History of Geo- and Space Open Access Open Sciences 10th EMS Annual Meeting and 8th European Conference on Applied Climatology (ECAC) 2010 Adv. Sci. Res., 6, 141–146, 2011 www.adv-sci-res.net/6/141/2011/ Advances in doi:10.5194/asr-6-141-2011 Science & Research © Author(s) 2011. CC Attribution 3.0 License. Open Access Proceedings Drinking Water Data validation procedures in agricultural meteorologyEngineering – a prerequisite for their use Access Open and Science J. Estevez´ 1, P. Gavilan´ 2, and A. P. Garc´ıa-Mar´ın1 Earth System 1University of Cordoba,´ Projects Engineering, Cordoba,´ Spain 2IFAPA Center “Alameda del Obispo”, Junta de Andaluc´ıa, Cordoba,´ Spain Science Received: 16 December 2010 – Revised: 27 April 2011 – Accepted: 13 May 2011 – Published: 20 May 2011 Open Access Open Data Abstract. Quality meteorological data sources are critical to scientists, engineers, climate assessments and to make climate related decisions. Accurate quantification of reference evapotranspiration (ET0) in irrigated agriculture is crucial for optimizing crop production, planning and managing irrigation, and for using water resources efficiently. Validation of data insures that the information needed is been properly generated, iden- tifies incorrect values and detects problems that require immediate maintenance attention. The Agroclimatic Information Network of Andalusia at present provides daily estimations of ET0 using meteorological informa- tion collected by nearly of one hundred automatic weather stations. It is currently used for technicians and farmers to generate irrigation schedules. Data validation is essential in this context and then, diverse quality control procedures have been applied for each station. Daily average of several meteorological variables were analysed (air temperature, relative humidity and rainfall). The main objective of this study was to develop a quality control system for daily meteorological data which could be applied on any platform and using open source code. Each procedure will either accept the datum as being true or reject the datum and label it as an outlier. The number of outliers for each variable is related to a dynamic range used on each test. Finally, geographical distribution of the outliers was analysed. The study underscores the fact that it is necessary to use different ranges for each station, variable and test to keep the rate of error uniform across the region. 1 Introduction The Agroclimatic Information Network of Andalusia (RIAA in Spanish) was deployed to provide coverage to most Meteorological information is one of the most important of the irrigated areas of the region and to improve irriga- tools used by agriculture producers in decision making tion water management (De Haro et al., 2003). Its exploita- (Weiss and Robb, 1986). Some of the applications for these tion and maintenance are carried out by the IFAPA (Agri- climate data include: crop water-use estimates, irrigation cultural Research Institute of Regional Government of An- scheduling, integrated pest management, crop and soil mois- dalusia). This network provides at present daily estima- ture modeling, design and management of irrigation and tions of reference evapotranspiration (ET0) using meteoro- drainage system and frost and freeze warnings and forecasts logical information collected by nearly one hundred auto- (Meyer and Hubbard, 1992). matic weather stations (Gavilan´ et al., 2008). This informa- tion is easily accessible due to it is published in the Web: Andalusia is located in the south of the Iberian Peninsula. http://www.juntadeandalucia.es/agriculturaypesca/ifapa/ria/. This region is situated between the meridians 1◦ and 7◦ W Meteorological data validation is very important for hy- and the parallels 37◦ and 39◦ N, with an extension around drological designs and agricultural decision makings, con- 9 Mha. The climate is semiarid, typically Mediterranean, cretely to estimate irrigation schedules. The quality control with very hot and dry summers. In Andalusia 900 000 ha are system discussed herein was applied to 85 stations, summa- irrigated (around 20 % of the cultivated area) under very dif- rized in Table 1. The rest of the stations have been recently ferent conditions (Gavilan´ et al., 2006). installed and their data series were too short. Quality con- trol system consists of procedures or tests against which data are tested, setting data flags to provide guidance to end users. Correspondence to: J. Estevez´ These flags give information about which tests have been ap- ([email protected]) plied satisfactorily or not to meteorological data. Published by Copernicus Publications. 142 J. Estevez´ et al.: Data validation procedures in agricultural meteorology Table 1. Summary of automated weather stations used in the study. Table 1. Continued. Stations Elevation Latitude Longitude Stations Elevation Latitude Longitude ◦ ◦ (Province) (m) (◦)(◦) (Province) (m) ( )( ) Basurta-Jerez (CADIZ)´ 60 36.75 −6.01 Santo Tome´ (JAEN)´ 571 38.03 −3.08 Jerez Frontera (CADIZ)´ 32 36.64 −6.01 Jaen´ (JAEN)´ 299 37.89 −3.77 Villamart´ın (CADIZ)´ 171 36.84 −5.62 Palacios-Villafran. (SEVILLA) 21 37.18 −5.93 Conil Frontera (CADIZ)´ 26 36.33 −6.13 Cabezas S. Juan (SEVILLA) 25 37.01 −5.88 Vejer Frontera (CADIZ)´ 24 36.28 −5.83 Lebrija 2 (SEVILLA) 40 36.90 −6.00 − Jimena Frontera (CADIZ)´ 53 36.41 −5.38 Aznalcazar´ (SEVILLA) 4 37.15 6.27 − Puerto Sta. Mar´ıa (CADIZ)´ 20 36.61 −6.15 Puebla del R´ıo II (SEVILLA) 41 37.08 6.04 ´ − La Mojonera (ALMERIA)´ 142 36.78 −2.70 Ecija (SEVILLA) 125 37.59 5.07 La Luisiana (SEVILLA) 188 37.52 −5.22 Almer´ıa (ALMERIA)´ 22 36.83 −2.40 Osuna (SEVILLA) 214 37.25 −5.13 Tabernas (ALMERIA)´ 435 37.09 −2.30 La Rinconada (SEVILLA) 37 37.45 −5.92 Finana˜ (ALMERIA)´ 971 37.15 −2.83 Sanlucar´ la Mayor (SEVILLA) 88 37.42 −6.25 V. Fatima-Cuevas´ (ALMERIA)´ 185 37.39 −1.76 Villan.R´ıo-Minas (SEVILLA) 38 37.61 −5.68 Huercal-Overa´ (ALMERIA)´ 317 37.41 −1.88 Lora del R´ıo (SEVILLA) 68 37.66 −5.53 ´ − Cuevas Almanz. (ALMERIA) 20 37.25 1.79 Los Molares (SEVILLA) 90 37.17 −5.67 ´ Adra (ALMERIA) 42 36.74 −2.99 Guillena (SEVILLA) 191 37.51 −6.06 ´ N´ıjar (ALMERIA) 182 36.95 −2.15 Puebla Cazalla (SEVILLA) 229 37.21 −5.34 ´ T´ıjola (ALMERIA) 796 37.37 −2.45 Carmona-Tomejil (SEVILLA) 79 37.40 −5.58 ´ Belmez´ (CORDOBA) 523 38.25 −5.20 Malaga´ (MALAGA)´ 68 36.75 −4.53 ´ Adamuz (CORDOBA) 90 37.99 −4.44 Velez-M´ alaga´ (MALAGA)´ 49 36.79 −4.13 ´ Palma del R´ıo (CORDOBA) 134 37.67 −5.24 Antequera (MALAGA)´ 457 37.05 −4.55 ´ Hornachuelos (CORDOBA) 157 37.72 −5.15 Estepona (MALAGA)´ 199 36.44 −5.20 ´ El Carpio (CORDOBA) 165 37.91 −4.50 Archidona (MALAGA)´ 516 37.07 −4.42 ´ Cordoba´ (CORDOBA) 117 37.86 −4.80 Sierra Yeguas (MALAGA)´ 464 37.13 −4.83 ´ Santaella (CORDOBA) 207 37.52 −4.88 Churriana (MALAGA)´ 32 36.67 −4.50 ´ Baena (CORDOBA) 334 37.69 −4.30 Pizarra (MALAGA)´ 84 36.76 −4.71 Baza (GRANADA) 814 37.56 −2.76 Cartama´ (MALAGA)´ 95 36.71 −4.67 Puebla D.Fadriq. (GRANADA) 1110 37.87 −2.38 Loja (GRANADA) 487 37.17 −4.13 Pinos Puente (GRANADA) 594 37.26 −3.77 Iznalloz (GRANADA) 935 37.41 −3.55 Jerez Marques. (GRANADA) 1212 37.19 −3.14 2 Materials and methods Cadiar´ (GRANADA) 950 36.92 −3.18 Zafarraya (GRANADA) 905 36.99 −4.15 Almun˜ecar´ (GRANADA) 49 36.74 −3.67 2.1 Source of data Padul (GRANADA) 781 37.02 −3.59 Tojalillo-Gibraleon´ (HUELVA) 52 37.31 −7.02 The dataset used in the present study was obtained from the Lepe (HUELVA) 74 37.24 −7.24 daily database of the RIAA and it was from 2004 to 2009. Gibraleon´ (HUELVA) 169 37.41 −7.05 Each station is controlled by a CR10X datalogger (Camp- Moguer (HUELVA) 87 37.14 −6.79 bell Scientific) and is equipped with sensors to measure air Niebla (HUELVA) 52 37.34 −6.73 Aroche (HUELVA) 299 37.95 −6.94 temperature and relative humidity (HMP45C probe, Vaisala), Puebla Guzman´ (HUELVA) 288 37.55 −7.24 solar radiation (pyranometer SP1110 Skye), wind speed and El Campillo (HUELVA) 406 37.66 −6.59 direction (wind monitor RM Young 05103) and rainfall (tip- Palma Condado (HUELVA) 192 37.36 −6.54 ping bucket rain gauge ARG 100). Air temperature and rel- Almonte (HUELVA) 18 37.15 −6.47 ative humidity are measured at 1.5 m and wind speed at 2 m Moguer-Cebollar (HUELVA) 63 37.24 −6.80 Huesa (JAEN)´ 793 37.74 −3.06 above soil surface. Data from stations are transferred to the Pozo Alcon´ (JAEN)´ 893 37.67 −2.92 data-collecting seat (Main Center) by using GSM modems. S.Jose´ Propios (JAEN)´ 509 37.85 −3.22 This information is saved in a database. The Main Center is Sabiote (JAEN)´ 822 38.08 −3.23 responsible for quality control procedures that comprise the Torreblascopedro (JAEN)´ 291 37.98 −3.68 routine maintenance program of the network, including sen- ´ Alcaudete (JAEN) 645 37.57 −4.07 sor calibration and data validation. Mancha Real (JAEN)´ 436 37.91 −3.59 Ubeda´ (JAEN)´ 358 37.94 −3.29 Accuracy of ET0 calculations depends on the quality and Linares (JAEN)´ 443 38.06 −3.64 the integrity of meteorological data used (Allen, 1996), being Marmolejo (JAEN)´ 208 38.05 −4.12 necessary data quality control application. Different proce- Chiclana Segura (JAEN)´ 510 38.30 −2.95 dures for quality assurance have been described by Meek and ´ Higuera Arjona (JAEN) 267 37.95 −4.00 Hatfield (1994), Allen (1996), Shafer et al. (2000) and Feng et al.