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Morphometric analysis of UK lake systems as a compliance tool for the European Water Framework Directive

机译:英国湖泊系统的形态学分析作为欧洲水框架指令的合规工具

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The European Water Framework Directive 2000 (WFD) stipulates that surface water bodies, such as lakes, should achieve good ecological and chemical status (pollutant levels) by 2015. However, the extant environmental monitoring programmes of most member states have major deficiencies in terms of the baseline data required, thus potentially jeopardising the compliance schedules of the WFD. Great Britain has over 40 000 lakes >1 ha, but bathymetric data are available for less than 2%. This paper presents a collation of available bathymetric data (622 sites) and demonstrates the utility of morphometiic analysis to bridge the gap between surveyed and un-surveyed systems. Type-specific relations between mean (Dmv) and maximum (Dmax) water depths were developed for natural lakes (r2 values ranging from 0.87 to 0.99), as well as modified systems and impoundments (r2 values ranging from 0.74 to 0.99). Stepwise regression was also undertaken to predict D,m and Dmax using only map-derived information (such as lake area, catchment area and shoreline length). The results varied markedly between "geological types", with "medium alkalinity" (MA) lakes giving the highest coefficients of determination (R2 of 0.79 and 0.82, respectively). Predicting D,m is important because it permits calculation of parameters such as the volume (V) (and hence residence time) and dynamic ratio (DR) which provides a measure of the likely extent of sediment re-suspension. This preliminary analysis has demonstrated the potential of the morprrometric approach to generate valuable parameters from limited field investment and will provide a valuable stop-gap until the results of the WFD's comprehensive monitoring programmes are realized.
机译:欧洲水框架指令2000(WFD)规定,到2015年应达到湖泊等地面水体,如湖泊,应达到良好的生态和化学地位(污染物水平)。然而,大多数成员国的现存环境监测计划有重大缺陷所需的基线数据,从而可能危及WFD的合规时间表。英国拥有超过4万棵湖泊> 1公顷,但是浴权数据可用不到2%。本文介绍了可用的碱基数据(622个位点)的整理,并展示了形态学分析的效用,以弥合受测量和未调查系统之间的差距。平均值(DMV)和最大(DMAX)水深之间的类​​型特定关系用于自然湖泊(R2值范围为0.87至0.99),以及改性系统和蓄水量(R2值范围为0.74至0.99)。还采用逐步回归仅使用仅使用地图衍生的信息(例如湖区,集水区和海岸线长度)来预测D,M和DMAX。 “地质型”之间的结果在“地质类型”之间具有多样化,“中碱度”(MA)湖泊,其测定系数最高(分别为0.79和0.82)。预测D,M是重要的,因为它允许计算诸如体积(V)(以及因此停留时间)和动态比(DR)的参数,其提供了沉积物重新悬架的可能程度的测量。这一初步分析证明了莫雷雷米方法从有限的现场投资产生有价值参数的潜力,并将提供有价值的停止差距,直到粮食计划署的综合监测计划的结果实现。

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