Deep soil recharge (DSR) (at depth greater than 200
Recharge is an important source of groundwater budget and it is also a fundamental process that links the surface hydrological processes (e.g., precipitation), vadose zone process (e.g., infiltration and soil moisture dynamics), and the saturated zone process (e.g., groundwater flow) (Sanford, 2002; McWhorter and Sunada, 1977). How to accurately estimate recharge has remained a persistent challenge and an active research topic in the hydrological science community over many decades (Gee and Hillel, 1988; Scanlon, 2013; Sanford, 2002). 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). In this study, we will challenge the concept of using a constant recharge coefficient to estimate the recharge in arid and semi-arid regions based on a multi-year field investigation.
As water tables in many arid and semi-arid regions are relatively deep
(greater than 2
In general, there are three methods of measuring DSR in arid and semi-arid regions. The first method is an empirical approach which assigns a constant recharge coefficient associated with a certain precipitation event (Allison et al., 1994; Jiménez-Martínez et al., 2010). The empirical approach is simple to use but it lacks a rigorous theoretical base, and the recharge coefficient has to be calibrated through a groundwater flow model in the region, which is often not available.
The second method is a modeling approach involving numerical models such as HYDRUS (Šimůnek et al., 2012), SWAT (Arnold et al., 2012), UNSATH (Fayer, 2000), SWIM (Krysanova et al., 2005), and SWAP (van Dam, 2000) to calculate DSR. Modeling is an efficient way to test different hypothetical scenarios and it may be used to predict DSR in the future if the model is calibrated carefully. Detailed water balance models can be used for irrigated agriculture, but they usually cannot predict evapotranspiration accurately, especially when plants suffer seasonal water stress and plant cover is sparse (Gee and Hillel, 1988). 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).
The third method includes a cluster of experimental techniques such as isotopic tracers (Klaus and McDonnell, 2013), water fluxes (Katz et al., 2016), and lysimeters (Scanlon, 2013). Among them, lysimeters are instruments that directly measure the hydrological cycle in infiltration, runoff, and evaporation. Generally, this instrument is located in an open observation field or as a controlled device, working either solely or in groups (Good et al., 2015). In a typical lysimeter, soil is filled into a column surrounded by impermeable lateral boundaries; thus, water can only enter or leave the column from upper or lower boundaries (Duncan et al., 2016; Fritzsche et al., 2016). A drainage system is usually placed at the bottom (Glenn et al., 2013). The depth of soil in the column depends on the experimental purpose. Experiments can be done with the same type of soil at different depths in a single column or in different columns but at the same depth. The soil surface can be cultivated with different crops or left as bare land. Observations can be recorded with weight or volume of water.
Application of above-mentioned methods for assessing DSR in arid and semi-arid regions has met a variety of challenges, primarily due to the fact that precipitation events often happen in the form of short pulses with highly variable intensity (Collins et al., 2014). The intermittent and unpredictable characteristics of precipitation events led to highly variable moisture and nutrient levels in the soils (Beatley, 1974; Huxman et al., 2004). It is unclear how the precipitation amount, time, and interval will affect the water moisture of arid and semi-arid regions, especially the change of deep soil water storage.
In this study, a new type of lysimeter is designed to accurately measure the amount of DSR in arid and semi-arid regions. With the help of a 3-year (2013–2015) field investigation with this new lysimeter, one can answer the following question: is the concept of an annual recharge coefficient valid or not for estimating DSR at a given location in arid and semi-arid regions? Before the introduction of this new type of lysimeter, it is necessary to briefly explain the challenges faced by the conventional lysimeter for studying DSR in arid and semi-arid regions.
Lysimeters have been used to access the amount of water consumed by
vegetation for more than 300 years (Howell et al.,
1991). The type of lysimeter that is specifically designed to measure
evapotranspiration (ET), called the precision-weighing lysimeter, has been
developed within the past six decades. In order to satisfy different
requirements and needs, there are various designs of weighing
lysimeters, with surface areas ranging from 1.0 to over
29
The following issues deserve special attention when applying the conventional lysimeter for measuring recharge. Firstly, soil layers are inevitably disturbed when installing the instrument, so the result may not reflect the actual recharge in native (undisturbed) soils (Weihermüller et al., 2007). Secondly, the cost is too high to use multiple lysimeters to observe large-scale infiltration (Stessel and Murphy, 1992). Thirdly, when precipitation strength is relatively light and concentrated, a large lysimeter cannot sensitively and rapidly measure DSR (Goldhamer et al., 1999; Farahani et al., 2007). The conventional lysimeter often cannot answer the questions as to what soil layer different levels of precipitation can infiltrate and how much the infiltration amount is under different levels of precipitation (Gee and Hillel, 1988; Ogle and Reynolds, 2004).
The conventional lysimeter as shown in Fig. 1a may meet additional
challenges when applied to arid and semi-arid regions. Firstly, the
water table depths in arid and semi-arid regions may be much greater
than the maximal depth of a conventional lysimeter
(2.5
To resolve the above-mentioned issues faced by the conventional lysimeter, a new type of lysimeter is designed with specific considerations of the unique precipitation patterns and soil characteristics in arid and semi-arid regions. This new lysimeter is illustrated schematically in Fig. 1b.
Schematic diagram of conventional lysimeter
This new lysimeter has a few innovations (see Fig. 1b) that can be
outlined as follows. Instead of setting the upper boundary of the
lysimeter at ground surface, the new design has its upper boundary at
a designed depth (denoted as depth A in Fig. 1b) where infiltration
will be measured. A cylindrical container with a diameter of 20 to
40
Before the measurement, one necessary preparation is to inject water from the top of the instrument at depth A using water pumps; the injection will stop until water starts to drip out from the base at depth B. One usually has to wait 10 days to allow the water profile in column AB to reach equilibrium. When water stops flowing out from depth B, the soil water in the column is regarded as reaching its equilibrium state, in which the soil moisture at depth B reaches the maximum field capacity. Under such an equilibrium status, the amount of infiltration entering the upper surface of the lysimeter will be discharged (with the same amount) from the base of the lysimeter after a certain delay time.
The proposed new method has a few innovative features that have not been considered in previous studies. Firstly, it can measure DSR at any given layer of a multi-layer soil system using a single apparatus installed in the field. Secondly, continuous real-time measurements can be recorded over any given time period; thus, a time series of DSR can be obtained, which will be very useful to understand the soil water dynamics at sandy areas of arid and semi-arid regions. Thirdly, the apparatus is portable and easy to install; thus, a large amount of data can be collected in various locations of a study area using multiple lysimeters, and spatial recharge distribution can also be obtained straightforwardly. This method is field tested in arid and semi-arid sandy regions of western China. It provides key references for the evaluation of water resources, water balance, and the stability assessment of sand-fixing vegetation in arid and semi-arid areas. It also provides data that are much needed for evaluating soil water contents and groundwater resources of those areas. An important feature of this new lysimeter is that it can provide reliable DSR data to examine the concept of the annual recharge coefficient when comparing with the precipitation data.
Figure 2 shows the location of the study which is located in Ejin Horo
Banner, on the eastern margin of Mu Us Sandy Land in the Ordos Basin
of China (geographic location: 39
Geographic location of the experimental area.
In terms of geological structure, Mu Us Sandy Land is in the Ordos
Basin, a large-scale syncline sedimentary basin with nearly
north–south striking axis, and is of Mesozoic and Paleozoic ages. The
basin covers an area of 640
Deposited in the basin are, in turn, Lower Paleozoic carbonate rocks,
Upper Paleozoic–Mesozoic clastic rocks, and Cenozoic sedimentary rocks
with a total depth of more than 6000
The hydrostratigraphic units of the Ordos Basin are quite complex,
consisting of multiple connected aquifers. Following the order from
bottom to top, the multiple aquifers are primarily made from various
rock types of a karst aquifer consisting of Precambrian and Ordovician
limestone, a fractured aquifer consisting of Carboniferous and
Jurassic clastic rocks, a porous-fractured aquifer of Cretaceous
clastic rocks, and a porous aquifer consisting of unconsolidated
Cenozoic and Quaternary sediments. Generally speaking, Mu Us Sandy
Land has relatively rich groundwater resources. The shallow
groundwater reservoir is estimated to hold about 120.3 billion metric
tons of freshwater. Groundwater is mainly recharged by precipitation
with an annual average recharge amount of 1.4 billion metric
tons. Fine sands are the dominating sediments observed in the
experimental site. In the upper 200
Research on the relationship between precipitation and DSR of bare sand land in arid and semi-arid regions is beneficial to understand the soil water dynamics of those regions. Because vegetation is absent, complexity related to transpiration process by plants is not a concern. Based on two time series of real-time data of precipitation and DSR, one can examine the relationship between DSR and precipitation. This study can serve as a basis for further study of DSR in semi-fixed and fixed sand lands with different fractional vegetation covers.
On 1 September 2012, a mobile sand dune within the study site was set
as the monitoring plot (geographic location:
39
The statistics of precipitation and DSR are shown in Table 1, which
reveals that there is an obvious difference of precipitation at the
experimental plot from 2013 to 2015. The annual precipitation is
83
It appears that there is no clear correlation between the annual DSR and the annual precipitation according to the data of 2013–2015. In another words, use of the annual recharge coefficient for the study site becomes questionable as such a coefficient implies that there is a close correlation between the annual DSR and the annual precipitation, which is not supported by the data of 2013–2015 here. Therefore, we will scrutinize the precipitation pattern and intensity more closely to decipher the connection of precipitation and DSR in the following.
The annual precipitation–DSR relationship from 2013 to 2015.
Research on bare sandy soil water dynamic processes usually focuses on
temporal and vertical differences (Ritsema and Dekker, 1994; Postma
et al., 1991). In terms of temporal soil moisture variation over an
annual cycle, the process could be divided into soil moisture
replenishment, depletion, and relatively stable periods. In terms of
vertical soil moisture variation, soil water content usually first
increases with depth and then decreases based on an interplay of
mutual infiltration and evaporation processes. In general, soil could
be divided as a surface dry sand layer, a layer with drastic moisture
change, and a layer with relatively stable moisture
content. Specifically, the soil deeper than 160
In our study site, 2013 is an especially dry year with only
83
Precipitation and DSR patterns in 2013.
In 2014, the annual precipitation is 205.6
The strongest single-day precipitation in 2014 is 15
Precipitation and DSR patterns in 2014.
Precipitation and DSR patterns in 2015.
As shown in Fig. 5, the total annual precipitation of 2015 is
186.4
Percentage of valid precipitation in total precipitation amount.
Interannual statistics of strong precipitation and its percentage in total annual precipitation amount.
Based on observational data and analysis in Sect. 3.2.1, one can see
that precipitation intensity, to some extent, influences DSR. For the
sake of illustration, the precipitation intensity for bare sand land
is roughly classified into light, moderate, and strong events with
precipitation amounts less than 6
According to this classification, statistics of moderate to strong
precipitation events and their percentage shares in the annual
precipitation from 2013 to 2015 are shown in Table 2. In 2013, there
are only two precipitation events with intensity greater than
6
Among these 3 years, 2015 has the largest percentage of
moderate-to-strong precipitation over the annual precipitation. However, in
this same year, one has seen the smallest ratio of annual
DSR/precipitation ratio or annual recharge coefficient (see
Table 1). This implies that the annual DSR does not seem to be
positively correlated to the annual total precipitation. This finding
has a few profound consequences. It basically states that assigning
a constant annual recharge coefficient for a particular soil
regardless of precipitation patterns is not a good practice, because
annual DSR is not always proportional to the total annual
precipitation. Instead, it appears to be more closely related to
individual precipitation events stronger than 10
The single-day intensive precipitation contribution to DSR in 2013.
Table 3 lists the number of strong precipitation (with amount greater
than 10
As shown in Table 3, the strongest single-day precipitation
(32
In summary, one may conclude that annual DSR in arid and semi-arid regions mainly relies on strong precipitation events, but the determination of the threshold for strong precipitation events that directly contribute to DSR is still unclear and requires further investigation.
Under the condition of continuous precipitation, it may be difficult
to discretize precipitation into individual events. The following
example illustrates a procedure to deal with this situation. As shown
in Fig. 6, there is a 13-day continuous precipitation process in 2013
from 27 July to 8 August, and the accumulative precipitation is
43.8
This improved lysimeter is on the real-time dynamic monitoring of DSR, and it provides reliable evidence for an accurate evaluation of precipitation-related recharging capability of bare sand lands in arid and semi-arid regions. However, there are a number of issues that deserve further attention and require additional investigations in the future. The moisture evaporation, the soil absorption of moisture, and the water infiltration of post-evaporative redistribution are all very complex processes, especially in arid and semi-arid regions. It is sometimes difficult to clearly distinguish the amount of evaporation and DSR with conventional methods as outlined in the introduction. This study selects precipitation and infiltration data during the period from 1 April to 30 November, so the influence of freeze–thaw process during winter is avoided, and the experimental design and data analysis are simplified. For these reasons, the next steps should be a full-term monitoring, systematic study on DSR, as well as a study on the soil temperature and daily temperature influences on DSR.
Although this experiment does not address the issue of soil temperature effect on DSR in great detail, the relationship between DSR and soil temperature is evident. In general, a higher temperature means a stronger evaporation demand and thus an often smaller DSR.
Through the analysis of this study, one can see that the use of an
annual recharge coefficient for the study area is not supported by the
data collected from the new lysimeter, as the annual recharge is not
positively correlated with the annual total precipitation. Instead, we
find that the recharge is somewhat positively correlated with a few
strong precipitation events (greater than 10
This investigation is based on detailed analysis of precipitation and DSR data at the study site without involving modeling effort which certainly will be explored in the future as well. This study represents our first attempt of questioning the application of a recharge coefficient concept in arid and semi-arid regions.
This study uses a newly designed lysimeter to study three consecutive
years (2013–2015) of DSR underneath bare sand land on the eastern
margin of Mu Us Sandy Land in the Ordos Basin of China. The objective
is to identify the characteristics of the DSR distribution and the
factors affecting the DSR distribution. Specifically, we like to
examine if the commonly used recharge coefficient concept can be
applied for arid and semi-arid regions such as the eastern margin of
Mu Us Sandy Land of China. The following conclusions can be drawn from
this study:
The annual recharge coefficient concept is generally inapplicable for
estimating DSR in the study site. Precipitation pattern, including precipitation intensity and
precipitation season, significantly influences DSR. The temperature influences the DSR/precipitation ratio, which is lower
in summer than in other seasons, given the similar precipitation
intensity. DSR is not correlated with the annual precipitation. Instead, it is
correlated with the strong precipitation (greater than 10
The data used in this study can be accessed by contacting the corresponding author directly.
The authors declare that they have no conflict of interest.
This study was supported with research grants from the Ministry of Science and Technology of the People's Republic of China (2013CB429901). Edited by: Graham Fogg Reviewed by: two anonymous referees