CSIRO Land and Water, EcoSciences Precinct, 41 Boggo Road, Dutton Park 4102, Australia.
Mar Pollut Bull. 2012;65(4-9):101-16. doi: 10.1016/j.marpolbul.2011.08.009. Epub 2011 Sep 1.
Land use (and land management) change is seen as the primary factor responsible for changes in sediment and nutrient delivery to water bodies. Understanding how sediment and nutrient (or constituent) concentrations vary with land use is critical to understanding the current and future impact of land use change on aquatic ecosystems. Access to appropriate land-use based water quality data is also important for calculating reliable load estimates using water quality models. This study collated published and unpublished runoff, constituent concentration and load data for Australian catchments. Water quality data for total suspended sediments (TSS), total nitrogen (TN) and total phosphorus (TP) were collated from runoff events with a focus on catchment areas that have a single or majority of the contributing area under one land use. Where possible, information on the dissolved forms of nutrients were also collated. For each data point, information was included on the site location, land use type and condition, contributing catchment area, runoff, laboratory analyses, the number of samples collected over the hydrograph and the mean constituent concentration calculation method. A total of ∼750 entries were recorded from 514 different geographical sites covering 13 different land uses. We found that the nutrient concentrations collected using "grab" sampling (without a well defined hydrograph) were lower than for sites with gauged auto-samplers although this data set was small and no statistical analysis could be undertaken. There was no statistically significant difference (p<0.05) between data collected at plot and catchment scales for the same land use. This is most likely due to differences in land condition over-shadowing the effects of spatial scale. There was, however, a significant difference in the concentration value for constituent samples collected from sites where >90% of the catchment was represented by a single land use, compared to sites with <90% of the upstream area represented by a single land use. This highlights the need for more single land use water quality data, preferably over a range of spatial scales. Overall, the land uses with the highest median TSS concentrations were mining (∼50,000mg/l), horticulture (∼3000mg/l), dryland cropping (∼2000mg/l), cotton (∼600mg/l) and grazing on native pastures (∼300mg/l). The highest median TN concentrations are from horticulture (∼32,000μg/l), cotton (∼6500μg/l), bananas (∼2700μg/l), grazing on modified pastures (∼2200μg/l) and sugar (∼1700μg/l). For TP it is forestry (∼5800μg/l), horticulture (∼1500μg/l), bananas (∼1400μg/l), dryland cropping (∼900mg/l) and grazing on modified pastures (∼400μg/l). For the dissolved nutrient fractions, the sugarcane land use had the highest concentrations of dissolved inorganic nitrogen (DIN), dissolved organic nitrogen (DON) and dissolved organic phosphorus (DOP). Urban land use had the highest concentrations of dissolved inorganic phosphorus (DIP). This study provides modellers and catchment managers with an increased understanding of the processes involved in estimating constituent concentrations, the data available for use in modelling projects, and the conditions under which they should be applied. Areas requiring more data are also discussed.
土地利用(和土地管理)变化被认为是导致泥沙和养分向水体输送变化的主要因素。了解泥沙和养分(或成分)浓度如何随土地利用而变化,对于理解土地利用变化对水生生态系统的当前和未来影响至关重要。获取基于适当土地利用的水质数据对于使用水质模型计算可靠的负荷估算也很重要。本研究整理了澳大利亚流域已发表和未发表的径流量、成分浓度和负荷数据。从径流量事件中收集了总悬浮泥沙(TSS)、总氮(TN)和总磷(TP)的水质数据,重点是集水区内有单一或多数贡献面积属于单一土地利用的地区。在可能的情况下,还收集了有关养分溶解形式的信息。对于每个数据点,都包括了有关站点位置、土地利用类型和状况、集水区、径流量、实验室分析、在整个水文图上收集的样本数量以及平均成分浓度计算方法的信息。从覆盖 13 种不同土地利用的 514 个不同地理位置共记录了约 750 个条目。我们发现,使用“抓斗”采样(无明确定义的水文图)收集的养分浓度低于使用有测流计的自动采样器收集的浓度,尽管该数据集很小,无法进行统计分析。对于同一土地利用,在图块和集水区尺度上收集的数据之间没有统计学上的显著差异(p<0.05)。这很可能是由于土地状况的差异掩盖了空间尺度的影响。然而,对于集水区超过 90%的面积由单一土地利用代表的站点与集水区上游面积不到 90%由单一土地利用代表的站点相比,采集的成分样本的浓度值存在显著差异。这突出表明需要更多的单一土地利用水质数据,最好是在不同的空间尺度上。总的来说,TSS 浓度最高的土地利用是矿业(约 50,000mg/l)、园艺(约 3000mg/l)、旱地作物(约 2000mg/l)、棉花(约 600mg/l)和放牧原生牧场(约 300mg/l)。TN 浓度最高的是园艺(约 32,000μg/l)、棉花(约 6500μg/l)、香蕉(约 2700μg/l)、改良牧场放牧(约 2200μg/l)和糖(约 1700μg/l)。对于 TP,林业(约 5800μg/l)、园艺(约 1500μg/l)、香蕉(约 1400μg/l)、旱地作物(约 900mg/l)和改良牧场放牧(约 400μg/l)。对于溶解的养分部分,甘蔗土地利用的溶解无机氮(DIN)、溶解有机氮(DON)和溶解有机磷(DOP)浓度最高。城市土地利用的溶解无机磷(DIP)浓度最高。本研究为建模人员和集水区管理人员提供了对估计成分浓度所涉及的过程的深入了解、用于建模项目的数据可用性以及应在何种条件下应用这些数据的了解。还讨论了需要更多数据的领域。