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

<p>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.</p><p>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’s.</p><p>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.</p>

scholarly journals Remote sensing-based soil water balance for irrigation water accounting at the Spanish Iberian Peninsula

2018 ◽  
Vol 380 ◽  
pp. 29-35 ◽  
Author(s):  
Jesús Garrido-Rubio ◽  
Alfonso Calera Belmonte ◽  
Lorena Fraile Enguita ◽  
Irene Arellano Alcázar ◽  
Mario Belmonte Mancebo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Water Balance ◽  
Iberian Peninsula ◽  
Soil Water ◽  
Irrigation Water ◽  
Water Governance ◽  
Soil Water Balance ◽  
Water Requirements ◽  
Water Accounting

Abstract. Temporal series maps of irrigated areas, and the corresponding irrigation water requirements based on remote sensing, is a recognized tool contributing to water governance at different scales, from water user associations to whole river basin districts. These thematic cartographies offer a first estimation of the crop irrigation requirements, and a biophysical based approach of the temporal and spatial distribution of the crop water use in the cultivated areas. This work describes the operational application of these methodologies, providing valuable information for water governance and management purposes. The basic products obtained in the whole Spanish part of the Iberian Peninsula during the period 2014–2017 were: (i) annual maps of irrigated crops based on time series of multispectral satellite imagery; and (ii) the direct remote sensing-based water accounting, by quantifying agricultural water flows (e.g. rainfall, irrigation, evapotranspiration, drainage and recharge), through a remote sensing-based soil water balance. Hence this paper provides a remote sensing based water accounting approach, which relies on dense time series of multispectral imagery acquired by the multisensor constellation arranged by Landsat 8 and Sentinel-2 satellites, jointly with meteorological data and agronomic knowledge. Then, based on these purpose and approach, annual and monthly maps of net irrigation water requirements have been elaborated at the most practical spatial and temporal scales for water governance purposes over big areas such river basin districts. This work summarizes the methodologies used and discuss the technical and non-technical feasibility of the proposed approach.

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 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.

Combining the FAO56 agrohydrological model and remote sensing data to assess water demand in a Sicilian irrigation district

2020 ◽  
Author(s):  
Matteo Ippolito ◽  
Mario Minacapilli ◽  
Giuseppe Provenzano
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Water Use ◽  
Irrigation Water ◽  
Remote Sensing Data ◽  
Irrigation Scheduling ◽  
Irrigation District ◽  
Sensing Data ◽  
Spatiotemporal Distributions ◽  
Crop Parameters

&lt;p&gt;Agricultural water use in irrigated areas plays a key role in the Mediterranean regions characterized by semi-arid climate and water shortage. In the face of optimizing irrigation water use, farmers must revise their irrigation practices to increase the drought resilience of agricultural systems and to avoid severe damages in agro-ecosystems. In this direction, during the last decades, the research has been focused on mathematical models to simulate the process of driving mass transport and energy exchanges in the Soil-Plant-Atmosphere system.&lt;/p&gt;&lt;p&gt;The objective of the paper was to test the suitability of the combination of FAO56 agro-hydrological model with remote sensing data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform, to assess the spatiotemporal distributions of crop water requirement and to schedule irrigation in an irrigation district of the south-west of Sicily, Italy.&lt;/p&gt;&lt;p&gt;The proposed approach allowed obtaining the spatiotemporal distributions of soil and crop parameters used in the FAO56 model implemented in a GIS environment to simulate the water balance, as well as to assess the actual irrigation strategy. The GIS database was organized to include soil and crop parameters, as well as the irrigation volumes actually delivered to each farmer; the latter data can be used not only as input for water balance to evaluate the efficiency of the actual irrigation strategies but also to identify different irrigation scheduling scenario obtained by the FAO56 procedure.&lt;/p&gt;&lt;p&gt;The first application was carried out for the period 2014-2017, to identify a combination of irrigation scheduling parameters to be implemented in the model aimed at reproducing the ordinary strategy adopted by the farmers, based on the spatiotemporal variability of soil and climate forcings. When the model outputs were aggregated for single crop types, a fairly good agreement was found between simulated and actual seasonal irrigation volumes delivered either at the level of district and secondary units. Alternative scenarios of irrigation water distribution were then identified and analyzed, to provide irrigation technicians and policymakers a decision support tool to improve the efficiency of irrigation systems and to optimize the distribution based on the availability of water resources.&lt;/p&gt;

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