Search Results (5)

The Qilian Mountains (QMs) act as the “water tower” of the Hexi Corridors, playing an important role in the regional ecosystem security and economic development. Therefore, it is of great significance to understand the spatiotemporal characteristics of precipitation in the QMs. This study evaluated the performance of 21 models of phase 6 of the Coupled Model Intercomparison Project (CMIP6) from 1959 to 1988 based on ERA5 and in situ datasets. In addition, the precipitation changing trend from 2015 to 2100 was projected according to four shared socioeconomic pathways (SSPs): namely, SSP126, SSP245, SSP370, and SSP585. The results have shown the following: (1) all CMIP6 models could reflect the same precipitation changing trend, based on the observed datasets (−2.01 mm·10a⁻¹), which was slightly lower than that of ERA5 (2.82 mm·10a⁻¹). Multi-mode ensemble averaging (MME) showed that the projected precipitation-change trend of the four scenarios was 5.73, 9.15, 12.23, and 16.14 mm·10a⁻¹, respectively. (2) The MME and ERA5 showed the same precipitation spatial pattern. Also, during the period 1959–1988, the MME in spring, summer, autumn and winter was 130.07, 224.62, 95.96, and 29.07 mm, respectively, and that of ERA5 was 98.57, 280.77, 96.85, and 22.64 mm, respectively. The largest precipitation difference in summer was because of strong convection and variable circulation. (3) From 2015 to 2100, the snow-to-rain ratio was between 0.1 and 1.1, and the snow-to-rain ratio climate tendency rate was concentrated in the range of −10~0.1 mm·10a⁻¹. Both of these passed the significance test (p < 0.05). The projected rainfall of all four SSPs all showed an increasing trend with values of 6.20, 11.31, 5.64, and 20.41 mm·10a⁻¹, respectively. The snowfall of the four SSPs all showed a decreasing trend with values of 0.42, 2.18, 3.34, and 4.17 mm·10a⁻¹, respectively. Full article

The Yellow River Water Allocation Management Method was put into place in 1998 to decrease the Yellow River water amount used by upstream areas and provide more water to downstream regions. Rainfall and Yellow River’s infiltration are the main groundwater supply in the downstream area of Yellow River. The groundwater table in the downstream area has continued to decrease since 1979, and the extracted groundwater for irrigation is the main reason for this. Whether the increased river water amount could improve the decreased groundwater level is uncertain. Therefore, we used remote sensing images, groundwater level observations, meteorological data, and unit mean irrigation rate to identify the irrigation events for river water and groundwater, estimate the annual river water irrigation amount and groundwater irrigation amount, and analyze the effects of river water allocation on the groundwater table. Our analysis showed that the area of double-irrigated farmland (farmland that could be irrigated by both groundwater and river water) tended to decrease, while well-irrigated farmland area (farmland that could only be irrigated by groundwater) remained unchanged during the study period. The number of annual irrigation events tended to increase, and the usage of river water remained consistent throughout this period. The increased number of well irrigation events caused annual groundwater usage for irrigation to increase. However, the usage of river water for irrigation remained stable. The increased usage of groundwater for irrigation led the groundwater table to continually decrease from 1998 to 2019. This indicates that there are shortcomings to the current water allocation policy, and that further improvements are needed to prevent continued decrease in groundwater levels. Full article

With the large-scale development of urbanization in the world, phenomena such as the unbalanced allocation of various elements of the rural regional system, as well as the decline of the economic and social structure and functions in the process of urban and rural economic and social transformation and development in China, have endangered the healthy development of rural areas. The “hollowing” of rural areas is becoming more and more intense, and the governance of hollow villages has become a key link to stimulating the vitality of rural development and realizing the coordinated development of urban and rural areas. Taking a typical hollow village in Fangsi Town, Yucheng City, Shandong Province, China as an example, through the recognition method of hollow villages mode, the study adopted the in-depth interviews and questionnaires to obtain governance of hollow villages. Moreover, this study uses the actor–network theory to discuss the governance model mechanism and policy response of hollow villages, extract the applicable conditions of different hollow village governance modes, and provide the promotion of the hollow village governance mechanism. Our findings show that: (1) the governance modes of hollow villages are diverse. Under certain geographical conditions, the governance of hollow villages shows the relocation and merger–urban–rural integration mode, village integration-scale operation mode, village intensive-idle land revitalization mode, and original site optimization–sightseeing tourism development mode, along with other types. In the process of promotion and use, appropriate adjustments should be made in combination with differences and changes in system conditions, and the accurate governance of villages should be carried out. (2) The governance process of hollow villages is dynamic. The governance of hollow villages represents a heterogeneous network of actors led by key actors, which mainly realizes changes in the rural material space. With the change of development goals of the hollow village, the network of actors has been readjusted around the new OPP, and the role of the actors has changed, correspondingly showing a transition from the governance of the hollow village to the optimized development, thus further realizing the transformation of the hollow village. Full article

The downstream plain of the Yellow River is experiencing some of the most severe groundwater depletion in China. Although the Chinese government has issued policies to ensure that the Yellow River can provide enough irrigation waters for this region, groundwater levels continue to decrease. Yucheng City was selected as a case study. A new method was designed to classify the cropland into various irrigated cropland. Subsequently, we analyzed data regarding these irrigated-cropland categories, irrigation norms, and the minimum amount of irrigation water being applied to cropland. The results showed that 91.5% of farmland can be classified as double irrigated (by both canal/river and well water), while 8.5% of farmland can be classified as well irrigated. During the irrigation season, the sediments brought in by the river have blocked portions of the canals. This has led to 23% of the double-irrigated cropland being irrigated by groundwater, and it is thus a main factor causing reductions in groundwater supply. These blocked canals should be dredged by local governments to mitigate local groundwater depletion. The method for classifying irrigated cropland from high-resolution images is valid and it can be used in other irrigated areas with a declining groundwater table for the sustainable use of groundwater resources. Full article

Yucheng City is located in northwestern Shandong Province, China, and is situated on the Huang-Huai-Hai Plain, the largest alluvial plain in China. In this study, 86 surface soil samples were collected in Yucheng City and analyzed for cation exchange capacity (CEC), soil organic matter (SOM), pH, available phosphorus (avail. P), phosphorus (P), aluminum (Al), and iron (Fe). These soils were also analyzed for ‘total’ chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), mercury (Hg), cadmium (Cd), and lead (Pb), together with 92 wheat samples and 37 corn samples. There was no obvious heavy metal contamination in the soil and irrigation water. But the long-term accumulation of heavy metals in soil has lead to an increase of Ni, As, Hg and Pb concentrations in some of wheat and corn samples and Cd in wheat samples. Because of the numerous sources of soil heavy metals and the lower level of heavy metal in irrigation water, there is no significant relation between soil heavy metal concentrations and irrigation water concentrations. Cr, Ni were mainly from the indigenous clay minerals according to multivariate analysis. Little contribution to soil heavy metal contents from agricultural fertilizer use was found and the local anomalies of As, Cd, Hg, Pb in wheat and corn grain are attributed to the interactive effects of irrigation and fertilizer used. Aerial Hg, however may also be the source of Hg for soil, wheat and corn. Full article