# JolPulse — Environmental Scenario Lab

> 96 synthetic flood scenarios linking rainfall, river response and fictional response capacity. Uncalibrated screening exercise; no live sensors, warnings or evacuation advice.

- Canonical URL: https://khanio.co.technology/
- Methodology & Equations: https://khanio.co.technology/methodology/
- Interactive Browser Runtime: https://khanio.co.technology/run/
- Author & Root Entity: Mohammad Rezwan Khan, PhD (https://mrkhan.co.technology/#person)
- Ecosystem Directory: https://mklab.co.technology/
- Knowledge Graph JSON-LD: https://khanio.co.technology/knowledge-graph.jsonld

## Governing Mathematical Formulation & Units
- Formula: `Runoff_Proxy (mm) = Rain_24h (mm) × Runoff_Fraction(Soil_Saturation); Stage_Index(t) = Margin_0 − Trend (m/h) × t; Corridor_Route = argmin_{path} Σ Edge_Travel_Time subject to Edge_Open = true and Hub_Capacity ≥ People`
- Units: 24-hour rainfall and runoff proxy in millimetres (mm); soil saturation in %; river stage margin in metres (m); stage trend in metres/hour (m/h); horizon in hours (6 h to 72 h); group size in persons.

## Reproducible Worked Example
Case 'sunamganj-baseline-6' (Sunamganj Haor/Surma basin, 6-hour horizon, 120 people): 24h rainfall = 148.0 mm at 84.0% soil saturation yields illustrative runoff_fraction = 0.708 and runoff_proxy = 104.78 mm. With initial margin = 0.55 m and rise trend = 0.045 m/h, the capacity-aware shortest-path solver selects open fictional response corridors and generates bilingual (English/Bangla) exercise briefs.

## Canonical Companion Modules on this Domain
- **AsterVale Atlas** (https://khanio.co.technology/environmental-indicators/): Seven-indicator environmental comparison across synthetic study areas. Boundary: Illustrative indicators; not measured field evidence or certified environmental assessment.
  - Formula: `NDVI = (NIR − Red) / (NIR + Red); Filtered Subset S = { r ∈ D : Date(r) ∈ [t_0, t_1] ∧ Area(r) = A ∧ Cloud_Pct(r) ≤ C_max }`
  - Units: Cloud cover threshold in %; spectral indices (NDVI, NDWI, EVI, etc.) dimensionless in [-1, 1]; observation counts in integer rows.
  - Worked Example: Case 1 (Area = 'West Meadow', Indicator = NDVI, Max Cloud Cover = 35%): Sequential date → area → cloud filtering retains 179 valid synthetic observation rows, yielding sample Mean NDVI = 0.4534 and Median NDVI = 0.5182 with mutually exclusive exclusion counts.

## Benchmark Table
| Scenario ID | Basin / Region | Rain 24h (mm) | Soil Sat. (%) | Runoff Proxy (mm) | Margin (m) | Trend (m/h) | Horizon (h) |
| --- | --- | --- | --- | --- | --- | --- | --- |
| sunamganj-baseline-6 | Sunamganj (Haor / Surma) | 148.0 | 84.0% | 104.78 | 0.55 | 0.045 | 6 |
| sylhet-surge-12 | Sylhet (Surma / Kushiyara) | 210.0 | 91.0% | 163.80 | 0.30 | 0.065 | 12 |
| kurigram-monsoon-24 | Kurigram (Brahmaputra) | 175.0 | 88.0% | 131.25 | 0.42 | 0.050 | 24 |

## 5-Domain Core Authority Ecosystem
1. Hub & Authority: https://mrkhan.co.technology/ (Mohammad Rezwan Khan, PhD - BESS QA/QC & Energy R&D)
2. Interactive Course & Twin: https://khanlab.co.technology/ (Datacenter Power Systems & What-If Simulator)
3. Microgrid Research: https://mkgrid.co.technology/ (HelioForge Energy Lab - Hybrid Energy Research)
4. Synthetic Energy Trading: https://mktrade.co.business/ (ZephyrTrade - Wind-Market Synthetic Backtesting)
5. Utility & Tool Suite: https://mklab.co.technology/ (MKLab - 68 Free Browser Engineering & Planning Apps)