Characterising deep vadose zone water movement and solute transport under typical irrigated cropland in the North China Plain

Abstract

Understanding the dynamics and mechanisms of soil water movement and solute transport is essential for accurately estimating recharge rates and evaluating the impacts of agricultural activities on groundwater resources. In a thick vadose zone (0–15 m) under irrigated cropland in the piedmont region of the North China Plain, soil water content, matric potential, and solute concentrations were measured. Based on these data, the dynamics of soil water and solutes were analysed to investigate the mechanisms of soil water and solute transport. The study showed that the 0–15‐m vadose zone can be divided into three layers: an infiltration and evaporation layer (0–2 m), an unsteady infiltration layer (2–6 m), and a quasi‐steady infiltration layer (6–15 m). The chloride, nitrate, and sulphate concentrations all showed greater variations in the upper soil layer (0–1 m) compared to values in the deep vadose zone (below 2 m). The average concentrations of these three anions in the deep vadose zone varied insignificantly with depth and approached values of 125, 242, and 116 mg/L. The accumulated chloride, sulphate, and nitrate were 2,179 ± 113, 1,760 ± 383, and 4,074 ± 421 kg/ha, respectively. The soil water potential and solute concentrations indicated that uniform flow and preferential flow both occurred in the deep vadose zone, and uniform flow was the dominant mechanism of soil water movement in this study. The piston‐like flow velocity of solute transport was 1.14 m per year, and the average value of calculated leached nitrate nitrogen was 107 kg/ha∙year below the root zone. The results can be used to better understand recharge processes and improve groundwater resources management.

Responses of soil water dynamic processes and groundwater recharge to irrigation intensity and antecedent moisture in the vadose zone

“…Excessive irrigation not only causes a large amount of water loss through bottom percolation (Bacon, Stone, Binns, Leslie, & Edwards, ; Min, Shen, & Pei, ) but it also wastes valuable irrigation water resources. Also, as a great part of vertical recharge to the local groundwater (Scanlon, Reedy, & Gates, ), it also acts as a source of pollution (e.g., nitrogen leaching) in the intense agricultural regions (Min, Shen, Pei, & Jing, ; Pei et al, ; Pei, Shen, & Liu, ), which results in increasingly serious groundwater environmental pollution and is also closely linked with water percolation (Liu, Sun, Ji, & Simunek, ; Yolcubal, Gündüz, & Sönmez, ; Zhu et al, ). Accordingly, a better understanding of soil moisture movement and water percolation is crucial to developing effective irrigation and protecting hydro‐ecological systems.…”

Is annual recharge coefficient a valid concept in arid and semi-arid regions?

“…It is generally accepted that recharge is correlated with precipitation in some fashions, and many studies adopt the concept of a recharge coefficient (Turkeltaub et al, 2015;Kalbus et al, 2006;Allocca et al, 2014), which is the ratio of the actual recharge to the precipitation, to estimate the recharge (Fiorillo et al, 2015;Allocca et al, 2014). The magnitude of such a recharge coefficient is controlled by a complex interplay of multiple factors such as moisture dynamics in the vadose zone (Schymanski et al, 2008), depth to water table, vegetation, etc., and the recharge coefficient is often regarded as a temporally invariant value at a given location (Fiorillo et al, 2015;Min et al, 2017;Vauclin et al, 1979). Specifically, it is assumed to be primarily controlled by the total precipitation and not too much by the temporal fluctuation of precipitation events (Hickel and Zhang, 2006;Acworth et al, 2016).…”

“…When recharge is estimated as residual in water balance models, it can cause miscalculation as much as an order of magnitude (Scanlon, 2013;Voeckler et al, 2014). When using soil water flow models with measured or estimated soil hydraulic conductivities and tension gradients, similar miscalculation can also occur (Nyman et al, 2014;Gee and Hillel, 1988). In addition, the modeling usually involves upscaling of parameter values over a spatially and temporally discretized mesh from measurements which are made on specific moments and locations.…”

“…Such an upscaling process is not always easy to execute and it could sometimes lead to serious errors. This is particularly true for arid and semi-arid regions where most precipitation may be episodic (occurring in short and unpredictable events) (Modarres and da Silva, 2007;Zhou et al, 2016) and may be confined to restricted portions of the area (Gee and Hillel, 1988).…”

Estimating Deep Drainage Using Deep Soil Moisture Data under Young Irrigated Cropland in a Desert‐Oasis Ecotone, Northwest China

“…Wyatt et al (2017) estimated daily drainage rates at the Oklahoma Mesonet using soil moisture data with site‐specific soil hydraulic properties and a unit‐gradient assumption. In recent years, numerical modeling has become perhaps the most widely used method to estimate deep drainage (Min et al, 2017; Wang et al, 2016). Wang et al (2016) used inverse modeling, including vegetation data, for estimating natural groundwater recharge from a large‐scale soil moisture monitoring network across Nebraska.…”