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Sediment discharge from an agricultural watershed: investigating the influence of land-cover fragmentation using the GSSHA model

机译:农业流域的泥沙排放:使用GSSHA模型调查土地覆盖碎片化的影响

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Land-cover patterns may serve as significant predictors of sediment discharge. The GSSHA model, a distributed physically-based watershed model, was used for the Todoroki watershed (Ishigaki Island, Okinawa, Japan) to estimate sediment discharge for different land-cover conditions as inferred from Landsat images (1984-2003). Results indicate that over the past 20 years, the changing land cover of the Todoroki watershed, in the direction of increasing sugarcane areas, had enhanced sediment discharge from the watershed. However, landscape patterns exhibited a comparable or even stronger relationship with sediment discharge compared to land-cover percentages. Based on regression analyses, four pattern metrics (number of patches, radius of gyration, splitting, and cohesion) accounted for 99% of the variability of discharged sediment volume (RMSE = 9.6) compared to 89.5% represented by land-cover percentages (RMSE = 31.6). The pattern metrics plus percentages of forest and sugarcane jointly represented almost 100% of the variability (RMSE = 0.0015). Pattern metrics have more predictive capability than land-cover percentages and can improve understanding of watershed sediment discharge process.
机译:土地覆盖的格局可以作为沉积物排放的重要预测指标。 GSSHA模型是基于物理的分布式分水岭模型,用于Todoroki分水岭(日本冲绳县石垣岛),根据Landsat影像(1984-2003年)推断出不同土地覆盖条件下的泥沙排放量。结果表明,在过去的20年中,Todoroki流域的土地覆盖变化(沿甘蔗面积增加的方向)增强了该流域的泥沙排放。然而,与土地覆盖率相比,景观格局与泥沙排放具有可比甚至更强的关系。根据回归分析,四种模式指标(斑块数,回转半径,分裂和粘聚)占排泄沉积物体积变化率(RMSE = 9.6)的99%,而以土地覆盖率(RMSE)代表的变化率为89.5%。 = 31.6)。模式指标加上森林和甘蔗的百分比共同代表了几乎100%的变异性(RMSE = 0.0015)。模式指标比土地覆盖率具有更强的预测能力,并且可以增进对流域沉积物排放过程的了解。

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