Estimation of Evapotranspiration Rates and Root Water Uptake Profiles From Soil Moisture Sensor Array Data

Li, Weiyu; Wainwright, Haruko M.; Yan, Qina; Zhou, Haiyan; Dafflon, Baptiste; Wu, Yuxin; Versteeg, Roelof; Tartakovsky, Daniel M.

doi:10.1029/2021wr030747

Cited by 4 publications

(12 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, since the internal permeability of the swollen SAP is much smaller than the permeability of the soil matrix [49] we treat the SAP as being completely impermeable to water flow. Then, computing the probability that a given point within the SAP-soil mixture is encompassed by a randomly-placed swollen SAP grain [50] yields the new porosity of the SAP-soil mixture, ε = ε control e −ϕ (7) where ϕ = V SAP /V is the total volume fraction occupied by swollen SAP with V SAP = N SAP ν SAP and V ≈ N soil ν soil /(1 − ε control ) representing the total swollen SAP volume (neglecting the soil grains) and the total system volume, respectively. Finally, assuming for simplicity that the hydraulic radius R is set by the soil grain size and is therefore unchanged upon SAP addition, and that the pore space tortuosity is also unchanged upon SAP addition, then yields our final approximate prediction for the SAP-soil mixture permeability k:…”

Section: Results Of Coefficient Of Permeability Measurementsmentioning

confidence: 99%

“…Optimum management of this resource is particularly important from the point of view of agricultural production or biotechnological solutions used in environmental engineering [4,5]. The physicochemical properties of the upper soil layer will determine the mutual interactions between water infiltration, runoff, and evaporation under given climatic conditions, and therefore influence its usability for supporting plant growth [6,7]. Hence, in recent decades, grains of super-absorbent polymers (SAP) have attracted increasing interest as soil additives to rationally tune these properties and to stabilize the soil [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Characteristics of Time-Dependent Changes of Coefficient of Permeability for Superabsorbent Polymer-Soil Mixtures

et al. 2022

View full text Add to dashboard Cite

Water uptake dynamics of superabsorbent polymers (SAP) in soil is of key importance for the optimum application of these materials in environmental engineering and agriculture, so goal of this paper is to determine time dependent values of coefficient of permeability for various SAP-soil mixtures. Retaining water in soil is a key requirement in critical zones to support plant growth. There is an urgent need for technologies that can increase soil water retention, given the increasing prevalence of droughts and scarcity of clean water as the climate changes, combined with the rising demand for food by a growing world population. SAPs are materials that can absorb significant amounts of water, and thus have tremendous potential to help increase water retention in soil. However, while some studies have characterized the equilibrium swelling behavior of SAPs in soil, how their addition influences the time-dependent flow of water through soil remains poorly understood. Here, we address this gap in knowledge by directly measuring the coefficient of permeability of SAP-soil mixtures, testing different soil grain sizes, SAP grain sizes, and different SAP-soil ratios. We find that SAP addition can dramatically hinder the flow rate of water through soil—reducing the permeability by several orders of magnitude, and in some cases causing complete blockage of water infiltration, at mass fractions as small as 1%. In this scenario coefficient of permeability of 1.23 × 10−4 m/s dropped by a factor of ~10 after 14 min, a factor of ~100 after 36 min, and by nearly a factor of ~1000 after 63 min, eventually causing complete blockage of infiltration after 67 min. Authors concluded that in this particular situation the size and quantity of SAP particles was enough to nearly completely fill the available pore space resulting in rendering the soil column almost completely impermeable. Moreover, we demonstrate that these effects are well-described by a simple hydraulic model of the mutual interactions between SAP and soil grains, providing more generally-applicable and quantitative principles to model SAP-soil permeability in applications. Ultimately, this work could help evaluate the optimal proportions and grain sizes of SAPs to use for a given soil to simultaneously achieve a desirable permeability along with increased water holding capacity in the plant root zone.

show abstract

Section: Results Of Coefficient Of Permeability Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Characteristics of Time-Dependent Changes of Coefficient of Permeability for Superabsorbent Polymer-Soil Mixtures

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Algorithm 1 summarizes the EnKF strategy described above. General considerations allow one to expect this algorithm to significantly outperform the previous versions of EnKF used to estimate ET from soil‐moisture data (Li et al., 2021; Pan & Wood, 2006; Reichle et al., 2008) in terms of either accuracy or efficiency or both. Unlike these one‐dimensional methods, Algorithm 1 accounts for the horizontal component of the water flux, which is likely to be pronounced in heterogeneous soils subjected to drip irrigation.…”

Section: Alternative Strategies For Et Estimationmentioning

confidence: 99%

“…A key advantage of ensemble-based (Bayesian) data assimilation (DA) methodologies is that their estimates of the relevant system parameters and state variables are equipped with uncertainty (error) bounds (Boso & Tartakovsky, 2022). Among these tools, ensemble Kalman filter (EnKF) has gained popularity because of computational expediency; among other hydrologic applications, it was used to estimate, from soil-moisture sensor-array data, water content and total ET rate (Pan & Wood, 2006;Reichle et al, 2008) and spatial distributions of ET rates and root water-uptake (Li et al, 2021) in vertical (1D) soil columns.The vertical-flow assumption alleviates the computational cost of ensemble-based DA techniques, for example, variational DA, EnKF and particle filters, and is arguably adequate at the basin scale. At the field scale of interest to smart agriculture, the 1D assumption implies a homogeneous soil with sprinkler/spray irrigation patterns that are similar to rainfall.…”

mentioning

confidence: 99%

“…

Smart agriculture relies on modern data collection and analysis technologies to reduce water consumption and increase crop yield. In the process, the data collected by a network of soil-moisture sensors are used to improve predictions of infiltration rate (Wang & Tartakovsky, 2011), wetting depth (Sinsbeck & Tartakovsky, 2015, evapotranspiration (ET) rate (Li et al, 2021), etc. We focus on ET estimation, because its improved accuracy is pivotal to the optimization of crop irrigation (Martín et al, 2021), the assessment of the impact of inundation (Ban et al, 2018), etc.

…”

mentioning

confidence: 99%

See 1 more Smart Citation

Fast and Accurate Estimation of Evapotranspiration for Smart Agriculture

Tartakovsky

2023

Water Resources Research

Self Cite

View full text Add to dashboard Cite

The ability to quantify evapotranspiration (ET) is crucial for smart agriculture and sustainable groundwater management. Efficient ET estimation strategies often rely on the vertical‐flow assumption to assimilate data from soil‐moisture sensors. While adequate in some large‐scale applications, this assumption fails when the horizontal component of the local flow velocity is not negligible due to, for example, soil heterogeneity or drip irrigation. We present novel implementations of the ensemble Kalman filter (EnKF) and the maximum likelihood estimation (MLE), which enable us to infer spatially varying ET rates and root water uptake profiles from soil‐moisture measurements. While the standard versions of EnKF and MLE update the predicted soil moisture prior to computing ET, ours treat the ET sink term in Richards' equation as an updatable observable. We test the prediction accuracy and computational efficiency of our methods in a setting representative of drip irrigation. Our strategies accurately estimate the total ET rates and root‐uptake profiles and do so up to two‐orders of magnitude faster than the standard EnKF.

show abstract

Estimating evapotranspiration from soil moisture using the improved soil water balance method in cold mountainous areas

Lai,

Tian,

Kang

et al. 2023

Journal of Hydrology X

View full text Add to dashboard Cite

Estimation of Evapotranspiration Rates and Root Water Uptake Profiles From Soil Moisture Sensor Array Data

Cited by 4 publications

References 48 publications

The Characteristics of Time-Dependent Changes of Coefficient of Permeability for Superabsorbent Polymer-Soil Mixtures

The Characteristics of Time-Dependent Changes of Coefficient of Permeability for Superabsorbent Polymer-Soil Mixtures

Fast and Accurate Estimation of Evapotranspiration for Smart Agriculture

Estimating evapotranspiration from soil moisture using the improved soil water balance method in cold mountainous areas

Contact Info

Product

Resources

About