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Challenge

Build an ERA5 Drought Soil Moisture Parametric Simulator

Simulate parametric multi-layer soil moisture triggers for rainfed pastureland using ECMWF ERA5 reanalysis datasets. Model index basis risk and calculate payout frequencies under historical drought conditions.

Data ScienceHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Simulate parametric multi-layer soil moisture triggers for rainfed pastureland using ECMWF ERA5 reanalysis datasets. Model index basis risk and calculate payout frequencies under historical drought conditions.

Agricultural Actuarial Modeler

Generate CDS API requests for volumetric soil water layer parameters across multiple agricultural seasons.

Ingest daily soil moisture time series and compute cumulative dry-anomaly duration indexes.

Model synthetic parametric trigger mechanics against historical regional crop yield losses.

Quantify trigger false positives and false negatives to evaluate contract basis risk.

JupyterLab dashboard and CLI exporting synthetic payout curves and trigger diagnostic tables.

Use ECMWF CDS API client sandbox with cached volumetric soil water reanalysis test records. Starter examples below are synthetic. They are not downloaded records.

Copernicus Climate Data Store client Structure cdsapi requests specifying reanalysis datasets, dates, and volumetric soil variables.

optuna, cdsapi, numpy, pandas. Optuna optimizes parametric trigger thresholds to minimize basis risk against loss indicators. Local Python script with LLM assistance for actuarial summary documentation.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

CDS API script contains valid variable and date range parameters.

Calculates cumulative soil moisture deficit across consecutive dry days.

Outputs optimized trigger threshold and simulated historical payout frequency.

```json [ { "input": { "zone_id": "KANSAS_ZONE_4", "target_moisture_m3_m3": 0.15, "consecutive_days_trigger": 14, "daily_soil_moisture": [ 0.18, 0.14, 0.13, 0.12, 0.11, 0.1, 0.12, 0.11, 0.13, 0.12, 0.11, 0.1, 0.09, 0.08, 0.07, 0.16 ] }, "expected_output": { "zone_id": "KANSAS_ZONE_4", "max_consecutive_dry_days": 14, "trigger_activated": true, "simulated_payout_rate": 1, "basis_risk_score": 0.12 } }, { "input": { "zone_id": "KANSAS_ZONE_5", "target_moisture_m3_m3": 0.15, "consecutive_days_trigger": 14, "daily_soil_moisture": [ 0.22, 0.2, 0.18, 0.17, 0.16, 0.15, 0.14, 0.16, 0.17, 0.18 ] }, "expected_output": { "zone_id": "KANSAS_ZONE_5", "max_consecutive_dry_days": 1, "trigger_activated": false, "simulated_payout_rate": 0, "basis_risk_score": 0.04 } } ] ```

Simulations are academic and actuarial models, not authorized insurance contract commitments. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Simulations are academic and actuarial models, not authorized insurance contract commitments. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

CDS API script contains valid variable and date range parameters. Calculates cumulative soil moisture deficit across consecutive dry days. Outputs optimized trigger threshold and simulated historical payout frequency.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Generate CDS API requests for volumetric soil water layer parameters across multiple agricultural seasons. Ingest daily soil moisture time series and compute cumulative dry-anomaly duration indexes. Model synthetic parametric trigger mechanics against historical regional crop yield losses. Quantify trigger false positives and false negatives to evaluate contract basis risk.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

CDS API script contains valid variable and date range parameters. Calculates cumulative soil moisture deficit across consecutive dry days. Outputs optimized trigger threshold and simulated historical payout frequency.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

JupyterLab dashboard and CLI exporting synthetic payout curves and trigger diagnostic tables.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Simulations are academic and actuarial models, not authorized insurance contract commitments.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Generate CDS API requests for volumetric soil water layer parameters across multiple agricultural seasons.

  • Ingest daily soil moisture time series and compute cumulative dry-anomaly duration indexes.

  • Model synthetic parametric trigger mechanics against historical regional crop yield losses.

  • Quantify trigger false positives and false negatives to evaluate contract basis risk.

Resources and assets

Reference links and supporting material

Dataset notes

Use ECMWF CDS API client sandbox with cached volumetric soil water reanalysis test records. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

Optuna

Hyperparameter Optimization

Evaluated output

No output checks are configured.

Evaluation checks
  • Generate CDS API requests for volumetric soil water layer parameters across multiple agricultural seasons....
  • CDS API script contains valid variable and date range parameters. Calculates cumulative soil moisture defic...
  • JupyterLab dashboard and CLI exporting synthetic payout curves and trigger diagnostic tables.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 1 configured tool

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • Optuna · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build an ERA5 Drought Soil Moisture Parametric Simulator