多源信息集成的2022年克鲁伦河流域草原型流域面源污染入河负荷空间分布数据集研制

doi:10.19788/j.issn.2096-6369.100027

Abstract

Abstract:

The Kherlen River Basin is located along the Silk Road, and jointly building a green road is an important part of the top-level design of the Silk Road. China and Mongolia face the common challenge and responsibility of protecting the ecological security of the basin. Therefore, it is important to clarify the spatial distribution of grassland-type load estimation of non-point sources (NPS) pollution into the Kherlen River Basin, which is essential for the division of the optimal spatial control unit of NPS pollution in the basin. On the basis of Chinese self-developed DPeRS (Diffuse Pollution estimation with Remote Sensing) model, this paper has developed a method for estimating the grassland-type load distribution of NPS pollution into river in the basin, by combining the NPS pollution characteristics of surface runoff on grassland and incorporating the spatial distribution of NPS pollution loads in hydro-fluctuation zone. The method is driven by remote sensing data, and it can realize the distribution of NPS pollution load estimation into river at the pixel level month by month. Compared to the previous NPS pollution simulation models, this method comprehensively takes into account the impact of hydro-fluctuation zone NPS pollution on rivers. The grassland-type load estimation of NPS pollution is composed of two parts: the NPS pollution of surface runoff on grassland and the NPS pollution of hydro-fluctuation zone on grassland. The NPS pollution load of surface runoff on grassland into the river is mainly estimated from the dissolved state and erosion particle state. Firstly, the nitrogen and phosphorus balance of grassland was calculated based on ground data (such as wet and dry deposition data, soil data, grassland utilization intensity) and remote sensing data in the Kherlen River Basin. Then, space load estimation is carried out by coupling a quantitative remote sensing inversion model with the ground model of NPS pollution, by combining the spatial distribution characteristics of continuous parameters in estimating the grassland-type NPS pollution, such as precipitation in the watershed, soil nitrogen and phosphorus content. Grassland NPS pollution loads in hydro-fluctuation zone is estimated based on the extent of hydro-fluctuation zone extracted from month-by-month Sentinel 2 imagery from April-October, 2019-2022. And the volume of grassland-type NPS pollution loads in the hydro-fluctuation zone is calculated by the release rates of NPS pollution total nitrogen and total phosphorus obtained from submerged release simulation experiments of soil columns in different land use type in the hydro-fluctuation zone. Based on above methods, the spatial distribution dataset of grassland-type NPS pollution load into river is finally obtained. And the NPS pollution load of total nitrogen and total phosphorus into river is 3542.5 t/yr and 1559.9 t/yr in 2022, respectively. The total nitrogen and phosphorus of surface runoff type NPS into the river were 3105.0 t/yr and 1387.1 t/yr, respectively. The total nitrogen and phosphorus of hydro-fluctuation zone type NPS into the river were 437.5 t/yr and 172.8 t/yr, respectively. This dataset provides a strong support for the realization of high-precision division technology of NPS pollution control unit, which is of great reference significance for China and Mongolia to maintain the resource and ecological security along the Silk Road.

Data summary:

Item	Description
Dataset name	Research of Spatial Distribution Dataset of Grassland-type Non-point Sources Pollution Loading to Rivers in the Kherlen River Basin in 2022 Integrated by Multi-source Information
Specific subject area	Land resources and information technology
Research topic	Grassland-type (NPS) pollution loading to rivers in the Kherlen River Basin
Time range	2022 year
Temporal resolution	No
Geographical scope	Kherlen River basin
Spatial resolution	30 meter
Data types and technical formats	Grassland-type NPS pollution of total phosphorus loading to rivers in the Kherlen River Basin with 30 m resolution (TIF format) Grassland-type NPS pollution of total nitrogen loading to rivers in the Kherlen River Basin with 30 m resolution (TIF format)
Dataset structure	The dataset is 2022 grassland-type NPS pollution of total phosphorus and total nitrogen loading to rivers in the Kherlen River Basin with 30 m resolution
Volume of dataset	2.73 GB
Key index in dataset	Grassland-type NPS pollution of total phosphorus loading to rivers in the Kherlen River Basin Grassland-type NPS pollution of total nitrogen loading to rivers in the Kherlen River Basin
Data accessibility	https://cstr.cn/17058.11.sciencedb.agriculture.00114 https://doi.org/10.57760/sciencedb.agriculture.00114
Financial support	Research and development on remote sensing monitoring and assessment technology of non-point source pollution in Kherlen River Basin under the national key research and development program（2021YFE0102300）

Key words: Kherlen River Basin, grassland-type NPS pollution of basin, loads into river, NPS pollution of surface runoff, NPS pollution of hydro-fluctuation zone

XIE ChengYu, WANG ChenYi, HUANG Li, GAO BingBo, YIN WenJie, SUKHBAATAR Chinzorig, WANG QingTao, CHEN HuaJie, FENG QuanLong, LI ShuHua, FENG AiPing. Research of Spatial Distribution Dataset of Grassland-type Non- point Sources Pollution Loading to Rivers in the Kherlen River Basin in 2022 Integrated by Multi-source Information[J].Journal of Agricultural Big Data, 2025, 7(1): 31-42.

Figures/Tables 12

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References 14

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[9]	赵串串, 冯倩, 侯文涛, 等. 基于AnnAGNPS模型的灞河流域非点源污染模拟研究. 环境污染与防治, 2019, 41(3):317-322.
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数据名称	单位	数据来源
流域消落带区域	——	提取2019—2022年4—10月有效哨兵2影像
30 m土地利用数据	——	https://data.casearth.cn/sdo/detail/5fbc7904819aec1ea2dd7061
30 m克鲁伦河流域土壤类型	——	http://globalchange.bnu.edu.cn/research/soil
30 m克鲁伦河流域坡度坡长	°	https://wist.echo.nasa.gov/api//
30 m克鲁伦河流域植被覆盖度	%	https://ladsweb.nascom.nasa.gov/search
30 m克鲁伦河流域草地氮磷平衡量	t/yr	基于草地氮磷平衡量计算得到
克鲁伦河流域氮磷干湿沉降数据	kg·m²/(ha·yr)	流域草地面积乘以氮、磷沉降通量参数
消落带淹没面源释放速率	mg/(m²·d)（裸土/植被覆盖地类）； mg/(g·d)（粪便覆盖地类）	基于现场采样的消落带淹没释放模拟实验
淹没概率	--	克鲁伦河月度30 m空间分辨率的水体分布数据
消落带地类覆盖度	%	10 m×10 m样方调查
草原牲畜量（羊）	只	统计年鉴和草原蒙古包数据
羊粪便排泄系数	kg/（只·年）	参考文献中获取^[13]

	总氮释放速率			总磷释放速率
土地类型	裸土 [mg/(m²·d)]	植被覆盖 [mg/(m²·d)]	粪便覆盖 [g/(m²·d)]	裸土 [mg/(m²·d)]	植被覆盖 [mg/(m²·d)]	粪便覆盖 [g/(m²·d)]
H4	9.75	9.67	0.12	4.06	11.60	0.01
H7	9.75	8.65	0.01	1.20	3.41	0.01
M1	0.01	0.12	0.07	0.51	0.01	0.02
M2	0.05	0.10	0.07	0.02	0.08	0.01
M3	0.13	0.01	0.01	0.41	0.02	0.01
平均值	3.94	3.71	0.06	1.24	3.02	0.01

NPS污染	消落带覆盖类别	消落带内NPS污染释放量（t/年）
NPS污染	消落带覆盖类别	全流域	中国境内	蒙古境内
总氮	裸土	114.2	39.4	74.9
	植被	119.5	41.2	78.3
	粪便	203.8	28.7	175.1
总磷	裸土	35.9	12.4	23.6
	植被	97.3	33.5	63.8
	粪便	39.6	5.4	34.2

Research of Spatial Distribution Dataset of Grassland-type Non- point Sources Pollution Loading to Rivers in the Kherlen River Basin in 2022 Integrated by Multi-source Information

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