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Livestock is one of major sources of greenhouse gas (GHG) emissions in China. Clarifying spatiotemporal characteristics of GHG emissions from livestock and exploring influencing factors can provide reference for grasping regional changes of GHG emission and formulate strategies of carbon reduction for livestock industry. However, existing literatures considered both spatial and temporal impacts and dynamic evolution trend of these factors seldomly. This paper used the life cycle assessment (LCA) method to estimate GHG emissions of livestock in 114 cities of the YRB from 2000 to 2021. On this basis, spatiotemporal heterogeneity of influencing factors was analyzed by using geographically and temporally weighted regression (GTWR) model. Finally, future evolution trend of GHG emissions from livestock was predicted by combining traditional and spatial Markov chain. Four main results were listed as follows. Firstly, GHG emission in the life cycle of livestock industry increased from 57.202 million tons (Mt) carbon dioxide equivalent (CO 2 e) in 2000 to 77.568 Mt CO 2 e in 2021. Secondly, structure of livestock industry, labor flow and mechanization were vital factors that led to increase of GHG emissions from livestock. Positive effects of labor flow and mechanization were increasing year by year, while negative effect of urbanization and positive effect of economic development were decreasing year by year. Markov chain analysis shown that probability of keeping high level of GHG emissions of livestock in the YRB unchanged were 96% (T = 1) and 90% (T = 5), and there also existed a Matthew effect. In addition, probability of level transfer of GHG emission in urban livestock was spatially dependent. Government should formulate strategies for livestock development and optimize low-carbon transformation of energy structure for livestock and poultry husbandry based on local conditions and key driving factors in the future. Meanwhile, boundaries of administrative divisions should be broken to promote reduction of GHG emissions in livestock comprehensively. • GHG emissions from livestock in cities of the YRB continued to rise from 2000 to 2021. • GHG emissions per unit of GDP of livestock shown a downward trend. • Analyzing parameter of factors from spatiotemporal aspect by using GTWR model. • Probability of GHG emission transfer in urban livestock was spatially dependent. [ABSTRACT FROM AUTHOR]

This paper explored the drought propagation phenomenon based on meteorological, hydrological, and agricultural aspects in the Yangtze River basin (YRB), China. To evaluate meteorological, hydrological, and agricultural droughts, this paper used three drought indices, standardized precipitation evapotranspiration index (SPEI), standardized runoff index (SRI), and standardized soil moisture index (SSMI), respectively. The community land model (CLM) in the YRB to generate the monthly evapotranspiration, soil moisture, runoff data, which are required for the estimation of drought index, were applied. Different mean durations (6-and 12-month) were used for drought estimation, and propagations of meteorological to hydrological and meteorological and agricultural droughts were investigated for different durations as SPEI6-SRI6, SPEI6-SSMI6, SPEI12-SRI12, SPEI12-SSMI12. The average drought propagation between 1950 and 2010 presented the highest autocorrelation and correlation with one-month lags in four combinations of drought indices in SPEI6-SRI6, SPEI6-SSMI6, SPEI12-SRI12, and SPEI12-SSMI12. Additionally, this paper estimated the optimal lags of SPEI-SRI and SPEI-SSMI drought propagations using mean 6-and 12-month lag times for six representative drought periods. Therefore, the propagation phenomenon of meteorological to hydrological and to agricultural droughts were confirmed in the YRB. • SPEI, SRI, and SSMI indices have been applied to the Yangtze River basin (YRB). • Propagation analysis of SPEI-SRI and SPEI-SSMI have extended to 1951–2010. • Mean 12-month duration shows clearer drought propagation than mean 6-month duration. • SPEI-SSMI presents 1–7 months propagation time. • SPEI-SRI presents 1–2 months propagation time. [ABSTRACT FROM AUTHOR]

Land cover change (LCC) is both a consequence and a cause of global environmental change. This paper attempts to construct a framework to reveal the driving mechanism and ecological effects of different ecological factors under LCC and to explore the ecological characteristics of future LCC. A rule-mining framework based on a land expansion analysis strategy (LEAS) in the patch-generating land use simulation (PLUS) model was used to analyze the drivers of LCC. Neighborhood analysis and ecological effect index were used to investigate multiple ecological effects of LCC. Remote sensing-based ecological indices (RSEI) and the PLUS and stepwise regression model were introduced to explore and predict the integrated ecological effect of LCC. Focusing on the Weihe River basin, study's main drivers of LCC were precipitation, temperature, elevation, population, water table depth, proximity to governments and motorways, GDP, and topsoil organic carbon were the main drivers of LCC. Change directionality were similar for the effects of greenness and biomass formation but opposite for summertime and wintertime temperature. In addition, the conversion of land cover types to cropland had the most significant integrated ecological effect, followed by forest, grassland-shrubland, and other types. The RSEI is predicted to rise to 0.77 in 2030, and the areas where the ecological quality grade will improve and decrease are concentrated on the east and west sides of Ziwuling Mountain, respectively. The findings of this study have practical significance for land management and ecological protection. • The PLUS Model is used to explore driving mechanism of land cover change (LCC). • Ecological effects of LCC are analyzed from multiple and integrated perspectives. • The integrated ecological effect of land cover types converted to cropland is the most significant. • The PLUS model with stepwise regression predicts a decreasing trend of RSEI in 2030. [ABSTRACT FROM AUTHOR]

Cities worldwide are facing a significant threat of stormwater hazards caused by the increase in extreme downpours and urbanization. Meso-level urban stormwater management focuses on alleviating the detrimental impacts of urban flooding and enhancing water resource utilization at the block or community scale, typically through 1) specific policies and management rules; 2) catchment-scale scenario simulation, optimization and evaluation; 3) the group of stormwater control measures implementation. It may effectively coordinate macro-level urban stormwater management planning and micro-level distributed stormwater control facilities. This study conducts a review of Urban Stormwater Management at Meso-level (USM-M) with a view to research publication trends, citation analysis, geographic spread and subject category, as well as content analysis, including temporal progression and research gaps. The Web of Science database and CiteSpace are used for the bibliometric analysis of 66 articles from 2006 to 2021. The results show that the number of USM-M topic articles generally has an upward trend over the years. Whilst the United States and China are leading research on this topic, the European countries have diverse local research and dense cooperation. Research foci have generally shifted from theoretical frameworks to multi-element subdivided topics and specific technical roadmaps. Moreover, the spatial layout optimization and multi-functional integration are, or will be, potential research directions in terms of enhancing stormwater utilization and co-benefits of USM-M. This systematic review concludes trends, challenges and potential approaches of USM-M, and aims to provide recommendations for researchers and policymakers on the development of a more advanced and comprehensive USM-M. • This paper aims to quantitatively and qualitatively review how Urban Stormwater Management at Meso-level (USM-M) is being studied and applied. • The question was "What are the trends, challenges and approaches of USM-M research?". • USM-M is applied at the catchment, block, community scale, and play a coordinator role between macro-level and micro-level. • Research focus has shifted from theoretical frameworks to subdivided topics and specific technical roadmaps. • Optimal spatial layout and multi-functional integration of USM-M implementation are potential directions. [ABSTRACT FROM AUTHOR]

Understanding the changes in hydrological process is a key subject for water resource management of a high-diversity watershed. In this paper, through an establishment of a SWAT-based model, the effects of climate change and its induced vegetation change on hydrological process were analyzed in the East River Basin. The model could well simulate the hydrological processes of the basin including surface runoff (SURQ), groundwater (GWQ), lateral flow (LATQ), total water yield (WYLD), actual evapotranspiration (ET), and groundwater recharge (PERC). Under the vegetation change induced by temperature increase, the effects of the vegetation change on hydrological process were larger than that of the temperature change. Under the vegetation change caused by the increase of temperature and precipitation, the vegetation change enhanced the effects of climate change on annual SURQ, LATQ, GWQ, WYLD, and PERC of the basin. Under spatial scale, when the temperature and precipitation changed simultaneously, the increase of precipitation could promote the increase of annual ET in sub-watersheds. Also, the annual SURQ, WYLD, GWQ and ET in western sub-watersheds were more sensitive to the cumulative changes of vegetation and climate. This work can provide useful information to decision makers in water resource management of watersheds. • A SWAT-based model was established for a multi-level simulation. • Response of hydrological process to a climate-driven vegetation change was explored. • Effect of climate and vegetation changes on hydrological process was quantified. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid method integrated unbiased grey model (UGM) and artificial neural network (ANN) into an interval two-stage fuzzy credibility-constrained programming (ITFCP) framework is proposed for water resources allocation of the Yalong River research area. Through the grey correlation analysis and the eXtreme Gradient Boosting (XGboost) algorithm, the economic and social indicators are related to the water demands of different water sectors in different regions can be obtained for building water demand prediction model. According to the unbiased grey prediction of the socio-economic development data of each region in the Yalong River Basin (YRB), water demand prediction models are constructed by using neural network. The establishment of a hybrid two-stage interval fuzzy credibility-constrained programming model can analyze the uncertainties existing in the process of water resources allocation. Taking 2020, 2025, and 2030 as the planning years, the developed model studies and reveals the system benefits at different credibility levels, the water shortage of each user in sub-regions and the water resources allocation situation to provide suggestion for managers to optimize the allocation of water resources. Compared to the previous methods, this integrated model can help decision-makers set management policies more sustainably and profitably. • A simulation-optimization method was developed. • The method represents a combination of unbiased grey model (UGM) and artificial neural network (ANN). • Interval two-stage fuzzy credibility-constrained programming was used as a general framework. • The developed method was applied to support water management in Yalong River Basin, China. [ABSTRACT FROM AUTHOR]

This paper explores how human disturbance and hydrologic elements affect the spatial distribution pattern of plant diversity in the watershed, taking Shamu watershed in the World Natural Heritage Site as a case study. Spatial analysis of multisource remote sensing and plant diversity plots data were conducted using linear mixed effects models and structural equation models. Results revealed that the distribution of plant diversity in the watershed is mainly affected by human disturbance. However, under similar human disturbance levels, hydrologic elements also affect the plant diversity within the watershed. The topographic undulation and surface runoff significantly promote plant diversity, while the river network density, the watershed shape factor, the river longitudinal gradient do not. The influence of topographic undulation is more obvious than that of runoff on plant diversity, but the effect of topographic undulation and runoff on plant diversity is getting weaker from upstream to downstream within the watershed. In addition, the impact of hydrologic elements on plant diversity is mainly regulated by environmental factors Pre and Tem. The findings clarify how human disturbance and hydrologic elements affect plant diversity distribution within the watershed, optimizing the conservation theory of plant diversity resources and scientifically guiding the region's sustainable development. • Human disturbance contributes most to plant diversity. • Surface runoff and topographic undulation promote plant diversity. • Precipitation and temperature regulate the hydrological impact on plant diversity. • Weaker restrictions of hydrologic elements on plant diversity in downstream. [ABSTRACT FROM AUTHOR]

The ecological compensation (EC) mechanism is an innovative institutional arrangement which can effectively realize the coordinated development of social-economic growth and ecological protection. The current research on the evaluation of the implementation effect of EC mechanism mainly focuses on its environmental performance, how the EC mechanism guides the economically underdeveloped areas in the upper reaches of the basin to embark on the road of high-quality economic development, especially the mechanism of how EC triggers the optimization and upgrading of industrial structure, it is a topic worthy of in-depth discussion. This study takes China's first cross-provincial horizontal EC mechanism pilot (Xin'an River Basin EC) as the research object and regards it as a quasi-natural experiment. This paper selects the annual panel data of the 11 cities involved from 2009 to 2019 and builds a DID model to study the mechanism of EC affecting industrial structure adjustment systematically. The results show that the EC mechanism mainly promotes the adjustment of the industrial structure in the pilot area through two paths, this is achieved by triggering the transfer of backward or highly polluting industries and promoting the upgrading of the industrial structure. At the same time, technological innovation plays a part intermediary role in the impact of EC to promote the upgrading of industrial structure. Further analysis found that the larger the funds of compensation input, the higher the assessment intensity, the better the effects are. Finally, this study puts forward relevant policy recommendations to further release the potential of the horizontal EC for the reference of decision-makers. • We evaluated the mechanism of ecological compensation (EC) on industrial structure. • EC affects the adjustment of industrial structure through industrial transfer and industrial upgrading. • Technology innovation plays a vital role in the process of EC mechanism guiding industrial upgrading. • The compensation amount and standard play a key role in the effectiveness of EC. [ABSTRACT FROM AUTHOR]