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Soil moisture

Soil moisture, also known as soil , refers to the amount of contained within the unsaturated zone of above the table, typically quantified as the volumetric —the ratio of the volume of to the total volume of (including solids, , and air), often expressed as a . Surface soil moisture pertains to the top 5–10 cm of , where it directly influences and uptake, while root-zone soil moisture extends deeper (up to 1–2 m) to support growth. This parameter is fundamental to numerous Earth system processes, serving as a key integrator of , , and . In , soil moisture governs water availability, , and overall , with deficits leading to reduced yields and excesses causing or damage. Hydrologically, it regulates the partitioning of rainfall into infiltration versus , modulates , and affects and dynamics. In the , soil moisture drives land-atmosphere feedbacks by controlling fluxes, rates, and regional temperature extremes, making it essential for and modeling. Its variability, influenced by , cover, , and , underscores its role in resilience and worldwide.

Fundamentals

Definition and Importance

Soil moisture refers to the held within the pores of , which can be quantified in two primary ways: volumetrically, as the ratio of the volume of to the total of (denoted as θ, in units of m³ per m³ ), or gravimetrically, as the of per unit of dry , often expressed as a . This exists in various forms, from tightly bound to more mobile states, influencing the 's physical and chemical properties. Soil moisture plays a critical role in by facilitating chemical and physical breakdown processes that contribute to soil development over time. It enables through the soil , allowing elements to dissolve and move to plant roots, while also supporting plant growth by providing the necessary for physiological processes such as and . In , soil moisture levels guide decisions to optimize yields and prevent water stress, whereas in , it determines rates of infiltration, runoff, and , thereby regulating the . Furthermore, as an Climate Variable recognized by the , soil moisture mediates land-atmosphere interactions, influencing weather patterns, propagation, and regional dynamics. The significance of soil moisture was first systematically explored in 19th-century , notably by Eugene W. Hilgard, who in the 1890s linked variations in soil water content to crop yields and irrigation efficiency in arid regions. On a global scale, inadequate soil moisture contributes to , which affects up to 40% of the world's land, exacerbating droughts and posing severe threats to by reducing . This ties directly to , particularly Goal 6 on clean water and sanitation through sustainable water management, and Goal 15 on life on land by addressing soil degradation and ecosystem resilience.

Key Moisture Concepts

Field capacity represents the maximum amount of water that soil can retain against the force of gravity after excess water has drained away, typically measured at a soil water suction of -0.33 (-33 kPa). This state occurs 1-2 days after , when drainage has largely ceased, and the water is held primarily in smaller pores by forces. Volumetric at field capacity varies by ; for example, loams typically hold 0.25-0.35 m³/m³, while sands hold less and clays more due to differences in pore size distribution. The permanent wilting point is the minimum soil moisture level at which plants can no longer extract sufficient water to prevent , even when the soil is shaded and temperatures are favorable for recovery; this occurs at approximately -15 bar suction. Below this threshold, water is held too tightly by soil particles for most plant roots to access it. Volumetric contents at the permanent wilting point range from 0.05-0.10 m³/m³ in sands to 0.15-0.20 m³/m³ in clays, reflecting greater retention in finer-textured soils. Available water capacity, often abbreviated as AWC, is the portion of soil water that plants can readily use, calculated as the difference between field capacity and the permanent wilting point. In medium-textured soils like loams, AWC typically ranges from 0.10-0.20 m³/m³, providing a buffer for plant growth during dry periods. Water below the permanent wilting point is considered unavailable to plants, as it remains bound to soil particles despite its presence. These thresholds are crucial for determining water availability, directly influencing plant physiological processes such as transpiration and nutrient uptake. Soil saturation occurs when all pores are completely filled with , corresponding to a of 0 , allowing free under . At this point, air is displaced from the matrix, and if saturation persists, it can lead to conditions that inhibit root respiration and promote . moisture deficit refers to the shortfall between current and , while surplus indicates excess beyond the 's storage capacity, often leading to runoff or . These concepts are integral to models, such as the Thornthwaite-Mather -water-balance approach, where they help simulate water supply-demand dynamics to predict yields and needs.

Measurement and Monitoring

In Situ Techniques

In situ techniques for measuring soil moisture involve direct, ground-based methods that provide localized data at specific depths and sites, offering high accuracy for point-scale assessments but requiring physical access to the soil. These approaches contrast with by enabling precise, on-site quantification of or potential, essential for of broader systems and detailed hydrological studies. Common methods include sampling-based and probe-based sensors, each suited to different soil conditions and measurement needs, though they often demand site-specific to account for , , and . The gravimetric method serves as the standard reference technique for determining soil by direct sampling. It involves collecting undisturbed soil cores or subsamples from desired depths, weighing them to obtain the wet , oven-drying at approximately 105°C for 24 hours to remove , and reweighing to find the dry . The gravimetric is then calculated as the ratio of loss to dry soil , expressed as a , which can be converted to volumetric using the soil's for comparability with other methods. This destructive approach is labor-intensive, time-consuming due to drying periods, and unsuitable for frequent monitoring, yet it remains the for validating sensor-based techniques owing to its absolute accuracy without needs. Tensiometers provide a direct measure of soil water matric potential, which indicates the energy status of in the and guides decisions. These devices consist of a sealed filled with , connected to a porous inserted into the at a specific depth; as dries, moves out of the into the surrounding , creating a partial that is measured via a manometer or . Standard tensiometers operate effectively in the wet to moderately moist , from 0 to -80 centibars (approximately -0.1 to -0.8 ), beyond which limits readings unless using specialized vacuum-regulating designs. They are widely used for real-time scheduling in , as lower potentials signal increasing plant , though they require periodic maintenance to refill and de-air the system. Neutron moisture meters estimate volumetric soil water content through neutron thermalization, a non-destructive method suitable for deeper profiles. The device emits fast neutrons from a radioactive source (typically americium-beryllium) into the via an access tube; these neutrons slow down upon colliding with atoms in molecules, and the returning neutrons are counted to infer . Measurements can reach depths of 1-2 meters with access tubes, providing integrated values over a spherical of about 30 cm radius, but accuracy depends on -specific to correct for variations in clay content, , and , typically achieving ±0.02 m³/m³ precision. This technique is valuable for long-term field monitoring in research and , though its use of radioactive materials necessitates licensing and safety protocols. Time-domain reflectometry (TDR) measures soil dielectric permittivity by sending electromagnetic pulses along parallel metal rods inserted into the soil, offering rapid, non-destructive volumetric water content estimates. The travel time of the reflected pulse correlates with the soil's dielectric constant, which is dominated by water's high permittivity (around 80) compared to soil solids (3-5) and air (1); empirical models, such as Topp's equation, convert this to water content θ without soil-specific calibration in many cases. TDR sensors achieve high accuracy of ±0.02 m³/m³ across a wide range (0-0.6 m³/m³), support real-time data logging, and are robust in various soils, though performance can degrade in highly saline or air-gapped conditions. Developed in the 1980s, this method has become a staple for precision agriculture and vadose zone studies due to its minimal soil disturbance and automation potential. The heat pulse method infers water content from transient thermal properties using needle-like sensors embedded in the . A heater probe emits a short heat pulse (typically 1-30 seconds), while adjacent thermistors monitor changes; the heat dissipation rate, influenced by water's high , allows calculation of thermal conductivity and , from which volumetric is derived via models like those based on de Vries theory. This approach excels in lysimeters and profile arrays for simultaneous measurement of moisture, , and even water flux, with accuracies around ±0.01-0.03 m³/m³ after , and is particularly useful in heterogeneous or for studying water movement dynamics. Recent refinements, including dual-probe configurations, enhance resolution for near-surface applications. Advances in wireless sensor networks since the have enabled continuous, automated monitoring of soil moisture across fields using IoT-integrated devices. These networks deploy low-power nodes equipped with TDR, , or heat pulse sensors, communicating via radio frequencies (e.g., or ) to a central gateway for , reducing manual labor and enabling spatial mapping over hectares. Early implementations focused on battery-efficient protocols and powering, achieving deployment densities of 1-10 nodes per with refresh rates of minutes to hours; challenges like signal interference in wet soils have been addressed through mesh topologies and . Such systems support scalable precision and environmental , with studies demonstrating up to 30% savings in .

Remote Sensing Methods

Remote sensing methods provide indirect estimates of over large spatial scales using - and aircraft-based sensors, leveraging electromagnetic interactions with the surface to infer content without direct contact. These techniques are essential for global monitoring, offering coverage that methods cannot achieve, and play a key role in climate monitoring by tracking as an Essential Climate Variable. Microwave approaches dominate due to their penetration through clouds and sensitivity to properties, which vary significantly with , while optical and methods complement them in clear-sky conditions. Passive measures natural thermal emissions from the soil at L-band frequencies (around 1.4 GHz), where the inversely correlates with soil moisture because wetter soils emit less microwave radiation. The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission, launched on November 2, 2009, exemplifies this approach, providing global soil moisture maps at a spatial resolution of about 35-50 km with a revisit time of 1-3 days. SMOS retrieves moisture in the top 0-5 cm of soil with an accuracy of approximately 0.04 m³/m³, though performance degrades in areas with dense or saline soils. These sensors are particularly effective for bare or sparsely vegetated surfaces, as higher frequencies increase atmospheric but reduce vegetation opacity. Active microwave remote sensing, such as (), transmits pulses and measures from the soil surface, where soil moisture increases the dielectric constant and thus enhances radar return signals. The Copernicus mission, with Sentinel-1A launched on April 3, 2014, operates at C-band (5.4 GHz) and delivers high-resolution (down to 5 m) soil moisture estimates by inverting models that account for and incidence angle. achieves accuracies around 0.05 m³/m³ for the top 5-10 cm layer, benefiting from its all-weather capability and frequent revisits (6-12 days), but requires corrections for topographic effects in rugged terrains. Combining active and passive data, as in SMOS-Sentinel fusions, improves resolution to 1-3 km while maintaining reasonable precision. Optical and thermal infers soil moisture indirectly through proxies like vegetation indices or land surface temperature, as drier soils lead to higher thermal emissions and stressed vegetation with lower (NDVI) values. NASA's Landsat-8, operational since 2013, and MODIS on /Aqua satellites provide multispectral data at resolutions of 30 m and 250-1000 m, respectively, enabling correlations between shortwave reflectance and surface moisture under clear skies. These methods are limited to the top 1-2 cm and are heavily affected by , atmospheric aerosols, and canopy occlusion, achieving accuracies of 0.05-0.08 m³/m³ only in sparse vegetation areas. They serve as valuable supplements to microwave data for high-resolution mapping in arid regions. Data assimilation models integrate observations with land surface models to enhance soil moisture estimates, propagating surface measurements into root-zone profiles and reducing uncertainties from sparse observations. NASA's (SMAP) mission, launched in January 2015, combines L-band passive radiometry (36 km resolution) with active radar (discontinued in 2015 but fused with ) to produce global maps every 2-3 days at 9-36 km resolution, with an overall accuracy of 0.04 m³/m³ validated against networks. SMAP's assimilates data into models like the Catchment Land Surface Model, improving forecasts for hydrological applications. Both SMOS and SMAP datasets are designated as Essential Climate Variables, supporting long-term climate trend analysis. Key challenges in include interference from vegetation cover, which attenuates microwave signals and masks emissions, and , which scatters waves unpredictably, leading to retrieval errors up to 0.1 m³/m³ in heterogeneous landscapes. Validation relies on ground-based networks like the International Soil Moisture Network, but discrepancies arise from scale mismatches between satellite footprints and point measurements. variations and further complicate inversions, necessitating ancillary data like maps for corrections. Recent developments since 2020 have leveraged to enhance retrievals, particularly in heterogeneous terrains, by training models on multi-sensor to disentangle vegetation and roughness effects. For instance, convolutional neural networks fusing , , and optical achieve sub-1 km resolutions with accuracies improved by 20-30% over traditional physics-based methods in complex environments. The NASA-ISRO NISAR mission, launched on July 30, 2025, employs L- and S-band to generate global soil moisture products at 200 m with a 6-12 day revisit cycle, significantly improving near-surface moisture estimates in vegetated and complex terrains. These approaches, as in the Consistent Artificial Intelligence-based Soil Moisture dataset, enable consistent long-term global monitoring, addressing gaps in legacy missions and advancing applications in and prediction.

Soil-Water Dynamics

Water Retention

Soil water retention refers to the capacity of soil to hold water within its pores against gravitational drainage, primarily through physical forces acting at the soil-water . between water molecules and soil particle surfaces forms thin films around particles, while among water molecules maintains continuity within pores. In smaller pores, —resulting from and the combined effects of and —creates forces that elevate water levels and resist drainage, thereby enhancing retention in unsaturated conditions. Soil texture profoundly influences retention capacity, as finer particles provide greater surface area for adhesion and smaller pores for capillary forces. Clay soils, with high clay content, exhibit stronger retention due to their extensive microporosity, whereas sandy soils drain rapidly owing to larger pores and lower surface area. For example, field capacity—the water content after gravity drainage—in clay soils typically reaches about 0.4 m³/m³, compared to roughly 0.1 m³/m³ in sands. This difference arises because clays hold water at higher suctions via capillary retention, while sands release it more readily at low suctions. The soil water characteristic curve quantifies retention by relating volumetric water content (θ) to soil water potential (ψ), typically expressed in megapascals (negative for unsaturated conditions). A seminal empirical model for this curve is the van Genuchten equation, which provides a continuous, sigmoid-shaped fitting diverse soils: \theta(\psi) = \theta_r + \frac{\theta_s - \theta_r}{\left[1 + (|\alpha \psi|^n)\right]^m} Here, θ_s represents saturated , θ_r residual , α a inversely related to air-entry , n a influencing curve steepness, and m = 1 - 1/n for monotonicity. This model, derived from matching analytical solutions to rise theories, enables prediction of retention across ψ ranges from to . Organic matter and further modulate retention; amendments like increase and aggregate formation, boosting water-holding capacity by 10-20% in coarse-textured soils through enhanced micropore volume and hydrophilic surfaces. Conversely, compaction collapses pores, diminishing retention by reducing available space for capillary water. affects retention via changes in water and , with warmer soils (e.g., above 25°C) exhibiting lower θ at given ψ due to weakened capillary forces. influences retention osmotically, as dissolved salts lower the osmotic potential component of total ψ, requiring higher θ to achieve matric potentials and thus increasing overall for a fixed total ψ.

Water Flow

Water flow in soil refers to the movement of water through the interconnected pore spaces of the soil matrix, driven primarily by gradients in water potential. This transport is governed by physical laws that account for both saturated conditions, where pores are fully filled with water, and unsaturated conditions, where air and water coexist in the pores. In saturated flow, water moves freely under the influence of gravity and pressure gradients, whereas in unsaturated flow, the process is more restricted due to the tortuous paths through water-filled films and capillaries, resulting in slower velocities compared to saturated conditions. The foundational description of soil water flow is provided by , originally formulated for saturated flow through porous media. states that the volumetric flux q (volume of water per unit area per unit time) is proportional to the : q = -K \frac{dh}{dz} where K is the saturated , h is the , and z is the vertical distance. For unsaturated soils, the law is extended as the Buckingham-Darcy law, incorporating the soil water pressure head \psi: q = -K(\psi) \frac{d}{dz} (\psi + z) Here, K(\psi) decreases with increasing soil dryness (more negative \psi), reflecting the reduced connectivity of water pathways in unsaturated conditions. For downward vertical flow, this simplifies to q = -K(\psi) \left( \frac{d\psi}{dz} + 1 \right). This extension highlights that unsaturated flow rates are significantly lower than saturated rates due to the dependence on matric potential gradients. Soil water flow manifests in distinct types based on driving forces and soil saturation. Gravity-driven drainage occurs in saturated soils, where excess water percolates downward under gravitational pull, often following rainfall or irrigation events that exceed soil storage capacity. Capillary rise represents upward unsaturated flow, where water is drawn from a water table or saturated zone into drier overlying soil layers through adhesive and cohesive forces in fine pores, counteracting over distances of several centimeters to meters depending on . Infiltration describes the initial entry of water at the soil surface, transitioning from high initial rates to equilibrium; the initial infiltration rate can be approximated by Horton's empirical equation: f(t) = f_c + (f_0 - f_c) e^{-kt} where f(t) is the infiltration rate at time t, f_0 is the initial rate, f_c is the constant final rate, and k is a decay constant. This process is crucial for surface water entry but slows as surface layers approach saturation. Soil properties profoundly influence water flow rates and pathways. Texture determines saturated hydraulic conductivity K, with coarse-textured sands exhibiting high values around $10^{-4} m/s due to large pores that facilitate rapid drainage, while fine-textured clays have low K on the order of $10^{-9} m/s because of small, tortuous pores that impede flow. Macropores, such as earthworm channels or root voids, create preferential flow paths that bypass the soil matrix, allowing rapid transport of water and solutes at rates approaching saturated conductivity and enhancing overall infiltration in structured soils. Osmotic and pneumatic flows play minor roles in most soil water dynamics. Osmotic flow arises from solute concentration gradients in saline soils, inducing water movement toward regions of lower content across semi-permeable barriers, but its contribution is typically negligible compared to gravitational or matric forces unless levels are extreme. Pneumatic effects, driven by air differences in soil pores, can influence water displacement in aerated or compacted zones, yet they remain secondary to dominant potential gradients in natural settings. Advanced modeling of soil water flow integrates these mechanisms through the Richards equation, which couples water retention and transport in unsaturated media: \frac{\partial \theta}{\partial t} = \nabla \cdot \left[ K(\psi) (\nabla \psi + \nabla z) \right] where \theta is volumetric , t is time, and the term \nabla z accounts for . Derived from combining the with the Buckingham-Darcy law, this simulates transient flow under varying boundary conditions and is widely used in hydrological simulations.

Plant-Soil-Water Relationships

Water Uptake by Plants

absorb from the primarily through their systems via , where moves from the soil solution across semi-permeable root membranes into the root cells due to a gradient, and to a lesser extent by . hairs, which are tubular extensions of root epidermal cells, dramatically increase the surface area available for , enhancing contact between and particles. This allows to extract more efficiently from the soil . The movement of water into and through the plant is largely driven by transpiration pull, explained by the cohesion-tension theory. As water evaporates from mesophyll cells through stomata, it creates (tension) in the vessels, pulling a continuous column of from the roots upward; this tension can reach up to -20 bars in the under high rates. architecture plays a key role in accessing available , with extensive fibrous systems in crops like exhibiting total root lengths of approximately 622 km per plant, maximizing exploration of the volume. In contrast, deep-rooted species such as develop taproots extending up to 7–9 meters or more into the , enabling access to stored in subsoil layers during surface drying. Many form symbiotic associations with arbuscular mycorrhizal fungi, whose hyphae extend far beyond the root depletion zone into the soil, effectively increasing the absorptive surface area and facilitating transport directly to the host . This is particularly beneficial in dry soils, where mycorrhizal often maintain higher status and uptake compared to non-mycorrhizal counterparts by bridging gaps in availability. Water uptake is limited when soil moisture drops below the permanent point, at which the soil is too low (typically around -1.5 ) to sustain osmotic flow into , leading to plant and halted absorption. Additionally, uptake follows diurnal patterns influenced by , with rates peaking at midday when solar radiation and evaporative demand are highest, before declining in the afternoon as decreases.

Consumptive Use and Water Use Efficiency

Consumptive use refers to the total amount of water consumed by crops through evapotranspiration, encompassing transpiration from plant surfaces and evaporation from the soil and intercepted water within the crop canopy. This process directly depletes soil moisture, as water is drawn from the soil profile to sustain plant growth and is not returned to the system, making it a critical factor in agricultural water balance. Under optimal conditions, consumptive use aligns with crop evapotranspiration (ETc), calculated as ETc = Kc × ETo, where Kc is the crop-specific coefficient and ETo is the reference evapotranspiration derived from the FAO Penman-Monteith equation. However, when soil moisture falls below the readily available water threshold, a water stress coefficient (Ks) reduces ETc, limiting consumptive use to conserve soil reserves and prevent plant wilting. Soil moisture availability profoundly influences consumptive use by regulating the rate of water extraction from the root zone, with drier soils promoting stomatal closure to minimize losses. In irrigated systems, management practices such as irrigation can lower consumptive use by 10-20% in crops like while maintaining yields, as reduced evaporation redirects water toward productive transpiration. For instance, in arid regions, consumptive use for major crops like can reach 1,200-1,600 mm per season, heavily dependent on maintaining above 50% of to avoid stress-induced reductions. Water use efficiency (WUE) quantifies the productivity of consumptive use, defined as the ratio of or grain yield produced per unit of transpired or evapotranspired, typically expressed in kg m⁻³ or g kg⁻¹. At the leaf level, intrinsic WUE is measured as the net photosynthetic rate (A_n) divided by (g_s), or A_n / transpiration rate (E), highlighting how soil moisture sustains open stomata for efficient carbon without excessive loss. Adequate soil moisture enhances WUE by maximizing transpiration efficiency (TE = / transpired ), with studies showing improvements in C3 crops like under controlled moisture regimes that avoid . Conversely, prolonged low soil moisture triggers partial stomatal closure, reducing and dropping WUE in field conditions, as observed in across varying types. Improving WUE involves optimizing soil moisture through practices like mulching, which reduces non-productive by 20-40%, thereby increasing the proportion of water allocated to and production. At the crop scale, WUE can be modeled as yield = × TE × harvest index, where maintaining soil moisture near boosts TE via enhanced water uptake. Seminal assessments, such as those using FAO-56 frameworks, demonstrate that integrating soil moisture with elevates WUE in diverse agroecosystems, from 1.0-1.5 kg m⁻³ in dryland to over 2.0 kg m⁻³ in irrigated .

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