River Basin Development Research Articles

Assessing the effects of topographic gradients on landscape patterns: The study case of Tingjiang river basin, China

With the progress of urbanization, the natural geographical characteristics of different river basins have also undergone tremendous changes, and bring many environmental and social issues. It is of great significance to the sustainable development of river basins to reveal the relationship between topographic and landscape patterns. Therefore, we selected Tingjiang river basin, utilizing remote sensing images from 1991, 2004, and 2017, as well as the digital elevation model (DEM) data, we computed a topographic classification system consisting of four levels (Low level, Low-medium level, Medium-high level, High level). This approach enables us to study the gradient impact of topography and investigate the mechanism influencing the landscape pattern. The results show: (1) Low-medium and medium-high topographic levels are dominant in the research sites, accounting 49.35% and 38.47%, respectively. (2) Bare land showed a significant decrease while construction, cultivated, and forest land increased from 1991 to 2017. (3) Forest land is mainly concentrated in the middle-high and high-topographic levels whereas construction land, cultivated land, water area and bare land are mainly concentrated in the middle-low and low-topographic level. (4) The landscape pattern significantly varies with the topographic gradient, where the conversion to construction land is widespread in the low-topographic area, while alternation between cultivated land and forest land mainly occurs in the medium-low and medium-high topographic areas. Consequently, these findings provide insights into the impact of topography on river basin landscape pattern, which could guide sustainable development in the future.

Spatio-temporal evolution characteristics of eco-efficiency in the Yellow River Basin of China based on the super-efficient SBM model.

It is of great significance to study the trends and internal differences of eco-efficiency in the Yellow River Basin for ecological protection and high-quality development of the Yellow River Basin. According to the characteristics of the Yellow River Basin in China, the eco-efficiency evaluation system was constructed, and the super-efficiency slack-based measure (SBM) model and the super-efficiency SBM model of undesired output were used to calculate the eco-efficiency levels of provinces in the Yellow River Basin from 2005 to 2020, and the variation trend and internal differences were analyzed. The results show that when only the expected output was considered, the eco-efficiency of the Yellow River Basin as a whole and each province showed a fluctuating upward trend, but there were obvious differences. Qinghai Province, Sichuan Province, and Ningxia Autonomous Region had high eco-efficiency, while Shaanxi Province, Shanxi Province, and Inner Mongolia Autonomous Region had low eco-efficiency. Compared with only considering the expected outputs, eco-efficiency of Qinghai Province had improved significantly when considering non-expected outputs. The eco-efficiency of Shandong Province and Henan Province had improved significantly after 2016, while the eco-efficiency of the two provinces had decreased significantly before 2016. The eco-efficiency of Shaanxi, Shanxi, Inner Mongolia, Ningxia, and Gansu had declined to varying degrees. Finally, the reasons for the differences in eco-efficiency in various provinces in the Yellow River Basin were analyzed, and suggestions for improving the eco-efficiency of the Yellow River Basin were put forward.

Comprehensive evaluation and stability analysis of ecosystem quality of Yellow River Basin during 1980–2019

AbstractQuality and stability are the basic characteristics of ecosystems, reflecting their structure, process, functional integrity, ability to resist disturbance, self‐regulation, and dynamic balance. The quantitative description of ecosystem quality and stability is an indispensable and important task to promote the ecological protection and high‐quality development of the Yellow River Basin as a major national strategy. In this study, an index evaluation system was constructed from the perspective of system governance, considering the special characteristics of the Yellow River Basin, and an entropy weight model was used to establish a multi‐indicator long time series ecosystem quality evaluation index (EQI) to quantitatively describe the ecological quality changes in the Yellow River Basin over 40 years. The dissipative structure theory and Brussels apparatus model were used to establish quantitative indicators and methods, and provide ideas for the study of ecosystem homeostasis transformation in the Yellow River basin. This study found that: (1) the average EQI value of the Yellow River Basin ecosystem for 40 years was 63.96, the maximum and minimum values were 69.65 and 59.45, respectively; the overall quality showed an oscillating trend of improvement, with an annual increase of 0.03, and the spatial distribution was better in the downstream than in the midstream, and in the midstream than in the upstream; (2) The key factors influencing the system changed gradually from the total water consumption and total annual precipitation in the basin in the early stage to the average income of residents in the last 10 years. (3) The system steady‐state transition force values from 1980 to 2019 were all <0, the steady‐state conversion force of the Yellow River Basin ecosystem was low, but the overall trend was oscillating upward, and the overall trend was getting closer to the critical condition of steady‐state conversion.

Preface

Preface

Monitoring Surface Water Area Changes in the Aral Sea Basin Using the Google Earth Engine Cloud Platform

The surface water area and types in the Aral Sea Basin (ASB) have undergone extensive changes due to the impacts of climate change and anthropogenic activities. This study explores the changes in the surface water area in the ASB based on the Google Earth Engine cloud platform. Then, we integrate multi-source data to identify 1559 lakes and 196 reservoirs from the Joint Research Centre Global Surface Water (JRC GSW) dataset. Our results indicate that the lake area (34,999.61 km2) is about 10 times that of the reservoir area (3879.08 km2) in the ASB. The total area of surface water in the ASB decreased by 23,194.35 km2 or 34.58% from 1992 to 2020. Specifically, the areas of permanent water shrunk at a rate of 1278.6 km2/year, while the areas of seasonal water increased at a rate of 522.5 km2/year. The proportion of lakes and reservoirs in the total surface water has decreased from 79.33% (during 1992–2000) to 75.21% (during 2000–2010) to 63.94% (during 2010–2020). The water that should have flowed into the Aral Sea to maintain its permanent water may have been converted into two parts. Part of it might continue to be permanent water but show up in other regions, while part of it might convert to seasonal water (especially in the Aral Sea itself and the ASB plain area). Our study bridges the limitations of previous studies that have ignored seasonal water change and builds a water area list for 1755 lakes/reservoirs (≥0.1 km2) for the first time. The results can serve as important knowledge for water resource management and sustainable river basin development in ASB.

Analysis of the implementation effects of ecological restoration projects based on carbon storage and eco-environmental quality: A case study of the Yellow River Delta, China

As an important means to address global climate change and land-use/land-cover (LULC) change, ecological restoration projects (ERPs) have a large effect on carbon storage functions and eco-environmental quality. However, the various ERPs carried out in the Yellow River Delta region have important implications for ecological security strategies in China. Therefore, based on land-use data and remote sensing image data, with the help of ArcGIS and Google Earth Engine (GEE) platforms, this study uses the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, an improved remote sensing ecological index (RSEI) model and other methods to deeply examine the evolutionary trends of eco-environmental quality and carbon storage during the implementation of ERPs in the Yellow River Delta and selects key implementation areas for in-depth analysis to determine the implementation effects of ERPs. Our findings suggested that the RSEI and carbon storage levels in the study area had opposite evolutionary trends from 2001 to 2020. Among them, the RSEI showed a fluctuating upwards trend (0.4461 (2001) and 0.5185 (2020)), while the total carbon stock showed a fluctuating downwards trend (30.67 Tg (2001) and 26.40 Tg (2020)). However, from 2015 to 2020, the RSEI and carbon storage were at a relatively stable level, which indirectly indicated that the ERPs carried out during the period from 2015 to 2020 had achieved a good comprehensive implementation effect. In addition, the areas with better improvement effects from 2015 to 2020 were primarily located in the mouth of the Yellow River Delta (Areas C and D), and their RSEI and the total carbon stock showed a certain upwards trend. This research can promote the formulation of the management strategy of ERPs in the Yellow River Delta, which is of tremendous importance to the ecological environmental preservation and high-quality development of the Yellow River Basin.

Modern Concepts on the Origin and Distribution of Acipenserids (Acipenseridae)

The current data on the place and time of origin of Acipenseriformes and the family Acipenseridae, as well as on their distribution in connection with the history of the development of sea and river basins, are summarized. The supposed areas of the initial radiation of Acipenseriformes and their long-term habitation were in eastern Laurasia on a part of the modern Chita Region, Eastern and Central Mongolia, and northern and northeastern China. The eastern part of Asia should also be considered the place of origin of the family Acipenseridae. The widespread distribution of Acipenseriformes was facilitated mainly by the formation of diadromous forms from primarily freshwater species, the origin of which is associated with multiple transgressions and regressions of the ocean. Modern potamodromous acipenserids were probably formed as a result of the return of anadromous forms to living in fresh water; i.e., they are secondarily freshwater species.

Spatial and temporal dynamics of large natural lake areas and shoreline morphology in the Yellow River Basin.

Given their important roles in the regulation and storage functions for river flow and in the regional ecological environment and ecosystem services, natural lakes are essential for the ecological protection and high-quality development of the Yellow River Basin. We used the Landsat TM/OLI remote sensing data to analyze the area changes of Dongping Lake, Gyaring Lake, and Ngoring Lake, three representative large natural lakes in the Yellow River Basin from 1990 to 2020. We used the landscape ecology approach to study the morphological characteristics of lake shoreline and shoreland changes and the relationship between the landscape indices. The results showed that the main areas of Gyaring Lake and Ngoring Lake were mainly in the trend of expansion, while the main area of Dongping Lake significantly reduced during 1990-2000 and 2010-2020. The changes in the area of lake all occurred mainly near the lake inlet of the river. The shoreline morphology of Dongping Lake was more complex, with the fragmentation and aggregation of shoreland landscape significantly changed. The circularity ratio of Gyaring Lake gradually decreased with the expansion of the lake area, and the number of patches in its shoreland changed significantly. The fractal dimension index-mean of the shoreland of Ngoring Lake was relatively high, the complexity of its shoreline landscape was stronger, and the number of patches had increased significantly from 2000 to 2010. Meanwhile, there was a significant correlation between certain lake shoreline (shoreland) landscape indices. The changes in circularity ratio and shoreline development coefficient caused changes in the patch density of shoreland.

Evaluation and Analysis of Development Status of Yellow River Beach Area Based on Multi-Source Data and Coordination Degree Model

The Yellow River beach area is the basic component of the Yellow River Basin. Promoting the comprehensive improvement and high-quality development of the Yellow River beach area is an important guarantee of the long-term stability of the Yellow River and an important part of promoting the high-quality development and ecological protection of the Yellow River Basin. In this paper, four new indexes (flood risk intensity index, accessibility index, biological abundance index, and remote sensing ecological index) were extracted from geospatial data and remote sensing images, and a quantitative evaluation model (Ecology-Economy -Society-Flood, EESF) for the development of the Yellow River beach area were constructed based on social statistics, such as flood control and control in the beach area. The coordinated development level of the Yellow River beach area was evaluated by combining the “CRITIC–entropy weight method” and “‘single index quantification–multi-index synthesis–multi-criteria integration’ (SMI-P)—coordination degree model” methods. The spatial autocorrelation model was used to analyze the spatial distribution characteristics of the coordinated development level, and the global sensitivity and uncertainty analysis (GSUA) was carried out for the sensitivity and uncertainty of the parameters. Taking the Yellow River beach area in Shandong Province in 2009 and 2019 as the study object, the research results showed that during this period, the coordinated development level of the Yellow River beach area in Shandong Province showed a gradual upward trend, from 0.344 to 0.580, reaching a basic coordinated state; the overall coordinated development level of the beach area showed significant autocorrelation and small spatial heterogeneity. Grain production was the most sensitive parameter in the coordinated development model of the beach area. The beach area should rationally develop and utilize agricultural resources and promote the integration of ecological industries.

Optimization of a multipurpose river basin in anambra state, Nigeria

In this study, the multipurpose objective of development in the Anambra River basin was examined. The study's goals are to determine the net benefits of the various objectives under each purpose currently carried out by the Anambra River Basin, to identify the best way to achieve the goals, and to show, through logical and mathematical reasoning, how money could be allocated to the various goals of a dam project in Anambra State effectively. Economic Efficiency (EE), Regional Economic Redistribution (RER), Social Well-Being (SW), Youth Empowerment (YE), and Environmental Quality Improvement are the objectives taken into account in the study (EQI). The optimization problem in the multi-purpose-objective development of the Anambra State river basin was solved utilizing the multi-start optimization method. The study showed that the basin would achieve enormous financial benefits if it used its N15.0 billion strategic development budget over four years for various purposes as illustrated. The results showed that the following allocation of the five purposes should be optimized simultaneously for an N15.0 billion four-year strategic development fund: EE should receive N0.762 billion, RER should receive N0.594 billion, SW should receive N0.649 billion, YE should receive N0.683 billion, and environmental quality improvement should receive N4.768 billion. It was found that Environmental Quality Improvement was allocated the higher amount while Regional Economic Redistribution was allocated the least amount for the development. The study's findings recommended that the management of the basin stop the practice of allocating funds to various uses at their discretion, which has led to significant oversight and the improper distribution of scarce resources. As a result, every fund distribution must be justified using logic and mathematics. To increase the accuracy of the data, the Anambra State River Basin Development Authorities must intensify record-keeping activities.

Spatial-Temporal Evolution Patterns and Influencing Factors of Hotels in Yellow River Basin from 2012 to 2022

Governmental attention towards the high-quality development of the Yellow River basin has brought new development opportunities for the hotel industry. This study aims to reveal the spatial-temporal evolution patterns and influencing factors of hotels in the Yellow River Basin from 2012 to 2022, based on economic, social, and physical geographic data of 190,000 hotels in the Yellow River flowing. With the help of a GIS technology system, the spatial-temporal evolution patterns of all hotels, star hotels, and ordinary hotels were explored, respectively. Then, the significant influencing factors of these patterns were revealed by using geographic detector and Person correlation analysis. The following conclusions were drawn: (1) the overall scale of the hotel industry in the Yellow River Basin expanded year by year, achieving rapid growth from 2016, and fluctuating around 2020 due to the impact of the novel coronavirus epidemic; the overall spatial distribution had significant regional differences, showing the structural characteristics of “southeast more, northwest less”; (2) there was a great difference in the degree of spatial autocorrelation agglomeration among prefecture-level cities, and the degree of agglomeration of both the hotel industry as a whole and general hotels decreased year by year, showing a random distribution in 2022; star hotels were always distributed randomly. Additionally, a strong synergistic correlation was shown between the number of ordinary hotels and the number of star hotels in local space; (3) overall, the development of the hotel industry was significantly affected by seven factors: structural force, macro force, ecological force, internal power, consumption power, intermediary power, and external power. There were differences in the forces acting on different types of hotels, which gives a pattern recognition in-depth.

River Basin Development for Water and Food Security

Irrigation and DrainageEarly View ICID River Basin Development for Water and Food Security Ashwin B. Pandya, Ashwin B. PandyaSearch for more papers by this authorPrachi Sharma, Prachi SharmaSearch for more papers by this author Ashwin B. Pandya, Ashwin B. PandyaSearch for more papers by this authorPrachi Sharma, Prachi SharmaSearch for more papers by this author First published: 27 March 2023 https://doi.org/10.1002/ird.2833Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Early ViewOnline Version of Record before inclusion in an issue RelatedInformation

Assessing Progress and Interactions toward SDG 11 Indicators Based on Geospatial Big Data at Prefecture-Level Cities in the Yellow River Basin between 2015 and 2020

Rapid urbanization brings a series of dilemmas to the development of human society. To address urban sustainability, Sustainable Development Goal 11 (SDG 11) is formulated by the United Nations (UN). Quantifying progress and interactions toward SDG 11 indicators is essential to achieving Sustainable Development Goals (SDGs). However, it is limited by a lack of data in many countries, particularly at small scales. To address the gap, this study used systematic methods to calculate the integrated index of SDG 11 at prefecture-level cities with different economic groups in the Yellow River Basin based on Big Earth Data and statistical data, analyzed its spatial aggregation characteristics using spatial statistical analysis methods, and quantified synergies and trade-offs among indicators under SDG 11. We found the following results: (1) except for SDG 11.1.1, the performance of the integrated index and seven indicators improved from 2015 to 2020. (2) In GDP and disposable income groups, the top 10 cities had higher values, whereas the bottom 10 cities experienced greater growth rates in the integrated index. However, the indicators’ values and growth rates varied between the two groups. (3) There were four pairs of indicators with trade-offs that were required to overcome and eight pairs with synergies that were crucial to be reinforced and cross-leveraged in the future within SDG 11 at a 0.05 significance level. Our study identified indicators that urgently paid attention to the urban development of the Yellow River Basin and laid the foundation for local decision-makers to more effectively implement the 2030 Agenda for Sustainable Development (the 2030 Agenda).

Optimizing Water Distribution in Transboundary Rivers Based on a Synthesis–Dynamic–Harmonious Approach: A Case Study of the Yellow River Basin, China

It has been difficult to revise and adjust the water distribution of the Yellow River in 1987 (1987 water distribution scheme). By gathering data and studies from previous literature, this paper summarized some water distribution ideas, principles and rules in transboundary rivers. We proposed the “synthesis–dynamic–harmonious” water distribution method (SDH), and applied it to the actual conditions of the Yellow River basin. Through the SDH method, we calculated a new scheme for water distribution in the Yellow River and analyzed the results. The key findings of this study are summarized below. Firstly, the water distribution of transboundary rivers required the establishment of advanced water distribution ideas. Secondly, the proposed water distribution method took into account a variety of factors: with the change in distributable water volume, the same ratio changes and meets the minimum water demand and water efficiency constraints. Thirdly, the 1987, the water distribution scheme needed some adjustment. Fourthly, under the new Yellow River basin water distribution scheme (“19ZQT” water distribution scheme), Shandong, Inner Mongolia, and Henan account for 50% of the total water distribution. Sichuan accounts for only 0.3% of the total. Compared with the 1987 water distribution scheme, Hebei and Tianjin reduced the amount of water allocated by 51.2%, while Shaanxi increased it by 24.89%. In this paper, considering the changes in the total distributable water volume, the new Yellow River water distribution scheme (“19ZQT” water distribution scheme) assumed water distribution of 37 billion m3 and 30 billion m3, upon which calculations were performed. This study should provide a scientific and reasonable scheme for water distribution of transboundary rivers, and rational utilization of water resources. It should lay a solid foundation for the high-quality development of the Yellow River basin.

Analysis of the Nonlinear and Spatial Spillover Effects of the Digital Economy on Carbon Emissions in the Yellow River Basin

Low-carbon development of the Yellow River Basin (YRB) is an inherent requirement for implementing ecological protection and high-quality development strategies in the YRB and an important way to achieve China’s carbon peak and neutrality goals. However, utilization of the newly emerging digital economy to reduce carbon emissions in the YRB remains a largely unexplored topic. Based on panel data obtained from 56 cities in the YRB from 2011 to 2019, the nonlinear and spatial spillover effects of the digital economy on carbon emissions were studied using spatial econometric and multiple threshold effect models. The results showed that: (1) The digital economy had an inverted U-shaped relationship with carbon emissions, initially increasing and subsequently decreasing, with a more prominent impact intensity in upstream cities; (2) The digital economy had distinct negative spatial spillover effects on carbon emissions, with more significant effects observed in the midstream and downstream; (3) The digital economy had a nonlinear threshold effect on carbon emissions. When the optimization level of the industrial structure was above a certain threshold, the digital economy reduced carbon emissions. Based on these results, we propose suggestions for accelerating the healthy growth of the digital economy while promoting carbon emission reductions across the YRB.

Coordinated analysis and evaluation of water–energy–food coupling: A case study of the Yellow River basin in Shandong Province, China

Water resources, energy, and food are important basic resources for high-quality regional development. In the process of rapid development of regional economy, how to coordinate the development of basic resources has become one of the most serious challenges to the high-quality development of the Yellow River basin and even the whole Yellow River basin in Shandong province. Previous studies have produced few such analyses and evaluations for cities in the Yellow River basin, and there is a lack of research on multi-scale analysis, evaluation and prediction of urban coupling and coordinated development level. Hence, in this study, we propose an indicator system consisting of 24 indicators for the water resources, energy, and food system based on panel data for 9 cities in the Yellow River basin in Shandong Province for 2011–2020. Spatial autocorrelation analysis and temporal and spatial distribution analysis were used to determine the current state of water resources, energy, and food systems at multiple scales; combined weighting, comprehensive evaluation, and coupling coordination quantification were used to formulate the coupling coordination relationships of water resources–energy–food and identify the spatiotemporal formation and development of the water resources–energy–food system. A particle swarm optimization–back propagation model (PSO-BP) was used to predict the coupled and coordinated changes in the water resources–energy–food system for the next five years. The study results show that: (1) The composite index of the water resources–energy–food system showed an increasing trend, and the composite index of the food subsystem increased relatively quickly. (2) In 2020, the coupling coordination degree for eight of the nine cities in the Yellow River basin in Shandong Province was 0.70. Jinan, the exception, was at a critical stage of transitioning from low to moderate coupling, and the other eight cities were at the moderate stage of coupling coordination. (3) The coupling coordination of the water resources–energy–food system is increasing; it has transitioned from low to moderate and is about to transition to the stage of good coupling coordination. (4) The PSO-BP model predicted that the coupling coordination of water resources–energy–food systems in the Yellow River basin in Shandong Province will reach the stage of good coupling coordination in 2023. The research results presented in this paper can provide a theoretical basis for formulating policy recommendations in the Yellow River basin in Shandong Province.

Extreme streamflow and sediment load changes in the Yellow River Basin: Impacts of climate change and human activities

In recent decades, the increasing frequency and magnitude of extreme hydrological events due to climate change and human activities have caused substantial economic losses and damages to human wellbeing. Here, we investigated the spatiotemporal variations of streamflow extremes (QE) and sediment load extremes (SE) in the Yellow River (YR) during 1956–2019. Furthermore, the effects of main human activities and climate change were identified by establishing quantitative relationships between these factors and changing hydrological extremes. Specifically, the QE and SE have decreased significantly (p < 0.05) since 1956 except the headwater (reach above Tangnaihai). However, the QE increased significantly (p < 0.05) during 2000–2019 due to increased extreme precipitation, while the SE tended to stabilize at most stations. Besides, the contribution of QE to annual streamflow declined distinctly in the upper-middle reaches (Lanzhou-Tongguan reach) but increased significantly in the lower reaches (reach below Huayuankou). Likewise, the contribution of SE to annual sediment load increased remarkably in the middle-lower reaches (Huayuankou-Lijin reach). Furthermore, the timing of QE and SE generally tended to disperse from the flood season to the four seasons. While extreme precipitation fundamentally caused the extreme water and sediment discharge, the magnitude and hazard of QE and SE can be strongly regulated by human activities. Particularly, mainstream dams can artificially regulate QE and SE magnitudes and relationships and reduce their synchronization probability, and intra-basin engineering construction and revegetation measures can substantially reduce their possible peaks in a power function form. In addition, changes in the extreme water–sediment relationships indicated that declining erosive power in the middle reaches and decreasing sediment availability in the lower reaches dominated SE reduction. This study provides a scientific basis for flood risk management and water resources development and utilization in large complex river basins.

A social-ecological coupling model for evaluating the human-water relationship in basins within the Budyko framework

Correctly understanding the coordinated development between the social economy and the ecological environment is the key to achieving the sustainable development of river basins. Previous coupling coordination degree models are empirical ones and very complex, without physical parameters. Here, a novel social-ecological coupling model was established to meet the challenge. Within the Budyko framework, nD was adopted to characterize the social-ecological coupling coordination degree of the human-water relationship in basins. In addition, a social-ecological coupling coordination model with basins in northern Shaanxi Province, China as units. The multiple linear regression (MLR) model was used to quantitatively analyze the evolutional relationship between economic development and ecological environment. Research results show that R2 is larger than 0.6 in the comprehensive evaluation results of the novel model. This means that the model can well reflect changes in vegetation coverage and simplify expression of the coordinated development of social-ecological systems. The evaluation results of the human-water relationship in the basins are gradually improved year by year and the coordination state evolved constantly. The two systems have positive promotion effects on each other. The social-ecological coupling coordination degree (D) is spatially different, and various basins are listed in a descending order as the Yanhe, Wuding, and Kuye river basins according to D. D of the three basins all evolves from 0.2 (moderate incoordination) to 0.6 (mild coordination). Combined with analysis of ARIMA time series, it is anticipated that the human-water relationship will reach moderate coordination by 2030. Finally, without changing the premise of the social-ecological coupling model, limitations of the current model factors can be improved for future research to provide policy suggestions exploring ways to coordinate development of social-ecological systems in northern Shaanxi.

Modern Concepts on the Origin and Distribution of Acipenserids (Acipenseridae)

The current data on the place and time of origin of Acipenseriformes and the family Acipenseridae, as well as on their distribution in connection with the history of the development of sea and river basins, are summarized. The supposed areas of the initial radiation of Acipenseriformes and their long-term habitation were in eastern Laurasia on a part of the modern Chita Region, Eastern and Central Mongolia, and northern and northeastern China. The eastern part of Asia should also be considered the place of origin of the family Acipenseridae. The widespread distribution of Acipenseriformes was facilitated mainly by the formation of diadromous forms from primarily freshwater species, the origin of which is associated with multiple transgressions and regressions of the ocean. Modern potamodromous acipenserids were probably formed as a result of the return of anadromous forms to living in fresh water; i.e., they are secondarily freshwater species

Interactions between Soil Moisture and Water Availability over the Inner Mongolia Section of the Yellow River Basin, China

The ecological conservation and high-quality development of the Yellow River Basin (YRB) has been declared as a major national strategy of China. Surface water availability (precipitation minus evapotranspiration, PME) poses challenges to the sustainability of ecosystems of the YRB. Noteworthy is that the Mongolian section of the YRB (IMYRB) is a critical ecological barrier in Northern China. Soil moisture (SM) changes are highly sensitive to PME and important for regional ecological security. However, SM vs. PME interactions and relevant mechanisms within the IMYRB are poorly understood. We found significant decreases in SM and PME over the east IMYRB (r = 0.7, p &lt; 0.05). During the wet (July, August, and September) and dry (April, May, and June) seasons, as well as the whole year, decreased SM drives increased PME through land-atmosphere interactions over more than 90% of the IMYRB. Reduction in SM decreased evapotranspiration over more than 80% of the IMYRB, increased surface temperature across more than 79% of the IMYRB, boosted atmospheric vertical ascent over more than 75% of the IMYRB, and enhanced moisture convergence and PME. This study highlights the land-atmosphere interactions over the IMYRB, implicating basin-scale impacts of climatic changes on water resources.