MasterFaculty of Environmental Sciences and Sustainability

Smart Water Networks and Sustainable Hydrology

Welcome to the advanced study of water innovation! I am Prof. Dr. Elif Doğan. As a professor and a pioneering force in the field of Smart Water Networks and Sustainable Hydrology, I bring a unique blend of engineering expertise and environmental insight to the study of water systems. I am honored to lead the Smart Water Networks and Sustainable Hydrology (M.Sc.) program at Nexier University.

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Level: Master
Learning model: Professor + Mentor
Named list: See the named lists · 12 months recommended

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The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

Academic focus

Mastering the Design and Management of Smart Water Systems; Specializing in Hydrological Modeling, IoT-Based Monitoring Networks, and Data-Driven Approaches to Water Resource Management.

Practical focus

Hydrology, Civil Engineering, Data Analytics, Sensor Networks, Public Policy, Leadership in Water Resource Management.

After this programme

Success journey, careers and practice

Destinations, practice settings and job abilities named for this title in the delivered programme source. From graduation onwards where the source names that path.

Success journey

Internships in technology companies or environmental organizations
Roles as water resources engineers or data analysts
Consultancy in advanced smart water networks and sustainable hydrology
Support roles in academic research projects on smart water networks

Career opportunities

Director of Water Innovation for utility companies or environmental agencies
Smart Water Network Designer for technology companies
Hydrologist specializing in sustainable water management
Researcher in Smart Water Networks and Sustainable Hydrology

Jobs and projects

Cultivating an interdisciplinary approach, integrating environmental engineering, computer science, and data analytics
Developing strategic thinking for smart water networks and sustainable hydrology
Enhancing problem-solving through the analysis of complex water challenges
Critical thinking for a comprehensive and nuanced understanding of Smart Water Networks and Sustainable Hydrology

Copied from the delivered professor and mentor rows for this title.

This programme

What you study, and what it builds

Gains and skills named for this title, listed as a reader would scan them.

What you gain
- Mastering advanced practical skills in Hydrology and Civil Engineering.
- Gaining expertise in Data Analytics and Sensor Networks.
- Developing problem-solving abilities for complex Public Policy.
- Cultivating an interdisciplinary approach, integrating environmental engineering, computer science, and data analytics at an advanced level.
Skills you build
- Mastering AI-powered techniques for hydrological flow optimization.
- Applying advanced engineering principles to smart water networks and sustainable hydrology.
- Interpreting and analyzing complex water systems and their implications for water resource management.
- Identifying optimal water distribution and predicting flood risks.

Listed courses

Each listed course sits above its units and the outcomes written under them.

Smart Water Networks and Sustainable Hydrology

01Mastering the Design and Management of Smart Water Systems
1. FoundationsFoundations of Mastering the Design and Management of Smart Water Systems
  The learner can master advanced practical skills in Hydrology and Civil Engineering, as applied to Mastering the Design and Management of Smart Water Systems.
  The learner can gain expertise in Data Analytics and Sensor Networks, as applied to Mastering the Design and Management of Smart Water Systems.
2. MethodsMethods in Mastering the Design and Management of Smart Water Systems
  The learner can develop problem-solving abilities for complex Public Policy, as applied to Mastering the Design and Management of Smart Water Systems.
  The learner can cultivating an interdisciplinary approach, integrating environmental engineering, computer science, and data analytics at an advanced level, as applied to Mastering the Design and Management of Smart Water Systems.
3. ApplicationApplication of Mastering the Design and Management of Smart Water Systems
  The learner can master AI-powered techniques for hydrological flow optimization, as applied to Mastering the Design and Management of Smart Water Systems.
  The learner can apply advanced engineering principles to smart water networks and sustainable hydrology, as applied to Mastering the Design and Management of Smart Water Systems.
02Hydrological Modeling
1. FoundationsFoundations of Hydrological Modeling
  The learner can interpreting and analyze complex water systems and their implications for water resource management, as applied to Hydrological Modeling.
  The learner can identify optimal water distribution and predicting flood risks, as applied to Hydrological Modeling.
2. MethodsMethods in Hydrological Modeling
  The learner can apply a method from Hydrological Modeling to a documented case.
  The learner can select an appropriate method from Hydrological Modeling for a stated problem.
3. ApplicationApplication of Hydrological Modeling
  The learner can evaluate a practice of Hydrological Modeling against a stated criterion.
  The learner can transfer Hydrological Modeling to a new documented context.
03IoT-Based Monitoring Networks
1. FoundationsFoundations of IoT-Based Monitoring Networks
  The learner can explain the core terms of IoT-Based Monitoring Networks.
  The learner can distinguish related ideas inside IoT-Based Monitoring Networks.
2. MethodsMethods in IoT-Based Monitoring Networks
  The learner can apply a method from IoT-Based Monitoring Networks to a documented case.
  The learner can select an appropriate method from IoT-Based Monitoring Networks for a stated problem.
3. ApplicationApplication of IoT-Based Monitoring Networks
  The learner can evaluate a practice of IoT-Based Monitoring Networks against a stated criterion.
  The learner can transfer IoT-Based Monitoring Networks to a new documented context.
04Data-Driven Approaches to Water Resource Management
1. FoundationsFoundations of Data-Driven Approaches to Water Resource Management
  The learner can explain the core terms of Data-Driven Approaches to Water Resource Management.
  The learner can distinguish related ideas inside Data-Driven Approaches to Water Resource Management.
2. MethodsMethods in Data-Driven Approaches to Water Resource Management
  The learner can apply a method from Data-Driven Approaches to Water Resource Management to a documented case.
  The learner can select an appropriate method from Data-Driven Approaches to Water Resource Management for a stated problem.
3. ApplicationApplication of Data-Driven Approaches to Water Resource Management
  The learner can evaluate a practice of Data-Driven Approaches to Water Resource Management against a stated criterion.
  The learner can transfer Data-Driven Approaches to Water Resource Management to a new documented context.
05Ethical Implications of AI in Water Governance
1. FoundationsFoundations of Ethical Implications of AI in Water Governance
  The learner can explain the core terms of Ethical Implications of AI in Water Governance.
  The learner can distinguish related ideas inside Ethical Implications of AI in Water Governance.
2. MethodsMethods in Ethical Implications of AI in Water Governance
  The learner can apply a method from Ethical Implications of AI in Water Governance to a documented case.
  The learner can select an appropriate method from Ethical Implications of AI in Water Governance for a stated problem.
3. ApplicationApplication of Ethical Implications of AI in Water Governance
  The learner can evaluate a practice of Ethical Implications of AI in Water Governance against a stated criterion.
  The learner can transfer Ethical Implications of AI in Water Governance to a new documented context.
06Advanced Hydrological Modeling and Data Analytics
1. FoundationsFoundations of Advanced Hydrological Modeling and Data Analytics
  The learner can explain the core terms of Advanced Hydrological Modeling and Data Analytics.
  The learner can distinguish related ideas inside Advanced Hydrological Modeling and Data Analytics.
2. MethodsMethods in Advanced Hydrological Modeling and Data Analytics
  The learner can apply a method from Advanced Hydrological Modeling and Data Analytics to a documented case.
  The learner can select an appropriate method from Advanced Hydrological Modeling and Data Analytics for a stated problem.
3. ApplicationApplication of Advanced Hydrological Modeling and Data Analytics
  The learner can evaluate a practice of Advanced Hydrological Modeling and Data Analytics against a stated criterion.
  The learner can transfer Advanced Hydrological Modeling and Data Analytics to a new documented context.
07Smart Water Networks and Sensor Technologies
1. FoundationsFoundations of Smart Water Networks and Sensor Technologies
  The learner can explain the core terms of Smart Water Networks and Sensor Technologies.
  The learner can distinguish related ideas inside Smart Water Networks and Sensor Technologies.
2. MethodsMethods in Smart Water Networks and Sensor Technologies
  The learner can apply a method from Smart Water Networks and Sensor Technologies to a documented case.
  The learner can select an appropriate method from Smart Water Networks and Sensor Technologies for a stated problem.
3. ApplicationApplication of Smart Water Networks and Sensor Technologies
  The learner can evaluate a practice of Smart Water Networks and Sensor Technologies against a stated criterion.
  The learner can transfer Smart Water Networks and Sensor Technologies to a new documented context.
08Public Policy for Water Resource Management
1. FoundationsFoundations of Public Policy for Water Resource Management
  The learner can explain the core terms of Public Policy for Water Resource Management.
  The learner can distinguish related ideas inside Public Policy for Water Resource Management.
2. MethodsMethods in Public Policy for Water Resource Management
  The learner can apply a method from Public Policy for Water Resource Management to a documented case.
  The learner can select an appropriate method from Public Policy for Water Resource Management for a stated problem.
3. ApplicationApplication of Public Policy for Water Resource Management
  The learner can evaluate a practice of Public Policy for Water Resource Management against a stated criterion.
  The learner can transfer Public Policy for Water Resource Management to a new documented context.
09Case Studies in Smart Water Networks and Sustainable Hydrology
1. FoundationsFoundations of Case Studies in Smart Water Networks and Sustainable Hydrology
  The learner can explain the core terms of Case Studies in Smart Water Networks and Sustainable Hydrology.
  The learner can distinguish related ideas inside Case Studies in Smart Water Networks and Sustainable Hydrology.
2. MethodsMethods in Case Studies in Smart Water Networks and Sustainable Hydrology
  The learner can apply a method from Case Studies in Smart Water Networks and Sustainable Hydrology to a documented case.
  The learner can select an appropriate method from Case Studies in Smart Water Networks and Sustainable Hydrology for a stated problem.
3. ApplicationApplication of Case Studies in Smart Water Networks and Sustainable Hydrology
  The learner can evaluate a practice of Case Studies in Smart Water Networks and Sustainable Hydrology against a stated criterion.
  The learner can transfer Case Studies in Smart Water Networks and Sustainable Hydrology to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

My expertise spans the intricate domains of Mastering the Design and Management of Smart Water Systems; Specializing in Hydrological Modeling, IoT-Based Monitoring Networks, and Data-Driven Approaches to Water Resource Management. My work seamlessly integrates environmental engineering, computer science, and data analytics. I am widely recognized for my contributions, with publications like "AI for Urban Flood Prediction and Early Warning Systems" and "Blockchain for Decentralized Water Allocation and Trading" listed on these platforms. I hold prestigious memberships as a "Director of Water Innovation" at Veolia and a "Keynote Speaker" at the World Water Forum. My thought leadership is evident through my advanced research on water-energy-food nexus, climate change impacts on water security, and the ethical implications of AI in water governance, frequently featured in publications like Water Research or Journal of Hydrology.

Applied mentorship

My expertise lies in understanding and navigating the advanced technical challenges of smart water networks, focusing on Hydrology, Civil Engineering, Data Analytics, Sensor Networks, Public Policy, and Leadership in Water Resource Management. I focus on the practical implementation and application of theoretical concepts, explaining complex interdisciplinary topics in a clear and concise manner. I guide my students through the challenging integration aspects of different fields and ensure they grasp the nuances of combining disparate data types, fostering a detail-oriented and methodical approach.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

My research is focused on the future of water management in a changing world:

Book: "Flowing Intelligence: Smart Water Networks and Sustainable Hydrology." This book provides advanced insights into mastering the design and management of smart water systems. It covers hydrological modeling, IoT-based monitoring networks, and data-driven approaches to water resource management.

Peer-Reviewed Journal Article: "AI for Smart Water Network Management: Optimizing Distribution and Consumption." Published in the Journal of Water Resources Innovation, this article presents groundbreaking research on mastering the engineering and economic principles of smart grids. It specializes in integrating variable renewable energy sources, energy storage, and AI-powered grid management, showcasing novel control algorithms and predictive models that enhance grid stability, efficiency, and resilience in a high-renewable energy future.

Article: "AI for Adaptive Water Resource Allocation in Arid Regions: Balancing Agricultural, Industrial, and Domestic Demands." This article details the application of AI algorithms for adaptive water resource allocation in arid and semi-arid regions, where water scarcity is a critical challenge. It explores how AI can analyze real-time climate data, water consumption patterns, and stakeholder needs to dynamically optimize water distribution among agricultural, industrial, and domestic sectors, ensuring equitable access and sustainable resource management.

Blog Post (Current Academic Topic): "The Rise of AI for Urban Flood Prediction: Safeguarding Cities in a Changing Climate." This blog post academically explores how Artificial Intelligence is revolutionizing urban flood prediction and management, moving beyond traditional hydrological models to incorporate real-time data from weather radar, IoT sensors in drainage systems, and social media. It discusses how AI can provide hyper-local, accurate flood forecasts, optimize emergency response, and inform urban planning for climate resilience. It highlights successful case studies and the ethical considerations of data privacy in real-time urban monitoring.

Blog Post (Controversial Topic): "The Algorithmic Water Dictator: If AI Controls Our Water Supply, Is It Resource Optimization or Environmental Injustice? The Ethical Cost of Automated Scarcity Management." This article provocatively discusses the highly controversial and unsettling future where advanced AI systems autonomously manage and optimize entire water supply networks, from source allocation and distribution to pricing and rationing during droughts. It questions whether AI, despite its potential for efficiency, could inadvertently exacerbate water inequalities, leading to algorithmic discrimination in access to a fundamental human right, or make decisions that prioritize efficiency over environmental justice or vulnerable communities' needs. It raises profound ethical questions about control over essential resources, data privacy of water consumption patterns, and the imperative to ensure equitable and human-centered governance of our water future.

R / 02

Mentor practice lens

My contributions focus on understanding and navigating the advanced technical challenges of smart water networks:

"AI for Urban Water Cycle Management: Predictive Models and Optimization" (Research Paper).

"IoT-Based Sensor Networks for Real-Time Water Quality Monitoring in Developing Regions" (Technical Manual).

"Policy Instruments for Sustainable Water Resources Management: A Comparative Analysis" (Policy Brief).

Adaptive capability

Professor superpower

I possess a remarkable "superpower": Hydrological Flow Optimizer. When a student proposes a new water distribution network or a climate change adaptation strategy for water resources, I can instantly use the GAF engine to simulate water flow dynamics, predict flood risks, and optimize resource allocation under various climate scenarios and urban development plans. This allows for precise and resilient water infrastructure design.

Adaptive capability

Mentor superpower

I possess a remarkable "superpower": Water Infrastructure Resilience Modeler. When students are designing water infrastructure, I can instantly activate a GAF-powered "Water Infrastructure Resilience Modeler." This tool simulates the network's vulnerability to various disruptions (e.g., pipe bursts, contamination events, cyberattacks) and predicts its recovery time, visually highlighting critical points of failure and suggesting optimal design modifications for maximum resilience and continuous water supply.

Your academic team

Guidance with depth and continuity

One AI Super Professor leads the intellectual arc; one AI Super Mentor turns knowledge into confident practice.

AI Super Professor

Prof. Dr. Elif Doğan

Mastering the Design and Management of Smart Water Systems; Specializing in Hydrological Modeling, IoT-Based Monitoring Networks, and Data-Driven Approaches to Water Resource Management.

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AI Super Mentor

Dr. Wulan Wati

Hydrology, Civil Engineering, Data Analytics, Sensor Networks, Public Policy, Leadership in Water Resource Management.

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Same faculty and level

Related programs

Named lists

Named lists for this house

Core. Bachelor, Master and Doctorate by duration. Enrolment is not open. Nothing here is a sale.

Duration	Bachelor	Master This programme	Doctorate
9 months · Fast track	15000 EUR	12000 EUR	15000 EUR
12 months · Recommended	18000 EUR	15000 EUR	18000 EUR
15 months · Standard	21000 EUR	18000 EUR	21000 EUR
18 months · Flexible	24000 EUR	21000 EUR	24000 EUR
21 months · Extended	27000 EUR	24000 EUR	27000 EUR
24 months · Part-time	30000 EUR	27000 EUR	30000 EUR

These are the owner lists. Enrolment is not open. Nothing here is a sale.

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Smart Water Networks and Sustainable Hydrology

Academic focus

Practical focus

Internships in technology companies or environmental organizations

Roles as water resources engineers or data analysts

Consultancy in advanced smart water networks and sustainable hydrology

Support roles in academic research projects on smart water networks

Director of Water Innovation for utility companies or environmental agencies

Smart Water Network Designer for technology companies

Hydrologist specializing in sustainable water management

Researcher in Smart Water Networks and Sustainable Hydrology

Cultivating an interdisciplinary approach, integrating environmental engineering, computer science, and data analytics

Developing strategic thinking for smart water networks and sustainable hydrology

Enhancing problem-solving through the analysis of complex water challenges

Critical thinking for a comprehensive and nuanced understanding of Smart Water Networks and Sustainable Hydrology

Research leadership

Applied mentorship

Professor research lens

Mentor practice lens

Professor superpower

Mentor superpower

Prof. Dr. Elif Doğan

Dr. Wulan Wati

Find the program that expands your universe.