Threshold Rainfall Ranges for Landslide Occurrence in Matara District and Findings of a Social Survey on Emergency Preparedness

Matara district has faced several devastating landslide events within past few decades. Impacts of those landslide events would have been reduced if the threats had been identified early enough and the early warnings were disseminated at the right time. The objectives of this research were (a) to identify the effects of antecedent rainfall on the probability of landslide occurrence and (b) to analyse the knowledge of the community on landslide response, preparedness and landslide warning signs in general. During this study the major landslide events occurred in 2003 and 2017 were studied for the rainfall impact. The landslide locations were collected and the rainfall relevant to each and every landslide location was extracted by using a GIS-based interpolation method. Simultaneously a social survey was conducted to achieve the second objective described above. Starting from the daily rainfall of two days prior to landslide event (i.e. Day 3) till the daily rainfall of landslide day (Day 1), there was an identifiable pattern. There is more than 90 percent chance for a landslide to occur, when the rainfall of the day of the landslide event is close to 300 mm (in our case 290 mm) or above with a rainfall of ~80 mm or above on the previous day (Day 2). The majority of the events (over 94 percent) had a daily rainfall of ~80 mm or above on Day 3. The cumulative rainfall of the landslide day up to three days prior to the landslide event shows a significant pattern (Day 1-Day 4). There is more than 94% chance for a landslide to occur when the total rainfall received on Day 1 and Day 2 exceeds 375 mm. Overall, when there is a rainfall event of ~80 mm or over, people need to be warned/cautions about a potential landslide within the next three days, if the rainfall continues to be high. Social survey shows that during 2017 event/s people were more prepared for landslides compared to 2003, but still there are many steps to be taken in terms of response, preparedness and early warnings.Keywords: Landslides, Rainfall pattern, Early warnings, Community preparednes

Topographical Effects on Soil Carbon in a High Grown Tea Plantation of Nawalapitiya

Soil organic carbon (SOC) storage is an important component of global carbon cycle and climate change mitigation. SOC storage depends on climate, topography and soil properties. The main objective of this research was to quantify average soil SOC content across the toposequence of a selected mountain terrain. The secondary objective was to compare the impact of microclimatic variables and slope angle on soil organic carbon content. It was hypothesized that mountainous locations with an overall high percent slope have lower SOC than the mountainous locations with lower percent slope.In this study, four slope positions across the toposequence of two tea fields (Field A and Field B) within Queensberry tea estate, Nawalapitiya were sampled for soil analyses. Measurements on micrometeorological variables (soil and air temperature, relative humidity, wind velocity, light intensity), litter and soil cores were taken in the field, and soil parameters including soil moisture, pH, texture and SOC stocks were analyzed in the laboratory.The overall average soil organic carbon stock in the studied soils was 159.85 t/ha .The overall percent slope of field A (25 percent) was higher than that of field B (21 percent). A significant difference in soil carbon stock could be seen among the slope positions considered across the toposequence of each field (P<0.0005). Percent soil moisture (P<0.0005; adjusted R²=61.60%) and sampling fields (which differed in overall slope angle; P<0.005; adjusted R²=26.48%) have a notable effect on SOC stock while litter depth (F=2.68; P>0.05) have no significant effect on SOC stock. The SOC stock was higher at the field B (172.16 t/ha) which had the lower percent slope while SOC stock was lower at the field A (147.52t/ha) which had the higher percent slope. Therefor our hypothesis that mountainous locations with high percent slope would have lower SOC than the mountainous locations with lower percent slope was supported.Overall, the SOC stocks were significantly different with regard to the differences in slope angle (as found for the two fields) and the slope position across the toposequence (as observed within each field) in the medium-gradient tea plantation considered in the current study. Among the microclimatic variables, only the moisture had a significant influence on the SOC stock.Keywords: SOC stock, Slope position, Slope angle, Percent soil moisture, Medium-gradient tea plantatio

Incorporation of crop phenology in Simple Biosphere Model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands

Croplands are man-made ecosystems that have high net primary productivity during the growing season of crops, thus impacting carbon and other exchanges with the atmosphere. These exchanges play a major role in nutrient cycling and climate change related issues. An accurate representation of crop phenology and physiology is important in land-atmosphere carbon models being used to predict these exchanges. To better estimate time-varying exchanges of carbon, water, and energy of croplands using the Simple Biosphere (SiB) model, we developed crop-specific phenology models and coupled them to SiB. The coupled SiB-phenology model (SiBcrop) replaces remotely-sensed NDVI information, on which SiB originally relied for deriving Leaf Area Index (LAI) and the fraction of Photosynthetically Active Radiation (fPAR) for estimating carbon dynamics. The use of the new phenology scheme within SiB substantially improved the prediction of LAI and carbon fluxes for maize, soybean, and wheat crops, as compared with the observed data at several AmeriFlux eddy covariance flux tower sites in the US mid continent region. SiBcrop better predicted the onset and end of the growing season, harvest, interannual variability associated with crop rotation, day time carbon uptake (especially for maize) and day to day variability in carbon exchange. Biomass predicted by SiBcrop had good agreement with the observed biomass at field sites. In the future, we will predict fine resolution regional scale carbon and other exchanges by coupling SiBcrop with RAMS (the Regional Atmospheric Modeling System)

ANALYSIS OF THE EMISSION TRADING POTENTIAL IN SRI LANKA FOR GLOBAL GREENHOUSE GAS MARKET UNDER THE KYOTO PROTOCOL

Under the United Nations Framework Convention of Climate Change (UNFCCC) reductionof Green House Gas (GHG) emissions become a global good with shared and differentiatedresponsibility vested with member countries. The Kyoto Protocol was adopted in 191)7 asthe legally hinding instrument to achieve the objectives of UNFCCC. This protocolintroduced three controversial mechanisms namely Joint Implementation (11. Article 6).Clean Development Mechanism (CDM, Article 12) and the emission trading (Article J 7) furthe establishment of markets for GHG emission reduction.Under the Annex I of UNFCCC countries are obliged to reduce their GHG by 5.2'7< fromthe total 1990 level. Global commitments under the common but di Ilcrentiatcdresponsihility principle of UNFCCC for reducing the emissions vary and depends on thecountry's level of emission. Accordingly Annex I countries were given emission reductiontargets c.g. Japan 6Lk. EU 8L.k. and US 7CJL. This issue has drawn attention or the developedcountries since it could alter their lifestyles drastically. The flexible mechanism permitsdeveloped countries to purchase GHG emission potential from developing countriesSelling GHG emission potential (although an income source) has been viewed as sellingdevelopment potential of developing countries. This puts the developing countries in adilemma in making decisions on emission trading. Therefore an in-depth knowledge onmarket potential of GHG is important.The objective of this paper is to review the flexible mechanisms under the Kyoto Protocoli.e. 11, CDM and emission trading along with principles. modalities and procedures inrelation to Sri Lankan environmental conditions and to estimate the total GHG marketpotential for Sri Lanka if the country decides to participate in the global GHG market. Thispaper presents an economic analysis of GHG market in Sri Lanka with an attempt toinvestigate the relationship between rate of emission and economic growth. This ventureessentially creates an equity problem which is discussed using different discount rates.Data from secondary sources. in particular GHG inventories for Sri Lanka for J 1)94 & 11)1)5years arc used to estimate Sri Lankan emission trading potential. These figures will heuseful for predicting Sri Lankan contribution to the emission trading market. Sinks andSources and the sectors of emission are discussed separately in order to identify the mostimportant sectors in terms of emission trading. The paper also discusses the disadvantagesof emission trading, particularly whether this would limit our development potential andsovereignty. the major criticisms against the emission trading. Finally, this paper presentsthe relationship between GHG emission. emission trading potential and economicdevelopment under various scenarios.

\u3ci\u3eCorrigendum to\u3c/i\u3e “Incorporation of crop phenology in Simple Biosphere Model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands” published in Biogeosciences, 6, 969–986, 2009

In the above mentioned manuscript a mistake in Fig. 11 occured. The corrected version of the figure is as follows

Amorphization of Pseudocapacitive T−nb\u3csub\u3e2\u3c/sub\u3eo\u3csub\u3e5\u3c/sub\u3e Accelerates Lithium Diffusivity as Revealed Using Tunable Isomorphic Architectures

Intercalationpseudocapacitancecan combinecapacitor-likepower densitieswith battery-likeenergy densities.Such surface-limitedbehaviorrequiresrapid diffusionwhere amorphizationcan increasesolid-statediffusivity.Here intercalationpseudoca-pacitivematerialswith tailoredextentsof amorphizationin T-Nb2O5are first reported.Amorphizationwas characterizedwithWAXS, XPS, XAFS, and EPR which suggesteda peroxide-rich(O22) surface that was consistentwith DFT predictions.A seriesof tunableisomorphicarchitecturesenabledcomparisonswhileindependentlyvaryingtransportparameters.Throughprocessof elimination,solid-statelithium diffusionwas identifiedas thedominantdiffusive-constraintdictatingthe maximumvoltagesweep rate for surface-limitedkinetics(vSLT), termed the Surface-LimitedThreshold(SLT). ThevSLTincreasedwith amorphizationhoweverstable cycling requiredcrystallineT-Nb2O5. A current-responsemodel using series-impedanceswell-matchedtheseobservations.This perspectiverevealedthat amorphizationof T-Nb2O5enhancedsolid-statediffusionby 12.2% and increasedsurface-limitationsby 17.0% (stablesamples).This approachenabledretaining95% lithiationcapacityat ~800mVs1(1,600C-rate equivalent)

Evaluating the agreement between measurements and models of net ecosystem exchange at different times and timescales using wavelet coherence: an example using data from the North American Carbon Program Site-Level Interim Synthesis

Earth system processes exhibit complex patterns across time, as do the models that seek to replicate these processes. Model output may or may not be significantly related to observations at different times and on different frequencies. Conventional model diagnostics provide an aggregate view of model–data agreement, but usually do not identify the time and frequency patterns of model–data disagreement, leaving unclear the steps required to improve model response to environmental drivers that vary on characteristic frequencies. Wavelet coherence can quantify the times and timescales at which two time series, for example time series of models and measurements, are significantly different. We applied wavelet coherence to interpret the predictions of 20 ecosystem models from the North American Carbon Program (NACP) Site-Level Interim Synthesis when confronted with eddy-covariance-measured net ecosystem exchange (NEE) from 10 ecosystems with multiple years of available data. Models were grouped into classes with similar approaches for incorporating phenology, the calculation of NEE, the inclusion of foliar nitrogen (N), and the use of model–data fusion. Models with prescribed, rather than prognostic, phenology often fit NEE observations better on annual to interannual timescales in grassland, wetland and agricultural ecosystems. Models that calculated NEE as net primary productivity (NPP) minus heterotrophic respiration (HR) rather than gross ecosystem productivity (GPP) minus ecosystem respiration (ER) fit better on annual timescales in grassland and wetland ecosystems, but models that calculated NEE as GPP minus ER were superior on monthly to seasonal timescales in two coniferous forests. Models that incorporated foliar nitrogen (N) data were successful at capturing NEE variability on interannual (multiple year) timescales at Howland Forest, Maine. The model that employed a model–data fusion approach often, but not always, resulted in improved fit to data, suggesting that improving model parameterization is important but not the only step for improving model performance. Combined with previous findings, our results suggest that the mechanisms driving daily and annual NEE variability tend to be correctly simulated, but the magnitude of these fluxes is often erroneous, suggesting that model parameterization must be improved. Few NACP models correctly predicted fluxes on seasonal and interannual timescales where spectral energy in NEE observations tends to be low, but where phenological events, multi-year oscillations in climatological drivers, and ecosystem succession are known to be important for determining ecosystem function. Mechanistic improvements to models must be made to replicate observed NEE variability on seasonal and interannual timescales