Temperate mixed forests are complex ecosystems composed of multiple vegetation types with very different physiological characteristics which are distributed over the landscape. This dissertation investigates the influence of these mixed plant landscapes on eddy-covariance flux data, and in particular, uses an ecohydrological model to study the influence of climate variability and insect infestation on a mixed forest at the Harvard Forest Long Term Ecological Research site in Massachusetts. There are significant seasonal and interannual variabilities in the extent and the orientation of the footprints of a flux tower (EMS-tower) as the Harvard Forest. The Gross Primary Productivity (GPP) flux was found to be largely dependent on the vegetation density during the green-up and senescence periods, but not during the mature period. Half of the interannual anomalies in the mature period GPP flux can be explained by the variation in the proportion of coniferous evergreen needleleaf forest (ENF) in the footprint. Every 1% decrease of ENF resulted in the increase of the GPP flux by 20 gC m-2. The spatially-distributed process-based Regional Hydro-Ecological Simulation System (RHESSys) model was implemented in two headwater catchments at the Harvard Forest to simulate water and carbon cycles from 1992 to 2008. Results were evaluated using field measurements such as streamflow and the GPP and evapotranspiration (ET) fluxes at two flux towers. The simulated annual GPP flux of the deciduous forest showed strong and significant long-term increases, six times higher than the GPP flux of the coniferous forest, while the increase in ET flux of both forests was small yet significant. The Harvard Forest was infested by Hemlock Woolly Adelgid (HWA) between 2004 and 2008, and although there has not yet been a significant increase in the total annual mortality, the small stature stands have started to die off by 5.7%. The HWA infestation has already resulted in an increased streamflow in the catchment dominated by hemlock stands (44% in area). In 2014, the increased annual streamflow was estimated as 81 mm using the RHESSys model with an embedded representation of the HWA-induced loss of water conductivity (calibrated using the Hemlock tower ET flux).

[EN] Water is the foundation for all biological life on Earth and one of the basic links between the biosphere and atmosphere. It is equally fundamental for humans and nature (Tolba, 1982). In an environment of growing scarcity and competition for water, increasing the understanding of all fluxes of the water cycle lies at the heart of the scientific community's goals. Traditionally, water and vegetation have been considered as different systems. However, it is necessary to take a holistic approach which considers the question of the water cycle in an integrated manner by taking into account both: blue water and green water (Birot et al., 2011). Around this idea, the new discipline Ecohydrology emerged in the early 20th century and, from then; it has grown steadily as shown by the increasing number of research lines and scientific papers related to this new field. However, most of the current hydrological models includes the vegetation as static parameter and not as state variable. There are some exceptions taking explicitly the vegetation as state variable but in those cases, the models' complexity and parametrical requirements increase substantially. In practice, we have to deal against the 'data scarcity - high parametrical requirements' issue really often. To reduce that issue, two strategies can be applied: (1) simplification of the models' conceptual scheme and (2) increase of data availability by incorporating new sources of information. In this thesis, we explored the use of a distributed parsimonious ecohydrological modelling (with low parametrical requirements) calibrated and validated exclusively with remote sensing data. First, we used the parsimonious ecohydrological model proposed by Pasquato et al. (2015) in an experimental plot located in a semi-arid Mediterranean forest. The results in this previous stage suggested that the model was able to adequately reproduce the dynamics of vegetation as well as the soil moisture variations. In other words, it has been shown that a parsimonious model with simple equations can achieve good results in general terms. But, as long as we applied the model at plot scale, the challenging task to reproduce the spatial variation of the vegetation and water cycle remained. To explore the spatio-temporal variation of the vegetation and the water cycle, the distributed version of the parsimonious ecohydrological model used previously was applied in a basin located in Kenya, concretely in the Upper Ewaso Ngiro River basin. In order to explore the potential applicability of the satellite data, we calibrated the model using exclusively the NDVI provided by NASA. First of all, we had to deal with the fact that we were not calibrating the model with only one temporal series such as historical streamflow as usual. In fact, satellite data is composed by one temporal series per pixel. We had to identify how to use spatio-temporal (and not only temporal) data during models' calibration and validation. In that sense, unfortunately, there is still a deep lack in literature. A methodology based on the use of Empirical Orthogonal Function analysis was proposed and successfully applied. This experience provided amazing and promising results. The obtained results demonstrated that: (1) satellite data of vegetation dynamics contains an extraordinary amount of information that can be used to implement ecohydrological models in scarce data regions; (2) the proposed semi-automatic calibration methodology works satisfactorily and it allows to incorporate spatio-temporal data in the model parameterization and (3) the model calibrated only using satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet point. It is important to highlight the positive consequences of this last result particularly in ungauged basins where the use of satellite data could be an alternative in order to obtain a proxy of the streamflow at outlet point. / [ES] El agua es la base de toda vida biológica en la Tierra y uno de los enlaces básicos entre la biosfera y la atmósfera. Es igualmente fundamental para los seres humanos y la naturaleza (Tolba, 1982). Tradicionalmente, el agua y la vegetación se han considerado como sistemas diferentes pero es claramente necesario tomar un enfoque holístico que considere la cuestión del ciclo del agua de una manera integrada, teniendo en cuenta tanto el agua azul como el agua verde (Birot et al., 2011). Alrededor de esta idea surgió la nueva disciplina llamada Ecohidrología a principios del siglo XX y desde entonces, no ha dejado de crecer tal y como demuestran el creciente aumento de líneas de investigación y publicaciones científicas relacionadas con este nuevo campo. Sin embargo, la mayoría de los modelos hidrológicos actuales incluye la vegetación como un parámetro estático y no como una variable de estado. Hay algunas excepciones que toman explícitamente la vegetación como variable de estado, pero en esos casos, la complejidad y el número de parámetros a determinar de los modelos aumentan sustancialmente. En la práctica, tenemos que hacer frente a la temible combinación de "escasez de datos - alto número de parámetros a determinar" con mucha frecuencia. Para reducir este problema, se pueden aplicar dos estrategias: (1) simplificar la complejidad conceptual de los modelos y así reducir el número de parámetros a calibrar, y/o (2) aumentar la disponibilidad de datos mediante la incorporación de nuevas fuentes de información. En esta tesis, hemos explorado el uso de un modelo ecohidrológico distribuido y parsimonioso (con pocos parámetros a determinar) que ha sido completamente calibrado y validado exclusivamente con datos de teledetección. En primer lugar, se utilizó el modelo ecohidrológico parsimonioso propuesto por Pasquato et al. (2015) en una parcela experimental situada en un bosque mediterráneo semiárido. Los resultados obtenidos en esta primera etapa de la tesis sugirieron que el modelo era capaz de reproducir adecuadamente la dinámica de la vegetación, así como las variaciones de humedad del suelo. En otras palabras, se pudo demostrar que un modelo parsimonioso con ecuaciones simples puede lograr buenos resultados en términos generales. Pero, como el modelo había sido aplicado a escala de parcela, todavía quedaba como tarea pendiente reproducir la variación espacial de la vegetación y del ciclo hidrológico. Para explorar la variación espacio-temporal de la vegetación y del ciclo del agua, se aplicó la versión distribuida del modelo ecohidrológico y parsimonioso utilizado previamente en una cuenca situada en Kenia. Con el fin de explorar la posible aplicabilidad de los datos de satélite, calibramos el modelo utilizando exclusivamente el NDVI proporcionada por la NASA. Se aplicó con éxito una metodología basada en el uso de la identificación de las funciones ortogonales empíricas (EOF por sus siglas en inglés). Esta última prueba proporcionó resultados prometedores: (1) los datos de satélite contienen una cantidad extraordinaria de información que puede ser usado para implementar modelos ecohidrológicos en regiones donde no se dispone de tal cantidad de información; (2) la metodología de calibración propuesta funciona satisfactoriamente y permite incorporar datos espacio-temporales en el proceso de parametrización del modelo, y (3) el modelo calibrado sólo con datos de satélite es capaz de reproducir tanto la dinámica espacio-temporal de la vegetación así como el caudal observado en el punto de desagüe de la cuenca. Es importante destacar las consecuencias positivas de este último resultado sobre todo en cuencas no aforadas, donde el uso de datos de satélite podría ser una alternativa para obtener una aproximación del recurso en el punto de desagüe. / [CA] L'aigua és la base de tota vida biològica a la Terra i un dels enllaços bàsics entre la biosfera i l'atmosfera. És igualment fonamental per als éssers humans i la naturalesa (Tolba, 1982). Tradicionalment, l'aigua i la vegetació s'han considerat com a sistemes diferents però és clarament necessari prendre un enfocament holístic que considere la qüestió del cicle de l'aigua d'una manera integrada, tenint en compte tant l'aigua blava com l'aigua verda (Birot et al., 2011). Al voltant d'aquesta idea va sorgir la nova disciplina anomenada Ecohidrología a principis del segle XX i des de llavors, no ha deixat de créixer tal com demostren el creixent augment de línies de recerca i publicacions científiques relacionades amb aquest nou camp. No obstant això, la majoria dels models hidrològics actuals inclou la vegetació com un paràmetre estàtic i no com una variable d'estat. Hi ha algunes excepcions que prenen explícitament la vegetació com a variable d'estat, però en aquests casos, la complexitat i el nombre de paràmetres a determinar dels models augmenten substancialment. En la pràctica, hem de fer front a la temible combinació de "escassetat de dades - alt nombre de paràmetres a determinar" amb molta freqüència. Per reduir aquest problema, es poden aplicar dues estratègies: (1) simplificar la complexitat conceptual dels models i així reduir el nombre de paràmetres a calibrar, i/o (2) augmentar la disponibilitat de dades mitjançant la incorporació de noves fonts d'informació. En aquesta tesi, hem explorat l'ús d'un model ecohidrològic distribuït i parsimoniòs (amb pocs paràmetres a determinar) que ha estat completament calibrat i validat exclusivament amb dades de teledetecció. En primer lloc, es va utilitzar el model ecohidrològic i parsimoniòs proposat per Pasquato et al. (2015) en una parcel·la experimental situada en un bosc mediterrani semi-àrid. Els resultats obtinguts en aquesta primera etapa de la tesi van suggerir que el model era capaç de reproduir adequadament la dinàmica de la vegetació, així com les variacions d'humitat del sòl. En altres paraules, es va poder demostrar que un model parsimoniòs amb equacions simples pot aconseguir bons resultats en termes generals. Però, com el model havia estat aplicat a escala de parcel·la, encara quedava com a tasca pendent reproduir la variació espacial de la vegetació i del cicle hidrològic. Per explorar la variació espai-temporal de la vegetació i del cicle de l'aigua, es va aplicar la versió distribuïda del model ecohidrològic i parsimoniòs utilitzat prèviament en una conca situada a Kenya. Al mateix temps, amb la finalitat d'explorar la possible aplicabilitat de les dades de satèl·lit, calibrem el model utilitzant exclusivament el NDVI proporcionat per la NASA. Es va aplicar amb èxit una metodologia basada en l'ús de la identificació de les funcions ortogonals empíriques (EOF per les seues sigles en anglès). Aquesta última prova va proporcionar resultats sorprenents i prometedors. De fet, els resultats obtinguts van demostrar que: (1) les dades de satèl·lit contenen una quantitat extraordinària d'informació que pot ser usada per implementar models ecohidrològics en regions on no es disposa de tal quantitat d'informació; (2) la metodologia de calibratge proposat funciona satisfactòriament i permet incorporar dades espai-temporals en el procés de parametrització del model, i (3) el model calibrat només amb dades de satèl·lit és capaç de reproduir tant la dinàmica espai-temporal de la vegetació així com el cabal observat en el punt de desguàs de la conca. És important destacar les conseqüències positives d'aquest últim resultat sobretot en conques no aforades, on l'ús de dades de satèl·lit podria ser una alternativa per obtenir una aproximació del recurs en el punt de desguàs. / Ruiz Pérez, G. (2016). On the use of satellite data to calibrate a parsimonious ecohydrological model in ungauged basins [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/72639

In recent years, the Soil-Plant-Atmosphere (SPA) continuum has faced unprecedented challenges due to anthropogenic modifications and climate change. Understanding the complex dynamics of this system in response to such changes is crucial for addressing contemporary environmental concerns. Albert Einstein's famous quote, "The measure of intelligence is the ability to change", resonates deeply throughout this doctoral thesis. This thesis aims to address the complex issue of SPA interactions by developing a comprehensive set of models capable of representing the intricate dynamics of this system. At the core of this research lies the integration of sophisticated descriptions of hydrological and plant biochemical processes into a novel ecohydrological model, GEOSPACE-1D (Soil Plant Atmosphere Continuum Estimator model in GEOframe). Through a combination of theoretical exploration, engineering methodologies, and empirical experiments, this thesis aims to advance our understanding of SPA interactions. The development of adaptable models, represents a significant contribution to the field. The thesis emphasizes the practical implications of employing models to analyze experimental data, thereby enhancing our comprehension of various phenomena. In conclusion, this thesis provides valuable insights into SPA interactions and lays the groundwork for future research and applications. By embracing the challenge of understanding and modeling the SPA continuum, this work contributes to the ongoing efforts to address environmental challenges and promote sustainable practices.

Doctor of Philosophy / Department of Biological & Agricultural Engineering / Stacy L. Hutchinson and Kyle R. Douglas-Mankin / Ecohydrology, a sub-discipline of hydrology, deals with the ecological impacts of and interactions with the hydrological cycle. Changes in hydrology of the Great Plains rivers, and their impacts on water quality, water resources, aquatic ecosystems, and fish species distributions have been documented. The major goal of this study was to develop and test methods to analyze watershed-level ecohydrological characteristics. The specific objectives were (a) to detect past temporal trends and spatial variability in hydrologic indices, (b) to evaluate the presence and/or extent of spatial and temporal relationships between climatic and ecohydrological variables and riverine historical data on fauna species density and distribution, and (c) to assess model calibration strategies for accurate ecohydrological indicator simulation. The Kansa River Basin (KRB), which has substantial land use, soil and climate variability, as well as variation in anthropogenic drivers (dams, diversions, reservoirs, etc.), was the focus of this study. Thirty eight hydrological indicators were generated using the indicators of hydrologic alterations software for 34 stations in the KRB using 50-year streamflow records and trend analysis using Mann-Kendall, Seasonal Kendall, and Sen’s slope estimator tests. Across the KRB a decreasing trend was evident for annual mean runoff, summer and autumn mean runoff, 30-day, 90-day minimum flows, and 1-day, 3-day, 7-day, 30-day and 90-day maximum flows. Most of the significant negative trends were observed in the High Plains ecoregion. Two hydrologic indicators, high-flow pulse count and mean summer streamflow, were significantly different in streams that lost two indicator fish species, indicating that changes in streamflow have altered the fish habitat of this region. The Soil and Water Assessment Tool (SWAT) biophysical model calibrated using a multi-objective framework (multi-site, multivariable and multi-criteria) was able to simulate most of the ecohydrological indicators at different hydrological conditions and scales. The SWAT model provided robust performance in simulating high-flow-rate ecohydrologic indicators. However ecohydrologic indicators performance was highly dependent on the level of calibration and parameterization. The effect of calibration and parameterization on ecohydrologic indicators performance varied between watersheds and among subwatersheds.

Northern Canadian peatlands contain vast deposits of carbon. It is with growing urgency that we seek a better understanding of their assimilative capacity. Assimilative capacity and peat accumulation in raised bogs are linked to primary productivity of resident Sphagnum species. Understanding moisture-mediated photosynthesis of Sphagnum spp. is central to understanding peat production rates. The relationship between depth to water table fluctuation and spectral reflectance of Sphagnum moss was investigated using multispectral imaging at a recovering raised bog on the southwest coast of British Columbia, Canada. Burns Bog is a temperate oceanic ombrotrophic bog. Three ecohydrological indicator species of moss were chosen for monitoring: S. capillifolium, S. papillosum, and S. cuspidatum. Three spectral vegetation indices (SVIs) were used to characterize Sphagnum productivity: the normalized difference vegetation index 660, the chlorophyll index, and the photochemical reflectance index. In terms of spectral sensitivity and the appropriateness of SVIs to species and field setting, we found better performance for the normalized difference vegetation index 660 in the discrimination of moisture mediated species-specific reflectance signals. The role that spatiotemporal scale and spectral mixing can have on reflectance signal fidelity was tested. We were specifically interested in the relationship between changes in the local water table and Sphagnum reflectance response, and whether shifting between close spatial scales can affect the statistical strength of this relationship. We found a loss of statistical significance when shifting from the species-specific cm2 scale to the spectrally mixed dm2 scale. This spatiospectral uncoupling of the moisture mediated reflectance signal has implications for the accuracy and reliability of upscaling from plot based measurements. In terms of species-specific moisture mediated reflectance signals, we were able to effectively discriminate between the three indicator species of Sphagnum along the hummock-to-hollow gradient. We were also able to confirm Sphagnum productivity and growth outside of the vascular growing season, establishing clear patterns of reflectance correlated with changes in the local moisture regime. The strongest relationships for moisture mediated Sphagnum productivity were found in the hummock forming species S. capillifolium. Each indicator Sphagnum spp. of peat has distinct functional traits adapted to its preferred position along the ecohydrological gradient. We also discovered moisture mediated and species-specific reflectance phenologies. These phenospectral characteristics of Sphagnum can inform future monitoring work, including the creation of a regionally specific phenospectral library. It’s recommended that further close scale multispectral monitoring be carried out incorporating more species of moss, as well as invasive and upland species of concern. Pervasive vascular reflectance bias in remote sensing products has implications for the reliability of peatland modelling. Avoiding vascular bias, targeted spectral monitoring of Sphagnum indicator species provides a more reliable measure for the modelling of peatland productivity and carbon assimilation estimates. / Graduate