Cristina Aguilar

Bio: Cristina Aguilar is an academic researcher from University of Córdoba (Spain). The author has contributed to research in topics: Hydrological modelling & Normalized Difference Vegetation Index. The author has an hindex of 11, co-authored 46 publications receiving 513 citations. Previous affiliations of Cristina Aguilar include Universidade Federal de Ouro Preto & University of Barcelona.

Topographic effects on solar radiation distribution in mountainous watersheds and their influence on reference evapotranspiration estimates at watershed scale.

Abstract: . Distributed energy and water balance models require time-series surfaces of the climatological variables involved in hydrological processes. Among them, solar radiation constitutes a key variable to the circulation of water in the atmosphere. Most of the hydrological GIS-based models apply simple interpolation techniques to data measured at few weather stations disregarding topographic effects. Here, a topographic solar radiation algorithm has been included for the generation of detailed time-series solar radiation surfaces using limited data and simple methods in a mountainous watershed in southern Spain. The results show the major role of topography in local values and differences between the topographic approximation and the direct interpolation to measured data (IDW) of up to +42% and −1800% in the estimated daily values. Also, the comparison of the predicted values with experimental data proves the usefulness of the algorithm for the estimation of spatially-distributed radiation values in a complex terrain, with a good fit for daily values (R2 = 0.93) and the best fits under cloudless skies at hourly time steps. Finally, evapotranspiration fields estimated through the ASCE-Penman-Monteith equation using both corrected and non-corrected radiation values address the hydrologic importance of using topographically-corrected solar radiation fields as inputs to the equation over uniform values with mean differences in the watershed of 61 mm/year and 142 mm/year of standard deviation. High speed computations in a 1300 km2 watershed in the south of Spain with up to a one-hour time scale in 30 × 30 m2 cells can be easily carried out on a desktop PC.

Generating reference evapotranspiration surfaces from the Hargreaves equation at watershed scale

Abstract: . In this study, Hargreaves' formulation is considered to be appropriate for the water and energy balance at a daily scale due to its simplicity of application once the distributed values of temperature are available at cell scale. However, the coefficient of the Hargreaves equation must be previously calibrated. The interplay of different factors at different temporal scales became evident in the calibration process at the local scale of weather stations. The best fits against daily estimates by ASCE-PM were achieved when differentiating between the wet and the dry season. For the spatial distribution of Hargreaves coefficient at watershed scale, a regionalization in the area around each weather station was proposed in terms of areas of influence. The best results at watershed scale were obtained after a spatial correction for alpine areas, when the average of the difference cell by cell between ASCE-PM and Hargreaves's distributed daily estimates were 0.02 and 0.15 mm day−1 for the wet and the dry seasons, respectively. In all the cases, the best interpolation results were obtained using C-I (calculate and interpolate) procedures.

P–T–t–d evolution of orogenic middle crust of the Roc de Frausa Massif (Eastern Pyrenees): a result of horizontal crustal flow and Carboniferous doming?

Abstract: Structural, petrological and textural studies are combined with phase equilibria modelling of metapelites from different structural levels of the Roc de Frausa Massif in the Eastern Pyrenees. The pre-Variscan lithological succession is divided into the Upper, Intermediate and Lower series by two orthogneiss sheets and intruded by Variscan igneous rocks. Structural analysis reveals two phases of Variscan deformation. D1 is marked by tight to isoclinal small-scale folds and an associated flat-lying foliation (S1) that affects the whole crustal section. D2 structures are characterized by tight upright folds facing to the NW with steep NE–SW axial planes. D2 heterogeneously reworks the D1 fabrics, leading to an almost complete transposition into a sub-vertical foliation (S2) in the high-grade metamorphic domain. All structures are affected by late open to tight, steeply inclined south-verging NW–SE folds (F3) compatible with steep greenschist facies dextral shear zones of probable Alpine age. In the micaschists of the Upper series, andalusite and sillimanite grew during the formation of the S1 foliation indicating heating from 580 to 640 °C associated with an increase in pressure. Subsequent static growth of cordierite points to post-D1 decompression. In the Intermediate series, a sillimanite–biotite–muscovite-bearing assemblage that is parallel to the S1 fabric is statically overgrown by cordierite and K-feldspar. This sequence points to ~1 kbar of post-D1 decompression at 630–650 °C. The Intermediate series is intruded by a gabbro–diorite stock that has an aureole marked by widespread migmatization. In the aureole, the migmatitic S1 foliation is defined by the assemblage biotite–sillimanite–K-feldspar–garnet. The microstructural relationships and garnet zoning are compatible with the D1 pressure peak at ~7.5 kbar and ~750 °C. Late- to post-S2 cordierite growth implies that F2 folds and the associated S2 axial planar leucosomes developed during nearly isothermal decompression to 5 kbar at suprasolidus conditions. Almost complete consumption of garnet and late cordierite growth points to post-D2 equilibration at <4 kbar and <750 °C. The early metamorphic history associated with the S1 fabric is interpreted as a result of horizontal middle crustal flow associated with progressive heating and possible burial. The upright F2 folding and S2 foliation are associated with a pressure decrease coeval with the intrusion of mafic magma at mid-crustal levels. The D2 tectono-metamorphic evolution may be explained by a crustal-scale doming associated with emplacement of mafic magmas into the core of the dome.

Climate Change 2007: Impacts, Adaptation and Vulnerability.

Abstract: Impatti, adattamento e vulnerabilita Le cause e le responsabilita dei cambiamenti climatici sono state trattate sul numero di ottobre della rivista Cda. Approfondiamo l’argomento presentando il documento: “Cambiamenti climatici 2007: impatti, adattamento e vulnerabilita” votato ad aprile 2007 dal secondo gruppo di lavoro del Comitato Intergovernativo sui Cambiamenti Climatici (Intergovernmental Panel on Climate Change). Si tratta del secondo di tre documenti che compongono il quarto rapporto sui cambiamenti climatici.

Climate change 2014 - Mitigation of climate change

Abstract: The talk with present the key results of the IPCC Working Group III 5th assessment report. Concluding four years of intense scientific collaboration by hundreds of authors from around the world, the report responds to the request of the world's governments for a comprehensive, objective and policy neutral assessment of the current scientific knowledge on mitigating climate change. The report has been extensively reviewed by experts and governments to ensure quality and comprehensiveness.

Generalized joint attribute modeling for biodiversity analysis: median-zero, multivariate, multifarious data

Abstract: Probabilistic forecasts of species distribution and abundance require models that accommodate the range of ecological data, including a joint distribution of multiple species based on combinations of continuous and discrete observations, mostly zeros. We develop a generalized joint attribute model (GJAM), a probabilistic framework that readily applies to data that are combinations of presence-absence, ordinal, continuous, discrete, composition, zero-inflated, and censored. It does so as a joint distribution over all species providing inference on sensitivity to input variables, correlations between species on the data scale, prediction, sensitivity analysis, definition of community structure, and missing data imputation. GJAM applications illustrate flexibility to the range of species-abundance data. Applications to forest inventories demonstrate species relationships responding as a community to environmental variables. It shows that the environment can be inverse predicted from the joint distribution of species. Application to microbiome data demonstrates how inverse prediction in the GJAM framework accelerates variable selection, by isolating effects of each input variable's influence across all species.

Mapping Groundwater Potential Using a Novel Hybrid Intelligence Approach

Abstract: Identifying areas with high groundwater potential is important for groundwater resources management. The main objective of this study is to propose a novel classifier ensemble method, namely Random Forest Classifier based on Random Subspace Ensemble (RS-RF), for groundwater potential mapping (GWPM) in Qorveh-Dehgolan plain, Kurdistan province, Iran. A total of 12 conditioning factors (slope, aspect, elevation, curvature, stream power index (SPI), topographic wetness index (TWI), rainfall, lithology, land use, normalized difference vegetation index (NDVI), fault density, and river density) were selected for groundwater modeling. The least square support vector machine (LSSVM) feature selection method with a 10-fold cross-validation technique was used to validate the predictive capability of these conditioning factors for training the models. The performance of the RS-RF model was validated using the area under receiver operating characteristic curve (AUROC), success and prediction rate curves, kappa index, and several statistical index-based measures. In addition, Friedman and Wilcoxon signed-rank tests were used to assess statistically significant level among the new model with the state-of-the-art soft computing benchmark models, such as random forest (RF), logistic regression (LR) and naive Bayes (NB). Results showed that the new hybrid model of RS-RF had a very high predictive capability for groundwater potential mapping and exhibited the best performance among other benchmark models (LR, RF, and NB). Results of the present study might be useful to water managers to make proper decisions on the optimal use of groundwater resources for future planning in the critical study area.