBI) is not only a main industry that drives secondary industry development but it is also the basis of manufactures such as products of the petrochemical industry. It plays an important role in the regional development of Northeast China for hundred years. Nowadays, RBI is the most significant foundation to promote China’s government’s strategy of revitalizing old Northeastern industrial bases. It is of great academic and practical value to analyze to RBI development and its spatial evolution. We employ the Shift-Share analysis and exploratory spatial data analysis to examine the characteristics of RBI. Conclusions are as follows: 1) Shift-Share analysis shows that structure effect of RBI is higher than competitive effect. Both structure effect and competitive effect of Jinlin province are high, which represent a good growth trend. RBI of Heilongjiang province shows an opposite condition. Both of the two effects are negative value, indicating a depressed RBI development status. The main growth of RBI in Liaoning province comes from structure effect rather than competitive effect; 2) Spatial distribution of RBI shows an unbalanced status. Different cities have different dependence on RBI. Based on the ratio of RBI, cities are divided into 5 classifications. 3) Viewing from Moran’s I,RBI shows a trend from random to aggregation. Hot spots of RBI are moving towards coastal regions of Liaoning province. Different industries present different spatial evolution characteristics.According to these characteristics, some suggestions are pointed out, e.g. different industry policy, RBI technological innovation, industry zone and precision management,spatial optimal allocation and resources-oriented international strategy.
This article applies input-output analysis method to measuring the global value chain position of Northeast China’s industries. We find that in the northeast of China, the mining and other basic industries have a large amount of value-added in trade, but are faced with the threats of excess capacity and low-end locking. While the status of manufacturing industries is relatively low in trade, these industries show an obvious comparative disadvantage that tends to deteriorate. In terms of specific province in Northeast China, the overall level of industrial technology and status in Liaoning Province is higher, whose disadvantage in the mining is relatively small, the disadvantages of Jilin Province in the manufacturing industry is larger, and Heilongjiang Province has an average level of industrial value chain position, but has a more serious excess capacity and low-end locking risk in the mining. Therefore, in order to upgrade the global value chain position of Northeast China, we need to transform the traditional principle of industry development and foreign trade, strengthen the construction of innovation ability and combine information technology with traditional industry to realize a new industrial pattern and innovation-driven intensive development.
Industrial bases in Northeast China have made outstanding contributions to China’s modernization. However, the industries in this area declined sharply due to variety of reasons, which gradually became a regional problem. Industrial transition must be the key to solve the plight of its economic development. This article constructs an index system of industrial bases identification. From the national scale, it identifies and selects different industrial bases in Northeast China at the year 1985, 2001 and 2010. It then analyses the evolution characteristics of those industrial bases and explores different industrial evolution paths according to their types. Conclusions are as follows: 1) The overall industry status significantly decreased in Northeast China from 1985 to 2010. Most of its industrial bases have single industrial structures, which are dominated by traditional industries. This kind of structure has not undergone substantial changes, especially the equipment manufacturing industry. 2) Industrial bases in Northeast China can be extracted as three types: resource-based, mature and declining. Their industrial structure evolution paths are different, so are the corresponding transition modes. Resource-based industrial bases have maintained a single dominant industry. Their transformation should turn to resources deep processing while exploiting. The main focus of transformation should be on how to strengthen the supporting capability of alternative industries. As a result, this kind of bases would become new raw material bases or extend their industry chains to build comprehensive industrial bodies including energy, basic raw materials and equipment manufacturing. 3) The industry combination of mature industrial bases changed from multi-industry portfolio to double-industry portfolio. Mature industrial bases should continue to rely on industrial parks, developing advanced manufacturing and promoting industrialization by new urbanization. It means to develop modern service industry, improve urban environment and strengthen infrastructure construction. It aims to promote the products-manufacturing industries transforming to service-oriented ones as well as coordinate the development of manufacturing and service industries. 4) The industry combination of declining industrial bases evolved from multi-industry mixed mode to signal industry dominated mode. In the future, the development of declining industrial bases should depend on the division of regional integration, so as to promote their own industry development gradually.
In the globalization and information era, with the development of knowledge economy, regional innovation capacity is increasingly becoming the determinant of competitive advantage. Especially for Northeastern Old Industrial Base, the innovation of science and technology has become the key support for improving comprehensive regional strength, and the strong lead for changing the mode of regional industrial structure and production. It is against such a background that this article takes a close examination on the spatio-temporal evolution of innovation capacity and its economic contribution in Northeast China. Based on literature review, principal components analysis and fuzzy analytic hierarchy process, we establish innovation capacityindex(ICI), in order to provide a more comprehensive explanation of innovation development trends. We also try to gauge and justify the economic impacts of innovation development, by regression analysis and modeling economic contribution of innovation(ECI). The findings of this article are salutary. In general, in 2003-2014, Northeast China has achieved a great development in regional innovation capacity, and has improved the economic contribution of innovation. But its rank in China has declined, as the development of ICI in Western China and Central China are much faster. Firstly, the development of ICI in Jilin and Liaoning Province are much faster than Heilongjiang, while provincial gap is becoming bigger. At local scale, there are significant regional differences in ICI, while regional digital gap is becoming smaller. Secondly, the spatial distribution of ICI has obviously positive correlation with local GDP development. At provincial scale, innovation in Liaoning Province has strongly promoted economic development, while Jilin and Heilongjiang Province are much weakly. At local scale, the difference of ECI among cities is also very remarkable, while Shenyang, Dalian, Changchun and Daqing share much higher ECI. Thirdly, the development model of most cities are ‘low ICI-low ECI’ and ‘high ICI-high ECI’, which illustrate that there are critical spatial difference between cities’innovation capacity and its economic contribution.
Using grain production statistical data at county level from 2003 to 2013, this article analyzes the spatio-temporal pattern and its main driving factor of grain production in the west of Northeast China. Based on K-means cluster analysis, grain production contribution rate and PSR conceptual framework model is established. According to the given target of reducing maize sown area in the planned "sickle-shape" area of China, theoretic target of specific reducing maize sown area is calculated at county level in the west of Northeast China. This can provide a scientific reference for the optimum layout of grain production and change of grain structure. The results indicate that grain sown area and grain production has presented a rising trend in the west of Northeast China since 2003. More specifically, maize and rice have an advantage in grain sown area and production quantities, while the proportion of soybean decreases. Spatial pattern of grain production in the west of Northeast China had changed apparently. Most of this region has been replaced by the maize-based type due to an expansion of maize planting. The grain sown area, rather than the grain yield per hectare and inner-grain structure, is the main influential factor from the result of grain production contribution rate during 2003 to 2013. Evaluation composite index score of cultivated land ecological security in the west of Northeast China were all under 0.6 and all these composite index scores were in the range of the threshold interval between insecurity type and critical-insecurity type. From the perspective of spatial distribution, the insecurity type and relative-insecurity type were dominant, of which the percentage was 97.01%, and these two type region were concentrated-distribution. Therefore, measures must be taken urgently to adjust the grain structure for improving land ecological security in the west of Northeast China. Given the target of reducing maize sown area in the "sickle-shape" area and the theoretic result of PSR framework model, the theoretically calculated planning target of reducing maize sown area in the west of Northeast China is totally 1.45×106 hm2 (21.78×106 mu). In more detail, the theoretic reducing maize sown area is 1.13×106 hm2 (16.98×106 mu) in the agro-pasture transitional zone and the theoretic reducing maize sown area is 0.32×106 hm2 (4.80×106 mu) in the north cold region. On the basis of theoretic calculation, the regions of reducing maize sown area are mainly distributed in some counties of Chifeng City, Tongliao City, Xingan League, in the west of Jilin Province, in the west of Liaoning Province and some maize-based type region. According to previous analysis and results, reducing land should be conducted based on local ecology, economy and society conditions in the process of reducing maize sown area at county level. Simultaneously, land ecological security, the peasant livelihood substitute and benefit compensation should be taken fully into account to reduce maize sown area scientifically, rationally and sequentially.
Resources and environment are material conditions of economic development and foundation of human survival, which can promote economy development, both hinder economy development sometimes. In the long-term practice and study, people gradually realize the importance of coordinated development relationship between economy and environment. In recent years, the Changjiang River Economic Belt (CREB) becomes national development strategy, which ought to take task of driving economic development and shoulder responsibility of ecological environment protection. In this article, we firstly evaluate space and time patterns of economic-environmental coordinated development in CREB, and then analyze industrial pollution emissions and environmental quality situation of CREB. Results show below. Economic-environmental coordinated development degree reveals spatial differences that degree of the eastern CREB is bigger than central and eastern regions, and regions along the Changjiang River is higher than other regions. Regions with high coordinated development degree are mainly located in the Changjiang River Delta and parts in the capital cities of central and eastern CREB. Otherwise, regions with low coordinated development degree mainly are located in Chongqing, central Hubei Province, the northern Anhui Province and the southwestern Yunnan Province. Industrial wastewater discharges mostly in Chongqing, Suzhou and Hangzhou. Cities with coordinated development degree declined mainly are located in Jiangxi Province and Sichuan Province. Economic status of cities in the core of Changjiang River Delta is still prominent, but that of peripheral cities in the Changjiang River Delta is in a downward trend; and economy level rank of some cities in the central and western CREB rises significantly. Chongqing, Suzhou and Hangzhou are the regions which discharge industrial wastewater emissions mostly. Regions with most industrial SO2 emissions reveal three concentrated areas where are “Z” glyph area in the Changjiang River Delta, southwest area and central area. Shanghai, Hangzhou, Nanjing, Nantong, Xuzhou discharge industrial fumes emissions mostly. Cities with poor air quality are located in peripheral Changjiang River Delta and central and eastern CREB along the Changjiang River. Section water quality of Changjiang River upstream and downstream is poorer; nevertheless that in middle is better. Three suggestions put forward for CREB development: 1) To shoulder the dual responsibility of economic development and environmental protection and innovate system and mechanism of CREB development (e.g. green GDP). 2) To promote downstream urban economic transformation and upgrading and foster new economic growth poles in the upstream and midstream of the Changjiang River. At the same time, cities in the upstream and midstream should transfer concept of economic development from “race to bottom” to “race to up” and avoid serious pollution transfer in the industry transfer process. 3) To implement the most strict management and legal system and build demonstration belt of ecological civilization.
Since 2008, China has adopted a new round of regional planning and regions have formulated diverse regional plans to enhance their competitiveness. One of the most notable features is that the decentralization of central government facilitating the efforts of local governments on institutional innovation. However, previous studies examined cross-border region cooperation is conceptual, but the empirical studies are limited and little has known about the roles of local governments involved in for planning implementation. Pearl River Delta Reform and Development Plan (2008-2020) is the first regional planning proposed by provincial government and issued by central government in 2008. Its implementation and the role of local governments involved is a less researched area. There are a large number of research works regarding multi-level governance theory in the western academic world. However, whether it works well under Chinese context need a further exploration. Guangzhou-Foshan Metropolitan region is selected as a case. By means of in-depth interview and document analysis, this article aims to examine the roles of different levels of local governments in Guangzhou-Foshan regions in the process of implementing the Pearl River Delta Reform and Development Plan (2008-2020) by the combination of the macro perspective, policy initiatives, with micro perspective, project analysis. Driven by administrative pressures and economic development, the roles of provincial government and municipal governments have changed, and cross-border region cooperation has made good progress on institutional building. Moreover, it is found that the existing mode of Guangzhou-Foshan cooperation is regarded as a type of “project-based municipal city-level single cooperation mode”, which is rather vulnerable and instable; and this mode is quite different from western practices of multi-level governance. Despite the fact that the vertical communication and interaction between different local authorizes have increased, the governments at the district level and town level do not have an effective communication platform and a directly cooperative mechanism, due to the restriction of current administrative system in China. The citizens are excluded from this cross-border region cooperation, and have no channels to express their demands. The findings provide some policy implications on regional planning implementation and cross-border region cooperation for other regions in China.
Using the Correlation index of industrial structure transformation, the temporal and spatial evolution characteristics of industrial structure as well as the effects changing on regional development are explored with the spatial analysis of GIS from year 2000 to 2012 in Xuzhou Metropolitan Area. The results show as follows： in the recent 10 years, the speed and optimization of industrial transformation showed an increasing trend which had a positive impact on economic growth, while the degree of industrial structure rationalization decreased. The capital and technology intensive industry gradually played a dominant role in the superiority industries and leading industries, and the supporting role of leading industries need to be enhanced. The spatial distribution of industry evolved from agglomeration to diffusion, forming the development center along the East Longhai. The degree of spatial agglomeration performed different among industrial departments. Industrial specialization showed an obvious difference. The technical level of Xuzhou was higher than the peripheral region which presented a circle layer pattern. The positive impact of industrial optimization and share on economic growth was significant. Furthermore, it considered that industrial optimization and share both contributed to the reduction of energy consumption and sulfur dioxide emissions. The impact on region of different scale was different.
Forecasting of hydrological drought plays an important role in the decision-making process of water resources management. Bayesian networks provide an elegant tool to reflect the autocorrelation in the runoff record and develop the conditional probabilities, furnishing a framework for various types of probabilistic drought forecasting. This study presents a Bayesian probabilistic forecasting model based on best-fitted first-order copula functions. Standardized runoff index (SRI) is used to characterize the historical hydrological droughts and forecast probabilistic drought by season runoff correlations of a target season with the previous seasons in future. We used the Xidaqiao hydrological station in the Aksu River, sub-basin of the Trim River Basin of Xinjiang as a case, and apply the Bayesian probabilistic forecasting model to forecast the probability of autumn drought during the period 2000-2010 based on data from the previous summer, and testing the accuracy of the model. The results show that the probability of an autumn drought in the Aksu River Basin during 2001-2009 was low (24%-38%), with mainly abnormal and moderate droughts, whereas drought was very likely to occur in 2010 (95%), with the probability of occurrence of an exceptional drought being as high as 81%. The model is reliable and can forecast hydrological drought in the next season when current hydrological conditions are known. And the model can quantitatively express the uncertainty of hydrological drought and then improve its prediction accuracy. It does not require the linear assumption of normality and has a wide range of applications. The model provides an useful tool for uncertainty modeling through a probabilistic representation of model parameter uncertainty, developing conditional probabilities for given forecast variables, and returning the highest probable forecast along with an assessment of the uncertainty around that value. However, this study only selects the highest seasonal correlation as a condition, and further studies of hydrological drought forecasting are needed using high-dimensional copula functions. Furthermore, it’s a very urgent task to use more hydrological sites to forecast regional hydrological drought.
