Evapotranspiration (ET) is a significant hydrological process. It can be studied and estimated using remote sensing based methods at multiple spatial and temporal scales. Most commonly and widely used remote sensing based methods to estimate actual evapotranspiration (AET) are a) methods based on energy balance equations, b) vegetation coefficient based method and c) contextual methods. These three methods require reflectance and land surface temperature (LST) data measured at optical and thermal portion of the electromagnetic spectrum. However, these data are available only for clear sky conditions and fail to be retrieved under overcast conditions creating gaps in the data, which result in discontinuous of AET product. Moreover, energy balance equation based methods and evaporative fraction (EF) based contextual methods are difficult to apply over overcast conditions. In this context, vegetation coefficient based (Tasumi et al., 2005; Allen et al., 2005) and microwave remote sensing based methods can be applied under cloudy sky conditions (Sun et al., 2012), since microwave radiations can penetrate through clouds, but these data are available at coarse resolution. In the vegetation coefficient method temporal upscaling can be avoided. Therefore in this research vegetation coefficient based method is employed over Cauvery basin to estimate daily AET for clear and cloudy sky conditions. Required critical variables for this method such as reference evapotranspiration (ETo) and vegetation coefficients are obtained using LST and optical vegetation indices for all sky conditions. In this study, all sky conditions refer to both clear and cloudy sky conditions. Most important variable for estimation of ETo using radiation and temperature based models is air temperature (Ta). In this study, for better accuracy of Ta, two satellite based approaches namely, Temperature Vegetation Index (TVX) and Advance Statistical Approaches (ASA) were evaluated. In the TVX approach, in addition to traditional Normalized Difference Vegetation Index (NDVI), other vegetation indices such as Enhanced Vegetation Index (EVI) and Global Vegetation Moisture Index (GVMI) were also examined. In case of ASA, bootstrap technique was used to generate calibration and validation samples and Levenberg Marquardt algorithm was used to find the solution of the models. The better of the Ta results obtained out of these two approaches were employed in the ETo models and are referred as Ta based ETo models. Instead of Ta, processed LST data obtained directly from the satellite (Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS)) was applied in the ETo models and these are referred as LST based ETo models. These Ta and LST based Hargreaves-Samani (H-S), Makkink (Makk) and Penman Monteith Temperature (PMT) models were evaluated by comparing with the FAO56 PM model. Additionally, simple LST based equation (SLBE) proposed by Rivas et al. (2004) was also examined. Required solar radiation (Rs) data for ETo estimation was obtained from Kalpana1/VHRR satellite data. Results implied that, Ta based PMT model performed better than the Ta based H-S, Makk and SLBE with less RMSE, MAPE and MBE values for all land cover classes and for various climatic regions for clear sky conditions. LST based H-S, PMT, Makk and Ta based Makkink advection models predominantly overestimated ETo for the study region. In the case of TVX approach, to estimate maximum Ta (Tmax), GVMI performed better than NDVI and EVI. Nevertheless, TVX approach poorly estimated Tmax in comparison with statistical approach. ASA performed better for both Tmax and minimum Ta. This study demonstrates the applicability of satellite based Ta and ETo models by considering very few variables for clear sky conditions. Spatially distributed vegetation coefficients (Kv) data with high temporal resolution is another important variable in vegetation coefficient method for daily AET estimation and also it is in demand for crop condition assessment, irrigation scheduling, etc. But available Kv models application hinders because of two main reasons i.e 1) Spectral reflectance based Kv accounts only for transpiration factor but not evaporation, which fails to account for total AET. 2) Required optical spectral reflectances are available only during clear sky conditions, which creates gaps in the Kv data. Hence there is a necessity of a model which accounts for both transpiration and evaporation factors and also gap filling method, which produces accurate continuous quantification of Kv values. Therefore, different combinations of EVI, GVMI and temperature vegetation dryness index (TVDI) have been employed in linear and non linear regression techniques to obtain best model. This best Kv model had been compared with Guershman et al. (2009) Kv model. To fill the gaps in the data, initially, temporal fitting of Kv values have been examined using Savitsky-Goley (SG) filter for three years of data (2012 to 2014), but this fails when sufficient high quality Kv values were unavailable. In this regard, three gap filling techniques namely regression, Artificial Neural Networks (ANNs) and interpolation techniques have been analyzed. Microwave polarization difference index (MPDI) has been employed in ANN technique to estimate Kv values under cloudy sky conditions. The results revealed that the combination of GVMI and TVDI using linear regression technique performed better than other combinations and also yielded better results than Guershman et al. (2009) Kv model. Furthermore, the results indicated that SG filter can be used for temporal fitting and for filling the gaps, regression technique can be used as it performed better than other techniques for Berambadi station. Land Surface Temperature (LST) with high spatiotemporal resolution is required in the estimation of ETo to obtain AET. MODIS is one of the most commonly used sensors owing to its high spatial and temporal availability over the globe, but is incapable of providing LST data under cloudy conditions, resulting in gaps in the data. In contrast, microwave measurements have a capability to penetrate under clouds. The current study proposes a methodology by exploring this property to predict high spatiotemporal resolution LST under cloudy conditions during daytime and night time without employing in-situ LST measurements. To achieve this, ANN based models were employed for different land cover classes, utilizing MPDI at finer resolution with ancillary data. MPDI was derived using resampled (from 0.250 to 1 km) brightness temperatures (Tb) at 36.5 GHz channel of dual polarization from Advance Microwave Scanning Radiometer (AMSR)-Earth Observing System and AMSR2 sensors. The proposed methodology was quantitatively evaluated through three performance measures namely correlation coefficient (r), Nash Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE). Results revealed that during daytime, AMSR-E(AMSR2) derived LST under clear sky conditions corresponds well with MODIS LST resulting in values of r ranging from 0.76(0.78) to 0.90(0.96), RMSE from 1.76(1.86) K to 4.34(4.00) K and NSE from 0.58(0.61) to 0.81(0.90) for different land cover classes. For night time, r values ranged from 0.76(0.56) to 0.87(0.90), RMSE from 1.71(1.70) K to 2.43(2.12) K and NSE from 0.43 (0.28) to 0.80(0.81) for different land cover classes. RMSE values found between predicted LST and MODIS LST during daytime under clear sky conditions were within acceptable limits. Under cloudy conditions, results of microwave derived LST were evaluated with Ta which indicated that the approach performed well with RMSE values lesser than the results obtained under clear sky conditions for land cover classes for both day and nighttimes. These predicted LSTs can be applied for the estimation of soil moisture in hydrological studies, in climate studies, ecology, urban climate and environmental studies, etc. AET was estimated for all sky conditions using vegetation coefficient method. Essential parameter ETo under cloudy conditions was estimated using LST and Ta based PMT and H-S models and required solar radiation (Rs) in these two models estimated using equation proposed by Samani (2000). In this equation it was found that the differences between LSTmax or Tmax and LSTmin or Tmin could able to capture the variations due to cloudy sky conditions and hence can be used for estimating ETo under cloudy sky conditions. Results revealed that the estimated Rs correlated well with observed Rs for Berambadi station under cloudy conditions for the year 2013. PMT based ETo values were corresponded with observed ETo under cloudy sky condition. The difference between LST and Ta was less during cloudy conditions, therefore LST or Ta can be used as the only input in temperature based PMT model to estimate ETo. AET estimated correlated well with the observed AET values for clear and cloudy sky conditions. In addition, AET estimated using vegetation coefficient method was compared with two source energy balance (TSEB) method developed by Nishida et al. (2003) under clear sky conditions. It was found that the improved vegetation coefficient method performed better than the TSEB method for Berambadi station. Other microwave vegetation indices such as Microwave Vegetation Indices (MVIs) and Emissivity Difference Vegetation Index (EDVI) are available in literature. Therefore in this study, MVIs are used to predict LST under cloudy conditions using proposed methodology to check whether the MVIs could yield better LST values. Results showed that MPDI performed better than MVIs to predict LST under cloudy sky conditions. Furthermore, MPDI obtained using dual polarizations of 37 GHz channel Tb has advantage of having fine spatial resolution compared to MVIs, as it requires Tb of 19 GHz in addition to Tb of 37 GHz channel which is of coarse resolution and therefore uncertainties resulting from re-sampling technique can be minimized. x

Programa de Apoio aos Planos de Reestruturação e Expansão das Universidades Federais / This study analyzes simulations of Net Primary Production (NPP) from 15 different landsurface models (LSMs) and biomass pools from 6 different LSMs using meteorological conditions measured at 8 sites from Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project as drivers. The models were not calibrated for the sites. The sites are divided into four biome types: Evergreen Broadleaf Forests (4 sites); Deciduous Broadleaf Forest (1 site); Savanna (1 site); Pasture/Agriculture (2 sites). The mean daily cycles, monthly and annual means of NPP were intercompared and evaluated. There were considerable differences among the NPP simulations, and some of these differences reached up to two orders of magnitude in nocturnal values. Seasonality in dry periods of the NPP could be observed in some models for all biome types. The annual mean NPP simulations from two Evergreen Broadleaf Forests (K34 and K67 sites) were compared with the observations. In general, the simulations by most models do not represent very well the observations; however, the mean value from all simulations is able to represent the observed data. In general, models that represented the Dynamic Vegetation Carbon Fluxes and Nitrogen Cycling Models (DVN) were those that better represented the observed values, suggesting that a more specific description of the vegetation dynamics capture, even without calibration, the carbon exchanges with enough accuracy. The simulated biomass is also divergent between the models, although the distribution of that biomass follows the expected patterns for each biome type. Therefore, we believe that a model calibration can improve the simulations results. / Este estudo analisa simulações de Produção Primária Líquida (NPP) de 15 diferentes modelos de superfície (LSMs) e reservatórios de biomassa de 6 diferentes LSMs usando condições meteorológicas medidas em 8 sítios do projeto Large-Scale Biosphere-Atmosphere Experiment in Amazônia (LBA) como forçantes. Os modelos não foram calibrados para os sítios. Os sítios foram divididos em quatro tipos de biomas: Florestas de Folhas Largas Sempre-Verdes (4 sítios); Florestas de Folhas Largas Decídua (1 sítio); Savana (cerrado, 1 sítio); Pasto/Agricultura (2 sítios). Os ciclos de NPP médios diários, mensais e anuais foram intercomparados e avaliados. Existem diferenças consideráveis entre as simulações de NPP, e algumas destas diferenças alcançaram até duas ordens de magnitude em valores noturnos. Pôde ser observada sazonalidade de NPP em alguns modelos para todos os tipos de bioma. O NPP médio anual simulado em duas Florestas Sempre-Verdes (sítios K34 e K67) foi comparado com as observações. Em geral, as simulações da maior parte dos modelos não representam muito bem as observações; entretanto, o valor médio de todas as simulações consegue representar os dados observados. Em geral, modelos que representam a vegetação dinâmica, fluxos de carbono e ciclo do nitrogênio (DVN) foram aqueles que melhor representaram os valores observados, sugerindo que uma descrição mais específica da dinâmica da vegetação pode capturar, mesmo sem calibração, as trocas de carbono com suficiente precisão. A biomassa simulada é também divergente entre os modelos, embora a distribuição dessa biomassa segue os padrões esperados para cada tipo de bioma. Logo, acreditamos que uma calibração do modelo pode melhorar os resultados das simulações.

Les données de télédétection dans l'infrarouge thermique (IRT) sont une source indispensable d'information pour estimer les flux de surface et suivre le fonctionnement des agro-écosystèmes. Cependant, les mesures de température de surface sont sujettes à des effets directionnels très importants (présence de 'hot spot') pouvant entraîner une erreur allant jusqu'à une dizaine de degrés Celsius. Ils doivent être pris en compte en vue des applications opérationnelles. Le travail proposé ici vise à modéliser l'anisotropie directionnelle des couverts végétaux pour mettre au point des méthodes opérationnelles de correction des mesures satellitaires de température de surface. Il est largement motivé par les projets du CNES visant à élaborer une mission spatiale nouvelle combinant une haute résolution spatiale et des capacités fortes de revisite dans l'IRT. Deux étapes de travail ont été menées. La première repose sur l'utilisation du modèle déterministe de transfert Sol-Végétation-Atmosphère SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), capable de simuler les radiances directionnelles dans l'optique et l'IRT. Dans ce manuscrit, il est validé par rapport à des mesures de terrain et sa capacité à simuler correctement les effets d'anisotropie démontrée. Il est ensuite utilisé pour étudier de façon systématique la sensibilité de l'anisotropie directionnelle à la structure de la canopée, à son état hydrique, au forçage météorologique et aux configurations angulaires solaire et de visée. Les conséquences en terme d'impact combiné des caractéristiques orbitales des satellites, de la position géographique des sites observés et de la date d'acquisition sur l'anisotropie sont discutées. La seconde étape vise à proposer un modèle paramétrique simplifié (dit RL). SCOPE est ici utilisé en tant que générateur de données. Le modèle RL se révèle robuste et capable de restituer avec succès les signatures directionnelles sur le plan géométrique (position du hot spot) comme pour l'amplitude des effets directionnels. Une comparaison avec le seul autre modèle paramétrique utilisé jusqu'alors en télédétection IRT (le modèle de Vinnikov) confirme les qualités du modèle RL, ce qui en fait un candidat potentiel pour les chaines de traitement des futures données satellitaires. / Remotely-sensed data in thermal infrared (TIR) are an essential source of information to estimate surface fluxes and to monitor the functioning of agro-ecosystems. However, surface temperature measurements are prone to directional effects ('hot spot' phenomenon)which may result in an error up to 10°C. They have to be taken into account in the framework of operational applications. The work proposed here aims at modelling the directional anisotropy of continuous vegetated canopies in order to develop operational methods for correcting land surface temperature measurements carried out by TIR satellites. This work is mainly motivated by the CNES projects aiming at developing a new TIR spatial mission combining both high spatial resolution and high revisit time capacities. Two steps were carried out. The first is based on the use of the deterministic SVAT model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), able to simulate directional radiances at top of canopy in both optical and TIR domains. In this thesis, it is validated against experimental measurements and its ability to successfully simulate TIR directional anisotropy demonstrated. Then it is used to study the sensitivity of anisotropy to canopy structure, water status of soil and vegetation, meteorological forcing and solar and observer angular configurations. The consequences of the combined features of satellites orbits, geographical position of the scanned sites and acquisition date on anisotropy are discussed. In the second part, we propose a simplified parametric model (called 'RL'). SCOPE is used as a data generator. The RL model is deemed suitable and able to correctly reproduce directional signatures both in terms of geometry (hot spot position) and amplitude of these effects. A comparison with the only one parametric model previously used in TIR remote sensing (Vinnikov's approach) confirms the good capacities of the RL model. The RL model is thus a potential candidate to the future satellite processing chains.

En régions méditerranéennes, la gestion de l'eau à partir d'outils d'aide à la décision requiert la connaissance des échanges d'énergie et de masse entre la surface et l'atmosphère, dont l'évapotranspiration, qui représente la composante majeure du cycle hydrologique. Les avancées récentes, en termes de modélisation des Transferts Sol-Végétation-Atmosphère (TSVA) pour des couverts homogènes et d'assimilation des données de télédétection, principalement à l'échelle subrégionale, permettent d'envisager le passage à l'échelle régionale pour des couverts complexes de type cultures en rang. L'objectif de ce travail est de développer une modélisation versatile et de la caler par télédétection à l'échelle régionale sur un bassin versant viticole. Les investigations sont menées sur le bassin versant de la Peyne, dans le cadre de l'ORE OMERE. Une analyse bibliographique a permis de sélectionner un modèle TSVA à vocation régionale avec un nombre réduit de paramètres. L'implémentation de ce modèle est motivée par des objectifs de versatilité mais aussi d'inclusion dans une plateforme de simulation. Parallèlement, l'évapotranspiration a été spatialisée à l'échelle régionale par synergie des données télédétectées infrarouge thermique ASTER et Landsat. Les chroniques d'évapotranspiration obtenues sont ensuite utilisées pour caler le modèle TSVA. / In Mediterranean regions, decision making tools for water management require knowledge of water and mass exchanges between land surface and atmosphere, where evapotranspiration is the main component of the hydrological cycle. Recent advances, in terms of modeling and remote sensing, mainly at the subregional scale for homogeneous canopies, allow foreseeing the regional extent for complex landscapes such as row crops. This work aims to propose and calibrate a versatile modeling at the regional scale over a vineyard watershed, the calibration relying on remote sensing. A literature review allows selecting a SVAT model with a regional scope and a limited number of parameters. Model implementation is motivated by versatility and further inclusion into a simulation platform. Then, evapotranspiration is spatialized synergistically by using thermal infrared data from ASTER and Landsat remote sensors. Next, the time series obtained for evapotranspiration are used for calibrating the selected SVAT model. These investigations are conducted over the Peyne watershed, within the framework of the OMERE Observatory for environmental research.

Die vorliegende Arbeit hat zum Ziel, den Einfluss der Rückkopplung zwischen Landoberfläche und Atmosphäre auf den regionalen Wasserhaushalt abzuschätzen. Dazu erfolgen Modellsimulationen mit dem gekoppelten Vegetations-Grenzschichtmodell HIRVAC (HIgh Resolution Vegetation Atmosphere Coupler) für das Einzugsgebiet Sperrgraben (Bayerische Alpen). Im Ergebnis wird der Zusammenhang zwischen dem Entkopplungsfaktor Omega und der Verdunstung als Wasserhaushaltsgröße für einen festgelegten Zeitraum untersucht. Die Kombination eines vertikal hochaufgelösten Grenzschichtmodells (HUB) mit einem mechanistischen Photosynthesemodell (PSN6) im Modell HIRVAC ermöglicht eine detaillierte physikalische Beschreibung der turbulenten Austauschprozesse innerhalb der atmosphärischen Grenzschicht. Gleichzeitig werden die Wechselwirkungen zwischen Vegetation und Atmosphäre für jede Modellschicht innerhalb des Bestandes und zu jedem Modellzeitschritt simuliert. Die Definition des Entkopplungsfaktors erfordert die Festlegung eines geeigneten Referenzniveaus über der Vegetationsobergrenze zur Ermittlung der Widerstände gegen den turbulenten Austausch von Wärme und Feuchte. Die Bestimmung dieser Modellschichthöhe wird nach Untersuchungen zur Ausbildung der dynamischen Grenzschicht sowie der Vertikalprofile der Transportwiderstände und des Omega-Faktors vorgenommen. Die dabei erzielten Ergebnisse zum höhenabhängigen Verlauf des Entkopplungsfaktors über der Wiesenfläche und dem Fichtenbestand zeigen, dass mit dem Modell HIRVAC das unterschiedliche Kopplungsverhalten von kleinen Beständen mit glatter Oberfläche (Oberflächenrückkopplung) und hohen, rauen Beständen (Grenzschichtrückkopplung) qualitativ und auch quantitativ sehr gut wiedergegeben werden kann. Die Sensitivitätsstudien für die Landnutzungsarten Fichte und Wiese verdeutlichen den Einfluss veränderter Bestandesparameter wie Bestandeshöhe, LAI und Kronenschlussgrad auf den Entkopplungsfaktor und die Evapotranspiration. Sehr gut ersichtlich wird außerdem das unterschiedliche atmosphärische Turbulenzspektrum durch die Verwendung verschiedener Schließungsansätze im Modell und deren Einfluss auf die turbulenten Diffussionskoeffizienten. Die Ergebnisse werden mit dem Ziel der Ableitung einfacher Zusammenhänge zu Landschaftskennziffern parametrisiert. Zur Bereitstellung von flächenhaften Klimadaten wird das Modell HIRVAC mit einem Geographischen Informationssystem (ArcView) gekoppelt. Das Modell HIRGIS bietet eine geeignete Basis für die Regionalisierung von Klimagrößen im kleinräumig strukturierten Gelände. Auf der Grundlage der digitalen Gelände- und Landnutzungsdaten können topoklimatisch beeinflusste Größen, wie z.B. Einstrahlung, Temperatur, Strahlungsbilanz und Verdunstung für Gebiete flächendeckend berechnet werden. In den Ergebniswerten sind die Rückkopplungseffekte zwischen Bestand und Atmosphäre in aktueller Form enthalten. Außerdem entfallen Generalisierungseffekte, wie sie bei statistischen Übertragungsmethoden (Interpolation von Messwerten) auftreten. Durch die Möglichkeit der messwertunabhängigen Modellierung kann HIRGIS prinzipiell für Regionen mit anderem Gebietscharakter eingesetzt werden. Bei der Anwendung von HIRGIS auf das Einzugegebiet Sperrgraben wird allerdings deutlich, wie wichtig eine präzise Anpassung der Modellparametrisierung, insbesondere der Vegetation, an den Standort ist. Die erzeugten Karten zu den Klimagrößen liefern dem Nutzer eine gute Grundlage für klimatologische Gebietsinformationen. Eine Quantifizierung des Einflusses der Rückkopplung auf die Verdunstung im Einzugsgebiet Sperrgraben erweist sich für den untersuchten Zeitraum als schwierig. Die Ergebnisse zur Verdunstung zeigen trotzdem eine sehr gute Übereinstimmung mit Transpirationswerten aus Saftflussmessungen für Buche und Fichte im Einzugsgebiet Sperrgraben und decken sich mit den Transpirationswerten aus der Literatur für vergleichbare Bestände.

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As urbanization and global warming increase, an increasing importance is set on that urban planning processes take the possible effects of urban heat islands into account. In order to provide local city planners with site specific knowledge of the current situation in Stockholm, this study has explored the intra-urban heat island effect in Stockholm municipality by identifying major problem areas as well as addressing the statistical relationship between temperature and factors relating to land cover and urban planning strategies. Remotely sensed land surface temperature (LST) and the Swedish National Land Cover Database (NMD) have formed the data basis for the analyses that were carried out using GIS. The LST and land cover information have been extracted from randomly placed circle polygons in order to create a sample for the statistical analyses.  The results show that there exist differences in temperature within Stockholm municipality, both within the municipality as a whole and between various urban characters. In both cases, land cover is identified as an important, but not sole, factor to explain the differences. On land areas, artificial non-vegetated surfaces and forest is identified as the land cover classes of most relevance when it comes to the urban heat island effect. For both land cover classes, a strong correlation to LST is seen. Even though certain uncertainties and limitations are embedded in the data as well as in the method choices, the study can conclude in that the urban heat island effect is present in Stockholm municipality and that it can be derived from both land cover and urban characters. / I takt med att urbaniseringen och den globala uppvärmningen ökar kommer högre krav ställas på att stadsplaneringen tar hänsyn till de effekter som väntas uppstå kopplat till urbana värmeöar. I syfte att bistå lokala stadsplanerare med platsspecifik kunskap om den nuvarande situationen i Stockholm har den här studien utforskat intraurbana temperaturvariationer i Stockholms stad genom att identifiera de mest utsatta områdena samt genom att undersöka det statistiska sambandet mellan temperatur och faktorer kopplat till marktäcke och stadsutformning. Markens yttemperatur uppmätt från satellit och Nationella marktäckedata (NMD) har utgjort det främsta dataunderlaget för analyserna som genomförts med hjälp av GIS. Genom att extrahera information om yttemperatur och marktäcke från slumpmässigt placerade cirkelpolygoner kunde ett urval till de statistiska analyserna skapas.  Resultaten från studien visar att det finns skillnader i temperatur inom Stockholms stad, både inom kommunen som helhet och mellan olika stadsbyggnadskaraktärer. I båda fallen kan marktäcke identifieras som en viktig, men inte ensam, faktor till att förklara skillnaderna. På landområdena identifieras exploaterad mark och skog som de marktäcken med störst betydelse när det kommer till urbana värmeöar. För båda marktäckena ses i studien en stark korrelation till yttemperatur. Trots att vissa osäkerheter och begräsningar kan kopplas till både använd data och de metoder som använts kan slutsatsen att effekten från urbana värmeöar finns i Stockholms kommun dras. Dessutom kan konstateras att effekten kan härledas både till marktäcke och stadsbyggnadskaraktär.

科学研究費補助金 研究種目:基盤研究(A) 課題番号:14204044 研究代表者:安成哲三 研究期間:2002－2004年度

This research investigates soil respiration (Rs) in a boreal jack pine (Pinus banksiana Lamb.) fire scar chronosequence at Sharpsand Creek, Ontario, Canada. During two field campaigns in 2006 and 2007, Rs was measured in a chronosequence of fire scars in the range 0 to 59 years since fire. Mean Rs adjusted for soil temperature (Ts) and soil moisture (Ms) (Rs T,M) ranged from 0.56 μmol CO2/m2/s (32 years post fire) to 8.18 μmol CO2/m2/s (58 years post fire). Coefficient of variation (CV) of Rs adjusted for Ts and Ms ranged from 20% (16 years post fire) to 56% (58 years post fire). Across the field site, there was a significant exponential relationship between Rs adjusted for soil organic carbon (Cs) and Ts (P = 1.24*10-06; Q10 = 2.21) but no effect of Ms on Rs adjusted for Cs and Ts for the range 0.21 to 0.77 volumetric Ms (P = 0.702). Rs T,M significantly (P = 0.030) decreased after burning mature forest, though no significant (P > 0.1) difference could be detected between recently burned and unburned young forest. Rs was measured in recently burned boreal jack pine fire scar age categories that differed in their burn history and there was a significant difference in Rs T,M between previously 32 v 16 year old (P = 0.000) and previously 32 v 59 year old (P = 0.044) scars. There was a strong significant exponential increase in S R T,M with time since fire (r2 = 0.999; P = 0.006) for the chronosequence 0, 16 and 59 years post fire, and for all these age categories, Rs T,M was significantly different from one another (P < 0.05). The Joint UK Land Environment Simulator (JULES) was used to model vegetation re-growth over successional time at Sharpsand Creek, though it appeared to perform poorly in simulating leaf area index and canopy height. JULES probably over estimated heterotrophic Rs at Sharpsand Creek when Ts corrected simulated values were compared with measured Rs T,M. The results of this study contribute to a better quantitative understanding of Rs in boreal jack pine fire scars and will facilitate improvements in C cycle modelling. Further work is needed in quantifying autotrophic and heterotrophic contributions to soil respiration in jack pine systems, monitoring soil respiration for extended time periods after fire and improving the ability of JULES to simulate successional vegetation re-growth.