Analysis Of Semi-Distributed And Global Hydrological Models In The Central Tropical Basins Of The Gulf Of Mexico To The Effects Of Extreme Hydrometeorological Phenomena

In the last years extreme hydrometeorological phenomena have increased in number and intensity affecting the inhabitants of various regions, an example of these effects are the central basins of the Gulf of Mexico (CBGM) that they have been affected by 55.2% with floods and especially the state of Veracruz (1999-2013), leaving economic, social and environmental losses. Mexico currently lacks sufficient hydrological studies for the measurement of volumes in rivers, since is convenient to create a hydrological model (HM) suited to the quality and quantity of the geographic and climatic information that is reliable and affordable. Therefore this research compares the semi-distributed hydrological model (SHM) and the global hydrological model (GHM), with respect to the volumes of runoff and achieve to predict flood areas, furthermore, were analyzed extreme hydrometeorological phenomena in the CBGM, by modeling the Hydrologic Modeling System (HEC-HMS) which is a SHM and the Modèle Hydrologique Simplifié à I\u27Extrême (MOHYSE) which is a GHM, to evaluate the results and compare which model is suitable for tropical conditions to propose public policies for integrated basins management and flood prevention. Thus it was determined the temporal and spatial framework of the analyzed basins according to hurricanes and floods. It were developed the SHM and GHM models, which were calibrated, validated and compared the results to identify the sensitivity to the real model. It was concluded that both models conform to tropical conditions of the CBGM, having MOHYSE further approximation to the real model. Worth mentioning that in Mexico there is not enough information, besides there are no records of MOHYSE use in Mexico, so it can be a useful tool for determining runoff volumes. Finally, with the SHM and the GHM were generated climate change scenarios to develop risk studies creating a risk map for urban planning, agro-hydrological and territorial organization

Using grey clustering to evaluate nitrogen pollution in estuaries with limited data

[EN] Many techniques exist for the evaluation of nutrient pollution, but most of them require large amounts of data and are difficult to implement in countries where accurate water quality information is not available. New methods tomanage subjectivity, inaccuracy or variability are required in such environments so that watermanagers can invest the scarce economic resources available to restore themost vulnerable areas. We propose a new methodology based on grey clusteringwhich classifies monitoring sites according to their need for nitrogen pollution management when only small amounts of data are available. Grey clustering focuses on the extraction of information with small samples, allowing management decision making with limited data. We applied the entropy-weight method, based on the concept of information entropy, to determine the clustering weight of each criterion used for classification. In order to reference the pollution level to the anthropogenic pressure, we developed two grey indexes: the Grey Nitrogen Management Priority index (GNMP index) to evaluate the relative need for nitrogen pollution management based on a spatiotemporal analysis of total nitrogen concentrations, and the Grey Land Use Pollution index (GLUP index), which evaluates the anthropogenic pressures of nitrogen pollution based on land use. Both indexes were then confronted to validate the classification. We applied the developedmethodology to eight estuaries of the SouthernGulf ofMexico associated to beaches,mangroves and other coastal ecosystems which may be threatened by the presence of nitrogen pollution. The application of the new method has proved to be a powerful tool for decision making when data availability and reliability are limited. This method could also be applied to assess other pollutants.This work was supported by Erasmus Mundus -MAYANET Grant Agreement Number 2014-0872/001-001, funded with support of the European Commission, and an Excellence Scholarship awarded by the Mexican Government through the Mexican Agency for International Development Cooperation (AMEXCID). The Mexican National Water Commission provided the field data.Temino-Boes, R.; Romero-Lopez, R.; Ibarra-Zavaleta, SP.; Romero Gil, I. (2020). Using grey clustering to evaluate nitrogen pollution in estuaries with limited data. The Science of The Total Environment. 722:1-12. https://doi.org/10.1016/j.scitotenv.2020.137964S112722Adame, M. F., Najera, E., Lovelock, C. E., & Brown, C. J. (2018). Avoided emissions and conservation of scrub mangroves: potential for a Blue Carbon project in the Gulf of California, Mexico. Biology Letters, 14(12), 20180400. doi:10.1098/rsbl.2018.0400Adriaenssens, V., Baets, B. D., Goethals, P. L. M., & Pauw, N. D. 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Distributed Hydrological Modeling: Determination of Theoretical Hydraulic Potential & Streamflow Simulation of Extreme Hydrometeorological Events

The progressive change in climatic conditions worldwide has increased frequency and severity of extreme hydrometeorological events (EHEs). México is an example that has been affected by the occurrence of EHE leading to economic, social, and environmental losses. The objective of this research was to apply a Canadian distributed hydrological model (DHM) to tropical conditions and to evaluate its capacity to simulate flows in a basin in the central Gulf of Mexico. In addition, the DHM (once calibrated and validated) was used to calculate the theoretical hydraulic power (THP) and the performance to predict streamflow before the presence of an EHE. The results of the DHM show that the goodness of fit indicators between the observed and simulated flows in the calibration process Nash-Sutcliffe efficiency (NSE) = 0.83, ratio of the root mean square error to the standard deviation of measured data (RSR) = 0.41, and percent bias (PBIAS) = −4.3) and validation (NSE = 0.775, RSR = 0.4735, and PBIAS = 2.45) are satisfactory. The DHM showed its applicability: determination of THP showed that the mean flows are in synchrony with the order of the river reaches and streamflow simulation of 13 EHEs (NSE = 0.78 ± 0.13, RSR = 0.46 ± 0.14 and PBIAS = −0.48 ± 7.5) confirmed a reliable efficiency. This work can serve as a tool for identifying vulnerabilities before floods and for the rational and sustainable management of water resources