逐像元水量平衡计算 P = ET + Q + ΔS,评估闭合差。Per-pixel water balance computation P = ET + Q + ΔS with closure residual assessment. 输出各分量/闭合差 GeoTIFF + 报告 JSON。
编程
geoskill-water-purification-mapping
试用简化 InVEST Budyko 水量平衡计算产水量,叠加 NDVI 调制的植被截留系数得水源涵养量,并估算养分截留净化量。Maps water retention and purification with a simplified InVEST water yield model. 输出产水/涵养/净化三张 GeoTIFF。
它能做什么
简化 InVEST Budyko 水量平衡计算产水量,叠加 NDVI 调制的植被截留系数得水源涵养量,并估算养分截留净化量。Maps water retention and purification with a simplified InVEST water yield model. 输出产水/涵养/净化三张 GeoTIFF。
技能文档
水源涵养/净化功能制图 | Water Purification Mapping
Water yield is computed with a Budyko-style water balance Y = P - AET, where AET/P = 1 + φ - (1+φ^ω)^(1/ω), φ = ET0/P is the dryness index, and ω is the soil-water parameter (default 1.5). Water retention = water yield × NDVI-modulated vegetation interception coefficient (saturating type, capped at 0.85); water purification estimates nitrogen retention as nutrient load × NDVI-modulated interception efficiency (default 0.65).
Use cases: water-retention function assessment, watershed water-purification service accounting, and ecological conservation red line delineation.
Dependencies / 依赖
pip install numpy rasterio scipy
Usage / 使用方法
Example 1: Synthetic Climate/Soil/Vegetation Scenario
python geoskill-water-purification-mapping.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./output
示例 2:真实 5 波段输入(precip,et0,awc,ndvi,n_load)
python geoskill-water-purification-mapping.py --input water_inputs.tif --output-dir ./real
示例 3:调整 Budyko ω 参数
python geoskill-water-purification-mapping.py --bbox 116 39 117 40 --synthetic --omega 2.0 --output-dir ./tuned
Example 4: Different Regions
python geoskill-water-purification-mapping.py --bbox 121 31 122 32 --synthetic --output-dir ./shanghai
Example 5: Silent Batch Mode
python geoskill-water-purification-mapping.py --bbox 113 23 114 24 --synthetic --quiet --output-dir ./batch
Output / 输出
| File | Format | Description |
|---|---|---|
water_yield.tif | GeoTIFF (float32) | Water yield (mm/yr), EPSG:4326 |
water_retention.tif | GeoTIFF (float32) | Water retention (mm/yr) |
nutrient_retention.tif | GeoTIFF (float32) | Nitrogen retention (kg/ha/yr) |
water_purification_params.json | JSON | ω parameter and per-product means/totals |
output-manifest.json | JSON | Run manifest (inputs/outputs/QA/software versions) |
Data Source / 数据源 / Source
Local GeoTIFF (optional 5-band factor input); the Budyko water balance is a public hydrological model; synthetic mode is generated locally with no external data source.
Privacy / 隐私声明 / Privacy
- Fully offline by default; no network requests are made
--syntheticmode reads no external data- All computation is done locally; no user data is uploaded
License / License
MIT
name: geoskill-water-purification-mapping description: '简化 InVEST Budyko 水量平衡计算产水量,叠加 NDVI 调制的植被截留系数得水源涵养量,并估算养分截留净化量。Maps water retention and purification with a simplified InVEST water yield model. 输出产水/涵养/净化三张 GeoTIFF。'
水源涵养/净化功能制图 | Water Purification Mapping
产水量用 Budyko 风格水量平衡 Y = P - AET,其中 AET/P = 1 + φ - (1+φ^ω)^(1/ω),φ = ET0/P 为干燥指数,ω 为土壤水分参数(默认 1.5)。水源涵养量 = 产水量 × NDVI 调制的植被截留系数(饱和型,上限 0.85);水质净化用养分负荷 × NDVI 调制截留效率(默认 0.65)估算氮截留量。
适用场景:水源涵养功能评估、流域水质净化服务核算、生态保护红线划定。
依赖
pip install numpy rasterio scipy
使用方法
示例 1:合成气候/土壤/植被场景
python geoskill-water-purification-mapping.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./output
示例 2:真实 5 波段输入(precip,et0,awc,ndvi,n_load)
python geoskill-water-purification-mapping.py --input water_inputs.tif --output-dir ./real
示例 3:调整 Budyko ω 参数
python geoskill-water-purification-mapping.py --bbox 116 39 117 40 --synthetic --omega 2.0 --output-dir ./tuned
示例 4:不同区域
python geoskill-water-purification-mapping.py --bbox 121 31 122 32 --synthetic --output-dir ./shanghai
示例 5:静默批量
python geoskill-water-purification-mapping.py --bbox 113 23 114 24 --synthetic --quiet --output-dir ./batch
输出
| 文件 | 格式 | 说明 |
|---|---|---|
water_yield.tif | GeoTIFF (float32) | 产水量(mm/yr),EPSG:4326 |
water_retention.tif | GeoTIFF (float32) | 水源涵养量(mm/yr) |
nutrient_retention.tif | GeoTIFF (float32) | 氮截留量(kg/ha/yr) |
water_purification_params.json | JSON | ω 参数与各产物均值/总量 |
output-manifest.json | JSON | 运行清单(输入/输出/QA/软件版本) |
数据源 / Source
本地 GeoTIFF(5 波段因子输入,可选);Budyko 水量平衡为公开水文模型;合成模式本地生成,无外部数据源。
隐私声明 / Privacy
- 默认完全离线运行,不发起任何网络请求
--synthetic模式不读取任何外部数据- 所有计算在本地完成,不上传用户数据
License
MIT
相关技能
用当量因子法评估供给、调节、支持、文化四类生态系统服务价值。Estimates four ecosystem service values with a simplified InVEST plus equivalent-factor method. 输出四类服务价值 GeoTIFF 与总量 JSON。
基于生境异质性假说,用 NDVI 生产力、纹理结构异质性与地形粗糙度三类代理估算物种丰富度空间分布。Maps species richness proxies from NDVI, texture and terrain heterogeneity. 输出物种丰富度与生境质量 GeoTIFF + 参数 JSON。
基于 NDVI 时序积分估算累积生物量,叠加气候校正得到生产力指数。Estimates cumulative biomass from NDVI time-series integration with climate correction to yield a productivity index.
由 NDVI 幂律异速生长方程估算地上生物量碳,叠加根茎比地下碳与类型化土壤碳密度。Estimates carbon stocks from biomass allometry and soil carbon density. 输出地上碳/土壤碳/总碳三张 GeoTIFF 与汇总 JSON。
Priestley-Taylor 与简化 SEBAL 蒸散发估算,从净辐射/气温/LST/NDVI 计算 ET (mm/day)。Priestley-Taylor and simplified SEBAL evapotranspiration estimation from net radiation/air temperature/LST/NDVI. 输出 ET 栅格 + 统计 JSON。