Aquifer Vector Module¶

File: computing/misc/aquifer_vector.py

Overview¶

This module generates aquifer vector layers by processing principal aquifer data and calculating intersection statistics with micro-watersheds (MWS). It provides detailed aquifer characteristics including yield values, lithology, and groundwater potential.

Purpose¶

Processes aquifer boundary data to: - Calculate intersection areas between aquifers and MWS - Determine aquifer classification (Alluvium vs Hard-Rock) - Compute weighted yield contributions - Distribute to GEE, GeoServer, and STAC

Architecture¶

flowchart TD
    A[Celery Task Triggered] --> B[ee_initialize]
    B --> C[Load MWS ROI]
    C --> D[Load Principal Aquifers]
    D --> E[Map Yield Values]
    E --> F[Filter Valid Yields]
    F --> G[Process Each MWS Feature]
    G --> H[Find Intersecting Aquifers]
    H --> I[Calculate Intersection Area]
    I --> J[Compute Weighted Yield]
    J --> K[Determine Aquifer Class]
    K --> L[Build Feature Properties]
    L --> M[Flatten Results]
    M --> N[Export to GEE]
    N --> O{Asset Exists?}
    O -->|Yes| P[save_layer_info_to_db]
    P --> Q[make_asset_public]
    Q --> R[sync_fc_to_geoserver]
    R --> S[Generate STAC]
    S --> T[Update Sync Status]
    T --> U[Return True]

Components¶

Main Task: `generate_aquifer_vector()`¶

Location: Line 22

Parameters: | Parameter | Type | Description | |-----------|------|-------------| | state | str | State name | | district | str | District name | | block | str | Block/tehsil name | | gee_account_id | int | GEE account identifier |

Returns: bool - Whether layer was successfully synced to GeoServer

Processing Logic¶

1. Yield Value Mapping¶

The module maps textual yield descriptions to numerical values:

yield_dict = ee.Dictionary({
    "": "NA",
    "-": "NA",
    "Upto 2%": 0.02,
    "1-2%": 0.02,
    "Upto 1.5%": 0.015,
    "Upto 3%": 0.03,
    # ... more mappings
    "8 - 16%": 0.16,
    "Not Explored": "NA",
    # ... additional mappings
})

2. MWS Processing¶

For each MWS feature:

flowchart LR
    A[MWS Geometry] --> B[Filter Aquifers by Bounds]
    B --> C[For Each Aquifer]
    C --> D[Calculate Intersection]
    D --> E[Compute Area]
    E --> F[Calculate Weighted Yield]
    F --> G[Determine Class]
    G --> H[Build Feature]

3. Aquifer Classification¶

aquifer_class = ee.Algorithms.If(
    ee.String(principal_value).equals("Alluvium"), 
    "Alluvium", 
    "Hard-Rock"
)

4. Feature Properties¶

Each output feature contains:

Property	Description
`uid`	MWS unique identifier
`id`	Feature ID
`area_in_ha`	MWS area in hectares
`total_weighted_yield`	Watershed-level weighted yield aggregated across intersecting aquifer patches
`%_area_aquifer`	Percentage of MWS covered by aquifer
`aquifer_count`	Number of aquifers intersecting MWS
`aquifer_class`	"Alluvium" or "Hard-Rock"
`principle_aq_*_percent`	Percentage coverage for each principal aquifer category tracked in the module
`Age`	Geological age
`Lithology_`	Lithology code
`Major_Aq_1`	Major aquifer code
`Major_Aqui`	Major aquifer name
`Principal_`	Principal aquifer type
`Recommende`	Recommended aquifer attribute carried through from the dominant intersecting feature
`yeild__`	Yield class string carried through from the dominant intersecting feature
`zone_m`	Zone attribute carried through from the dominant intersecting feature
`y_value`	Numerical yield value

Integration Points¶

computing/misc/aquifer_vector.py
├── computing.utils
│   ├── sync_fc_to_geoserver()    # GeoServer sync
│   ├── save_layer_info_to_db()   # Database persistence
│   └── update_layer_sync_status() # Status tracking
├── utilities.gee_utils
│   ├── ee_initialize()           # GEE authentication
│   ├── valid_gee_text()          # Text sanitization
│   ├── check_task_status()       # Task monitoring
│   ├── make_asset_public()       # ACL management
│   ├── is_gee_asset_exists()     # Asset existence check
│   ├── export_vector_asset_to_gee() # Vector export
│   └── get_gee_asset_path()      # Asset path generation
├── utilities.constants
│   └── GEE_DATASET_PATH          # Dataset path
└── computing.STAC_specs
    └── generate_vector_stac()    # STAC metadata generation

Output¶

Platform	Asset/Layer Name	Workspace
GEE	`aquifer_vector_{district}_{block}`	N/A
GeoServer	`aquifer_vector_{district}_{block}`	`aquifer`

Dataset Name: Aquifer

STAC Layer Name: aquifer_vector

Usage¶

# Trigger via Celery
from computing.misc.aquifer_vector import generate_aquifer_vector

result = generate_aquifer_vector.delay(
    state="Rajasthan",
    district="Jaipur",
    block="Sanganer",
    gee_account_id=1
)

Key Calculations¶

Intersection Area¶

intersection = mws_geom.intersection(aquifer_geom, 1)
intersection_area_ha = intersection.area(1).divide(10000)

Weighted Yield¶

fraction = intersection_area.divide(mws_geom.area(1))
weighted_yield = fraction.multiply(aquifer.get("y_value"))

Dependencies¶

ee (Google Earth Engine Python API)
Celery - Distributed task queue