Dr Belen Marti-Cardona PhD MSc MEng CICCP
I am a civil engineer specialised in hydrological and hydraulic modelling, and in the exploitation of Earth observation data for hydrological and environmental engineering applications. My experience in Earth observation includes the use of SAR, thermal and optical imagery from space, aircraft and UAV platforms. In addition to my permanent academic role, in the last few years I have worked as a data scientist for companies on the analysis and integration of Earth observation data into their commercial products.
I graduated in MEng civil engineering from the Universitat Politecnica de Catalunya-BarcelonaTech (UPC) in 1997. My early career experience was in the construction of water-related infrastructure, followed by their design in the prestigious engineering company SENER, Spain. I then moved to the engineering firm, Jacobs in Reading, UK, where I worked on the numerical simulation of flood events and flood mapping, for projects commissioned by the Environment Agency. This experience provided me with priceless expertise in the state-of-the art hydrodynamic numerical modelling and digital mapping techniques. I became a chartered engineer by the ICE at that time.
Funded by the prestigious La Caixa fellowship, I completed a two-year MSc at the University of California, Davis, USA (2004). There, I had the privilege to learn from and work as a research assistant with world-leading scientists in the fields of hydrology and remote sensing.
Back in Barcelona I joined the UPC, Institut Flumen-CIMNE, as a research and teaching assistant. My involvement in an exciting project at the wildlife sanctuary of the Doñana wetlands gave me the unique opportunity to sample the site on countless (and sometimes wild) occasions, and to compare the sampled biophysical parameters with satellite SAR data and hydraulic modelling simulations. That work provided me with deep understanding of the SAR-soil-water-vegetation interaction, and made up my PhD too! My participation in other Flumen-CIMNE projects allowed me to exploit thermal and optical satellite and drone data, with a couple of nice competitive projects won and successfully completed in the way.
Life matters brought me to the UK, where I am currently a Lecturer in Water Resources Modelling and Remote Sensing. Soon after my arrival, I developed and promoted the launch of a module on GIS and Remote Sensing which is currently being taught. I also teach hydrology and hydraulics at different levels, and feel proud to have infected my enthusiasm for those disciplines to some of my students. I am also pleased with my holistic background as an engineer, which places me in an advantaged position to develop novel applications of remote sensing data.
My research interests involve innovative applications of remote sensing data to water resources problems, including sustainable use, impact of soil moisture on rainfall-runoff transformations, drought mapping and monitoring, evaluation of evapotranspiration water losses per land cover type, assessment of climatic and anthropogenic spatiotemporal impacts, and large scale near-real time crop and soil moisture mapping at the field scale (“field scale” being crucial). I am thrilled about implementing artificial intelligent analysis into these applications.
Areas of specialism
University roles and responsibilities
- Lecturer in Water Resources Management and Hydraulic Modelling (ENGM057)
- Lecturer in GIS and Remote Sensing (ENGM285)
- Lecturer in Environmental Engineering and Hydrology (ENG3177)
- Lecturer in Hydraulics and Environmental Quality (ENG2101)
The high spatial resolution images of the Ribarroja reservoir, acquired by the airborne hyperspectral TASI sensor, show spatial patterns which complemented the in-situ point measurements and contributed valuable data for validating the three-dimensional thermo-hydrodynamic model of the reservoir.
patterns of surface water temperature in the
Mequinenza reservoir, Spain, in 2016. We also estimated
its thermal impact on the river by comparing
upstream and downstream temperatures.
que se encuentran los camélidos. En las últimas décadas se ha observado la recesión de algunos bofedales y lagunas andinas. En la
cuenca del rio Locumba, Perú, se ha postulado que esta recesión puede estar ligada al consumo de los recursos hídricos para usos
agrícolas y mineros. El estudio que aquí se presenta utiliza imágenes satelitales para determinar la superficie de agua en las
principales lagunas naturales, así como el área ocupada por los bofedales y la superficie agrícola,desde la década de los 70 hasta la
actualidad. La tarea incluye además el cómputo de la evapotranspiración real en las áreas cultivadas de la cuenca a partir de dos
imágenes recientes correspondientes a los períodos seco y húmedo. La teledetección aporta de este modo una serie histórica de
datos espaciales cuantitativos de gran valor para determinar la variación de cubiertas naturales e investigar sus causas.
reservoirs, on the Ebro River. The spatially continuous information of these maps reveals the impact of the reservoir on
the river?s natural thermal gradient in two different periods of the year. The high spatial resolution images of the Ribarroja
reservoir, acquired by the airborne hyperspectral TASI sensor,
due to mixed land and water thermal pixels. In the case of the Landsat images, radiance mixing can also
affect pure water pixels due the cubic convolution resampling of the native thermal measurements. Some authors
recommended a general-purpose margin of two thermal pixels to the banks or a minimum river width of three
pixels, to avoid near bank effects in water temperature retrievals. Given the relatively course spatial resolution of
satellite thermal sensors, the three pixel margin severely restricts their application to temperature mapping in
many rivers. This study proposes a new algorithm to enhance the retrieval of stream surface temperature using
Landsat 8 thermal data, although it is also applicable to Landsat 7 and Landsat 5. The aim is not to perform a
subpixel radiance unmixing but to refine the selection of unmixed, reliable pixels for temperature mapping. For
this purpose, the spatial arrangement of native Landsat thermal pixels is approximated, and pure water pixels in
the downscaled thermal band are selected accordingly. The least-favourable cubic convolution near-bank radiance
mixing is simulated on image basis. Only pure thermal water pixels unaffected by the simulated worstcase
resampling are selected. The algorithm allowed retrieving water surface temperature in reaches down to
120m wide, clearly improving the existing three pixel, i.e. 300m for Landsat 8, recommendation. The enhancing
algorithm was applied to a reach in the Ebro River reach, Spain. It provided spatially distributed temperatures in
narrow parts, upstream and downstream of a wide reservoir, offering new insight of the overall impact of the
reservoir over the river thermal regime.
central part of the Andean mountain range, and it is one
of the lakes most affected by climate warming. Since surface
evaporation explains most of the lake?s water losses,
reliable estimates are paramount to the prediction of global
warming impacts on Lake Titicaca and to the region?s water
resource planning and adaptation to climate change. Evaporation
estimates were done in the past at monthly time
steps and using the four methods as follows: water balance,
heat balance, and the mass transfer and Penman?s equations.
The obtained annual evaporation values showed significant
dispersion. This study used new, daily frequency hydrometeorological
measurements. Evaporation losses were calculated
following the mentioned methods using both daily
records and their monthly averages to assess the impact of
higher temporal resolution data in the evaporation estimates.
Changes in the lake heat storage needed for the heat balance
method were estimated based on the morning water surface
temperature, because convection during nights results in a
well-mixed top layer every morning over a constant temperature
depth. We found that the most reliable method for determining
the annual lake evaporation was the heat balance
approach, although the Penman equation allows for an easier
implementation based on generally available meteorological
parameters. The mean annual lake evaporation was found
to be 1700mmyearÉ¹. This value is considered an upper
limit of the annual evaporation, since the main study period
was abnormally warm. The obtained upper limit lowers by
200mmyearÉ¹, the highest evaporation estimation obtained
previously, thus reducing the uncertainty in the actual value.
Regarding the evaporation estimates using daily and monthly
averages, these resulted in minor differences for all methodologies.