Sparse Vegetation Cover Research Articles

Spatio-temporal dynamics of soil moisture driven by ‘Grain for Green’ program on the Loess Plateau, China

The continuous afforestation has led to significant changes in soil moisture (SM) dynamics on the Loess Plateau, China (LPC). However, evaluating the spatio-temporal distributions and driving factors of the SM changes following afforestation is challenging because of the difficulty of accessing areas and the lack of long-term series records. Here, we evaluated the accuracy of Global Land Evaporation Amsterdam Model (GLEAM) SM product by comparing with in-situ SM data in LPC, and quantified the spatio-temporal variations of SM in different periods from 1982 to 2015 under the ‘Grain for Green’ program (GGP). The results showed that the Normalized Difference Vegetation Index (NDVI) was well matched with the SM variations in more than 46% area of LPC from 1982 to 2015, which mainly located at the vegetated areas. The variations of SM responding to revegetation displayed obvious southeast-negative and northwest-positive patterns, which was the wet region (annual precipitation >450 mm) to be dry and dry region (annual precipitation ≤450 mm) to be wet. Path coefficient value revealed that the positive effect of vegetation activity for grassland on SM was ascribed to its promotion on the occurrence of rainfall (mean path coefficient = 0.278). Precipitation played vital impact on the SM in bareland and sparsely vegetated area, and evapotranspiration played a dominant role in the SM dynamic of the forestland, especially at the early stage of GGP (From 2000 to 2010), while precipitation and NDVI had stronger effects than evapotranspiration on the SM dynamics of grassland. Our study suggests that in arid and semi-arid areas, vegetation achieves the optimal water retention capacity when the vegetation fractions are 1.4%–3.7% and 3.8%–7.2%, respectively. Hence, vegetation should not be further expanded in semi-humid areas, but should be further restored in arid and semi-arid areas with sparse or excessively sparse vegetation cover (especially in desert).

Imaging Spectroscopic Analysis of Biochemical Traits for Shrub Species in Great Basin, USA

The biochemical traits of plant canopies are important predictors of photosynthetic capacity and nutrient cycling. However, remote sensing of biochemical traits in shrub species in dryland ecosystems has been limited mainly due to the sparse vegetation cover, manifold shrub structures, and complex light interaction between the land surface and canopy. In order to examine the performance of airborne imaging spectroscopy for retrieving biochemical traits in shrub species, we collected Airborne Visible Infrared Imaging Spectrometer—Next Generation (AVIRIS-NG) images and surveyed four foliar biochemical traits (leaf mass per area, water content, nitrogen content and carbon) of sagebrush (Artemesia tridentata) and bitterbrush (Purshia tridentata) in the Great Basin semi-desert ecoregion, USA, in October 2014 and May 2015. We examined the correlations between biochemical traits and developed partial least square regression (PLSR) models to compare spectral correlations with biochemical traits at canopy and plot levels. PLSR models for sagebrush showed comparable performance between calibration (R2: LMA = 0.66, water = 0.7, nitrogen = 0.42, carbon = 0.6) and validation (R2: LMA = 0.52, water = 0.41, nitrogen = 0.23, carbon = 0.57), while prediction for bitterbrush remained a challenge. Our results demonstrate the potential for airborne imaging spectroscopy to measure shrub biochemical traits over large shrubland regions. We also highlight challenges when estimating biochemical traits with airborne imaging spectroscopy data.

Evaluation of Manning’s n Roughness Coefficient in Arid Environments by Using SAR Backscatter

The prediction of arid region flash floods (magnitude and frequency) is essential to ensure the safety of human life and infrastructures and is commonly based on hydrological models. Traditionally, catchment characteristics are extracted using point-based measurements. A considerable improvement of point-based observations is offered by remote sensing technologies, which enables the determination of continuous spatial hydrological parameters and variables, such as surface roughness, which significantly influence runoff velocity and depth. Hydrological models commonly express the surface roughness using Manning’s roughness coefficient (n) as a key variable. The objectives were thus to determine surface roughness by exploiting a new high spatial resolution spaceborne synthetic aperture radar (SAR) technology and to examine the correlation between radar backscatter and Manning’s roughness coefficient in an arid environment. A very strong correlation (R2 = 0.97) was found between the constellation of small satellites for Mediterranean basin observation (COSMO)-SkyMed SAR backscatter and surface roughness. The results of this research demonstrate the feasibility of using an X-band spaceborne sensor with high spatial resolution for the evaluation of surface roughness in flat arid environments. The innovative method proposed to evaluate Manning’s n roughness coefficient in arid environments with sparse vegetation cover using radar backscatter may lead to improvements in the performance of hydrological models.

Fuelwood resources and their use pattern by Bhotia community in Niti valley, Western Himalaya

The local communities of the Himalaya have been using fuel wood as one of the major sources of energy since millennia. Their dependency on these resources as primary source of fuel wood has resulted in unsustainable pressures on the forests. The present communication aims to access the fuel wood resource and consumption pattern of Bhotia, an ethnic community in a cold arid and buffer zone of Nanda Devi Biosphere Reserve, i.e. Niti valley in the Western Himalaya. Within the Niti valley, 87 households in six villages were surveyed using open and close-ended structured questionnaire. Use Index (I%) of each fuel wood species was calculated to evaluate the key species used by the inhabitants and their preferences. The study revealed use of 10 species for fuel wood (five species each of tree and shrub) by the Bhotias. Pinus wallichiana (I = 96.6%) followed by Cedrus deodara (93.1%) were the preferred tree species for fuel wood, while among shrubs, Juniperus indica and J. communis were extensively used. Fuel wood consumption in the Niti valley was much lower (1.6±0.2 kg household-1 day-1) than other villages in the Greater Himalaya (4.9±0.4 kg household-1 day-1). The seasonally employed which formed 23% of the surveyed households, collected almost twice as much fuel wood than the employed households (9.2±0.4 and 5.2±0.4 quintals season-1, respectively). As the area is characterized by sparse vegetation cover, low primary productivity and short growing season, and is thus highly susceptible to irreversible changes of natural habitats. The study suggests that providing alternate and non-conventional energy sources such as solar cookers and fuel efficient portable ovens to the inhabitants at subsidized rates could reduce the pressure on nearby forests. Botanica Orientalis – Journal of Plant Science (2017) 11: 1–6

Soil moisture estimation using land surface temperature and soil temperature at 5 cm depth

ABSTRACTSoil Temperature (ST) data, obtained from either field works or satellite imagery, has frequently been studied for Soil Moisture (SM) estimation. However, a combination of ST data at different depths and soil surface temperature, i.e., Surface Radiometric Temperature (SRT) or Land Surface Temperature (LST), has not yet been well investigated for accurate SM prediction. In this study, an empirical model was first developed to estimate SM at 5 cm Depth (SM5D) over areas with no or sparse vegetation cover using the field SRT and field ST data at 5 cm Depth (ST5D). A Root Mean Square Error (RMSE) and a correlation coefficient (r) of 0.037 m3 m−3 and 0.8 were obtained using this model, respectively. Then, the SRT was substituted by the LST obtained from Landsat thermal bands and ST5D was estimated using the ST data collected at the nearest weather station to the study area by developing a regression equation. The second model demonstrated an RMSE and r of 0.035 m3 m−3 and 0.71, respectively. Overall, it was concluded that the proposed models had high potential for SM estimation using the ST data at different depths collected in the field or acquired by optical satellites.

Assessing gully erosion susceptibility in Mayurakshi river basin of eastern India

The present study assessed the extent to which the gully erosion susceptibility could be successfully modeled in Mayurakshi river basin as a function of four gully controlling factor clusters (topographical, erosivity, erodibility, and resisting). Gully erosion zones have been identified through two different models (correlation matrix and logistic regression) incorporating 15 conditioning indicators. Both the models have generated quite identical result regarding gully erosion susceptibility. It illustrates that extreme erosion-susceptible zones cover almost 16% of the basin area followed by high susceptibility with almost 28% areal coverage. This susceptibility is dominantly confined within the upper catchment. Older and newer alluvial plains of the lower catchment belong to low susceptibility to relatively safe situation. Models are validated by constructing ROC curve and calculating Kappa statistics. Both the approaches certified the validity of the models. The factor clustering shows that the positively influencing clusters like erosivity factors and erodibility factors are playing a dominant role with, respectively, 76 and 75% correlation with gully erosion susceptibility, whereas the resistant factors achieved only 32% correlation which denotes week significance due to containing sparse vegetation cover having low canopy density as well as poor crop management and conservation practice.

Is cattle grazing more important than landscape heterogeneity for grasshoppers in Afromontane grassland?

Overgrazing is a major driver of habitat degradation, especially in southern Africa. Although grasshoppers are adapted to and benefit from natural disturbances, such as grazing by indigenous game and burning, we do not know how they respond to heavy cattle grazing, and how this response interacts with different fire regimes. We also do not know whether grasshoppers respond principally to these disturbances, to changes in the vegetation layer, or to larger landscape attributes (e.g. elevation). We addressed these questions in the topographically heterogeneous Central Midlands of KwaZulu-Natal Province, South Africa. We compared grasshopper assemblages among sites differing in grazing intensity (light, moderate and heavy), fire regime, rocky outcrops and vegetation structure, and attributes of landscape heterogeneity. The local environment (rocky outcrops, bare ground cover, grass height and total vegetation cover) was more important than landscape attributes for all measures of diversity. Grasshopper species richness was best explained by grazing intensity, with the specific response determined by fire regime. Greatest species richness was consistently recorded in heavily-grazed grassland. Thus, we found no evidence in support of the Intermediate Disturbance Hypothesis. Grasshopper assemblage composition of areas with light grazing was different from those with heavy grazing, but areas with light grazing were similar to those with moderate grazing under all fire regimes. Different suites of grasshopper species were adapted to changes in the local environment, with greatest diversity (Shannon H’) associated with elevated levels of bare ground and sparse vegetation cover. The greatest proportion of rare, endemic and sensitive grasshoppers (incl. Lentula minuta, Machaeridia conspersa and Qachasia fastigiata) was associated with a greater proportion of vegetation cover. The sensitivity of grasshopper assemblages to fire-grazing interactions, and the habitat requirements of different suites of species necessitates consideration of different types (fire and grazing) as well as levels of disturbances when adjusting management practices. We recommend that conservation of rare, endemic and sensitive grasshoppers should be prioritized, as these are most vulnerable to local extirpation.

<i>Picea schrenkiana</i> tree-ring chronologies development and vegetation index reconstruction for the Alatau Mountains, Central Asia

In this study, a total of 176 tree cores from Schrenk spruce (<i>Picea schrenkiana</i>) were used to establish a tree-ring chronology and a 167-year July–October normalized differential vegetation index (NDVI) for the Alatau Mountains in Central Asia was reconstructed using this newly developed chronology. The tree-ring based NDVI reconstruction tracks the observed data well (<i>r</i>=0.577, <i>p</i><0.01, n=25) and precisely captures the drought events recorded in historical documents that occurred over a large area in 1917 and 1938. After applying a 21-year moving average, three dense (1860–1870, 1891–1907, and 1950–1974) and three sparse (1871–1890, 1908–1949, and 1975–2006) vegetation coverage periods were found in this reconstruction. Spatial correlation proves that the reconstructed NDVI series contains climatic signals representative for a large area including southern Kazakhstan. Although a comparison between this reconstruction and four climatic reconstructions for southeastern Kazakhstan, Nilka (in the Ili region), the Issyk Lake, and the Aksu region reveals similar variations, the coherence between these reconstructions become weak with the increase in spatial distance from north to south. In addition to the local representation, it was also demonstrated that the newly developed NDVI index can indicate the large-scale circulations over Eurasia, with the higher NDVI associated with stronger westerly winds from the Atlantic to the Alatau Mountains, and the lower NDVI associated with the weaker winds.

Use of remote sensing indicators to assess effects of drought and human-induced land degradation on ecosystem health in Northeastern Brazil

Land degradation (LD) is one of the most catastrophic outcomes of long-lasting drought events and anthropogenic activities. Assessing climate and human-induced impacts on land can provide information for decision makers to mitigate the effects of these phenomena. The Northeastern region of Brazil (NEB) is the most populous dryland on the planet, making it a highly vulnerable ecosystem especially when considering the lingering drought that started in 2012. The present work consisted of detecting trends in biomass [leaf area index (LAI)] anomalies as indicators of LD in NEB. We also assessed how the loss of vegetation impacts the LD cycle, by measuring trends in albedo and evapotranspiration (ET). LAI, albedo and ET data were derived from MODIS sensors at 8-day temporal and 500 m spatial resolutions. For precipitation anomalies, we relied on CHIRPS-v2 10-day temporal at 5 km spatial resolution data. For detecting trends, we applied the Theil-Sen slope analysis on time series of MODIS LAI, albedo and ET images. Trend analysis was performed for the periods ranging from 2002–2012 (no severe droughts) to 2002–2016 (including the last drought). LAI trends were more pronounced and had a stronger signal than ET and albedo, therefore, LAI was our choice for mapping LD. The first analysis highlighted the human-induced LD prone areas whereas the last detected drought-induced LD prone areas. Considering only the trending areas, which was about 23.4% of the total, 4.5% of this area has undergone human-induced degradation whereas drought was responsible for 73%, although, not mutually exclusive. As reported in the literature and official data, grazing intensification might be a factor driving human-induced degradation. We noticed that the range of variation of LAI is narrow and even narrower for albedo, which demonstrates that land surface response is more influenced by soil reflectivity rather than the characteristic sparse vegetation coverage (LAI ranging from 0.04 to 0.4 in the Caatinga biome), which can barely alter albedo. Finally, the effects of LD on ET anomalies were assessed by Granger causality and impulse-response analyses as means to link land surface feature changes to the hydrological cycle. Albedo had a slightly weaker impulse than LAI on ET whereas precipitation played a major role. These relations are site-specific and, land surface features (biomass and albedo) showed to have a more substantial influence on ET in severely degraded areas. We concluded that drought led to trends indicating LD prone areas in NEB and the degradation cycle has positive feedback derived from ET reduction resulting in an increased net moisture deficit, although the latter statement has yet to be further investigated. The study warns of the desertification risk that NEB is facing and the need for the authorities to take action to mitigate degradation and drought effects on both traditionally surveyed (desertification nuclei) and newfound LD prone areas. We also highlight the limitation of confirming LD, as to date there is no post-drought data available and, lessons learned from the Sahel case make us cautious about claiming that an area is in fact degraded.

Using VIIRS-DNB and landsat data for impervious surface area mapping in an arid/semiarid region

ABSTRACTMapping impervious surface area (ISA) in arid/semiarid regions is of great importance because of the vulnerable ecological situation there. However, using remote sensing data for ISA mapping in arid/semiarid landscapes is still very difficult because of the complexities of ISA, such as bare soils, impervious surface areas, and sparse vegetation cover. The Visible Infrared Imaging Radiometer Suite with Day/Night Band (VIIRS-DNB) carried by the Suomi National Polar-orbiting Partnership, focusing on earth nighttime light, provides novel ways to map urban information, but is still little used in ISA mapping. In this paper, we explore a new index based on VIIRS-DNB data called the improved impervious surface index (IISI). We use a linear regression model for fractional ISA estimation in an arid/semiarid urban region, and the IISI was used as an independent variable. Reference ISAs from selected sites were mapped from Landsat images and were used as a dependent variable in this model. The results indicate that the IISI-based model provides good estimation with coefficient of determination (R2)of 0.70, much greater accuracy than that using normalized VIIRS-DNB data. This method is very valuable for fractional ISA mapping in an arid/semiarid region.

Using negative soil adjustment factor in soil-adjusted vegetation index (SAVI) for aboveground living biomass estimation in arid grasslands

All values of soil adjustment factor (L) from 0 to 1 in the soil-adjusted vegetation index (SAVI) were found to be undesirable in arid areas with sparse vegetation cover. We hypothesized that the negative soil adjustment factor in the SAVI would be satisfactory in arid areas. In the study, we explored the potential of negative soil adjustment factor in the SAVI against a set of field measurements during the growing season of 2009 in the desert steppe of Inner Mongolia, China. As hypothesized, negative soil adjustment factor was found to give satisfactory reduction of soil background noise. SAVI (L = −0.2) (R2 = 0.64, RMSE = 18.4 g m−2, rRMSE = 25.5%, n = 120) provided dramatic improvements over optimal NDVI (normalized difference vegetation index) (that is, SAVI (L = 0)) (R2 = 0.44, RMSE = 22.7 g m−2, rRMSE = 31.4%, n = 120) for aboveground living biomass (AGB) estimation among tested vegetation indices. A physical basis for the negative soil adjustment factor was also explored. Results showed that, the intersected points between approximate vegetation isolines and soil line were situated in the domain of positive values of NIR (near-infrared) and red in the first quadrant of NIR-red plane, and the slopes of vegetation isolines increased with increasing AGB in the desert steppe, thus resulting in negative factor by shifting the origin toward positive intersected points. This runs counter to reported vegetation isolines behavior for SAVI, in which the intersected points were situated in the region of negative values of NIR and red in the third quadrant. The good performance of negative factor was also observed for percent green cover (PGC) estimation in the desert steppe. We further proposed a conceptual model to describe vegetation isolines behavior in arid grasslands. Our findings will complement widely used soil adjustment factor. Further study is needed to validate the negative soil factor and test the conceptual model in other arid grasslands.

Spatial feature analysis of a cosmic-ray sensor for measuring the soil water content: Comparison of four weighting methods

To quantitatively analyze the spatial features of a cosmic-ray sensor (CRS) (i.e., the measurement support volume of the CRS and the weight of the in situ point-scale soil water content (SWC) in terms of the regionally averaged SWC derived from the CRS) in measuring the SWC, cooperative observations based on CRS, oven drying and frequency domain reflectometry (FDR) methods are performed at the point and regional scales in a desert steppe area of the Inner Mongolia Autonomous Region. This region is flat with sparse vegetation cover consisting of only grass, thereby minimizing the effects of terrain and vegetation. Considering the two possibilities of the measurement support volume of the CRS, the results of four weighting methods are compared with the SWC monitored by FDR within an appropriate measurement support volume. The weighted average calculated using the neutron intensity-based weighting method (Ni weighting method) best fits the regionally averaged SWC measured by the CRS. Therefore, we conclude that the gyroscopic support volume and the weights determined by the Ni weighting method are the closest to the actual spatial features of the CRS when measuring the SWC. Based on these findings, a scale transformation model of the SWC from the point scale to the scale of the CRS measurement support volume is established. In addition, the spatial features simulated using the Ni weighting method are visualized by developing a software system.

Evolution of integrated lake status since the last deglaciation: A high-resolution sedimentary record from Lake Gonghai, Shanxi, China

Alpine lakes not only provide internationally important habitats for endangered species, they also play a crucial role in the regional water balance. Unfortunately, a rapid loss of alpine lakes in China has occurred in recent decades; however, intensive human activities, together with regional differences in the responses of lakes to climate change, has impeded our understanding of the contribution of climate change to the loss of these lakes. To better understand how alpine lakes will evolve with continuing global warming, we used the analysis of new sedimentary proxies from Lake Gonghai, an undisturbed alpine lake, together with a review of published records, to reconstruct variations in integrated lake status since the last deglaciation. From 14,660–11,890 cal. yr BP the lake was in the most unstable state, indicated by the highest amplitude fluctuations in lake level and the within-lake environment. The lake status experienced clear millennial-scale changes. During the early and middle Holocene (11,890–3200 cal. yr BP), the most stable lake status occurred, consistent with the highest precipitation levels. Owing to the highest level of freshwater influx in the middle Holocene (8–5 ka), the lake water was the deepest and most acidic. At this time, the dense vegetation cover resulted in maximum catchment stability and the lowest level of soil erosion, and hence the lowest sediment accumulation rate. From 3200 cal. yr BP, decreasing mean annual precipitation resulted in a moderately stable lake status, a shallow water depth and more alkaline lake water. The sparse vegetation cover caused a dramatic increase in the erosion rate and hence in the sediment accumulation rate. We infer that variations in local humidity were the major control on the integrated lake status during the last ~14,600 cal. yr BP. With the anticipated progression of global warming, the status of the alpine lakes in the region may continue to deteriorate and appropriate mitigation strategies are imperative.

Estimation of Surface Soil Moisture in Cornfields Using a Modified MODIS-Based Index and Considering Corn Growth Stages

In this paper, we propose a new method for estimating soil moisture in cornfields, based on regression models using moderate resolution imaging spectroradiometer (MODIS) data and field measurements. Soil moisture is related to the perpendicular drought index (PDI) and vegetation supply water index (VSWI). Thus, we propose a modified MODIS-based index (MMI) combining PDI and VSWI, to build regression models incorporating MMI and in situ soil moisture measurements. In the MMI, PDI is used to estimate soil moisture in areas with bare soil or sparse vegetation cover, and VSWI is used for estimation of soil moisture in areas with other cover types. Considering the dependence of soil moisture estimation on corn growth stages, we incorporated five growth stages—seeding, seedling, growing, maturing, and harvesting stages in the regression models for soil moisture estimation. These models were built for each stage using five years of soil moisture data obtained through field measurements combined with daily MMI at 1-km spatial resolution. Our results show that the MMI is strongly correlated to in situ soil moisture at each corn growth stage, and furthermore, these correlations are dependent on vegetation cover and growth stage. The correlation coefficients between field-measured and model-estimated soil moisture were 0.73, 0.67, 0.66, 0.74, and 0.63 for each growth stage, respectively. The estimated soil moisture was more accurate than SMOS-BEC soil moisture Level 3 products. These findings show that our model is a feasible method for estimating surface soil moisture accurately at the 1-km scale for cornfields in the study area.

Enough space in a warmer world? Microhabitat diversity and small‐scale distribution of alpine plants on mountain summits

AbstractAimGlobal warming is predicted to shift distributions of mountain species upwards, driven by a release from climatic restrictions at their upper distribution limit and increased biotic pressure at their lower distribution limit. In alpine ecosystems, which are characterized by large microclimatic diversity and sparse vegetation cover, the relative importance of abiotic and biotic drivers for species distribution is poorly understood. To disentangle abiotic and biotic mechanisms affecting distributions of alpine species, we investigated how alpine plant species with differing elevational ranges and frequency trends over the past century differ in their microhabitat distribution, and how they respond to neighbouring vegetation.LocationA total of 11 summits (2635—3410 m a.s.l.) in SE‐Switzerland.MethodsWe quantified the microscale abundance of 12 species in relation to biogeographic (frequency trend, i.e., change in occurrences over the past century, and elevational range on summits) and local microhabitat characteristics (temperature, substrate type). We assessed species size traits in relation to neighbouring vegetation characteristics to investigate possible neighbour interactions.ResultsSpecies with increasing frequency on summits over the past century were most abundant on scree and warmer slopes. Species with negative or stable frequency trends on summits were more abundant on organic soil and colder slopes. The preferred microhabitats of the latter were rarest overall, decreased with increasing elevation, and had the most competitive neighbours. Size of one high‐alpine specialist, Ranunculus glacialis was negatively related to cover of neighbouring vegetation, whereas other species showed no response to neighbours.Main conclusionsLong‐term frequency trends of species correlate with their microhabitat association. Species with most negative frequency trends show preferences for the rarest microhabitat conditions, where they likely experience higher competitive pressure in a warming climate. This finding emphasizes the importance of characterizing microhabitat associations and microclimatic diversity to assess present and future distributions of alpine plant species.

Low flow controls on stream thermal dynamics

Water level fluctuations in surface water bodies, and in particular low flow drought conditions, are expected to become more frequent and more severe in the future due to the impacts of global environmental change. Variations in water level, and therefore in-channel water volume, not only have the potential to directly impact stream temperature, but also aquatic vegetation coverage which, in turn, may affect stream temperature patterns and dynamics. Manipulation experiments provide a systematic approach to investigate the multiple environmental controls on stream temperature patterns. This study aims to use temperature data loggers and fibre optic distributed temperature sensing (FO-DTS) to investigate potential drought impacts on patterns in surface water and streambed temperature as a function of change in water column depth. To quantify the joint impacts of water level and associated vegetation coverage on stream temperatures, investigations were conducted in outdoor flumes using identical pool-riffle-pool features, but with spatially variable water levels representative of different drought severity conditions. Naturally evolved vegetation growth in the flumes ranged from sparse vegetation coverage in the shallow flumes to dense colonization in the deepest. Observed surface water and streambed temperature patterns differed significantly within the range of water levels and degrees of vegetation coverage studied. Streambed temperature patterns were more pronounced in the shallowest flume, with minimum and maximum temperature values and diurnal temperature variation being more intensively affected by variation in meteorological conditions than daily average temperatures. Spatial patterns in streambed temperature correlated strongly with morphologic features in all flumes, with riffles coinciding with the highest temperatures, and pools representing areas with the lowest temperatures. In particular, the shallowest flume (comprising multiple exposed features) exhibited a maximum upstream-downstream temperature warming of 3.3°C (T in=10.3°C, T out=13.5°C), exceeding the warming observed in the deeper flumes by ∼2°C. Our study reveals significant streambed and water temperature variation caused by the combined impacts of water level and related vegetation coverage. These results highlight the importance of maintaining minimum water levels in lowland rivers during droughts for buffering the impacts of atmospheric forcing on both river and streambed water temperatures.

Improved method of freeze–thaw erosion for the Three-River Source Region in the Qinghai–Tibetan Plateau, China

ABSTRACTIn order to quantitatively evaluate the intensity of FT erosion, eight typical factors, including annual FT cycle days, precipitation, average diurnal phase-changed water content, rainfall erosivity during the FT period, wind field intensity during the FT period, slope, aspect, and vegetation, were introduced to establish an improved evaluation method of FT erosion in the TRSR, which had better applicability in TRSR with an overall precision of 93%. Results showed that FT erosion was widely distributed in the TRSR, with zones of slight, mild, and moderated erosion being the most widely distributed. During 2000–2015, a slight improvement can be observed in the condition of FT erosion over the whole study region. Vegetation coverage was the dominant factor affecting the intensity of FT erosion in the zones with sparse vegetation or bare land, whereas the climate factors played an important role in high vegetation coverage area. Vegetation coverage played a dominant role in affecting the FT erosion intensity in zones with 0.3 ≤ VC < 0.6, whereas the terrain and climate factors played an more important role in areas with sparse vegetation (VC < 0.3) or high vegetation coverage (VC ≥ 0.6). Meanwhile, slope was of great importance in affecting the process of FT erosion in zones with slopes of >18°.

Three years of morphologic changes at a bowl blowout, Cape Cod, USA

This study presents measurements of blowout topography obtained with annual terrestrial laser surveys carried out over a three-year period at a single, large bowl blowout located in the Provincelands Dunes section of Cape Cod National Seashore, in Massachusetts. The study blowout was selected because its axis is aligned with northwest winds that dominate the region, and because it was seemingly interacting with a smaller saucer blowout that had recently formed on the southern rim of the primary feature. Assuming that blowouts enlarge both horizontally and vertically in response to the wind regime, the objectives of the study were to determine both the amount of horizontal growth that the blowout experiences annually and the spatial patterns of vertical change that occur within the blowout. Changes to the blowout lobe surrounding the feature were also determined for areas with sparse enough vegetation cover to allow laser returns from the sand surface. The results show that the blowout consistently expanded outward during the three years, with the greatest expansion occurring at its southeast corner, opposite the prevailing winds. The most significant occurrence was the removal, in the first year, of the ridge that separated the two blowouts, resulting in a major horizontal shift of the southern rim of the new combined blowout. This displacement then continued at a lesser rate in subsequent years. The rim also shifted horizontally along the northwest to northeast sections of the blowout. Significant vertical loss occurred along the main axis of the blowout with the greatest loss concentrated along the southeast rim. On the lobe, there were large areas of deposition immediately downwind of the high erosion zones inside the blowout. However, there were also small erosion areas on the lobe, extending downwind from eroding sections of the rim. This study shows that: 1. blowouts can experience significant areal and volumetric changes in short periods of time; 2. significant changes may occur relatively suddenly when adjacent blowouts combine into a single feature; and 3. the sediment transport paths are highly controlled by the topography. The joining of two blowouts not only creates a new larger feature, but it also releases large amounts of sediment that are then distributed across the landscape downwind, creating a potential for major changes to a landscape over the longer term.

Hydrological cycle and water balance estimates for the megadune–lake region of the Badain Jaran Desert, China

AbstractThe hydrology and water balance of megadunes and lakes have been investigated in the Badain Jaran Desert of China. Field observations and analyses of sand layer water content, field capacity, secondary salt content, and grain size reveal 3 types of important natural phenomenon: (a) vegetation bands on the leeward slope of the megadunes reflect the hydrological regime within the sandy vadose zone; (b) seepage, wet sand deposits, and secondary salt deposits indicate the pattern of water movement within the sandy vadose zone; (c) zones of groundwater seeps and descending springs around the lakes reflect the influence of the local topography on the hydrological regime of the megadunes. The seepage exposed on the sloping surface of the megadunes and gravity water contained within the sand layer confirm the occurrence of preferential flow within the vadose zone of the megadunes. Alternating layers of coarse and fine sand create the conditions for the formation of preferential flows. The preferential flows promote movement of water within the sand layer water that leads to deep penetration of water within the megadunes and ultimately to the recharging of groundwater and lake water. Our results indicate that a positive water balance promotes recharge of the megadunes, which depends on the high permeability of the megadune material, the shallow depth of the surface sand layer affected by evaporation, the occurrence of rainfall events exceeding 15 mm, and the sparse vegetation cover. Water balance estimates indicate that the annual water storage of the megadunes is about 7.5 mm, accounting for only 8% of annual precipitation; however, the shallow groundwater per unit area under the megadunes receives only 3.6% of annual precipitation, but it is still able to maintain a dynamic balance of the lake water. From a water budget perspective, the annual water storage in the megadunes is sufficient to serve as a recharge source for lake water, thereby enabling the long‐term persistence of the lakes. Overall, our findings demonstrate that precipitation is a significant component of the hydrological cycle in arid deserts.

Long and short term population dynamics of acacia trees via remote sensing and spatial analysis: Case study in the southern Negev Desert

Monitoring vegetation dynamics in hyper-arid zones is important because any decrease in the already sparse vegetation cover in these areas could considerably affect the entire ecosystem. The new generation of high spatial resolution satellite (HSR) sensors is suitable for monitoring trees in arid regions because of the distinct and separate objects that trees represent in these environments. The main limitation of modern HSR sensors is the lack of a historical archive that would otherwise enable meaningful landscape change detection, especially in arid regions where tree population dynamics are naturally very slow. This study uses spatial analysis to gain information regarding the long- and short-term dynamic processes affecting the acacia tree population in Wadi Ktora, in the southern Arava Valley, Israel. The data is extracted from a single HSR aerial photograph composed of three spectral bands in the visible and infrared spectrum (green, red, and near infrared).A map of individual acacia trees that is extracted from a colour infrared aerial photograph of Wadi Ktora from 2010 enables the examination of spatial distribution patterns for both tree size and foliage health. Tree size distribution is used as an indicator of long-term (decades) hydrologic spatial processes affecting the acacia population. The tree health distribution is used as an indicator for short-term (months to a few years) hydrologic spatial processes, such as the paths of recent flash floods events. Comparing the distributions of tree size and normalized difference vegetation index (NDVI) enables differentiation between the long-term and short-term processes that brought the population to its present state.Using spatial statistic grouping, the distribution of the trees in the wadi (ephemeral stream) is divided into three distinct categories: (1) large trees with high NDVI values, (2) large trees with low NDVI values, and (3) small trees with medium NDVI values. Using the resulting classification, we divided the wadi into three sections, each representing a unique combination of long- and short-term hydrologic processes affecting the acacia trees. We suggest that the lack of spatial correlation between tree size and health status is a result of spatio-temporal changes in the water supply.