Remote sensing–based soil water balance for irrigation water accounting at plot and water user association management scale

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.

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Assessing Irrigation Water Use with Remote Sensing-Based Soil Water Balance at an Irrigation Scheme Level in a Semi-Arid Region of Morocco

Remote Sensing ◽

10.3390/rs13061133 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1133

Author(s):

Mohamed Hakim Kharrou ◽

Vincent Simonneaux ◽

Salah Er-Raki ◽

Michel Le Page ◽

Saïd Khabba ◽

...

Keyword(s):

Remote Sensing ◽

Water Balance ◽

Soil Water ◽

Irrigation Water ◽

Management Practices ◽

Irrigation District ◽

Soil Water Balance ◽

Balance Model ◽

Irrigation Water Use ◽

Semi Arid

This study aims to evaluate a remote sensing-based approach to allow estimation of the temporal and spatial distribution of crop evapotranspiration (ET) and irrigation water requirements over irrigated areas in semi-arid regions. The method is based on the daily step FAO-56 Soil Water Balance model combined with a time series of basal crop coefficients and the fractional vegetation cover derived from high-resolution satellite Normalized Difference Vegetation Index (NDVI) imagery. The model was first calibrated and validated at plot scale using ET measured by eddy-covariance systems over wheat fields and olive orchards representing the main crops grown in the study area of the Haouz plain (central Morocco). The results showed that the model provided good estimates of ET for wheat and olive trees with a root mean square error (RMSE) of about 0.56 and 0.54 mm/day respectively. The model was then used to compare remotely sensed estimates of irrigation requirements (RS-IWR) and irrigation water supplied (WS) at plot scale over an irrigation district in the Haouz plain through three growing seasons. The comparison indicated a large spatio-temporal variability in irrigation water demands and supplies; the median values of WS and RS-IWR were 130 (175), 117 (175) and 118 (112) mm respectively in the 2002–2003, 2005–2006 and 2008–2009 seasons. This could be attributed to inadequate irrigation supply and/or to farmers’ socio-economic considerations and management practices. The findings demonstrate the potential for irrigation managers to use remote sensing-based models to monitor irrigation water usage for efficient and sustainable use of water resources.

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Green-blue water accounting in a soil water balance

Advances in Water Resources ◽

10.1016/j.advwatres.2019.05.012 ◽

2019 ◽

Vol 129 ◽

pp. 112-117 ◽

Cited By ~ 12

Author(s):

Arjen Y. Hoekstra

Keyword(s):

Water Balance ◽

Soil Water ◽

Soil Water Balance ◽

Blue Water ◽

Water Accounting

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Estimating Evapotranspiration of an Apple Orchard Using a Remote Sensing-Based Soil Water Balance

Remote Sensing ◽

10.3390/rs8030253 ◽

2016 ◽

Vol 8 (3) ◽

pp. 253 ◽

Cited By ~ 24

Author(s):

Magali Odi-Lara ◽

Isidro Campos ◽

Christopher Neale ◽

Samuel Ortega-Farías ◽

Carlos Poblete-Echeverría ◽

...

Keyword(s):

Remote Sensing ◽

Water Balance ◽

Soil Water ◽

Apple Orchard ◽

Soil Water Balance

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Exploring the Use of Vegetation Indices for Validating Crop Transpiration Fluxes Computed with the MOHID-Land Model. Application to Vineyard

Agronomy ◽

10.3390/agronomy11061228 ◽

2021 ◽

Vol 11 (6) ◽

pp. 1228

Author(s):

Tiago B. Ramos ◽

Lucian Simionesei ◽

Ana R. Oliveira ◽

Ramiro Neves ◽

Hanaa Darouich

Keyword(s):

Remote Sensing ◽

Water Balance ◽

Soil Water ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Vegetation Indices ◽

Remote Sensing Data ◽

Soil Water Balance ◽

Growing Seasons ◽

Crop Coefficients

The success of an irrigation decision support system (DSS) much depends on the reliability of the information provided to farmers. Remote sensing data can expectably help validate that information at the field scale. In this study, the MOHID-Land model, the core engine of the IrrigaSys DSS, was used to simulate the soil water balance in an irrigated vineyard located in southern Portugal during three growing seasons. Modeled actual basal crop coefficients and transpiration rates were then compared with the corresponding estimates derived from the normalized difference vegetation index (NDVI) computed from Sentinel-2 imagery. On one hand, the hydrological model was able to successfully estimate the soil water balance during the monitored seasons, exposing the need for improved irrigation schedules to minimize percolation losses. On the other hand, remote sensing products found correspondence with model outputs despite the conceptual differences between both approaches. With the necessary precautions, those products can be used to complement the information provided to farmers for irrigation of vine crop, further contributing to the regular validation of model estimates in the absence of field datasets.

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Reducing sugarcane irrigation demand through planting date adjustment in Alagoas State, Brazil

Revista Brasileira de Engenharia Agrícola e Ambiental ◽

10.1590/1807-1929/agriambi.v25n2p75-81 ◽

2021 ◽

Vol 25 (2) ◽

pp. 75-81

Author(s):

Ronaldo S. Resende ◽

Thais Nascimento ◽

Tatiane B. de Carvalho ◽

Julio R. A. Amorim ◽

Lineu Rodrigues

Keyword(s):

Water Balance ◽

Soil Water ◽

Irrigation Water ◽

Planting Date ◽

Soil Water Balance ◽

Planting Dates ◽

Sugarcane Cultivar ◽

Irrigation Water Demand ◽

Subsurface Drip ◽

Brazilian Northeast

ABSTRACT Sugarcane is both an important crop for the Brazilian Northeast economy, which faces severe water scarcity, and a water-intensive crop. Thus, it is important to develop irrigation strategies to reduce irrigation water demand in the region. This study aims to determine the sugarcane planting date that results in the maximum rainwater availability to the crop in the growing cycle. The crop effective precipitation was estimated from a soil water balance performed during three planting cycles of sugarcane, cultivar ‘RB 92579’. The crop was planted under subsurface drip irrigation in five months: October, November, December, January, and February, corresponding to the dry season period of the region. The experiment was conducted at the Açúcar e Álcool Coruripe Mill, located in the Coruripe municipality, State of Alagoas, Brazil, during the years 2012 to 2016. For all planting dates and growing cycles studied, the average effective rainy precipitation was equal to 30% of the total rainfall under irrigated conditions and 54.5% without considering the irrigation component in the soil water balance. November was the planting date that resulted in the minimum irrigation depth for the sugarcane growing cycle, with the potential irrigation water saving ranging from 5 to 129 mm.

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