AWARE characterization factor samples
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Files contain 5000 samples of AWARE characterization factors, as well as sampled independent data used in their calculations and selected intermediate results. AWARE is a consensus-based method development to assess water use in LCA. It was developed by the WULCA UNEP/SETAC working group. Its characterization factors represent the relative Available WAter REmaining per area in a watershed, after the demand of humans and aquatic ecosystems has been met. It assesses the potential of water deprivation, to either humans or ecosystems, building on the assumption that the less water remaining available per area, the more likely another user will be deprived. The code used to generate the samples can be found here: https://github.com/PascalLesage/aware_cf_calculator/ Samples were updated from v1.0 in 2020 to include model uncertainty associated with the choice of WaterGap as the global hydrological model (GHM). The following datasets are supplied: <strong>1) AWARE_characterization_factor_samples.zip</strong> Actual characterization factors resulting from the Monte Carlo Simulation. Contains 4 zip files: * monthly_cf.zip: contains 116,484 arrays of 5000 monthly characterization factor samples for each of 9707 watershed and for each month, in csv format. Names are cf_<BAS34S_ID>_<MONTH>.csv, where <BAS34S_ID> is the watershed id and <MONTH> is the first three letters of the month ('jan', 'feb', etc.). * average_agri_cf.zip: contains 9707 arrays of 5000 annual average, agricultural use, characterization factor samples for each watershed, in csv format. Names are cf_average_agri_<BAS34S_ID>.csv. * average_non_agri_cf.zip: contains 9707 arrays of 5000 annual average, non-agricultural use, characterization factor samples for each watershed, in csv format. Names are cf_average_non_agri_<BAS34S_ID>.csv. * average_unknown_cf.zip: contains 9707 arrays of 5000 annual average, unspecified use, characterization factor samples for each watershed, in csv format. Names are cf_average_unknown_<BAS34S_ID>.csv.. <strong>2) AWARE_base_data.xlsx</strong> Excel file with the deterministic data, per watershed and per month, for each of the independent variables used in the calculation of AWARE characterization factors. Specifically, it includes: Monthly irrigation<br> Description: irrigation water, per month, per basin<br> Unit: m3/month<br> Location in Excel doc: Irrigation<br> File name once imported: irrigation.pickle<br> table shape: (11050, 12) Non-irrigation hwc: electricity, domestic, livestock, manufacturing<br> Description: non-irrigation uses of water<br> Unit: m3/year<br> Location in Excel doc: hwc_non_irrigation<br> File name once imported: electricity.pickle, domestic.pickle,<br> livestock.pickle, manufacturing.pickle<br> table shape: 3 x (11050,) avail_delta<br> Description: Difference between "pristine" natural availability<br> reported in PastorXNatAvail and natural availability calculated<br> from "Actual availability as received from WaterGap - after<br> human consumption" (Avail!W:AH) plus HWC.<br> This should be added to calculated water availability to<br> get the water availability used for the calculation of EWR<br> Unit: m3/month<br> Location in Excel doc: avail_delta<br> File name once imported: avail_delta.pickle<br> table shape: (11050, 12) avail_net<br> Description: Actual availability as received from WaterGap - after human consumption<br> Unit: m3/month<br> Location in Excel doc: avail_net<br> File name once imported: avail_net.pickle<br> table shape: (11050, 12) pastor<br> Description: fraction of PRISTINE water availability that should be reserved for environment<br> Unit: unitless<br> Location in Excel doc: pastor<br> File name once imported: pastor.pickle<br> table shape: (11050, 12) area<br> Description: area<br> Unit: m2<br> Location in Excel doc: area<br> File name once imported: area.pickle<br> table shape: (11050,)<br> It also includes: * information (k values) on the distributions used for each variable (uncertainty tab) * information (k values) on the model uncertainty (model uncertainty tab) * two filters used to exclude watersheds that are either in Greenland (polar filter) or without data from the Pastor et al. (2014) method (122 cells), representing small coastal cells with no direct overlap (pastor filter). (filters tab) <strong>3) independent_variable_samples.zip</strong> Samples for each of the independent variables used in the calculation of characterization factors. Only random variables are contained. For all watershed or watershed-months without samples, the Monte Carlo simulation used the deterministic values found in the AWARE_base_data.xlsx file. The files are in csv format. The first column contains the watershed id (BAS34S_ID) if the data is annual or the (BAS34S_ID, month) for data with a monthly resolution. the other 5000 columns contain the sampled data. The names of the files are <variable_name.csv>. <strong>4) intermediate_variables.zip</strong> Contains results of intermediate calculations, used in the calculation of characterization factors. The zip file contains 3 zip files: * AMD_world_over_AMD_i.zip: contains 116,484 arrays (for each watershed-month) of 5000 calculated values of the ratio between the AMD (Availability Minus Demand) for the watershed-month and AMD_glo, the world weighted AMD average. Format is csv.<br> * AMD_world.zip: contains one array of 5000 calculated values of the world average AMD. Format is csv. * HWC.zip: contains 116,484 arrays (for each watershed-month) of 5000 calculated values of the total Human Water Consumption. Format is csv. <strong>5) watershedBAS34S_ID.zip</strong> Contains the GIS files to link the watershed ids (BAS34S_ID) to actual spatial data.
本数据集包含5000份AWARE特征因子（AWARE characterization factors）样本，以及用于计算这些特征因子的独立采样数据与部分中间计算结果。 AWARE是一种基于共识开发的、用于生命周期评估（Life Cycle Assessment，LCA）中水资源使用评价的方法，由WULCA UNEP/SETAC工作组研发。该方法的特征因子表征流域在满足人类与水生生态系统需水要求后，单位面积剩余可利用水量的相对水平，用于评估人类或水生生态系统面临的水资源短缺风险，其核心假设为：单位面积剩余可利用水量越少，其他用水主体面临缺水的概率越高。 生成本数据集样本的代码可从以下链接获取：https://github.com/PascalLesage/aware_cf_calculator/。本数据集于2020年从v1.0版本更新，新增了因选用WaterGap作为全球水文模型（Global Hydrological Model，GHM）所带来的模型不确定性相关内容。 本次提供的数据集包含以下内容： <strong>1) AWARE_characterization_factor_samples.zip</strong>：蒙特卡洛模拟生成的实际特征因子文件，内含4个压缩包： * monthly_cf.zip：包含116484组数据阵列，对应9707个流域逐月的5000份月度特征因子样本，格式为CSV。文件命名格式为`cf_<BAS34S_ID>_<MONTH>.csv`，其中`<BAS34S_ID>`为流域ID，`<MONTH>`为月份前三位英文缩写（如jan、feb等）。 * average_agri_cf.zip：包含9707组数据阵列，对应每个流域的5000份农业用水年度平均特征因子样本，格式为CSV。文件命名格式为`cf_average_agri_<BAS34S_ID>.csv`。 * average_non_agri_cf.zip：包含9707组数据阵列，对应每个流域的5000份非农业用水年度平均特征因子样本，格式为CSV。文件命名格式为`cf_average_non_agri_<BAS34S_ID>.csv`。 * average_unknown_cf.zip：包含9707组数据阵列，对应每个流域的5000份未指定用途用水年度平均特征因子样本，格式为CSV。文件命名格式为`cf_average_unknown_<BAS34S_ID>.csv`。 <strong>2) AWARE_base_data.xlsx</strong>：用于存储确定性数据的Excel文件，包含每个流域、每个月的AWARE特征因子计算所需的各类自变量数据，具体包括： 1. 月度灌溉用水量：描述为各流域逐月的灌溉用水量，单位为m³/月，在Excel文档中的位置为`Irrigation`工作表，导出后的文件名为`irrigation.pickle`，数据形状为(11050, 12)。 2. 非灌溉用水（电力、生活、畜牧、制造业）：描述为各类非灌溉用水的用水量，单位为m³/年，在Excel文档中的位置为`hwc_non_irrigation`工作表，导出后的文件名为`electricity.pickle`、`domestic.pickle`、`livestock.pickle`及`manufacturing.pickle`，数据形状为3×(11050,)。 3. avail_delta：描述为“原始自然可获得水量（来自PastorXNatAvail）”与“经人类消费后从WaterGap获取的实际可获得水量（Avail!W:AH）加上人类用水消费（Human Water Consumption，HWC）”之间的差值。该差值需加入计算得到的水量可获得量中，方可得到用于计算生态需水（Environmental Water Requirement，EWR）的水量可获得量。单位为m³/月，在Excel文档中的位置为`avail_delta`工作表，导出后的文件名为`avail_delta.pickle`，数据形状为(11050, 12)。 4. avail_net：描述为经人类消费后从WaterGap获取的实际可获得水量，单位为m³/月，在Excel文档中的位置为`avail_net`工作表，导出后的文件名为`avail_net.pickle`，数据形状为(11050, 12)。 5. pastor：描述为需为生态系统保留的原始自然可获得水量占比，无单位，在Excel文档中的位置为`pastor`工作表，导出后的文件名为`pastor.pickle`，数据形状为(11050, 12)。 6. 流域面积：描述为流域面积，单位为m²，在Excel文档中的位置为`area`工作表，导出后的文件名为`area.pickle`，数据形状为(11050,)。 此外，该Excel文件还包含： * 各变量对应分布的参数（k值）信息（存储于`uncertainty`工作表）； * 模型不确定性相关参数（k值）信息（存储于`model uncertainty`工作表）； * 两类筛选器：用于剔除格陵兰岛流域的极地筛选器，以及用于剔除Pastor等人2014年研究中无数据的122个小型沿海无重叠区域流域的筛选器（存储于`filters`工作表）。 <strong>3) independent_variable_samples.zip</strong>：用于存储特征因子计算所需的各类自变量的采样数据，仅包含随机变量样本。对于无采样数据的流域或流域-月份组合，蒙特卡洛模拟将直接使用`AWARE_base_data.xlsx`中的确定性数值。所有文件均为CSV格式，第一列为流域ID（BAS34S_ID，年度数据）或（流域ID，月份）（月度分辨率数据），其余5000列为采样得到的数值。文件命名格式为`<variable_name>.csv`。 <strong>4) intermediate_variables.zip</strong>：包含特征因子计算过程中生成的中间计算结果，该压缩包内含3个子压缩包： * AMD_world_over_AMD_i.zip：包含116484组数据阵列（对应每个流域-月份），存储5000份该流域-月份的可获得水量减需水量（Availability Minus Demand，AMD）与全球加权AMD平均值（AMD_glo）的比值数据，格式为CSV。 * AMD_world.zip：包含1组存储5000份全球平均AMD计算值的阵列，格式为CSV。 * HWC.zip：包含116484组数据阵列（对应每个流域-月份），存储5000份总人类用水消费量的计算值，格式为CSV。 <strong>5) watershedBAS34S_ID.zip</strong>：包含用于将流域ID（BAS34S_ID）与实际空间数据关联的GIS文件。
