scholarly journals Variation in the estimations of ET<sub>o</sub> and crop water use due to the sensor accuracy of the meteorological variables

2013 ◽  
Vol 13 (6) ◽  
pp. 1401-1410 ◽  
Author(s):  
R. Moratiel ◽  
A. Martínez-Cob ◽  
B. Latorre
Keyword(s):  
Water Management ◽  
Wind Speed ◽  
Relative Humidity ◽  
Irrigation Water ◽  
Meteorological Variables ◽  
Crop Water ◽  
Water Requirements ◽  
Crop Water Use ◽  
Irrigation Districts ◽  
Annual Scale

Abstract. In agricultural ecosystems the use of evapotranspiration (ET) to improve irrigation water management is generally widespread. Commonly, the crop ET (ETc) is estimated by multiplying the reference crop evapotranspiration (ETo) by a crop coefficient (Kc). Accurate estimation of ETo is critical because it is the main factor affecting the calculation of crop water use and water management. The ETo is generally estimated from recorded meteorological variables at reference weather stations. The main objective of this paper was assessing the effect of the uncertainty due to random noise in the sensors used for measurement of meteorological variables on the estimation of ETo, crop ET and net irrigation requirements of grain corn and alfalfa in three irrigation districts of the middle Ebro River basin. Five scenarios were simulated, four of them individually considering each recorded meteorological variable (temperature, relative humidity, solar radiation and wind speed) and a fifth scenario combining together the uncertainty of all sensors. The uncertainty in relative humidity for irrigation districts Riegos del Alto Aragón (RAA) and Bardenas (BAR), and temperature for irrigation district Canal de Aragón y Cataluña (CAC), were the two most important factors affecting the estimation of ETo, corn ET (ETc_corn), alfalfa ET (ETc_alf), net corn irrigation water requirements (IRncorn) and net alfalfa irrigation water requirements (IRnalf). Nevertheless, this effect was never greater than ±0.5% over annual scale time. The wind speed variable (Scenario 3) was the third variable more influential in the fluctuations (±) of evapotranspiration, followed by solar radiation. Considering the accuracy for all sensors over annual scale time, the variation was about ±1% of ETo, ETc_corn, ETc_alf, IRncorn, and IRnalf. The fluctuations of evapotranspiration were higher at shorter time scale. ETo daily fluctuation remained lower than 5 % during the growing season of corn and alfalfa. This estimation fluctuation in ETo, ETc_corn, ETc_alf , IRncorn, and IRnalf at daily time scale was within an acceptable range, and it can be considered that the sensor accuracy of the meteorological variables is not significant in the estimation of ETo.

scholarly journals Detecting the Response of Irrigation Water Management to Climate by Remote Sensing Monitoring of Evapotranspiration

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2045 ◽  
Author(s):  
Fatima-Ezzahra El Ghandour ◽  
Silvia Maria Alfieri ◽  
Youssef Houali ◽  
Adnane Habib ◽  
Nadia Akdim ◽  
...  
Keyword(s):  
Water Management ◽  
Time Series ◽  
Water Use ◽  
Irrigation Water ◽  
Water Demand ◽  
Actual Evapotranspiration ◽  
Crop Water ◽  
Water Release ◽  
Crop Water Use ◽  
Annual Variability

This study on a large irrigation scheme in Morocco addressed a two-fold question: (a) does the local water management authority adapt water releases to atmospheric water demand ET0-P? and (b) does crop actual evapotranspiration respond to inter- and intra-annual variability in water releases? We have evaluated the inter-annual variability of ET0-P during the period 1992–2017 and compared its anomalies (i.e., deviations from average) with anomalies in annual water release. Overall, it appeared that anomalies in water release were consistent with anomalies in ET0-P. The actual evapotranspiration (ETa) was estimated using a time series of multi-spectral satellite image data by applying the Surface Energy Balance (SEBAL) algorithm in a dry, wet, and reference year. We have determined the quartiles of the distribution of the ET0-P time series to identify these three years. The dry year was 2015–2016, the wet year was 2014–2015, and the reference (median of ET0-P) was 2013–2014. Finally, we compared seasonal and annual anomalies in ET0-P, ETa and release, Wd of irrigation water. In the period 1992–2017, the relative anomalies in ET0-P and Wd were similar only in 2000–2001 and 2015–2016. The analysis of anomalies in water inflow and stocks confirmed the response in increased Wd following wet years with higher inflow and replenishment of the reservoir. The response of crop water use to the irrigation water supply was evaluated by comparing anomalies in the ratio of actual to maximum ET, i.e., ETa/ETc with anomalies in Wd. As regards the Sidi Bennour, Faregh, and Gharbia districts, the relative anomalies in ETa/ETc and Wd were consistent, i.e., they had the same sign and comparable magnitude. Overall, the study shows that water delivery Wd responds to inter-annual variability in the pre-irrigation season water inflows into the reservoirs, rather than in ET0-P. On the other hand, actual crop water use, i.e., ETa/ETc, does respond to inter- and intra-annual variability in Wd. This evidence suggests that there is scope for adaptive water management based on a flexible adaptation of water release to inter- and intra-annual variability in water demand.

scholarly journals SEASONAL AND INTERANNUAL PATTERN OF METEOROLOGICAL VARIABLES IN CUIABÁ, MATO GROSSO STATE, BRAZIL

2015 ◽  
Vol 33 (3) ◽  
pp. 477 ◽  
Author(s):  
Nadja Gomes Machado ◽  
Marcelo Sacardi Biudes ◽  
Carlos Alexandre Santos Querino ◽  
Victor Hugo De Morais Danelichen ◽  
Maísa Caldas Souza Velasque
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Meteorological Data ◽  
Seasonal Pattern ◽  
Global Radiation ◽  
Meteorological Variables ◽  
Maximum Temperature ◽  
Wet Season ◽  
Agricultural Producers ◽  
Mato Grosso

ABSTRACT. Cuiab´a is located on the border of the Pantanal and Cerrado, in Mato Grosso State, which is recognized as one of the biggest agricultural producers of Brazil. The use of natural resources in a sustainable manner requires knowledge of the regional meteorological variables. Thus, the objective of this study was to characterize the seasonal and interannual pattern of meteorological variables in Cuiab´a. The meteorological data from 1961 to 2011 were provided by the Instituto Nacional de Meteorologia (INMET – National Institute of Meteorology). The results have shown interannual and seasonal variations of precipitation, solar radiation, air temperature and relative humidity, and wind speed and direction, establishing two main distinct seasons (rainy and dry). On average, 89% of the rainfall occurred in the wet season. The annual average values of daily global radiation, mean, minimum and maximum temperature and relative humidity were 15.6 MJ m–2 y–1, 27.9◦C, 23.0◦C, 30.0◦C and 71.6%, respectively. Themaximum temperature and the wind speed had no seasonal pattern. The wind speed average decreased in the NWdirectionand increased in the S direction.Keywords: meteorological variables, climatology, ENSO. RESUMO. Cuiabá está localizado na fronteira do Pantanal com o Cerrado, no Mato Grosso, que é reconhecido como um dos maiores produtores agrícolas do Brasil. A utilização dos recursos naturais de forma sustentável requer o conhecimento das variáveis meteorológicas em escala regional. Assim, o objetivo deste estudo foi caracterizar o padrão sazonal e interanual das variáveis meteorológicas em Cuiabá. Os dados meteorológicos de 1961 a 2011 foram fornecidos pelo Instituto Nacional de Meteorologia (INMET). Os resultados mostraram variações interanuais e sazonais de precipitação, radiação solar, temperatura e umidade relativa do ar e velocidade e direção do vento, estabelecendo duas principais estações distintas (chuvosa e seca). Em média, 89% da precipitação ocorreu na estação chuvosa. Os valores médios anuais de radiação diária global, temperatura do ar média, mínima e máxima e umidade relativa do ar foram 15,6 MJ m–2 y–1, 27,9◦C, 23,0◦C, 30,0◦C e 71,6%, respectivamente. A temperatura máxima e a velocidade do vento não tiveram padrão sazonal. A velocidade média do vento diminuiu na direção NW e aumentou na direção S.Palavras-chave: variáveis meteorológicas, climatologia, ENOS.

scholarly journals Optimization of irrigation water in South Africa for sustainable and beneficial use

2017 ◽  
Author(s):  
◽  
Akinola Mayowa Ikudayisi
Keyword(s):  
South Africa ◽  
Water Use ◽  
Crop Yield ◽  
Optimization Algorithm ◽  
Irrigation Water ◽  
Irrigation Scheduling ◽  
Crop Water ◽  
Land Area ◽  
Water Requirements ◽  
Irrigation Water Use

Water is an essential natural resource for human existence and survival on the earth. South Africa, a water stressed country, allocates a high percentage of its available consumptive water use to irrigation. Therefore, it is necessary that we optimize water use in order to enhance food security. This study presents the development of mathematical models for irrigation scheduling of crops, optimal irrigation water release and crop yields in Vaal Harts irrigation scheme (VIS) of South Africa. For efficient irrigation water management, an accurate estimation of reference evapotranspiration (ETₒ) should be carried out. However, due to non-availability of enough historical data for the study area, mathematical models were developed to estimate ETₒ. A 20-year monthly meteorological data was collected and analysed using two data–driven modeling techniques namely principal component analysis (PCA) and adaptive neuro-fuzzy inference systems (ANFIS). Furthermore, an artificial neural network (ANN) model was developed for real time prediction of future ETₒ for the study area. The real time irrigation scheduling of potatoes was developed using a crop growth simulation model called CROPWAT. It was used to determine the crop water productivity (CWP), which is a determinant of the relationship between water applied and crop yield. Finally, a new and novel evolutionary multi-objective optimization algorithm called combined Pareto multi-objective differential evolution (CPMDE) was applied to optimize irrigation water use and crop yield on the VIS farmland. The net irrigation benefit, land area and irrigation water use of maize, potatoes and groundnut were optimized. Results obtained show that ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity have less significance on the value of ETₒ. Also, ANN models with one hidden layer showed better predictive performance compared with other considered configurations. A 5-day time step irrigation schedule data and graphs showing the crop water requirements and irrigation water requirements was generated. This would enable farmers know when, where, and how much water to apply to a given farmland. Finally, the employed CPMDE optimization algorithm produced a set of non-dominated Pareto optimal solutions. The best solution suggests that maize, groundnut and potatoes should be planted on 403543.44 m2, 181542.00 m2 and 352876.05 m2areas of land respectively. This solution generates a total net benefit of ZAR 767,961.49, total planting area of 937961.49 m2 and irrigation water volume of 391,061.52 m3. Among the three crops optimized, maize has the greatest land area, followed by potatoes and groundnut. This shows that maize is more profitable than potatoes and groundnut with respect to crop yield and water use in the study area.

Estimating rice water requirements in the Lis Valley (Portugal) using remote sensing platforms: preliminary results for the 2020 cultivation season

2021 ◽  
Author(s):  
Romeu G. Jorge ◽  
Isabel P. de Lima ◽  
João L.M.P. de Lima
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Irrigation Water ◽  
Crop Yields ◽  
Irrigation District ◽  
Water Requirements ◽  
Local Conditions ◽  
Preliminary Results ◽  
Sentinel 2A ◽  
Rice Water

&lt;p&gt;In irrigated agricultural areas, where the availability of water for irrigation does not rely on any water storage, water management requires special attention, in particular under large annual and inter-annual variability in the hydrological regime and the uncertainty of climate change. The inherent increased vulnerability of the agro-ecosystem, makes the monitoring of crop conditions and water requirements a valuable tool for improving water use efficiency and, therefore, crop yields.&lt;/p&gt;&lt;p&gt;This presentation focus on one such agricultural area, located in the Lis Valley (Centre of Portugal), which is a rather vulnerable area also facing drainage and salinity problems. The study aims at contributing to better characterizing the temporal and spatial distribution of rice water requirements during the growing season. Irrigation water sources are the Lis River and its tributaries, which discharges depend directly from precipitation. The most important problems of water distribution in the Lis Valley irrigation district are water shortage and poor water quality in the dry summer period, aggravated by limitations of the irrigation and drainage systems that date back to the end of the 1950&amp;#8217;s.&lt;/p&gt;&lt;p&gt;We report preliminary results on using remote sensing data to better understand rice cropping local conditions, obtained within project GO Lis (PDR2020-101-030913) and project MEDWATERICE (PRIMA/0006/2018). Rice irrigation is traditionally conducted applying continuous flooding, which requires much more irrigation water than non-ponded crops, and therefore needs special attention. In particular, data obtained from satellite Sentinel-2A land surface imagery are compared with data obtained using an unmanned aerial vehicle (UAV). Data for rice cultivated areas during the 2020 cultivation season, together with weather and crop parameters, are used to calculate biophysical indicators and indices of water stress in the vegetation. Actual crop evapotranspiration was appraised with remote sensing based estimates of the crop coefficient (Kc) and used to assess rice water requirements. Procedures and methodologies to estimate Kc were tested, namely those based on vegetation indices such as the Normalized Difference Vegetation Index (NDVI). Results are discussed bearing in mind the usefulness of the diverse tools, based on different resolution data (Sentinel-2A and UAV), for improving the understanding of the impacts of irrigation practices on crop yield and main challenges of rice production and water management in the Lis Valley irrigation district.&lt;/p&gt;

scholarly journals Water Management Using Drones and Satellites in Agriculture

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 874 ◽  
Author(s):  
Javier J. Cancela ◽  
Xesús P. González ◽  
Mar Vilanova ◽  
José M. Mirás-Avalos
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Water Status ◽  
Irrigation Management ◽  
Irrigation Efficiency ◽  
Agricultural Systems ◽  
Special Issue ◽  
Crop Water ◽  
Water Requirements ◽  
Remote Sensing Techniques

This document intends to be a presentation of the Special Issue “Water Management Using Drones and Satellites in Agriculture”. The objective of this Special Issue is to provide an overview of recent advances in the methodology of using remote sensing techniques for managing water in agricultural systems. Its eight peer-reviewed articles focus on three topics: new equipment for characterizing water bodies, development of satellite-based technologies for determining crop water requirements in order to enhance irrigation efficiency, and monitoring crop water status through proximal and remote sensing. Overall, these contributions explore new solutions for improving irrigation management and an efficient assessment of crop water needs, being of great value for both researchers and advisors.

scholarly journals Integrating Sentinel-2 Imagery with AquaCrop for Dynamic Assessment of Tomato Water Requirements in Southern Italy

Agronomy ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 404 ◽  
Author(s):  
Anna Dalla Marta ◽  
Giovanni Battista Chirico ◽  
Salvatore Falanga Bolognesi ◽  
Marco Mancini ◽  
Guido D’Urso ◽  
...  
Keyword(s):  
Irrigation Water ◽  
Dynamic Assessment ◽  
Canopy Cover ◽  
Development Stage ◽  
Crop Water ◽  
Water Requirements ◽  
Tomato Crop ◽  
Crop Water Requirements ◽  
Aquacrop Model ◽  
Sentinel 2

A research study was conducted in an open field tomato crop in order to: (i) Evaluate the capability of Sentinel-2 imagery to assess tomato canopy growth and its crop water requirements; and (ii) explore the possibility to predict crop water requirements by assimilating the canopy cover estimated by Sentinel-2 imagery into AquaCrop model. The pilot area was in Campania, a region in the south west of Italy, characterized by a typical Mediterranean climate, where field campaigns were conducted in seasons 2017 and 2018 on processing tomato. Crop water use and irrigation requirement were estimated by means of three different methods: (i) The AquaCrop model; (ii) an irrigation advisory service based on Sentinel-2 imagery known as IRRISAT and (iii) assimilating the canopy cover estimated by Sentinel-2 imagery into AquaCrop model Sentinel-2 imagery proved to be effective for monitoring canopy growth and for predicting irrigation water requirements during mid-season stage of the crop, when the canopy is fully developed. Conversely, the integration of the Sentinel-2 imagery with a crop growth model can contribute to improve the irrigation water requirement predictions in the early and development stage of the crop, when the soil evaporation is not negligible with respect to the total evapotranspiration.

A New Approach for Meteorological Variables Prediction at Kuala Lumpur, Malaysia, Using Artificial Neural Networks: Application for Sizing and Maintaining Photovoltaic Systems

2012 ◽  
Vol 134 (2) ◽  
Author(s):  
Tamer Khatib ◽  
Azah Mohamed ◽  
M. Mahmoud ◽  
K. Sopian
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Energy ◽  
Ambient Temperature ◽  
Meteorological Variables ◽  
Mean Bias Error ◽  
Artificial Neural ◽  
Prediction Approach

This research presents a new meteorological variables prediction approach for Malaysia using artificial neural networks. The developed model predicts four meteorological variables using sun shine ratio, day number, and location coordinates. These meteorological variables are solar energy, ambient temperature, wind speed, and relative humidity. However, three statistical values are used to evaluate the proposed model. These statistical values are mean absolute percentage error (MAPE), mean bias error (MBE), and root mean square error (RMSE). Based on results, the developed model predicts accurately the four meteorological variables. The MAPE, RMSE, and MBE in predicting solar radiation are 1.3%, 5.8 (1.8%), and 0.9 (0.3%), respectively, while the MAPE, RMSE, and MBE values for ambient temperature prediction are 1.3%, 0.4 (1.7%), and 0.1 (0.4%), respectively. In addition, the MAPE, RMSE, and MBE values in relative humidity prediction are 3.2%, 3.2, and 0.2. As for wind speed prediction, it is the worst in accuracy among the predicted variables because the MAPE, RMSE, and MBE values are 28.9%, 0.5 (31.3%), and 0.02 (1.25%). Such a developed model helps in sizing photovoltaic (PV) systems using solar energy and ambient temperature records. Moreover, wind speed and relative humidity records could be used in estimating dust concentration group which leads to dust deposition on a PV system.

Potential evapotranspiration for the south coast of Puerto Rico with the Hargreaves-Samani technique

1969 ◽  
Vol 72 (1) ◽  
pp. 57-63 ◽  
Author(s):  
Megh R. Goyal
Keyword(s):  
Water Management ◽  
Puerto Rico ◽  
Potential Evapotranspiration ◽  
South Coast ◽  
Semiarid Region ◽  
Crop Water ◽  
The South ◽  
Water Requirements ◽  
Vegetables And Fruits ◽  
Maximum Minimum

The Hargreaves and Samani model was used to estimate monthly potential evapotranspiration (PET) for Central Aguirre, Fortuna and Lajas substations and Magueyes Island located on the south coast of Puerto Rico. The model uses maximum, minimum and average temperatures. Daily PET varies from 3.68 to 5.37 mm/day in the region with minimum in December and maximum in July. Annual PET was 1613.3 mm/year for Central Aguirre, 1653.5 for Fortuna, 1846.9 for Lajas, 1857.9 for Magueyes Island, with a regional average of 1704.6. These PET values can be used to estimate crop water requirements for vegetables and fruits, to plan irrigation and water management projects, and to schedule irrigation in the semiarid region of Puerto Rico.

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