Water Balance Characteristics of the Salix Shelterbelt in the Kubuqi Desert

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Water Balance Characteristics of the Salix Shelterbelt in the Kubuqi Desert


1. Introduction

Land degradation and desertification constitute significant global ecological challenges with direct implications for human survival and development [1]. While afforestation has proven effective in ameliorating the local ecological environment and mitigating land erosion and soil loss [2], the unique desert climate imposes severe constraints on shelterbelt survival and establishment because of chronic water scarcity. Under this specific climate condition, the water use of a plant generally depends on the water absorbed by the plant, the distribution of the root system, and the sensitivity of the vegetation to soil and atmospheric drought [3]. In light of these circumstances, conducting a comprehensive assessment of the water balance within areas is imperative. This assessment is crucial for scientifically understanding and managing the water supply to sandy region shelterbelts [4]. It also plays a pivotal role in developing suitable strategies for vegetation growth, ecosystem restoration, and tailored reforestation plans in sandy environments.
The water balance of forestland refers to the ability of vegetation to maintain the dynamic water balance of the atmosphere–vegetation–soil during the long-term growth process. This shows that the water balance of forest stands is not just static but is also complex, exhibiting elasticity and a robust dynamic network. This stability involves a balance between forest climate, vegetation, soil, water resources, and other factors [5,6]. In this regard, the study of water balance is carried out through the synergistic effect of plant transpiration, soil evaporation, precipitation, canopy interception, soil moisture, runoff production, and other factors [7]. Spatial variations in these factors inevitably lead to changes in the water balance. Therefore, extensive research is required to investigate the gradients of these influential factors [8].
Vegetation transpiration, soil evaporation, and vegetation canopy interception are collectively called ecosystem total evapotranspiration [9,10]. Vegetation evapotranspiration is by far the largest water flux on the Earth’s land surface. The core components of quantitative evapotranspiration are the determination of water use efficiency and an estimation of the system water balance. A large number of evapotranspiration research methods have been derived from this type of research, including remote sensing research [11], vorticity research [12], Bowen ratio research [13], etc. Each measurement method has advantages and disadvantages. The remote sensing estimation method is affected by the time of the image and spatial resolution limitations [11], and the Bowen ratio method and disaster correlation method are difficult to use to calculate evapotranspiration measurements at the regional/large watershed scale [14]. Therefore, simultaneous field research on rainfall canopy interception, plant transpiration, and soil evaporation is the most accurate and reliable method to obtain total evapotranspiration from forestland [7]. In addition, the amount of soil water also has a certain impact on the water balance of forestland, especially in arid inland river areas with shallow groundwater levels. The connectivity of the soil will affect the supply of underground runoff and groundwater. In this regard, it is necessary to monitor the changing characteristics of the soil moisture content within the vegetation ecosystem in a dynamic manner [15].
There are currently rich research results on water balance. For example, Joffre et al. studied the water balance under different site conditions and obtained the yield in a Mediterranean region [16]. Gerten et al. demonstrated the important impact of climate change on water balance dynamics by simulating runoff and evapotranspiration on a large scale [17]. Shawn et al. studied changes in climate water balance by analyzing the distribution of species at different altitudes [18]. Dai Junfeng et al. studied the water balance of a forest-grass system through a model and found that evapotranspiration was the core of forestland water balance expenditure [19]. Yu Xinxiao and others proposed a water balance equation of a forest ecosystem in a loess area through dynamic research on the water balance of forestland and grassland [20]. However, it is worth noting that the current research on the relationship between water balance and forest water mainly focuses on unilateral research on canopy interception, forestland evapotranspiration, or soil layers, and there is a lack of continuous field research on the water balance of the water–vegetation–soil complex [21]. Comprehensive evaluations of the water balance across entire forest stands are limited. This limitation hampers the development of ecohydrological models for sandy areas and poses challenges to the regulation of forest structure and the implementation of coordinated forest–water management strategies.
The Kubuqi Desert is located in the southwest of China’s Inner Mongolia Autonomous Region, with a fragile ecological environment and serious soil erosion. The establishment of shelterbelts has greatly improved local climate conditions; stabilized the regional ecological environment; and, indeed, led to the success of afforestation in some areas in preventing desertification [22]. Given the current frequency of climate extremes, shelterbelt productivity, quality, and health may be further threatened by growing water budget imbalances. Salix is a pioneer tree species in the Kubuqi Desert shelterbelt. Its excellent adaptability and low water consumption make it widely used in desert afforestation projects, effectively preventing the spread of desert areas. However, detailed studies on the water balance of these Salix species have been limited to date.

To address this gap, this study conducted systematic and quantitative monitoring within the Kubuqi Desert’s Ordos afforestation zone, Inner Mongolia Autonomous Region, China. This study delved deeply into hydrological processes and soil moisture variations during the growing season of Salix shelterbelts. Through the continuous monitoring of water–vegetation–soil, canopy interception, Salix forest transpiration, forest evaporation, soil water storage, etc., the forest water balance status was estimated. Through comprehensive evaluation, this study aimed to elucidate the characteristics of the water balance of these shelterbelts and then provide guidance on water management for ecological restoration in arid and semiarid transitional areas from the perspective of the water balance. This research poses two key questions: first, can desert willow stands in the Kubuqi Desert maintain a water balance during the growing season, and second, based on the characteristics of the water balance, can we determine how improved stand management strategies can be developed in the future?

2. Materials and Methods

2.1. Study Area

The study area is located at the Caositan Forestry Station of the Ordos Afforestation General Field in the Kubuqi Desert of the Inner Mongolia Autonomous Region (Figure 1). The geographical coordinates are 40°14′24″ N, 110°39′14″ E, located on the eastern edge of the Kubuqi Desert. The region has a temperate continental monsoon climate, with an average annual temperature of 6.1 °C, hot days, and cold nights. The average annual precipitation is 273 mm, and the precipitation in the growing season is 247 mm. Westerly and northwesterly winds prevail throughout the year, with an average wind speed of approximately 3.6 m/s. The climate type is classified as mid-temperate arid or semiarid. The growing season of Salix stands is mainly from May to September. The soil is mainly meadow wind–sand soil, and the understory herbaceous vegetation is mainly sandy vegetation.

2.2. Plot Setting and Investigation

The experiment was carried out in June 2022. On the basis of the investigation of the site conditions and forest stand structure of the sample plot, a middle-aged Salix protective forest at the afforestation site was selected as the research object, and a 30 m × 30 m area was randomly selected from each forest stand. In the test plot, basic information such as plant height, diameter at breast height, and crown width was collected.

2.3. Determination of Meteorological Factors

A small automatic weather station was installed in an open and unobstructed location around the sample plot to simultaneously monitor meteorological factors outside the forest, including temperature, wetness index, wind speed, wind direction, solar radiation, and precipitation; data were recorded every 10 min. Simultaneously, three plastic rain tubes with a diameter of 20 cm were randomly placed in the open space of the sample plot for backup and correction.

2.4. Measurement of Throughfall and Stemflow in the Forest and Calculation of Canopy Interception

Following the method outlined by Levia and Germer [23], 9 Salix clumps were randomly selected in the sample plot, as shown in Figure 2. Plastic barrels with an outer diameter of 20 cm were selected to receive penetrating rain. A total of 12 plastic barrels were placed under each Salix clump; 4 rows of collection tubes (the angle between the rows was 90°) were used. The distances between the water collection barrels under the Salix plants and the main trunk were approximately 30, 70, and 120 cm. The rainfall was calculated after the rainfall was measured using a graduated cylinder.

T F = 1 m × F A i = 1 m ( V T ) i × 10

where TF is the throughfall (mm); VT is the volume of penetrating rain in the i-th plastic bucket (mL); m is the number of plastic barrels under the canopy; FA is the cross-sectional area of the plastic bucket mouth (cm2).

Since Salix plants are characterized by multiple branches, we applied the standard branch method to compute the total shrub-generated stemflow volume. A total of 9 Salix clumps with penetrating rain barrels were selected as objects. All base diameter dimensions of each Salix clump were measured and marked with a Vernier caliper. The average base diameter of each Salix clump was calculated; 5 branches were selected from the east, west, south, north, and middle that were closest to the average base diameter (the error in selecting branches did not exceed 3 mm); and a total of 45 stemflow collection devices were installed and arranged. The stemflow collector was affixed using hot melt glue and sealed with waterproof hot melt glue, ensuring that rainwater can flow into the plastic bottle of the collection device through the rubber tube. After each rainfall event, we utilized a measuring cylinder to quantify the stemflow volume (mL) within the bottle.

The formula for calculating trunk stemflow is as follows:

V S = ( 1 5 i = 1 5 V S

) × N

S F = V S / ( S P × 1000 )

where VS is the stemflow volume of the Salix (mL); VS is the stemflow measured after rain on a single branch of Salix (mL); N is the number of Salix branches; SF is the stemflowof the Salix (mm); and SP is the projected canopy area of the Salix (m2).

According to the principle of water balance, canopy interception loss was estimated, which is numerically equal to the difference between total rainfall and net rainfall.

I L = P g N = P g ( T F + S F )

where IL is the canopy interception loss (mm), Pg is the rainfall outside the forest (mm), and N is the net rainfall (mm).

2.5. Measurement of Trunk Sap Flow and Calculation of Stand Transpiration

As shown in Figure 3, we utilized an EMS 62 SAP FLOW SYSTEM (Czech Republic, www.emsbrno.cz (12 December 2023)) for sap flow measurements. The measuring principle is based on the stem heat balance method (SHB) with external heating and internal temperature sensing [24,25]. Within the test area, we selected three well-developed and moderately sized individual Salix clumps. For each clump, we chose standard branches in four cardinal directions: east, west, south, and north. To measure sap flow, we employed a 0.8 mm diameter drill to create holes in the xylem of the Salix stem, where we installed stemflow sensors. These sensors were enclosed in tinfoil bags and securely fastened with insulating tape. Stem sap flow in the Salix plants was continuously monitored throughout the growing season using Mini32 data collection devices, which collected and recorded fluid flow data. The measured sap flow rate was then extrapolated from individual branches to the forest stand level.
Following the approach outlined by researchers in [26,27], we employed the cross-sectional area of the basal diameter as the scaling factor to estimate shrub transpiration for the entire forest stand.

T =   1 n i = 1 n ( A t / A i ) ( 1000 J S / ρ A s )

where At, Ai, and As are the total basal stem cross-sectional area in the sampling plot, the basal cross-sectional area of stem i, and the land surface area of the plot (m2), respectively. Js is the sap flow rate in stem i (kg·h−1), ρ is the density of water (kg·m−3), and n is the number of gauged stems.

2.6. Understory Evapotranspiration and Community Evapotranspiration

Following the research plan of [28,29,30], we positioned three custom-made microlysimeters beneath each Salix clump to measure sap flow and monitor understory evapotranspiration, which included soil evaporation and understory vegetation transpiration. These three lysimeters were placed at specific locations on the east side of each Salix clump, near the root neck, half of the crown width, and at the crown edge.

The microlysimeters were constructed using PVC pipes. The inner cylinder had an 11 cm inner diameter and was held at a height of 20 cm, with a 16 cm diameter sleeve. An impermeable layer of pearl cotton separated the sleeve and the inner cylinder to prevent rainwater from entering the gap. The bottom of the inner cylinder was fitted with 300-mesh yarn, permitting moisture passage, and securely fastened with tape (as illustrated in the image).

Throughout the research period, we removed the microlysimeter for weighing twice daily at 7:00 and 19:00 using an electronic balance with a precision of 0.01 g. The electronic balance remained in a fixed location and was protected by a windproof cover during weighing. Two measurements were taken, and the difference between them represented the understory evapotranspiration for that particular day.

E T u n d e r = 1 3 ( 10 × ( ( Δ M s ρ ) / A l

) )

where ETunder is the amount of evapotranspiration under the forest on different single days (mm·d−1); Al is the surface area of the microlysimeter (cm2); ρ is the density of water (g·m−3); and ΔMs is the daily water storage change in the microlysimeter (g·d−1).

Evapotranspiration from artificial shrub communities in deserts consists of shrub transpiration and underbrush evapotranspiration [31].

E T = T + E T u n d e r

where ET is the evapotranspiration of the Salix community, and ET is the total evapotranspiration of the Salix community.

2.7. Determination of Soil Hydrological Characteristics and Calculation of Water Storage Capacity

The soil profile was excavated at the base of the Salix forest to a depth of 80 cm for a total of 4 layers, each spaced 20 cm apart. To minimize errors, three soil samples were randomly collected from each layer using a ring knife. These soil samples were subsequently transported to the laboratory and subjected to soil water retention rate measurements via the ring–knife soaking method.

To monitor the soil moisture dynamics near the Salix trees within the shelterbelt, representative locations were selected. Soil moisture sensors (EC-5, METER, Pullman, WA, USA) were deployed to continuously monitor changes in the soil volumetric moisture content across each soil layer (0–20, 20–40, 40–60 cm). Three sensors are randomly arranged in each layer. Subsequently, soil moisture gains and losses during specific time intervals were calculated.

W i = 10 × V i × h i

Δ W = ( W e W i )

where hi and Vi are the thickness (cm) and water volume content (cm3·cm−3) of the i-th layer of soil, respectively; ΔW is the soil moisture gain; and loss (mm), We, and Wi are the water storage capacities of the 1 m soil layer at the end and beginning of the stage, respectively (mm).

2.8. Water Balance and Yield Calculations for the Sample Plots

The following formula was used to calculate the forestland yield for each observation period.

P = E T + Δ W + R + Q

where P is the amount of rainfall outside the forest during a certain period (mm); ET is the forest stand evapotranspiration during a certain period (mm), including canopy interception (IL) and community evapotranspiration (ET mm); ΔW is the change in water storage in the 0~60 cm soil layer during a certain period (mm); R is the yield in a certain period (including surface runoff and soil flow, mm); and Q is the exchange of water from the study soil layer to the deep layer or lateral direction during a certain period (mm). A positive value indicates that soil moisture leaks from the study soil layer to the deep layer or laterally, and a negative value indicates that the study soil layer receives water input from the deep soil or the upper slope.

During the study period, the surface runoff and in-soil flow in the soil layer in the sample plot were very low and can be ignored; R = 0. Q is a positive value and indicates that there is water side leakage from the study soil layer to the deep layer, which is the flow of forest resources in this study.

4. Discussion

4.1. Analysis of Forestland Precipitation Redistribution Characteristics

The redistribution of rainfall by the forest canopy is a dynamic and complex process. Factors such as substructures, rainfall characteristics [32,33], and local microclimates [34] all have certain impacts. Among these factors, rainfall characteristics outside the forest are among the core influencing factors [35]. Research shows that penetrating rain and stemflow generally account for 70% to 90% of rainfall outside the forest [36]. During the study period (6.15–10.30), penetrating rain, stemflow, and canopy interception in the Salix forest accounted for 88.64%, 2.68%, and 8.68%, respectively, of the total precipitation, which is similar to the conclusions of Levia [37].
Through regression analysis and curve fitting, rainfall was shown to be positively correlated with throughfall, stemflow, and canopy interception. This finding is consistent with the conclusions of most related studies. The canopy interception rate exhibited a downward trend as a logarithmic function. This may be because, when the rainfall is low, the branches of the canopy trees can completely intercept the rainfall, and the interception rate is close to 100% [38]. As rainfall increases, the total rainfall gradually increases and eventually reaches the saturated canopy interception volume [39,40]. When the rainfall outside the forest continues to increase, the interception amount of the forest canopy itself will remain basically constant [41]. This means that small rainfall events are more likely to cause canopy interception losses than large rainfall events.

4.2. Analysis of Forestland Transpiration and Understory Evapotranspiration

Research shows that the stemflow of different plant species has significant diurnal and seasonal dynamic characteristics [42]. In this study, the total transpiration of Salix salix showed obvious differences between seasons during the study period. The transpiration increased significantly beginning in August, peaked in early September, and began to decrease significantly in October, indicating an overall parabolic shape. Studies have shown that a saturated water vapor pressure difference has a greater impact on vegetation transpiration than a constant water vapor pressure difference [43]. In this study, affected by heavy rainfall in August, vegetation increased transpiration to increase water absorption and nutrient uptake in the soil, and transpiration increased significantly. However, photosynthetically active radiation is also the main factor affecting stemflow [44]. In August, because of frequent rain and relatively weak solar radiation, the amount of Salix transpiration did not reach its peak in August. Dynamic changes in transpiration and environmental factors are not completely synchronized [45]. Therefore, maximum transpiration occurs in early September.

4.3. Analysis of the Total Evapotranspiration and Components of Salix

Given differences in meteorology, forest stands, soil characteristics, etc., it becomes difficult to directly compare differences in water balance between different regions. Therefore, we selected the main influential factors of the water balance for analysis and comparison. To facilitate comparisons between different studies, we expressed each water balance component as a proportion of precipitation during the same period, such as the canopy interception rate, the tree transpiration rate, the soil water storage change rate (soil water storage change/precipitation amount), and the yield flow rate. The following is a description of the total evapotranspiration and component characteristics of the Salix shelterbelt in the Kubuqi Desert during the growing season:

The total evapotranspiration in the Kubuqi Desert Salix shelterbelt growing season (June–October 2022) was 185.62 mm, which was 77.58 mm (29.5%) lower than the precipitation in the same period (263.20 mm). The components and proportions of precipitation during the same period were as follows: forest evapotranspiration, 94.43 mm (35.88%); forest stand transpiration, 68.34 mm (25.97%); and canopy interception, 22.85 mm (8.68%). Table 4 shows the evapotranspiration data for shrubs in different regions of the world. According to the table data, in 2006, the local forest stand had evapotranspiration greater than precipitation and was in a state of water deficit. However, after the long-term maintenance of the forestland and the adaptation of tree species, although rainfall declined at this stage, the vegetation basically ensured normal growth. The evapotranspiration value of the Salix in this study was similar to that of the Salix in the Mu Us Desert and the Creosotebush in the Santa Rita Experimental Range (which lies entirely within the Sonoran Desert) but significantly lower than that of the Salix community on the Loess Plateau and in the Yanchi area of Ningxia. This may be due to dry climate conditions that reduce evapotranspiration in vegetation to retain more water for its growth. In addition, the proportions of the average evapotranspiration components in the Mu Us Desert to the average precipitation in the same period are as follows: understory evapotranspiration, 89.03 mm (31.74%); canopy interception, 47.69 mm (17%); and stand transpiration, 43.24 mm (15.41%). The ranking of evapotranspiration is slightly different from this study, which may be due to density, meteorological factors, and other factors, which results in less transpiration in forest trees in the Mu Us Desert [46]. Moreover, we can see that evapotranspiration is greater than precipitation in the Loess Plateau and the Chihuahuan Desert, which indicates that, in addition to relying on rainfall, local vegetation also needs other water supply channels to ensure vegetation growth.

4.4. Soil Water Storage Change Characteristics

The water storage capacity of soil profoundly affects the stability of ecosystems in response to drought. During periods of heavy rainfall, the soil in the root layer can store additional water to maintain the transpiration and growth of plants in the forest. This process is reflected in fluctuating changes in the soil moisture content. In this study, the total evapotranspiration of the Salix plantation during the growing season was 77.58 mm lower than the precipitation during the same period, but around August, the forestland experienced a water deficit (Q 54] in their study using isotope technology; i.e., plantations may utilize additional water sources.
The concentrated heavy rainfall in August caused the soil moisture in the forest to reach a peak. However, as shown in Figure 9b, the peak soil moisture content did not occur after the maximum rainfall in early August but instead occurred during the sub-maximum rainfall in mid-August. This may be because the soil moisture content is delayed because of excessive drought in the early stage. After the concentrated rainfall in August, although the soil did not reach a fully saturated state, in September and after, although the rainfall frequency was not high, the soil moisture content remained higher than before August.

4.5. Shelterbelt Water Balance and Runoff Impact

Given differences in the response of different soil layers to precipitation input and evapotranspiration output, these processes have varying degrees of impact on the drought resistance of a forest. Therefore, there are also differences in the time lags of different precipitation inputs and evapotranspiration outputs, which have been confirmed in the studies of Liu Wenhao and others [8]. Therefore, it is necessary to comprehensively consider all the factors to scientifically assess the forestland water balance.

The total precipitation in the 2022 growing season from June to October reached 263.2 mm. Notably, concentrated precipitation and heavy rainfall began to occur in August, causing the soil moisture content to reach a peak and the soil water storage to increase. The Q value shows that, except for Q > 0 in August, Q was negative in the other months. This shows that, except in August, the soil layer needs additional water input, and the yield is negative at this time. In fact, when we were in the sand digging a pit at the bottom of a willow (we carried out soil excavation and determined the location of the root system in order to bury the water content sensor), we found that soil at about 1 m deep was in a slightly moist state. This may be due to the recharge of groundwater or a phenomenon caused by water storage in the previous year. The counter-supply of groundwater at this time can ensure that the forest stand can still maintain normal evapotranspiration growth in June and July when there is less rainfall. When August comes, the heavy rainfall allows soil moisture to be exchanged deeply or laterally, thereby allowing the soil moisture to replenish water during later water shortages.

Overall, the low consumption of water in the study area makes it possible for the forestland to maintain its water balance throughout the growing season (for which the cumulative Q value is positive). Notably, our study mainly used the water balance method for calculation, so there may be some uncertainty in the results. To more accurately estimate the various components of the forestland water balance, future research on forest runoff and water input should be supplemented.


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