AQUA: Water Infrastructure, Ecosystems, and Society

Special Issue on: Exploring the Rise of AI-Based Smart Water Management Systems

Data-driven smart applications for water system management enable better governance and operational implementation, as well as improving potential public participation. Despite the use of significant computational techniques by water systems, the water industry is under-performing behind other sectors in terms of the digital revolution. This digitization transformation could help smart water systems expand their operations. Water utilities could exploit the potential of artificial intelligence technology to make better informed decisions, improve the delivery of services and lower costs.

In an era where sustainable resource management is paramount, the emergence of artificial intelligence (AI)-based smart water management systems stands as a game-changer. These systems are revolutionizing our approach to water resource management, promising a more sustainable and efficient future.

AI is an area of research and development that deals with computer intelligence simulations. AI and computer vision are primarily applied to decision-making activities to provide an adequate supply of water. Specifically, water systems can maximize data and information to make better decisions to improve the delivery of services, optimize investment capital, and lower operational expenses, such as environmental implications. Water utilities are often joining the ranks of other industries, particularly energy, without fully comprehending the principles and consequences of incorporating information and communications technology (ICT) in their management. IoT devices may be used to measure the Potential of Hydrogen (PH) and Total Dissolved Solids (TDS) contribution of different water types using AI-based Arduino programming language. An artificial intelligence-based leak detection approach employs hydrophone technology sensors to measure even minor leaks in water pipes via noise. Additionally, through utilizing ground and light sensors, AI development solutions for water supply systems can properly estimate the amount of water and fertilizers necessary in particular fields. By recognising microorganisms, AI can improve present systems. This technology is superior to the current way of identifying possibly hazardous microbes using biochemical chips.

We are pleased to publish our Special Issue entitled 'Exploring the Rise of AI-Based Smart Water Management Systems'.

Guest Editors:

Dr. Padam Jee Omar, Department of Civil Engineering, Indian Institute of Technology, (Banaras Hindu University, Varanasi), India

Dr. Qi Wang, School of Civil and Transportation Engineering, Guangdong University of Technology, China

Dr. Pankaj Kumar Gupta, Department of Geography and Environmental Management, Faculty of Environment, University of Waterloo, Canada  

Editorial: Exploring the rise of AI-based smart water management systems

Padam Jee Omar; Pankaj Gupta, Qi Wang

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (11): iii–iv.

DOI: https://doi.org/10.2166/aqua.2023.005

AI for Predicting Gravity Dam Seepage: Challenges & Solutions

Priyanka Ashok Garsole, Shantini Bokil, Vijendra Kumar, Arunabh Pandey, Niraj S. Topare

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (7): 1228–1248.

DOI: https://doi.org/10.2166/aqua.2023.042

A novel tuned Custom ensemble machine learning model to predict abutment scour depth in clear water conditions

Lalit Kumar, Mohammad Saud Afzal, Somshubhra Ghosh

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (5): 798–813.

DOI: https://doi.org/10.2166/aqua.2023.047

Climate change Forecasting Using Data Mining Algorithms

Parul Khatri, Tripti Arjariya, Nikita Shivhare Mitra

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (6): 1065–1083.

DOI: https://doi.org/10.2166/aqua.2023.046

A comparison of the performance of SWAT and artificial intelligence models for monthly rainfall–runoff analysis in the Peddavagu River Basin, India

Padala Raja Shekar, Aneesh Mathew, Arunabh Pandey, Avadhoot Bhosale

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (9): 1707–1730.

DOI: https://doi.org/10.2166/aqua.2023.048

Assessing the performance of Wheat (Triticum aestivum L.) crop by managing irrigation and nitrogen fertilizer under semi-arid environment

Anshuman Gunawat, Devesh Sharma, Aditya Sharma, Swatantra Kumar Dubey

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (7): 1211–1227.

DOI: https://doi.org/10.2166/aqua.2023.032

Optimization of batch study parameters for the adsorption of lead(II) ions onto spent tea grains

Surendra Singh Chauhan, Prabhat Kumar, Singh Dikshit

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (6): 996–1024.

DOI: https://doi.org/10.2166/aqua.2023.020

Performance evaluation of artificial neural network model in hybrids with various preprocessors for river streamflow forecasting

Sadegh Momeneh, Vahid Nourani

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (6): 947–968.

DOI: https://doi.org/10.2166/aqua.2023.010

Study of acidic air pollutant (SO 2 and NO 2 ) tolerance of microalgae with sodium bicarbonate as growth stimulant

Saurabh Srivastava, Padam Jee Omar, Shiwanshu Shekhar, Sneha Gupta

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (5): 739–749.

DOI: https://doi.org/10.2166/aqua.2023.013

Using image texture to monitor the growth and settling of flocs

Qidong Ma, Yan Liu, Zhangwei He, Haiguang Wang, Ruolan Wang

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (10): 1825–1836.

DOI: https://doi.org/10.2166/aqua.2023.014

Accuracy evaluation of scour depth equations under the submerged vertical jet

Sai Guguloth, Manish Pandey

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (4): 557–575.

DOI: https://doi.org/10.2166/aqua.2023.015

ANFIS based Soft Computing Models for Forecasting EDI over an Arid Region of India

Ayilobeni Kikon, B. M. Dodamani, Surajit Deb Barma, Sujay Raghavendra Naganna

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (6): 930–946.

DOI: https://doi.org/10.2166/aqua.2023.204

Development and optimization of the dye removal process by Trichoderma reesei using starch effluent as a growth supplement

Shweta Kalia, Saurabh Samuchiwal, Vidushi Dhaka, Anushree Malik

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (3): 395–410.

DOI: https://doi.org/10.2166/aqua.2023.003

Mechanistic action of pesticides on pests and their consequent effect on fishes and human health with remediation strategies

Anita Singh, Monika Mahajan, Richa Kothari, Naveen Kumar Singh, Rajeev Pratap Singh

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (3): 363–380.

DOI: https://doi.org/10.2166/aqua.2023.233

Statistical evaluation of snow accumulation and depletion from remotely sensed MODIS snow time series data using the SARIMA model

Mohit Kumar, Reet Kamal Tiwari, Kamal Kumar, Kuldeep Singh Rautela

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (3): 348–362.

DOI: https://doi.org/10.2166/aqua.2023.231

A Comparison of SCS-CN Based Models for Hydrological Simulation of the Aghanashini River, Karnataka, India

Harmandeep Singh, Mohammad Afaq Alam, Priyank J. Sharma, Kuldeep Singh Rautela

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (4): 507–519.

DOI: https://doi.org/10.2166/aqua.2023.213

Persistence of heavy metals and human health risk assessment in the South Indian industrial area

Kondarathi Arunakumari, Farveen Begum, Lagudu Surinaidu, Mogali Jayaraja Nandan, Umamaheswari Alapati

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (6): 898–913.

DOI: https://doi.org/10.2166/aqua.2023.210

ANN-based PCA to predict evapotranspiration: a case study in India

Marykutty Abraham, Sankaralingam Mohan

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (7): 1145–1163.

DOI: https://doi.org/10.2166/aqua.2023.201

Assessment of wastewater treatment potential of sand beds of River Ganga at Varanasi, India

Anoop Narain Singh, Ankur Mudgal, Ravi Prakash Tripathi, Padam Jee Omar

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (5): 690–700.

DOI: https://doi.org/10.2166/aqua.2023.200

Water, sanitation, and hygiene practices among rural households and related health impacts: a case study from some North Indian villages

Anjali Malan, Meenakshi Suhag, Pankaj Kumar Gupta, Hardeep Rai Sharma

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (6): 885–897.

DOI: https://doi.org/10.2166/aqua.2023.199

Temporal moment-based approach to understand the dissolved-phase LNAPL recovery and associated characteristics in the porous system under dynamic groundwater table conditions

Abhay Guleria, Pankaj Kumar Gupta, Sumedha Chakma, Brijesh Kumar Yadav

AQUA — Water Infrastructure, Ecosystems and Society (1 November 2023) 72 (4): 479–490.

DOI: https://doi.org/10.2166/aqua.2023.1889