The present Thesis deals with understanding, measuring and modelling epidemic cholera. The relevance of the endeavour stems from the fact that mathematical epidemiology, properly guided by model-guided field validation, is a reliable and powerful tool to monitor and predict ongoing epidemics in time for action, and to save lives through evaluation of the effectiveness of mitigation policies or the deployment of medical staff and supplies. In recent years, waterborne diseases – and cholera in particular – have consolidated their role as a major threat for developing countries, where sanitation conditions are poor and the vulnerability to extreme events is highest. Several important features controlling the dynamics of occurrence and spreading of the disease in a region are studied in the present Thesis, from both theoretical and experimental perspective. Understanding the basic processes that regulate cholera infection is key to build reliable prediction tools. In this Thesis several driving mechanisms of cholera are investigated, with the objective of connecting together hydro-climatology, ecology and epidemiology in a comprehensive framework. First, the role of water volume fluctuations is analyzed partly through a bifurcation study in a mostly theoretical assessment. Such work is then particularized in a field campaign carried out in rural Bangladesh, where hydro-climatological variables and Vibrio cholerae concentrations have been monitored for more than a year in one of the ponds constituting the local water reservoir. Concomitantly, a procedure for the detection of Vibrio cholerae, based on flow cytometry, is tested in the field. Further emphasis is also given to the role of human mobility in disseminating the disease among different communities. In particular, the contribution of human mobility in the dispersal of vibrios along the hydrologic network is specifically analyzed. All the knowledge collected in these studies is then used to add essential details to a modeling framework that is applied to the dramatic case of the Haiti epidemic. A spatially explicit model, taking into account both hydrological transport and human mobility, is developed to simulate the spreading of the disease since its onset. It is also shown that the resurgence of the disease, coinciding with the rainy season of June-July 2011, can only be reproduced if hydrological forcings are considered. The framework is tested by forcing it with synthetic rainfall scenarios and projecting epidemiological outputs. It is shown that the model can quantify correctly the number of cases in a given time span, even when calibrated with limited information. This result allows then to use it as a tool to assess a priori the effectiveness of intervention policies, such as vaccination and sanitation. The effect of these two is tested both in the short- and in the long-term, with different results. Such endeavour represents the ultimate goal of the work presented in this Thesis – albeit further effort is needed to link together public health management and mathematical epidemiology in this field.