Opportunity

SAM #W912BV26CX100

Prado Dam Spillway Hydroforecasting Software and Services Solicitation

Buyer

USACE Tulsa District

Posted

August 24, 2026

Respond By

September 08, 2026

Identifier

W912BV26CX100

NAICS

513210, 541512

The U.S. Army Corps of Engineers, Tulsa District, is seeking hydroforecasting software and services to support the Prado Dam Spillway Modification Project in Corona, California. - Government Buyer: - U.S. Army Corps of Engineers - Tulsa District - Products/Services Requested: - AI-powered hydroforecasting software and implementation services - Streamflow forecasts across multiple horizons: - Short-term (10-day) - Seasonal (90-day) - Annual (daily, 1-year) - Historical reforecasts delivered in CSV format - Extended quantiles for full hydrograph prescription at each model timestep - Probabilistic confidence intervals for each forecast point - Unique/Notable Requirements: - Solution must combine AI-powered hydrological and meteorological models with traditional approaches - Forecasts must support risk-informed decision making for emergency protective measures and construction project action plans - Platform must demonstrate deep hydrologic expertise and accurate rainfall/inflow prediction - Estimated Contract Value: - $25,000 to $350,000 - Period of Performance: - 5 years - No specific OEMs or vendors are named in the solicitation, but the requirement is for specialized hydroforecasting software and services.

Description

The purpose of this work is to provide streamflow forecasts across short-term (10-day), seasonal (90-day), and annual (daily, 1-year) horizons to enable informed risk-informed decision making. This streamflow model / forecast should contain forecast points at the inflow to Prado Dam, inclusion of historical reforecasts for validation period delivered in CSV files, extended quantiles to enable prescription of the full hydrograph at each model timestep, and clear probabilistic confidence intervals for each forecast point.

The model should provide AI powered hydrological and meteorological forecasts in conjunction with traditional models. The AI-powered platform will be expected to deliver precise, multi-horizon streamflow forecasts, from hourly to annual, leveraging deep hydrologic expertise. Its core value lies in accurately predicting rainfall events and basin inflow volumes that could necessitate emergency protective measures within our construction project’s action plan, which mitigates risks to personnel and infrastructure.

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