Soil thickness DSM data of the Southern Gulf catchments (NT and Qld) generated by the Southern Gulf Water Resource Assessment

Soil thickness is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Southern Gulf Water Resource Assessment (SOGWRA) through the digital soil mapping process (DSM). This soil thickness raster data represents a modelled dataset of soil thickness presented as a positive number in meters eg a value of 1.12 shows the soil thickness is 1.12m deep and is derived from measured site data and environmental covariates. This data may underrepresent areas of soils deeper than 1.5m as the input data was mostly only recorded to a maximum of 1.5m where achievable being the extent of the hydraulic soil corer and the general agricultural soil depth. Soil thickness is a parameter used in land suitability assessment for plant edaphic requirements (root development and structural growth) and physical support and a component in other limitations including available water capacity (AWC). This raster data provides improved soil information used to underpin and identify opportunities and promote detailed investigation for a range of sustainable regional development options and was created within the ‘Land Suitability’ activity of the CSIRO SOGWRA. A companion dataset and statistics reflecting reliability of this data are also provided and can be found described in the lineage section of this metadata record. Processing information is supplied in ranger R scripts and attributes were modelled using a Random Forest approach. The DSM process is described in the CSIRO SOGWRA published report ‘Soils and land suitability for the Southern Gulf catchments’. A technical report from the CSIRO Southern Gulf Water Resource Assessment to the Government of Australia. The Southern Gulf Water Resource Assessment provides a comprehensive overview and integrated evaluation of the feasibility of aquaculture and agriculture development in the Southern Gulf catchments NT and Qld as well as the ecological, social and cultural (indigenous water values, rights and aspirations) impacts of development. \nLineage: This soil thickness dataset has been generated from a range of inputs and processing steps. Following is an overview. For more information refer to the CSIRO SOGWRA published reports and in particular ' Soils and land suitability for the Southern Gulf catchments’. A technical report from the CSIRO Southern Gulf Water Resource Assessment to the Government of Australia. 1. Collated existing data (relating to: soils, climate, topography, natural resources, remotely sensed, of various formats: reports, spatial vector, spatial raster etc). 2. Selection of additional soil and land attribute site data locations by a conditioned Latin hypercube statistical sampling method applied across the covariate data space. 3. Fieldwork was carried out to collect new attribute data, soil samples for analysis and build an understanding of geomorphology and landscape processes. 4. Database analysis was performed to extract the data to specific selection criteria required for the attribute to be modelled. 5. The R statistical programming environment was used for the attribute computing. Models were built from selected input data and covariate data using predictive learning from a Random Forest approach implemented in the ranger R package. 6. Create soil thickness Digital Soil Mapping (DSM) attribute raster dataset. DSM data is a geo-referenced dataset, generated from field observations and laboratory data, coupled with environmental covariate data through quantitative relationships. It applies pedometrics - the use of mathematical and statistical models that combine information from soil observations with information contained in correlated environmental variables, remote sensing images and some geophysical measurements. 7. Companion predicted reliability data was produced from the 500 individual Random Forest attribute models created. 8. QA Quality assessment of this DSM attribute data was conducted by three methods. Method 1: Statistical (quantitative) method of the model and input data. Testing the quality of the DSM models was carried out using data withheld from model computations and expressed as OOB and R squared results, giving an estimate of the reliability of the model predictions. These results are supplied. Method 2: Statistical (quantitative) assessment of the spatial attribute output data presented as a raster of the attributes “reliability”. This used the 500 individual trees of the attributes RF models to generate 500 datasets of the attribute to estimate model reliability for each attribute. For continuous attributes the method for estimating reliability is the Coefficient of Variation. This data is supplied. Method 3: A workshop was conducted in March 2023 to review DSM soil attribute and land suitability products and facilitated an alternative to the field external validation carried out in other northern Australia water resource assessments. Stakeholders from the NT and Qld jurisdictions reviewed, evaluated and discussed the soundness of the data and processes. The workshop desk top assessment approach provided recommendations for acceptance, improvement and re-modelling of attributes based on expert knowledge and understanding of the soil distribution and landscape in the study area and available data.\n

土壤厚度是通过数字土壤制图过程（Digital Soil Mapping, DSM）支撑南湾水资源评估（Southern Gulf Water Resource Assessment, SOGWRA）土地适宜性评价的18项土壤属性之一。该土壤厚度栅格数据是一个建模数据集，以米为单位的正数表示土壤厚度（例如，值1.12表示土壤厚度为1.12米），基于实测站点数据和环境协变量生成。由于输入数据大多仅记录到最大1.5米（这是液压取土器的可达范围及一般农业土壤深度），因此该数据可能低估了土壤深度超过1.5米的区域。土壤厚度是土地适宜性评价中用于植物土壤需求（根系发育和结构生长）和物理支撑的参数，也是包括有效水容量（Available Water Capacity, AWC）在内的其他限制因素的组成部分。该栅格数据提供了改进的土壤信息，用于支撑和识别多种可持续区域发展方案的机会，并促进详细调查，其生成于CSIRO SOGWRA的“土地适宜性”活动中。还提供了反映该数据可靠性的配套数据集和统计信息，可在本元数据记录的谱系部分中找到相关描述。处理信息由ranger R脚本提供，属性通过随机森林（Random Forest）方法建模。DSM过程详见CSIRO SOGWRA发布的报告《南湾流域土壤与土地适宜性》——CSIRO南湾水资源评估项目向澳大利亚政府提交的技术报告。南湾水资源评估全面概述并综合评估了北领地（NT）和昆士兰州（Qld）南湾流域水产养殖和农业发展的可行性，以及发展对生态、社会和文化（原住民水价值、权利和愿望）的影响。

谱系：该土壤厚度数据集由一系列输入和处理步骤生成。以下是概述，更多信息请参考CSIRO SOGWRA发布的报告，尤其是《南湾流域土壤与土地适宜性》——CSIRO南湾水资源评估项目向澳大利亚政府提交的技术报告。1. 整理现有数据（涉及土壤、气候、地形、自然资源、遥感等，格式多样：报告、空间矢量、空间栅格等）。2. 通过在协变量数据空间应用条件拉丁超立方统计抽样方法，选择额外的土壤和土地属性站点数据位置。3. 开展野外工作，收集新的属性数据、用于分析的土壤样本，并建立对地貌学和景观过程的理解。4. 进行数据库分析，提取符合待建模属性特定选择标准的数据。5. 使用R统计编程环境进行属性计算。基于选定的输入数据和协变量数据，通过ranger R包实现的随机森林方法进行预测学习，构建模型。6. 生成土壤厚度数字土壤制图（DSM）属性栅格数据集。DSM数据是地理参考数据集，由野外观测和实验室数据结合环境协变量数据通过定量关系生成。它应用土壤计量学——即使用数学和统计模型，将土壤观测信息与相关环境变量、遥感图像及部分地球物理测量信息相结合。7. 配套的预测可靠性数据由创建的500个独立随机森林属性模型生成。8. 通过三种方法对该DSM属性数据进行质量评估（Quality Assessment, QA）。方法1：模型和输入数据的统计（定量）方法。使用模型计算中保留的数据测试DSM模型质量，结果以袋外误差（Out-of-Bag, OOB）和决定系数（R squared）表示，用于估计模型预测的可靠性。这些结果已提供。方法2：以属性“可靠性”栅格形式呈现的空间属性输出数据的统计（定量）评估。利用属性随机森林模型的500棵独立决策树生成500个属性数据集，以估计每个属性的模型可靠性。对于连续属性，可靠性估计方法为变异系数（Coefficient of Variation）。该数据已提供。方法3：2023年3月举办研讨会，审查DSM土壤属性和土地适宜性产品，为澳大利亚北部其他水资源评估中开展的野外外部验证提供替代方案。北领地和昆士兰州的利益相关者审查、评估并讨论了数据和过程的合理性。研讨会的桌面评估方法基于专家对研究区土壤分布、景观及可用数据的知识和理解，为属性的接受、改进和重新建模提供了建议。