WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - technical guide

Vickneswaran, K.; Retief, H.; Padilha, R.; Dickens, C.; Silva, P.; Garcia Andarcia, M. 2024. WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - technical guide. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation. 23p.

The present document provides a comprehensive overview of the development, architecture, and capabilities of the Limpopo Digital Twin Chatbot or Copilot (WaterCopilot). WaterCopilot is an AI-driven virtual assistant designed to enhance data accessibility and support decision-making for water management in the Limpopo River Basin (LRB). It has been developed through collaboration between the International Water Management Institute (IWMI) and Microsoft Research. WaterCopilot integrates advanced natural language processing with real-time data retrieval to address key challenges in water resource management, including fragmented information sources, manual data processing, and delays in response.

The document outlines the project's objectives, system architecture, and modular plugin approach, which enables the Copilot to seamlessly connect with various datasets, including real-time environmental data, historical records, and policy documents related to water availability, rainfall patterns, and environmental flow. By leveraging Azure OpenAI services, WaterCopilot interprets user queries and retrieves relevant information. Key features of the Copilot include real-time monitoring of water availability, rainfall patterns, and environmental flow alerts, as well as userfriendly data visualizations and contextual insights.

The deployment strategy utilizes Docker containers on AWS infrastructure, ensuring scalability, reliability, and efficient performance of the Copilot. This document also addresses the technical challenges encountered during development, the solutions implemented to create a robust and adaptable system, and outlines future work aimed at further enhancing WaterCopilot's capabilities. This detailed documentation serves as a technical guide to understanding WaterCopilot's capabilities, architecture, and future directions, emphasizing its role in supporting sustainable water management across the LRB.