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This document is a summary of a special issue on fluvial geomorphology, river management, and restoration. The issue addresses the role of fluvial geomorphology in landscape evolution and the impact of human activities on fluvial systems. It also discusses the influence of climatic changes on rivers and their interaction with marine systems. The special issue includes research papers from different parts of the world, covering topics such as river restoration, water availability in rural communities, and fish passage in restored fluvial channels. The papers use various methods of investigation, including field surveys, modeling, and statistical analyses. Overall, the special issue contributes to the understanding of fluvial dynamics and the vulnerability of fluvial environments. [Extracted from the article]

Since 1990, global forest area has been reducing; tropical forests have suffered from different anthropogenic and natural factors that account for forest loss. Tropical deforestation is the second driver of anthropogenic emissions; increasing demand and investments in tropical forests drive these emissions. These forests attract significant foreign direct investments, but the effects of these investments on carbon emissions from land use, land-use change, and forestry are not well enshrined in the literature for the countries under study. This paper seeks to analyse the impact of foreign direct investments on carbon emissions from land use, land-use change, and forestry amongst 30 tropical forest countries from 1996 to 2019. The sampled countries were disaggregated by tropical blocs: Amazon, Congo basin, Australasia, and Southeast Asia, and by income levels; low-income, lower-middle, upper-middle, and high-income. The findings reveal a U-shape structure of the impact of FDI on carbon emissions from LULUCF within Congo basin and Amazon countries; at higher levels of FDI, emissions from LULUCF will increase while Australasia and Southeast Asian countries show an inverted U-shape impact, thus at higher levels of FDI, there will be a negative and significant impact on carbon emissions from LULUCF. The income levels reveal an inverted U-shape for low-income and high-income countries and a U-shape for upper-middle-income countries; the impact for lower-middle-income countries is not significant. Overall, for the whole sample, the impact depicts a U-shape. This paper proposes high-level development of environmental conditions for FDI for different sectors that align with country and regional green growth plans. Enhancing national and regional governance systems to enforce decisions and fight corruption effectively can significantly promote green FDI for green growth. [ABSTRACT FROM AUTHOR]

The Yangtze River (hereafter referred to as the YZR), the largest river in China, is of paramount importance for ensuring water resource security. The Yangtze River Basin (hereafter referred to as the YRB) is one of the most densely populated areas in China, and complex human activities have a significant impact on the ecological security of water resources. Therefore, this paper employs theories related to ecological population evolution and the Driving Force-Pressure-State-Impact-Response (DPSIR) model to construct an indicator system for the ecological security of water resources in the YRB. The report evaluates the ecological security status of water resources in each province of the YRB from 2010 to 2019, clarifies the development trend of its water resource ecological security, and proposes corresponding strategies for regional ecological security and coordinated economic development. According to the results of the ecological population evolution competition model, the overall indicator of the ecological security of water resources in the YRB continues to improve, with the safety level increasing annually. Maintaining sound management of water resources in the YRB is crucial for sustainable socioeconomic development. To further promote the ecological security of water resources in the YRB and the coordinated development of the regional economy, this paper proposes policy suggestions such as promoting the continuous advancement of sustainable development projects, actively adjusting industrial structure, continuously enhancing public environmental awareness, and actively participating in international ecological construction and seeking cooperation among multiple departments. [ABSTRACT FROM AUTHOR]

This paper analyses the effects of environmental flows on water quality within a highly regulated basin, focusing on the Turia River basin in the eastern Iberian Peninsula. Through water management and water quality models, a series of simulations were conducted, introducing variations in the outflows of the Loriguilla reservoir to evaluate the effects of different environmental flow scenarios on water quality, particularly at the location of the intake for the water supply to Valencia. Three environmental flow scenarios were analyzed, alongside an alternative management scenario, considering their implications on water quality and reliability of water demand. The findings of this paper, particularly the nitrate (NO3−) concentration evolution, highlight the influence of minimum e-flow and e-flow regimes on water quality within the basin. These results suggest that while modifying the current flow regime can lead to some improvements in nitrate concentrations at the Valencia supply intake point, the primary cause of high nitrate concentrations is attributed to irrigation return flow and the pre-existing contamination of the aquifer. This analysis offers valuable insights into the complexities of water quality management in regulated basins, emphasizing the need for a multi-faceted approach to address the diverse factors influencing water quality and demand supply reliability. [ABSTRACT FROM AUTHOR]

In the late stage of underground brine mining in salt lakes, the method of injecting fresh water is often used to extract the salt from the brine storage medium. This method of freshwater displacement breaks the original water–rock equilibrium and changes the evolution process of the original underground brine. To explore the mechanism of salt release in saline water-bearing media under conditions of relatively fresh lake water dissolution, this paper analyzes the changes in the chemical parameters of brine from 168 sampling points in the Mahai salt lake in the Qaidam Basin at three stages (before exploitation, during exploitation, and late exploitation) by correlation analysis, ion ratio analysis, and other methods and investigate the variations in porosity and the evolution laws of brine. The results show that the changes in the main ion content and brine mineralization during the exploitation process are small. The changes in Ca2+ content are significant due to the low solubility of calcium minerals, the precipitation of gypsum during the mixing process, and the adsorption of cations by alternating with Ca2+. Primary intergranular pore skeletons are easily corroded to form secondary pores, which increase the geological porosity. Na+ and Cl- are the dominant ions in the brine in the study area, but the concentration of Ca2 + decreased significantly under the influence of mining, by 41.7% in the middle period and 24.5% in the late period. The correlation between Ca2+ and salinity changes significantly in different mining stages, and the reason for the decrease of Ca2+ may be due to the influence of mineral dissolution, mixing, and anion-cation exchange. The porosity of the layer in the study area showed the opposite trend of Ca2+, and the porosity increased first and then decreased. The innovation of this paper lies in analyzing the reasons and mechanisms of the disturbance of artificial dissolution mining on stratum structure by comparing the hydrochemical characteristics and porosity of underground brine storage media in three different mining stages. The research in this paper provides a theoretical basis for the calculation of brine resource reserves and the sustainable development of underground brine in salt lake areas. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic presented the unique challenge of having to deliver novel vaccines during a public health crisis. For pediatric patients, it was further complicated by the delayed timeline for authorizing the vaccine and the differences in dosing/products depending on the patient's age. This paper investigates the relationship between the spatial accessibility and uptake of the COVID-19 vaccine in King County, WA, USA. Public data for COVID-19 vaccine sites were used to calculate spatial accessibility using an enhanced two-step floating catchment area (E2SFCA) technique. Spatial regression analyses were performed to look at the relationship between spatial accessibility and ZIP-code-level vaccination rates. The relationships of these data with other socioeconomic and demographic variables were calculated as well. Higher rates of vaccine accessibility and vaccine coverage were found in adolescent (12- to 17-year-old) individuals relative to school-age (5- to 11-year-old) individuals. Vaccine accessibility was positively associated with coverage in both age groups in the univariable analysis. This relationship was affected by neighborhood educational attainment. This paper demonstrates how measures such as E2SFCA can be used to calculate the accessibility of the COVID-19 vaccine in a region and provides insight into some of the ecological factors that affect COVID-19 vaccination rates. [ABSTRACT FROM AUTHOR]

Sichuan-Tibet Railway spans several watersheds such as Jinsha River and Yalong River, and Potential landslides are frequent along the route, which poses serious hazards to the normal construction and operation of the railroad. The traditional time-series InSAR technology is limited by the number of images and other restrictions, and has a long solution time, making it difficult to obtain information on short-term occurrence of deformation and unable to perform wide-area potential landslides monitor quickly. In this paper, taking a geological hazard-prone area in the Jinsha River basin (or a section of the Sichuan-Tibet line) as an example, based on the Sentinel-1 satellite SAR data provided by the Copernicus program of ESA, the model corrects the interferometric superposition deformation results obtained from a small number of SAR images (less than 7), decodes the corrected rate results, and identifies a total of 13 areas where deformation obviously occurs A total of 13 typical areas with significant deformation were identified. The identified typical areas were time-series solved and their deformation was traced. The method provides a new idea for identification and monitor of Potential landslides in a wide area and further promotes the development of disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

The riparian zone is an area where land and water are intertwined, and vegetation is rich and complexly distributed. The zone can be directly involved in ecological regulation. In order to protect the ecological environment of the riparian zone, it is necessary to monitor the distribution of vegetation. However, there are many disturbing factors in extracting riparian vegetation, the most serious of which are water bodies with similar colours to the vegetation. To overcome the influence of water bodies on vegetation extraction from UAV imagery of riparian areas, this paper proposes a novel approach that combines the marked watershed algorithm with vegetation index recognition. First, the image is pre-segmented using edge detection, and the output is further refined with the marked watershed algorithm. Background areas are classified as potential regions for vegetation distribution. Subsequently, the final vegetation distribution is extracted from these potential vegetation areas using the vegetation index. The segmentation threshold for the vegetation index is automatically determined using the OTSU algorithm. The experimental results indicate that our method, when applied to UAV aerial imagery of the riparian zone, achieves an overall accuracy of over 94%, a user accuracy of over 97%, and a producer accuracy of over 93%. [ABSTRACT FROM AUTHOR]

Losses from catastrophic floods are driving intense efforts to increase preparedness and improve response to disastrous flood events by providing early warnings. Yet accurate flood forecasting remains a challenge due to uncertainty in modeling, calibrating, and validating a useful early warning system. This paper presents the Requisitely Simple (ReqSim) flood forecasting system that includes key variables and processes of basin hydrology and atmospheric forcing in a data-driven modeling framework. The simplicity of the modeling structure and data requirements of the system allows for customization and implementation in any medium to large rain-fed river basin globally, provided there are water level or discharge measurements at the forecast locations. The proposed system's efficacy is demonstrated in this paper through providing useful forecasts for various river basins around the world. This include 3–10-day forecasts for the Ganges and Brahmaputra rivers in South Asia, 2–3-day forecast for the Amur and Yangtze rivers in East Asia, 5–10-day forecasts for the Niger, Congo and Zambezi rivers in West and Central Africa, 6–8-day forecasts for the Danube River in Europe, 2–5-day forecasts for the Parana River in South America, and 2–7-day forecasts for the Mississippi, Missouri, Ohio, and Arkansas rivers in the USA. The study also quantifies the effect of basin size, topography, hydrometeorology, and river flow controls on forecast accuracy and lead times. Results indicate that ReqSim's forecasts perform better in river systems with moderate slopes, high flow persistence, and less flow controls. The simple structure, minimal data requirements, ease of operation, and useful operational accuracy make ReqSim an attractive option for effective real-time flood forecasting in medium and large river basins worldwide. [ABSTRACT FROM AUTHOR]

Within a river catchment, the relationship between pollutant load migration and its related factors is nonlinear generally. When neural network models are used to identify the nonlinear relationship, data scarcity and random weight initialization might result in overfitting and instability. In this paper, we propose an averaged weight initialization neural network (AWINN) to realize the multi-index integrated prediction of a pollutant load under data scarcity. The results show that (1) compared with the particle swarm optimization neural network (PSONN) and AdaboostR models that prevent overfitting, AWINN improved simulation accuracy significantly. The R2 in test sets of different pollutant load models reached 0.51–0.80. (2) AWINN is effective in overcoming instability. With more hidden layers, the stability of the models' outputs was stronger. (3) Sobol sensitivity analysis explained that the main influencing factors of the whole process were the flows of the catchment inlet and outlet, and main factors changed across seasons. The algorithm proposed in this paper can realize stably integrated prediction of pollutant load in the catchment under data scarcity and help to understand the mechanism that influences pollutant load migration. [ABSTRACT FROM AUTHOR]

This special issue of the journal "Water" focuses on the management and sustainable development of the Yellow River basin in China. It includes twenty academic papers covering various aspects of Yellow River basin management, such as water resources allocation, ecological protection, and environmental restoration. The papers provide insights into topics such as climate change's impact on the river's natural runoff and the challenges and potential solutions for water resource allocation and efficient utilization. The document emphasizes the need for coordinated development, ecological protection, and sustainable management of the Yellow River Basin. It also highlights the challenges of managing pollutants and understanding the water-sediment relationship in the basin. Additionally, the governance of the Yellow River Basin should consider cultural preservation and integrate it into the water management strategies. [Extracted from the article]

This paper delves into the multi-port berth allocation problem (MBAP), enriching the traditional berth allocation problem (BAP) with vessel speed optimization (VSO). In the MBAP, it is assumed that there is cooperation between the port and the shipping companies, and the operation of the vessels and the ports is planned to maximize the overall benefits. Exploring this potential collaboration between ports and shipping entities has the potential to mitigate, or even resolve, the challenges plaguing maritime transportation, e.g., port congestion and suboptimal vessel schedules, to ultimately enhance the efficiency of maritime trade. In this paper, a new mixed-integer linear programming (MILP) model for the MBAP is formulated, which attempts to minimize the total cost incurred during operations, with various constraints such as vessel sailing, the vessel space–time relationship in ports, and the planning period. Meanwhile, an innovative variable neighborhood search (VNS) algorithm is presented, in which the initial solution generation method and neighborhood structures are proposed according to the MBAP characteristics. Furthermore, two sets of MBAP instances are generated to test the proposed MILP and VNS, of which the first set is based on real-world port data and the second on existing studies. The numerical experiments verify that the VNS can efficiently and reliably solve instances of all scales, with each neighborhood structure contributing uniquely to the iterative process. In addition, by analyzing the impact of varying oil prices on the MBAP, the study offers valuable management insights. Finally, a case study based on real data from a port group in the Yangtze River Basin is presented to further demonstrate the necessity of considering vessel service time window and planning period in the MBAP as well as the important role of the VSO in scheduling. [ABSTRACT FROM AUTHOR]

In times of climate change, periods of drought will occur more frequently. This causes challenges for water use, ranging from limitations on the navigability of water courses, limited availability of water for irrigation and drinking water supply, reduced hydropower production, increasing concentrations of pollutants, deteriorating water quality, and ecosystem degradation. Dealing with droughts, however, is a complex puzzle due to the multi-level governance characteristics of international river basins and the need to meet the freshwater demands of all sectors involved. This increases the need to address drought issues in a coordinated way, along all levels of decision making. Thus far, the way this must be executed has been under-researched. This paper addresses this knowledge gap as it aims to provide design principles for good multi-level drought risk governance in international river basins. In order to meet our aim, we first reviewed literature on multi-level and good governance and established an assessment framework. This framework was applied in a case study on drought risk governance in the international Rhine basin. Policy documents were analyzed and key informants interviewed. We found that although the governance practice in the basin meets most of our framework criteria, differences between the international level, the Netherlands, Germany, and Switzerland also occurred. We have synthesized our findings into a list of 10 design principles for good multi-level drought risk governance, which could function as a starting point for the analysis and improvement of other multi-level drought risk governance practices. [ABSTRACT FROM AUTHOR]

Shape vectorization is a key stage of the digitization of large-scale historical maps, especially city maps that exhibit complex and valuable details. Having access to digitized buildings, building blocks, street networks and other geographic content opens numerous new approaches for historical studies such as change tracking, morphological analysis and density estimations. In the context of the digitization of Paris atlases created in the 19th and early 20th centuries, we have designed a supervised pipeline that reliably extract closed shapes from historical maps. This pipeline is based on a supervised edge filtering stage using deep filters, and a closed shape extraction stage using a watershed transform. It relies on probable multiple suboptimal methodological choices that hamper the vectorization performances in terms of accuracy and completeness. Objectively investigating which solutions are the most adequate among the numerous possibilities is comprehensively addressed in this paper. The following contributions are subsequently introduced: (i) we propose an improved training protocol for map digitization; (ii) we introduce a joint optimization of the edge detection and shape extraction stages; (iii) we compare the performance of state-of-the-art deep edge filters with topology-preserving loss functions, including vision transformers; (iv) we evaluate the end-to-end deep learnable watershed against Meyer watershed. We subsequently design the critical path for a fully automatic extraction of key elements of historical maps. All the data, code, benchmark results are freely available at https://github.com/soduco/Benchmark_historical_map_vectorization. [ABSTRACT FROM AUTHOR]

In recent years, environmental damage caused by economic development has been increasing in China's Yellow River basin (YRB), one of the country's most important economic zones. Finding an appropriate governance model is a prerequisite to ensuring the coordinated development of the YRB. Traditional analysis focus on city or province level, which is less accurate and ignores the interaction between spaces. This paper explores the distribution, spatial relationships and influencing factors of the level of coordinated development at county level in the YRB and its impact on the study area's environment. This investigation aims to provide scientific support for the region's governance. We used the equivalent value method, the entropy method, a coupling coordinating degree model and the double-fixed spatial Durbin model to quantify, spatialize and assess the relationship between the value of ecosystem services and economic development and to analyze the drivers of ecological changes and the spatial interaction effects in the YRB from 2010 to 2020. The results show that (1) The degree of ecological-economic coupling coordination in the YRB steadily increased over the study period and is high in eastern areas but low in the western area. The growth rate is fast in the east and slow in the west and the gap has gradually enlarged. (2) Adjusting the industrial ratios alone cannot improve the level of local coordinated development. The intensity of government public expenditure support can significantly affect the coordinated development level of local, and the intensity of the impact on the neighboring areas depends on the difficulty of intercommunication between areas. (3) Increasing rural disposable income in mountainous areas can effectively increase the level of local coupling coordination but can also lead to a decrease in coupling coordination in the surrounding areas. (4) The influence of the normalized difference vegetation index on coupling coordination depends on local land values. [ABSTRACT FROM AUTHOR]

Agricultural drought events have become more frequent in the Inner Mongolia inland river basin in recent years, and the spatio-temporal evolution characteristics and development rules can be accurately and comprehensively understood using the three-dimensional identification method. In this paper, standardized soil moisture index (SSMI) was used to characterize agricultural drought, and modified Mann–Kendall trend test (MMK) and 3D recognition of drought events were used to analyze the spatio-temporal evolution characteristics of agricultural drought events in this basin and reveal the drought development law. The relationships between drought and temperature (T), precipitation (P), evapotranspiration (E), and humidity (H) were analyzed using a cross-wavelet method. The results are as follows: (1) When the time scale of agricultural drought was short (monthly scale), the alternations of dry and wet were frequent, but the SSMI index of all scales showed a downward trend; (2) The spatial distribution characteristics of drought change trend in four seasons were similar, but the area with a significant downward trend of drought in spring was the largest, and the area of high frequency region was also the largest, and the drought trend was the most obvious; (3) The most serious agricultural drought event occurred from October 2000 to May 2002, and reached its maximum value in September 2001 (drought area and drought severity of 2.26 × 105 km2 and 3.61 × 105 months·km2, respectively), which mainly experienced five processes—drought onset–intensification–decay–re-intensification–termination—and the migration path of the drought center showed the characteristics of southwest–northeast transmission; (4) All the four meteorological factors were correlated with SSMI, and P had a greater impact on SSMI. This article aims to reveal the spatio-temporal evolution of agricultural drought events in the Inner Mongolia inland river basin, and provide a new way to accurately evaluate the spatio-temporal evolution of drought. [ABSTRACT FROM AUTHOR]

Water resources are crucial for the development of ecosystems and humanity. The Yellow River Basin (YRB), as an important ecological area in China, is facing significant challenges in ecological protection and high-quality development due to global climate change and intense human activities. In order to alleviate the water resources crisis in the YRB, it is necessary to calculate the resilience of the water resources system and identify the main influencing factors. This paper considered the factors of water resources, social economy, and ecological environment, then constructed an evaluation framework of the water resources system resilience (WRSR) from three aspects: resistance, restoration, and adaptability. Taking nine provinces along the YRB as a case study, the WRSR was measured by using the entropy weight TOPSIS model, and its driving factors were analyzed with Geographical Detectors (GD). The results showed that: (1) From 2010 to 2022, the WRSR in the Yellow River Basin and various provinces was showing a fluctuating increasing trend, in which Ningxia had the highest average WRSR (0.646), while Shanxi had the lowest (0.168). (2) From three dimensions, the development trends of resistance, restoration, and adaptability in the YRB and various provinces from 2010 to 2022 were relatively stable. Shandong's resistance level far exceeded that of other provinces, having the highest average resistance value (0.692), and Ningxia had the highest average value of restoration (0.827) and adaptability (0.711). However, Gansu had the lowest average value of resistance (0.119), Sichuan had the lowest average value of restoration (0.097), and Shandong had the lowest average value of adaptability (0.110). (3) In terms of impact factors, the development and utilization rate of water resources (C13) and the development and utilization rate of surface water resources (C14) in the restoration subsystem consistently ranked in the top two of influencing factors. Similarly, the water consumption per 10,000 yuan of GDP (C26) in the adaptability subsystem consistently ranked within the top ten. On the other hand, the natural population growth rate (C6) in the resistance subsystem, as well as the impact of ammonia nitrogen emissions (C9) and total precipitation (C2) in wastewater, exhibited an upward trend. Based on these, this paper provides relevant suggestions for improving the WRSR in the YRB. [ABSTRACT FROM AUTHOR]

Scientifically measuring the level of environmental governance (EGL) and understanding its spatial convergence has important reference value for ecological governance. In this paper, the global entropy method is applied to measure the EGL of 284 prefecture-level cities in China from 2007 to 2019, which are divided into three major river basins, including the Yellow River, Yangtze River, and Pearl River, to observe the spatial–temporal evolutionary characterization through a standard deviation ellipse model. The coefficient of variation and the spatial econometric model are the tools used to conduct the spatial convergence test. The results are as follows: (1) China's EGL is low overall, though it is fluctuating upward at low magnitude, and the three major river basins follow the ranking: The Pearl River Basin > The Yangtze River Basin > The Yellow River Basin. (2) Spatially, the distribution pattern of China's EGL changes from "scattered and sporadic" to "multipolar core". (3) The center of China's environmental governance was concentrated in the east from 2007 to 2019, and the EGL in the midstream and downstream regions of the three major river basins increased rapidly. (4) Environmental governance in China has significant absolute and conditional β-convergence characteristics, as do the three major basins, while the ranking of convergence speed remains "Yangtze River Basin > Yellow River Basin > Pearl River Basin". Of these, economic development accelerated the convergence rate of environmental governance in China and its three major river basins; financial pressure significantly inhibited the convergence of the EGL of the Yellow River Basin. The improvement of the EGL in the Pearl River Basin was also negatively influenced by the industrial structure. [ABSTRACT FROM AUTHOR]

Purpose: Improving agricultural carbon-output efficiency is an important path to realize the "double carbon" goal in the Yellow River Basin. In the context of rapid urbanization development, it is significant to explore whether promoting urbanization will affect agricultural carbon-output efficiency. Methods: Based on panel data of 75 cities in the Yellow River Basin from 2000 to 2020, this paper uses the super-DEA model, three-dimensional kernel density model, and Markov chain model to measure and analyze the spatio-temporal evolution of agricultural carbon-output efficiency in the Yellow River Basin. The panel Tobit model is used on this basis to analyze the relationship between urbanization and carbon-output efficiency in agriculture. Results: The results show the following: (1) The level of agricultural carbon-output efficiency in the Yellow River Basin is low and has not reached an effective state, showing a slow downward trend in general where the agricultural carbon-output efficiency in the lower reaches is higher than that in the middle reaches, and the upper reaches has the lowest. (2) Agricultural carbon-output efficiency in the Yellow River Basin has a negative trend of transitioning to a low level overall and maintaining its original level, and it is difficult to realize the leapfrog transfer between states. Agricultural carbon-output efficiency has an obvious spatial spillover effect and "club convergence" phenomenon; the high-efficiency area has a positive driving effect on the neighborhood area, while the low-efficiency area has a negative impact on the neighborhood area. (3) The level of urbanization has a significant positive impact on the carbon-output efficiency of agriculture in the upper, middle, and lower reaches of the Yellow River Basin, which plays an important role in promoting the green development of agriculture. [ABSTRACT FROM AUTHOR]

In the process of societal development, forest land categories often conflict with other land use types, leading to impacts on the ecological environment. Therefore, research on changes in forest land categories has increasingly become a globally focused topic. To anticipate potential forest ecological security issues under urbanization trends, studies on regional land use simulation become more important. This paper, based on land use data from the Ganjiang River basin, analyzes the distribution characteristics and changing trends of land use types from 2000 to 2020. Using the CA-Markov model, it predicts the land use pattern of the basin in 2040 and analyzes the transfer characteristics of forest land categories. The conclusions indicate that, between 2000 and 2020, the most significant trend in land use evolution was the transfer between various subcategories of forest land, especially frequent in the high-altitude mountainous areas in the southern and western parts of the basin. The land use pattern prediction model constructed in this paper has a kappa index of 0.92, indicating high accuracy and reliability of the predictions. In 2040, the most significant land evolution phenomenon would be from forest land to arable land to construction land, particularly pronounced around large cities. Over the next 20 years, the focus of land use evolution may shift from the southern part of the basin to the central and northern parts, with urban expansion possibly becoming the main driving force of land use changes during this period. Forest land restoration work is an effective method to compensate for the loss of forest land area in the Ganjiang River basin, with key areas for such work including Longnan, Yudu, Xingguo, Ningdu, Lianhua, and Yongxin counties. [ABSTRACT FROM AUTHOR]

Traditional villages, rich in historical and cultural value, hold a high level of preservation value. In the process of urbanization, traditional villages face the crisis of decline, making it difficult to perpetuate the carried cultural heritage. The Ganjiang River Basin hosts numerous traditional villages with rich research value, making the study of their preservation and development in this region a significant topic. This paper, from the perspective of landscape ecology, employs geographic detectors to analyze the driving factors behind the emergence of traditional villages in the Ganjiang River Basin, summarizing the spatial distribution characteristics of traditional villages. A classification method based on village landscape features is adopted to categorize traditional villages in the Ganjiang River Basin, providing a reference for planning the preservation and development of traditional villages. The research results show that plain areas are more suitable for the continuation of traditional villages; a single suitable environmental element cannot provide an environment conducive to the development of traditional villages, which is the result of the combined effect of multiple suitable elements; the study has divided traditional village landscapes into nine types, with clear distribution differences among different types of villages; for different regions and types of traditional villages, it is necessary to balance development and protection tendencies and plan differently according to environmental characteristics. [ABSTRACT FROM AUTHOR]

The integral development of agriculture and tourism heavily depends on natural resources, especially agricultural resources, and it also may contribute to the sustainability of agriculture. The sustainability of agriculture is usually measured by the agricultural eco-efficiency. The main objective of this paper is to demonstrate the impact of the agriculture and tourism integration on agricultural eco-efficiency, so as to reflect the role of the agriculture and tourism integration on promoting agricultural sustainability. Applying panel data of 19 provinces in Yangtze River Basin and Yellow River Basin in China from 2008 to 2019, this paper uses a PSTR model to demonstrate the impact of agriculture and tourism integration on agricultural eco-efficiency and its mechanisms. It is found that in the study area, the integration of agriculture and tourism can contribute to improvements in agricultural eco-efficiency, and when levels of integration are high, the promotional effect is enhanced. However, impacts vary among different regions to some extent. In terms of influencing mechanisms, inputs of agricultural labor, sown crop area, effective irrigation area and other factors decrease with continuous improvements of integration. The input of pesticides, fertilizers and other factors does not decrease in the initial stage of integration but undergoes a rapid decrease after crossing a threshold value. And it demonstrates that the integration of agriculture and tourism is beneficial for improving the agricultural eco-efficiency, so that it will contribute to agricultural sustainability. Meanwhile, this paper offers a new research perspective for discovering effects of agriculture and tourism integration, providing implications for formulating regional policies for the integration. [ABSTRACT FROM AUTHOR]

The characteristics and stages of collapse-filling in paleo-underground rivers vary in recharge-runoff-discharge zones, constraining the associated fracture-caved reservoirs in carbonate strata. This paper comprehensively uses core, fluid inclusion, and carbon-oxygen isotope to probe the evolution process and migration of collapse-filling in paleo-underground rivers in the Northern Uplift of the Tarim Basin. The results show that 1) more than three stages of collapse-filling were identified in recharge-runoff-discharge zones, and a four-stage differential collapse-filling process was proposed to summarize the evolution of paleo-underground rivers. 2) The collapse-filling process varies spatiotemporally in the recharge, runoff, and discharge zones. Hydrodynamic strength and filling capacity migrate gradually from the recharge zone to the discharge zone. 3) Collapse-filling mechanisms, including gravity, suffusion, and suction-erosion mechanisms, also vary along with the collapse-filling evolution process of paleo-underground rivers. The research provided a new insight to recognize and interpret the differential planar distribution and vertical filling of the paleo-underground river system, which can be further applied to investigate the fracture-caved karst reservoirs. [ABSTRACT FROM AUTHOR]

Introduction: Programme Science (PS) and community‐led monitoring (CLM) intersect in unexpected and promising ways. This commentary examines a CLM initiative in Malawi and South Africa to highlight the crucial role of CLM in bolstering the PS framework. By leveraging data sources often overlooked by conventional research and evaluation approaches, CLM emerges as a pivotal element in enhancing programme effectiveness. This paper delineates the fundamental principles of CLM, presents programme outcomes derived from CLM methodologies and contextualizes these findings within the broader framework of PS. Discussion: The Citizen Science Project implements CLM continuously at 33 health facilities: 14 in Malawi (eight in Kasungu District and six in Dedza District), and 19 in South Africa (all in the West Rand District), representing a total catchment area of 989,848 people. Monitoring indicators are developed in an iterative process with community groups. The indicators are unique to each country, but both focus on the uptake of health services (quantitative) and barriers to access (qualitative). Monthly clinic records surveys capture 34 indicators in Malawi and 20 in South Africa and are supplemented by qualitative interviews with care recipients and healthcare workers. Qualitative interviews provide additional granularity and help confirm and explain the more macro trends in service coverage as described in quantitative data. The resulting data analysis reveals key themes that help stakeholders and decision‐makers to solve problems collaboratively. Noteworthy outcomes include a substantial increase in multi‐month dispensing of antiretroviral therapy (ART) during COVID‐19 (from 6% to 31%) with a subsequent recovery surpassing of HIV service benchmarks in Malawi post‐pandemic. Conclusions: While quantifying direct impact remains challenging due to the project's design, CLM proves to be a robust methodology that generates credible data and produces impactful outcomes. Its potential extends beyond the health sector, empowering community leadership and fostering interventions aligned with community needs. As CLM continues to evolve, its integration into PS promises to improve relevance, quality and impact across diverse disciplines. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with data pertinent to transportation networks, which model situations in which objects move along a graph-like structure. We assume that these networks are equipped with sensors that monitor the network and the objects moving along it. These sensors produce time-series data resulting in sensor networks. Examples are river-, road- and electricity networks. Geographical information systems are used to gather, store and analyse data, and we focus on these tasks in the context of data emerging from transportation networks equipped with sensors. While tailored solutions exist for many contexts, they are limited for sensor-equipped networks at this moment. We view time-series data as temporal properties of the network and approach the problem from the viewpoint of property graphs. In this paper, we adapt and extend the theory of the existing property graph databases to model spatial networks, where nodes and edges can contain temporal properties that are time-series data originating from the sensors. We propose a language for querying these property graphs with time series, in which time-series and measurement patterns may be combined with graph patterns to describe, retrieve and analyse real-life situations. We demonstrate the model and language in practice by implementing both in Neo4j and explore questions hydrology researchers pose in the context of the Internet of Water, including salinity analysis in the Yser river basin. [ABSTRACT FROM AUTHOR]

This data paper presents microplastic (MP) concentration and composition data from four campaigns in a one-year period in the Seine River within the Greater Paris area. Detailed data on MP occurrence, physical water parameters, hydrological conditions, and potential sewer point sources are presented. Initial analysis of the data set shows that MP concentrations were significant (median: 600 particles m-3 and 100 mg m-3) and MP fluxes showed variations across sampling sites and campaigns. Three polymer types (polypropylene -- PP, polyethylene -- PE, polystyrene -- PS) account for 96% of the total number of MP. This dataset provides valuable insights for understanding river MP pollution under anthropogenic pressure. [ABSTRACT FROM AUTHOR]

Background: Urban ecological health is crucial for the long-term sustainable development of watershed. Accurately evaluating the health level of the ecological environment helps to develop reasonable strategies for ecological environment restoration and resource management. This paper constructed a comprehensive evaluation index system based on the Pressure-State-Response (PSR) framework and evaluated the ecological health of eleven administrative regions in the Wei River Basin (WRB), northwest China in 1980, 2000, and 2020 using an evaluation model established by fuzzy mathematics. Further, obstacle degrees were used to quantify the contribution of pressure, state, and response modules, as well as individual indicators to ecological health. Results: The comprehensive evaluation system constructed based on the PSR framework could effectively reflect the ecological health conditions of different regions in the WRB. During the study period, the ecological health went through a process of first deterioration and then improvement. By 2020, the ecological health of seven administrative regions reached healthy levels. The state module was the main obstacle module of the PSR framework to the ecological health of the most regions. The population density (P1), patch density of construction land (S5), comprehensive elasticity index (S8), soil erosion index (R1), and per capital GDP (R3) were the most crucial individual indicators affecting the ecological health. For different cities, the main obstacle factors varied. In economically developed cities, the limiting effect of P1 was more significant, while in economically underdeveloped cities, the limiting effect of R3 was stronger. Conclusions: In response to the special natural environment and socio-economic conditions of arid and semi-arid areas in the WRB, an ecological health evaluation index system suitable for the characteristics of the basin was constructed. The results indicated that, to improve the levels of urban ecological health, it is necessary to restore the natural ecological environment and control population size while accelerating economic construction. Our results can provide scientific support for the ecological health evaluation and protection of the WRB and even the arid and semi-arid areas in northwest China. [ABSTRACT FROM AUTHOR]

Braided rivers can provide substantial recharge to regional aquifers, with flow exchange between surface water and groundwater occurring at a range of spatial and temporal scales. However, the difficulty in measuring and modelling these complex and dynamic river systems has hampered process understanding and the upscaling necessary to quantify these fluxes. This is due to an incomplete understanding of the hydrogeological structures that control river–groundwater exchange. In this paper, we present a new conceptualisation of subsurface processes in braided rivers based on observations of the main losing reaches of three braided rivers in Aotearoa / New Zealand. The conceptual model is based on a range of data, including lidar, bathymetry, coring, particle size distribution, groundwater level and temperature monitoring, radon-222, electrical-resistivity tomography and fibre-optic cables. The combined results indicate that sediments within the recently active river braidplain are distinctive, with sediments that are poorly consolidated and better sorted compared with adjacent deposits from the historical braidplain that become successively consolidated and intermixed with flood silt deposits due to overbank flow. A distinct sedimentary unconformity, combined with the presence of geomorphologically distinct lateral boundaries, suggests that a "braidplain aquifer" forms within the active river braidplain through the process of sediment mobilisation during flood events. This braidplain aquifer concept introduces a shallow storage reservoir to the river system, which is distinct from the regional aquifer system, and mediates the exchange of flow between individual river channels and the regional aquifer. The implication of the new concept is that surface water–groundwater exchange occurs at two spatial scales: the first is hyporheic and parafluvial exchange between the river and braidplain aquifer; the second is exchange between the braidplain aquifer and regional aquifer system. Exchange at both scales is influenced by the state of hydraulic connection between the respective water bodies. This conceptualisation acknowledges braided rivers as whole "river systems", consisting of channels and a gravel aquifer reservoir. This work has important implications for understanding how changes in river management (e.g. surface water extraction, bank training and gravel extraction) and morphology may impact groundwater recharge (and potentially flow, temperature attenuation and ecological resilience) under dry conditions. [ABSTRACT FROM AUTHOR]

The objective of this study was to conduct a detailed analysis of the available flow series in the Chiriquí Viejo River basin in Panama. This paper examines the patterns of variation within these series and calculates various hydrological indexes indicative of the region's hydrology. Utilizing advanced hydrological indexes within the Chiriquí Viejo River basin in Panama, which spans an area of 1376 km2 and supports an estimated population of 100,000 inhabitants, analytical methods were employed to compute indexes such as the Daily Flow Variation Index (QVAR), the Slope of the Flow Duration Curve (R2FDC), the Hydrological Regulation Index (IRH), and the average duration of low (DLQ75) and high (DHQ25) flow pulses. The results indicate moderate flow variability (QVAR of 0.72) and a Hydrological Regulation Index (IRH) of 2.32, signifying a moderate capacity for flow regulation. Notably, low flow events (DLQ75) lasted approximately 3.73 days, while high flow events (DHQ25) lasted around 4.08 days. The study highlights a significant capacity to respond to extreme events, with maximum annual flows reaching 80.25 m3/s and minimum flows dropping to 3.01 m3/s. Despite the significant contribution of the basin to hydroelectric power generation and other economic activities, there is an observed need for sustainable management that accommodates hydrological fluctuations and promotes resource conservation. The conclusions indicate that these findings are critical for future planning and conservation strategies in the region, emphasizing the importance of integrating multidisciplinary approaches for Hydro-Social Sustainability. This novel and holistic approach underscores the interdependence between hydrological dynamics, socio-economic activities, and environmental sustainability, aiming to ensure the long-term resilience of the Chiriquí Viejo basin and its communities. [ABSTRACT FROM AUTHOR]

Accurate estimation of surface evapotranspiration (ET) in the Heihe River Basin using remote sensing data is crucial for understanding water dynamics in arid regions. In this paper, by coupling physical constraints and machine learning for hybrid modeling, we develop a hybrid model based on surface conductance optimization. A hybrid modeling algorithm, two physical process-based ET algorithms (Penman–Monteith-based and Priestley–Taylor-based ET algorithms), and three pure machine learning algorithms (Random Forest, Extreme Gradient Boosting, and K Nearest Neighbors) are comparatively analyzed for estimating the ET. The results showed that, in general, the machine learning model optimized by parameters was able to better predict the surface conductance of the hybrid model. Driver analyses showed that radiation, normalized difference vegetation index (NDVI), and air temperature had high correlations with ET. The hybrid model had a better prediction performance for ET than the other five models, and it improved the R2 of the two physical process-based algorithms to 0.9, reduced the root mean square error (RMSE) to 0.5 mm/day, reduced the BIAS to 0.2 mm/day, and improved the Kling–Gupta efficiency (KGE) to 0.9. The hybrid model outperformed the others across different time scales, displaying lower BIAS, RMSE, and higher KGE. Spatially, its ET patterns aligned with regional vegetation changes, with superior accuracy in annual ET estimation compared to the other models. Comparison with other ET products shows that the estimation results based on the hybrid model have better performance. This approach not only improves the accuracy of ET estimation but also improves the understanding of the physical mechanism of ET estimation by pure machine learning models. This study can provide important support for understanding ET and hydrological processes under different climatic and biotic vegetation in other arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

Exploring the spatial coupling relationship and interaction mechanism between green urbanization (GU) and tourism competitiveness (TC) is of great significance for promoting urban sustainable development. However, the lack of research on the interaction mechanism between GU and TC limits the formulation of effective environmental management policy and urban planning. Taking 734 counties in the Yellow River Basin (YRB) as the study area, this paper analyzes the spatial coupling relationship between GU and TC on the basis of comprehensive evaluation of GU and TC. Then, the interactive mechanism between GU and TC is systematically discussed, and the synergistic development strategy of the two is proposed. The results show that the GU level presents a multicore circle structure, with provincial capitals, prefecture-level urban districts and economically developed counties in east-central regions as high-value centers. The TC at county scale presents a multi-center spatial structure. Additionally, there is a significant positive spatial coupling between GU and TC in the YRB. The analysis further reveals that green urbanization level, social progress, population development, infrastructure construction, economic development quality, and eco-environmental protection has a observably influence on TC. Tourism competitiveness, service competitiveness, location competitiveness, resource competitiveness, market competitiveness, environmental influence, and talent competitiveness has a observably influence on GU. TC can promote GU, and the improvement of green urbanization level can support the development of tourism competitiveness. According to the spatial zoning method, 734 counties are divided into 6 categories, and the coordinated development strategy of GU and TC for each type of district is proposed. [ABSTRACT FROM AUTHOR]

Flood hazard mapping is currently in a transitional phase involving the use of data and methods that were traditionally in the domain of local studies in a regional or nationwide context. Challenges include the representation of local information such as hydrological particularities and small hydraulic structures, as well as computational and labour costs. This paper proposes a methodology of flood hazard mapping that merges the best of the two worlds (local and regional studies) based on experiences in Austria. The analysis steps include (a) quality control and correction of river network and catchment boundary data; (b) estimation of flood discharge peaks and volumes on the entire river network; (c) creation of a digital elevation model (DEM) that is consistent with all relevant flood information, including riverbed geometry; and (d) simulation of inundation patterns and velocities associated with a consistent flood return period across the entire river network. In each step, automatic methods are combined with manual interventions in order to maximise the efficiency and at the same time ensure estimation accuracy similar to that of local studies. The accuracy of the estimates is evaluated in each step. The study uses flood discharge records from 781 stations to estimate flood hazard patterns of a given return period at a resolution of 2 m over a total stream length of 38 000 km. It is argued that a combined local–regional methodology will advance flood mapping, making it even more useful in nationwide or global contexts. [ABSTRACT FROM AUTHOR]

The current paper aims to assess the effects of landscape change in a mountain river basin in the north of Iran through quantifying, mapping, and assessing carbon storage. The analyses were performed based on previous alterations in land use and land cover (LULC) (1988–2018) and on expected changes determined by three LULC alteration setups for 2048. The Landsat imagery from 2018, 2008, 1998, and 1988 was used for evaluating and predicting the spatiotemporal distributions of LULC changes. The future LULC image prediction has been generated using Land Change Modeler (LCM) module of TerrSet software for the years 2028, 2038, and 2048. Validation was carried out by overlaying the actual and projected to 2018 map. We integrated the Markov Chain (MC) and InVEST Carbon Storage and Sequestration (InVEST-CSS) models for simulating the ecosystem carbon storage and the long-term monetary valuation. In this process, we considered social costs/economic value because of the area's loss and gain of stored carbon. The results show that forests and rangelands with good and poor conditions decreased by 631.2, 10,374, and 10,254 ha, respectively, from 1988 to 2018. Overall, modeling and mapping LULC changes showed a descending trend in forests (0.66%), agriculture (0.1%), and rangelands (4.1%) in 2048. In addition, carbon storage has already been lost by 9.9 million tons (76.98 ha−1) from 1988 to 8.8 million tons (68.86 ha−1) in 2018 and is expected to have an 8.4 million tons (65.25 ha−1) loss by 2048. Monitoring the economic value of carbon storage from 1988 to 2018 shows a loss of $US 15684338 (121.8 ha−1) and estimates a loss of $US6972622 (54.18 ha−1) by 2048. Therefore, spatiotemporal design of InVEST model by estimating the carbon value over time focuses on continuous monitoring actions for both the carbon pools dynamic and LULC pattern. This consideration causes reduction the uncertainty of estimated models and also increases the continuous cost of those changes. This will help government and decision makers for long-term and accurate carbon sequestration strategies for ecosystem. [ABSTRACT FROM AUTHOR]

To investigate the spatial and temporal changes in fractional vegetation coverage (FVC) and their driving forces in different regions of the Inner Mongolia section of the Yellow River Basin, this paper observed the spatial trends and stability of FVC in these regions based on the MOD13Q1 information regarding the 2000–2020 period as a data source. It used the dimidiate pixel model to invert FVC, and based on the centre of gravity migration model, the coefficient of variation and the Mann–Kendall and Sen's slope estimator test, it studied the spatial variation trend and stability of FVC in the four relevant areas of the Inner Mongolia section; an attribution analysis using a geodetector was also conducted. The following results were found: (1) in terms of temporal FVC change in the relevant areas, from 2000 to 2020, the overall FVC showed an increasing trend, indicating an obvious hierarchy of change as per different seasonal scales (summer > growing season > fall > spring). There is a mutation point in FVC in different areas, and the FVC sequence is random. (2) Regarding spatial change, the overall FVC showed a trend of being high in the eastern regions and low in the western regions and low–high–low from the north to the south; the stability of the Hetao Irrigation District–Wuliangsuhai Area changed more significantly with the successive seasons, and the degraded areas of FVC were mainly distributed in the city centre of the Kundulun River–Daheihe River Area and in the Hetao Irrigation District in the summer. (3) In terms of driving factors, soil type had a relatively higher explanatory power regarding the Hetao Irrigation District–Wuliangsuhai Area, rainfall had a relatively higher explanatory power regarding the Morin River–Wuding River Area and the Kundulun River–Daheihe River Area, and land use had a relatively higher explanatory power regarding the Ten Kongtui–Heidaigou Area. [ABSTRACT FROM AUTHOR]

Small intermountain river basins are most suitable for developing new methods to estimate water balance due to their well-defined catchment boundaries, relatively rapid runoff processes, and accessible landscapes for study. In general terms, dissecting the hydrograph of a small mountain river requires calibration of the flow model against multi-year data sets, including (a) glacier mass balance and snow water content, (b) radiation balance calculation, (c) estimation of the groundwater contribution, and (d) water discharge measurements. The minimum primary data set is limited to the precipitation and temperature distributions at the catchment. This approach postulates that the conditions for the formation of all components of river flow are known in advance. It is reduced to calculating the dynamic balance between precipitation (input part) and runoff, ablation, and evaporation (output part). In practice, accurately accounting for the inflow and outflow components of the balance, as well as the impact of regulating reservoirs, can be a challenging task that requires significant effort and expense, even for the extensively researched catchments. Our studies indicate the potential benefits of an approach based on one-time, but detailed, observations of stable isotope composition, temperature, and water chemistry, in addition to standard datasets. This paper presents the results of the 2022–2023 work conducted in the basin of the small mountain river Ala-Archa, located on the northern slope of the Kyrgyz Range in Tien-Shan, which was chosen as an example due to its well-studied nature. Our approach could identify previously unknown factors of flow formation and assess the time and effectiveness of work in similar conditions. [ABSTRACT FROM AUTHOR]

Multi-stakeholder participation processes in watershed management face challenges due to limited monitoring and baseline data, resulting in a lack of awareness among stakeholders about the current state of the watershed. This knowledge gap often leads to conflicts of interest, wherein the broader impacts of individual decisions are overlooked. To overcome these limitations, this paper explores the design and implementation of a Serious Game (SG) aimed at coproducing a watershed management plan at the basin scale within the specific context of the Campoalegre River basin in Colombia. By providing an interactive platform, the SG facilitates collaboration between local actors, who may be unfamiliar with existing watershed plans, and decision-makers. The goal is to create a participatory space where stakeholders can comprehend the watershed management plan structure and prioritize actions based on various climatic, social, and economic conditions. Following the application of the SG, stakeholders demonstrated an improved understanding of the basin, fostering increased participation, open debate, and the proposal of actions. These outcomes serve as valuable inputs for the implementation of water management planning policies, showcasing the potential of SGs in bridging knowledge gaps, and fostering effective multi-stakeholder engagement. [ABSTRACT FROM AUTHOR]

Traditional univariate drought indices may not be sufficient to reflect comprehensive information on drought. Therefore, this paper proposes a new composite drought index that can comprehensively characterize meteorological and hydrological drought. In this study, the new drought index was established by combining the standardized precipitation index (SPI) and the standardized baseflow index (SBI) for the Jiaojiang River Basin (JRB) using the copula function. The prediction model was established by training random forests on past data, and the driving force behind the combined drought index was explored through the LIME algorithm. The results show that the established composite drought index combines the advantages of SPI and SBI in drought forecasting. The monthly and annual droughts in the JRB showed an increasing trend from 1991 to 2020, but the temporal characteristics of the changes in each subregion were different. The accuracies of the trained random forest model for heavy drought in Baizhiao (BZA) and Shaduan (SD) stations were 83% and 88%, respectively. Furthermore, the Local Interpretable Model-Agnostic Explanations (LIME) interpretation identified the essential precipitation, baseflow, and evapotranspiration features that affect drought. This study provides reliable and valid multivariate indicators for drought monitoring and can be applied to drought prediction in other regions. [ABSTRACT FROM AUTHOR]

Pyrite is an important proxy used to reflect the redox state of a sedimentary environment. Currently available studies on pyrite focus on the process of sulfur cycles between an ocean and sediment. However, our understanding of the biogeochemical cycle of sulfur in terrestrial lake basins remains unclear, and the growth patterns of different types of pyrite are poorly understood. In this paper, we used samples from the 34 section of the Qianjiang depression in the Jianghan Basin as direct research objects by combining pyrite and sulfur isotope determination. The one-dimensional diffusion–advection–reaction simulation (1D-DAR) model was applied to simulate the changes in the pyrite content and sulfur isotope values in the sediment. The results show that the sediments in the saline lake basin environment contain a high organic matter content, a high sedimentation rate, and a high H2S diffusion oxidation rate, reflecting the strong reducing background and high productivity of this ancient lake. Sensitivity tests revealed that the organic matter content and H2S diffusion oxidation rate at the sediment–water interface are sensitive to the pyrite content. The sedimentation rate, organic matter content, and sulfate concentration are sensitive to the pyrite's sulfur isotope values. However, the variation in the active iron content had little effect on the pyrite content or sulfur isotope value. [ABSTRACT FROM AUTHOR]

There have been several incidences of flood recently, which are believed to be aggravated by increased climatic variables as a result of perceived changes in climatic conditions (due to climate change) in the Cross River Basin. The basin is the most extensively developed and used river basin in the management of the water resources of the Cross River and Akwa Ibom States in Nigeria. In this paper, 30 years (from 1992 to 2021) of hydro-meteorological data (annual average rainfall, maximum and minimum temperatures, hu midity, duration of sunlight (sunshine hours), evaporation, wind speed, soil temperature, cloud cover, solar radiation, and atmospheric pressure) from four stations in the Cross River Basin were obtained from the Nigerian Meteorological Agency (NIMET), Abuja and subjected to trend detection analysis using the Mann–Kendall test to determine the trend in climatic parameters. The results indicate that there is a significant upward trend in annual rainfall in Ogoja but a downward trend in Calabar. The evaporation trend is significantly downward in Eket, whereas in Calabar, there is an upward trend in solar radiation. Generally, there is a significant rise in annual maximum temperature across the basin. Serial correlation and segmented regression analyses were performed to measure the impact of fluctuations in monthly and long-term Tahiti and Darwin's Sea level pressures on the climatic variables at the Cross River Basin catchment. These analyses were necessary to determine the extent of the influence of the El Nino Southern Oscillation climatic cycle. The analyses show no significant association between the El Niño Southern Oscillation (ENSO) and rainfall or between the ENSO and runoff in the catchment. This implies that the impact of the ENSO on rainfall and runoff in the Cross River Basin catchment is not considerable. The intercepts derived from the segmented regression in Eket and Ogoja show significant positive trends in both areas for rainfall and runoff. The trends in intercepts suggest that there are external factors influencing rainfall and runoff other than ENSO events, thus strengthening the assertion of climate change. Results from this study will facilitate the understanding of the variability in climatic parameters by stakeholders in the basin, researchers, policymakers, and water resource managers. [ABSTRACT FROM AUTHOR]

The increasing incidence of retrogressive thaw slumps (RTSs) in permafrost regions underscores the need for detailed spatial and temporal analysis using InSAR technology to monitor and predict dynamic changes in the process of RTSs. Nevertheless, current InSAR deformation forecasting methods employing deep learning strategies such as the traditional long short-term memory (LSTM) and recent transformer models encounter difficulties in effectively capturing temporal features. Moreover, they are limited in their ability to directly integrate spatial information. In this paper, an innovative deep learning approach named Spacetimeformer is proposed for predicting medium- and short-term InSAR deformation of RTSs in the Chumar River area. This method employs a transformer architecture with a spatiotemporal attention mechanism, which enhances the long-term prediction capabilities of time series models and dynamic spatial modeling. It is applicable to multivariate InSAR spatiotemporal deformation prediction problems. The findings include a list of 72 RTSs compiled based on derived InSAR deformation maps and Sentinel-2 optical images, of which 64 have an average deformation rate exceeding 10 mm/year, indicating signs of permafrost degradation. The density distribution of the displacement maps predicted by the Spacetimeformer model aligned well with the InSAR deformation maps obtained from the small baseline subset (SBAS) method, with the overall prediction deviation controlled within 20 mm. In addition, the point-scale prediction results were compared with LSTM and transformer models. This study indicates that the Spacetimeformer network achieved good results in predicting the deformation of RTSs, with a root mean square error of 1.249 mm. The Spacetimeformer method for deformation prediction with the spacetime mechanism presented in this study can serve as a general framework for multivariate deformation prediction based on InSAR results. It can also quantitatively assess the spatial deformation characteristics and deformation trends of RTSs. [ABSTRACT FROM AUTHOR]

This paper presents a method to analyze and improve the set of equations constituting a rainfall‐runoff model structure based on a combination of a data assimilation algorithm and polynomial updates to the state equations. The method, which we have called "Data Assimilation Informed model Structure Improvement" (DAISI) is generic, modular, and demonstrated with an application to the GR2M model and 201 catchments in South‐East Australia. Our results show that the updated model generated with DAISI generally performed better for all metrics considered included Kling‐Gupta Efficiency, NSE on log transform flow and flow duration curve bias. In addition, the elasticity of modeled runoff to rainfall is higher in the updated model, which suggests that the structural changes could have a significant impact on climate change simulations. Finally, the DAISI diagnostic identified a reduced number of update configurations in the GR2M structure with distinct regional patterns in three sub‐regions of the modeling domain (Western Victoria, central region, and Northern New South Wales). These configurations correspond to specific polynomials of the state variables that could be used to improve equations in a revised model. Several potential improvements of DAISI are proposed including the use of additional observed variables such as actual evapotranspiration to better constrain internal model fluxes. Plain Language Summary: This paper presents a data‐driven method to improve rainfall‐runoff models used to generate future water resources scenario in climate change studies. The method, which we have called "Data Assimilation Informed model Structure Improvement" (DAISI) is generic, modular, and demonstrated with an application to monthly streamflow simulations over a large data set of catchments in South‐East Australia. Our results show that DAISI improves model performance for a wide range of metrics and increases the sensitivity of the model to climate inputs, which is critical in climate change scenarios. Finally, the improvements identified by DAISI take a simple mathematical form with distinct regional patterns in three sub‐regions of the study domain (Western Victoria, central region, and Northern New South Wales). Several improvements of DAISI are discussed including the inclusion of additional observed variables such as evapotranspiration to better constrain model simulations. Key Points: Data Assimilation Informed model Structure Improvement method diagnoses hydrological model structures by combining data assimilation with a polynomial update of state equationsThe method was applied to the GR2M rainfall‐runoff model with significantly improved streamflow simulations in 201 Australian catchmentsThe method identified updates to state equations with marked regional characteristics that could guide future improvement of GR2M [ABSTRACT FROM AUTHOR]

Introduction: The Gansu section of the Yellow River Basin is an important water resource conservation and replenishment area for the entire Yellow River Basin. With urbanization and socio-economic development, it is urgent to study the characteristics of land-use change and its future simulation in order to realize the coordinated ecological and economic development. Methods: Based on the patch-generating land-use simulation (PLUS) model, this paper investigated the main drivers of land-use type expansion with a comprehensive consideration of natural and socio-economic aspects; moreover, the study simulated land-use change in 2030 under the four scenarios of natural development, cultivated land protection, ecological priority, and economic construction. Results: The results showed the following: 1) the prediction of land-use types continued the historical evolution since 1980. Grassland, cultivated land, and forest land were still the dominant land types, accounting for more than 87% of the basin's total area. Water bodies and wetlands remained relatively stable, and there was an obvious increase of approximately 20% in construction land. 2) Construction land and grassland were primarily driven by the social factor of the distance from the primary road and the distance from the secondary road, respectively. The cultivated land was greatly affected by the economic factor of population density. 3) The cultivated land protection scenario was the only one of the four scenarios that could make the cultivated land area increase positively, with an increase rate of 0.5%. This scenario also restricted effectively the conversion of cultivated land into construction land. The ecological priority scenario can expand grassland obviously with a proportion of 1.82% and slow down oasis desertion. The economic construction scenario can increase the construction land area the most by a rate of 25.5% to accelerate the economic development of specific regions in the study area. Discussion: Therefore, implementing policies on the basis of choosing suitable scenarios in different areas was significant for optimizing the land-use structure, promoting the efficient use of land resources and ecological environment in the Gansu section of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Wildfires pose one of the greatest threats to the world's forests soils. After exposure to fire, forests lose many of their ecological functions; moreover, the repercussions can extend well beyond the forest itself, as the erosive processes attributable to the combustion of vegetation and the soil's lack of protection against rainfall are likely to impact any areas of a catchment, contaminating reservoirs, estuaries and aquifers. A forest fire is not solely, therefore, an environmental issue, but also a social and economic problem. The recovery of a forest is heavily dependent on just how the soil has been affected and how rapidly the latter can be restored. Fire intensity is critical in understanding the temporal evolution of the forest, while its location--a clear determinant of its climate and the ecosystem it occupies--can undermine the functionality of the forest system and is critical in determining the duration of the effects of the fire episode. This paper undertakes a review of the literature with the aim of understanding what might be understood when studies speak of the long-term effects of fire on the soil and when a soil might be considered to have recovered from these effects. What is evident is that many variables have a role to play and that not all soil properties recover at the same rate; indeed, some may never be restored to pre-fire levels. [ABSTRACT FROM AUTHOR]

Sand boil formation at the toe of river embankments is the typical manifestation of the initiation and progression of an internal erosion process known as backward erosion piping, which is recognized to be a major concern in many river systems worldwide. In Italy, more than 130 sand boils have been detected along the Po River, many of them experiencing recurrent reactivations during high-water events. In recent years, as part of the activities of the European project LIFE SandBoil, the Italian authority responsible for flood protection and flood damage reduction along the Po River has implemented a GIS-based web application to catalogue the sand boils observed in its operating area. The resulting database allows keeping records of a comprehensive and varied set of information, in terms of predisposing factors, initiation conditions and surface effects. Taking as a reference a well-documented cross-section of the Po River prone to piping, this paper describes the main features of this versatile and flexible tool, whose long-term aim is to support vulnerability studies and the development of risk maps against piping. The database, which might also accommodate data from different river basins, is thus meant to help in flood risk management, by suggesting priorities for the implementation of mitigation measures and allowing the monitoring of intervention effectiveness. [ABSTRACT FROM AUTHOR]

With a huge capital and labor input influx, inter-basin water transfer (IBWT) projects have been shown to effectively mitigate water stress and ensure the water demand for social and economic development in the receiving area. Whether they have promoted the improvement of regional water use efficiency (WUE) is crucial for sustainable management of regional water resources. Targeting the South-to-North Water Transfer Project (SNWTP), the largest and most ambitious inter-basin water transfer project in China, this study establishes quantitatively econometric models to analyze the impact of different water diversion projects, specifically the eastern route of the SNWTP (ER-SNWTP), middle route of the SNWTP (MR-SNWTP), and diversion from the main stream of the Yellow River (DYR), on the regional water consumption per unit of GDP; regional water stress, water use structure, economic structure, and urbanization level are used as control variables in different types of cities in the Yellow River Basin, and some intriguing results are found. While the overall water transfer project demonstrates a positive impact on water use efficiency, the effects of the three water transfer measures vary significantly. The ER-SNWTP does not exhibit a notable positive effect on regional water use efficiency, whereas the MR-SNWTP demonstrates a significant positive impact. Interestingly, the DYR has a notable negative influence on water use efficiency in developed cities. The water use structure, shaped by the pricing, scale, and policies of different projects, emerges as a pivotal factor in explaining these differences. Finally, this paper suggests that the impact of water transfer projects on the improvement of regional water use efficiency be viewed from a more comprehensive and developmental perspective. [ABSTRACT FROM AUTHOR]

Rain gardens are used to solve urban problems related to the negative impact of stormwater. (1) Scientific contributions from different countries provide general guidelines for the design and operation of rain gardens in different geographical areas. Given the small spatial scale of rain gardens, the use of existing infiltration models often leads to design errors. (2) The purpose of this paper is to develop a hydrological model by introducing a system of equations that extends the ability to calculate the rate, flow rate and time of saturation of layers with moisture and rainwater leakage from the rain garden system. (3) The results obtained allow us to describe the dynamic processes of passage and saturation of layers of the rain garden at a certain point in time, which extends the ability to calculate the flow rate. It was established that the smaller the area of the rain garden compared to the area of the catchment basin, the faster it reaches its full saturation. Increasing the thickness of the rain garden layers allows for an increase in the efficiency of water retention at a lower value of the area ratio. (4) The practical significance of the results obtained is especially important for the correct description of hydrodynamics in the system and determining the optimal conditions for the effective functioning and management of the rain garden structure for any climatic region. [ABSTRACT FROM AUTHOR]

Shallow-water deltas are a subject of sedimentary research and represent a significant target for oil and gas exploration. The Yanchang Formation of the Triassic in the Ordos Basin comprises numerous shallow-water delta blocks. This paper addresses the core issues pertaining to the sedimentary facies, sedimentary characteristics and sand body distribution of the Chang 9 oil layer formation of the Upper Triassic in the Ordos Basin. Guided by the relevant theories and methods of contemporary sedimentology and sedimentary geology, the reservoir characteristics are described and studied in detail through ordinary thin sections, cast thin sections, graphical representations of particle size and scanning electron microscopy experiments. The experimental results indicate that the porosity in the study area ranges from 3% to 12% and that the permeability is between 0 and 1.5 × 10−3 μm2, which is consistent with classification as an ultra-low-porosity and ultra-low-permeability reservoir. The Chang 9 sandstone is composed of feldspar sandstone and lithic feldspar sandstone. The average content of quartz is low, at less than 31%, while the average content of feldspar is high, at more than 34%. The average content of rock debris is between 10% and 20%. Therefore, the compositional maturity of the Chang 9 sand body is generally low. The particle size distribution exhibits a positive deviation, indicating that the sediments in the sand body are primarily coarse-grained components. The kurtosis of the particle size–frequency curve is observed to vary from flat to very sharp. The Chang 91 lake is classified as a shore shallow lake with basin subsidence and lake transgression. The Chang 9 period saw the development of the Chang 91 sedimentary facies into a semi-deep lake–deep lake environment. The vertical structural style of the Chang 9 oil layer formation in the basin can be roughly summarized into three basic structural types: the sedimentary structures observed in the area include box-shaped upward thinning, bell-shaped upward thinning and funnel-shaped upward thickening. The delta front area in Chang 9 is notable for its size and the prevalence of underwater distributary channel microfacies. The sand body distribution is stable, with sand layer thicknesses ranging from 15 to 30 m. The evaluation and summary of the sedimentary characteristics of the Chang 9 oil layer formation provide a geological basis for future exploration and development in the study area. [ABSTRACT FROM AUTHOR]

Global hydrological models enhance our understanding of the Earth system and support the sustainable management of water, food and energy in a globalized world. They integrate process knowledge with a multitude of model input data (e.g., precipitation, soil properties, and the location and extent of surface waterbodies) to describe the state of the Earth. However, they do not fully utilize observations of model output variables (e.g., streamflow and water storage) to reduce and quantify model output uncertainty through processes like parameter estimation. For a pilot region, the Mississippi River basin, we assessed the suitability of three ensemble-based multi-variable approaches to amend this: Pareto-optimal calibration (POC); the generalized likelihood uncertainty estimation (GLUE); and the ensemble Kalman filter, here modified for joint calibration and data assimilation (EnCDA). The paper shows how observations of streamflow (Q) and terrestrial water storage anomaly (TWSA) can be utilized to reduce and quantify the uncertainty of model output by identifying optimal and behavioral parameter sets for individual drainage basins. The common first steps in all approaches are (1) the definition of drainage basins for which calibration parameters are uniformly adjusted (CDA units), combined with the selection of observational data; (2) the identification of potential calibration parameters and their a priori probability distributions; and (3) sensitivity analyses to select the most influential model parameters per CDA unit that will be adjusted by calibration. Data assimilation with the ensemble Kalman filter was modified, to our knowledge, for the first time for a global hydrological model to assimilate both TWSA and Q with simultaneous parameter adjustment. In the estimation of model output uncertainty, we considered the uncertainties of the Q and TWSA observations. Applying the global hydrological model WaterGAP, we found that the POC approach is best suited for identifying a single "optimal" parameter set for each CDA unit. This parameter set leads to an improved fit to the monthly time series of both Q and TWSA as compared to the standard WaterGAP variant, which is only calibrated against mean annual Q , and can be used to compute the best estimate of WaterGAP output. The GLUE approach is almost as successful as POC in increasing WaterGAP performance and also allows, with a comparable computational effort, the estimation of model output uncertainties that are due to the equifinality of parameter sets given the observation uncertainties. Our experiment reveals that the EnCDA approach performs similarly to POC and GLUE in most CDA units during the assimilation phase but is not yet competitive for calibrating global hydrological models; its potential advantages remain unrealized, likely due to its high computational burden, which severely limits the ensemble size, and the intrinsic nonlinearity in simulating Q. Partitioning the whole Mississippi River basin into five CDA units (sub-basins) instead of only one improved model performance in terms of the Nash–Sutcliffe efficiency during the calibration and validation periods. Diverse parameter sets achieved comparable fits to observations, narrowing the range for at least three parameters. Low coverage of observation uncertainty bands by GLUE-derived model output bands is attributed to model structure uncertainties, especially regarding artificial reservoir operations, the location and extent of small wetlands, and the lack of representation of rivers that may lose water to the subsurface. These uncertainties are also likely to be responsible for significant trade-offs between optimal fits to Q and TWSA. Calibration performed exclusively against TWSA in regions without Q observations may worsen the Q simulation as compared to the uncalibrated model variant. We recommend that modelers improve the realism of the output of global hydrological models by calibrating them against observations of multiple output variables, including at least Q and TWSA. Further work on improving the numerical efficiency of the EnCDA approach is necessary. [ABSTRACT FROM AUTHOR]

In this paper, we analysed the temporal and spatial distributions of ancient archaeological sites in China as well as their influencing factors. Our aim was to reveal the developmental trajectory of Chinese civilisation and to explore the natural and cultural factors affecting human distribution, with the goal of providing insights for the conservation and development of ancient relics. We employed spatial analysis methods using ArcGIS 10.8 software, such as kernel density analysis and trend surface analysis, to analyse 1194 historical ancient sites listed in the National Cultural Relics Protection Units of China. The research findings are as follows: (1) the distribution of ancient sites demonstrates an agglomerative spatial pattern. The nearest neighbour index (R < 1) for sites from various historical periods indicates an agglomerative spatial distribution of ancient sites across historical periods, with the clustering degree being relatively poor for sites from the Wei-Jin, Northern and Southern Dynasties and in the Ming and Qing periods. The regions with a concentration of ancient sites are the middle and lower reaches of the Yangtze River and Yellow River Basins. Furthermore, there is a higher abundance of ancient sites in the southeastern region than in the northwestern region. (2) The distribution of ancient sites in different historical periods also exhibits an imbalance, with an overall decreasing trend in the number of ancient sites in China. Notably, more ancient sites were found for the prehistoric and pre-Qin periods. The temporal trend of ancient sites during historical periods follows a trajectory from northeast to northwest, northeast to southwest, etc. (3) The temporal and spatial distributions of ancient sites are influenced by multiple factors, including social development, the natural environment, geographical elements, and socioeconomic and political factors. Finally, based on an understanding of the spatiotemporal distribution pattern of ancient sites and the factors that influence this pattern, recommendations for conservation and development can be proposed and supported by modern technological methods, with the aim of offering insights for the protection and sustainable development of heritage sites. [ABSTRACT FROM AUTHOR]

In many countries, the advancement of hydropower resources has been hindered by economic factors and insufficient data on topography, streamflow, environmental sensitivity, power grid, and, most importantly, the location of potential hydropower sites. This challenge is particularly pronounced in certain African and Latin American river systems. Developing web-based maps of hydropower resources based on geographic information systems and advanced mapping technologies can facilitate the initial assessment of hydropower sites. This is especially relevant for developing sites in remote areas and data-scarce regions. The available geospatial datasets, remote sensing technologies, and advanced GIS modelling techniques can be used to identify potential hydropower sites and assess their preliminary characteristics. This paper reviews web-based hydropower atlases in African and Latin American countries. Their main features are represented and compared with the recently launched HYPOSO map viewer covering two African countries (Cameroon and Uganda) and three Latin American countries (Bolivia, Colombia, and Ecuador). This hydropower atlas consists of 20 spatial layers. Its particular focus is to present a geospatial dataset of new hydropower sites with concise information for potential investors. These so-called virtual hydropower atlases can be only one type of discovery at the early project stage, automatically identifying sites worthy of further investigation. A formal validation of the web-based atlases, including the HYPOSO hydropower atlas, is briefly considered. Creating open-access hydropower map viewers is anticipated to significantly enhance the hydropower development database in these nations, offering valuable insights for small and medium-scale projects. [ABSTRACT FROM AUTHOR]