Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2023
Forfattere
Chathura Palliyaguru Vindhya Basnayake Randika K. Makumbura Miyuru Gunathilake Nitin Muttil Eranga M. Wimalasiri Upaka RathnayakeSammendrag
Soil degradation is a serious environmental issue in many regions of the world, and Sri Lanka is not an exception. Maha Oya River Basin (MORB) is one of the major river basins in tropical Sri Lanka, which suffers from regular soil erosion and degradation. The current study was designed to estimate the soil erosion associated with land use changes of the MORB. The Revised Universal Soil Loss Equation (RUSLE) was used in calculating the annual soil erosion rates, while the Geographic Information System (GIS) was used in mapping the spatial variations of the soil erosion hazard over a 30-year period. Thereafter, soil erosion hotspots in the MORB were also identified. The results of this study revealed that the mean average soil loss from the MORB has substantially increased from 2.81 t ha−1 yr−1 in 1989 to 3.21 t ha−1 yr−1 in 2021, which is an increment of about 14.23%. An extremely critical soil erosion-prone locations (average annual soil loss > 60 t ha−1 yr−1) map of the MORB was developed for the year 2021. The severity classes revealed that approximately 4.61% and 6.11% of the study area were in high to extremely high erosion hazard classes in 1989 and 2021, respectively. Based on the results, it was found that the extreme soil erosion occurs when forests and vegetation land are converted into agricultural and bare land/farmland. The spatial analysis further reveals that erosion-prone soil types, steep slope areas, and reduced forest/vegetation cover in hilly mountain areas contributed to the high soil erosion risk (16.56 to 91.01 t ha−1 yr−1) of the MORB. These high soil erosional areas should be prioritized according to the severity classes, and appropriate land use/land cover (LU/LC) management and water conservation practices should be implemented as recommended by this study to restore degraded lands.
Sammendrag
This study assessed the meteorological and hydrological droughts and their relationship over 30 years from 1985 to 2015 in the largest river basin (Mahaweli River Basin (MRB)) in Sri Lanka. Data from 14 rainfall, 5 temperature, and 5 streamflow stations in and near the MRB were used in the present study. Universal drought indices including Standardized Precipitation Index (SPI) and Standardized Precipitation–Evapotranspiration Index (SPEI) were used to assess meteorological droughts. The Standardized Streamflow Index (SSI) was used in investigating hydrological droughts. Correlations between meteorological and hydrological droughts were obtained, annual variations were observed (in terms of SPI, SPEI, and SSI), and the spatial distributions of selected drought events were analyzed. Our results revealed that the highest correlation was found in long-term dry conditions in the wet zone. In addition, some negative correlations found showed the opposite behavior of correlations. Furthermore, in annual variations of droughts, extreme droughts were recorded in the dry zone as maximum values, while results were more prominent in the wet zone. In addition, the spatial distribution performed using SPI, SPEI, and SSI showed an extremely dry condition in 2004. Our findings are beneficial for policymaking and for the decision-makers in assessing meteorological and hydrological drought risks in the future.
Forfattere
Jayanga T. Samarasinghe Charuni P. Wickramarachchi Randika K. Makumbura Pasindu Meddage Miyuru Gunathilake Nitin Muttil Upaka RathnayakeSammendrag
Climate change has had a significant impact on the tourism industry in many countries, leading to changes in policies and adaptations to attract more visitors. However, there are few studies on the effects of climate change on Sri Lanka’s tourism industry and income, despite its importance as a destination for tourists. A study was conducted to analyze the holiday climate index (HCI) for Sri Lanka’s urban and beach destinations to address this gap. The analysis covered historical years (2010–2018) and forecasted climatic scenarios (2021–2050 and 2071–2100), and the results were presented as colored maps to highlight the importance of HCI scores. Visual analysis showed some correlation between HCI scores and tourist arrivals, but the result of the overall correlation analysis was not significant. However, a country-specific correlation analysis revealed interesting findings, indicating that the changing climate can be considered among other factors that impact tourist arrivals. The research proposes that authorities assess the outcomes of the study and conduct further research to develop adaptive plans for Sri Lanka’s future tourism industry. The study also investigated potential scenarios for beach and urban destinations under two climate scenarios (RCP 4.5 and RCP 8.5) for the near and far future, presenting the findings to tourism industry stakeholders for any necessary policy changes. As Sri Lanka expects more Chinese visitors in the future due to ongoing development projects, this study could be valuable for policymakers and industry stakeholders when adapting to changing climate and future tourist behavior. While more research is needed to fully understand the effects of climate change on Sri Lanka’s tourism industry, this study serves as a starting point for future investigations.
Forfattere
Ruchiru D. Herath Uttam Pawar Dushyantha M. Aththanayake Kushan D. Siriwardhana Dimantha I. Jayaneththi Chatura Palliyaguru Miyuru Gunathilake Upaka RathnayakeSammendrag
Climate change, urbanization, and many anthropogenic activities have intensified the floods in today’s world. However, poor attention was given to mitigation strategies for floods in the developing world due to funding and technical limitations. Developing flood inundation maps from historical flood records would be an important task in mitigating any future flood damages. Therefore, this study presents the predictive capability of the Rainfall-Runoff-Inundation (RRI) model, a 2D coupled hydrology-inundation model, and to build flood inundation maps utilizing available ground observation and satellite remote sensing data for Kalu River, Sri Lanka. Despite the lack of studies in predicting flood levels, Kalu River is an annually flooded river basin in Sri Lanka. The comparative results between ground-based rainfall (GBR) measurement and satellite rainfall products (SRPs) from the IMERG satellite have shown that SRPs underestimate peak discharges compared to GBR data. The accuracy and the reliability of the model were assessed using ground-measured discharges with a high coefficient of determination (R2 = 0.89) and Nash–Sutcliffe model efficiency coefficient (NSE = 0.86). Therefore, the developed RRI model can successfully be used to simulate the inundation of flood events in the KRB. The findings can directly be applied to the stakeholders.
Sammendrag
Climate change can have an influence on rainfall that significantly affects the magnitude frequency of floods and droughts. Therefore, the analysis of the spatiotemporal distribution, variability, and trends of rainfall over the Mahi Basin in India is an important objective of the present work. Accordingly, a serial autocorrelation, coefficient of variation, Mann–Kendall (MK) and Sen’s slope test, innovative trend analysis (ITA), and Pettitt’s test were used in the rainfall analysis. The outcomes were derived from the monthly precipitation data (1901–2012) of 14 meteorology stations in the Mahi Basin. The serial autocorrelation results showed that there is no autocorrelation in the data series. The rainfall statistics denoted that the Mahi Basin receives 94.8% of its rainfall (821 mm) in the monsoon period (June–September). The normalized accumulated departure from the mean reveals that the annual and monsoon rainfall of the Mahi Basin were below average from 1901 to 1930 and above average from 1930 to 1990, followed by a period of fluctuating conditions. Annual and monsoon rainfall variations increase in the lower catchment of the basin. The annual and monsoon rainfall trend analysis specified a significant declining tendency for four stations and an increasing tendency for 3 stations, respectively. A significant declining trend in winter rainfall was observed for 9 stations under review. Likewise, out of 14 stations, 9 stations denote a significant decrease in pre-monsoon rainfall. Nevertheless, there is no significant increasing or decreasing tendency in annual, monsoon, and post-monsoon rainfall in the Mahi Basin. The Mann–Kendall test and innovative trend analysis indicate identical tendencies of annual and seasonal rainfall on the basin scale. The annual and monsoon rainfall of the basin showed a positive shift in rainfall after 1926. The rainfall analysis confirms that despite spatiotemporal variations in rainfall, there are no significant positive or negative trends of annual and monsoon rainfall on the basin scale. It suggests that the Mahi Basin received average rainfall (867 mm) annually and in the monsoon season (821 mm) from 1901 to 2012, except for a few years of high and low rainfall. Therefore, this study is important for flood and drought management, agriculture, and water management in the Mahi Basin.
Forfattere
Ravindu Panditharathne Miyuru Gunathilake Imiya M. Chathuranika Upaka Rathnayake Mukand S. Babel Manoj K. JhaSammendrag
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.
Sammendrag
Wetlands are simply areas that are fully or partially saturated with water. Not much attention has been given to wetlands in the past, due to the unawareness of their value to the general public. However, wetlands have numerous hydrological, ecological, and social values. They play an important role in interactions among soil, water, plants, and animals. The rich biodiversity in the vicinity of wetlands makes them invaluable. Therefore, the conservation of wetlands is highly important in today’s world. Many anthropogenic activities damage wetlands. Climate change has adversely impacted wetlands and their biodiversity. The shrinking of wetland areas and reducing wetland water levels can therefore be frequently seen. However, the opposite can be seen during stormy seasons. Since wetlands have permissible water levels, the prediction of wetland water levels is important. Flooding and many other severe environmental damage can happen when these water levels are exceeded. Therefore, the prediction of wetland water level is an important task to identify potential environmental damage. However, the monitoring of water levels in wetlands all over the world has been limited due to many difficulties. A Scopus-based search and a bibliometric analysis showcased the limited research work that has been carried out in the prediction of wetland water level using machine-learning techniques. Therefore, there is a clear need to assess what is available in the literature and then present it in a comprehensive review. Therefore, this review paper focuses on the state of the art of water-level prediction techniques of wetlands using machine-learning techniques. Nonlinear climatic parameters such as precipitation, evaporation, and inflows are some of the main factors deciding water levels; therefore, identifying the relationships between these parameters is complex. Therefore, machine-learning techniques are widely used to present nonlinear relationships and to predict water levels. The state-of-the-art literature summarizes that artificial neural networks (ANNs) are some of the most effective tools in wetland water-level prediction. This review can be effectively used in any future research work on wetland water-level prediction.
Sammendrag
På oppdrag fra Bane NOR har NIBIO overvåket vannkvalitet i resipienter som kan motta avrenning fra anleggsarbeider i forbindelse med utbygging av Follobanen. NIBIO har driftet opptil 10 målestasjoner utstyrt med multiparametersensorer for automatisk overvåking av vannkvalitet. I tillegg har det blitt tatt ut vannprøver ved opptil 15 stasjoner og utført biologiske undersøkelser ved opptil seks stasjoner. Overvåkingen har pågått i vannforekomster nedstrøms riggområdet på Åsland og i Alna i Oslo, i bekker sør for stasjonsområdet på Ski, langs anleggsområdet mellom Ski og Langhus, samt ved Sagdalsbekken i Langhus. Årsrapporten omfatter alle resultater samlet inn på disse stasjonene i 2022 og har blitt sammenlignet med tidligere resultater.
Sammendrag
Light penetration plays a vital role in lakes and drinking water reservoirs, influencing fundamental processes such as primary production and thermal budgets. The Secchi depth (ZSD) and the compensation depth (ZCD) are commonly used measurements in this context. ZSD is determined through visual inspection using a Secchi disc, while ZCD represents the depth at which photosynthetic activity balances respiration and can be measured using a quantum irradiance sensor. Through in situ water-core samples from 23 lakes within a lake district in Southeastern Norway, we observed that DNOM exerts a diverse influence on these light irradiance measurements. If DNOM concentrations are reduced to half or a quarter of the current concentration, similar to what was measured during the 1980s, the median ZCD:ZSD ratios are estimated to have decreased by approximately 30 and 60% since then, respectively. Conversely, a plausible future climate-driven doubling or quadrupling of the present DNOM concentrations are estimated to further decrease the median ZCD:ZSD ratios in the lake district with approximately 10 and 25%, respectively. From this, the ZCD:ZSD ratios seem to have experienced a considerable long-term decline attributed to both climate change and the recovery from acid rain, and a further climate-driven decrease is expected.
Sammendrag
Levels of dissolved natural organic matter (DNOM) are increasing in our boreal watercourses. This is manifested by an apparent increase in its yellow to brown colour of the water, i.e., browning. Sound predictions of future changes in colour of our freshwaters is a prerequisite for predicting effects on aquatic fauna and a sustainable operation of drinking water facilities using surface waters as raw water sources. A model for the effect of climate on colour (mg Pt L-1) has been developed for two surface raw water sources in Scotland, i.e., at Bracadale and Port Charlotte. Both sites are situated far out on the Scottish west coast, without major impact of acid rain, with limited amounts of frost, and with limited recent land-use changes. The model was fitted to 15 years long data-series on colour measurements, provided by Scottish Water, at the two sites. Meteorological data were provided by UK Met. The models perform well for both sites in simulating the variation in monthly measured colour, explaining 89 and 90% of the variation at Bracadale and Port Charlotte, respectively. These well fitted models were used to predict future changes in colour due to changes in temperature and precipitation based on median climate data from a high emission climate RCP8.5 scenario from the HadCM3 climate model (UKCP18). The model predicted an increase in monthly average colour during growing season at both sites from about 150 mg Pt L-1 to about 200 mg Pt L-1 in 2050–2079. Temperature is found to be the most important positively driver for colour development at both sites.