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Abstract Planting structure adjustment (PSA) affects agricultural water saving, and is an essential part of water-saving agricultural construction. This study introduced virtual water theory and innovatively constructed a model to assess the water-saving effects of PSA in Shiyang River Basin over the past 38 years, explore the relationship between planting structure and water saving, and clarify the most water-saving planting structure. The results showed that the sown area of economic crops consistently increased as food crop areas decreased in the four counties (districts) from 1980 to 2017. Being considered a “big water consumer”, wheat has lost its dominant position. The water requirements of major crops in the four counties and districts showed an increasing trend. The total area proportion of vegetables, wheat, corn, and oil-bearing crops (Abbreviated as TPVWCO) directly determined the water-saving amount. The lower the TPVWCO, the better the water-saving effect. Taking 1980 as the reference year, the most water-saving years in Gulang, Liangzhou, Yongchang, and Minqin were 2007, 1981, 2008, and 2005, respectively. Taking 2007 as the reference year, there were no water-saving years available after that due to the higher TPVWCO. Taking into account food security, ecological and economic benefits, it was recommended to control the TPVWCO at 40% in the Shiyang River Basin in the future. The land vacated should be planted with cotton in Minqin, while the land vacated in the other three counties should be planted with fruits. The research results would provide scientific basis for optimizing the planting structure and managing agricultural water resources in inland river basins in arid regions.

Drought propagation is a complex process, and understanding the propagation mechanisms of meteorological drought to soil drought is crucial for early warning, disaster prevention, and mitigation. This study focuses on eight tributaries in the upper reaches of the Shiyang River. Based on the Standardized Precipitation Index (SPI) and the Standardized Soil Moisture Index (SSMI), the Drought Propagation Intensity Index (DIP) and Copula function were applied to quantify the intensity and time of drought propagation from meteorological to soil drought and explored the drought propagation patterns at different temporal and spatial scales in these tributaries. Results showed that, in the 0–10 cm soil layer, the propagation intensity of meteorological drought to soil drought was peer-to-peer, with a propagation time of one month. In the middle (10–40 cm) and deep (40–100 cm) soil layers, propagation characteristics differed between the eastern and western tributaries. The western tributaries experienced stronger drought propagation intensity and shorter propagation times (2–4 months), while the eastern tributaries exhibited peer-to-peer propagation intensity with longer times (4–10 months). The large areas of forests and grasslands in the upper reaches of the Shiyang River contributed to strong land–atmosphere interactions, leading to peer-to-peer drought propagation intensity in the 0–10 cm soil layer. The eastern tributaries had extensive cultivated land, where irrigation during meteorological drought enhanced soil moisture, resulting in peer-to-peer propagation intensity in the middle (10–40 cm) and deep (40–100 cm) soil layers. In contrast, the western tributaries, with larger forest areas and widespread permafrost, experienced high water consumption and limited recharge in the 10–40 cm and 40–100 cm soil layers, leading to strong drought propagation.

Study region: Upper Shiyang River in the eastern Qilian Mountains, China. Study focus: Quantifying the impacts of anthropogenic and climate change on wet and dry hydrological variability was done by improving the Slope Change Ratio of Cumulative Quantities (ISCRCQ) method. New hydrological insights for the region: The scientific method is critical to quantify the driving factors of dry-wet hydrological changes. In this study, the slope change ratio of cumulative quantity (SCRCQ) method was improved to quantify the impacts of human activities and climate change on dry-wet hydrological changes. The results show a hydrological aridification trend at an annual scale from 1961 to 2016 in the upper reaches of the Shiyang River. However, the dry-wet hydrological change trends of the six tributaries differed: the hydrological humidification of the four western tributaries was apparent, while the remaining tributaries showed hydrological aridification. The influences of human activities and climate change on dry-wet hydrological changes were also evidently distinct in the different tributaries. Changing in climate is a vital factor triggering the dry-wet hydrological changes in the western tributaries, while human activities have completely changed the direction of the dry-wet hydrological changes and intensified the hydrological aridification in the eastern tributaries. Human activities have resulted in an increase both in the frequency of droughts and in the risk of socio-economic droughts. Thus, human activities in the region of eastern tributaries should be controlled within reasonable limits.

Drought is a common hydrometeorological phenomenon and a pervasive global hazard. To monitor global drought-wetness conditions comprehensively and promptly, this research proposed a spatial distance drought index (SDDI) which was constructed by four drought variables based on multisource remote sensing (RS) data, including the normalized difference vegetation index (NDVI), land surface temperature (LST), soil moisture (SM), and precipitation (P), using the spatial distance model (SDM). The results showed that the consistent area of SDDI with the 1-month and 3-month standardized precipitation-evapotranspiration index (SPEI1 and SPEI3), and the self-calibrating Palmer drought severity index (scPSDI) accounted for 85.5%, 87.3%, and 85.1% of the global land surface area, respectively, indicating that the index can be used to monitor global drought-wetness conditions. Over the past two decades (2001–2020), a discernible spatial distribution pattern has emerged in global drought-wetness conditions. This pattern was characterized by the extreme drought mainly distributed deep within the continent, surrounded by expanding moderate drought, mild drought, and no drought areas. On the annual scale, the global drought-wetness conditions exhibited an upward trend, while on the seasonal and monthly scales, it fluctuated steadily within a certain cycle. Through this research, we found that the sensitive areas of drought-wetness conditions were mainly found on the east coast of Australia, the Indus Basin of the Indian Peninsula, the Victoria and Katanga Plateau areas of Africa, the Mississippi River Basin of North America, the eastern part of the Brazilian Plateau and the Pampas Plateau of South America.

Vegetation is one of the most important indicators of climate change, as it can show regional change in the environment. Vegetation health is affected by various factors, including drought, which has cumulative and time-lag effects on vegetation response. However, the cumulative and time-lag effects of drought on different terrestrial vegetation in China are still unclear. To address this issue, this study examined the cumulative and time-lag effects of drought on vegetation from 2001 to 2020 using the Standardized Precipitation Evapotranspiration Index (SPEI) in the Global SPEI database and the Normalized Difference Vegetation Index (NDVI) in MOD13A3. Based on Sen-Median trend analysis and the Mann–Kendall test, the change trend and significance of the NDVI from 2001 to 2020 were explored. The Pearson correlation coefficient was used to analyze the correlation between the SPEI and NDVI at each cumulative scale and time-lag scale and to further analyze the cumulative and time-lag effects of drought on vegetation. The results show the following: (1) The NDVI value increased at a rate of 0.019/10 years, and the increased area of the NDVI accounted for 80.53% of mainland China, with a spatial trend of low values in the west and high values in the east. (2) The average SPEI cumulative time scale most relevant to the NDVI was 7.3 months, and the cumulative effect demonstrated a high correlation at the scale of 9–12 months and revealed different distributions in different areas. The cumulative effect was widely distributed at the 9-month scale, followed by the 12-month scale. The correlation coefficients of cumulative effects between the SPEI and NDVI for cropland, woodland and grassland peaked at 9 months. (3) The average SPEI time-lag scale for the NDVI was 6.9 months, and the time-lag effect had the highest correlation coefficient at the 7-month scale. The strongest time-lag effect for cropland and grassland was seen at 7 months, while the strongest time-lag effect for woodland was seen at 6 months. Woodland had a lower time-lag effect than grassland at different scales. The research results are significant for their use in aiding the scientific response to drought disasters and making decisions for climate change precautions.

Scientifically evaluating the influence of ecological restoration projects on the water conservation function (WCF) of regional ecosystems is the foundation for formulating regional ecological restoration policies and optimizing and adjusting ecological restoration projects. In this paper, we considered fully the runoff generation and confluence process in the Qilian Mountains with the actual situation of the basin and re-rated the parameter Z to improve the simulation accuracy of InVEST model. On this basis, the impact of ecological restoration project on the WCF in the upper reaches of Shiyang River Basin (SRB) in the eastern part of Qilian Mountains was quantified. The results showed that, on the whole, the water conservation depth (WCD) of forest land was the largest (138.5 mm) and that of cultivated land was the smallest (24.78 mm), while the water conservation coefficient of forest land was also the largest (93.36%) and that of unused land was the smallest (16.67%). From 1986 to 2018, the WCD showed an increasing trend in the upper reaches of SRB, among them, the WCD in the western tributaries increased faster than that in the eastern tributaries from 1986 to 2000. The significantly increased areas were mainly distributed in the middle reaches of the western tributaries and the river source areas of the eastern tributaries, while the significantly decreased areas were mainly distributed in the river source areas of the western tributaries and the cultivated land expansion area in the middle reaches of the eastern tributaries. From 2000 to 2018, the WCD of the eastern tributaries increased more than that of the western tributaries. The significantly increased areas were mainly distributed in the four eastern tributaries, and the significantly decreased areas were scattered in the middle and lower reaches of each tributary. From 1986 to 2000, the overall influence of land use change on the increase in WCD was negative, while the influence of climate and land use change on the increase in water conservation were both positive from 2000 to 2018. The influence of land use change on WCD was different in different tributaries. Among them, that of the western tributaries (except the Dongda River) was positive in two different periods, while that of the eastern tributaries (except the Xiying River) was changed from negative to positive. The implementation of ecological restoration project was one of the main reasons for the improvement of WCF in Qilian Mountains from 2000 to 2018, with a contribution of 9.04%. In the future, the protection and restoration of decreased areas of WCF should be strengthened, and the Z value determined in this paper is expected to be applied in the arid inland river basins of northwest China.

The impact of the land use landscape pattern on river hydrochemistry has significant scale effects. It is the premise and foundation of landscape optimization and the conservation of water resources to accurately identify the core scale of the landscape pattern impacting on river hydrochemistry. Taking Binggou River Basin in the source region of Shiyang River Basin as the study area, this paper selected the three spatial scales of catchment area, buffer zone, and riparian zone, and the relationships between land use types and landscape indices and river hydrochemical characteristics were analyzed at different spatio-temporal scales using redundancy analysis. The results showed that the hydrochemistry characteristics of Binggou River Basin had strong temporal variability, and the rainy season was the key period when the land use landscape pattern affected the river hydrochemistry. The sub-watershed and riparian scales were the core scales of influence of the landscape pattern on river hydrochemistry in Binggou River Basin. In particular, the landscape pattern index contributed the most to the river hydrochemistry at the sub-watershed scale on the whole, which was the core scale affecting river hydrochemistry. The “source” or “sink” functions of the same land use type also changed as the scale changed. Forest land showed weak “source” effect at the sub-watered scale, but a strong interception effect on the soil erosion process at the riparian scale, which is a typical “sink” landscape.

Ecosystems in arid areas are fragile and are easily disturbed by various natural and human factors. The purpose of this study is to clarify the hydrological and ecological processes of arid inland river basins in Eurasia and provide a scientific basis for their sustainable development. From 2015 to 2020, we took the Shiyang River Basin, which has the highest utilization rate of water resources and the most prominent contradiction of water use, as a typical demonstration basin to establish and improve the isotope hydrology observation system. The data in the observation system are classified by water type (precipitation, river water, lake water, groundwater, soil water, and plant water). Six observation systems with stable isotopes as the main observation elements, including river source region, oasis region, reservoir channel system region, oasis farmland region, ecological engineering construction region, and salinization process region, have been built, and meteorological and hydrological data have also been collected. We will gradually improve the various observation systems, increase the data of observation sites, and update the data set yearly. We can use these data to carry out hydrometeorological and ecological scientific research and provide a scientific basis for water resources utilization and ecological environment restoration in arid areas. The datasets are available at https://data.mendeley.com/datasets/d5kzm92nn3/1 (Zhu et al., 2021). [ABSTRACT FROM AUTHOR]