New Zealand Process Attribute Mapping: National surface water quality (2014-2018)

This dataset was developed to evaluate the method for Rissmann et al. (submitted to JGR Biogeosciences) 'A hydrochemically guided landscape-based classification for water quality: a case study application of process-attribute mapping (PoAM) at a national scale'. The data was produced from an independent surface water quality dataset, comprising 991 long-term monitoring sites across New Zealand. Water quality data was downloaded from Land Air Water Aotearoa (LAWA) for each year between 2014 – 2018 (https://www.lawa.org.nz/). Water quality data includes total nitrogen, nitrate nitrite nitrogen, ammoniacal nitrogen, total phosphorus, dissolved reactive phosphorus, turbidity, black disk (clarity), and E.coli as an indicator of microbial contamination. LAWA data is collected by each regional authority, with quality assurance performed according to National Environmental Monitoring and Reporting Standards (Davies-Colley et al., 2012). A minimum of 60 repeat measures are included for each site and medians calculated for the 5-year period. Before use by Rissmann et al., internal quality control in this project removed urban catchments and sites with point source impacts, including sites downstream of municipal wastewater discharges (identified as outliers), reducing the dataset to 811 sites. Site water quality medians for each monitoring point were combined with the mean process attribute gradient score for the capture zone. Process attribute gradients represent the four dominant processes controlling water composition, specifically atmospheric, hydrological, microbially mediated redox, physical and chemical weathering (see below). These process gradients are coupled with two land use gradients and catchment area above the monitoring site for water quality evaluation. Further details can be found in Rissmann et al. (submitted). Atmospheric O18 Precipitation source PPT Precipitation volume Hydrological RCD Macroscale recharge domain OLF Overland flow, OLFDL restricted to area of developed land DD Deep drainage LAT Lateral drainage ART Artificial drainage HYD Soil slaking and dispersion as a soil hydrological index NBP Soil zone bypass under soil moisture deficit EWT Equilibrium water table and aquifer potential Redox SRP Soil reduction potential GRP Geological aquifer reduction potential Weathering SGC Surface/top regolith strength BGC Basal regolith strength Geothermal GTH High enthalpy geothermal (≥180 °C)本数据集旨在为Rissmann等人（提交至《Journal of Geophysical Research: Biogeosciences》，JGR Biogeosciences）的研究《水文地球化学导向的基于景观的水质分类：全国尺度过程-属性映射（Process-Attribute Mapping, PoAM）的案例应用》评估相关方法。本数据集源自独立地表水水质数据集，涵盖新西兰境内991个长期监测点位。水质数据下载自Land Air Water Aotearoa（LAWA）平台2014至2018年各年度的公开数据（数据来源：https://www.lawa.org.nz/）。所包含的水质指标涵盖总氮、硝态氮与亚硝态氮、氨氮、总磷、溶解性活性磷、浊度、黑盘透明度，以及作为微生物污染指示菌的大肠杆菌（E.coli）。LAWA数据由新西兰各区域管理机构采集，并依据《国家环境监测与报告标准》开展质量控制工作（Davies-Colley等，2012）。每个监测点位至少包含60次重复测量，研究计算了该5年监测时段的水质指标中位数值。在Rissmann等人使用本数据集前，本项目通过内部质量控制流程移除了城市集水区及受点源污染影响的点位（包括市政污水排放口下游被识别为异常值的监测点位），最终将数据集缩减至811个有效点位。 各监测点位的水质中位数值与对应捕获区的平均过程属性梯度得分相结合。过程属性梯度代表控制水体化学组成的四大主导过程，具体为大气过程、水文过程、微生物介导的氧化还原过程以及物理与化学风化过程（详见下文）。上述过程梯度将与两类土地利用梯度以及监测点位上游集水区面积相结合，用于水质评估研究。更多细节可参见Rissmann等人（已投稿）的研究论文。 本次研究涉及的各类过程指标及其缩写说明如下： 1. 大气过程相关：大气氧18（Atmospheric O18）、降水源（Precipitation, PPT）、降水量（Precipitation volume） 2. 水文过程相关：宏观尺度补给域（Macroscale recharge domain, RCD）、地表径流（Overland flow, OLF；其中OLFDL仅限已开发土地区域）、深层排水（Deep drainage, DD）、侧向排水（Lateral drainage, LAT）、人工排水（Artificial drainage, ART）、土壤崩解与分散（作为土壤水文指标，Soil slaking and dispersion as a soil hydrological index, HYD）、土壤水分亏缺下的土壤区旁路（Soil zone bypass under soil moisture deficit, NBP）、平衡地下水位与含水层势能（Equilibrium water table and aquifer potential, EWT） 3. 氧化还原过程相关：土壤还原势（Soil reduction potential, SRP）、地质含水层还原势（Geological aquifer reduction potential, GRP） 4. 风化过程相关：表层/顶土层强度（Surface/top regolith strength, SGC）、基底土层强度（Basal regolith strength, BGC） 5. 地热过程相关：高焓地热（≥180℃，High enthalpy geothermal, GTH）