Watershed Nutrient Pollution Source Counterfactual QA Dataset
- Records
- 5000
- Size
- 0.3GB
- Format
- JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
This dataset provides counterfactual question-answer examples about nutrient sources in watersheds, including agricultural runoff and wastewater discharge. Examples describe baseline watershed and water-quality conditions, interventions that remove or change a source, relevant evidence, and comparative conclusions. Answers state assumptions, cautiously assess likely changes in nutrient levels and water quality, and identify evidence limits, supporting training and evaluation for environmental reasoning and water-quality impact analysis.
Overview
Dataset Insights
Preview
Sample Examples
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| question | string | Asks how the specified source intervention would likely affect nutrient conditions or water quality compared with the baseline. |
| assumptions | string | States the assumptions required for the counterfactual comparison, such as other nutrient sources and environmental conditions remaining unchanged. |
| evidence_notes | string | Summarizes observations, studies, or other evidence relevant to the baseline and counterfactual comparison, including known limitations. |
| evidence_boundary | string | Explains what the available evidence supports and identifies uncertainty, missing information, or limits on causal attribution. |
| watershed_scenario | string | Describes the watershed, baseline conditions, relevant nutrient levels, and context needed to interpret the scenario. |
| source_intervention | string | Specifies the nutrient source removed or changed in the counterfactual scenario and any assumptions about the intervention. |
| counterfactual_answer | string | Compares the likely water-quality outcome under the counterfactual with the baseline using appropriately qualified language. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use
Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization
No PII, no real company names, simulated scenarios follow industry standards
Compliance System
Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs
FAQ
Frequently Asked Questions
- What does the dataset contain?
- Each example is organized around a watershed scenario and includes baseline conditions, a nutrient-source intervention, relevant evidence, a question, and a counterfactual answer. Assumptions and evidence boundaries can also be specified for the comparison.
- How does it handle uncertainty?
- Answers compare the intervention scenario with the baseline using qualified, conditional language. They state assumptions, such as other sources or environmental conditions remaining unchanged, and identify gaps in evidence or limits on causal attribution.
- Which training and evaluation tasks does it support?
- It supports counterfactual and causal reasoning, nutrient pollution source analysis, and water-quality impact assessment. It can also help evaluate whether a model gives appropriately cautious environmental science answers based on the evidence provided.
- How can I obtain the data and confirm its license?
- Use the dataset product page or the provider's designated channel to review and obtain the data. Availability, download options, and permitted uses depend on the applicable product listing and license; confirm that the terms cover your intended research or commercial use.
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Cite this Work
@dataset{Mobiusi2026,
title={Watershed Nutrient Pollution Source Counterfactual QA Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/7ee1365ea807fcc97ce44e171acbf09d?dataset_task_cate_id=6},
urldate={2026-10-19},
keywords={watershed nutrient pollution,counterfactual QA dataset,water quality change analysis,agricultural runoff impact,wastewater discharge assessment,environmental causal reasoning,nutrient source analysis,environmental QA training},
version={1.0}
}Using this in research? Please cite us.