International Journal of Water (6 papers in press)

Regular Issues

• Accuracy of rainfall prediction using deep learning based on a recurrent neural network with an LSTM layer method  
  by Rindra Yusianto, Rabei Raad Ali, Pulung Nurtantio Andono, Herwin Suprijono 
  Abstract: This study aims to improve the accuracy of rainfall prediction using deep learning on agro-industrial commodity planting land. The variables used are temperature, humidity, and rainfall data as training and test data. The deep learning model used in this study is a Recurrent Neural Network (RNN) with an LSTM layer. The study results show that the RNN model with the LSTM Layer in deep learning can predict rainfall based on temperature and humidity data. We found that the accuracy during the training stage using 375 LSTM layers was better with 100 epochs because the result was 91.25% compared to 1000 epochs, only obtaining an accuracy of 89.32%, and 1500 epochs of 87.27%.
  Keywords: deep learning; LSTM layer; RNN; prediction accuracy; rainfall prediction.
  DOI: 10.1504/IJW.2025.10073347
   
  
• Classification based forecasting models using medium range hydro-meteorological data of the flood affected districts of Kerala  
  by Sweta Shukla, T.V. Vijay Kumar, Vikas Mittal 
  Abstract: Floods are one of the most recurring and damaging phenomena across the globe. India experiences frequent flood incidents due to its geographical setting, climatic conditions and poor drainage system. In recent past, uncontrolled and unplanned human interventions in flood plains have aggravated the flood impacts leading to increase in flood events in riverine and coastal plains. To minimize such occurrences, preparedness measures need to be adopted and implemented that would enable better forecasting of flood events. This paper aims to design flood forecasting models for the districts of Kerala where recurring floods are one of the most concerning issues. Five machine learning techniques are used for forecasting floods in Kerala using the hydro-meteorological flood dataset consisting of meteorological parameters. The experimental results show that amongst all models, Random Forest (RF) model has a comparatively better ability to forecast meteorological conditions that may lead to floods in Kerala.
  Keywords: hazard; disaster risk reduction; flood forecasting; artificial intelligence; machine learning.
  DOI: 10.1504/IJW.2025.10074916
   
  
• Extraction the soil moisture index and land surface temperature for Newport County in Wales, UK, through analysing Landsat 8-OLI using GIS  
  by Hayder H. Kareem 
  Abstract: Soil moisture has high potential impact on climate change and drought. The soil moisture index (SMI) is calculated using remote sensing, a process called the satellite sensor method. Land surface temperature (LST) was found in three ways using multispectral data including red, near-infrared (NIR) and thermal infrared bands (TIRS1 and TIRS2). Soil moisture maps for Newport County, Wales, UK are produced using geographical information systems (GIS). The distribution range of LST was 4.446 11.571
  Keywords: SMI; soil moisture index; LST; land surface temperature; GIS; geographical information systems; Newport County; Wales; United Kingdom.
  DOI: 10.1504/IJW.2025.10074917
   
  
• Epilithic diatoms as indicators of water quality in Upano River, Ecuador  
  by Patricio Méndez, Rogelio Ureta, Luis Tierra, Ángel Flores 
  Abstract: This study investigates the impact of urbanization and agriculture on the water quality of river ecosystems, using epilithic diatoms as bioindicators. The Upano river sub-basin, affected by hy-dropower, mining, and livestock farming, was chosen as the study area. Sampling was performed during summer and winter, analyzing physical and chemical parameters, like identifying and counting diatoms. The results showed a pattern of eutrophication along the sub-basin, with var-iations in water quality related to anthropogenic influence. There were recognized 36 species of diatoms, whose diversity and abundance reflect the ecological condition of the water. The study emphasizes that biological indexes are valuable, as they complement the physicochemical measurements and attain effective water resource management, therefore highlighting the need for integrated approaches to the preservation of aquatic ecosystems.
  Keywords: bioindicators; diatom index; water quality; species richness; phytoplankton.
  DOI: 10.1504/IJW.2025.10076170
   
  
• An Integrated Modeling Approach for Sustainable Development of the UNESCO classified ecosystem (Ichkeul Lake, North Africa)  
  by Bechir Bejaoui 
  Abstract: This paper presents the results of a simulation study on the impact of integrating water intake and output for and from Lake Ichkeul, a Ramsar and UNESCO reserve wetland in North Tunisia. Three scenarios were simulated over nine years, with varying amounts of freshwater injected into the lake from different dams. The study showed that a non-active lake management policy would result in severe ecosystem degradation, with the lake eventually becoming a salt marsh. Under the status quo, the area and density of Potamogeton would decrease dramatically and the number of migratory birds would rapidly decline. The second scenario would allow the ecosystem to be barely resilient and maintain itself, while the third scenario would lead to long-term sustainability and stabilize all ecosystem components. The results of the present study have implications for water management policies and the preservation of the unique biodiversity of the Ichkeul Lake ecosystem.
  Keywords: Ichkeul Lake; Water management; Ecosystem resilience; Wetland conservation; Scenarios.
  DOI: 10.1504/IJW.2025.10076267
   
  
• Cownomics and water ecology: towards a sustainable rejuvenation process in India  
  by Rabinarayan Patnaik 
  Abstract: Water is the lifeblood of the world, and global civilization cannot sustain itself without relying on it. However, this invaluable and indispensable resource has been wasted and rendered unusable due to various man-made and natural reasons. This has led to a deadly scenario known as the water crisis, which has become increasingly severe globally, including in India. Many traditional methods for water rejuvenation exist, but none have been deemed sustainable and eco-friendly solutions. In contrast, Cownomics is the only in-situ water treatment process that has begun changing perceptions of these technologies. With encouraging results in various water rejuvenation projects in lakes and rivers across India, it has been applied to rejuvenate six heritage water bodies situated in coastal areas of Cuttack and Puri in Odisha (an Eastern state in India). An outcome based study like this can be useful for policymakers and stakeholders in the future.
  Keywords: cownomics; pollution; rejuvenation; sustainability; water crisis; water policy; ground water; water stress; heritage water bodies; vedic treatment.
  DOI: 10.1504/IJW.2025.10076758