School of Civil Engineering and UCD Dooge Centre for Water Resources Research, University College Dublin, Ireland.
School of Civil Engineering, UCD Dooge Centre for Water Resources Research and UCD Earth Institute, University College Dublin, Ireland.
Sci Total Environ. 2018 Apr 1;619-620:672-684. doi: 10.1016/j.scitotenv.2017.10.134. Epub 2017 Nov 29.
Estimates of sediment yield are important for ecological and geomorphological assessment of fluvial systems and for assessment of soil erosion within a catchment. Many regulatory frameworks, such as the Convention for the Protection of the Marine Environment of the North-East Atlantic, derived from the Oslo and Paris Commissions (OSPAR) require reporting of annual sediment fluxes. While they may be measured in large rivers, sediment flux is rarely measured in smaller rivers. Measurements of sediment transport at a national scale can be also challenging and therefore, sediment yield models are often utilised by water resource managers for the predictions of sediment yields in the ungauged catchments. Regression based models, calibrated to field measurements, can offer an advantage over complex and computational models due to their simplicity, easy access to input data and due to the additional insights into factors controlling sediment export in the study sites. While traditionally calibrated to long-term average values of sediment yields such predictions cannot represent temporal variations. This study addresses this issue in a novel way by taking account of the variation from year to year in hydrological variables in the developed models (using annual mean runoff, annual mean flow, flows exceeded in five percentage of the time (Q5) and seasonal rainfall estimated separately for each year of observations). Other parameters included in the models represent spatial differences influenced by factors such as soil properties (% poorly drained soils and % peaty soils), land-use (% pasture or % arable lands), channel slope (S1085) and drainage network properties (drainage density). Catchment descriptors together with year-specific hydrological variables can explain both spatial differences and inter-annual variability of suspended sediment yields. The methodology is demonstrated by deriving equations from Irish data-sets (compiled in this study) with the best model efficiency of 0.84 and best model fit of adjusted R of 0.82. Presented approach shows the potential for regression based models to model contemporary suspended sediment yields in small river systems.
泥沙输出量的估算对于河流系统的生态和地貌评估以及流域内土壤侵蚀的评估非常重要。许多监管框架，如源自东北大西洋保护海洋环境公约的奥斯陆和巴黎委员会（OSPAR），都要求报告年度泥沙通量。虽然在大河中可以进行测量，但在较小的河流中很少进行泥沙通量测量。在国家范围内进行泥沙输运测量也可能具有挑战性，因此，水资源管理者通常会使用泥沙输出量模型来预测未测量流域的泥沙输出量。由于其简单性、易于获取输入数据以及对研究地点控制泥沙输出的因素的额外了解，基于回归的模型经实地测量校准后，可能比复杂的计算模型具有优势。虽然传统上是根据泥沙输出量的长期平均值进行校准，但这种预测无法代表时间变化。本研究通过在开发的模型中考虑到水文变量的逐年变化（使用每年的平均径流量、每年的平均流量、超过 5%时间的流量（Q5）和每年单独估计的季节性降雨量），以新颖的方式解决了这个问题。模型中包含的其他参数代表了受土壤性质（%排水不良土壤和%泥炭土）、土地利用（%牧场或%耕地）、河道坡度（S1085）和排水网络性质（排水密度）等因素影响的空间差异。流域描述符以及每年特定的水文变量可以解释悬浮泥沙输出量的空间差异和年际变化。该方法通过从爱尔兰数据集（本研究中编制）推导出方程来演示，最佳模型效率为 0.84，最佳模型拟合调整 R 为 0.82。所提出的方法表明，基于回归的模型具有在小河流系统中模拟当代悬浮泥沙输出量的潜力。
