1 Introduction

Opencast mining involves displacement of large amounts of excess material(mine waste)from coal mining activities. This anthropogenic change in soil structure exerts a profound effect on the original water balance,especially in transition zones between arid and semi-arid regions with fragile environments(Vasssilis and Wyseure, 1998; Wu et al., 2011). Therefore,a series of vegetation restoration projects,including tree planting,agricultural reclamation,botanical garden construction, and other ventures,was conducted in these coal mine refuse dumps(Ezeaku,2012; Li et al., 2013). Restorations have played a major role in controlling soil erosion,l and degradation, and desertification(Radeloff et al., 2000; Wang C et al., 2013; Wei et al., 2013). However,a number of problems,such as the decline of groundwater and the death of revegetated plants in some regions,which directly influences the sustainability of ecological restoration and the s and -binding efficiency of the vegetation,remain in practice(Li et al., 2013). Precipitation is often the sole source of water replenishment in arid and semi-arid areas(Michael and Wei, 2010). Hence,some irrational artificial vegetation configuration modes(such as improper species selection and large community density)lead to various levels of soil water deficit,which occurs when soil water consumption exceeds the natural rainfall compensation(Michael and Wei, 2010). Thus,quantitative studies of the interaction between soil moisture and vegetation under different vegetation configuration modes,as well as investigation of the causes of plant water deficit and degree of compensation,are necessary(Nicolau,2003). These pursuits present important implications for regional vegetation restoration and reconstruction(Li et al., 2013).

Species selection and configuration are considered essential procedures for every rehabilitation process(Brenner,1985). Previous studies have shown that grasses,trees,shrubs, and their combinations are the main plants that revegetate the established refuse dumps of an opencast coal mine(Singh et al., 1996). Li et al.(1997)suggested that artificial grass planting is necessary to protect the coal mine environment. Liu and Li(2011)divided waste l and into four types and provided suggestions on the appropriate species and their configurations in terms of optimal plant allocation for each area; this analysis was based on the number of reclamation years and the growth state of the vegetation in the waste l and of the Haizhou open-pit coal mine. However,in the Pingshuo open-pit coal mine,the favorable pattern for revegetation was shown to include planting trees,shrubs, and grasses(Li et al., 2009). These variations in findings imply that no single type of revegetation is applicable to all vegetative restorations; differences in site conditions,climates, and environments result in a wide range of approaches for vegetation rehabilitation(Bao et al., 2012). However,after establishment of different plants,concerns on whether or not the revegetated ecosystems would succeed and how the revegetated ecosystems would transition to vegetation succession have been raised,there have no unified conclusion with regard to these issues(Li et al., 2013).

The present study reports an investigation of the vegetative restoration of the northern refuse dump in the Heidaigou open-pit coal mine,which was established in 1995. This revegetation involved the planting of communities of trees,shrubs,grasses, and combinations of these plants. After nearly 20 years of vegetation succession,the plant species composition,as well as soil and moisture status in the area has undergone considerable changes. Hence,the Heidaigou open-pit coal mine serves as an ideal platform for studies on quantifying the degree of soil water deficit and determining the spatial distribution of these differential deficits in various vegetation configuration models. This study specifically aims to determine(1)the plant and soil succession features in different vegetation configuration models and (2)plant water deficit degree and the spatiotemporal distribution of the compensation degree to these deficits in different vegetation configurations model. Our goal is to provide a scientific basis for species selection and vegetation reconstruction of the refuse dumps in open-cut coal mines from the perspective of eco-hydrology.

The Heidaigou open-pit coal mine is located in the middle of the Zhungeer coal field in the Inner Mongolia Autonomous Region of China. Considering its reserves,the mine ranks as the third largest coal mine in the country. The altitude of the site is 1,025-1,302 m, and the geographical coordinates are 39°43′N to 39°49′N and 111°13′E to 111°20′E. The Heidaigou coal mine occupies a total area of 5,124 ha, and the waste dumps occupy more than 629 ha of the total area. The site is located in a temperate continental semi-arid climate zone that is cold in winter,dry and windy in spring,hot in summer, and mild and pleasant in autumn. The annual average temperature is 7.2 °C, and the average annual rainfall is 426.3 mm; rain falls predominantly(60%-70%)between June and September. The average annual evaporation is 1,943.6 mm, and the relative humidity is 58%. The wind is mostly calm,flowing in a north-northwest direction at an average speed of 2.2 m/s. The coal mine is situated in a typical steppe ecological region,with Stipa species comprising the main vegetation.

The northern refuse dump was established in 1995, and the total reclamation area measures 186.9 ha. These dumps are located at a site away from the coal-bearing area or situated inside the mines as internal dumps created by in-pit dumping in voids formed from coal extraction(Adibee et al., 2013). The soils of overburdened dumps are physically,nutritionally, and biologically poor. They usually consist of a mixture of fine-grained to coarse-grained particles and rock fragments,which cause geotechnical and environmental problems on disposal. As seen in Figure 1,the topography of the area is undulating. The reclamation and revegetation of surface coal-mine disturbances have established sustainable and healthy arable-l and ecosystems from bare mounds,although the natural succession occurs through a very slow process. The weathered materials were stabilized by vegetation succession and mixed with organic materials,resulting in improved physical properties of the materials and more favorable conditions for plant growth.

Figure 1 View of the refuse dump at the Heidaigou opencast coal mine

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As shown in Table 1,the main plants selected to populate the reclaimed areas include trees(such as Robinia pseudoacacia,Pinus tabulaeformis, and Populus simonii),shrubs(such as Tamarix chinensis,Caragana mirophylla,Hippophae rhamnoides,Artemisia gmelinii,Armeniaca sibirica, and Artemisia giraldii), and grasses(such as Stipa bungeana,Bothriochloa ischaemum,Pennisetum centrasiaticum,Lespedeza potaniniiv,Corispermum tylocarpum,Astragalus meliltoides,Thermopsis lanceolata,Leymus secalinus,Medicago sativa,Calamagrostis epigejos, and Cleistogenes quarrosa). The major plantation configurations comprise trees,shrubs,grasses,trees + shrubs,trees + grasses,shrubs + grasses, and trees + shrubs + grasses. In the monoculture plantation configurations,the suitable cultivated distance of the plantlets and rows are 2m×3m and 1m×1m for trees and shrubs,respectively. The grasses were planted together, and the densities of planting spacing for the trees + shrubs,trees + grasses, and shrubs + grasses configurations were 1m×2m,3m×3m, and 2m×2m,respectively. In the trees + shrubs + grasses configurations,the grasses were interplanted about 1 m away from the shrubs and trees at densities of 1m×2m and 1m×3m,respectively. Each of the configurations was planted in separate plots.

Table 1 Description lf seven vegetation configurations with differert revegetated species and a natural community located in refuse dumps on Heidaigou open-pit col mine

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Three quadrats were established for each of the seven plantation configurations found in the northern refuse dumps. A reference site consisting of native vegetation with no previous damage by coal mining was also chosen. Overall,24 quadrats were used in the study. The survey area of the shrubs measured 10m×10m,whereas that of the herbs was 1m×1m. The species richness(number of species per quadrat),shrub cover,herbaceous cover, and other parameters of the artificial vegetation communities were measured monthly in 2013. The coverage of the biological soil crusts(BSCs)was measured using a point sampling frame(2.5cm×2.5cm grid; 169 points per 30cm×30cm quadrat). Before sampling,the soil surface was sprayed with deionized water to render BSC components readily visible. At each quadrat,the total coverage was estimated as the proportion of the 169 points occupied by the visible components of the crusts(Li et al., 2010). Precipitation was recorded every 30 min using tipping bucket-type rain gauges(Casella)in Campbell CR30X data-loggers. Soil moisture in the different vegetation configurations was determined from samples collected monthly in 2013 using a soil auger through the oven-drying method(0-200 cm). The soil sampling sites were the same as the plant observation plots, and the soil samples were obtained from the sites of different ages at 0-50 cm depth in triplicate during the 2013 growing season. Air-dried soil samples were sieved through a 2 mm screen and used for further analysis. Soil bulk density was determined by inserting a metallic core(0.05 m in depth and diameter)into the soil. The soil organic matter(SOM)was measured using the K₂Cr₂O₇ method(Nelson and Sommers, 1975). The total N was measured using the Kjeltec system with a 1,026 distilling unit(Tecator AB,Höganäs,Sweden). Phosphorus and potassium were measured using st and ard methods for observation and analysis developed by the Chinese Ecosystem Research Network(CERN)(Liu,1996).

Soil water storage was measured by the drying method. Soil water storage was calculated as follows(Jiao et al., 2013): soil water storage(mm)= [(mass of damp soil − mass of dried soil)/mass of dried soil × 100] × soil thickness(mm)× volume weight per layer. The most suitable moisture content for plant growth is 60% of the field capacity; moisture lower than this threshold will result in plant growth stress and ,consequently,plant water deficit(Hu,1992). We used the degree of soil water deficit and the extent of compensation to this storage deficit to determine the actual water requirement of plants. The formula for plant water deficit degree is as follows: DPW(%)= D_a/F_c × 100%,D_a = 0.6F_c − W_c,where D_a is the amount of plant water deficit(mm),F_c is the soil field capacity(mm), and W_c is the actual soil water storage(mm). The formula for the degree of compensation of plant water storage deficit is as follows: CPW(%)= ΔW/D_ac × 100%,where ΔW = W_cm − W_cc and D_ac = 0.6F_c − W_cc. ΔW refers to the increment of soil water storage at the end of the rainy season(mm),W_cc is the actual soil water storage at the beginning of the rainy season(mm),W_cm is the actual soil water storage at the end of the rainy season(mm), and D_acis the soil water storage at the beginning of the rainy season(mm).

Descriptive statistics was employed to calculate the means and st and ard errors from each set of duplicates. ANOVA and the least significant difference(LSD)test were used to determine the significance of the differences in contrasting treatments. These analyses were conducted using the SPSS 13 package(SPSS 13.0 Inc.,Chicago,IL,USA). Graphic plotting was conducted with Origin 7.0 software(OriginLab Corporation,Northampton,MA,USA).

Figure 2a shows that the coverage of herbaceous plants in the tree,shrub, and tree + shrub communities was lower than 5% for each case,whereas that of the grass,tree + grass,shrub + grass, and tree + shrub + grass communities generally exceeded 20%. Similarly,the coverage of shrubs was higher in the tree,shrub,tree + shrub,tree + grass,shrub + grass, and tree + shrub + grass communities. However,shrubs were rarely found in the grass communities; when shrubs were observed in these communities,their coverage was usually less than 1%. When compared with the natural vegetation community,in which the coverage of herbaceous plants and shrubs was 75% and 5%,respectively,the shrub + grass community was more conducive to maintenance. In the monoculture vegetation configuration models,such as those in the tree and shrub communities,the variation of species richness and abundance of plant composition were less than those of the other vegetation configuration models,as seen in Figure 2b. The relatively high species richness and abundance in the grass community was mainly due to changes of the soil structure of dumps that had accumulated rich seed germination in the soil seed bank. In this case,a high coverage was achieved(Figure 2b), and a relative stability in richness was maintained. Some biennial(Echinops gmelinii Turcz. and Scorzonera capito Maxim.) and perennial(Stipa bungenana Trin. ex Bge.)species also appeared in the community. Small annual grasses(Eragrostics cilianensis Link ex Vign. Lut.),Setaria viridis Beauv.,as well as Corispermum patelliforme Iljin,also became the dominant species in the herbaceous layer.

Figure 2 Plant coverage (a), richness and abundance (b), nutrients (c), and biological soil crust coverage (d) in different vegetation configurations. T represents trees, S represents shrubs, G represents grasses, and N represents natural vegetation

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The species richness and abundance of the different vegetation configurations remained lower than those of the natural vegetation community. This finding suggests that the revegetated plants in the refuse dumps still requires a relatively longer time to recover to the status of the natural vegetation community. As seen in Figure 2c,soil SOM,N, and P contents in the different vegetation configurations were lower than those in the natural vegetation communities according to following order: tree + shrub + grass > shrub + grass > grass > tree + shrub > tree + grass > shrub > tree communities. However,SOM and soil nutrients(N and P)concentrations in the monoculture vegetation configuration of trees,shrubs, and grasses significantly differed from those of the tree + shrub,tree + grass, and shrub + grass communities(P <0.05). By contrast,differences among tree + shrub,tree + grass, and shrub + grass communities were insignificant(P >0.05). With vegetation succession,BSCs gradually formed and developed in the different vegetation configurations(Figure 2d). These BSCs comprise cyanobacteria,green algae,lichens,mosses, and other organisms that are closely integrated with soil surface particles. BSCs are mainly distributed in shrub-based communities,such as in the tree and shrub communities,in which BSC coverage could reach up to 60%. However,in herb-based communities,such as in the grass,tree + grass,shrub + grass, and tree + shrub + grass communities,the BSC coverage was relatively low(30% or less). In the natural vegetation community,BSC coverage was generally maintained at about 25%,which indicates its relationship with shrub and herbaceous coverage.

The rainfall in 2013 and the variations in soil water storage and deficit at 0-200 cm in different vegetation configurations are shown in Figure 3. Rainfall mainly occurred from June to August,accounting for 85% of the total rainfall amount throughout the growing season. The average values for soil water storage throughout the growing season showed the following order: natural vegetation(215.87 mm)> shrubs + grasses(208.69 mm)> grasses(206.55 mm)> trees + shrubs(188.07 mm)> shrubs(185.79 mm)> trees + grasses(179.96 mm)> trees(173.05 mm)> trees + shrubs + grasses(167.77 mm). Pairwise comparison testing revealed no significant differences in the soil water storage values between the shrub and tree + shrub communities,tree and tree + grass communities, and grass and shrub + grass communities(P >0.05). However,when put them together for comparison,differences among each configurations were statistically significant(P <0.05). All of the vegetation configurations,including those with natural vegetation,showed soil moisture deficits. Among the configurations studied,soil moisture deficits in the tree,tree + shrub, and tree + shrub + grass communities were the most serious(120-150 mm). The water deficit in the shrub + grass communities was relatively low(80 mm). Differences in soil moisture deficit between the tree and tree + shrub communities were insignificant(P >0.05),mainly because herbal plants were few in number in the corresponding experimental sites and shallow soil moisture consumption exerted no strong effects. No significant soil moisture deficit occurred after rainfall supplementation. Natural vegetation communities contain loose soil,possess a higher rainfall infiltration capacity, and allow relatively limited evaporation and plant transpiration; thus,soil moisture contents were higher in these cases and nearly no soil water deficit was observed.

Figure 3 Precipitation, soil water storage, and deficits in different vegetation configurations. T represents trees, S represents shrubs, G represents grasses, and N represents natural vegetation

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The seasonal plant water deficit degree at 0-200 cm depth in different vegetation configurations are shown in Table 2. The seasonal plant water deficit degree changed uniformly across the different months,generally showing "V" shaped fluctuations throughout the year. In particular,the plant water deficit degree was the highest at the beginning of April(about 30%),gradually reduced to a minimum in June(about 5%),increased slowly, and then reached maximum values at October. This pattern is consistent with the rainfall distribution in this area; plant water deficit degree was significantly alleviated in the rainy season. However,regardless of season,plant water deficits degree in the tree + shrub + grass(27.67%),tree(25.54%), and tree + grass(26.87%)communities were greater than those in the other vegetation configurations. The shrub(21.75%),grass(20.05%), and shrub + grass(18.44%)vegetation configurations showed the lowest plant water deficit degree,which suggests that they are the optimal vegetation configuration modes for vegetation reconstruction of refuse dumps in open-cut coal mines. Differences in plant water deficit degree of a particular vegetation configuration across different months were significant(P <0.05). In each month,differences in plant water deficit degree among different vegetation configurations were significant(P <0.05)in the rainy season(June to August)but insignificant(P >0.05)in other months. Furthermore,differences in the plant water deficit degree of the mixed vegetation configuration were more apparent than those in the monoculture plantation communities.

Table 2 Temporal change of plant water deficit degree in different vegetation configurations

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As seen from Table 3,the compensation degree of soil water storage in each community was negative,which implies that from April to October,regardless of vegetation configuration models,all supplementary water was consumed by the plants and did not replenish soil moisture. In this case,the soil moisture was not compensated throughout the rainy season. If winter precipitation does not replace the soil moisture to achieve initial levels,plants would inevitably deteriorate. The compensation degree of soil water storage in the grass and shrub + grass communities were greater than those in the tree,shrub,tree + grass, and tree + shrub communities; in particular,the natural vegetation community exhibited the largest degree of compensation. Differences in compensation among the above configurations were significant(P <0.05),which indicates that plant growth and plant drought resistance in the grass and shrub + grass communities are superior to those of the other vegetation configurations.

Spatial changes in the plant water deficit degree among the different vegetation configurations at different soil depths are shown in Table 4. Considerable differences in plant water deficit degree and a large gap of non-uniform vertical distribution were observed. For instance,in the tree communities,the spatial distribution of plant water deficit comprised low levels at the soil surface,increased gradually with the soil depth,reached a maximum value at 120-160 cm soil depth(about 40%), and remained constant thereafter. Plant water deficit declined at 160 cm,which indicates that the degree of plant water deficit increases beyond 100 cm soil depth. This soil depth corresponds to the layer with no compensation from rainfall and lower groundwater; furthermore,tree root distribution begins beyond 100 cm. These data demonstrate that the deep-soil water deficit is much higher than that at the 0-100 cm soil layer. The tree + shrub communities generally exhibited the same tendency as the tree communities,which showed an increasing degree of plant water deficit with increasing soil depth.

Table 4 Spatial change of plant water deficit degree in different vegetation configurations

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The spatial pattern of plant water deficit degree in the shrub community gradually increased with soil depth at the 0-80 cm surface layer and then reached a maximum at 40-80 cm. Despite rainfall supplementation,the plant water deficit degree remained elevated(at around 30%)mainly because of shrub roots distributed in this soil profile. Beyond this level,the degree of plant water deficit began to decline with increasing soil depth and remained stable at the 120 cm soil depth. The plant water deficit degree in the grass,tree + grass,shrub + grass, and tree + shrub + grass communities was high in the surface soil layer,especially for the grass community,which showed 40% plant water deficit,but decreased with increasing soil depth. By contrast,in the tree + grass and shrub + grass vegetation communities,the plant water deficit degree began to rise at the 80 cm soil layer and then remained stable,likely because of the root distribution of trees and shrubs and the lack of rainfall compensation beyond 80 cm,which results in high water deficits at the corresponding depths tested. The plant water deficit degree in the natural vegetation communities,which mainly include grasses,was similar to that in the grass communities,that is,high surface water deficits that decreased with increasing soil depth. Despite this similarity,however,the plant water deficit degree in the natural vegetation communities was lower than that in any other vegetation configuration,which suggests that ecological recovery is a slow process in an extremely arid desert environment. In this case,conservation of soil moisture is a crucial issue for l and managers. Among the different vegetation configuration models,the degree of plant water deficit at the 0-80 cm soil layer changed more violently when compared with that of below the 80 cm soil layer,especially for monoculture plantation communities. Furthermore,differences in the degree of plant water deficit among various vegetation configurations in the same soil layer were significant(P <0.05).

The degree of plant water compensation reflects the cumulative effect of rainfall and soil moisture deficit. As displayed in Table 5,plant water compensation degree among the different vegetation configurations generally changed via a uniform pattern,that is,the degree of plant water compensation was the lowest(−72.1%)at the surface and increased with increasing soil depth. Plant water compensation degree levels stabilized at 80 cm or deeper(12.0%-19.6%). Because of surface soil evaporation and plant transpiration in the tree,shrub,tree + grass, and tree + shrub vegetation communities,plant water compensation degree was the lowest(negative values)in these configurations,which indicates that water compensation is less than water consumption in the surface soil layers of these communities. Plant water compensation degree was relatively extensive in the 20-40 cm soil layer because of the interplay between rainfall and soil evaporation combined with the influence of root concentration. Thus,the degree of compensation of water was also extensive, and the difference was significant(P <0.05)across different vegetation configuration models. Beyond the 40 cm soil layer,the soil moisture content was lost due to plant transpiration, and the effect of rainfall compensation was weak. The degree of plant water compensation decreased slowly until water compensation remained stable. However,the plant water compensation degree between the different soil layers was not obvious,especially in the monoculture plantation communities. Among these monoculture communities,the natural vegetation communities,shrub + grass, and grass communities showed around 10% change in water compensation,whereas the other vegetation configurations changed between 20% and 40%.

Table 5 Spatial changes in the degree of plant water compensation among different vegetation configurations

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In arid and semi-arid areas,rainfall is the sole source of water replacement. Water balance and plant transpiration are the most important factors in plant export; soil water deficit is a major factor limiting vegetation restoration and reconstruction(Schwinning and Ehleringer, 2001; Li et al., 2004; Huang et al., 2013). Many vegetation reconstruction models have been established in ecological engineering projects(Hu et al., 2012). The first step in restoration is the selection of plant species. Trees,shrubs, and grasses are usually chosen. A wide choice of species may be available for planting in different vegetation zones,but the overall principle is to select the native species(Li et al., 2013). In present study,P. simonii trees were selected for revegetation. P. simonii is generally known to exhibit high water consumption and hence is unsuitable for the revegetation of arid zones(Li et al., 2003). However,during early stages of vegetation restoration,P. simonii facilitates l and recovery through its relatively high survival rate and topsoil stabilization(Li et al., 2003). Major shrub plants in restoration include the seabuckthorn,which is an ideal reclamation plant in opencast coal mine refuse dumps. Seabuckthorn can form a canopy of artificial shrubs in the short term(three to five years) and its soil fertility and soil conservation effect are significant(Yang et al., 2014). The main grasses selected included the purple alfalfa,Panicum maximum Jacq., and Melilotus suaveolens. These grasses are common and widely spread species in arid areas(Li et al., 1997). After plant species selection,the next stage involves configuring vegetation,including adoption of various combinations of the selected species. In present study,various combinations of trees,shrubs, and grasses were considered. During this process,we found that,with respect to natural vegetation,single-type configurations of trees or shrubs are not the best option,as the selected plants in this case consume a large amount of water and the plant richness and abundance in these communities are low. However,the BSCs coverage in single-vegetation configurations if fairly well-developed,which significantly affects rainfall interception and infiltration(Li et al., 2013).

The variations in soil water storage among different vegetation configurations were consistent with the rainfall distribution. The soil water storage dynamics changed across different months during the rainy season,which reveals the differential effects of rainfall on soil water compensation in various vegetation configurations. The disparities observed were attributed to the soil textures and presence of different vegetation types(Wang Y et al., 2013). Compared with the natural vegetation communities,each artificial vegetation displayed a certain degree of soil moisture deficit. Tree,tree + shrub, and tree + shrub + grass communities exhibited the most serious deficits,whereas the shrub + grass community showed relatively small deficits. This observation can be mainly attributed to the high water consumption in the tree communities and unreasonable vegetation configurations(Kyushik et al., 2005). The plant water deficit degree in various vegetation communities also differed; the grass community exhibited the lowest plant water deficit degree when compared with the other vegetation configurations,most of which showed deficits of 25% or less. The plant water deficit degrees in the tree and shrub communities were generally the same. Thus,to prevent further soil moisture loss,water complements,such as irrigation,are necessary; otherwise,the revegetated plant density should be limited within a reasonable range(Braud et al., 2001; Yu et al., 2006; Zhou et al., 2006). Soil water storage in each of the different vegetation configurations was in the deficit state prior to the rainy season and did not change thereafter despite some rainfall compensation. As rising temperatures cause high soil evaporation and water consumption by vegetation transpiration during the growing season(Huang et al., 2010),soil water storage deficit is not effectively alleviated. Hence,we conclude that,under the existing vegetation configurations,if winter precipitation cannot replenish soil moisture to achieve initial normal levels,deterioration of vegetation will be inevitable(Xia and Shao, 2008).

Plant water compensation degree comprises the interaction between rainfall infiltration recharge and the water consumption of the plant-soil ecosystem. Therefore,underst and ing the degree of plant water compensation and taking certain measurements in different vegetation configurations could promote the recovery of soil water deficit(Hsiao,1973). The spatial variation of plant water deficit degree changes coincides with plant root distribution(Rodrigues et al., 1995; Benjamin and Nielsen, 2006). Higher plant water deficit degree result in a greater degree of plant water compensation. The plant water compensation degree in the tree and shrub communities is equal and consistent with the vertical distribution of plant roots. As trees such as P. simonii and the Chinese pine are deep-rooted plants,rainfall infiltration will not meet their growth dem and s in semi-arid regions, and their roots would consume stored deep-soil water. Thus,soil moisture deficit is serious and difficult to recover at certain depths. The plant water compensation degree was lowest at the ground surface,increased sharply with increasing soil depth until 80 cm, and then became relatively constant at 160 cm or deeper. The rainfall infiltration depth was shallower in this area and the maximum rainfall infiltration depth was only 60 cm; beyond this depth,the soil moisture deficit was difficult to recover and became stable for the long term(Duan et al., 2006; Lei et al., 2009). The soil water content of the surface layer of the grass and shrub + grass communities was lower than that of the deep soil layers. This finding was primarily attributed to the shallow-rooted plants in these configurations,which mainly consume shallow soil moisture, and the extremely arid regional climate coupled with a low-vegetation cover and high shallow-soil evaporation. Thus,the moisture deficit was considerable at the 0-100 cm soil layer but low beyond 100 cm. As the root system distribution characteristics of grass and shrub + grass communities enabled efficient rainfall absorption and utilization,these vegetation configuration models should be considered as optimal plant restoration models for arid and semi-arid regions. However,the plant densities in these models must be strictly controlled to avoid excessive soil moisture consumption.

The sustainability of ecosystem restoration of refuse dumps at open-pit coal mines depends on plant species selection,their configuration, and the optimal use of water resources. In this study,the succession of the revegetated plants and soil water storage and deficit of different vegetation configurations(trees,shrubs,grasses,trees + shrubs,trees + grasses,shrubs + grasses, and trees + shrubs + grasses)were investigated and compared with those of natural vegetation communities in the northern refuse dumps of the Heidaigou open-pit coal mine. Plant water deficit degree and its spatiotemporal distribution among the different configurations were also studied. Results showed that different vegetation configurations exert important effects on the vegetation cover(shrubs and herbaceous cover),richness,abundance,soil nutrients(SOM,N and P), and BSCs coverage of the soil surface. Plant water deficit degree in the grass and shrub + grass communities varied by 20%; this variation was the lowest observed among the different vegetation configurations. The degrees of plant water compensation in the grass and shrub + grass communities were greater than those in the tree,shrub,tree + grass, and tree + shrub communities; in particular,natural vegetation communities showed the largest degree of plant water compensation. In terms of vertical distribution,the degree of plant water compensation in the surface layer was minimal,increased rapidly with increasing depth, and then remained stable in deeper soil layers. In the tree communities,plant water compensation degree were low in the soil surface and reached maximum values at the 120-160 cm soil depth(about 40%). Where plant water compensation degree of the shrub communities gradually increased with increasing depth at the 0-80 cm layer and reached maximum values at the 40-80 cm soil layer. By contrast,in the grass,tree + grass,shrub + grass, and tree + shrub + grass communities,the degree of plant water deficit was highest in the surface soil layer,especially for the grass communities(40% deficit), and decreased with increasing soil depth. For the tree + grass and shrub + grass communities,plant water deficit degree began to rise at the 80 cm soil layer and then remained constant. The lowest plant water compensation degree was noted on the surface,increased with increasing soil depth, and then stabilized at 80 cm or deeper. The compensation degree in the natural vegetation communities,shrub + grass, and grass communities changed by about 10%,while that in the other vegetation communities changed between 20% and 40%. Overall,we conclude that the shrub + grass and grass configuration modes are the optimal vegetation restoration models in terms of ecohydrology for future ecological engineering projects.