Turbidity,　relating　to　underwater　light　attenuation,　is　an　important　optical　parameter　for　water　quality　evaluation.　Satellite　estimation　of　turbidity　in　alpine　rivers　is　challenging　for　common　ocean　color　retrieval　models　due　to　the　differences　in　optical　properties　of　the　water　bodies.　In　this　study,　we　present　a　simple　two-band　semi-analytical　turbidity　(2BSAT)　retrieval　model　for　estimating　turbidity　in　five　alpine　rivers　with　varying　turbidity　from　1.01　to　284　NTU.　The　model　was　calibrated　and　validated,　respectively,　while　using　one　calibration　dataset　that　was　obtained　from　the　Three　Parallel　Rivers　basin　and　two　independent　validation　datasets　that　were　obtained　from　the　Kaidu　River　basin　and　the　Yarlung　Zangbo　River　basin.　The　results　show　that　the　model　has　excellent　performance　in　deriving　turbidity　in　alpine　rivers.　We　verified　the　consistency　of　the　simulated　reflectance　and　satellite-based　reflectance　and　calibrated　the　2BSAT　model　for　the　specified　bands　of　high　spatial　resolution　satellites　in　order　to　achieve　the　goal　of　remote　sensing　monitoring.　It　is　concluded　that　the　model　can　be　used　for　the　quantitative　monitoring　of　turbidity　in　alpine　rivers　using　satellite　images.　Based　on　the　model,　we　used　the　Sentinel-2　images　from　one　year　to　identify　the　seasonal　patterns　of　turbidity　of　five　alpine　rivers　and　the　Landsat　series　images　from　1989　to　2018　to　analyze　the　turbidity　variation　trends　of　these　rivers.　The　results　indicate　that　the　turbidity　of　these　alpine　rivers　usually　presents　the　highest　level　in　summer,　followed　by　spring　and　autumn,　and　the　lowest　in　winter.　Meanwhile,　the　variation　trends　of　turbidity　over　the　past　30　years　present　distinctly　different　characteristics　in　the　five　rivers.