Upaka Rathnayake

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Verified

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• PhD
• Professor at Atlantic Technological University

Climate change has significantly impacted global hydrometeorological variables, placing increasing stress on groundwater resources. This study investigates long-term groundwater level trends in the Republic of Karakalpakstan, Uzbekistan, using a combination of non-parametric statistical models. The Mann-Kendall test, Spearman's rank correlation, an...

Deforestation poses a significant conservation challenge on a global scale, endangering both plant life and the interconnected animal communities reliant upon it. This loss is primarily propelled by anthropogenic activities, emphasizing the need for meticulous monitoring tools tailored to the intricacies of regional socio-political and cultural dyn...

This study introduces artificial intelligence models for the first time in the Republic of Ireland to forecast particulate matter (PM 10). By integrating local environmental data with cutting-edge predictive algorithms, this research specifically targets high-impact urban areas in Ireland. The models not only account for complex air quality tempora...

In this study, a machine learning-based predictive model was developed for the Musa petti Wind Farm in Sri Lanka to address the need for localized forecasting solutions. Using data on wind speed, air temperature, nacelle position, and actual power, lagged features were generated to capture temporal dependencies. Among 24 evaluated models, the ensem...

System conveyance efficiency of the canals is highly important in planning new irrigation development schemes. Enhancing the efficiencies directly influences sustainable agricultural practices. This study, conducted in 2022–2023, assessed conveyance losses in three major irrigation schemes in Sri Lanka: Maduru Oya, Hurulu Wewa, and Minipe Left Bank...

New agricultural technologies have increased agricultural capacity and efficiency. Artificial intelligence-basedmethodologies have been widely adopted in agricultural systems, resulting in successes in smart crop manage-ment, smart plant breeding, smart livestock farming, precision aquaculture farming, and agricultural robotics.However, machine lea...

Traditionally, ASR expansion is determined using experimental and finite element method (FEM) based numerical modelling. However, these methods are time-consuming and computationally costly, which makes ASR prediction challenging. Machine learning (ML) techniques can serve as effective alternatives for the early detection of expansion in concrete s...

Soil management is a crucial aspect of sustainable agriculture, and traditional knowledge has played a pivotal role in shaping practices that maintain soil health over time. This study examines the significance of traditional soil management techniques used in Uttar Pradesh, India, and assesses their effectiveness in addressing modern agricultural...

Natural flood management strategies are increasingly recognized as sustainable alternatives to conventional engineered flood control measures. Among these, leaky dams, also known as woody debris dams or log dams, have emerged as effective nature-based solutions for mitigating flood risks while preserving essential ecosystem services. This review tr...

Leaky dams have become essential nature-based solutions for flood management, providing sustainable alternatives to traditional engineered flood control methods. This review delves into the mechanisms by which leaky dams operate, including the regulation of water flow through velocity reduction and distribution across floodplains, effective sedimen...

Urbanization is accelerating rapidly, highlighting the critical role of aligning with sustainable development goals, urban green and blue spaces (UGS and UBS). These spaces play a crucial role in enhancing the health and well-being of city residents in terms of ecology. Acknowledging the importance of urban ecology, this study utilizes Sentinel-2A...

Hydrologic processes in a watershed are typically simulated through hydrologic models 25 due to their availability in the public domain and improved computational capacities. However, 26 choosing a suitable model among the many available for a region of interest is challenging. In our 27 work, we compared streamflow generated by the Soil and Water...

Kala Oya is one of the drier river basins in Sri Lanka that is affected by droughts for certain time periods. Water shortages are visible in crop yields and public water supply due to climate change. Consequently, the Soil and Water Assessment Tool (SWAT) was used to develop hydrological models, and Water Evaluation and Planning (WEAP) software was...

Groundwater quality assessment is crucial for sustainable water resource management and public health protection. This study evaluated the Water Quality Index (WQI) of groundwater in the southern part of Gujarat focusing on the Valsad District. Groundwater in this region occurs in porous, unconsolidated formations and fracture formations, both unde...

This study presents the assessment of groundwater potential and its recharge areas in marginal alluvial and hard rock areas of the Trans-Yamuna region of Prayagraj district, Uttar Pradesh, India. Nine pivotal thematic layers under the geomorpho- logical and hydrogeological categories have been considered for study. The weight of each layer was det...

The need to encourage sustainable construction practices to conserve the rapidly diminishing natural resources increases. Moreover, increases in impermeable areas in urban regions increase flood risk and impose significant stresses on stakeholders. The research presented here was conducted on using recycled low-carbon materials in permeable pavemen...

Cabbage (Brassica oleracea var. capitata) is commonly cultivated in high altitudes and features dense, tightly packed leaves. The Green Coronet variety is well-known for its robust growth and culinary versatility. Maximizing yield is crucial for food sustainability. It is essential to predict the soil's major nutrients (nitrogen, phosphorus , and p...

Effective management of stormwater runoff is crucial in refugee camps and temporary shelters. Across the Africa, this is vital especially with the intense rainfalls due to the climate effect. Sustainable Drainage Systems (SuDS) can be implemented to provide potential sources of water resources across refugee camps and internally displaced people (I...

This research provides empirical insights into the mechanical properties of concrete made with fine electric arc furnace slag aggregates. The utilization of fine electric arc furnace slag as aggregates in concrete production could be a catalyst in addressing the current unsustainable extraction rates of the natural non-renewable resources thereby p...

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This study examines the spatio-temporal dynamics of drought and microclimate variability in Rajasthan, India, from 2010 to 2022 using the Standardized Drought Composite Index (SDCI). The SDCI integrates the Temperature Condition Index (TCI), Precipitation Condition Index (PCI), and Vegetation Condition Index (VCI) to assess drought severity. Remote...

Benthic diatoms are being used as indicators to assess the biological quality of surface waters in Kosovo. The Klina River is the left tributary of the White Drin River Basin, with a length of 69 km. The study assessed the level of surface water quality in the Klina River using 12 diatomic indices calculated with the Omnidia program. For this purpo...

Accurate prediction of river flow is crucial for water resource management and flood forecasting. This study employs advanced machine learning (ML) models, including CatBoost, Light Gradient-Boosting Machine, Random Forest, and XGBoost, to predict flow at ‘Mandleshwar’ using level data from key locations along the Narmada River Basin. The dataset c...

Thirteen GCMs under Coupled Model Intercomparison Project-6 were analyzed against IMD grid data using compromise programming (CP) to identify the optimal model. This innovative multi-criteria decision-making approach balances competing performance metrics to enhance model selection. The CP matrix indicated that the MPI-ESM1-2-HR model optimally sim...

Climate change has become an emerging topic, leading to widespread damage. However, when considering climate, attention is drawn to various scales, and urban microclimate has emerged as a trending subject due to its direct relevance to human living environments. Among the microclimatic factors, temperature and precipitation are utilized in order to...

This paper introduces a discrete-time nonlinear coupled dynamical flow on networks, aiming to model and analyze the behaviour of interconnected systems where the dynamics of each node depend both on its intrinsic nonlinear evolution and on coupling interactions with adjacent nodes. The mathematical formulation captures these dynamics in matrix form...

This paper explores the ergodic properties of multi-agent Iterated Function Systems (IFS) with subjective probabilities. We extend the IFS framework to multi-agent systems where interacting agents update their states based on weighted mappings, interaction strengths, and subjective probability distortions. Conditions for ergodicity are established,...

Tropical cyclones are one of nature’s most catastrophic occurrences, causing significant humanitarian crises, economic losses, and human fatalities, particularly in coastal regions. This paper explores the diverse challenges, such as health, inequality, and developmental issues caused by tropical cyclones. Accordingly, a structured literature revie...

Floods have been identified as one of the world's most common and widely distributed natural disasters over the last few decades. Floods' negative impacts could be significantly reduced if accurately predicted or forecasted in advance. Apart from large-scale spatiotemporal data and greater attention to data from the Internet of Things, the worldwid...

Proper water resource management is one of the most critical problems in the world. However ongoing climate change on top of urbanization and population growth adversely impacts water resources management. Therefore, to reach the localized goals, inter-basin water transfer has been given significant attention. This paper aims to understand the impo...

Understanding the cyclic loading behaviour of geopolymer concrete (GPC) after exposure to elevated temperatures is vital in judging the damage to structures and fire-resistant applications. However, effectively forecasting the compressive strength of GPC under cyclic loading circumstances following exposure to elevated temperatures is complex. This...

This study conducts a comprehensive analysis of gender inequality in Sri Lanka, focusing on the relationship between key socioeconomic factors and the Gender Inequality Index (GII) from 1990 to 2022. By applying machine learning techniques, including Decision Trees and Ensemble methods, the study investigates the influence of economic indicators su...

Spillways regulate water flow rates to maintain optimum levels in reservoirs. These come in different designs; the ogee spillways are some of the most safe and effective. In this paper, the impact of reverse curve geometry modifications on the water surface profile and pressure profile is tested to help bridge the deficiency in the understanding of...

This study aims to develop an AI prediction system for watersheds, utilizing data from Sri Lanka and Vietnam in collaboration with overseas researchers. Initially, a foundational AI prediction system will be constructed, and basic data will be gathered based on river data from Japan. Subsequently, topographic data of the watershed area, managed by...

Global and regional water resources systems will be impacted by climate change and the inflow to drinking water reservoirs is a significant issue. Urbanization increases water demand in cities, and deteriorating infrastructures lead to leaks in water distribution systems. The study aims to evaluate and create a new water distribution system for Sur...

Understanding soil salinity levels is essential for effective agricultural planning and, consequently, for ensuring food security and sustainability. However, poor practices have significantly impacted soil salinity levels in many developing countries. In Uzbekistan, soil salinity levels have not been adequately assessed and documented over the pas...

Due to the soil’s low strength and high sensitivity to deterioration, designing and building in soft soil is extremely challenging and can result in structural damage. Insufficient space in urban areas has presented a challenge to excavate deep into the earth, and it is increasing the required area for the provision of public services. The function...

This study aims to investigate the transformative potential of incorporating ChatGPT into academic research while addressing consequential challenges and ethical concerns. The chatbot, as a large language model (LLM), allows users to interact with it, providing advantages in the academic research context. The benefits of real-time interaction, info...

The COVID-19 lockdown resulted in a reduction in human activities, lowering pollution levels in these rivers. Nevertheless, limited research can be found on the impact of COVID-19 on river water quality in Sri Lankan rivers. Therefore, this research was carried out to investigate the water quality index (WQI) of four major rivers (Mahaweli, Nilwala...

The development of hydraulic structures has impacted the river discharge and sediment transportation, thus highlighting the river planform changes. Among 103 river catchments in Sri Lanka, the Mahaweli River is the longest river with the largest basin. Many development projects over the years diversely impacted the changes in river masks. However,...

The Bednja River in Croatia and its tributaries are essential components of the hydrographic network in the region, impacting the lives and livelihoods of approximately 60,000 people residing there. By accurately forecasting water flow using machine learning models, it is possible to improve early warning systems for floods and flash floods. In thi...

Granular filter media are integral to sustainable drainage systems (SuDS) for their efficiency in removing pollutants from urban runoff. This study focuses on understanding the filtration processes within these media by combining a pilot experimental study with a modeling approach. The experimental study involved characterizing the physical and hyd...

The concentrations of cadmium, copper, lead, zinc, nickel, and chromium in samples of sediment, water, and Typha angustifolia plants in the stream of the Drenica River were determined to assess the level of pollution. According to sediment analysis results from seven locations, the concentrations of Cu, Ni, Zn, and Cr exceeded the permitted limits...

Socioeconomic developments, ineffective drainage systems, and insufficient river control, all contribute to significant loss of property and life due to the constant threat of floods. Therefore, controlling flood threats across Rel River, Dhanera, Gujarat has become even more crucial due to floods causing strain throughout the area during monsoon s...

Water quality assessment and prediction play crucial roles in ensuring the sustainability and safety of freshwater resources. This study aims to enhance water quality assessment and prediction by integrating advanced machine learning models with XAI techniques. Traditional methods, such as the water quality index, often require extensive data colle...

The cascaded adaptive neuro-fuzzy inference system (ANFIS) is widely employed for modeling and controlling nonlinear systems. It combines human experience and knowledge with neural networks' learning capability and fuzzy systems' pattern extraction ability. This integration enables the development of effective models across diverse application doma...

Conventional machine learning techniques in diagnosing cardiovascular disease have a limitation owing to the lack of interpretability of models. This study utilised an explainable machine learning approach to predict the likelihood of having CVD. Four machine learning models were employed for CVD diagnosis: Decision Tree (DT), K-Nearest Neighbor (K...

Sewer systems are usually built with a self-cleaning system that keeps the bottom of the channel free of sediment to lessen the effects of the constant buildup of sediment particles. Because of this, it is important to accurately predict the particle Froude number (Fr) when making sewer systems. For the prediction of Fr, five different sets of inpu...

Freshwater salinization and alkalinisation strongly depend on human and natural factors. We used an explainable machine learning approach to investigate the impact of natural and human factors on the salinity and alkalinity in rivers in the United States. The model achieved coefficient of determination of 0.89 for salinity predictions and0.92 for a...

This study is the first attempt to use explainable machine learning (ML) to investigate the factors influencing physical development and the athlete's performance in the Karakalpakstan and Khwarazm regions of the Republic of Uzbekistan. Three physical fitness tests (Dribbling Shuttle, Goal Accuracy, and Yo-Yo intermittent), anthro-pometrics, and he...

This study reviews recent advancements in food science and technology, analyzing their impact on the development of intelligent food packaging within the complex food supply chain. Modern food technology has brought about intelligent food packaging, which includes sensors, indicators, data carriers, and artificial intelligence. This innovative pack...

Lessons learned from previous flood disasters are significant in mitigating future flood damages. Therefore, this study aims at understanding the disastrous damage caused by the 2017 flood that occurred in southern Sri Lanka. Most of the recent studies related to natural disasters have incorporated geospatial analysis to produce more convincing map...

Forecasting the time-dependent scour depth (dst) is very important for the protection of bridge structures. Since scour is the result of a complicated interaction between structure, sediment, and flow velocity, empirical equations cannot guarantee an advanced accuracy, although they would preserve the merit of being straightforward and physically i...

In river research, forecasting flow velocity accurately in vegetated channels is a significant challenge. The forecasting performance of various independent and hybrid machine learning (ML) models are thus quantified for the first time in this work. Utilizing flow velocity measurements in both natural and laboratory flume experiments, we assess the...

Ahmedabad, a city in India, experiences varying climatic patterns and is prone to extreme rainfall and relies on established intensity-duration-frequency (IDF) relationships for critical infrastructure planning and flood management. While the city has existing IDF relationships, these curves were established some time ago and still lack well-establ...

Soil erosion is a significant environmental issue in most mountainous areas and is further exacerbated due to ongoing climatic changes and anthropogenic activities. Soil erosion not only triggers natural disasters like landslides but also degrades the fertile topsoil layers. Therefore, modeling and evaluation of soil erosion in mountainous areas an...

Geopolymer concrete is a sustainable and eco-friendly substitute for traditional OPC (Ordinary Portland Cement) based concrete, as it reduces greenhouse gas emissions. With various supplementary cementitious materials, the compressive strength of geopolymer concrete should be accurately predicted. Recent studies have applied deep learning technique...

Rice is a crucial crop in Sri Lanka, influencing both its agricultural and economic landscapes. This study delves into the complex interplay between economic indicators and rice production, aiming to uncover correlations and build prediction models using machine learning techniques. The dataset, spanning from 1960 to 2020, includes key economic var...

A comprehensive study was conducted to provide research clarifications and evaluations of measures aimed at controlling stormwater runoff from roads and highways. The study specifically focuses on sustainable strategies, particularly permeable pavement systems (PPS), as a solution for stormwater management within the framework of sustainable draina...

The article provides a comprehensive review of the use of the Internet of Things (IoT) in agriculture, along with its advantages and disadvantages. However, it's important to recognize that IoT holds immense potential for generating new ideas that could drive innovations in modern agriculture and address several challenges faced by farmers today. A...

In a recent paper by Sajindra et al [1], the soil nutrient levels, specifically nitrogen, phosphorus, and potassium, in organic cabbage cultivation were predicted using a deep learning model. This model was designed with a total of four hidden layers, excluding the input and output layers, with each hidden layer meticulously crafted to contain ten...

Measurement inaccuracies and the absence of precise parameters value in conceptual and analytical models pose challenges in simulating the rainfall-runoff modeling (RRM). Accurate prediction of water resources, especially in water scarcity conditions, plays a distinctive and pivotal role in decision-making within water resource management. The sign...

Chronic Kidney Disease (CKD) is increasingly recognised as a major health concern due to its rising prevalence. The average survival period without functioning kidneys is typically limited to approximately 18 days, creating a significant need for kidney transplants and dialysis. Early detection of CKD is crucial, and machine learning methods have p...

Machine learning techniques have garnered considerable attention in modern technologies due to their promising outcomes across various domains. This paper presents the comprehensive methodology of an optimized and efficient forecasting approach for Particulate Matter 10, specifically tailored to predefined locations. The execution of a comparative...

Sediment deposition has a substantial effect on the hydraulic capacity of channels in urban drainage and sewer systems. In this sense, the self-cleaning concept has been extensively used in the construction of urban drainage and sewer systems. In this regard, the design of the sewer system heavily depends on the accurate forecasting of the particle...

This study evaluates the rainfall erosivity (RE) and erosivity density (ED) over the Kelani River basin, Sri Lanka for a period of 31 years (1990-2020). The river basin is well known for its annual floods during the southwestern monsoon season and severe erosion including landslides can be observed. The catchment was analyzed for its RE using the W...

An effective approach to identifying the size and intensity of land transitions is vital for land use and management decisions. This study used a transfer matrix and intensity analysis to quantify the land conversion from 1995 to 2015 in the Aral Sea Basin (ASB). The analysis is based on annual land cover data from the European Space Agency Climate...

Climate change stands as one of the most pressing challenges confronting global ecosystems and human livelihoods. The agriculture sector of Anuradhapura district, Sri Lanka, well renowned for its pivotal role in the nation's food production, faces an increasing threat from the changing climate. This study aims to incorporate the indicator system me...

Soil temperatures at both surface and various depths are important in changing environments to understand the biological, chemical, and physical properties of soil. This is essential in reaching food sustainability. However, most of the developing regions across the globe face difficulty in establishing solid data measurements and records due to po...

Improper disposal of paddy stalks residue via open burning or soil incorporation creates contamination hazards by releasing particulate matter, residue ash, and breakdown chemicals into the environment. This study aimed to repurpose these stalks by converting them into activated carbon. Box Behnken Design BBD within the response surface methodology...

Climate change is a serious global issue causing more extreme weather patterns, resulting in more frequent and severe events like urban flooding. This review explores the connection between climate change and urban flooding, offering statistical, scientific, and advanced perspectives. Analyses of precipitation patterns show clear changes, establish...

This paper presents the application of regression trees as a versatile alternative to other machine learning and statistical modelling techniques to forecast the power generation at five renewable power plants: one large hy-dropower plant, two mini hydropower plants, and two wind farms in Sri Lanka. The prediction models for each power station were...

Rainfall Intensity Duration Frequency (IDF) curves can be identified as a major role in the planning of urban drainage infrastructure. Sri Lanka, which is an island surrounded by the Indian Ocean, is frequently exposed to various climatic alterations. Sri Lanka has specific region-wise IDF relationships for the entire country, however, these IDF cu...

This data article presents information on the measurement of Indirect Tensile Stiffness Modulus of laboratory and field asphalt mixtures. The asphalt mixes are composed of three distinct binders that were categorised by their penetration grade (40/55-TLA, 60/75-TLA, and 60/70-MB) and aggregates (limestone, sharp sand, and filler). The asphalt mixtu...

Mangroves are amongst the richest ecosystems in the world providing valuable goods and services to millions of people while enhancing the resilience of coastal communities against climate change induced hazards, especially island nations. However, these mangroves are severely affected by many anthropogenic activities. Therefore, understanding the s...

Groundwater potential investigation is one of the most significant and crucial aspects in arid and semi-arid regions like Marathwada. Marathwada is often susceptible to water scarcity and drought due to monsoon variability. Therefore, it is indispensable to identify groundwater potential zones (GWPZs) to meet human needs. The present research used...

Turmeric cultivation primarily thrives in India, with significant presence in Bangladesh, Thailand, Cambodia, China, Indonesia, Philippines, and Malaysia. India leads globally in both area (0.19 Mha) and production (0.844 MT) of turmeric. Despite this, there's a recognized gap in research regarding the combined effects of mulching and drip fertigat...

Tomatoes are essential in both agriculture and culinary spheres, demanding rigorous quality assessment. It is highly advantageous to discern the maturity level and the time range post-harvesting of tomatoes in the market through visual analysis of their images. This research endeavors to forecast tomato quality by accurately determining the maturit...

This study presents the first attempt in Sri Lanka to generate a forest fire risk map covering the entire country using a GIS-based forest fire index (FFI) model. The model utilized seven parameters: land use, temperature, slope, proximity to roads and settlements, elevation, and aspect. All these parameters were derived using GIS techniques with A...

Cabbage (Brassica oleracea) is a green cruciferous vegetable. Major nutrients (nitrogen, phosphorus, and potassium) are frequently applied to the soil due to low fertility levels. However, optimizing required fertilizer levels are extremely important to avoid any overuse and underuse. Therefore, it is important to develop a comprehensive methodolog...

Streamflow forecasting is essential for effective water resource planning and early warning systems. Streamflow and related parameters are often characterized by uncertainties and complex behaviors. Recent studies have turned to machine learning (ML) to predict streamflow. However, many of these methods have overlooked the interpretability and caus...