The bottlenecks in enhancing regional green development are resource shortages, environmental pollution, and ecological degradation. Taking the Dongliao River Basin (DRB) of Jilin Province as an example, this study explored green development from a multidimensional perspective. Based on the dimension evaluation results of REECC (resources, environment, and ecological carrying capacity), PLES (production–living–ecological space), and ER (ecological redline), the coupling coordination degree model and spatial autocorrelation model were constructed to explore the coupling coordination degree and spatial distribution of green development. The results showed that REECC had significant spatial differences, and the REECC index showed an increasing trend from northwest to southeast. In 2018, the overall level of green development in the DRB has obvious spatial dependence, but there were spatial differences, with a more obvious polarization from northwest to southeast. The spatial distribution of the coupling degree and coupling coordination degree is roughly the same, and there is a clustering distribution. The conclusions have practical significance for future environmental protection and economic production in the DRB.
The Songliao Plain is the largest maize (Zea mays L.) cropland area in China and, thus, is most influenced by water stress. To mitigate the adverse impact of water stress on maize yield and quality, various agricultural irrigation strategies have been implemented. Based on land surface temperature and an enhanced vegetation index, this study constructed the temperature vegetation dryness index (TVDI) and combined the Hurst index and Sen trend to analyze the spatiotemporal characteristics of drought and waterlogging. From the correlation between TVDI and gross primary productivity, the weight coefficients of different growth cycles of maize were derived to determine the drought and waterlogging stresses on maize in Songliao Plain for 2000–2020. The drought hazard on the western side of Songliao Plain was high in the west and low in the east, whereas the waterlogging hazard was high in the east. Waterlogging likely persisted according to the spatiotemporal trends and patterns of drought and waterlogging. During the second growth cycle, maize was most severely affected by water stress. There was a spatial heterogeneity in the severity of the hazards and the stress degree of maize. For the reason that precipitation in the study area was concentrated between mid-late July and early August, maize was susceptible to drought stress during the first two growth stages. Irrigation concentrated in the early and middle stages of maize growth and development in the western part of the Songliao Plain reduced the drought stress-induced damage. Spatiotemporally-detected drought and waterlogging couplings and hazards for maize in the Songliao Plain for 2000–2020 provide actionable insights into the prevention and mitigation of such disasters and the implementation of water-saving irrigation practices at the regional scale.
Global warming has altered the uniformity of precipitation in Inner Mongolia, China, eventually leading to droughts. Further studies are necessary to determine the relationship between the concentration of precipitation and drought.Therefore, we assessed the spatial and temporal characteristics of the precipitation concentration degree (PCD), precipitation concentration period (PCP), and standardized precipitation evapotranspiration index (SPEI) in Inner Mongolia in the past and predict changes in the three indices under different scenarios in the future (2018-2100) using measured model data and Sen's slope and Mann-Kendall trend analysis. The correlation between PCD/PCP and SPEI was explored using Pearson's correlation coefficient. The results showed that the spatial distribution of PCD and PCP in Inner Mongolia exhibited significant east-west differences. The PCD values were 0.42-0.76, with high-value areas in the east. PCD showed a decreasing trend in both historical and future scenarios, indicating an even distribution of precipitation and an increased risk of drought. The PCP values were 190 -226 , with high-value areas mainly in the western region. Except for in the Representative Concentration Pathways RCP4.5 and RCP8.5, PCP values in the historical and RCP2.6 scenarios showed a decreasing trend, indicating an earlier onset of maximum precipitation. SPEI values ranged between −1.23 and 1.17, with all future scenarios showing a decreasing trend and the historical scenario showing an increasing trend. The stations with positive correlation between SPEI and PCD accounted for 89.13, 67.39, 91.3, and 95.65% of Inner Mongolia, while those with positive correlation with PCP accounted for 43.47, 60.87, 56.52, and 4.35%, indicating that the correlation between drought variation and precipitation concentration is strong. These results can help reduce and prevent droughts and floods caused by changes in precipitation patterns and provide a basis for the rational use of water resources for preventing droughts and making relief decisions.
Hydrological connectivity affects the material cycling and energy transfer of ecosystems and is an important indicator for assessing the function of aquatic ecosystems. Therefore, clarification of hydrologic connectivity and its optimization methods is essential for basin water resources management and other problems; however, most of the current research is focused on intermittently flooded areas, especially in terms of optimization, and on hydrological regulation within mature water structures, while research on hydrological connectivity in dry, low rainfall plain areas remains scarce. Based on the graph and binary water cycle theories, this study assessed and hierarchically optimized the structural hydrological connectivity of the Dongliao River Basin (DRB), integrating artificial and natural connectivity, and explored the hydrological connectivity optimization method in the arid plain region at the basin scale to increase connectivity pathways. The spatial analysis and evaluation of hydrological connectivity was also carried out based on the results of the hierarchical optimization, and provided three scenarios for the construction of hydrological connectivity projects in the basin. The hierarchical optimization yielded a total of 230 new water connectivity paths, and the overall hydrological connectivity increased from 5.07 to 7.64. Our results suggest a large spatial correlation in hydrological flow obstruction in the DRB. The center of gravity of circulation obstruction shifted to the south after optimization for different levels of connectivity. With the increase in the optimization level of hydrological connectivity, the national Moran index rose and then fell. The magnitude of the increase in hydrological connectivity effects varied at different optimization levels, and there were sudden points’ increase points. From an application point of view, Scenario 1 is necessary and the most cost effective is Scenario 2, which provides a scientific basis for guiding the construction of future ecological projects in the DRB.
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