Abstract
The spatial characteristics and the high-duty water regions of the Water Usage Patterns (WUP) are very important for the allocation and management of water resources. Taken Hubei province, China as an example, we adopted the exploratory spatial data analysis (ESDA) method to investigate the spatial dependence and local patterns of the WUP from 2003 to 2012. Subsequently, the spatial variation mechanisms were analyzed through the gravity center model. The results indicated that the overall spatial dependence of the agricultural WUP was detected (more significant after 2008). Moreover, the global spatial autocorrelation analysis results on the domestic WUP showed statistical significance (Moran’s I > 0.1, P < 0.05). These indicated that the local patterns were presented. The high values clustering areas of the agricultural and domestic WUP were mainly distributed in the central province and in the western province respectively. However, the approximate random distribution was identified for the industrial WUP because the industrial development had been conducted widely in the whole province during these years. Furthermore, the governmental policies and natural environment contributed to the spatial evolution tendency of the WUP. An increasing trend of the spatial association of the agricultural WUP and a significant decreasing trend of that of the domestic WUP, which suggested that the natural circumstance superiority and the industrial structure adjustment related to water utilization has been utilized and implemented effectively. This study can provide a useful reference and guidance for scientific planning of water resource systems.
Similar content being viewed by others
References
Al-Faraj FAM, Tigkas D, Scholz M (2016) Irrigation efficiency improvement for sustainable agriculture in changing climate: a transboundary watershed between Iraq and Iran. Environ Process 3:603–616. doi:10.1007/s40710-016-0148-0
Anselin L (1995) Local indicators of spatial association-LISA. Geogr Anal 27:93–115
Anselin L (1999) Interactive techniques and exploratory spatial data analysis. Geographical information systems: principles, techniques, management and applications. Cambridge, Geoinformation Int, pp 253–266
Braz G, de Paiva AC, Silva AC, de Oliveira ACM (2009) Classification of breast tissues using Moran’s index and Geary’s coefficient as texture signatures and SVM. Comput Biol Med 39:1063–1072. doi:10.1016/j.compbiomed.2009.08.009
Chen C, Ma H, Chen N, Chen H (2014) The evolution of network gravity center for rural residents tourist flow in China. Geogr Res 33:1306–1314 (in Chinese)
Chen Y-Y et al (2015) Spatial analysis of Schistosomiasis in Hubei Province, China: a GIS-based analysis of Schistosomiasis from 2009 to 2013. Plos One 10. doi:10.1371/journal.pone.0118362
Cracolici MF, Cuffaro M, Nijkamp P (2009) A spatial analysis on Italian unemployment differences. JISS 18:275–291. doi:10.1007/s10260-007-0087-z
Dall’erba S (2005) Distribution of regional income and regional funds in Europe 1989-1999: an exploratory spatial data analysis. Ann Reg Sci 39:121–148. doi:10.1007/s00168-004-0199-4
Fischer G, Tubiello FN, Van Velthuizen H, Wiberg DA (2007) Climate change impacts on irrigation water requirements: effects of mitigation, 1990-2080. Technol Forecast Soc Chang 74:1083–1107. doi:10.1016/j.techfore.2006.05.021
Getis A, Ord JK (1992) The analysis of spatial association by use of distance statistics. Geogr Anal 24:189–206. doi:10.1111/j.1538-4632.1992.tb00261.x
House-Peters LA, Chang H (2011) Urban water demand modeling: review of concepts, methods, and organizing principles. Water Resour Res 47. doi:10.1029/2010wr009624
Hussien WA, Memon FA, Savic DA (2016) Assessing and modelling the influence of household characteristics on Per capita water consumption. Water Resour Manag 30:2931–2955. doi:10.1007/s11269-016-1314-x
Jiang Y (2009) China’s water scarcity. J Environ Manag 90:3185–3196. doi:10.1016/j.jenvman.2009.04.016
Kerckhof A, Spalevic V, Van Eetvelde V, Nyssen J (2016) Factors of land abandonment in mountainous Mediterranean areas: the case of Montenegrin settlements. Springerplus 5. doi:10.1186/s40064-016-2079-7
Li Q, Wei Y-N, Dong Y (2016) Coupling analysis of China’s urbanization and carbon emissions: example from Hubei Province. Nat Hazards 81:1333–1348. doi:10.1007/s11069-015-2135-6
Messner SF, Anselin L, Baller RD, Hawkins DF, Deane G, Tolnay SE (1999) The spatial patterning of county homicide rates: an application of exploratory spatial data analysis. J Quant Criminol 15:423–450. doi:10.1023/a:1007544208712
Min M, Zhao W, Hu T, Chen J, Nie X (2014) Influential factors of spatial distribution of wheat yield in china during 1978-2007: a spatial econometric analysis. IEEE J Sel Top Appl Earth Obs Remote Sens 7:4453–4460. doi:10.1109/jstars.2014.2325898
Mukheibir P, Currie L (2016) A whole of water approach for the city of Sydney. Water Util J 12:27–38
National Bureau of Statistics of China (2015) China statistical yearbook. China Statistics Press, Beijing
Patacchini E, Rice P (2007) Geography and economic performance: exploratory spatial data analysis for great Britain. Reg Stud 41:489–508. doi:10.1080/00343400600928384
Qin Z, Zhang P (2011) Simulation analysis on spatial pattern of urban population in Shenyang City, China in Late 20th century. Chin Geogr Sci 21:110–118. doi:10.1007/s11769-011-0444-6
Quah D (2011) The global economy’s shifting centre of gravity. Global Pol 2:3–9
Rybarczyk G, Wu C (2010) Bicycle facility planning using GIS and multi-criteria decision analysis. Appl Geogr 30:282–293
Schlosser CA et al (2014) The future of global water stress: an integrated assessment. Earths Future 2:341–361. doi:10.1002/2014ef000238
Sun W, Li WH, Tang ZP, Fan J (2016) Industrial structure optimization in central China under the energy constraint. J Geogr Sci 26:1377–1388. doi:10.1007/s11442-016-1333-9
Tang CH, Yi YJ, Yang ZF, Cheng X (2014) Water pollution risk simulation and prediction in the main canal of the South-to-North Water Transfer Project. J Hydrol 519:2111–2120. doi:10.1016/j.jhydrol.2014.10.010
Tobler WR (1970) A computer movie simulating urban growth in the detroit region. Econ Geogr 46:234–240, Stable URL: http://www.jstor.org/stable/143141
Tsakiris G (2015) The status of the European waters in 2015: a review. Environ Process 2:543–557. doi:10.1007/s40710-015-0079-1
Venetsanou P, Voudouris K, Kazakis N, Mattas C (2015) Impacts of urbanization, agriculture and touristic development on groundwater resources in the eastern part of Thermaikos Gulf (North Greece): an application of DPSIR model for sustainable development. Eur Water 51:3–13
Wang J, Liu Y (2009) The changes of grain output center of gravity and its driving forces in China since 1990. Resour Sci 31:1188–1194
Wu H, Wang XJ, Shahid S, Ye M (2016a) Changing characteristics of the water consumption structure in Nanjing City, Southern China. Water 8. doi:10.3390/w8080314
Wu Y, Li S, Yu S (2016b) Monitoring urban expansion and its effects on land use and land cover changes in Guangzhou city, China. Environ Monit Assess 188. doi:10.1007/s10661-015-5069-2
Ye X, Wu L (2011) Analyzing the dynamics of homicide patterns in Chicago: ESDA and spatial panel approaches. Appl Geogr 31:800–807. doi:10.1016/j.apgeog.2010.08.006
Yue W, Zhang Y, Ye X, Cheng Y, Leipnik MR (2014) Dynamics of multi-scale intra-provincial regional inequality in Zhejiang, China. Sustainability 6:5763–5784. doi:10.3390/su6095763
Zhang S, Zhang K (2007) Comparison between general Moran’s index and getis-Ord general G of spatial autocorrelation. Acta Sci Natur Univ Sunyatseni 46:93–97
Zheng WS, Run JY, Zhuo RR, Jiang YP, Wang XF (2016) Evolution process of urban spatial pattern in Hubei province based on DMSP/OLS nighttime light data. Chin Geogr Sci 26:366–376. doi:10.1007/s11769-016-0814-1
Zhou Y, Wang Y, Li Y, Zwahlen F, Boillat J (2012) Hydrogeochemical characteristics of central Jianghan Plain, China. Environ Earth Sci 68:765–778. doi:10.1007/s12665-012-1778-9
Zhou H, Huang J, Yuan Y, Tang B (2016) An examination of a partial least squares-based dynamic water quota model for urban industries: a case study of the Wuhan City hospital industry. Urban Water J 13:156–166. doi:10.1080/1573062x.2014.949798
Acknowledgements
This work was supported by the CRSRI Open Research Program (CKWV2015242/KY); the National Natural Science Foundation of China [No.41071104], [No.41171319], [No.41571514]; the Fundamental Research Funds for the Central Universities (WUT: 142208001).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflicts of Interest
The authors declare no conflict of interest.
Rights and permissions
About this article
Cite this article
Zhou, H., Huang, J. & Yuan, Y. Analysis of the Spatial Characteristics of the Water Usage Patterns Based on ESDA-GIS: An Example of Hubei Province, China. Water Resour Manage 31, 1503–1516 (2017). https://doi.org/10.1007/s11269-017-1591-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-017-1591-z