Spatial and Temporal Variations of Aeolian Sediment Input to The

Aeolian Research 30 (2018) 1–10

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Aeolian Research

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Spatial and temporal variations of aeolian sediment input to the tributaries MARK (the Ten Kongduis) of the upper Yellow River ⁎ Hui Yanga,b, Changxing Shia, a Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China b Hebei University of Water Resources and Electric Engineering, Hebei, China

ARTICLE INFO ABSTRACT

Keywords: The Ten Kongduis of the upper Yellow River, located in Inner Mongolia, northern China, is an area with active Ten Kongduis wind-water coupled erosion and hence one of the main sediment sources of the Yellow River. In this study, we Aeolian sand analyzed the characteristics of spatial and temporal variations of aeolian sediment input to the river channel. For Terrestrial laser scanning this purpose, three segments of sand dune-covered banks of the Maobula and the Xiliugou kongduis were in- Remote sensing images vestigated three times from November 2014 to November 2015 using a 3-D laser scanner, and the displacement Aeolian-ﬂuvial interaction of banks of desert reaches of three kongduis was derived from interpreting remote sensing images taking in the years from 2005 to 2015. The data of the surveyed sand dunes reveal that the middle kongduis were fed by aeolian sand through the sand dunes moving towards the river channels. The amount of aeolian sediment input was estimated to be about 14.94 × 104 t/yr in the Maobula Kongdui and about 5.76 × 104 t/yr in the Xiliugou Kongdui during the period from November 2014 to November 2015. According to the interpretation results of remote sensing images, the amount of aeolian sediment input to the Maobula Kongdui was about 15.74 × 104 t in 2011 and 18.2 × 104 t in 2012. In the Xiliugou Kongdui, it was in the range of 9.52 × 104 − 9.99 × 104 tin 2012 and in the springs of 2013 and 2015. In the Hantaichuan Kongdui, it was 7.04 × 104 t in 2012, 7.53 × 104 t in the spring of 2013, and 8.52 × 104 t in the spring of 2015. Owing to the changes in wind and rainfall, both interseasonal and interannual sediment storage and release mechanisms exist in the processes of aeolian sand being delivered into the kongduis. However, all of the aeolian sediment input to the Ten Kongduis should be delivered downstream by the river ﬂows during a long term.

1. Introduction In general, the aeolian sand input to the river channel includes the sediment blown into the river channel by winds directly, and the col- In arid and semi-arid zones, wind erosion is an important environ- lapse of sand dunes on the banks due to river lateral erosion (Yang mental issue that affects 28% of the global land area experiencing the et al., 1988). The factors influencing the amount of aeolian sand input land degradation (Buschiazzo and Zobeck, 2008; Webb et al., 2006). and its contribution to the sediment yield of a basin are diverse, in- Aeolian-fluvial interactions mainly control the extent, shape and cluding topography, wind, water and the angle of the river with the boundaries of an individual dunefield (Bullard and McTainsh, 2003). In wind directions and so on. The complicated factors make it difficult to aeolian and fluvial coupled system, rivers usually act as the boundaries calculate the amount of aeolian sand input accurately with the tradi- of aeolian transport, and aeolian sand is a main source of sediment tional research methods and measurements (Bullard and Livingstone, (Bullard and Livingstone, 2002). Effects of aeolian activity on fluvial 2002). Recently, the development of remote sensing technology pro- systems include diversion and damming of rivers (Mason et al., 1997), vides many new methods for monitoring surface morphology (Tarolli narrowing or constriction of valleys (Marker, 1977), channel avulsion et al., 2009), in which the terrestrial laser scanning (TLS) technology (McIntosh, 1983; Jacobberger, 1988; Jones and Blakey, 1997; Bourke and the remote sensing images have been widely used in the study of and Pickup, 1999) and bifurcation (Tooth, 1999) and waterhole de- surface process by lots of scholars (Werner and Andreas, 2005; Milan velopment (Knighton and Nanson, 1994). Ephemeral rivers can be et al., 2007; Williams et al., 2014; Yao et al., 2011; Ta et al., 2013; Liu blocked or diverted by sand dunes (Teller and Lancaster, 1986; Jia and and Coulthard, 2015). Wang, 2014). The Kubuqi Desert is located in the northern part of the Ordos

⁎ Corresponding author. E-mail address: [email protected] (C. Shi). http://dx.doi.org/10.1016/j.aeolia.2017.10.002 Received 8 April 2017; Received in revised form 24 October 2017; Accepted 24 October 2017 1875-9637/ © 2017 Elsevier B.V. All rights reserved. H. Yang, C. Shi Aeolian Research 30 (2018) 1–10

Fig. 1. Locations of the Ten Kongduis and the plots surveyed.

Plateau in Inner Mongolia, China. It is bordered by the Yellow River to 2. Materials and methodology the west, north and east, and its terrain slopes gently from south to north (Du et al., 2014). The eastern part of the Kubuqi Desert crosses 2.1. Study area the middle reaches of ten tributaries of the Yellow River and these tributaries are called the Ten Kongduis (kongdui is the transliteration of This study was conducted in the Ten Kongduis tributaries of the ephemeral flood gullies in Mongolian). Given the special location of the upper Yellow River (Fig. 1). These tributaries are nearly parallel to each Kubuqi Desert, the wind and water erosion are strongly coupled in the other, and flow from south to north and drain into the Yellow River. Ten Kongduis basins. Aeolian sediments could be deposited and stored The Ten Kongduis have a temperate continental monsoon climate in the channels of the Ten Kongduis during the windy seasons, and they and belong to the eastern Ordos Plateau desert region in the physical might be washed away by floods during the following wet seasons. regionalization of China (YRIHR, 2009). The average annual tempera- According to the previous studies on the sediment yield and sediment ture ranges from 6.1 °C to 6.6 °C in the northern Kubuqi Desert and the delivery of the Ten Kongduis, the aeolian sand in the middle reaches is annual evaporation is 2200 mm. The average annual precipitation one of the main sediment sources and highly promotes the sediment ranges from only 200 mm to 400 mm, decreasing gradually from the content of floods from the upper reaches (Xu, 2014). The sediment- east to the west and it is the least in the Kubuqi Desert. The rainfall in laden floods have frequently destroyed railways, highways, and fac- the Ten Kongduis appears mainly in the form of rainstorms and con- tories located in the lower regions of the Ten Kongduis and the sedi- centrates in the months from July to September, accounting for 71.2% ment yielded from the kongduis has caused serious silting in the Yellow of the annual precipitation. These rainstorms usually generate short- River. lived but high hyperconcentrated flows. Strong winds (> 17.2 m/s) and The research about the amount of aeolian sediment input to the sandstorms often happen in winter and spring with an annual average kongduis so far is still few. Through simulating the daily saltation frequency of 24 days and the average wind speed is 2.7 m/s (Liu, 2013). emission in the Kubuqi Desert by a saltation submodel of the Integrated At Dalateqi weather station in the study area, the annual average fre- Wind-Erosion Modeling System, Du et al. (2014) estimated that the quency of the strong winds and sandstorms are 25.2 and 19.7 days, annual quantity of aeolian saltation sand that was deposited in the Ten respectively. At Dongsheng weather station, they are 34.5 and Kongduis ranged from 0.0204 × 108 t to 0.139 × 108 t during the 19.2 days, and at Baotou weather station, they are 46.8 and 21.6 days, period from 2001 to 2010. However, this simulated result has not been respectively (YRIHR, 2009). Under the special physical conditions, the validated via field observation and measurement. The process of fluvial- study area is a typical water-wind coupled erosion zone. aeolian interaction was investigated by Ma et al. (2013) in a tributary of According to the extracted watersheds and drainage networks from the Dinghonggou Kongdui and by Wang and Ta (2016) in a tributary of the GDEM (http://www.gscloud.cn/) of the study area, the drainage the Maobula Kongdui. Ma et al. (2013) find the ratio of wind erosion area of each of the Ten Kongduis changes from 213 to 1301 km2 with a and water erosion to be 1.8:1 for the year 2010. Wang and Ta (2016) total of 8269 km2 and the stream length ranges from 37.1 to 114.7 km. provide a ratio of 1:1 for the year 2012. The two studies just chose a The channel slope ranges from 3.59‰ to 8.09‰. In the middle reaches typical study area in the Ten Kongduis and didn't study the temporal of the kongduis, the Kubuqi Desert is covered mainly by drifting sand change of wind erosion as well. dunes to the west and by semi-fixed or fixed sand dunes to the east of The objectives of this paper are to reveal the interseasonal and in- the mainstream of the Hantaichuan Kongdui. The stream lengths of terannual changes and spatial variations in the amount of aeolian se- desert reaches in the Maobula, Xiliugou and Hantaichuan Kongdui are diment input to the Ten Kongduis and to figure out the mechanism of 31.8 km, 22.4 km and 16.6 km, respectively (Yang and Shi, 2017). sediment erosion in the desert reaches of the kongduis through an empirical investigation. This research can provide some references for 2.2. TLS technology the sand-fixation projects built by the local governments and for re- searchers interested in aeolian erosion in the rivers across the deserts. Three segments of river-facing slopes of sand dunes beside the mainstreams of two kongduis have been monitored three times during

2 H. Yang, C. Shi Aeolian Research 30 (2018) 1–10

Table 1 2.4. Error propagation Details of scanning plots. We used the standard deviation of the error as a measure of the Surveyed Surveying Number Registration Data Points Average ﬀ area dates of errors (m) point error in assessing the di erence between two DEMs. The propagated stations spacing error from two surfaces can be derived as follows (Brasington et al., (m) 2000, 2003; Lane et al., 2003).

MBLSQ 2014.11 10 0.0077 45678 0.01 Utσσ=+()2 ()2 dune* 2015.06 8 0.0058 46622 0.01 crit 1 2 (1) 2015.11 8 0.0067 213245 0.005 where Ucrit is the critical threshold error, σ1 and σ2 are the standard UXLGSQ 2014.11 4 0.0023 520318 0.002 * deviation of error in each surface respectively (assuming a Gaussian dune 2015.06 4 0.0042 724988 0.002 fi 2015.11 4 0.0045 1844861 0.001 distribution of errors) and t is the critical value at the chosen con dence level. This procedure may be used to derive a level of significant change VXLGSQ 2014.11 5 0.0049 704030 0.004 ff dune* 2015.06 5 0.0021 2176968 0.003 detection, which can be applied to the DEM of di erence and calcula- 2015.11 5 0.0056 2670548 0.002 tion of volumetric changes. The t value may be set at t >1(1σ), in which case the confidence limit for the detection of change is 68 per- * MBLSQ is the dune in the Maobula Kongdui, UXLGSQ and VXLGSQ is the un- cent (Lane et al., 2003), or at t > 1·96 (2σ), in which case the con- vegetated and vegetated dunes in the Xiliugou Kongdui, respectively. fidence limit is equal to 95 percent (Brasington et al., 2000, 2003). We use the 95 percent confidence limit in this study. 2014 to 2015, i.e., November 2014 which was before the windy season, June 2015 which was between the windy season and the rainy season, 2.5. Meteorologic data and sand drift potential and November 2015 which was after the rainy season. One of the monitored segments is in the Maobula Kongdui and the other two The data of seven weather stations surrounding the Kubuqi Desert segments that are about 200 m apart are in the Xiliugou Kongdui. All are available (Fig. 1). According to the division of the controlling re- the surveyed dunes are active and located on the west banks of main- gions of these weather stations by Du et al. (2014) using the Thiessen streams. Their locations are shown in Fig. 1. polygon, the region containing the upstream and middle reaches of the The TLS instrument-FARO Laser Scanner Focus3D was used to collect Ten Kongduis belongs to the Dongsheng station, so only the records at a series of independent datasets recording range distance, relative this station are used here for analyzing the characteristics of rainfall height, surface color and reflectivity. The instrument covers a and wind in the Ten Kongduis. The data were downloaded from the 360 × 300 degree vision and has a manufacturer specified point pre- website http://data.cma.cn/. Wind data were measured at 10 m above cision of 2 mm at a range of 50 m for 90% albedo. Each of the plots was the ground. measured from many stations (Table 1). Scans were generally restricted Drift potential is used for describing the potential maximum amount to the range of 10 m in the front of the scanner for ensuring high quality of sand transport by winds with a velocity above the threshold of point resolution across the surface. A relative coordinate system was (Fryberger and Dean, 1979). It is calculated as follows: chosen through fixing several pins at each plot before the first mea- 2 surement as the reference and some spheres were set in every station, DP=− V() V Vt t (2) which makes the merging process less cumbersome and more accurate. Co-registering and georeferencing the scan data was done using where DP is the drift potential, in VU (vector units); V is the measured FARO’s scene software, and the noises caused by vegetation were re- 10-min wind velocity, in m/s; Vt is the threshold wind velocity for moved with manual operation and merged scans were clipped in the winds to entrain sediment, in m/s; and t is the proportion of time during Geomagic Studio software. With the 3D Analyst tool of ESRI’s ArcGIS, which wind velocity is greater than Vt. The threshold wind velocity Vt the triangular irregular network (TIN) of the plots was created, pro- was estimated to be 6 m/s for the mean particle sizes of 0.25 mm in the jected in Gauss Kruger coordinate system. In order to circle out the study area under dry conditions (Fryberger and Dean, 1979). common zone of each dune surveyed at all the three times, DEMs were Resultant drift potential (RDP) represents the net DP or the vectorial constructed in ArcGIS with the TIN data and were linearly resampled to sum of the DP values in each compass direction. It is calculated as a grid with a resolution of 0.1 m, which was deemed to be an appro- follows (Al-Awadhi et al., 2005): priate compromise between computational efficiency, information loss, 220.5 and sufficient resolution to resolve grid-scale morphology. The scanned RDP=+() C D (3) surfaces of each plot consist of 0.46–26.7 million points, with an – average point spacing of 0.001 0.01 m and a point density of CVUθ= ∑ ()sin() (4) 19106–404235 points/m2. The details of scanning data, including the number of stations, registration errors and average point spacing are DVUθ= ()cos() shown in Table 1. ∑ (5)

where VU represents the DP in each wind direction (in this paper, we grouped winds into 16 directions), in VU, and θ is the midpoint of each 2.3. Remote sensing data wind orientation class measured clockwise from north (Zhang et al., 2015). The remote sensing data used in this study are the satellite images of The resultant drift direction (RDD) represents the direction of net the Google earth. The satellite images available and suitable for this trend of sand drift. It is calculated as follows (Al-Awadhi et al., 2005): study were taken at some times in the years from 2005 to 2015. We ﬁ depicted the banks of each kongdui visually identi ed within Google RDD= arctan( C / D ) (6) earth and created polygons in ArcGIS to calculate the areas of erosion and accretion, respectively. Then multiplying the areas of erosion by Directional variability (RDP/DP) is the ratio of the resultant drift the average height of the dunes along the rivers, we can estimate the potential (RDP) to the drift potential (DP). A RDP/DP ratio of close to1 volume of aeolian sediment input during a period. indicates a more unidirectional wind regime (Al-Awadhi et al., 2005; Zhang et al., 2015).

3 H. Yang, C. Shi Aeolian Research 30 (2018) 1–10

Fig. 2. Rose maps of the wind direction and wind speed at Dongsheng station in 2006–2015.

4 H. Yang, C. Shi Aeolian Research 30 (2018) 1–10

35 35 200 200 Fig. 3. Distribution of the wind speed of dominant direction max in 2006-2013 max in 2006-2013 180 180 30 average in 2006-2013 30 average in 2006-2013 (left) and distribution of monthly precipitation (right) at 160 160 min in 2006-2013 min in 2006-2013 Dongsheng station in 2006–2015. 25 25 140 140 2014 2014 120 120 20 2015 20 2015 100 100 15 15 80 80 Precipitation (mm) Precipitation (mm) 10 10 60 60 40 40 Frequency percentage (%) Frequency percentage (%) 5 5 20 20 0 0 0 0 2-3 4-5 6-7 8-9 10-11 12-13 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Speed (m/s) Month

3. Results in Fryberger and Dean (1979). Considering the variations of sand drift potential and rainfall, our surveys should be suitable for estimating the 3.1. Wind and rainfall characteristics annual aeolian sediment input in the ﬁve years before 2015.

The rose diagrams of the wind speed and wind direction at 3.3. Amount of aeolian sediment input derived from field surveys Dongsheng station during the years from 2006 to 2015 showed that the west wind dominated every year (Fig. 2). Also, the wind speed of the Comparing the data derived in November 2014, June 2015 and dominant direction concentrated all in 4–7 m/s during 2006–2015 November 2015, the variations of volumes of the MBLSQ, UXLGSQ and (Fig. 3). The distribution of monthly precipitation (Fig. 3) showed that VXLGSQ dunes were calculated, with the negative values for erosion the annual rainfall concentrated mainly in the months from June to and the positive for deposition (Table 2). The estimation errors were September. Using the SPSS, the significance levels for the difference calculated by Formula (1). As it was found that the middle part of the between the mean monthly rainfall and annual rainfall in 2014 and bottom of the MBLSQ dune had experienced anthropogenic destruction 2015 against other years were found to be more than 0.05 except for in November 2015, the MBLSQ dune was divided into two sections, i.e., those in February and April when, as shown in Fig. 3, the monthly the north one and the south one. precipitation was below 20 mm. So, there was no significant difference According to Table 2, over the periods from November 2014 to both in monthly rainfall and annual rainfall between years from 2006 to November 2015, the total volume of sand accumulation on the MBLSQ 2015. dune was 311.5 m3, and the average sand flux from the dune to the river was 11.5 t/m in the north section and 5.3 t/m in the south section 3.2. Sand drift potential along the channel. As the MBLSQ dune rises from the river bed, the sand flux should be regarded as the amount of aeolian sediment input. The annual DP, RDD, and directional variability (RDP/DP)at Considering the lengths of the north and south sections and using a dry Dongsheng station among the years from 2006 to 2015 are shown in bulk density of 1.52 g/cm3 for the dune sand (Wang, 2015), the mean Fig. 4. It can be seen that the annual DP was less than 50 UV from 2006 flux of aeolian sediment input in the Maobula Kongdui was about 8.4 t/ to 2015 at Dongsheng station (Fig. 4a), so this region had a low energy m from November 2014 to November 2015. wind regime (DP < 200 UV) according to the classification schemes of During the first monitoring period, the deposition volume of the wind environment made by Fryberger and Dean (1979). Also, it is clear unvegetated XLGSQ dune was 11.63 m3 and the vegetation dune was that the annual DP was lower in the years from 2011 to 2015 than in the 6.83 m3. The average sand flux of the unvegetated XLGSQ dune was five years before 2011, and the DP value in 2015 was close to the mean 2.0 t/m and the vegetated XLGSQ dune was 0.41 t/m. During the DP in the five years after 2011. In contrast, RDD was relatively stable second monitoring period, both the vegetated and unvegetated dunes (Fig. 4b), ranging from 336° to 359°. The annual directional variability were eroded with a flux of 4.8 t/m and 3.2 t/m, respectively. No matter (Fig. 4c) was intermediate, with values between 0.5 and 0.8, which was the deposition or the erosion, the sand flux of the unvegetated XLGSQ in the directional category of obtuse or acute bimodal distribution given dune was larger than that of the vegetated XLGSQ dune.

Fig. 4. Wind energy environment in the study area from 50 a 365 45 360 b 2006 to 2015. (a) DP, drift potential; (b) RDD, resultant drift 40 355 direction; (c) RDP/DP, directional variability. 35 350

30 )

° 345 25 340 DP (VU)DP

20 RDD ( 335 15 10 330 5 325 0 320 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Year Year

0.9 0.8 c 0.7 0.6 0.5 0.4 RDP/DP 0.3 0.2 0.1 0 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Year

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Table 2 Volume changes of dunes along the banks of Maobula and Xiliugou kongduis.

Study area Stream length (m) Area of sand dunes scanned (m2) Volume changes (m3) Estimation errors (m3)

2014.11–2015.06 2015.06–2015.11

MBLSQ dune in the north 27 130 131.22 77.28 0.37 MBLSQ dune in the south 30 54 81.08 21.92 UXLGSQ dune 9 211 11.63 -28.17 0.40 VXLGSQ dune 25 1007 6.83 -53.25 0.88

Fig. 5. Dune topography along parts of the channels of the Maobula, Xiliugou and Hantaichuan kongduis.

3.4. Amount of aeolian sediment input derived from satellite images each of the Maobula and the Xiliugou kongduis. In calculating the sand flux to the Xiliugou Kongdui, the data of only the bald dune were used According to the average annual sediment transport rate in the 16 because the length of reaches where the sand dunes were covered by wind directions of the shifting and semi-shifting dunes in the Kubuqi vegetation was negligible according to the images in Google earth. In Desert, the sediment transport rate induced by the wind erosion is large addition, the surveyed sand dunes in the Xiliugou Kongdui were eroded in the direction of W, NW and NNW (Yang et al., 1991). The Ten back in summer, so the sand flux to this kongdui in summer was esti- Kongduis flow from the north to the south, so it is mainly the dune mated using the ratio of sand flux to river from the surveyed dunes in sands on the left banks that are blown to the river channels. The images the Maobula Kongdui in summer to that in winter and spring. Finally, of Google earth and the field survey show that dunes were shifting on the amount of aeolian sediment inputwas estimated to be about the left bank of the desert reaches of the kongduis while dunes on the 14.94 × 104 t/yr in the Maobula Kongdui and about 5.76 × 104 t/yr in right bank were fixed or away from the rivers (Fig. 5). the Xiliugou Kongdui. As erosion/accretion of the right banks scarcely occurred in desert According to the quantities of aeolian sediment input to the three reaches of the three kongduis in the period under discussion, we cal- kongduis during different periods shown in Fig. 7, it was found that at culated the aeolian sand accumulated on the left banks as the amount of the same time scale, the average annual amount of aeolian sediment aeolian sediment input in the kongduis. The changes of parts of left input was similar in a watershed. For instance, in the Hantaichuan banks along the desert reaches of the Maobula, Xiliugou and Kongdui, the amount of aeolian sediment input was about 4 × 104 t/yr Hantaichuan kongduis during different periods are shown in Fig. 6. in about two years, such as 4.47 × 104 t/yr during November 2005 to Using the GDEM, the average relative heights of dunes along the May 2008, 4.19 × 104 t/yr during April 2013 to February 2015, and so banks depicted from the remoting images were obtained to be 1 m, on. Moreover, the average annual amount of aeolian sediment input in 0.55 m and 0.5 m in the Maobula, the Xiliugou and the Hantaichuan a relative long period is less than that in a short period. For instance, kongduis, respectively. The estimation errors of the average heights are the average annual amount of aeolian sediment input was about in the range of 0.94–2.77 m. Then, we calculated the accumulated vo- 9.5 × 104 t/yr and 7.5 × 104 t/yr in the Xiliugou and the Hantaichuan lumes of aeolian sand during different periods (Fig. 7). kongduis, respectively in the three periods from January 2012 to April 2013 (one year), from February to August 2015 (half a year) and from 4. Discussion April to July 2013 (three months). In contrast, it was about 4.7 × 104 t/ yr and 4.1 × 104 t/yr in the Xiliugou and the Hantaichuan kongduis, 4.1. Amount of aeolian sediment input respectively in the two periods from April 2013 to February 2015 and from July 2013 to August 2015 (both about two years). In a short The annual amount of aeolian sediment input from the Kubuqi period, like the periods from April to July 2013 and from February to Desert was counted by the surveyed sand flux to the river in the unit August 2015, the kongduis were in the windy season. According to the length along the main channel of each of the Maobula and the Xiliugou meteorological data of Dongsheng station, the frequency of rainstorms kongduis and the total length of each kongdui across the Kubuqi Desert, (the daily rainfall is above 50 mm) during the two periods was only which was also derived from the satellite images. The surveyed sand 8.7% and 2.2%, which means a low intensity of water erosion. There- flux was revised in light of the angle between the trend of the measured fore, we can infer that the estimated amount of aeolian sand is the segments and that of the main channel crossing the Kubuqi Desert for results of pure wind erosion and the amount of aeolian sediment input

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Fig. 6. Location changes of parts of left banks along the desert reaches of the Maobula, the Xiliugou and the Hantaichuan kongduis during diﬀerent periods.

in the windy season is nearly equal to the annual total. Relatively, the 4.2. Comparison of the quantities of aeolian sediment input to the Kongduis average annual amount of aeolian sediment input calculated with the satellite images spanning a period of years should have subtracted the As mentioned above, some scholars have already estimated the amount of aeolian sand eroded by the water erosion. quantities of aeolian sediment input to the Ten Kongduis. Du et al.

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20 18 MBL 16 XLG 14

t) HTC 4 12 10

10 8

Sediment 6 4 2 0

Period

Fig. 7. Quantities of aeolian sediment input to the Maobula, the Xiliugou and the Hantaichuan kongduis during diﬀerent periods (month/year-month/year).

(2014) used the integrated wind-erosion modeling system (IWEMS) kongduis is wide in the west and narrow in the east, with a width from proposed by Shao (2001) to simulate daily saltation emission in the 28 to 8 km. The area of the desert in the Ten Kongduis is 2762 km2.To Kubuqi Desert. They found that the annual quantity of aeolian sediment the west of the Hantaichuan Kongdui are mainly shifting dunes, with an blown into the Ten Kongduis was 2.04–14 × 106 t/yr, with an average area of 1963 km2, which accounts for 71.1% of the desert area; to the annual quantity of 7.33 × 106 t/yr. Through the data of field observa- east of the Hantaichuan Kongdui are mainly semi-shifting dunes, with tion, Wang and Ta (2016) calculated that the 8-km-long Sudalaer gully an area of only 799 km2 (YRIHR, 2009). Namely, the stream lengths of in the Maobula Kongdui was filled with aeolian sand of 8.34 × 104 t/yr desert reaches become shorter from the west to the east. In other words, in 2011, 8.66 × 104 t/yr in 2012 and 6.83 × 104 t/yr in 2013. The the amount of aeolian sediment input to the kongduis located in the mean annual flux of aeolian sediment input to the Sudalaer gully was west of the Hantaichuan Kongdui is larger than that in the east of the estimated to be about 10.43 t/m, 10.83 t/m and 8.54 t/m in 2011, 2012 Hantaichuan Kongdui. Therefore, the amount of aeolian sediment input and 2013, respectively. to the Maobula Kongdui should be larger than the average value In order to compare the results calculated by different scholars with (73.28 × 104 t/yr) in 2011 that was already more than 3 times of the this study, we estimated the average annual amount of aeolian sedi- results calculated by the other two methods. It may be the result of ment input to each kongdui with the results of Du et al. (2014), and variant dominant wind direction and wind speed in some segments of took it as that in the Maobula Kongdui in 2011. With the average an- the stream during different years. Moreover, Du et al. (2014) obtained nual flux given in Wang and Ta (2016) of aeolian sediment input to the the annual amount of aeolian sand that was deposited in the desert Sudalaer gully and the angle between the surveyed Sudalaer gully and reach of the Ten Kongduis (806.8 km) by accumulating the daily the desert reach of the Maobula Kongdui, we obtained the average amount of saltation sand in different periods. The saltation sediment is annual amount of aeolian sediment input to the Maobula Kongdui from not only the sands coming from the dunes but also other surface ma- 2011 to 2013 (Fig. 8). terials eroded by the wind. This should be one of the reasons why their As shown in Fig. 8, the results of this paper are closer to the results estimate is larger than those derived by the other two methods. of Wang and Ta (2016). We think the results estimated from Du et al. Meanwhile, in our opinion, the aeolian sediment input should be the (2014) may have large errors. This is because the Kubuqi Desert in the sediments that are deposited in the channel. The saltation sediment

80 Du et al. (2014) 70 Wang and Ta (2016) 60 This paper ) 4 50

30 Sediment (10

0 2011 2012 2013 2015 Year

Fig. 8. Quantities of aeolian sediment input to the Maobula Kongdui during 2011 to 2015 estimated from results of three studies.

8 H. Yang, C. Shi Aeolian Research 30 (2018) 1–10 proposed by Du et al. (2014) may include some sediments that are MBLSQ dune was silted up in both the dry and wet seasons from deposited in other areas. Ma et al. (2013) studied a tributary of the November 2014 to November 2015, indicating that the sediment blown Dinghonggou Kongdui called the Baerdonggou gully through field in- by the wind into the river in a year might not be carried downstream vestigation, meteorological observation, runoff plot experiment, topo- completely in the same year. The sediment storage and release is graphic survey and “3S” technology. They found that not all of the completely determined by the meteorological and hydrological condi- aeolian sand blown in the windy season was deposited in the main- tions. In the windy and dry years, the dunes on the river banks may stream. Some of the aeolian sand from the sand dunes on the west bank move towards to and thus narrow the channels continuously, and the (left bank) was deposited in the rill on the east bank (right bank) after storage of aeolian sand increases year by year. In the rainy years with crossing the mainstream, which was the amount of aeolian sediment less wind, the dunes on the river banks may be eroded by flows con- input to the gully, but some of the aeolian sand was carried further tinuously and move backward, so the river channels are widened and eastward by the wind and deposited in the zones beyond the main- the storage of aeolian sand decreases year by year. It has a low possi- stream of the gully. It can be concluded that the aeolian sand discharge bility that sandstorms in spring and heavy rainstorms in summer occur is larger than the amount of aeolian sediment input. According to the in the same year in the Ten Kongduis. For instance, Xu (2013) found results of the Baerdonggou gully calculated by Ma et al. (2013),we that the frequency of annual sandstorms was not correlated with the estimated that the aeolian sand discharge was 101 × 104t in the 25-km maximum daily rainfall of 1 day, 3 days and 5 days in the Xiliugou desert reach of the Dinghonggou Kongdui in 2010, which is close to the Kongdui. Meanwhile, according to satellite images, the dunes in the results of Du et al. (2014). Hantaichuan Kongdui moved towards to the river year by year during 2005 to 2015 (Fig. 6), illustrating that the storage of aeolian sediment 4.3. Relationship between the amount of aeolian sediment input and wind input increased year by year. Therefore, we can conclude that the speed mechanism of interannual sediment storage and release exists in the sediment delivery processes in the Ten Kongduis. Nevertheless, as the The rose diagrams of the wind speed and wind direction at Ten Kongduis are located in the northern Ordos Plateau and the Dongsheng station during 2006 to 2015 showed that the dominant channel gradients of desert reaches are large, a long-term accumulation wind direction was the west in every year (Fig. 2). The channels of the trend doesn’t exist in the river bed. The release quantity of aeolian Ten Kongduis are nearly perpendicular to the dominant wind direction, sediment input should be close to the storage quantity during a long so it is very conducive to the aeolian sand being delivered into the river period, that is, the average annual amount of aeolian sediment input and a high frequency of high winds will induce a large aeolian sediment should equal to that of aeolian sand carried downstream by the flows. input. Using the aeolian sediment inputs given above, we found indeed that the average annual sand flux of the dunes in the Xiliugou (qXLG, kg/ 5. Conclusions m·min) is related significantly with the frequency (f, %) of daily maximum wind speed (the highest mean wind speed in 10 min) of above (1). According to the data of the surveyed sand dunes, the mean flux of 6 m/s (the wind speed of sand saltation) at the Dongsheng weather aeolian sediment input at the MBLSQ dune was about 8.4 t/m in −4 1.004 2 station. The relation is qXLG =2×10 f (R = 0.656, N =6, the year-long period from November 2014 to November 2015. The P = .05). Thus, 65.6% of the variation of ASFRC in the Xiliugou average sand flux to the river of the unvegetated XLGSQ dune was Kongdui can be explained by the variation of frequency of the winds 2.0 t/m and that of the vegetated XLGSQ dune was 0.41 t/m over with a speed higher than the speed for sand saltation. Similarly, Xu the period from November 2014 to June 2015, while the vegetated (2013) argued that there was a strong positive correlation between the and unvegetated dunes were eroded with a flux of 4.8 t/m and amount of aeolian sediment input in each wind direction and the fre- 3.2 t/m, respectively, over the period from June 2014 to November quency of each wind direction in the Hantaichuan Kongdui as 71.8% of 2015. The amount of aeolian sediment input was estimated to be the volume variation of aeolian sediment input could be explained by about 14.94 × 104 t/yr in the Maobula Kongdui and about the frequency changes of each wind direction. 5.76 × 104 t/yr in the Xiliugou Kongdui over the period from November 2014 to November 2015. 4.4. Time scale effect on aeolian sediment input (2). According to the interpretation results of remote sensing images, the amount of aeolian sediment input to the Maobula Kongdui was Under the semi-arid climate conditions, the water erosion and wind about 15.74 × 104 t in 2011 and 18.2 × 104 t in 2012. The amount erosion often occur simultaneously or alternately, forming a kind of of aeolian sediment input to the Xiliugou Kongdui was 9.52 × 104 t unique complex erosion by wind and water or aeolian-fluvial interac- in 2012, 9.99 × 104 t in the spring of 2013, and 9.96 × 104 t in the tions. The wind erosion and water erosion happen alternately in the Ten spring of 2015. For the Hantaichuan Kongdui, the amount of Kongduis. Xu (2005) pointed out that wind-water coupled erosion was aeolian sediment input was 7.04 × 104 t in 2012, 7.53 × 104 tin the most conducive to the generation of hyperconcentrated flows. The the spring of 2013, and 8.52 × 104 t in the spring of 2015. Our data hyperconcentrated flows formed in the upper reaches by rainstorms in suggest that 65.6% of the variation of aeolian sediment input to the rainy seasons are favorable for the release of the sediment. Specifically, Xiliugou Kongdui can be explained by the variation of frequency of in spring and winter, a large volume of aeolian sediment is transported the wind with a speed above the speed for sand saltation. by the wind from sand dunes to the gullies, main channels and flood- (3). Both interseasonal and interannual sediment storage and release plains and temporarily stored there. In the following summer, the mechanisms exist in the processes of aeolian sediment being de- stored aeolian sediments are delivered downstream by the water. The livered into the Ten Kongduis owing to the changes in wind and data of the surveyed dunes in the Xiliugou Kongdui can prove the ex- rainfall. However, the average annual amount of aeolian sediment istence of the interseasonal sediment storage and release in the sedi- input to the kongduis should be close to that of aeolian sand ment delivery processes in the Ten Kongduis. transported downstream by the flows over a long term. The amount of aeolian sediment input in this study is the storage increment in the river of sediment coming from the sand dunes. The Acknowledgements fluvial transport of the aeolian sediments stored in the river realizes the release of aeolian sediments. The case of the monitored Xiliugou dunes This work was supported by the National Natural Science suggested that all of the aeolian sediment stored in the river in the Foundation of China [grant numbers 41671004, 41371036]. We are period from November 2014 to June 2015 could be carried downstream grateful to Dr. Hezi Yizhaq and the anonymous reviewers for their in- by river flows in the following summer. However, the monitored sightful and helpful comments.

9 H. Yang, C. Shi Aeolian Research 30 (2018) 1–10

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