Namoi Ecological expert elicitation and receptor impact models v01

## **Abstract** \n\nThe dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.\n\n\t\n\nReceptor impact models (RIMs) use inputs from surface water and groundwater models. For a given node, there is a value for each combination of hydrological response variable, future, and replicate or run number. RIMs are developed for specific landscape classes. The hydrological response variables that a RIM within a landscape class requires are organised by the R script RIM_Prediction_CreateArray.R into an array. The formatted data is available as an R data file format called RDS and can be read directly into R. The R script IMIA_NAM_RIM_predictions.R applies the receptor model functions (RDS object as part of Data set 1: Ecological expert elicitation and receptor impact models for the NAM subregion) to the HRV array for each landscape class (or landscape group) to make predictions of receptor impact varibles (RIVs). Predictions of a receptor impact from a RIM for a landscape class are summarised at relevant AUIDs by the 5th through to the 95th percentiles (in 5% increments) for baseline and CRDP futures. These are available in the NAM_RIV_quantiles_IMIA.csv data set. RIV predictions are further summarised and compared as boxplots (using the R script boxplotsbyfutureperiod.R) and as (aggregated) spatial risk maps using GIS.\n\n## **Dataset History** \n\nReceptor impact models (RIMs) are developed for specific landscape classes. The hydrological response variables that a RIM within a landscape class requires are organised by the R script RIM_Prediction_CreateArray.R into an array. The formatted data is available as an R data file format called RDS and can be read directly into R. \n\nThe R script IMIA_NAM_RIM_predictions.R applies the receptor model functions (RDS object as part of Data set 1: Ecological expert elicitation and receptor impact models for the NAM subregion) to the HRV array for each landscape class (or landscape group) to make predictions of receptor impact varibles (RIVs). Predictions of a receptor impact from a RIM for a landscape class are summarised at relevant AUIDs by the 5th through to the 95th percentiles (in 5% increments) for baseline and CRDP futures. These are available in the NAM_RIV_quantiles_IMIA.csv data set. RIV predictions are further summarised and compared as boxplots (using the R script boxplotsbyfutureperiod.R) and as (aggregated) spatial risk maps using GIS.\n\n## **Dataset Citation** \n\nBioregional Assessment Programme (2018) Namoi Ecological expert elicitation and receptor impact models v01. Bioregional Assessment Derived Dataset. Viewed 11 December 2018, http://data.bioregionalassessments.gov.au/dataset/487a471c-7fa3-4313-871d-e048b4f4c2b4.\n\n## **Dataset Ancestors** \n\n* **Derived From** [Landscape classification of the Namoi preliminary assessment extent](https://data.gov.au/data/dataset/360c39e5-1225-401d-930b-f5462fdb8005)\n\n* **Derived From** [Namoi CMA Groundwater Dependent Ecosystems](https://data.gov.au/data/dataset/a3e21ec4-ae53-4222-b06c-0dc2ad9838a8)\n\n* **Derived From** [National Groundwater Dependent Ecosystems (GDE) Atlas (including WA)](https://data.gov.au/data/dataset/6dbaee0d-8813-46b1-9c13-1b796e7ed3bf)\n\n* **Derived From** [Border Rivers Gwydir / Namoi Regional Native Vegetation Map Version 2.0. VIS_ID 4204](https://data.gov.au/data/dataset/b3ca03dc-ed6e-4fdd-82ca-e9406a6ad74a)\n\n* **Derived From** [Bioregional_Assessment_Programme_Catchment Scale Land Use of Australia - 2014](https://data.gov.au/data/dataset/6f72f73c-8a61-4ae9-b8b5-3f67ec918826)\n\n* **Derived From** [Murray-Darling Basin Aquatic Ecosystem Classification](https://data.gov.au/data/dataset/a854a25c-8820-455c-9462-8bd39ca8b9d6)\n\n

**摘要**

本数据集由生物区域评估计划（Bioregional Assessment Programme）从多源数据集衍生而来。源数据集的相关信息已在本元数据声明的「谱系（Lineage）」字段中注明。生成该衍生数据集所采用的处理流程，已在本元数据声明的「历史（History）」字段中予以说明。

受体影响模型（Receptor Impact Models，RIMs）会引入地表水与地下水模型的输入数据。针对特定节点，水文响应变量、未来情景以及重复运行次数的每一种组合均对应一个数值。RIMs是针对特定景观类别开发的。景观类别内的RIM所需的水文响应变量，将通过R脚本`RIM_Prediction_CreateArray.R`整理为数组。格式化后的数据以R数据格式（RDS）存储，可直接读取至R环境中。R脚本`IMIA_NAM_RIM_predictions.R`会将受体模型函数（RDS对象为数据集1：NAM子区域生态专家征询与受体影响模型的一部分）应用于每个景观类别（或景观组）的水文响应变量（hydrological response variable，HRV）数组，以预测受体影响变量（RIVs）。针对某一景观类别的RIM所得到的受体影响预测结果，会在相关AUID下，以5%为间隔，对基线情景与CRDP未来情景的结果计算第5至第95百分位数进行汇总。这些汇总结果存储于`NAM_RIV_quantiles_IMIA.csv`数据集。随后，可通过R脚本`boxplotsbyfutureperiod.R`将RIV预测结果进一步汇总并绘制为箱线图，或借助地理信息系统（GIS）生成（聚合后的）空间风险地图以进行对比分析。

**数据集历史**

受体影响模型（RIMs）是针对特定景观类别开发的。景观类别内的RIM所需的水文响应变量，将通过R脚本`RIM_Prediction_CreateArray.R`整理为数组。格式化后的数据以R数据格式（RDS）存储，可直接读取至R环境中。

R脚本`IMIA_NAM_RIM_predictions.R`会将受体模型函数（RDS对象为数据集1：NAM子区域生态专家征询与受体影响模型的一部分）应用于每个景观类别（或景观组）的HRV数组，以预测受体影响变量（RIVs）。针对某一景观类别的RIM所得到的受体影响预测结果，会在相关AUID下，以5%为间隔，对基线情景与CRDP未来情景的结果计算第5至第95百分位数进行汇总。这些汇总结果存储于`NAM_RIV_quantiles_IMIA.csv`数据集。随后，可通过R脚本`boxplotsbyfutureperiod.R`将RIV预测结果进一步汇总并绘制为箱线图，或借助GIS生成（聚合后的）空间风险地图以进行对比分析。

**数据集引用**

生物区域评估计划（2018）《Namoi生态专家征询与受体影响模型 v01》。生物区域评估衍生数据集。查看日期：2018年12月11日，http://data.bioregionalassessments.gov.au/dataset/487a471c-7fa3-4313-871d-e048b4f4c2b4。

**数据集溯源**

* **衍生自** [Namoi初步评估范围景观分类](https://data.gov.au/data/dataset/360c39e5-1225-401d-930b-f5462fdb8005)
* **衍生自** [Namoi CMA地下水依赖型生态系统](https://data.gov.au/data/dataset/a3e21ec4-ae53-4222-b06c-0dc2ad9838a8)
* **衍生自** [国家地下水依赖型生态系统（GDE）图集（含西澳地区）](https://data.gov.au/data/dataset/6dbaee0d-8813-46b1-9c13-1b796e7ed3bf)
* **衍生自** [Border Rivers Gwydir / Namoi区域原生植被地图 2.0版 VIS_ID 4204](https://data.gov.au/data/dataset/b3ca03dc-ed6e-4fdd-82ca-e9406a6ad74a)
* **衍生自** [生物区域评估计划 澳大利亚集水区尺度土地利用 - 2014](https://data.gov.au/data/dataset/6f72f73c-8a61-4ae9-b8b5-3f67ec918826)
* **衍生自** [墨累-达令流域水生生态系统分类](https://data.gov.au/data/dataset/a854a25c-8820-455c-9462-8bd39ca8b9d6)