## 5 Conclusions and Perspective  
Integrating GIS and DSS methods, the RHP-EWS, an integrated system for monitoring, collecting, analyzing, interpreting, and communicating data, and helping managers make timely effective decisions, was developed, which supported the temporal-spatial analysis of natural or anthropogenic threats to river health. RHP-EWS was utilized in treating the Maria super typhoon for managers of the Shanxi River watershed so that spatial distribution and temporal variations of HI, WQI, and IBI were visualized and submitted to managers. According to the alarm signals and decision suggestions from RHP-EWS, the managers were alerted and quickly responded to the risks to take action in advance. The operators of water facilities upgraded the water preprocessing (e.g., improving the filtration capacity and increasing flocculation duration). Meanwhile, to improve the ability of sediment discharge, the command to increase the gate opening degree were sent to dam managers. After these actions were taken, the drinking water supply for Wenzhou citizens was controlled. The tool made it much easier to assess the river health status and forecast its changing trends. It was helpful to notify managers with a timely attention warning and prevent the drinking water quality from being threatened for an effective, rapid response and the first deployed defense against risks. Additionally, the user interface operation was intuitive enough that minimally skilled operators could obtain the necessary information and communicate the important processing information to the managers and users.  
However, some issues should receive additional focus. For instance, HI, WQI, and IBI assessment and forecasting should be conducted at different time or spatial scales. Spatial scales are related to three scales: catchment, reach, and segment or section. Temporal scales are classified as short-, medium-, and long-term scales. Therefore, the most suitable scale should be chosen to accurately assess and predict river health. The suitable temporal or spatial scales for a health forecasting model are dictated by the purpose for which the model is to be used. For example, particularly if a trend analysis period is too short, changes in process variables would be too slow to be efficiently detected. In the present study, trend indices were calculated using scaled measurement values to find trend episodes and deviation indices for a short period. Because of the cost of monitoring, biotic indices were only measured at a few sites within a river basin and it is almost impossible to perform continuous long-term measurements for all reaches. Implementing an emergency response plan to issue an early warning before the actual impact is a very difficult task that requires collaborative efforts at all levels of government, including federal, state, county, and local authorities and significant prior planning and practice. For watershed level threats, warning information should be communicated and broadcasted by multilateral agencies to decision-makers at local levels.  
Conceptualization, Y.C. and J.X.; methodology, Y.C., J.X. and W.C.; software, J.X. and C.D.; investigation and data preprocessing, W.C., and C.D.; writing and original draft preparation, Y.C. and J.X.; reviewing, editing and supervision, Z.S.  
This research was funded by Nation Key R & D Program of China (2018 YFD0900805), National Natural Science Foundation of China (NSFC) (41471069), and Water Resource Technology Foundation of Zhejiang Province, China (RA1104, RC1527).  
The authors appreciate help from [PERSON] and [PERSON] at the Department of Water Resources of Zhejiang Province and [PERSON], [PERSON], and [PERSON] at the Water Resources Conservancy Bureau of Wenzhou for providing us with historical data and arranging the investigation. We also acknowledged [PERSON] and [PERSON] for arranging the surveying and field sampling.  
The authors declare no conflict of interest.