The　Chinese　Loess　Plateau,　the　world＇s　largest　loess　deposit,　is　characterized　by　distinctive　landforms　and　severe　soil　erosion.　Limited　long-term　observational　data　has　hindered　a　comprehensive　understanding　of　watershed　evolution　in　this　region.　This　study　uses　laboratory-based　artificial　rainfall　simulations　to　investigate　the　long-term　geomorphological　evolution　of　watersheds　on　the　Chinese　Loess　Plateau.　Digital　elevation　models　and　terrain　analysis　techniques　were　employed　to　analyze　geomorphological　processes.　Through　correlation　analysis　and　Sheffield　entropy　calculations,　an　optimal　combination　of　terrain　factors-including　slope,　aspect,　plan　curvature,　profile　curvature,　and　elevation-was　identified　to　accurately　describe　slope　characteristics.　Multi-resolution　image　segmentation,　Moran＇s　I,　and　weighted　variance　were　used　to　optimize　segmentation　parameters,　achieving　precise　slope　unit　segmentation.　Based　on　these　parameters,　we　classified　slope　shapes,　constructed　slope　shape　spectra,　and　analyzed　their　changes　over　time.　Results　indicate　that　as　the　watershed　evolves,　the　entropy　of　slope　spectra　increases　while　skewness　and　kurtosis　decrease,　indicating　greater　geomorphological　complexity　and　diversity.　The　watershed＇s　evolution　progresses　through　three　stages:　slope　shape　development,　slope　shape　growth,　and　slope　shape　maturity,　each　marked　by　distinct　geomorphological　features.　By　analyzing　landscape　indices　at　both　class　and　landscape　levels,　we　observed　significant　variation　during　the　early　development　stage,　followed　by　stabilization　during　the　maturation　phase.　These　findings　demonstrate　that　slope　shape　spectra　effectively　capture　the　dynamic　evolution　of　slopes　in　the　Chinese　Loess　Plateau,　offering　new　insights　for　understanding　its　geomorphological　evolution　and　providing　a　novel　method　for　quantitative　geomorphology.