该数据包含了祁连山国家公园1km分辨率2020-2099年逐年蒸散发、土壤水、产水、净植被初级生产力、干旱指数、水土流失、水源涵养和生境退化指数的三种气候情景五种模式均值的长期预测数据空间分布图", "ds_source": "
基于关键要素实测数据校正后的SWAT-DayCent生态水文模型模拟的各生态环境要素预测数据。", "ds_process_way": "
通过收集地形、土壤、土地利用、气象及水文等基础数据，构建以祁连山国家公园所在流域的生态水文耦合模型，基于观测的关键河道断面的径流、泥沙数据和遥感植被生产力数据对模拟的历史阶段的生态水文关键要读进行校准和验证。根据校准好的模型，以CMIP5发布的未来情景（RCP2.6，RCP4.5和RCP8.5）气候数据为基础驱动生态水文模型模拟预测未来祁连山国家公园所在流域的生态水文要素，得到2020-2099年逐年蒸散发、土壤水、产水、净植被初级生产力和水土流失量的时空分布数据。根据预测的气候-水文-生态关键要素，构建干旱、水源涵养和生境退化的评估模型，预测三者未来时空演化特征，得到2020~2099年干旱、水源涵养和生境退化指数1km分辨率的未来时空数据。最后以祁连山国家公园为边界，通过批量裁剪得到2020-2099年祁连山国家公园生态环境要素（蒸散发、产水、土壤水、净植被初级生产力、水土流失、干旱、水源涵养和生境退化指数）的未来预测数据。", "ds_quality": "
1.模型的输入数据来源于公开的数据库，其精度和质量有所保证。
2.未来气候情景数据通过了偏差校正处理，并与历史数据进行了充分的对比和验证。\n
3.模型构建完成后经过了历史逐月径流量、年输沙量、年净植被初级生产力等关键要素实测数据的校准和验证，保证了模拟结果的可靠性。", "ds_acq_start_time": "2020-01-01 00:00:00", "ds_acq_end_time": "2099-12-31 00:00:00", "ds_acq_place": "祁连山国家公园", "ds_acq_lon_east": 103.03333333333333, "ds_acq_lat_south": 36.755833333333335, "ds_acq_lon_west": 95.12083333333332, "ds_acq_lat_north": 39.74638888888889, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 105872198, "ds_files_count": 2, "ds_format": "NC4", "ds_space_res": "1km", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "6488e9eb-31de-427a-a6e1-a4a5e0a9c7dd.png", "ds_thumb_from": 2, "ds_ref_way": "吴一平，祁连山国家公园生态环境要素模拟预测数据集（2020-2099年），国家冰川冻土沙漠科学数据中心(www.ncdc.ac.cn)，2023，doi：10.12072/ncdc.nieer.db2737.2023", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "52109486-75ef-4764-a933-6380c6f42432", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "10.12072/ncdc.nieer.db2737.2023", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2023-02-28 21:26:33", "last_updated": "2023-03-01 11:05:59", "protected": false, "protected_to": "2025-01-01 00:00:00", "lang": "zh", "cstr": "11738.11.ncdc.nieer.db2737.2023", "i18n": { "en": { "title": "Simulation and prediction data of ecological and environmental factors in Qilian Mountain National Park during 2020 through 2099", "ds_format": "", "ds_source": "
\nBased on the predicted data of each ecological environment element simulated by SWAT-DayCent eco-hydrological model after the correction of the measured data of key elements.", "ds_quality": "
\n1. The input data of the model comes from the open database, and its accuracy and quality are guaranteed。 2. The future climate scenario data has passed the deviation correction processing, and has been fully compared and verified with the historical data.3. After the construction of the model, it has been calibrated and verified by the measured data of key elements such as historical monthly runoff, annual sediment discharge, and annual net vegetation primary productivity, ensuring the reliability of the simulation results.", "ds_ref_way": "", "ds_abstract": "
\nThis data includes the spatial distribution of long-term forecast data of the mean of five models of three climate scenarios in Qilian Mountain National Park with a resolution of 1 km from 2020 to 2009, including annual evapotranspiration, soil water, water production, net primary vegetation productivity, drought index, soil erosion, water conservation and habitat degradation index
", "ds_time_res": "年", "ds_acq_place": "Qilian Mountain National Park", "ds_space_res": "1km", "ds_projection": "", "ds_process_way": "\nBy collecting basic data such as terrain, soil, land use, meteorology and hydrology, the eco-hydrological coupling model of the basin where the Qilian Mountain National Park is located is constructed. Based on the observed runoff, sediment data and remote sensing vegetation productivity data of key river sections, the key eco-hydrological readings in the simulated historical stage are calibrated and verified. According to the calibrated model, based on the climate data of the future scenarios (RCP2.6, RCP4.5 and RCP8.5) released by CMIP5, the eco-hydrological model is driven to simulate and predict the eco-hydrological elements of the basin where the Qilian Mountain National Park is located in the future, and the spatial-temporal distribution data of annual evapotranspiration, soil water, water production, net vegetation primary productivity and water and soil loss from 2020 to 2009 are obtained. According to the predicted climate-hydro-ecological key elements, an assessment model of drought, water conservation and habitat degradation is constructed to predict the future spatiotemporal evolution characteristics of the three, and the future spatiotemporal data of drought, water conservation and habitat degradation index with a resolution of 1 km from 2020 to 1999 are obtained. Finally, taking the Qilian Mountain National Park as the boundary, the future forecast data of the ecological environment elements (evapotranspiration, water production, soil water, net vegetation primary productivity, water and soil loss, drought, water conservation and habitat degradation index) of the Qilian Mountain National Park from 2020 to 2009 are obtained through batch cutting.", "ds_ref_instruction": " " } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "ds_topic_tags": [ "生态环境要素，祁连山，气候情景，未来预测", "生态环境要素", "祁连山", "气候情景", "未来预测" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "祁连山国家公园" ], "ds_time_tags": [ 2020, 2099 ], "ds_contributors": [ { "true_name": "吴一平", "email": "rocky.ypwu@gmail.com", "work_for": "西安交通大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "王凡", "email": "2271268655@qq.com", "work_for": "西安交通大学", "country": "中国" } ], "ds_managers": [ { "true_name": "吴一平", "email": "rocky.ypwu@gmail.com", "work_for": "西安交通大学", "country": "中国" } ], "category": "其他" }