Simple statistical models for relating river discharge with precipitation and air temperature—Case study of River Vouga (Portugal)

Abstract

Simple statistical models were developed to relate available meteorological data with daily river discharge (RD) for rivers not influenced by melting of ice and snow. In a case study of the Vouga River (Portugal), the RD could be determined by a linear combination of the recent (P_R) and non-recent (P_NR) atmospheric precipitation history. It was found that a simple linear model including only P_R and P_NR cannot account for low RD. The model was improved by including non-linear terms of precipitation that accounted for the water loss. Additional improvement of the models was possible by including average monthly air temperature (T). The best model was robust when up to 60% of the original data were randomly removed. The advantage is the simplicity of the models, which take into account only P_R, P_NR and T. These models can provide a useful tool for RD estimation from current meteorological data.

Keywords

multiple regression / atmospheric precipitation / river discharge / runoff / Aveiro Lagoon

References

[1] Achleitner S, Schöber J, Rinderer M, Leonhardt G, Schöberl F, Kirnbauer R, Schönlaub H (2012). Analyzing the operational performance of the hydrological models in an alpine flood forecasting system. J Hydrol (Amst), 412–413: 90–100

[2] AEMET-IM (2011). Iberian Climate Atlas- Air temperature and precipitation (1971–2000). Ministerio de Medio Ambiente y Medio Rural y Marino (Spain), Instituto de Meteorologia (Portugal)

[3] Agroconsultores and Geometral (1995). Carta dos solos e da aptidão da terra do Entre-Douro e Minho [Map of Soils and Land Suitability of Entre-Douro and Minho]. Lisbon: DRAEDM

[4] Bellanger L, Tomassone R (2014). Exploration de données et méthodes statistiques: data analysis & data mining avec le logiciel R [Data Exploration and Statistical Methods: Data Analysis & Data Mining Using R]. Paris: Ellipses

[5] Beven K J (1989). Changing ideas in hydrology: the case of physically-based models. J Hydrol (Amst), 105(1–2): 157–172

[6] Beven K J (2012). Rainfall–Runoff Modeling: The Primer. Chichester: Wiley

[7] Brath A, Montanari A, Toth E (2004). Analysis of the effects of different scenarios of historical data availability on the calibration of a spatially-distributed hydrological model. J Hydrol (Amst), 291(3–4): 232–253

[8] Cerejo M, Dias J M (2007). Tidal transport and dispersal of marine toxic microalgae in a shallow, temperate coastal lagoon. Mar Environ Res, 63(4): 313–340

[9] Crawley M J (2007). The R book. Chichester: Wiley

[10] Dias J M, Abrantes I, Rocha F (2007). Suspended particulate matter sources and residence time in a mesotidal lagoon. J Coast Res, 50(Special issue): 1034–1039

[11] Dias J M, Lopes J F, Dekeyser I (1999). Hydrological characterisation of Ria de Aveiro, Portugal, in early summer. Oceanol Acta, 22(5): 473–485

[12] Du J, Xie S, Xu Y, Xu C, Singh V P (2007). Development and testing of a simple physically-based distributed rainfall-runoff model for storm runoff simulation in humid forested basins. J Hydrol (Amst), 336(3–4): 334–346

[13] ESBN (2005). Soil Atlas of Europe. Luxembourg: European Commission

[14] Espinha Marques J, Samper J, Pisani B, Alvares D, Carvalho J M, Chaminé H I, Marques J M, Vieira G T, Mora C, Sodré Borges F (2011). Evaluation of water resources in a high-mountain basin in Serra da Estrela, Central Portugal, using a semi-distributed hydrological model. Environmental Earth Sciences, 62(6): 1219–1234

[15] Gemmer M, Jiang T, Su B, Kundzewicz Z W (2008). Seasonal precipitation changes in the wet season and their influence on flood/drought hazards in the Yangtze River Basin, China. Quat Int, 186(1): 12–21

[16] Gourley J J, Vieux B E (2006). A method for identifying sources of model uncertainty in rainfall-runoff simulations. J Hydrol (Amst), 327(1–2): 68–80

[17] Hiscock K M, Lister D H, Boar R R, Green F M L (2001). An integrated assessment of long-term changes in the hydrology of three lowland rivers in eastern England. J Environ Manage, 61(3): 195–214

[18] Hurkmans R T W L, de Moel H, Aerts J C J H, Troch P A (2008). Water balance versus land surface model in the simulation of Rhine river discharges. Water Resour Res, 44(1): W01418

[19] IPMA (2015). Normais climatológicas 1971–2000 [Weather and Climate 1971–2000]. Retrieved from:

[20] Muthukrishnan S, Harbor J, Lim K J, Engel B A (2006). Calibration of a simple rainfall-runoff model for long-term hydrological impact evaluation. URISA Journal, 18(2): 35–42

[21] Oliveira J T, Pereira E, Ramalho M, Antunes M T, Monteiro J H (1992). Carta Geológica de Portugal 1/500 000 [Geological Map of Portugal 1/500 000]. 5th ed. Lisbon: Serviços Geológicos de Portugal

[22] R Core Team (2014). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.

[23] Rogado N J O, Batalha J F C S, Simões J J M F, Ribeiro L M (1992). Esboço duma carta de solos da Região de Aveiro na escala 1/100 000[Project of a soil map of Aveiro region on the scale 1/100 000]. Coimbra (Portugal): DRABL

[24] Sen Z (2010). Fuzzy Logic and Hydrological Modelling. Boca Raton: Taylor and Francis

[25] USGS (2009). Shuttle Radar Topography Mission 3-arc second data (version 2.1). Retrieved from:

[26] Van der Weijden C H, Pacheco F A L (2006). Hydrogeochemistry in the Vouga River basin (central Portugal): pollution and chemical weathering. Appl Geochem, 21(4): 580–613

[27] Vilaysane B, Takara K, Luo P, Akkharath I, Duan W (2015). Hydrological stream flow modelling for calibration and uncertainty analysis using SWAT model in the Xedone river basin, Lao PDR. Procedia Environ Sci, 28: 380–390

[28] Xu H, Taylor R G, Xu Y (2011). Quantifying uncertainty in the impacts of climate change on river discharge in sub-catchments of the Yangtze and Yellow River Basins, China. Hydrol Earth Syst Sci, 15(1): 333–344

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