Soil moisture as a potential variable for tracking and quantifying irrigation: A case study with proximal gamma-ray spectroscopy data

Filippucci, Paolo; Tarpanelli, Angelica; Massari, Christian; Serafini, Andrea; Strati, Virginia; Albéri, Matteo; Raptis, Kassandra Giulia Cristina; Mantovani, Fabio; Brocca, Luca

doi:10.1016/j.advwatres.2019.103502

Cited by 42 publications

(44 citation statements)

References 40 publications

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“…This equation fits the output of a full SVAT model (M o , EF) for a generic case to a range of input values of Fr and T* [6]. The simplified geometric algorithm based on the triangle shape, developed by [16,26], allows one to calculate M o from Equation (10). Thus,…”

Section: Soil Surface Moisture Availability Estimation (M O )mentioning

confidence: 99%

“…Similarly, retrieval of soil moisture and vegetation parameters from remotely sensed data has been very promising using microwave remote sensing techniques [7]. Other techniques for inferring soil moisture include: gamma radiation, hyperspectral, thermal and reflected solar radiation, proximal remote techniques such as cosmic-ray neutron and proximal gamma ray techniques [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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Limitations in Validating Derived Soil Water Content from Thermal/Optical Measurements Using the Simplified Triangle Method

Kasim¹,

Carlson

Usman

2020

Remote Sensing

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We assess the validity of the surface moisture availability parameter (Mo) derived from satellite-based optical/thermal measurements using the simplified triangle method. First, we show that Mo values obtained from the simplified triangle method agree closely with those generated from a soil/vegetation/atmosphere/transfer (SVAT) model for scenes over a field site at the Allahabad district, India. Next, we compared Mo values from the simplified triangle method for these same overpass scenes with surface soil water content measured at depths of 5 and 15 cm at this field site. Although a very weak correlation exists between remotely sensed values of Mo for the full scenes and measured soil water content measured at both depths, correlations increasingly improve for the 5 cm samples (but not for the 15 cm samples) as pixels were limited to increasingly smaller vegetation fractions. We conclude that the simplified triangle method would yield reasonable values of Mo and demonstrate good agreement with ground measurements, provided that validation is limited to pixels with little or no vegetation and to soil depths of 5 cm or less.

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Section: Soil Surface Moisture Availability Estimation (M O )mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Limitations in Validating Derived Soil Water Content from Thermal/Optical Measurements Using the Simplified Triangle Method

Kasim¹,

Carlson

Usman

2020

Remote Sensing

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“…Jalilvand et al [13] applied the SM2RAIN method with different settings for the evapotranspiration term to estimate irrigation water over the Miandoab plain, in Iran. Filippucci et al [14] obtained good performances in estimating water applied for irrigation over a pilot field in Italy by exploiting in-situ soil moisture observations obtained through an advanced sensor based on Proximal Gamma-Ray spectroscopy as the SM2RAIN input. Alternative approaches exploiting soil moisture to estimate irrigation can be found in the literature.…”

Section: Introductionmentioning

confidence: 99%

Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region

et al. 2020

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Despite irrigation being one of the main sources of anthropogenic water consumption, detailed information about water amounts destined for this purpose are often lacking worldwide. In this study, a methodology which can be used to estimate irrigation amounts over a pilot area in Spain by exploiting remotely sensed soil moisture is proposed. Two high-resolution disaggregation based on physical and theoretical scale change (DISPATCH) downscaled soil moisture products have been used: Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) at 1 km. The irrigation estimates have been obtained through the SM2RAIN algorithm, in which the evapotranspiration term has been improved to adequately reproduce the crop evapotranspiration over irrigated areas according to the Food and Agriculture Organization (FAO) model. The experiment exploiting the SMAP data at 1 km represents the main work analyzed in this study and covered the period from January 2016 to September 2017. The experiment with the SMOS data at 1 km, for which a longer time series is available, allowed the irrigation estimates to be extended back to 2011. For both of the experiments carried out, the proposed method performed well in reproducing the magnitudes of the irrigation amounts that actually occurred in four of the five pilot irrigation districts. The SMAP experiment, for which a more detailed analysis was performed, also provided satisfactory results in representing the spatial distribution and the timing of the irrigation events. In addition, the investigation into which term of the SM2RAIN algorithm plays the leading role in determining the amount of water entering into the soil highlights the importance of correct representation of the evapotranspiration process.

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“…Soil moisture changes can be derived from in situ observations (Brocca et al, 2015) or from satellite‐based radar data (Brocca et al, 2014). Later, this approach was also used to estimate irrigation volumes (Brocca et al, 2018; Dari et al, 2020; Filippucci et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Estimating water balance components in irrigated agriculture using a combined approach of soil moisture and energy balance monitoring, and numerical modelling

Schulz

Becker

Richard‐Cerda

et al. 2021

Hydrological Processes

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Information on water balance components such as evapotranspiration and groundwater recharge are crucial for water management. Due to differences in physical conditions, but also due to limited budgets, there is not one universal best practice, but a wide range of different methods with specific advantages and disadvantages. In this study, we propose an approach to quantify actual evapotranspiration, groundwater recharge and water inflow, i.e. precipitation and irrigation, that considers the specific conditions of irrigated agriculture in warm, arid environments. This approach does not require direct measurements of precipitation or irrigation quantities and is therefore suitable for sites with an uncertain data basis. For this purpose, we combine soil moisture and energy balance monitoring, remote sensing data analysis and numerical modelling using Hydrus. Energy balance data and routine weather data serve to estimate ET 0. Surface reflectance data from satellite images (Sentinel-2) are used to derive leaf area indices, which help to partition ET 0 into energy limited evaporation and transpiration. Subsequently, first approximations of water inflow are derived based on observed soil moisture changes. These inflow estimates are used in a series of forward simulations that produce initial estimates of drainage and ET act , which in turn help improve the estimate of water inflow. Finally, the improved inflow estimates are incorporated into the model and then a parameter optimization is performed using the observed soil moisture as the reference figure. Forward simulations with calibrated soil parameters result in final estimates for ET act and groundwater recharge. The presented method is applied to an agricultural test site with a crop rotation of cotton and wheat in Punjab, Pakistan. The final model results, with an RMSE of 2.2% in volumetric water content, suggest a cumulative ET act and groundwater recharge of 769 and 297 mm over a period of 281 days, respectively. The total estimated water inflow accounts for 946 mm, of which 77% originates from irrigation.

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Soil moisture as a potential variable for tracking and quantifying irrigation: A case study with proximal gamma-ray spectroscopy data

Cited by 42 publications

References 40 publications

Limitations in Validating Derived Soil Water Content from Thermal/Optical Measurements Using the Simplified Triangle Method

Limitations in Validating Derived Soil Water Content from Thermal/Optical Measurements Using the Simplified Triangle Method

Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region

Estimating water balance components in irrigated agriculture using a combined approach of soil moisture and energy balance monitoring, and numerical modelling

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