Soil Moisture Datasets of the Zhonggou River
Basin in the Loess Plateau of Gansu Province

Zhang, J.¹  Di, L.^1*  Li, X. Y.²  Chen, Z. N.³  Huang, H. X.⁴  Wang, A. M.⁵ 
Fang, S. M.¹  Ru, H. L.⁵  Jing, G. Y.¹  Zhang, X. M¹  Fei, J. E.¹  Ren, Y. B.⁶

1. College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China;

2. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China;

3. Gansu Institute of Forestry Science, Lanzhou 730020, China;

4. College of forestry, Gansu Agricultural University, Lanzhou 730070, China;

5. Pingliang institute of soil and water conservation Science, Pingliang 744000, China;

6. College of Agriculture and Forestry Science and Technology, Longdong University, Qingyang, 745000, China

Abstract: Based the National Natural Science Foundation of China ??Studies on Forest structure of Robinia pseudoacacia effect on the erosion control and ecological water consumption in Loess Plateau??and ??Temporal and spatial variation of Robinia pseudoacacia forest stand structure and hydrological effect in typical small watershed of the loess hilly-gully region in Gansu??.The robinia pseudoacacia planted in 1970s and natural recovery grassland were selected research site. Ten sample plots of forest land and three sample plots of grassland were set up according to the changes of vegetation type, forest age and site characteristics. The soil moisture of all samples was measured by drying method and Time Domain Reflectometer (TDR). The maximum depth of soil moisture measurement pipe is 3 meters, and the maximum depth of soil drill is 2 meters. In 2018, the complete observation of all sample plots was achieved, and the measured data of soil gravimetric moisture content and volumetric moisture content during the growing season were obtained. The dataset includes: 1.13 geographical location and topographic data of the observed plots, as well as the forest age, density, DBH and other main stand structure data; 2. Measured data of soil weight water content and volume water content from April to October, 2018.Format of data: XLSX. Datasets size: 252 KB. The partial dataset has been published online in the journal of Arid Zone Research on 15^th July, 2019.

Keywords: soil moisture, soil volumetric moisture content, robinia pseudoacacia, the Loess Plateau

1 Introduction

The climate drought and precipitation in the Loess Hilly Region of Gansu Province are less and unevenly distributed, low forest vegetation coverage, deterioration of ecological environment and serious soil erosion in this area. The relationship between vegetation and water is the core issue of ecological restoration and vegetation construction in the Loess Plateau of Gansu province^[1-3]. China has invested a series of key forestry ecological projects in this region, and a large area of ecological forests such as Robinia pseudoacacia, Pinus tabulaeformis, Platycladus orientalis, Hippophae rhamnoides and Caragana korshinskii have been constructed. However, in the process of ecological restoration in early large-scale plantation, the characteristics of natural environment and spatial and temporal distribution of soil moisture were neglected. In order to meet the needs of strong evapotranspiration of plants, the plantations have rapidly expanded their roots and utilized deep soil water storage, resulting in soil degradation in plantation grassland^[4]. At the same time, the tree species selection is not scientific, and the way of construction is not reasonable, resulting in a single tree species structure, high planting density, survival rate and preservation rate is low. Even if they survive, they grow very slowly and enter the degeneration stage earlier. As a result, a series of problems such as poor stability of forestry ecosystem, stagnation of growth and regeneration of forest trees, low ecological effect, soil drying, and decline of groundwater level have emerged one after another^[5-7]. Because the only source of soil moisture is rainfall, soil water consumption is much larger than precipitation, which leads to a long-term deficit of soil moisture^[8]. Consequently, the expected effect of ecological engineering construction has not been achieved. Therefore, it is of great theoretical significance for guiding the restoration and sustainable development of plantation vegetation in this area to study the eco-hydrological process of typical plantation in this area and to grasp the distribution of soil moisture in this area.

2 Metadata of Dataset

The name, author, geographical region, time, dataset files, data publishing and sharing service platform and data sharing policy of In situ soil moisture dataset in the Zhonggou River Basin of Loess Plateau (2018)^{[ 9]}are listed in Table 1.

3 Survey of Research Area and Data Development Method

3.1 Survey of Research Areas

The study area is located in Jingchuan County, Gansu Province (Figure. 1). It is a typical loess hilly and gully area. Slope direction: sunny slope, semi sunny slope, shady slope and semi shady slope, of which semi sunny slope is the main one^[11]. The climate in the study area is typical continental climate, with sunshine duration of 2,274 hours, annual average temperature of 10.7 ^oC, frost-free period of 174 days, annual average rainfall of 555 mm, annual evaporation of 1,181.6 mm, humidity of 0.81-1.04, dryness of 0.95?C1.28^[12]. The soil is black loam soil, yellow loam soil and brown soil. The vegetation type belongs to the forest grassland transition zone. The existing forest land area of the county is 5,420 km², and the forest coverage rate is 47.33%. The artificial forest planted in Guanshan forest farm is 132.7 km², mainly Robinia pseudoacacia^[7]. The experimental area of the project is located in Zhonggou river basin (35??20'N, 107??31'E) of Guanshan Forest Farm. The watershed covers an area of 2.09 km² and an elevation of 1,072-1,351 m. The vegetation type belongs to the transition zone between forest and grassland. Robinia pseudoacacia accounts for 92% of the total forest area. It can be roughly divided into four different forest ages: 20 years, 25 years, 30 years and 35 years.

Table 1  Metadata of ??In situ soil moisture dataset in the Zhonggou River Basin of Loess Plateau (2018)??

The stand stereo structure is simple, besides Robinia pseudoacacia, there are arbor such as Populusspp, Platycladus orientalis, Pinus tabulaeformis, Paulowniaspp and Salix matsudana etc; Shrub include Amorpha fruticosa, Prunus da­vidiana, Hippophae rhamnoides, Ca­r­agana korshinskii, Artemisia gme­linii, Stipa breviflora, Lespedeza fioribun­da, Syringa persica, Hippo­phae rh­a­­mn­oides Linn and Xanthocera sorbifolia etc; Understory herbs includeStipa breviflora, Astragalus adsurgens, Pennisetum centrasiaticum, Bothrio­chloais­cha­e­m­um, Setaria faberi and Che­nopodium album L and so on^[13?C15].

3.2 Raw Data Acquisition

3.2.1 Basic Information of Sample Plots

On the basis of comprehensive consideration of stand structure and site differentiation, 10 plots of Robinia pseudoacacia with different slope orientation, gradient, age and density and 3 plots of Grassland Slope were selected (See Table 2. Fig. 2 is the conventional plot of Robinia pseudoacacia forest and 3 is the Grassland Slope plot.).

3.2.2 Soil Moisture

The volumetric water content and the weight water content of soil were measured by TDR and drying method, respectively.

(1) Measurement of Soil Volume Moisture Content ^[15-16]

Measuring soil volumetric water content according to the transmission time of electromagnetic wave emitted by the detector (see Figure 4).

Table 2  Information sample plots of Zhonggou river basin in the Loess Plateau of Gansu province

Methods: TDR tubes were buried in 13 selected sample plots in the previous year. After calibration, trees germinated in the middle and late April of the following year until the end of October, which was a complete growing season. In theory, TDR tubes were measured every 15 days, and then added after raining. (The actual operation depends on the weather conditions and the time interval from the previous sampling. Sometimes individual sample plots did not be measured because of the water inflow in the measuring tube, resulting in data missing.)

The depth of measurement varies according to slope, aspect, age and planting density. The specific settings are as follows: Three 3-meter-long TDR tubes were buried in each sample plot of No. 1, No. 3, No. 4 and No. 5 respectively. Two 3-metre TDR tubes were buried in No.2 sample plot. Two 2-metre TDR tubes were buried in each runoff field of No. 6 and No. 11 sample plots. Three 2-meter TDR tubes were buried in each sample plot of No. 7, No. 8 and No. 9. TDR tubes of 3 meters and 2 meters were buried in each sample plot of No. 10 and No. 12 plots, respectively. Two 1.5-meter TDR tubes were buried in sample No. 13. Maximum test depth is 300 cm. The probe of t TDR is put into the observation tube during measurement. Measure 0-10, 10-20, 20-40, 40-60, 60-80 cm respectively. Read a data every 20 cm downward and record it. The measuring time basically keeps synchronization with the earth drilling observation.

Figure 2  Test plot No. 3

(2) Soil Weight and Water Content

Methods: From the middle of April when trees began to germinate to the end of October after defoliation, they were measured every 15 days (Figure 5) and added after rain. In actual measurements, adjustments are made according to weather conditions (sampling time will be lengthened by continuous precipitation) and the time interval from the previous sampling. Soil samples were taken from top to bottom with drills at different depths. Sampling depths were 0-120 cm, stratified by 0-10, 10-20, 20-40, 40-60, 60-80, 80-100 and 100-120 cm respectively. See Formula 1 for Calculating Soil Weight and Water Content.

                                      (1)

where, Q is soil moisture (%), W₁ is dry aluminium box weight (g), W₂ is (wet soil + aluminium box) weight (g), W₃ is (dry soil + aluminium box) weight (g)

4 Data Results

During the growing season from May to October, thesoil moisture content of Robinia pseudoacacia plantations with different densities showed as follows (Table 3, 4): 1600 trees??hm^-2 (18.75%) > 2196 trees. hm^-2 (15.93%) > 750 trees??hm^-2 (15.92%) > 4563 trees??hm^-2 (11.87%). Soil moisture content in different topographic locations, of which the Robinia pseudoacacia forest (upper) in the tableland surface is best, the middle in the Robinia pseudoacacia forest on the plateau (lower) in the tableland surface and the ditch Robinia pseudoacacia forest, and the worst in the beam of Robinia pseudoacacia forest. As far as slope aspect is concerned, soil moisture in shady slope is the best, in semi-shady slope and sunny slope is the middle, and in semi-sunny slope Robinia pseudoacacia plantation is the worst. As far as the vertical variation of soil moisture is concerned, it generally shows that the surface water content is the largest, which decreases with the deepening of the soil layer and then tends to be stable. For different topographic locations, the coefficient of variation of soil moisture of Robinia pseudoacacia forest on the tableland surface is the smallest and the soil moisture is relatively stable, while that of Robinia pseudoacacia forest on the beam is 90 cm thick and the water condition is the worst. Robinia pseudoacacia forest on the tableland surface (below) and Robinia pseudoacacia forest on the gully are in the middle. The change of slope direction is that the change of soil moisture of sunny slope and semi-sunny slope is more active than that of shady slope and semi-sunny slope, in which the sunny slope is more stable than the semi-sunny slope and the shady slope is more stable than the semi-sunny slope^[17].

Table 3  Soil volumetric moisture content in May 2018(partly)

Table 4  Mass water content of soil in May 2018 (partly)

5 Discussion and Conclusions

The seasonal variation of soil moisture in Robinia pseudoacacia plantation during the annual growth season was studied. It was found that the seasonal variation of soil moisture in Robinia pseudoacacia plantation could be divided into consumption period (May-June), replenishment period (July), regression period (August-September) and stabilization period (October). Despite the increase of rainfall in June, soil moisture is still declining, which may be attributed to the increased demand for water at the early growth stage of Robinia pseudoacacia and the enhanced evaporation of forest land, resulting in a much larger soil water consumption than supply. In July, the soil moisture fluctuated greatly in different plots, mainly because the strong rainfall had a significant impact on the surface layer, which made the surface soil moisture increase sharply. However, with the evaporation after rain strengthening, the soil moisture would change greatly. As far as the vertical change of soil moisture is concerned, the soil water content shows a similar trend with the change of rainfall. The continuous observation for many years can be used as an important index data of the regional ecological environment change. It can also be used as the basic input data for climate model, hydrological model and vegetation growth analysis.

Author Contributions

Di, L. made the total design of the layout of the experiment and the development of the data set. Chen, Z. N. assisted in experimental design and field observation layout. Li, X. Y. was mainly responsible for data analysis. Wang A. M., Jing, G. Y., Zhang, X. M., et al. were responsible for data collection. Di, L., and Zhang, J. carried out data verification and wrote manuscript.

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