Hydrognomon – open source software for the analysis of hydrological data

S. Kozanis, A. Christofides, N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Hydrognomon – open source software for the analysis of hydrological data, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 12419, doi:10.13140/RG.2.2.21350.83527, European Geosciences Union, 2010.



Hydrognomon is a software tool for the processing of hydrological data. It is an open source application running on standard Microsoft Windows platforms, and it is part of the openmeteo.org framework. Data are imported through standard text files, spreadsheets or by typing. Standard hydrological data processing techniques include time step aggregation and regularization, interpolation, regression analysis and infilling of missing values, consistency tests, data filtering, graphical and tabular visualisation of time series, etc. It supports several time steps, from the finest minute scales up to decades; specific cases of irregular time steps and offsets are also supported. The program also includes common hydrological applications, such as evapotranspiration modelling, stage-discharge analysis, homogeneity tests, areal integration of point data series, processing of hydrometric data, as well as lumped hydrological modelling with automatic calibration facilities. Here the emphasis is given on the statistical module of Hydrognomon, which provides tools for data exploration, fitting of distribution functions, statistical prediction, Monte-Carlo simulation, determination of confidence limits, analysis of extremes, and construction of ombrian (intensity-duration-frequency) curves. Hydrognomon is available for download from http://hydrognomon.org/.

PDF Full text:

See also: http://dx.doi.org/10.13140/RG.2.2.21350.83527

Our works that reference this work:

1. A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, A parametric model for potential evapotranspiration estimation based on a simplified formulation of the Penman-Monteith equation, Evapotranspiration - An Overview, edited by S. Alexandris, 143–165, doi:10.5772/52927, InTech, 2013.
2. A. Tegos, N. Malamos, and D. Koutsoyiannis, A parsimonious regional parametric evapotranspiration model based on a simplification of the Penman-Monteith formula, Journal of Hydrology, 524, 708–717, doi:10.1016/j.jhydrol.2015.03.024, 2015.
3. A. Tegos, H. Tyralis, D. Koutsoyiannis, and K. H. Hamed, An R function for the estimation of trend signifcance under the scaling hypothesis- application in PET parametric annual time series, Open Water Journal, 4 (1), 66–71, 6, 2017.
4. E. Dodangeh, K. Shahedi, K. Solaimani, and P. Kossieris, Usability of the BLRP model for hydrological applications in arid and semi-arid regions with limited precipitation data, Modeling Earth Systems and Environment, 2017.

Other works that reference this work (this list might be obsolete):

1. #Sebastianelli, S., M. Giglioni, C. Mineo, and S. Magnald, On the hydrologic-hydraulic revaluation of large dams, International Conference of Numerical Analysis and Applied Mathematics 2015 (ICNAAM 2015), 1738, 430003-1–430003-4, doi:10.1063/1.4952216, 2016.
2. #Mineo, C., S. Sebastianelli, L. Marinucci, and F. Russo, Assessment of the watershed DEM mesh size influence on a large dam design hydrograph, AIP Conference Proceedings, 1738, 430003, 2016.
3. Tsitroulis, I., K. Voudouris, A. Vasileiou, C. Mattas, M. Sapountzis, and F. Maris, Flood hazard assessment and delimitation of the likely flood hazard zones of the upper part in Gallikos river basin, Bulletin of the Geological Society of Greece, 50(2), 995-1005, doi:10.12681/bgsg.11804, 2016.
4. López J. J., O. Delgado, and M. A. Campo, Determination of the IDF curves in Igueldo-San Sebastián. Comparison of different methods, Ingeniería del Agua, 22(4), 209-223, doi:10.4995/Ia.2018.9480, 2018.
5. Nyaupane, N., B. Thakur, A. Kalra, and S. Ahmad, Evaluating future flood scenarios using CMIP5 climate projections, Water, 10, 1866, doi:10.3390/w10121866, 2018.
6. Vargas, M. M., S. Beskow, T. L. Caldeira, L. de Lima Corrêa, and Z. Almeida da Cunha, SYHDA – System of Hydrological Data Acquisition and Analysis, Brazilian Journal of Water Resources, 24, e11, doi:10.1590/2318-0331.241920180152, 2019.
7. Houessou-Dossou, E. A. Y., J. M. Gathenya, M. Njuguna, and Z. A. Gariy, Flood frequency analysis using participatory GIS and rainfall data for two stations in Narok Town, Kenya, Hydrology, 6(4), 90, doi:10.3390/hydrology6040090, 2019.
8. López Díez, A., P. Máyer Suárez, J. Díaz Pacheco, and P. Dorta Antequera, Rainfall and flooding in coastal tourist areas of the Canary Islands (Spain), Atmosphere, 10(12), 809, doi:10.3390/atmos10120809, 2019.
9. Pamirbek, M., X. Chen, S. Aher, A. Salamat, P. Deshmukh, and C. Temirbek, Analysis of discharge variability in the Naryn river basin, Kyrgyzstan, Hydrospatial Analysis, 3(2), 90-106, doi:10.21523/gcj3.19030204, 2019.

Tagged under: Software