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首页> 外文期刊>Earth-Science Reviews: The International Geological Journal Bridging the Gap between Research Articles and Textbooks >Traits of surface water pollution under climate and land use changes: A remote sensing and hydrological modeling approach
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Traits of surface water pollution under climate and land use changes: A remote sensing and hydrological modeling approach

机译:气候和土地利用变化下的地表水污染特征:遥感和水文模拟方法

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摘要

In this paper, spatial and temporal trajectories of land cover/land use change (LCLUC) derived fromLandsat data record are combined with hydrological modeling to explore the implication of vegetation dynamics on soil erosion and total suspended sediment (TSS) loading to surface rivers. The inter-annual coefficient of variation (CoV) of normalized difference vegetation index (NDVI) is used to screen the LCLUC and climate change. The Soil and Water Assessment Tool (SWAT) is employed to identify the monthly TSS for two times interval (1991 to 2001 and 2001 to 2011) at subbasin levels. SWAT model is calibrated from 1991 to 2001 and validated from 2002 to 2011 at three USGS gauging sites located in the study area. The Spearman's rank correlation of annual mean TSS is used to assess the temporal trends of TSS dynamics in the subbasins in the two study periods. The spatial correlation among NDVI, LCLUC, climate change and TSS loading rate changes is quantified by using linear regression model and negative/positive trend analysis. Our results showed that higher rainfall yields contribute to higher TSS loading into surface waters. A higher inter-annual accumulated vegetation index and lower interannual CoV distributed over the uplands resulted in a lower TSS loading rate, while a relatively low vegetation index with larger CoV observed over lowlands resulted in a higher TSS loading rate. The TSS loading rate at the basin outlet increased with the decrease of annual NDVI due to expanding urban areas in the watershed. The results also suggested nonlinearity between the trends of TSS loading with any of a specific land cover change because of the fact that the contribution of a factor can be influenced by the effects of other factors. However, dominant factors that shape the relationship between the trend of TSS loading and specific land cover changes were detected. The change of forest showed a negative relationshipwhile agriculture and pasture demonstrated positive relationships with TSS loading change. Our results do not show any significant causal relationship between urbanization and the TSS loading change suggesting that further investigation needs to be carried out to understand the mechanism of the impact of urban sprawl on surface water quality
机译:本文将由Landsat数据记录得出的土地覆盖/土地利用变化的时空轨迹与水文模型相结合,以探讨植被动态对土壤侵蚀和地表河流总悬浮泥沙(TSS)负荷的影响。归一化植被指数(NDVI)的年际变异系数(CoV)用于筛选LCLUC和气候变化。使用土壤和水评估工具(SWAT)来确定子盆地水平两次(1991年至2001年和2001年至2011年)的每月TSS。 SWAT模型于1991年至2001年进行了校准,并于2002年至2011年在研究区域内的三个USGS测量站进行了验证。年平均TSS的斯皮尔曼等级相关性用于评估两个研究时期子盆地中TSS动态的时间趋势。通过使用线性回归模型和负/正趋势分析来量化NDVI,LCLUC,气候变化和TSS负荷率变化之间的空间相关性。我们的结果表明,较高的降雨产量会导致较高的TSS负荷进入地表水中。较高的年际累积植被指数和较低的年际CoV分布在高地上导致较低的TSS负荷率,而相对较低的植被指数和较高的CoV在低地上观测到的则导致较高的TSS负荷率。流域出口处的TSS负荷率随着年NDVI的降低而增加,这是由于流域中城市面积的扩大。结果还表明,由于某个因素的贡献会受到其他因素的影响,因此在任何特定土地覆盖变化的情况下,TSS负荷趋势之间存在非线性关系。但是,检测到了影响TSS负荷趋势与特定土地覆盖变化之间关系的主导因素。森林变化与TSS负荷变化呈负相关,而农业和牧场与TSS负荷变化呈正相关。我们的结果并未显示出城市化与TSS负荷变化之间存在任何显着的因果关系,这表明需要开展进一步的调查以了解城市扩张对地表水水质影响的机制

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