## 5 Conclusions  
The water quality assessment method combining Markov and remote sensing realizes the innovation of large-scale spatial monitoring across administrative boundaries instead of traditional cross-sectional monitoring. The degree of water quality improvement simulated by the Markov model can intuitively reflect how much water quality has improved or deteriorated, and can understand how the TSS level has shifted spatially. It also reflects the changes in water quality by the trend analysis of the Markov model since the local implementation of the river chief system of China in 2016.  
Taking Hedi Reservoir in the trans-provincial basin of South China as an example, a specific three-band TSS model for the inland reservoir in Guangdong Province of South China was developed (\(R^{2}=0.81,~{}~{}N=34,p\) value \(<0.01\)) based on in situ spectra and Landsat OLI imagery, which is the first such study of an inland reservoir available in Guangdong or South China, where there are as many as 6562 reservoirs in Guangdong. The TSS retrieval results also show specific heterogeneity, that is, the spatial distribution characteristics of high upstream and low downstream, where the average concentration of TSS at 31.54 mg/L in the upstream is 2.5 times that of the downstream at 12.55 mg/L.  
Generally, there were strong seasonal differences in the TSS concentration and TSS were susceptible to rainfall. When the rainfall intensity is small during the dry season, the concentration of TSS in water from upstream mankind activity is greater than the resuspension rate caused by rainfall, meaning that the TSS concentration is negatively correlated with rainfall. Meanwhile, in the flood season, since the rainfall intensity is greater, the settling rate of TSS in water is less than the resuspension rate caused by rainfall, meaning that the TSS concentration increases with the rainfall intensity. Besides, man-made interventions such as regular filling of eucalyptus and fruit tree planting also had a certain impact on TSS.  
As for the Markov dynamic evaluation of the TSS concentration, the water quality improvement effect of the upstream Shijiao Town water area is the most obvious, especially in 2018, the improvement in the water quality level crossed three levels and the TSS concentration was the lowest, which indicate the effectiveness of implementing the river chief system of China starting in September of 2017. The reasons for the TSS concentration decrease are due to the reduction in sediment mining activities and the improvement in the surrounding ecological environment, which also show that the river chief system has made great contributions to water quality monitoring and governance.  
[PERSON] went through all sectional works and wrote the paper. [PERSON] and [PERSON] designed the structure of this paper and gave some technical guidance for the paper. [PERSON], [PERSON], and [PERSON] provided expert knowledge about methods and participated in discussion. [PERSON] and [PERSON] did modeling works and gave some guidance on the content of the article. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was supported by the Science and Technology Plan Project of Guangdong Province (grant numbers 2018B030320002, 2019A050506001), the Natural Science key fund of Guangdong province (grant number 2018B030311059) and National Natural Science Foundation of China (grant number 41801364).  
**Conflicts of Interest:** The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.