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
Sanjana Zoysa Vindhya Basnayake Jayanga T. Samarasinghe Miyuru Gunathilake Komali Kantamaneni Nitin Muttil Uttam Pawar Upaka RathnayakeSammendrag
Det er ikke registrert sammendrag
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.
Sammendrag
Det er ikke registrert sammendrag
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.
Forfattere
Yvonne RognanSammendrag
På vegne av Tinfos AS har NIBIO gjennomført overvåking av vannkvalitet i Hovlandsåna i 4. kvartal 2022. Miljøovervåkingen er tilknyttet etableringen av nye Flateland kraftverk i Vegusdal. I løpet av 2022 har arbeidene med Flateland kraftverk vært omfattende, og de har i perioder foregått tett på Hovlandsåna. Ved Myklebostad har etablering av inntaksdam medført behov for graving i, og omlegging av elva. Samtidig har det vært store variasjoner i vannføringen i elva og erosjon fra elvebredden har i perioder ført til økt partikkeltransport. I perioder med lavere vannføring har nitrogenavrenning fra anleggsarbeidene midlertidig påvirket vannkvaliteten, men den samlede tilstanden for totalnitrogen i Q4 var «svært god». Resultatene fra undersøkelsene av begroingsalger viser at tilstanden for disse er uforandret sammenlignet med 2021. Samlet sett ser det ikke ut til at anleggsarbeidene har hatt noen vedvarende negative konsekvenser for tilstanden i Hovlandsåna.
Sammendrag
Prosjektet hadde som mål å øke kunnskapen om økologisk tilstand i vannforekomster i jordbruksområder på Østlandet, der vannforekomstene er kraftig påvirket av hydromorfologiske inngrep, men ikke nødvendigvis er definert som sterkt modifiserte vannforekomster (SMVF) etter vannforskriften. For å få et representativt utvalg, ble ulike grader av utrettinger av elvestrengen valgt ut. Seks av åtte elver hadde mer enn 80 % av elveløpet rettet ut. Vi fant en sammenheng mellom graden av utretting og manglende kantvegetasjon. Halvparten av elvene hadde mindre enn 10 % intakt kantvegetasjon. Vi fant også en sammenheng mellom økende andel naturlig meandrerende deler av elva og økt tetthet av ørret (Salmo trutta). Tetthet av ørret øker også med andel kantvegetasjon langs hele elveløpet og økt variasjon i bunnsubstratet. Der det var mye hydromorfologiske variasjon i vannstrengen, var det flere arter av bunndyr enn der det var mindre hydromorfologiske variasjon. Ørret og laks kan brukes som indikatorarter for endret hydromorfologi, med dagens indekser. Vi vil anbefale å utvikle en indeks for bunndyr som responderer på hydromorfologiske endringer i vannstrengen. Bunndyr-indeksen ASPT ser ikke ut til å kunne benyttes. Vi vil anbefale å utarbeide indekser for graden av modifisering av vassdraget, herunder en indeks for graden av kantvegetasjon.
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.