Redistribution process of precipitation in ecological restoration activity of Pinus sylvestris var. mongolica in Mu Us Sandy Land, China

School of soil and water conservation, Beijing Forestry University, Beijing, China, 100083 Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China Jinyun Forest Ecosystem Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China Department of Geology and Geophysics, Texas A&M University, College Station, Texas, USA, 77843 5 Inner Mongolia Low Coverage Company, Hohhot, 010000, China


Introduction
China's semi-arid regions have experienced serious and continuous ecological and environment challenges for many decades with one third of the country was classified as desertification area

Research method
To explore the distribution characteristics of precipitation in the reconstructed forest land, we assume that the reconstructed forest land belongs to a relatively uniform landform system, thus we 135 can select a typical sample plot from this system for observation (Taigemiao experimental plot).
The landform in our study area is flat sandy land, as shown in Figure 1, PSM was planted in this area 30 years ago in belts, and the distance between the two belts was 15 meters. Under this uniform distribution of PSM forest land, it would be convenient to choose a PSM plot to monitoring precipitation redistribution process along the vertical direction instead of studying the 140 entire region, which is difficult or even impossible.
To study the redistribution characteristics of PSM forest land in Taigemiao experimental plot of MUSL, we set up an in situ observation system to observe the precipitation distribution in canopy interception, surface runoff, SWS, DSR and sap flow. Since 2015, the experimental field has been established. As the installation of the instrument will inevitably cause soil disturbance, we irrigate 145 the sample plot after the instrument installation to promote soil layer settlement. The observation data were collected a year later, from 2016, and the water distribution of precipitation in the atmosphere, soil layer and DSR are recorded and analyzed. DSR is an important factor for regional water balance research, thus we will use a newly designed lysimeter to measure DSR. As shown in Figure 2, the water source of PSM in MUSL is mainly 150 atmospheric water, the PSM has developed a shallow root system parallel to the ground surface to maximize the area to intercept the precipitation-induced infiltration. We have excavated and flushed the experiment plot to exam the root system distribution and found that the roots of PSM evenly distributed in the open space between the two PSM rows. The root distribution depth is concentrated at 80 cm depth, and few roots can reach 100 cm depth. The capillary water holding 155 height of sandy soil in this area is 80 cm. Therefore, we decide to lay the newly designed lysimeter at the depth of 200 cm, which include a 100 cm of root system, a capillary water rise height of 80 cm and additional 20 cm. Such an installation depth can ensure that the measured DSR will not absorbed by the plant root system. Although soil vapor flow may exist in sandy soil, particularly at shallow depths, the effect of soil vapor flow is regarded as secondary in this investigation. In 160 the future, soil vapor flow sensors are probably needed to quantify the exact nature of vapor flow.
By measuring the DSR and the water content of each soil layer, we can calculate evapotranspiration.
The schematics of the newly designed lysimeter schematics is shown in Figure 2B. The traditional lysimeter measuring face is at the ground surface and the measuring depth equals to the height of 165 the instrument. The newly designed lysimeter can be installed at any depth, depending on the sitespecific requirements. This instrument has two parts, an upper water balance part and a lower measuring part. The balance part has a cylinder with an upper opening and a filter mesh at the bottom. The filter mesh allows soil water to permeate but no soil particles can pass through. The height of the balance part is equal to the height of capillary rise of the in-situ sandy soil. As shown 170 in Figure 2B, when the soil at layer B is saturated, the soil water can rise to layer A because of the capillary force, but it would not overflow the cylindrical barrel, so as to reach a state of equilibrium.
When the upper layer A has moisture infiltration, the moisture balance state is broken, and the excess water will be discharged from layer B into the measurement part. The measurement section uses a tipping bucket water meter to automatically record the infiltration rate. This is the principle 175 of the newly designed lysimeter.
It is necessary to reduce the damage to the in-situ soil layer structure when installing the lysimeter.
As the PSM root system is evenly distributed in the open space of the forest belt, we decide to excavate a soil profile in the middle of the PSM forest to install the lysimeter. The sand structure is relatively loose and easy to collapse. Therefore, before excavation, we need to irrigate the plot 180 to reduce the risk of soil collapse during the instrument installation process. After irrigation, we will excavate a vertical soil profile in the middle of the forest belt. As the height of the instrument is 120 cm and the measuring surface depth is 200 cm, so we need to excavate a soil profile of 320 cm deep. After reaching a depth of 320 cm, we continue to excavate 100 cm in a direction parallel to the forest belt at the bottom of the profile, with a vertical cross section equaling to the side area 185 of the new lysimeter, 30 cm by 120 cm. This will ensure that the soil layer on the upper part of the instrument would remain undisturbed as much as possible. After this, soil moisture probes are installed at targeted depths, as shown in Figure 2. Using the in-situ soil to backfill the excavation and irrigating the soil profile to facilitate the soil settlement, the installation procedure is then completed. It takes a certain time for the soil to settle down, so we need to install the instrument The lower probe contained a heating element to heat the probe continuously. Each probe contained a thermocouple to measure the temperature at any moment. The temperature difference between these two probes was influenced by the stem sap flux rate. As the sap flow went upward, the 215 temperature difference between the two probes decreased. Therefore, by monitoring the temperature difference between the two probes one can calculate the sap flow rate (Granier, 1987).
Previous experiences have shown that in northern China, the average flow rate of the whole tree can be estimated with high precision using the flow rate on the northern side of the trunk of PSM through a simplified model as follows: 220 V= 0.0119 K-1.231 × 3600, K = (dTm -dT) /dT (1) where V is the sap flow rate (cm· hr -1 ), dTm is the maximum temperature difference between the heating probe and the reference probe when there is no sap flow, and dT is the temperature difference between the heating probe and the reference probe when sap flow occurs at any given moment. The total volume of sap flow (F) was: where F was the total volume of sap flow (cm 3 ); n was the number of sampling; Vi was the sap flow rate during the i-th sampling time interval (cm*hr -1 ); As was the area of sapwood (cm 2 ), and it was 196.755 cm 2 ; Δt was the sampling interval (hr). In 2016, the distribution ratios of precipitation in atmospheric water (ET), soil water and DSR in the PSM plot were 92.2%, 7.5% and 0.3%, respectively. We found that ET accounted for most of 290 the precipitation, but one should be noted that the observed proportion of ET in precipitation was likely to be larger than the true value. of the PSM plot decreased by 60.2%. Therefore, we could conclude that vegetation restoration significantly changed the distribution of precipitation in shallow soil. Precipitation was largely converted into groundwater in the BSL plot, while precipitation was intercepted in shallow soil, and large amount of precipitation converted to ET in the PSM plot.  year, the PSM forest has substantially changed the redistribution of precipitation.

Soil water storage measurement
As shown in Table 1 (Table 2). In the PSM plot, precipitation was closely correlated with ET (P = 0.99706), indicating that the increase of precipitation directly promoted the increase of ET. On the other hand, there was no direct correlation between sap flow and precipitation.
As shown in Table 1

SWS characteristics
SWS was calculated according to the soil volumetric water content of each soil layer and soil depth.
The accuracy of the soil moisture sensor (EC-5) decreased during the freeze-thaw period, thus we selected the soil moisture data from March to October for the calculation of SWS in this study. We calculated the annual changes in SWS in for the four years, as shown in Table 1. To compare the differences in SWS changes between dry and wet years, we selected SWS in a wet year (2016) and a dry year (2019) to conduct a more detailed comparison.
As shown in Table 1 To explore the daily change of SWS, we considered the SWS changes in 2016 in more detail.
Because 2016 was a wet year, there were more precipitation events available for comparison. As shown in Fig. 6a, the SWS increased rapidly after precipitation, and SWS was consumed after 415 precipitation. As shown in Fig. 6(b-d), SWS changed from positive to negative after precipitation because of vegetation transpiration and surface evaporation. The attenuation characteristics varied among different seasons. In the two precipitation-evapotranspiration events in the growing season, the SWS returned to 0 mm on 7 days after the cessation of one precipitation event in July and August, but returned to 0 mm on 12 days after the cessation of one precipitation cycle in September 420 (Fig. 6b, c). The soil evapotranspiration maintained a relatively constant rate after the precipitation events in September (Fig. 6d). The main factors affecting soil water storage in summer were transpiration and evaporation, whereas in autumn, transpiration reduced and only evaporation prevailed. We speculated that PSM had entered the dormancy period in late September, although the soil layer had not entered the freeze-thaw period at that time.

Characteristics of DSR
The DSR was determined by using the newly designed lysimeter ( Table 1)

435
In 2016, only 1 mm DSR occurred in the PSM plot, mainly from September 18 to September 20.
According to Figure 6d, even in wet years like 2016, precipitation in the PSM plots could not fully recharge groundwater. By September, the sap flow decreased sharply (Fig. 3a). Without the PSM interception, a small amount of precipitation was able to penetrate the shallow soil layer to become DSR. Most previous studies used remote sensing method for analysis on a large regional scale, but they could not provide sufficient specific experimental data for use in verification (Li and Pan, monitoring data were applied to consider the consequences of vegetation restoration. This study has been carried out for 4 years so far, and continuous data collection must be carried out to generate a long-term time-series dataset. In addition, we suggest the following areas for future   3. There was a freeze-thaw period up to 4 months in this region. In the freeze-thaw period, we could not accurately observe the change of soil moisture. In this study, we chose to show the annual soil moisture, because the thickness of freeze-thaw layer did not change substantially on a daily scale, and the error of soil moisture could be ignored. However, in the analysis at annual scale, we did not use the soil moisture during the freeze-thaw period. Based on the difference of SWS at the 530 end of one year and the beginning of the following year, we found that the soil moisture and DSR changed in the freeze-thaw period. Therefore, it was necessary to study the soil moisture change during the freeze-thaw season using an alternative method.
4. Existing studies have shown that vegetation restoration was conducive to the increase of precipitation in the region, but our observations showed that precipitation in MUSL exhibited significant fluctuations, to the extent that precipitation across most periods were considerably lower than the average precipitation across many years, suggesting that instability was likely in the future development of PSM in MUSL. To date, vegetation restoration has been carried out for 40 years. Although the vegetation coverage was relatively low in the early period and had little impact on the environment, vegetation coverage increased from 5% to 15% between 1979 and 540 2020, research was needed to examine whether the regional precipitation intensity changes need to be considered in more detail or not.

Conclusions
This study focused on the redistribution of precipitation in the PSM and BSL plots through