Streamflow forecasting in drylands is challenging. Data is scarce, catchments are highly human-modified and streamflow exhibits strong nonlinear responses to rainfall. The goal of this study was to evaluate the monthly and seasonal streamflow forecasting in two large catchments in the Jaguaribe River Basin in the Brazilian semi-arid area. We adopted four different lead times: one month ahead for monthly scale and two, three and four months ahead for seasonal scale. The gaps of the historic streamflow series were filled up by using rainfall-runoff modelling. Then, time series model techniques were applied, i.e., the locally constant, the locally averaged, the k-nearest-neighbours algorithm (k-NN) and the autoregressive model (AR). The criterion of reliability of the validation results is that the forecast is more skillful than streamflow climatology. Our approach outperformed the streamflow climatology for all monthly streamflows. On average, the former was 25% better than the latter. The seasonal streamflow forecasting (SSF) was also reliable (on average, 20% better than the climatology), failing slightly only for the high flow season of one catchment (6% worse than the climatology). Considering an uncertainty envelope (probabilistic forecasting), which was considerably narrower than the data standard deviation, the streamflow forecasting performance increased by about 50% at both scales. The forecast errors were mainly driven by the streamflow intra-seasonality at monthly scale, while they were by the forecast lead time at seasonal scale. The best-fit and worst-fit time series model were the k-NN approach and the AR model, respectively. The rainfall-runoff modelling outputs played an important role in improving streamflow forecasting for one streamgauge that showed 35% of data gaps. The developed data-driven approach is mathematical and computationally very simple, demands few resources to accomplish its operational implementation and is applicable to other dryland watersheds. Our findings may be part of drought forecasting systems and potentially help allocating water months in advance. Moreover, the developed strategy can serve as a baseline for more complex streamflow forecast systems.

We provide estimates of glacier mass changes in the High Mountain Asia (HMA) area from April 2002 to August 2016 by employing a new version of gravity solutions of the Gravity Recovery and Climate Experiment (GRACE) twin-satellite mission. We found a total mass loss trend of the HMA glaciers at a rate of -22.17 (±1.96) Gt/a. The largest mass loss rates of -7.02 (±0.94) and -6.73 (±0.78) Gt/a are found for the glaciers in Nyainqentanglha Mountains and Eastern Himalayas, respectively. Although most glaciers in the HMA area show a mass loss, we find a small glacier mass gain of 1.19 (±0.55) and 0.77 (±0.37) Gt/a in Karakoram Mountains and West Kunlun Mountains, respectively. There is also a nearly zero mass balance in Pamirs. Our estimates of glacier mass change trends confirm previous results from the analysis of altimetry data of the ICESat (Ice, Cloud and Land Elevation) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) DEM (Digital Elevation Model) satellites in most of the selected glacier areas. However, they largely differ to previous GRACE-based studies which we attribute to our different post-processing techniques of the newer GRACE data. In addition, we explicitly show regional mass change features for both the interannual glacier mass changes and the 14-a averaged seasonal glacier mass changes. These changes can be explained in parts by total net precipitation (net snowfall and net rainfall) and net snowfall, but mostly by total net radiation energy when compared to data from the ERA5-Land meteorological reanalysis. Moreover, nearly all the non-trend interannual mass changes and most seasonal mass changes can be explained by the total net radiation energy data. The mass loss trends could be partly related to a heat effect due to increased net rainfall in Tianshan Mountains, Qilian Mountains, Nyainqentanglha Mountains and Eastern Himalayas. Our new results for the glacier mass change in this study could help improve the understanding of glacier variation in the HMA area and contribute to the study of global change. They could also serve the utilization of water resources there and in neighboring areas.

Winter snowpack is an important source of moisture that influences the development of biological soil crusts (BSCs) in desert ecosystems. Cyanobacteria are important photosynthetic organisms in BSCs. However, the responses of the cyanobacterial community in BSCs to snowpack, snow depth and melting snow are still unknown. In this study, we investigated the cyanobacterial community composition and diversity in BSCs under different snow treatments (doubled snow, ambient snow and removed snow) and three snow stages (stage 1, snowpack; stage 2, melting snow; and stage 3, melted snow) in the Gurbantunggut Desert in China. In stages 1 and 2, Cyanobacteria were the dominant phylum in the bacterial community in the removed snow treatment, whereas Proteobacteria and Bacteroidetes were abundant in the bacterial communities in the ambient snow and doubled snow treatments. The relative abundances of Proteobacteria and Bacteroidetes increased with increasing snow depth. The relative abundances of Cyanobacteria and other bacterial taxa were affected mainly by soil temperature and irradiance. In stages 2 and 3, the relative abundance of Cyanobacteria increased quickly due to the suitable soil moisture and irradiance conditions. Oscillatoriales, Chroococcales, Nostocales, Synechococcales and unclassified Cyanobacteria were detected in all the snow treatments, and the most dominant taxa were Oscillatoriales and Chroococcales. Various cyanobacterial taxa showed different responses to snowpack. Soil moisture and irradiance were the two critical factors shaping the cyanobacterial community structure. The snowpack depth and duration altered the soil surface irradiance, soil moisture and other soil properties, which consequently were selected for different cyanobacterial communities. Thus, local microenvironmental filtering (niche selection) caused by snow conditions may be a dominant process driving shifts in the cyanobacterial community in BSCs.

Bacteria in desert soil have unique phylogeny and important ecological functions, and their responses to changes in precipitation need further attention. However, relevant studies have mainly focused on the surface soil, and studies on the responses of bacteria at different soil depths to variations in precipitation are rare. Thus, we used 16S rDNA high-throughput sequencing to investigate the changes in soil bacterial distribution along a mean annual precipitation gradient (50-150 mm) in the Alxa Desert, China, and compared the variation characteristics in the surface soil layer (0-10 cm) and subsurface soil layer (10-20 cm). Results showed that soil bacterial communities significantly changed along the precipitation gradient in both soil layers. However, the subsurface soil layer could support bacterial communities with higher diversity and closer internal relationships but more internal competition than the surface soil layer. Additionally, compared with the surface soil layer, variations in diversity and co-occurrence patterns in the subsurface soil layer were more in line with the changes in the mean annual precipitation, while bacterial community structure was less variable in the subsurface soil layer. Compared with the mean annual precipitation, soil moisture had little influence on the structure and diversity of soil bacterial community but had a high correlation with intercommunity connectivity. Therefore, soil moisture might play a complex role in mediating environmental conditions and soil bacterial community characteristics. Due to the different responses of surface and subsurface soil bacteria to the changes in precipitation, it is necessary to distinguish different soil layers when predicting the trends in desert soil bacterial conditions associated with precipitation, and prediction of subsurface soil bacteria may be more accurate.

Deserts are ideal places to develop ground-mounted large-scale solar photovoltaic (PV) power station. Unfortunately, solar energy production, operation, and maintenance are affected by geomorphological changes caused by surface erosion that may occur after the construction of the solar PV power station. In order to avoid damage to a solar PV power station in sandy areas, it is necessary to investigate the characteristics of wind-sand movement under the interference of solar PV array. The study was undertaken by measuring sediment transport of different wind directions above shifting dunes and three observation sites around the PV panels in the Hobq Desert, China. The results showed that the two-parameter exponential function provides better fit for the measured flux density profiles to the near-surface of solar PV array. However, the saltation height of sand particles changes with the intersection angle between the solar PV array and wind direction exceed 45°. The sediment transport rate above shifting dunes was always the greatest, while that around the test PV panels varied accordingly to the wind direction. Moreover, the aeolian sediment transport on the solar PV array was significantly affected by wind direction. The value of sand inhibition rate ranged from 35.46% to 88.51% at different wind directions. When the intersection angle exceeds 45°, the mean value of sediment transport rate above the solar PV array reduces to 82.58% compared with the shifting dunes. The results of our study expand our understanding of the formation and evolution of aeolian geomorphology at the solar PV footprint. This will facilitate the design and control engineering plans for solar PV array in sandy areas that operate according to the wind regime.

Sediment transport of sand particles by wind is one of the main processes leading to desertification in arid regions, which severely impairs the ability of mankind to produce and live by drifting sand into settlements. Optimization designs of artificial facilities have lately attracted extensive interest for human settlement systems in deserts because of their acceptable protection effect, convenience of implementation, and low material cost. However, the complexity of a settlement system poses challenges concerning finding suitable materials, artificial facilities, and optimization designs for sand deposition protection. In an effort to overcome these challenges, we propose a settlement system built with brick, solar panel, and building arrays to meet the basic needs of human settlements in arid regions while preventing wind-sand disasters. The wind flow and movement characteristics of sand particles in the brick, panel, and building arrays were calculated using computational fluid dynamics and discrete phase model. The performance of three types of arrays in wind-sand flow in terms of decreasing the wind velocity and sand-particle invasion distance was evaluated. The results show that the wind velocity near the surface and the sand invasion distance were significantly decreased in the space between the brick arrays through properly selected vertical size and interspaces, indicating that the brick arrays have an impressive sand fixing and blocking performance; their effective protection distance was 3-4 m. The building arrays increased the near-surface wind velocity among buildings, resulting in less deposition of sand particles. The solar panel arrays were similar to the building arrays in most cases, but the deposition of sand particles on solar panels exerted a negative effect on energy utilization efficiency. Therefore, taking the optimal configuration of the settlement system into consideration, this study concludes that (1) brick arrays, which were proven effective in preventing sand particles, must be arranged in an upwind area; (2) solar panel arrays could accelerate the wind flow, so they are best to be arranged at the place where sand particles deposited easily; and (3) building arrays present a better arrangement in downwind areas.

Ants (Formicidae, Hymenoptera) play an important role in seed bank, seedling establishment and plant composition of arid ecosystems. Thus, knowing plant-ant interaction provides useful information for managers to design restoration and conservation plans. In this study, the roles of desert harvester ants (Messor intermedius and Messor melancholicus) and scavenger ants (Cataglyphis nodus and Lepisiota semenovi) on plant communities were investigated in arid ecosystems of southeastern Iran. Two vegetation types were distinguished in the study area and the nest density of ant species was determined. Furthermore, plant composition and soil seed bank were estimated at different distances from the ant nests. Results showed that the density of M. intermedius and M. melancholicus nests was higher in dwarf shrub-shrub vegetation type and the density of C. nodus and L. semenovi nests was higher in dwarf shrub vegetation type. The harvester and scavenger ants had enhanced the seed bank to 55% and 70%, respectively. Therefore, the role of scavenger ants on the plant communities' seed bank was greater than that of harvester ants. Although the scavenger ants were more influential on the annuals and the invasive plant species, the radius impact of the harvester ants on the perennials was greater, i.e., a positive interaction existed between the perennial plants and the harvester ants. C. nodus and L. semenovi played an important role in enhancing the ecosystem's potential for restoration through establishment of pioneer species in early stage of succession. The activity of M. intermedius is crucial for the development and maintenance of climax plant communities in arid ecosystems through assisting the plant species' establishment in late stage of succession. It is essential to preserve the diversity of these key ant species for the maintenance and sustainability of shrubs in arid ecosystems.