Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2024
Authors
Sanjana De Zoysa Jeewanthi Sirisena Helani Perera Shalinda Fernando Miyuru Gunathilake Upaka RathnayakeAbstract
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 curves were developed more than 30 years ago. Many in-situ rainfall observations in Sri Lanka have insufficient record lengths and the absence of finer time scale records (e.g. 15 min, hourly) leading to unreliable IDF curve developments. Given this importance, the present paper demonstrates the application of Satellite-based Precipitation Product (SbPP) daily rainfall in developing IDF curves for Sri Lanka. Rainfall satellite estimates derived from Integrated Multi-satellite Retrievals for GPM (IMERG), Tropical Rainfall Measuring Mission (TRMM-3B42), and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR) have been used to evaluate the ability of application of remote sensing data to develop IDF curves for Sri Lanka against rain gauge (RG) data. Our study breaks new ground by generating 50 IDF curves tailored to specific locations covering the whole county Sri Lanka, using daily rainfall data from RGs and three SbPPs during the period between 1990 and 2019. This marks a significant departure from the conventional approach, offering a more granular understanding of rainfall patterns in the country. By providing IDF curves for individual locations, our research presents a novel contribution to Sri Lanka's IDF history. At first, to evaluate the accuracy of SbPPs, statistical analysis was conducted using continuous and categorical evaluation indices. Second, IDF curves were developed and compared with the presently available IDF curves. Results showcased that IMERG outperformed all SbPPs, while PERSIANN-CDR showed dire performances. The IMERG and TRMM-3B42 products tend to overestimate light precipitation regions in high elevations and overestimate heavy rainfall in low elevations compared to rain gauge data. Rainfall intensities derived by rain gauge data depicted relative changes within ±30% for shorter durations and ±20% for longer durations while SbPPs showed beyond ±30% difference concerning the previously developed IDFs. It was apparent that these products have significant inaccuracies which cannot be neglected when utilizing them in developing IDF curves. This study will be beneficial in solving design problems associated with urban runoff control and disposal where knowing the rainfall intensities of different return periods with different durations is vital.
Abstract
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 method which uses a set of indicators to assess the agricultural vulnerability (AV) to climate change in Anuradhapura district. The AV assessment used in this study involves three principal components exposure, sensitivity, and adaptive capacity. The indicators are normalized to allow spatial analysis and smooth integration within a geographic information system (GIS) framework. The AV of Anuradhapura district ranged from 0.32 to 0.67 and was divided among five levels very low, low, moderate, high, and very high. The findings suggest that Anuradhapura’s agricultural sector was significantly impacted by climate change as the majority of the total area was found to have very high, high, and moderate levels of AV with 25, 28, and 24%, respectively. The results obtained from this study are essential for formulating plans to improve Anuradhapura’s agricultural sector resilience and adaptability to ensure food security and livelihood sustainability considering the ever-changing climate.
Abstract
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 and river basins are highly important. The Uma Oya River Basin (UORB), Sri Lanka is an area with rich biodiversity and is also important for agricultural production. Moreover, this area is frequently discussed due to the ongoing developments of the Uma Oya Project. This paper presents a comprehensive evaluation of soil erosion in the UORB and results are compared for two decades from 2000 to 2020. The Revised Universal Soil Loss Equation (RUSLE) was used to determine the annual soil erosion rates. In addition, the spatial-temporal variation of land use and land cover was assessed in the UORB. Results revealed that extreme soil erosion scenarios occur when forests and other vegetation lands are converted to agricultural lands and farmlands. We found that soil loss in the area largely happened due to steep slopes, reduction of vegetation and forest covers, and growth of cultivation lands. Erosion-prone areas in the river basin are identified and conservation strategies are discussed. In addition, the impact of the ongoing climate change on the UORB is highlighted.
Authors
Zumry Niyas Charuni I. Madhushani Miyuru Gunathilake Vindhya Basnayaka Komali Kantamaneni Upaka RathnayakeAbstract
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 Wischmeier and Smith algorithm and for its ED using Kinnel's algorithm. The monthly rainfall data spreading over the river basin were used to analyze the monthly, seasonal, and annual RE and ED. Interestingly, the annual RE showed a linear increasing trend line over 31 years, and a maximum value of 2,831.41 MJ mm ha−1 h−1 yr−1 was able to be observed in the year 2016. The RE peaks in May which is in the southwestern monsoon season. This reveals that the risk of soil erosion in the basin is high in the southwestern monsoon season. In addition, land use and land cover changes over the years have adversely impacted the erosion rates. Therefore, it is highly recommended to investigate soil erosion in-depth and then implement relevant regulations to conserve the soil layers upstream of the river basin.
Authors
Randika K. Makumbura Prasad Dissanayake Miyuru Gunathilake Namal Rathnayake Komali Kantamaneni Upaka RathnayakeAbstract
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 ArcGIS10.4 and QGIS3.16. Data from Remote Sensing sources, particularly the MODIS hotspot real-world dataset, were employed to gather fire count information for the year 2020. Validation was conducted through the merging hotspot technique and kernel density estimation (KDE). The research findings highlight the districts in the Central and Uva provinces, such as NuwaraEliya (10.3 km2), Kandy (2.74 km2), and Badulla (10.41 km2), as having a “very low risk" of forest fire potential. Conversely, districts like Hambanthota (0.1 km2), Kaluthara (0.04 km2), and Kurunegala (0.2 km2) exhibit a “very high risk" of forest fire potential, although it is negligible compared country's total area. Overall, the study suggests that Sri Lanka is not currently facing a significant threat of forest fires and is a “medium risk" of forest fires as 49.49% of land falls under this category. These results are of immense value to relevant authorities, including the Ministry of Wildlife and Forest Resources Conservation, in formulating effective strategies to manage and mitigate forest fire risks in the country.
Authors
Rolf David Vogt Øyvind Aaberg Garmo Kari Austnes Øyvind Kaste Ståle Haaland James Edward Sample Jan-Erik Thrane Liv Bente Skancke Cathrine Brecke Gundersen Heleen de WitAbstract
Rising organic charge in northern freshwaters is attributed to increasing levels of dissolved natural organic matter (DNOM) and changes in water chemistry. Organic charge concentration may be determined through charge balance calculations (Org.−) or modelled (OAN−) using the Oliver and Hruška conceptual models, which are based on the density of weak acid functional sites (SD) present in DNOM. The charge density (CD) is governed by SD as well as protonation and complexation reactions on the functional groups. These models use SD as a key parameter to empirically fit the model to Org.−. Utilizing extensive water chemistry datasets, this study shows that spatial and temporal differences in SD and CD are influenced by variations in the humic-to-fulvic ratio of DNOM, organic aluminum (Al) complexation, and the mole fraction of CD to SD, which is governed by acidity. The median SD values obtained for 44 long-term monitored acid-sensitive lakes were 11.1 and 13.9 µEq/mg C for the Oliver and Hruška models, respectively. Over 34 years of monitoring, the CD increased by 70%, likely due to rising pH and declining Al complexation with DNOM. Present-day median SD values for the Oliver and Hruška models in 16 low-order streams are 13.8 and 15.8 µEq/mg C, respectively, and 10.8 and 12.5 µEq/mg C, respectively, in 10 high-order rivers.
Authors
Ståle Haaland Josef Hejzlar Bjørnar Eikebrokk Geir Orderud Ma. Cristina Paule‐Mercado Petr Porcal Jiří Sláma Rolf David VogtAbstract
Over the past four decades, an increase in Dissolved Natural Organic Matter (DNOM) and colour, commonly referred to as browning, has been noted in numerous watercourses in the northern hemisphere. Understanding the fluctuations in DNOM quality is a prerequisite for gaining insights into the biogeochemical processes governing DNOM fluxes. Such knowledge is also pivotal for water treatment plants to effectively tailor their strategies for removing DNOM from raw water. The specific ultraviolet absorbance (sUVa) index has been a widely applied measurement for assessing DNOM quality. The sUVa index is the UV absorbance (OD254) of water normalized for DNOM concentration. We have used a long-term dataset spanning from 2007 to 2022, taken from the Malše River in South Bohemia, to model DNOM and the sUVa index. We have applied regression models with a process-oriented perspective and have also considered the influence of climate change. Both DNOM and the sUVa index is positively related to temperature, runoff and pH, and negatively related to ionic strength over the studied period. Two distinct model approaches were employed, both explaining about 40% of the variation in sUVa over the studied period. Based on a moderate IPCC monthly climate scenario, simulations indicate that both DNOM and the sUVa index averages remain fairly stable, with a slight increase in winter season minima projected towards the year 2099. A slight decline in summer season maxima is simulated for DNOM, while the sUVa summer maximum remain stable. These findings suggest a robust resilience in both DNOM and the sUVa index against anticipated changes in temperature and runoff for the Malše River in South Bohemia.
Abstract
No abstract has been registered
Abstract
In this study, the influence of riverbed silting on the groundwater regime in a lowland area was investigated. The study area is situated at the Rye Island (Žitný Ostrov) in Slovakia, along the Gabčíkovo – Topoľníky canal, which is part of the drainage-irrigation canal system constructed in this locality. The Rye Island is an area with very low slope (0.25 10–4) and good climatic conditions for aquatic vegetation, therefore the canals are influenced by intensive silting processes. The spatial and temporal patterns of surface water – groundwater exchange are significantly influenced by the thickness of riverbed sediments and their permeability. The aim of this study was to evaluate the thickness and hydraulic conductivity of bed sediments in the Gabčíkovo – Topoľníky canal and to examine their influence on the groundwater – surface water interaction in the area. The hydraulic conductivity of the sediments was assessed from undisturbed samples by the falling head method. The obtained data were used for numerical simulations of groundwater heads by the TRIWACO model for different drainage and infiltration resistance conditions in the area of interest. The results of this study can support the planning of canal maintenance.
Abstract
The objectives of the study was to 1) investigate soil-plant-water interactions based on field measurements of plant reflectance and soil water content (SWC) in different inter-row managed vineyards, and 2) modeling changes in the SWC due to differences in soil physical parameters among slope positions and management methods. The study explored the impact of three different soil management practices on grapevine growth and soil health in vineyards: tilled (T), cover crops (CC), and perennial grass (NT) inter-rows. Data was collected for 2022 and 2023. At each study slopes, we had two measurement points along a slope section. To continuously monitor soil water and temperature conditions, sensors were strategically positioned at two depths of 15 cm and 40 cm below the soil surface along the slopes, both at the upper and lower points of the vineyard, while topsoil SWC was measured bi-weekly. Normalized Difference Vegetation Index (NDVI) and Photochemical Reflectance Index (PRI) sensors were used to measure leaf reflectance, while handheld instruments were used to measure additional NDVI and leaf Chlorophyll contents (SPAD). For the hydrological modeling we used SWAP (Soil-Water-Atmosphere-Plant), where the rswap R-package was used for calibration (2020 15 and 40cm data), validation (2021 15 and 40cm data), and statistical evaluation. In 2022, all three slopes showed a significantly higher SWC content for the higher points compared to the lower, while in 2023 the grassed slope upper point showed higher SWC (0.18 vs 0.15%). The highest NDVI values were measured for the cover cropped vineyard site (0.68). However, we found no significant differences among NDVI values based on inter-row management or slope position, only the grassed inter-row vineyard had differences in the NDVI values at the lower and upper points (p=0.034). The highest leaf chlorophyll contents were measured for the cover cropped vineyard site (305). Most of the leaf Chlorophyll values were not significantly different among slope positions. Using the SWAP model, data from the cover cropped inter-row vineyard was used for calibration and validation. We found good model fitting (NSE > 0.52; d_daily > 0.81). Reduced-tillage (RT) and drought tolerant plant (DTP) management scenarios were run to simulate SWC changes over time. Preliminary data shows that DTP significantly reduced, while RT did not significantly affect our site’s SWC.