Topography-adjusted solar radiation indices and their importance in hydrology

N. Mamassis, A. Efstratiadis, and E. Apostolidou, Topography-adjusted solar radiation indices and their importance in hydrology, Hydrological Sciences Journal, 57 (4), 756–775, doi:10.1080/02626667.2012.670703, 2012.



Solar radiation, direct and diffuse, is affected by surface characteristics, such as slope, aspect, altitude and shading. The paper examines the effects of topography on radiation, at multiple spatiotemporal scales, using suitable geometrical methods for the direct and diffuse components. Two indices are introduced for comparing the direct radiation received by areas at the same and different latitudes, respectively. To investigate the profile of direct radiation through the Greek territory, these are evaluated from hourly to annual basis, via GIS techniques. Moreover, different approaches are examined for estimating the actual global radiation at operational spatial scales (sub-basin and terrain), according to the available meteorological data. The study indicates that the errors of typical hydrometeorological modelling formulas, ignoring the topographic effects and the seasonal allocation of direct and diffuse radiation, depend on the spatial scale and they are non-uniformly distributed in time. In all cases, the estimations are improved by applying the proposed adjusting approaches. In particular, the adjustment of the measured global radiation ensures up to 10% increase of efficiency, while the modified Angström formula achieves slight (i.e. 2-4%) increase of efficiency and notable reduction of bias.

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Our works referenced by this work:

1. D. Koutsoyiannis, and Th. Xanthopoulos, Engineering Hydrology, Edition 3, 418 pages, doi:10.13140/RG.2.1.4856.0888, National Technical University of Athens, Athens, 1999.
2. E. Apostolidou, The effect of the surrounding topography on incoming solar radiation, Postgraduate Thesis, 131 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, July 2007.

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. N. Efthimiou, S. Alexandris, C Karavitis, and N. Mamassis, Comparative analysis of reference evapotranspiration estimation between various methods and the FAO56 Penman - Monteith procedure, European Water, 42 (19-34), 2013.
3. N. Mamassis, D. Panagoulia, and A. Novcovic, Sensitivity analysis of Penman evaporation method, Global Network for Environmental Science and Technology, 16 (4), 628–639, 2014.
4. R. Ioannidis, T. Iliopoulou, C. Iliopoulou, L. Katikas, A. Petsou, M.-E. Merakou, M.-E. Asimomiti, N. Pelekanos, G. Koudouris, P. Dimitriadis, C. Plati, E. Vlahogianni, K. Kepaptsoglou, N. Mamassis, and D. Koutsoyiannis, Solar-powered bus route: introducing renewable energy into a university campus transport system, Advances in Geosciences, 49, doi:10.5194/adgeo-49-215-2019, 2019.
5. G.-F. Sargentis, P. Siamparina, G.-K. Sakki, A. Efstratiadis, M. Chiotinis, and D. Koutsoyiannis, Agricultural land or photovoltaic parks? The water–energy–food nexus and land development perspectives in the Thessaly plain, Greece, Sustainability, 13 (16), 8935, doi:10.3390/su13168935, 2021.
6. A. Roxani, A. Zisos, G.-K. Sakki, and A. Efstratiadis, Multidimensional role of agrovoltaics in era of EU Green Deal: Current status and analysis of water-energy-food-land dependencies, Land, 12 (5), 1069, doi:10.3390/land12051069, 2023.

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

1. Kunkel, V., T. Wells, and G. R. Hancock, Soil temperature dynamics at the catchment scale, Geoderma, 273, 32–44, doi:10.1016/j.geoderma.2016.03.011, 2016.
2. Felicísimo Pérez, Á. M., and M.Á. Martín-Tardío, A method of downscaling temperature maps based on analytical hillshading for use in species distribution modelling, Cartography and Geographic Information Science, 45(4), 329-338, doi:10.1080/15230406.2017.1338620, 2018.
3. Frey, J., K. Kovach, S. Stemmler, and B. Koch, UAV photogrammetry of forests as a vulnerable process. A sensitivity analysis for a structure from motion RGB-image pipeline, Remote Sensing, 16(2), 912, doi:10.3390/rs10060912, 2018.
4. Aguilar, C., R. Pimentel, and M. J. Polo, Two decades of distributed global radiation time series across a mountainous semiarid area (Sierra Nevada, Spain), Earth System Science Data, 13, 1335-1359, doi:10.5194/essd-13-1335-2021, 2021.
5. Nepali, B. R., J. Skartveit, and C. B. Baniya, Impacts of slope aspects on altitudinal species richness and species composition of Narapani-Masina landscape, Arghakhanchi, West Nepal, Journal of Asia-Pacific Biodiversity, 14(3), 415-424, doi:10.1016/j.japb.2021.04.005, 2021.
6. Pisinaras V., F. Herrmann, A. Panagopoulos, E. Tziritis, I. McNamara, and F. Wendland, Fully distributed water balance modelling in large agricultural areas—The Pinios river basin (Greece) case study, Sustainability, 15(5), 4343, doi:10.3390/su15054343, 2023.

Tagged under: Course bibliography: Hydrometeorology, Hydrological processes, Students' works