Change in the runoff pattern in the upper basin of the Tempisque River under climate change scenarios
Statistical downscaling of precipitation and temperature monthly time series from General Circulation Model's (GCM) was conducted via Principal Component Analysis (PCA), Canonical Correlation Analysis (CCA), and Delta Scheme. The downscaled time series served as input to a water balance model, and the change in the mean value of runoff was estimated for two different time horizons.
- Leitón-Montero, J.J (2011). Change in the runoff pattern in the upper basin of the Tempisque River under climate change scenarios. Licentiate thesis. The University of Costa Rica.
Report on hydrology and sediments for the Costa Rican river basins draining directly to the San Juan River
Conceptualizing, planning, and conducting hydrological and sedimentological studies in the San Juan river basin to determine the average liquid and solid discharge regimes and build detailed sediment budged for the main basin system using the Universal Soil Loss Equation (USLE).
- Technical counseling to the Costa Rican legal team during the oral proceedings before the International Court of Justice at The Hague, The Netherlands (April 2015).
Methodology for the determination of adaptive flow
Regionalization of hydrological descriptors (mean annual runoff, variance, and flow duration curves) in three Costa Rican basins using the hydrostochastic interpolation approach.
- Krasovskaia, I., Gottschalk, L., Leitón-Montero, J.J., Zuñiga-Mora, J.A. & Leblois, E. (2014). REGINA - Regionalisation of hydrological descriptors. In I. Krasovskaia & L. Gottschalk (Eds.), Compensatory Flow Phase 2: Methodology for the determination of adaptive flow - Final Report. (English edition, pp. 25-79). San José, Costa Rica: Costa Rican Electricity Institute.
Statistical analysis of multi-model climate projections with a Bayesian hierarchical model over Europe
A hierarchical Bayesian model was used to analyze the seasonal temperature and precipitation projections over the PRUDENCE regions of the CH2018 multi-model ensemble (RCP8.5). The implementation of this model expands the work done by Kerkhoff (2014), Tay (2016), and Künsch (2017) by evaluating both temperature and precipitation variables for every region-season combination.
Posterior distributions for the parameters associated with bias assumption coefficients, climatological means, inter-annual variability, and additive bias were estimated. Similarly, climate change estimates were calculated, for five different time horizons, with respect to 1995. A generalized variation pattern was found for temperature along all the region-season combinations analyzed, while season-dependent and region-dependent patterns were identified for precipitation.
Reduction of the absolute additive bias due to dynamical scaling was evaluated by comparing the bias components associated with the RCM-GCM chains and their corresponding drivers. Results were evaluated in terms of the probabilities of reducing at least 20% in the said component, and region-season-chain combinations were classified based on this value.
- Leitón-Montero, J.J. (2017). Statistical analysis of multi-model climate projections with a Bayesian hierarchical model over Europe. Master thesis. ETH Zürich