Hector Nieto

Estimating evaporation is important when manag-
ing water resources and cultivating crops. Evaporation can be
estimated using land surface heat flux models and remotely
sensed land surface temperatures (LST), which have recently
become obtainable in very high resolution using lightweight
thermal cameras and Unmanned Aerial Vehicles (UAVs). In
this study a thermal camera was mounted on a UAV and ap-
plied into the field of heat fluxes and hydrology by concate-
nating thermal images into mosaics of LST and using these
as input for the two-source energy balance (TSEB) modelling
scheme. Thermal images are obtained with a fixed-wing
UAV overflying a barley field in western Denmark during
the growing season of 2014 and a spatial resolution of 0.20 m
is obtained in final LST mosaics. Two models are used: the
original TSEB model (TSEB-PT) and a dual-temperature-
difference (DTD) model. In contrast to the TSEB-PT model,
the DTD model accounts for the bias that is likely present
in remotely sensed LST. TSEB-PT and DTD have already
been well tested, however only during sunny weather condi-
tions and with satellite images serving as thermal input. The
aim of this study is to assess whether a lightweight thermal
camera mounted on a UAV is able to provide data of suf-
ficient quality to constitute as model input and thus attain
accurate and high spatial and temporal resolution surface en-
ergy heat fluxes, with special focus on latent heat flux (evapo-
ration). Furthermore, this study evaluates the performance of
the TSEB scheme during cloudy and overcast weather con-
ditions, which is feasible due to the low data retrieval alti-
tude (due to low UAV flying altitude) compared to satellite
thermal data that are only available during clear-sky condi-
tions. TSEB-PT and DTD fluxes are compared and validated
against eddy covariance measurements and the comparison
shows that both TSEB-PT and DTD simulations are in good
agreement with eddy covariance measurements, with DTD
obtaining the best results. The DTD model provides results
comparable to studies estimating evaporation with similar
experimental setups, but with LST retrieved from satellites
instead of a UAV. Further, systematic irrigation patterns on
the barley field provide confidence in the veracity of the spa-
tially distributed evaporation revealed by model output maps.
Lastly, this study outlines and discusses the thermal UAV im-
age processing that results in mosaics suited for model input.
This study shows that the UAV platform and the lightweight
thermal camera provide high spatial and temporal resolution
data valid for model input and for other potential applications
requiring high-resolution and consistent LST.

El objetivo de esta investigación es predecir la probabilidad de ocurrencia de incendios por causa natural (rayo) para la España peninsular mediante el ajuste de un modelo logístico. El modelo utiliza como variable dependiente los partes de incendios por causa de rayo y como variables independientes los índices meteorológicos (FFMC, DMC, 1h y 10h), las descargas de rayos, la topografía (pendiente, altitud y exposiciones), las coberturas forestales y los tipos de clima. Los resultados muestran que el DMC medio, los rayos totales, el clima oceánico y mediterráneo de montaña son las variables más explicativas en el proceso. El modelo ofrece una precisión global aceptable (64,12%). Esto demuestra que las condiciones climáticas, el grado de humedad del combustible y la actividad de tormentas están relacionadas con la probabilidad de ocurrencia de incendios.

... MIKE BASIN model was used to calculate water balance in Hong-Thai Binh river basin, whereMIKE NAM model was also used for inflow calculation in this basin. ... 3. Application of MIKE BASIN model to calculate the water balance in Hong-Thai Binh river basin 3.1. ...

Evapotranspiration is one of the key components of the water balance. Knowing its value is crucial for managing water resources, especially in areas with water scarcity. Despite that its determination at regional scales is a difficult task, since there is not a direct way for its measurement; remote sensing has proved to be a powerful tool to solve that issue. In this work the triangle method, based on the relation of the surface temperature with a vegetation index, was applied on Landsat5‐TM data over a heterogeneous patch of 5x5 km in the Henares river basin – part of the Tagus river basin in central Spain. On‐site measurements were carried out during the growing season of an experimental wheat field in 2010, including sensible heat flux (H) estimated with a scintillometer, soil heat flux (G), net radiation (Rn) and other typical meteorological data, which were used to obtain actual evapotranspiration (ET) rates at field scale, as a residual of the surface energy balance. A mask r...

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Fire risk indices are useful tools for fire prevention actions by fire managers. A fire ignition is either the result of lightning or human activities. In European Mediterranean countries most forest fires are due to human activities. However, lightning is still an important fire ignition source in some regions. Integration of lightning and human fire occurrence probability into fire risk indices would be necessary to have a complete picture of the causal agents and their relative importance in fire occurrence. We present two methods for the integration of lightning and human fire occurrence probability models at 1 × 1 km grid cell resolution in two regions of Spain: Madrid, which presents a high fire incidence due to human activities; and Aragón, one of the most affected regions in Spain by lightning-fires. For validation, independent fire ignition points were used to compute the Receiver Operating Characteristic (ROC)-Area Under de Curve (AUC) and the Mahalanobis Distance. Results in Madrid are satisfactory for the human fire occurrence probability model (AUC∼0.7) but less suitable for the lightning and the integrated models. In Aragón the fit for the human model is reasonable (AUC∼0.7) whereas for the integration methods is practically useless (AUC∼0.58).

The Dual Temperature Difference (DTD) model, introduced by Norman et al. (2000), uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST) to estimate surface energy fluxes. By using a time-differential temperature measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise) when surface fluxes are minimal, limiting application to data provided by geostationary satellites at sub-hourly temporal resolution. The DTD model has been applied primarily during the active growth phase of agricultural crops and rangeland vegetation grasses, and has not been rigorously evaluated during senescence or in forested ecosystems. In this paper we present modifications to the DTD model that enable applications using thermal observations from polar orbiting satellites, such as Terra and Aqua, with day and night overpass times over the area of interest. This allows the application of the DTD model in high latitude regions where large viewing angles preclude the use of geostationary satellites, and also exploits the higher spatial resolution provided by polar orbiting satellites. A method for estimating nocturnal surface fluxes and a scheme for estimating the fraction of green vegetation are developed and evaluated. Modification for green vegetation fraction leads to significantly improved estimation of the heat fluxes from the vegetation canopy during senescence and in forests. When the modified DTD model is run with LST measurements acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, generally satisfactory agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the Danish Hydrological ObsErvatory (HOBE) in western Denmark, indicating realistic patterns based on land use.