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Updated: Nov 1, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Improved water resource management framework for water sustainability and security
Sameh S Ahmed1, Rekha Bali2, Hasim Khan3
1Department of Civil and Environmental Engineering, College of Engineering, Majmaah University, Majmaah, 11952, Saudi Arabia; Mining and Metallurgical Engineering Department, Faculty of Engineering, Assiut University, Assiut, 71516, Egypt.
This study introduces an IoT-enabled Water Resource Management and Distribution Monitoring System (IWRM-DMS) for rural areas. The system effectively manages water needs and distribution, ensuring quality and minimizing demand with high efficiency.
Area of Science:
- Environmental Science
- Computer Science
Background:
- Water resources are critical for economic growth, social progress, and environmental health.
- Existing systems often struggle to meet the complex demands of water management, especially in rural settings.
Purpose of the Study:
- To present an innovative IoT-enabled Water Resource Management and Distribution Monitoring System (IWRM-DMS).
- To address water needs, distribution, and quality management in rural areas using advanced technology.
Main Methods:
- Implementation of an IWRM-DMS utilizing sensors (water flow, pH, pressure valve, ultrasound), gauge meters, and motors.
- Integration of Machine Intelligence for demand prediction within a decision support system.
- Development of a system to monitor water quality and ensure efficient distribution in villages.
Main Results:
- The IWRM-DMS demonstrated high performance with 96.93% efficiency and 98.24% reliability.
- Achieved reduced prediction errors with MAPE of 21.41% and RMSE of 15.12%.
- Showcased cost-effectiveness (95.7%) and improved prediction accuracy (95.29%).
Conclusions:
- The proposed IWRM-DMS is applicable in real-time environments for rural water management.
- The system effectively meets domestic water demands, optimizes distribution, and ensures water quality.
- The framework offers a significant improvement over existing methods in terms of efficiency, reliability, and cost.
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