The Relationship between Water Resources Use Efficiency and Scientific and Technological Innovation Level: Case Study of Yangtze River Basin in China

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DOI: https://doi.org/10.30564/jees.v5i2.5745

Abstract:

The Yangtze River Basin's water resource utilization efficiency (WUE) and scientific and technological innovation level (STI) are closely connected, and the comprehension of these relationships will help to improve WUE and promote local economic growth and conservation of water. This study uses 19 provinces and regions along the Yangtze River's mainstream from 2009 to 2019 as its research objects and uses a Vector Auto Regression (VAR) model to quantitatively evaluate the spatiotemporal evolution of the coupling coordination degree (CCD) between the two subsystems of WUE and STI. The findings show that: (1) Both the WUE and STI in the Yangtze River Basin showed an upward trend during the study period, but the STI effectively lagged behind the WUE; (2) The CCD of the two subsystems generally showed an upward trend, and the CCD of each province was improved to varying degrees, but the majority of regions did not develop a high-quality coordination stage; (3) The CCD of the two systems displayed apparent positive spatial autocorrelation in the spatial correlation pattern, and there were only two types: high-high (H-H) urbanization areas and low-low (L-L) urbanization areas; (4) The STI showed no obvious response to the impact of the WUE, while the WUE responded greatly to the STI, and both of them were highly dependent on themselves. Optimizing their interaction mechanisms should be the primary focus of high-quality development in the basin of the Yangtze River in the future. These results give the government an empirical basis to enhance the WUE and promote regional sustainable development.

References:

[1] UN World Water Development Report 2021 [Internet]. UN-Water [cited 2022 Dec 10]. Available from: https://www.unwater.org/publications/un-world-water-development-report-2021 [2] Chang, Y.J., Zhu, D., 2021. Water utilization and treatment efficiency of China's provinces and decoupling analysis based on policy implementation. Resources, Conservation and Recycling. 168, 105270. DOI: https://doi.org/10.1016/j.resconrec.2020.105270 [3] Yang, G., Gong, G., Gui, Q., 2022. Exploring the spatial network structure of agricultural water use efficiency in China: A social network perspective. Sustainability. 14(5), 2668. DOI: https://doi.org/10.3390/su14052668 [4] Wang, Q., Wang, X., 2020. Moving to economic growth without water demand growth—a decomposition analysis of decoupling from economic growth and water use in 31 provinces of China. Science of the Total Environment. 726, 138362. DOI: https://doi.org/10.1016/j.scitotenv.2020.138362 [5] Song, M., Wang, R., Zeng, X., 2018. Water resources utilization efficiency and influence factors under environmental restrictions. Journal of Cleaner Production. 184, 611-621. DOI: https://doi.org/10.1016/j.jclepro.2018.02.259 [6] Wang, Y., Bian, Y., Xu, H., 2015. Water use efficiency and related pollutants' abatement costs of regional industrial systems in China: A slacks-based measure approach. Journal of Cleaner Production. 101, 301-310. DOI: https://doi.org/10.1016/j.jclepro.2015.03.092 [7] Zhao, L., Sun, C., Liu, F., 2017. Interprovincial two-stage water resource utilization efficiency under environmental constraint and spatial spillover effects in China. Journal of Cleaner Production. 164, 715-725. DOI: https://doi.org/10.1016/j.jclepro.2017.06.252 [8] Bao, C., Fang, C.L., 2007. Water resources constraint force on urbanization in water deficient regions: A case study of the Hexi Corridor, arid area of NW China. Ecological Economics. 62(3-4), 508-517. DOI: https://doi.org/10.1016/j.ecolecon.2006.07.013 [9] Deng, G., Li, L., Song, Y., 2016. Provincial water use efficiency measurement and factor analysis in China: Based on SBM-DEA model. Ecological Indicators. 69, 12-18. DOI: https://doi.org/10.1016/j.ecolind.2016.03.052 [10] Liu, Y., Dong, F., 2021. How technological innovation impacts urban green economy efficiency in emerging economies: A case study of 278 Chinese cities. Resources, Conservation and Recycling. 169, 105534. DOI: https://doi.org/10.1016/j.resconrec.2021.105534 [11] Bouman, B.A.M., 2007. A conceptual framework for the improvement of crop water productivity at different spatial scales. Agricultural Systems. 93(1-3), 43-60. DOI: https://doi.org/10.1016/j.agsy.2006.04.004 [12] Statyukha, G., Kvitka, O., Shakhnovsky, A., et al., 2009. Water-efficiency as indicator for industrial plant sustainability assessment. Computer Aided Chemical Engineering. 26, 1227-1232. DOI: https://doi.org/10.1016/S1570-7946(09)70204-4 [13] Gregg, T.T., Strub, D., Gross, E., 2007. Water efficiency in Austin, Texas, 1983‐2005: An historical perspective. Journal‐American Water Works Association. 99(2), 76-86. DOI: https://doi.org/10.1002/j.1551-8833.2007.tb07870.x [14] Benedetti, I., Branca, G., Zucaro, R., 2019. Evaluating input use efficiency in agriculture through a stochastic frontier production: An application on a case study in Apulia (Italy). Journal of Cleaner Production. 236, 117609. DOI: https://doi.org/10.1016/j.jclepro.2019.117609 [15] Wang, F., Yu, C., Xiong, L., et al., 2019. How can agricultural water use efficiency be promoted in China? A spatial-temporal analysis. Resources, Conservation and Recycling. 145, 411-418. DOI: https://doi.org/10.1016/j.resconrec.2019.03.017 [16] Bian, Y., Yan, S., Xu, H., 2014. Efficiency evaluation for regional urban water use and wastewater decontamination systems in China: A DEA approach. Resources, Conservation and Recycling. 83, 15-23. DOI: https://doi.org/10.1016/j.resconrec.2013.11.010 [17] Lombardi, G.V., Stefani, G., Paci, A., et al., 2019. The sustainability of the Italian water sector: An empirical analysis by DEA. Journal of Cleaner Production. 227, 1035-1043. DOI: https://doi.org/10.1016/j.jclepro.2019.04.283 [18] Carvalho, P., Marques, R.C., 2016. Estimating size and scope economies in the Portuguese water sector using the Bayesian stochastic frontier analysis. Science of the Total Environment. 544, 574-586. DOI: https://doi.org/10.1016/j.scitotenv.2015.11.169 [19] Hong, N.B., Yabe, M., 2017. Improvement in irrigation water use efficiency: A strategy for climate change adaptation and sustainable development of Vietnamese tea production. Environment, Development and Sustainability. 19, 1247-1263. DOI: https://doi.org/10.1007/s10668-016-9793-8 [20] Zhang, F., Xiao, Y., Gao, L., et al., 2022. How agricultural water use efficiency varies in China—A spatial-temporal analysis considering unexpected outputs. Agricultural Water Management. 260, 107297. DOI: https://doi.org/10.1016/j.agwat.2021.107297 [21] Gautam, T.K., Paudel, K.P., Guidry, K.M., 2020. An evaluation of irrigation water use efficiency in crop production using a data envelopment analysis approach: A case of Louisiana, USA. Water. 12(11), 3193. DOI: https://doi.org/10.3390/w12113193 [22] Segovia-Cardozo, D.A., Rodríguez-Sinobas, L., Zubelzu, S., 2019. Water use efficiency of corn among the irrigation districts across the Duero river basin (Spain): Estimation of local crop coefficients by satellite images. Agricultural Water Management. 212, 241-251. DOI: https://doi.org/10.1016/j.agwat.2018.08.042 [23] Geng, Q., Ren, Q., Nolan, R.H., et al., 2019. Assessing China's agricultural water use efficiency in a green-blue water perspective: A study based on data envelopment analysis. Ecological Indicators. 96, 329-335. DOI: https://doi.org/10.1016/j.ecolind.2018.09.011 [24] Chen, Y., Yin, G., Liu, K., 2021. Regional differences in the industrial water use efficiency of China: The spatial spillover effect and relevant factors. Resources, Conservation and Recycling. 167, 105239. DOI: https://doi.org/10.1016/j.resconrec.2020.105239 [25] Oulmane, A., Ali, C., Frija, A., 2019. The water use efficiency and its determinants in small horticultural farms in Algeria. SN Applied Sciences. 1(10), 1236. DOI: https://doi.org/10.1007/s42452-019-1238-1 [26] Wang, X.Y., 2010. Irrigation water use efficiency of farmers and its determinants: Evidence from a survey in northwestern China. Agricultural Sciences in China. 9(9), 1326-1337. DOI: https://doi.org/10.1016/S1671-2927(09)60223-6 [27] Jin, W., Zhang, H.Q., Liu, S.S., et al., 2019. Technological innovation, environmental regulation, and green total factor efficiency of industrial water resources. Journal of Cleaner Production. 211, 61-69. DOI: https://doi.org/10.1016/j.jclepro.2018.11.172 [28] Kang, S., Hao, X., Du, T., et al., 2017. Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice. Agricultural Water Management. 179, 5-17. DOI: https://doi.org/10.1016/j.agwat.2016.05.007 [29] Miao, C., Fang, D., Sun, L., et al., 2018. Driving effect of technology innovation on energy utilization efficiency in strategic emerging industries. Journal of Cleaner Production. 170, 1177-1184. DOI: https://doi.org/10.1016/j.jclepro.2017.09.225 [30] Wang, H., Wang, M., 2020. Effects of technological innovation on energy efficiency in China: Evidence from dynamic panel of 284 cities. Science of the Total Environment. 709, 136172. DOI: https://doi.org/10.1016/j.scitotenv.2019.136172 [31] Yang, G., Gui, Q., Supanyo, P., et al., 2023. Temporal and spatial changes and influencing factors of low-carbon economy efficiency in China. Environmental Monitoring and Assessment. 195(1), 55. DOI: https://doi.org/10.1007/s10661-022-10599-3 [32] Xu, W., Zhang, X., Xu, Q., et al., 2020. Study on the coupling coordination relationship between water-use efficiency and economic development. Sustainability. 12(3), 1246. DOI: https://doi.org/10.3390/su12031246 [33] Zhang, Q., Shen, J., Sun, F., 2021. Spatiotemporal differentiation of coupling coordination degree between economic development and water environment and its influencing factors using GWR in China's province. Ecological Modelling. 462, 109794. DOI: https://doi.org/10.1016/j.ecolmodel.2021.109794 [34] Tang, C., Fan, J., Sun, W., 2015. Distribution characteristics and policy implications of territorial development suitability of the Yangtze River Basin. Journal of Geographical Sciences. 25, 1377-1392. DOI: https://doi.org/10.1007/s11442-015-1240-5 [35] Pellicer-Martínez, F., Martínez-Paz, J.M., 2016. Grey water footprint assessment at the river basin level: Accounting method and case study in the Segura River Basin, Spain. Ecological Indicators. 60, 1173-1183. DOI: https://doi.org/10.1016/j.ecolind.2015.08.032 [36] Sun, C., Zhao, L., Zou, W., et al., 2014. Water resource utilization efficiency and spatial spillover effects in China. Journal of Geographical Sciences. 24, 771-788. DOI: https://doi.org/10.1007/s11442-014-1119-x [37] Zhang, F., Sun, C., An, Y., et al., 2021. Coupling coordination and obstacle factors between tourism and the ecological environment in Chongqing, China: A multi-model comparison. Asia Pacific Journal of Tourism Research. 26(7), 811-828. DOI: https://doi.org/10.1080/10941665.2021.1925715 [38] Hu, Y., Huang, Y., Tang, J., et al., 2018. Evaluating agricultural grey water footprint with modeled nitrogen emission data. Resources, Conservation and Recycling. 138, 64-73. DOI: https://doi.org/10.1016/j.resconrec.2018.04.020 [39] Cui, S., Dong, H., Wilson, J., 2020. Grey water footprint evaluation and driving force analysis of eight economic regions in China. Environmental Science and Pollution Research. 27, 20380-20391. DOI: https://doi.org/10.1007/s11356-020-08450-8 [40] Wu, B., Zeng, W., Chen, H., et al., 2016. Grey water footprint combined with ecological network analysis for assessing regional water quality metabolism. Journal of Cleaner Production. 112, 3138-3151. DOI: https://doi.org/10.1016/j.jclepro.2015.11.009 [41] Zhang, L., Dong, H., Geng, Y., et al., 2019. China's provincial grey water footprint characteristic and driving forces. Science of the Total Environment. 677, 427-435. DOI: https://doi.org/10.1016/j.scitotenv.2019.04.318 [42] Tone, K., 2001. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research. 130(3), 498-509. DOI: https://doi.org/10.1016/S0377-2217(99)00407-5 [43] Yang, G., Gong, G., Luo, Y., et al., 2022. Spatiotemporal characteristics and influencing factors of tourism-urbanization-technology-ecological environment on the Yunnan-Guizhou-Sichuan Region: An uncoordinated coupling perspective. International Journal of Environmental Research and Public Health. 19(14), 8885. DOI: https://doi.org/10.3390/ijerph19148885 [44] Yang, G., Zhang, F., Zhang, F., et al., 2021. Spatiotemporal changes in efficiency and influencing factors of China's industrial carbon emissions. Environmental Science and Pollution Research. 28, 36288-36302. DOI: https://doi.org/10.1007/s11356-021-13003-8 [45] Guangming, Y., Qingqing, G., Fengtai, Z., et al., 2022. The temporal and spatial characteristics and influencing factors of low-carbon economy efficiency and science and technology development level in China's provinces from the perspective of uncoordinated coupling. Frontiers in Environmental Science. 10, 886886. DOI: https://doi.org/10.3389/fenvs.2022.886886