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Jose-Luis Molina   Professor  Senior Scientist or Principal Investigator 
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Jose-Luis Molina published an article in December 2018.
Research Keywords & Expertise
0 A
0 Bayesian networks
0 Water Framework Directive
0 water management
0 stochastic
Top co-authors See all
Diego Gonzalez-Aguilera

128 shared publications

TIDOP Group, Department of Cartographic and Land Engineering, University of Salamanca, Higher Polytechnic School of Avila, Avila, Spain

Pablo Rodríguez-Gonzálvez

82 shared publications

Department of Mining Technology, Topography and Structures, Universidad de León, Avda. Astorga, s/n, 24401 Ponferrada (León), Spain

Agustí Pérez-Foguet

60 shared publications

Engineering Sciences and Global Development (EScGD), Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya · BarcelonaTech (UPC), Jordi Girona, 1-3, 08034 Barcelona, Spain

Janez Sušnik

21 shared publications

Integrated Water Systems and Governance Department, IHE Delft Institute for Water Education, 2601 DA Delft, The Netherlands

Rocío Ballesteros

10 shared publications

Regional Centre of Water Research (CREA), Castilla-La Mancha University, Albacete, Spain

Publication Record
Distribution of Articles published per year 
(2009 - 2018)
Total number of journals
published in
Publications See all
Article 0 Reads 0 Citations Shape Optimization of Double-Arch Dams by Using Parameters Obtained Through Bayesian Estimators Enrico Zacchei, José Luis Molina Published: 18 December 2018
Iranian Journal of Science and Technology, Transactions of Civil Engineering, doi: 10.1007/s40996-018-0223-z
DOI See at publisher website
CONFERENCE-ARTICLE 16 Reads 0 Citations <strong>CAUSAL REASONING: AN ADAPTIVE/PREDICTIVE APPROACH FOR RUNOFF TEMPORAL BEHAVIOUR OF HIGH DEPENDENCE RIVERS</stron... Jose-Luis Molina, Santiago Zazo, Ana-María Martín Published: 15 November 2018
Proceedings of 3rd International Electronic Conference on Water Sciences (ECWS-3), doi: 10.3390/ECWS-3-05810
DOI See at publisher website ABS Show/hide abstract

A significant spatio-temporal alteration of traditional patterns for hydrological components´ behavior is currently being observed. In this sense, a higher variability, more frequent and unpredictable extreme events (rainfall, flood and drought) occur in many areas. This is primarily due to global warming, which is producing a growing variability and uncertainty of water systems and specially, rivers´ runoff. The understanding of these modifications and, consequently, this adaptive rivers´ behavior is not trivial and requires new approaches incorporating dynamic and stochastic approaches. Causal Reasoning, supported by Bayesian modelling is a powerful stochastic approach to extract the time dependent logical structure that inherently underlies hydrological series. The river basin memory is dynamically and stochastically characterized in terms of the runoff dependence strength over the time. In this study, by means of causality, the Temporally Conditioned/Non-conditioned runoff (TCR/TNCR) fractions are identified and quantified. This research has important implications and applications, such as to the knowledge of the historical adaptive rivers´ behavior, or to reservoirs´ dimensioning optimization. This approach has been successfully applied to an unregulated river basin in Spain with a very high dependence temporal runoff behavior, within Júcar river basin (Mijares). Having a tool that could dynamically adjust the reservoir and/or channel capacity may help for reaching the optimal design and dimensioning of hydraulic infrastructures, which involves a lot of economic savings. Further work will largely comprise the introduction of the spatial dimension so the tool can integrated a full spatio-temporal analysis. Furthermore, the analyzed runoff behavior trends will be further used for building predictive models.

Article 2 Reads 2 Citations Flood Hazard Assessment Supported by Reduced Cost Aerial Precision Photogrammetry Santiago Zazo, Pablo Rodríguez-Gonzálvez, José-Luis Molina, ... Published: 01 October 2018
Remote Sensing, doi: 10.3390/rs10101566
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Increasing flood hazards worldwide due to the intensification of hydrological events and the development of adaptation-mitigation strategies are key challenges that society must address. To minimize flood damages, one of the crucial factors is the identification of flood prone areas through fluvial hydraulic modelling in which a detailed knowledge of the terrain plays an important role for reliable results. Recent studies have demonstrated the suitability of the Reduced Cost Aerial Precision Photogrammetry (RC-APP) technique for fluvial applications by accurate-detailed-reliable Digital Terrain Models (DTMs, up to: ≈100 point/m2; vertical-uncertainty: ±0.06 m). This work aims to provide an optimal relationship between point densities and vertical-uncertainties to generate more reliable fluvial hazard maps by fluvial-DTMs. This is performed through hydraulic models supported by geometric models that are obtained from a joint strategy based on Structure from Motion and Cloth Simulation Filtering algorithms. Furthermore, to evaluate vertical-DTM, uncertainty is proposed as an alternative approach based on the method of robust estimators. This offers an error dispersion value analogous to the concept of standard deviation of a Gaussian distribution without requiring normality tests. This paper reinforces the suitability of new geomatic solutions as a reliable-competitive source of accurate DTMs at the service of a flood hazard assessment.
Article 0 Reads 1 Citation HidroMap: A New Tool for Irrigation Monitoring and Management Using Free Satellite Imagery Laura Piedelobo, Damián Ortega-Terol, Susana Del Pozo, David... Published: 15 June 2018
ISPRS International Journal of Geo-Information, doi: 10.3390/ijgi7060220
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Proper control and planning of water resource use, especially in those catchments with large surface, climatic variability and intensive irrigation activity, is essential for a sustainable water management. Decision support systems based on useful tools involving main stakeholders and hydrological planning offices of the river basins play a key role. The free availability of Earth observation products with high temporal resolution, such as the European Sentinel-2B, has allowed us to combine remote sensing with cadastral and agronomic data. This paper introduces HidroMap to the scientific community, an open source tool as a geographic information system (GIS) organized in two different modules, desktop-GIS and web-GIS, with complementary functions and based on PostgreSQL/PostGIS database. Through an effective methodology HidroMap allows monitoring irrigation activity, managing unregulated irrigation, and optimizing available fluvial surveillance resources using satellite imagery. This is possible thanks to the automatic download, processing and storage of satellite products within field data provided by the River Surveillance Agency (RSA) and the Hydrological Planning Office (HPO). The tool was successfully validated in Duero Hydrographic Basin along the 2017 summer irrigation period. In conclusion, HidroMap comprised an important support tool for water management tasks and decision making tackled by Duero Hydrographic Confederation which can be adapted to any additional need and transferred to other river basin organizations.
Article 0 Reads 0 Citations A novel planning approach for the water, sanitation and hygiene (WaSH) sector: The use of object-oriented bayesian netwo... R. Giné-Garriga, D. Requejo, J.L. Molina, A. Pérez-Foguet Published: 01 May 2018
Environmental Modelling & Software, doi: 10.1016/j.envsoft.2018.01.021
DOI See at publisher website
Article 1 Read 3 Citations Assessment of Temporally Conditioned Runoff Fractions in Unregulated Rivers José-Luis Molina, Santiago Zazo Published: 01 May 2018
Journal of Hydrologic Engineering, doi: 10.1061/(asce)he.1943-5584.0001645
DOI See at publisher website