Indian-App-Food-Stress

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GitHub - ATUERK73/IndiaApp-Food-Stress-Indicator: India App to Calculate Food Stress Indicator · GitHub

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ATUERK73

IndiaApp-Food-Stress-Indicator

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India Composite Food Stress Indicator

An exploratory Streamlit prototype for monitoring stress indicators related to<br>India's food supply:

rainfall anomalies in Kerala as a regional early indicator

regional rainfall and soil-moisture anomalies across major agricultural regions

regional wet-bulb temperature derived from air temperature and relative humidity

ENSO / El Nino conditions based on NOAA's Oceanic Nino Index (ONI)

an hourly refreshed NOAA ENSO outlook with the weekly index, alert status, and strengthening signal

fertilizer imports, prices, and a Strait of Hormuz scenario

an automatic staple-food price index with a manual override

Getting started

pip install -r requirements.txt<br>streamlit run app.py

Data sources and labeling

NASA POWER Daily API for rainfall and regional agroclimate data

NOAA CPC ONI for ENSO conditions

World Bank Pink Sheet for global fertilizer price benchmarks

Department of Fertilizers and official Indian publications for import data

IndexMundi as a fallback global urea price proxy

international rice, wheat, maize, and soybean-oil benchmarks as food-price proxies

The interface labels data as live/local, manual scenario input, or simulated<br>fallback data. Simulated data must not be interpreted as current observations.

Optional Indian fertilizer price dataset

Create data/india_fertilizer_prices.csv to display farmer-facing Indian prices<br>and maximum retail prices (MRPs). The file requires:

fertilizer, for example Urea, DAP, MOP, or NPK 10-26-26

bag_size_kg

price_inr_per_bag

Optional columns: as_of and source_note.

Optional IMD dataset

Create data/imd_kerala_daily.csv. The file requires:

date in ISO format (YYYY-MM-DD)

precipitation_mm for daily rainfall in millimeters

Methodology

The prototype calculates neither a crisis probability nor an official forecast.<br>It produces a heuristic Composite Stress Indicator ranging from 0 to 100. Kerala<br>is only a regional indicator and is not representative of India as a whole.

The interface also presents an experimental three-month outlook with three<br>alternatives: a baseline scenario, persistent dryness and price pressure, and a<br>favorable monsoon. Each path simulates 2,000 possible developments in weather,<br>ENSO, and prices. The P10-P90 band applies to the baseline scenario and represents<br>model uncertainty. The three scenarios have no assigned probabilities and do not<br>represent the probability of a food crisis. The forecast model has not yet been<br>operationally backtested or validated.

When NOAA expects strengthening, the ENSO forecast starts from the more recent<br>weekly Nino-3.4 value, provided it is higher than the ONI, and applies at least<br>+0.15 degrees C of model drift per month. This translation of NOAA's qualitative<br>outlook is an explicit model assumption, not an official NOAA ONI trajectory.

Composite Stress Indicator =<br>0.27 * MonsoonStress<br>+ 0.18 * ENSOStress<br>+ 0.18 * FertilizerStress<br>+ 0.135 * FoodPriceStress<br>+ 0.135 * CropConditionStress<br>+ 0.10 * WetBulbStress

CropConditionStress combines the root-zone soil-moisture anomaly with the<br>regional rainfall anomaly. It is a proxy, not an NDVI measurement.

Wet-bulb temperature is calculated using the Stull approximation from NASA POWER<br>daily values for air temperature at 2 meters and relative humidity. It is not the<br>same as WBGT. WetBulbStress uses the median of the regional daily maximum values:<br>temperatures up to 24 degrees C receive a stress score of 10, temperatures of<br>32 degrees C or higher receive a score of 100, and values in...

data food stress indicator regional noaa

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