Search Results (34)

Flooding is the most frequent natural hazard that accompanies hardships for millions of civilians and substantial economic losses. In Sri Lanka, fluvial floods cause the highest damage to lives and properties. Ratnapura, which is in the Kalu River Basin, is the area most vulnerable to frequent flood events in Sri Lanka due to inherent weather patterns and its geographical location. However, flood-related studies conducted based on the Kalu River Basin and its most vulnerable cities are given minimal attention by researchers. Therefore, it is crucial to develop a robust and reliable dynamic flood forecasting system to issue accurate and timely early flood warnings to vulnerable victims. Modeling the water level at the initial stage and then classifying the results of this into pre-defined flood risk levels facilitates more accurate forecasts for upcoming susceptibilities, since direct flood classification often produces less accurate predictions due to the heavily imbalanced nature of the data. Thus, this study introduces a novel hybrid model that combines a deep leaning technique with a traditional Linear Regression model to first forecast water levels and then detect rare but destructive flood events (i.e., major and critical floods) with high accuracy, from 1 to 3 days ahead. Initially, the water level of the Kalu River at Ratnapura was forecasted 1 to 3 days ahead by employing a Vanilla Bi-LSTM model. Similarly to water level modeling, rainfall at the same location was forecasted 1 to 3 days ahead by applying another Bi-LSTM model. To further improve the forecasting accuracy of the water level, the forecasted water level at day t was combined with the forecasted rainfall for the same day by applying a Time Series Regression model, thereby resulting in a hybrid model. This improvement is imperative mainly because the water level forecasts obtained for a longer lead time may change with the real-time appearance of heavy rainfall. Nevertheless, this important phenomenon has often been neglected in past studies related to modeling water levels. The performances of the models were compared by examining their ability to accurately forecast flood risks, especially at critical levels. The combined model with Bi-LSTM and Time Series Regression outperformed the single Vanilla Bi-LSTM model by forecasting actionable flood events (minor and critical) occurring in the testing period with accuracies of 80%, 80%, and 100% for 1- to 3-day-ahead forecasting, respectively. Moreover, overall, the results evidenced lower RMSE and MAE values (<0.4 m MSL) for three-days-ahead water level forecasts. Therefore, this enhanced approach enables more trustworthy, impact-based flood forecasting for the Rathnapura area in the Kalu River Basin. The same modeling approach could be applied to obtain flood risk levels caused by rivers across the globe. Full article

The annual increase in the world’s population significantly contributes to recent climate change and variability. Therefore, researchers, engineers, and professionals in all fields must integrate sustainability criteria into their decision-making. These criteria aim to minimize the environmental, social, economic, and energy impacts of human activities and industrial processes, helping mitigate climate change. This research focuses on developing scalable technology for the comprehensive use of avocados, adhering to sustainability principles. This work presents the modeling, simulation, and the WEP (Water-Energy-Product) technical evaluation of the process for obtaining bio-oil, chlorophyll, and biopesticide from the Creole-Antillean avocado. For this, the extractive-based biorefinery data related to water, energy, and products are taken from the material balance based on experimental results and process simulation. Then, eight process parameters are calculated, and eleven technical indicators are determined. Later, the extreme technical limitations for every indicator are demarcated, and an evaluation of the performance of the indicators is carried out. Results showed that the process has a high execution in aspects such as fractional water cost (TCF) and energy cost (TCE), as well as solvent reuse during extraction processes (SRI) and production yield, noting that the mentioned indicators are above 80%. In contrast, the metrics related to water management (FWC) and specific energy (ESI) showed the lowest performance. These discoveries support the use of optimization techniques like mass process integration. The energy-related indicators reveal that the process presents both benefits and drawbacks. One of the drawbacks is the energy source due to the high demand for electrical energy in the process, compared to natural gas. The specific energy intensity indicator (ESI) showed an intermediate performance (74%), indicating that the process consumes high energy. This indicator enables us to highlight that we can find energy aspects that require further study; for this reason, it is suitable to say that there is potential to enhance the energy efficiency of the process by applying energy integration methods. Full article

With the recent acceleration in urbanisation and industrialisation, industrial pollution has severely impacted inland water bodies and ecosystem services globally, causing significant restrains to freshwater availability and myriad damages to benthic species. The Kelani River Basin in Sri Lanka, covering only ~3.6% of the land but hosting over a quarter of its population and many industrial zones, is identified as the most polluted watershed in the country. This study used unsupervised learning (UL) and an indexing approach to identify potential industrial pollutant sources along the Kelani River. The UL results were compared with those obtained from a novel Industrial Pollution Index (IPI). Three latent variables related to industrial pollution were identified via Factor Analysis of monthly water quality data from 17 monitoring stations from 2016 to 2020. The developed IPI was validated using a Long Short-Term Memory Artificial Neural Network model (NSE = 0.98, RMSE = 0.81), identifying Cd, Zn, and Fe as the primary parameters influencing river pollution status. The UL method identified five stations with elevated concentrations for the developed latent variables, and the IPI confirmed four of them. Based on the findings from both methods, the industrial zones along the Kelani River have emerged as a likely source of pollution in the river’s water. The results suggest that the proposed method effectively identifies industrial pollution sources, offering a scalable methodology for other river basins to ensure sustainable water resource management. Full article

The Baoshan Cu-Pb-Zn deposit is situated at the intersection of the Qin-Hang Cu polymetallic and Nanling W-Sn polymetallic metallogenic belts. The age, lithology, petrogenesis, and tectonic setting of granodiorite porphyry within the deposit remain subjects of debate. Additionally, there is a lack of comparative studies with the W-Sn-related granites in the region. This study conducted whole-rock major and trace element analysis, Sr-Nd isotope analysis, and zircon U-Pb dating on the Baoshan granodiorite porphyry. The zircon U-Pb age of the granodiorite porphyry is 162 ± 1 Ma. The whole-rock SiO₂ and K₂O contents range from 65.87 to 68.21 wt.% and 3.42 to 5.62 wt.%, respectively, indicating that the granodiorite porphyry belongs to high-potassium calc-alkaline I-type granite. The granodiorite porphyry is characterized by enrichment in LREE and depletion in HREE (LREE/HREE ratio = 6.2–21.2). The samples of granodiorite porphyry generally exhibit weak negative Eu anomalies or no Eu anomalies (δEu = 0.62–1.04, mean = 0.82). The (⁸⁷Sr/⁸⁶Sr)_i and ε_Nd(t) values are 0.707717–0.709506 and −7.54 to −4.87, respectively. The whole-rock geochemical composition and Sr-Nd isotopic values indicate that the magma originated from the partial melting of the Mesoproterozoic ancient crust and Neoproterozoic mafic juvenile lower crust, with the addition of high oxygen fugacity and water-rich lithospheric mantle melts. The source of the granodiorite porphyry in the Baoshan deposit is significantly different from the crust-derived metapelite source of the W-Sn-related granite in the area, indicating that different magma sources might be the main reason for the co-spatial and nearly contemporaneous development of Cu-Pb-Zn and W-Sn mineralization in the southern Hunan region. Full article

In the context of global warming, the acceleration of the water cycle increases the risk of meteorological drought (MD) and hydrological drought (HD) in the arid region of Northwest China. The Manas River Basin is a typical agricultural oasis and the largest oasis farming area in Xinjiang, Northwest China. Droughts in this basin have significant implications for both agricultural production and the livelihoods of inhabitants. To evaluate the MD and HD and provide information for drought relief in the MRB, the standardized precipitation evapotranspiration index (SPEI) and standardized runoff index (SRI) were calculated using long-term rainfall and runoff data. Subsequently, combined with ArcGIS 10.3 software and the trend analysis method, the SPEI and SRI characteristics were evaluated at different time scales (1-, 3-, 6-, and 12-month). There were three main findings. First, both MD and HD were alleviated, with significantly more HD alleviation. MDs in spring and autumn exhibited a trend of aggravation. The SRIs in summer, autumn, and winter increased significantly at a confidence level of p < 0.01, with an insignificant decline in spring. In the 2010s, the frequency of light drought of MD was stable at 10% to 20%, while severe and extreme droughts increased. The frequency of HDs has decreased since the 1990s. Second, on annual and seasonal scales, MDs occurred mainly as light and moderate droughts. The highest frequency of MD was 24% of moderate droughts in winter. Spatially, the northern region of the MRB was characterized by more frequent light and extreme droughts. Third, runoff in the Manas River Basin increased significantly during the 1990s, which may have been related to the acceleration of glacial retreat in the Tianshan Mountains. This study can effectively reveal the changes in meteorological and hydrological drought in NWC and provide the basis for risk decision-making and management for watershed managers. Full article

This study aims to determine the influence of the fiscal, monetary, and public policy environment in Sri Lanka and its impact on sustainable development before and after COVID-19. This study used the document analysis qualitative research method to obtain and analyse fiscal, monetary, and public policy data. It assigned and measured the 17 United Nations Sustainable Development Goals (UN SDGs) values and trends. The goals were clustered into social, environmental, and sustainability-related intellectual capital to measure their dimensional capital status values and trends. Despite the economic crisis, Sri Lanka has moderately progressed in sustainable development, with most improvements in social capital. The environmental and sustainability-related intellectual capital dimensions follow. The 17 SDGs were advancing at various levels. Two were on track (Goal 4: Quality education and Goal 9: Industry, innovation, and infrastructure). Five moderately improved goals (Goal 2: Zero hunger, Goal 3: Good health and well-being, Goal 6: Clean water and sanitation, Goal 12: Responsible consumption and production, and Goal 13: Climate action). Seven were stagnant (Goal 5: Gender equality, Goal 7: Affordable clean energy, Goal 8: Decent work and economic growth, Goal 11: Sustainable cities and communities, Goal 14: Life below water, Goal 16: Peace, justice, and strong institutions, and Goal 17: Partnership for the goals). Two showed a decrease (Goal 1: Poverty and Goal 15: Life on land). No data are reported for Goal 10 (Reduce inequalities). Fiscal and monetary policies were overly focussed on economic repair and reconstruction. Public policy has nevertheless contributed to sustainable development. This is the first study to examine the multidimensional policy environment and its impact on sustainable development in Sri Lanka. Full article

This study investigates the factors that determine disclosure of the Sustainable Development Goals (SDGs) of companies listed on the Indonesian stock exchange in the period from 2017 to 2021. The research was conducted through an exploratory study using panel data (from each company’s websites), parametric correlations, and regression models. The findings show a 60% increase in the disclosure of the SDGs in sustainability reports from 2017 to 2021, with the highest level of disclosure achieved for SDG 3 (Health and well-being) and SDG 4 (Quality education). The lowest disclosure was for SDG 14 (Life below water). The study demonstrates statistically that governance factors such as the presence of women on the board of directors and the number of board meetings positively affect SDG disclosure in listed companies in Indonesia. Factors related to companies’ profitability, environmental sensitivity, and board size do not, however, influence SDG disclosure. These findings have implications for academics, stakeholders, practitioners, and governments who are strategically positioned to achieve the SDG agenda in 2030. This study has limitations in that the data were drawn only from companies in the SRI-KEHATI Index. Full article

The impact of global climate change is a challenge to the sustainability of many ecosystems, including soil systems. However, the performance of soil properties under future climate was rarely assessed. Therefore, this study was carried out to evaluate selected soil processes under climate change using an agri-environmental modeling approach to Sri Lanka. The Agricultural Production Systems Simulator (APSIM) model was used to simulate soil and plant-related processes using recent past (1990–2019) and future (2041–2070) climates. Future climate data were obtained for a regional climate model (RCM) under representative concentrations pathway 4.5 scenarios. Rainfalls are going to be decreased in all the tested locations under future climate scenarios while the maximum temperature showcased rises. According to simulated results, the average yield reduction under climate change was 7.4%. The simulated nitrogen content in the storage organs of paddy declined in the locations (by 6.4–25.5%) as a reason for climate change. In general, extractable soil water relative to the permanent wilting point (total available water), infiltration, and biomass carbon lost to the atmosphere decreased while soil temperature increased in the future climate. This modeling approach provides a primary-level prediction of soil dynamics under climate change, which needs to be tested using fieldwork. Full article

The water supply system plays a major role in the community. The water source is carefully selected based on quality, quantity, and reliability. The quality of water at its sources is continuously deteriorating due to various anthropogenic activities and is a major concern to public health as well. The Kalu River is one of the major water resources in Sri Lanka that supplies potable water to the Kalutara district (a highly populated area) and Rathnapura district. But, there has been no significant research or investigation to examine anthropogenic activities in the river. Due to this, it is difficult to find any proper study related to the overall water quality in the Kalu River. Therefore, this study covers a crucial part related to the water quality of the Kalu River. The spatiotemporal variation of river water quality is highly important not only to processing any treatment activities but also to implementing policy decisions. In this context, water quality management is a global concern as countries strive to meet the United Nations Sustainable Development Goal 6, which aims to ensure the availability and sustainable management of water and sanitation for all. Poor water quality can have severe consequences on human health, ecosystems, and economies. Contaminated water sources pose risks of waterborne diseases, reduced agricultural productivity, and ecological imbalances. Hence, assessing and improving water quality is crucial for achieving sustainable development worldwide. Therefore, this paper presents a comprehensive analysis of spatiotemporal analysis of the water quality of the Kalu River using the water quality data of eight locations for 6 years from 2017 to 2023. Nine water quality parameters, including the pH, electrical conductivity, temperature, chemical oxygen demand, biological oxygen demand, total nitrate, total phosphate, total sulfate, total chlorine, and hardness, were used to develop a simple equation to investigate the water quality index (WQI) of the river. Higher WQI values were not recorded near the famous Kalutara Bridge throughout the years, even though the area is highly urbanized and toured due to religious importance. Overall, the water quality of the river can be considered acceptable based on the results of the WQI. The country lockdowns due to COVID-19 might have impacted the results in 2020; this can be clearly seen with the variation of the annual WQI average, as it clearly indicates decreased levels of the WQI in the years 2020 and 2021, and again, the rise of the WQI level in 2022, as this time period corresponds to the lockdown season and relaxation of the lockdown season in the country. Somehow, for most cases in the Kalu River, the WQI level is well below 25, which can be considered acceptable and suitable for human purposes. But, it may need some attention towards the areas to find possible reasons that are not in the range. Nevertheless, the results suggest the importance of continuous water quality monitoring in the Kalu River. Full article

The energy in agricultural systems is two-fold: transformation and utilization. The assessment and proper use of energy in agricultural systems is important to achieve economic benefits and overall sustainability. Therefore, this study was conducted to evaluate the energy balance of crop and livestock production, net energy ratio (NER), and water use efficiency (WUE) of crops of a selected farm in Sri Lanka using the life cycle assessment (LCA) approach. In order to assess the diversification, 18 crops and 5 livestock types were used. The data were obtained from farm records, personal contacts, and previously published literature. Accordingly, the energy balance in crop production and livestock production was −316.87 GJ ha⁻¹ Year⁻¹ and 758.73 GJ Year⁻¹, respectively. The energy related WUE of crop production was 31.35 MJ m⁻³. The total energy balance of the farm was 736.2 GJ Year⁻¹. The results show a negative energy balance in crop production indicating an efficient production system, while a comparatively higher energy loss was shown from the livestock sector. The procedure followed in this study can be used to assess the energy balance of diversified agricultural systems, which is important for agricultural sustainability. This can be further developed to assess the carbon footprint in agricultural systems. Full article

This research aimed to apply the geospatial techniques and Analytical Hierarchy Process (AHP) approach to find vulnerable areas in terms of flooding in the Neluwa area, Sri Lanka. The study incorporated nine relevant criteria for the vulnerability classification under three sub-criteria; the built environment, physical environment, and socio-economic environment. Under the built environment, road networks and buildings were chosen as sub-criteria. The Normalized Difference Vegetation Index (NDVI), slope, elevation, water bodies, and stream density were taken as physical criteria. Land use and population density were considered as socio-economic criteria. All the criteria are set correctly in raster data, and their contents were well adduced. The study consisted of the use of different levels of criteria and combinations of different processes. The analytical results reveal that 14.24% and 30.24% of the total area are at a very-high risk and high risk for flooding, respectively. Only 5.17% of the land was classified as a risk-free area. Eastern, central, and western divisions of the study area are highly vulnerable to floods due to their low slopes. Based on the produced maps, the spatial extents and levels of risk were systematically identified. Data obtained through qualitative judgments related to the field were validated based on the approach used. The potential of this approach is effective in assessing the spatial vulnerability of these flood-affected areas. Using such criteria and a model-based approach will be constructive in identifying different flood scenarios and in providing a remunerative guideline for potential anticipatory measures and better land-based planning in the area. Full article

Kalametiya Lagoon, a highly threatened Sri Lankan wetland, has undergone drastic hydrological changes in recent decades, due to an upstream irrigation project. These changes led to the invasion of the lagoon water by monospecific Sonneratia caseolaris mangrove stands and Typha angustifolia reedbeds. As Kalametiya has been a nationally recognized bird sanctuary since 1984, this invasion is expected to have brought significant changes upon local avifauna. Therefore, this study aimed at determining the lagoon’s current bird diversity and distribution in relation with habitat types and environmental variables. Thirty-seven point-count stations were studied, between January and April 2022. Seventy-nine bird species, including four endemic and ten nationally threatened species, were encountered during the study period. Invertebrate feeders and polyphages were the richest and most diverse guilds. Bird communities were also found richer and more diverse in T. angustifolia reedbeds than in S. caseolaris mangroves. As feeding guild composition was significantly influenced by several environmental variables (i.e., water nitrate content, water TDS, water pH, soil pH), guilds could have great potential as bioindicators of the ecosystem if further studies are done to explore these relationships. Considering the important bird diversity found in the new habitats, this research brings additional proof that a management aiming at restoring the lagoon to its past state would bring significant changes to its avifaunal community. These changes could, in the future, be more precisely defined by a thorough comparison with past inventories of the lagoon’s bird community. Full article

In a paradigm shift in plastic wastes due to the COVID-19 pandemic, wetlands such as mangroves are threatened by a new form of pollution, plastics, on top of the eutrophication of estuarine waters due to nitrogen and phosphorus wastes/effluents that lead to cyanobacterial proliferation. Both plastic and nutrient pollution lead to prosperity of cyanotoxin-producing cyanobacteria that flourish in both and disperse leading to the detriment of fauna and flora in the mangrove ecosystem due to resulting toxicities. Although cyanotoxins are still a relatively poorly studied phenomenon in mangroves, their presence does create a focus of attention due to biofilm formation and the resultant flotation and sinking properties that are linked to cyanobacterial mats on plastic debris. Sri Lanka, being the first country in the world to conserve all its mangrove wetlands, does have a responsibility to prevent the invasion of plastics to this protected ecosystem, and binding with the Ramsar Convention, precluding plastic waste and their concomitant footprint, is a task at hand to the relative authorities. The path ahead mandates that we study the properties of plastics for cyanobacterial proliferation, biofilm formation, the fates of such plastics (flotation, dispersal and sinking), the cyanotoxin production changes that are attributed—or linked—to plastic pollution and the resultant impacts on mangrove ecosystems. Cyanotoxins are long-lived, and it is paramount that we find the necessary mechanisms to eliminate or curtail their production in mangrove ecosystems while establishing surveillance and monitoring of both the producers and the harmful agents. Cyanobacteria although vehicles for nitrogen fixation and replenishing of nutrients to an N-depleted ecosystem such as the mangroves, could lead to enhancements in cyanotoxins production. However, this phenomenon remains ambiguous and poorly studied in applied phycology in relation to mangroves. “New normal” plastics are lodged mostly on the surfaces of bark, prop roots, and pneumatophores, which are the localities where the highest level of new nitrogen is fixed, and this may lead to the proliferation of N-fixing, cyanotoxin-producing cyanobacteria, which may have repercussions on both flora and fauna of mangroves. Therefore, it is crucial that we monitor plastic pollution and find mechanisms for sanitizing plastics-imprinted mangroves to lessen the harmful footprint resulting from plastic overload. Full article

Rainfall is one of the dominating climatic parameters that affect water availability. Trend analysis is of paramount significance to understand the behavior of hydrological and climatic variables over a long timescale. The main aim of the present study was to identify trends and analyze existing linkages between rainfall and streamflow in the Nilwala River Basin (NRB) of Southern Sri Lanka. An investigation of the trends, detection of change points and streamflow alteration, and linkage between rainfall and streamflow were carried out using the Mann–Kendall test, Sen’s slope test, Pettitt’s test, indicators of hydrological alteration (IHA), and Pearson’s correlation test. Selected rainfall-related extreme climatic indices, namely, CDD, CWD, PRCPTOT, R25, and Rx5, were calculated using the RClimdex software. Trend analysis of rainfall data and extreme rainfall indices demonstrated few statistically significant trends at the monthly, seasonal, and annual scales, while streamflow data showed non-significant trends, except for December. Pettitt’s test showed that Dampahala had a higher number of statistically significant change points among the six rainfall stations. The Pearson coefficient correlation showed a strong-to–very-strong positive relationship between rainfall and streamflow. Generally, both rainfall and streamflow showed non-significant trend patterns in the NRB, suggesting that rainfall had a higher impact on streamflow patterns in the basin. The historical trends of extreme climatic indices suggested that the NRB did not experience extreme climates. The results of the present study will provide valuable information for water resource planning, flood and disaster mitigation, agricultural operations planning, and hydropower generation in the NRB. Full article

Due to the increase in population, growing urbanization, and higher demands for processed and unprocessed foods, resources related to food production have become scarce. Water and land can be considered as the primary resources to determine the crop production potential of a country. Ideally, countries that lack water and land resources can import these in virtual form. Sri Lanka is a country rich in water resources that faced bankruptcy recently. This study analyzes and explores the potential for use of land–water resources in Sri Lanka. A comprehensive framework is generated to identify the virtual land–water trade by considering ten major imports and nine major export crops in Sri Lanka. Consequently, the top ten imports/exports and top ten import/export trade partners are identified. The analysis reveals that Sri Lanka is a heavily import-dominant country, having seven times higher imports compared to exports. The country imports wheat, which is 82% of its import crops, and the same crop is the largest export (85% of crop export). Compared to its trade partners, Sri Lanka has sufficient water resources, but availability of arable land is limited. Banana is the largest export of the country, which involves higher embedded water and less land, matching the resource availability to Sri Lanka, whereas the trade partners are expected to continue importing the crop due to their water and land stress conditions. Finalization of the long-awaited agriculture policy of the country is strongly recommended. Full article