MBC Groundwater model uncertainty analysis

## **Abstract** \n\nThis 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\n\nThis data set comprises a series of outputs produced from the groundwater model runs. This include drawdown grids corresponding to 95 percentile drawdown obtained as a difference between the baseline and crdp runs. The follwoing steps were involved in producing these outputs.\n\n1) 200 runs each of the baseline and CRDP versions of the model were undertaken\n\n\n\n 2) The maximum drawdown (dmax) and time of maximum (Tmax) drawdown were computed for each of the 200 runs for each m odel layer.\n\n\n\n3) The 95th percentile of the Dmax and Tmax were computed by removing the highest 10 (5% of 200) Dmax and Tmax values using the C code in the folder 95_percentile_drawodwn\n\n\n\n4) The probablity of exceedence of 5 and 0.2 m drawdown were computed as a percentage of the 200 runs. The probabilities were gridded and plotted to the MBC maps.\n\n## **Purpose** \n\nThese formed the basis of the figures in the MBC 2.6.2 product.\n\n## **Dataset History** \n\nThis a derived data set. All the inputs for this data set were obtained from the groundwater model data set. The outputs have been derived from Monte Carlo runs to produce upper and lower statistical boundaries for uncertainty analysis. Plots were developed for inclusion in the MBC 2.6.2 product using outputs from Python scripts.\n\n\n\nThe grids in this dataset have been extracted to correspond to their respective geological model boundary.\n\n## **Dataset Citation** \n\nBioregional Assessment Programme (2016) MBC Groundwater model uncertainty analysis. Bioregional Assessment Derived Dataset. Viewed 25 October 2017, http://data.bioregionalassessments.gov.au/dataset/484c800e-55e0-465a-9243-c440311c51f3.\n\n## **Dataset Ancestors** \n\n* **Derived From** [MBC Groundwater model](https://data.gov.au/data/dataset/6fe25546-a6ca-44fc-a101-51b1758e2890)\n\n* **Derived From** [MBC Groundwater model mine footprints](https://data.gov.au/data/dataset/6c87cc94-7186-4fdd-a58c-6d52dc5856b1)\n\n* **Derived From** [MBC Groundwater model uncertainty plots](https://data.gov.au/data/dataset/44f36874-d053-4cfb-9ccd-d5407e3b1b18)\n\n* **Derived From** [MBC Groundwater model layer boundaries](https://data.gov.au/data/dataset/32b986d0-c3d0-4a01-a5a9-6fffde638e11)\n\n

## **摘要**

本数据集由生物区域评估计划（Bioregional Assessment Programme）基于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，而该衍生数据集的生成流程则详见本元数据声明的**历史（History）**字段。

本数据集包含一系列地下水模型（groundwater model）模拟运行的输出结果，其中包括由基准情景（baseline）与CRDP情景模拟的水位降深（drawdown）差值计算得到的95分位水位降深栅格数据。生成此类输出的具体步骤如下：

1）分别对该模型的基准情景版本与CRDP版本开展200次模拟运行。

2）针对每个模型层的200次模拟运行，分别计算其最大降深（Dmax）与最大降深出现时间（Tmax）。

3）通过移除200组数据中数值最高的10个（占总样本的5%）Dmax与Tmax值，结合`95_percentile_drawdown`文件夹中的C语言代码，计算得到Dmax与Tmax的95分位数。

4）以200次模拟运行为基准，计算水位降深超越5米与0.2米的概率（以百分比形式呈现）。随后将这些概率数据栅格化，并绘制至MBC地图中。

## **目的**

本数据集为"MBC 2.6.2"产品中的相关图表提供了核心数据支撑。

## **数据集历史**

本数据集为衍生数据集，其全部输入数据均来自地下水模型数据集。本次输出通过蒙特卡洛模拟（Monte Carlo runs）生成，用于构建不确定性分析所需的上下统计边界。相关绘图则依托Python脚本生成的输出结果完成，用于纳入"MBC 2.6.2"产品中。

本数据集内的栅格数据已按对应的地质模型边界进行提取。

## **数据集引用**

生物区域评估计划（2016）MBC地下水模型不确定性分析. 生物区域评估衍生数据集. 检索于2017年10月25日，http://data.bioregionalassessments.gov.au/dataset/484c800e-55e0-465a-9243-c440311c51f3.

## **数据集溯源**

* **衍生自** [MBC地下水模型](https://data.gov.au/data/dataset/6fe25546-a6ca-44fc-a101-51b1758e2890)
* **衍生自** [MBC地下水模型矿区影响范围](https://data.gov.au/data/dataset/6c87cc94-7186-4fdd-a58c-6d52dc5856b1)
* **衍生自** [MBC地下水模型不确定性绘图](https://data.gov.au/data/dataset/44f36874-d053-4cfb-9ccd-d5407e3b1b18)
* **衍生自** [MBC地下水模型层位边界](https://data.gov.au/data/dataset/32b986d0-c3d0-4a01-a5a9-6fffde638e11)

搜集汇总

背景与挑战

背景概述

该数据集是澳大利亚生物区域评估计划衍生的地下水模型不确定性分析数据集，基于蒙特卡洛模拟生成95百分位水位降深网格和超概率统计，用于评估Maranoa-Balonne-Condamine次区域的地下水变化风险。数据来源于多次模型运行，旨在支持水文地质学研究和决策制定，覆盖昆士兰州特定地质边界。