TY - JOUR
T1 - A generic framework to analyse the spatiotemporal variations of water quality data on a catchment scale
AU - Yang, Qinli
AU - Scholz, Miklas
AU - Shao, Junming
AU - Wang, Guoqing
AU - Liu, Xiaofang
N1 - Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2019/12
Y1 - 2019/12
N2 - Most spatiotemporal studies treat spatial and temporal analysis separately. However, spatial and temporal changes occur simultaneously and are correlated. In this study, we propose a generic framework to simultaneously analyse the spatial and temporal variations of water quality on a catchment scale. Specifically, we analyse the heterogeneity of temporal evolution of water quality data among different sampling sites, and the heterogeneity of spatial distribution of water quality data over different sampling times, respectively, by integrating the techniques of normalized mutual information, dynamic time wrapping and cluster analysis. To bring deep insight into the spatiotemporal variations, inter-change and intra-change are further defined and distinguished, respectively. Taking the Fuxi River catchment as a case study, results indicate that the proposed framework is intuitive and efficient. Beyond this, the generic framework can be expanded for other catchments and various environmental data.
AB - Most spatiotemporal studies treat spatial and temporal analysis separately. However, spatial and temporal changes occur simultaneously and are correlated. In this study, we propose a generic framework to simultaneously analyse the spatial and temporal variations of water quality on a catchment scale. Specifically, we analyse the heterogeneity of temporal evolution of water quality data among different sampling sites, and the heterogeneity of spatial distribution of water quality data over different sampling times, respectively, by integrating the techniques of normalized mutual information, dynamic time wrapping and cluster analysis. To bring deep insight into the spatiotemporal variations, inter-change and intra-change are further defined and distinguished, respectively. Taking the Fuxi River catchment as a case study, results indicate that the proposed framework is intuitive and efficient. Beyond this, the generic framework can be expanded for other catchments and various environmental data.
KW - Cluster analysis
KW - Dynamic time warping
KW - Environmental data
KW - Spatiotemporal analysis
UR - http://www.scopus.com/inward/record.url?scp=85034786742&partnerID=8YFLogxK
U2 - 10.1016/j.envsoft.2017.11.003
DO - 10.1016/j.envsoft.2017.11.003
M3 - Article
AN - SCOPUS:85034786742
SN - 1364-8152
VL - 122
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
M1 - 104071
ER -