African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6848

Full Length Research Paper

Status assessment and causal factors diagnosis of river system health

Jihong Xia1,2*, Junqiang Lin1 and Lei Ju1
1College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, 210098 China. 2National Center for Computational Hydroscience and Engineering, the University of Mississippi, Oxford, USA.
Email: [email protected], [email protected]

  •  Accepted: 24 April 2013
  •  Published: 09 May 2013


A healthy river system means its structures can cooperatively and orderly work together and all functions can be well brought to exert when the external disturbance is under a limit extent. This paper had presented the concept framework, which had included status assessment (SA) and cause diagnosis (CD). On the base of the method of describing entropy, health index (HI) of a river system had been defined via order degrees of indicators, which had been calculated by distance far away from their criteria as well as the health grade had been classified and the main problems had been addressed. Using partial least square (PLS) regression, CD had been conducted to diagnose main factors inducing these problems and to establish the regression equation between external variables and internal variable. Meanwhile, the variable importance projection (VIP) had been quantified. In the case of Anxi River, results of status assessment indicated that this river system was healthy in general. However, abiotic indices were low in S2 and S3 reach. After CD had been conducted, it had been revealed that problems of this river system had been induced by the variable of upstream discharge. It had been suggested helpfully that upstream discharge should be controlled in management. Therefore, river system health diagnosis was very helpful and beneficial to river system management.


Key words: River system health, status assessment, causal factors diagnosis, degree of order entropy, partial least square (PLS).