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The renewable-dominant hybrid generation systems (HGSs) are increasingly important to the electric power system worldwide. However, influenced by uncertain meteorological factors, the operational robustness of HGSs must be evaluated to inform the associated decision-making. Additionally, the main factors affecting the HGS's robustness should be urgently identified under deep uncertainties, as this provides valuable guidance for HGS capacity configuration. In this paper, a multivariate stochastic simulation method is developed and used to generate uncertain resource scenarios of runoff, photovoltaic power, and wind power. Subsequently, a long-term stochastic optimization model of the HGS is employed to derive the optimal operating rules. Finally, these operating rules are used to simulate the long-term operation of an HGS, and the results are used to evaluate the HGS's robustness and identify its main sensitivities. A clean energy base located in the Upper Yellow River Basin, China, is selected as a case study. The results show that the HGS achieves greater operational robustness than an individual hydropower system, and the robustness becomes weaker as the total capacity of photovoltaic and wind power increases. Additionally, the operational robustness of the HGS is found to be more sensitive to the total capacity than to the capacity ratio between photovoltaic and wind power. [ABSTRACT FROM AUTHOR]

Landslides are common natural disasters that cause serious damage to ecosystems and human societies. To effectively prevent and mitigate these disasters, an accurate assessment of landslide hazards is necessary. However, most traditional landslide hazard assessment methods rely on static assessment factors while ignoring the dynamic changes in landslides, which may lead to false-positive errors in the assessment results. This paper presents a novel landslide hazard assessment method for the Zagunao River basin, China. In this study, an updated landslide inventory was obtained for the Zagunao River basin using data from interferometric synthetic aperture radar (InSAR) and optical images. Based on this inventory, a landslide susceptibility map was developed using a random forest algorithm. Finally, an evaluation matrix was created by combining the results of deformation rates from both ascending and descending data to establish a hazard level that considers surface deformation. The method presented in this study can reflect recent landslide hazards in the region and produce dynamic assessments of regional landslide hazards. It provides a basis for the government to identify and manage high-risk areas. [ABSTRACT FROM AUTHOR]

Ponds constitute a pivotal component of aquatic ecosystems. The aquatic ecosystem of the Huai River Basin (HRB) in China was once damaged by severe pollution, and numerous ponds in the basin have not been secured. In this paper, Shenqiu County, a typical county in HRB with many ponds, is selected. Based on high-resolution images with ALOS in 2010, GF-2 in 2016, and GF-1 in 2022, we employed discriminant analysis (DA), classification and regression tree, support vector machine, and random forest to extract the ponds based on object-oriented and further analyzed the spatial-temporal variations of the ponds in this county. The results of the DA in these three years exhibited a higher kappa coefficient (>0.7), and overall accuracy (>75%), signifying superior performance when compared to the other three methods. There were 4625, 5315, and 4748 ponds in 2010, 2016, and 2022, with a total area of 12.87, 11.99, and 9.37 km2, respectively. The number of ponds had a trend of rising in the initial period (2010–2016) and falling later (2016–2022), while the total area revealed a continuous decline. Meanwhile, these ponds showed a clustering phenomenon with three main clustering areas, and the scope of the clustering areas also changed to a certain extent from 2010 to 2022. Our study offers valuable methodological support for the ecological monitoring and management of water environments in regions characterized by a dense concentration of ponds. The crucial data related to ponds in this study will help inform both environmental and social development initiatives within the area. [ABSTRACT FROM AUTHOR]

Ampelopsis grossedentata (AG) is mainly distributed in Chinese provinces and areas south of the Yangtze River Basin. It is mostly concentrated or scattered in mountainous bushes or woods with high humidity. Approximately 57 chemical components of AG have been identified, including flavonoids, phenols, steroids and terpenoids, volatile components, and other chemical components. In vitro studies have shown that the flavone of AG has therapeutic properties such as anti-bacteria, anti-inflammation, anti-oxidation, enhancing immunity, regulating glucose and lipid metabolism, being hepatoprotective, and being anti-tumor with no toxicity. Through searching and combing the related literature, this paper comprehensively and systematically summarizes the research progress of AG, including morphology, traditional and modern uses, chemical composition and structure, and pharmacological and toxicological effects, with a view to providing references for AG-related research. [ABSTRACT FROM AUTHOR]

The Qinghai–Tibet Plateau is the highest and largest permafrost area in the middle and low latitudes of China. In this region, permafrost thaw settlement is the main form of expressway subgrade disaster. Therefore, the quantitative analysis and regionalization study of permafrost thaw settlement deformation are of great significance for expressway construction and maintenance in the Qinghai–Tibet region. This paper establishes a thaw settlement prediction model using the thaw settlement coefficient and thaw depth. The thaw depth was predicted by the mean annual ground temperatures and active-layer thicknesses using the Radial Basis Function (RBF) neural network model, and the thaw settlement coefficient was determined according to the type of ice content. Further, the distribution characteristics of thaw settlement risk of the permafrost subgrade in the study region were mapped and analyzed. The results showed that the thaw settlement risk was able to be divided into four risk levels, namely significant risk, high risk, medium risk and low risk levels, with the areas of these four risk levels covering 3868.67 km2, 1594.21 km2, 2456.10 km2 and 558.78 km2, respectively, of the total study region. The significant risk level had the highest proportion among all the risk levels and was mainly distributed across the Chumar River Basin, Beiluhe River Basin and Gaerqu River Basin regions. Moreover, ice content was found to be the main factor affecting thaw settlement, with thaw settlement found to increase as the ice content increased. [ABSTRACT FROM AUTHOR]

Using data from 56 tight gas wells from the study field (Y field) in the Ordos basin of China, this paper presents performance-based reservoir characterization of the study field from production data and geophysical data. Post-fracturing evaluation is realized by applying our new modified production decline type curves for fractured wells. Compared to traditional type curves, our newly proposed modified dimensionless type curves help identify field data diagnostics for various flow regimes of fractured wells and also facilitate the curve matching process with real data to obtain fruitful and crucial reservoir and fractured well information, including key parameters such as reservoir flowing capacity (kh), well productivity, fracture length, drainage area and original gas in place. This paper intends to promote the extensive application of this new technique. With the support of the reservoir information provided by production decline analysis using our modified type curves, the commercial flow units are delineated in terms of interrelated porosity-permeability of sandstone based on pore throat aperture crossplotting and corresponding flow unit productivity. Furthermore, two crossplots of well logging interpreted porosity versus resistivity are constructed, suggesting their good correlated relationships with relative flow unit productivity and initial gas abundance in place, respectively. The two crossplots enable qualitative evaluation of formation penetrated by well, which makes them very useful and practical as wireline logging is basically available for every well. The well production routine is also analyzed systematically by considering a well's inflow performance, tubing performance and minimal liquid-carrying gas flow rate to investigate if a gas well is producing at optimal conditions or if a measure should be taken to improve the well's production. Through analysis of the Y field, this study introduces an integrated workflow with the support of the new modified type curves to effectively help understand the reservoir characteristics and the flow behaviors of the tight gas field. The key takeaway from this study is that the new modified dimensionless production decline curves in terms of q D M   v s.   t D M can be applied in field practice to achieve a systematically comparable understanding of the performance of MHFHWs globally. [ABSTRACT FROM AUTHOR]

China's Yangtze River Basin has an increasingly strong demand for crude oil. As a seaborne import port for crude oil, Ningbo-Zhoushan Port is under pressure to undertake the transshipment of crude oil to various oil terminals in the Yangtze River Basin. To alleviate the stress of crude oil transportation in Ningbo-Zhoushan Port, the port operator proposed the crude oil sea–river transshipment scheme in Nantong Port. Therefore, this paper aims to verify the feasibility of this scheme. We used the discrete event system modeling and entity relationship diagram method to construct the hierarchical and concept models of the Yangtze River Basin's crude oil sea–river transportation system. Furthermore, we developed corresponding simulation modules on the Witness platform and carried out a simulation experiment of the crude oil sea–river transfer scheme. In the experiment, we analyzed the influence of the transshipment ratio on berth utilization, waiting time, and sailing time of other ports by adjusting the parameter of the transshipment ratio. The experimental results show that when the transshipment rate reaches 100%, the utilization rates of loading and unloading berth in Nantong Port are 4% and 13%, respectively, which evidences that Nantong Port has transshipment potential. At the same time, the simulation experiment's statistical indicators, such as the utilization rate of oil berths, the queuing time of oil tankers, and the sailing time, not only confirm the feasibility of the crude oil sea–river transshipment scheme of Nantong Port but also confirm that the scheme is helpful to improve crude oil transportation efficiency. The simulation results benefit the port operation decision, and the established model and simulation module can be encapsulated and reused. [ABSTRACT FROM AUTHOR]

The Tarim River Basin (TRB) is situated in the hinterland of northwest China, which is an extremely arid and fragile ecological zone. In recent years, the region's ecological civilization construction has been facing huge challenges that are exacerbated by climate change and human activities. In order to verify the current ecological status of TRB, this paper explores the spatial and temporal variation in ecosystem service value (ESV) and the impact mechanism based on LUCC data from 2000 to 2020, using the adjusted unit area value equivalent method, the elasticity index method and the geo-probe analysis method. The results show that: (1) the ESV of the TRB has fluctuated since 2000, increasing by CNY 14.02 billion, especially in the Hotan River region. Among the individual ecosystem services, the increase in regulatory services is the largest, rising to CNY 8.842 billion. The growth of ESV mostly occurred in the mountains and oases. (2) The rise in ESV is mainly due to the conversion of barren land to water and grassland; ESV loss is mainly affected by the conversion of water to cropland and barren land and grassland to cropland and barren land. (3) Human activity impact or intensity (HAI) is the key driving factor for the spatial stratified heterogeneity of ESV, followed by elevation (DEM). In the interaction analysis, HAI∩DEM interaction is the primary reason for ESV's spatial differentiation. The study's findings show that the combined effects of human activities, DEM, and hydrothermal conditions underlie the spatial stratified heterogeneity of ESV in the TRB. This conclusion provides a scientific basis for future ecological civilization construction planning. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, we describe the well-preserved fossil seed cones of Nothotsuga found in the Mula Basin, Litang County, Sichuan Province, southwestern China. By detailed morphological comparisons, a new fossil species, Nothotsuga mulaensis Z. Li et J. L. Dong sp. nov. is named. This discovery suggests that Nothotsuga had a more northern distribution during the Miocene. In addition, it suggests that the Mula region had a humid and warm climate during this period. The ancient landform presents an intermountain lake basin, which would have been surrounded by higher mountains. After the Miocene, due to the uplift of the Tibetan Plateau, Nothotsuga was either unable to adapt to the extinction of the local environmental or was able to migrate to several scattered places in southern China. In this paper, we describe a new fossil species, Nothotsuga mulaensis Z. Li & J.L. Dong sp. nov. The discovery of the fossil species was based on well-preserved fossil seed cones that were found in the Mula Basin in Xiamula village, Litang County, Sichuan Province, southwestern China. The shapes of these fossils were characterized by ovate seed cones, rhombic or suborbicular scales with auriculate bases, and the bracts were ligulate-spathulate in shape. This finding suggests that Nothotsuga once had a wide distribution range in China and that it also inhabited the eastern Tibetan Plateau (TP). Nothotsuga mulaensis was distributed in an intermountain lake basin, at altitudes from 2000 to 2300 m, in a warm and humid environment. This finding also suggests that the eastern TP may have provided good habitat for Nothotsuga during the Miocene. In addition, we propose that the uplift, accompanied by the severe cooling and aridification that occurred after the Miocene, caused the disappearance of this species of Nothotsuga in the eastern TP. [ABSTRACT FROM AUTHOR]

To protect and restore this downstream ecosystem, the Tarim River Basin Administration Bureau (TBAB) initiated the Ecological Water Compensation (EWC) project from 2000 to 2018. Revealing the mechanism of vegetation-hydroecological response processes in the lower reaches of the Tarim River before and after EWC work is conducive to water resource planning, utilization and protection. In this paper, the spatiotemporal responses of vegetation and groundwater to EWC were examined at the points, lines, and area (PLA) scale by coupling remote sensing techniques and field station observation data collected between 2000 and 2017. The findings indicated that (1) In general, the regional fractional vegetation coverage (FVC) increased significantly, and the average FVC growth rate was 3.5%/year from 2000 to 2017 (R2 > 0.84, p < 0.01, 2-tailed). (2) The regional vegetation restoration process showed obvious fluctuations and stage characteristics, but the spatial scope of the significantly increased vegetation area was limited. Plants grew rapidly within 10 km of the river, while 10 km away from the water channel, no obvious change was observed. (3) Strong coupling relationships were identified among the FVC growth, EWC volume and groundwater depth variations (p < 0.05, 2-tailed). The response times of the regional vegetation and groundwater depth to EWC indicated one-year lags. The above results imply that the regional ecological environment was significantly improved over the study period, thus confirming that the EWC project made remarkable accomplishments. However, the effect of ecological restoration is not sufficiently stable at present. Vegetation restoration has mainly been centralized around the river channel and is greatly dependent on the annual EWC volume. In addition, the local conditions begin to degrade soon after an EWC project is terminated, and vice versa; when EWC commences, the FVC immediately begins to improve. Therefore, the current EWC achievements need to be further consolidated and strengthened in the future. [ABSTRACT FROM AUTHOR]

The Carboniferous–Triassic period was an important stage of global sea–land transformation, with coal formation in the Carboniferous, biological extinction at the end of the Permian, and global drought in the Triassic. The MS-1 well in the Mosuowan High of the Junggar Basin is the deepest well drilled in Northwestern China. In this paper, we investigate the sedimentary environment and climate evolution of the Mosuowan area in the central Junggar Basin during the Late Carboniferous–Early Permian by the petrothermal, lipid biomarker, and isotopic composition of mud shale core samples, and explore the tectonic–climatic events and Central Asian orogenic belt evolution driving the sedimentary environment. The study shows that the organic matter from the Upper Carboniferous to the Lower Permian is at a mature stage, but biomarkers maintained the primary information although the organic matter was subjected to thermal evolution. In the late Carboniferous period (Tamugan Formation), the study area was a closed remnant sea with a relatively humid climate, triggering lush terrestrial vegetation and high organic carbon content in the sediments, which had the potential to evolve into natural gas. During the Xiazijie Formation of the Middle Permian, tectonic activity shifted to the subsidence period, and the salinity of the water decreased after a large input of fresh water. The lake basin area expanded, and the content of aquatic organisms continued to increase. As the Lower Permian stratigraphy is missing, this sea–land transition seems to jump. The low and upper Urho Formations of the Middle–Upper Permian are a deltaic foreland deposit, and geochemical indicators show an overall lake retreat process with a continuous increase in organic matter content of terrestrial origin. The lithologic assemblage of the Triassic Baikouquan Formation is braided river deltaic sedimentation with migration of deposition centers of the lake basin. In conclusion, the Late Carboniferous–Early Permian period was influenced by global changes, Paleo-Asian Ocean subduction, and continental splicing, which resulted in a continuous increase in terrestrial organic matter, water desalination, and oxidation-rich sediments in the Mosuowan region, but the P–T biological mass extinction event was not recorded. [ABSTRACT FROM AUTHOR]

Precipitation data from ground-based observatories in the Dongting Lake basin are often missing, resulting in large errors in surface precipitation data obtained by interpolation, which affects the accuracy of hydro-meteorological studies. Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) is the main high-resolution precipitation product, which is available to supplement measured missing data. To evaluate the applicability of this product in the Dongting Lake basin at multiple spatial and temporal scales, this paper analyzes daily, monthly, seasonal, annual, and extreme precipitation events of the three latest IMERG precipitation products (IPPs) (IMERG-F, IMERG-E, and IMERG-L) using eight statistical evaluation metrics. We find that the spatial and temporal performance of IMERG precipitation products varies over different time scales and topographic conditions. However, all three metrics (CC, RMSE, and RB) of the IMERG-F precipitation products outperform the IMERG-E and IMERG-L precipitation products for the same period. In the comparison of IMERG and TRMM (Tropical Rainfall Measuring Mission) precipitation products on monthly and seasonal scales, IMERG-F performed the best. IPPs can capture precipitation more accurately on seasonal scales and perform better in winter, indicating good detection of trace precipitation. Both high and low altitudes are not favorable for the satellite detection of extreme precipitation in both general and extreme precipitation events. Overall, the accuracy of IMERG-F with correction delay is slightly better than that of IMERG-E and IMERG-L without correction under near-real-time conditions, which is applicable in the Dongting Lake basin. However, the correction process also exacerbates overestimation of the precipitation extent. [ABSTRACT FROM AUTHOR]

As the largest inland river basin in China, the Tarim River Basin is an important energy base and a key cotton-producing area in China. Therefore, the harmonious development of water resources, energy resources and cotton resources in the Tarim River Basin is a lifeline for stable quality and efficient development in this region. In this paper, the water–energy–cotton system of the Tarim River Basin is constructed and the weight of each index in the system is determined by using the entropy method. On this basis, the comprehensive development index of each subsystem and the water–energy–cotton system is calculated to measure the comprehensive development level of each system. Then, the coupling relationship between the three resources is quantitatively analyzed by using the coupling coordination degree model, and the mutual influence and strength of interaction between each system are calculated. Finally, a fractional regression model is established to analyze the factors affecting the coordinated development of the water–energy–cotton system in the Tarim River Basin. The results show that the comprehensive development index of the Tarim River Basin fluctuates obviously and the comprehensive development level of water resource systems is higher than that of the cotton resource and energy resource systems, and there are regional differences between each subsystem and the comprehensive development index of water–energy–cotton system. The coupling coordination degree of the basin is the primary coordination on the whole; however, there are significant differences in the coupling coordination degree of each region. In terms of influencing factors, the area of soil erosion treatment and water consumption in ecological environments both play a positive role in promoting the coupling coordination degree, and population size and GDP will hinder the development of the coupling coordination degree to a certain extent. [ABSTRACT FROM AUTHOR]

As the most basic physical geographic elements, basin terrain and river networks have high spatial complexity and are closely related. However, there is little research on the correlation between terrain and river networks. In this paper, the Yellow River Basin was selected as the study area. Topographic factors of multiple dimensions were calculated. The influence of different topographic factors on the river network structure at different scales and their correlation from a multifractal perspective based on geographical detectors and a geographically weighted regression model were determined. The explanatory power of topography on the river network structure at different scales was: multifractal spectrum width > multifractal spectrum difference > slope > average elevation > elevation maximum > elevation minimum, which generally indicated that the topographic factor that has the greatest influence on the river network structure is the complexity and singularity of the terrain. The second-order clustering of regression coefficients from the results of the geographically weighted regression model revealed that the Yellow River basin was divided into three types of high-aggregation areas, which are dominated by the Qinghai-Tibet Plateau, the Loess Plateau, and the Huang-Huaihai Plain, respectively. The clustering results also revealed that the river network structure was affected by different key topographic factors in the different types of areas. This research studies and quantifies the relationship between basin topography and river network structure from a new perspective and provides a theoretical basis for unraveling the development of topography and river networks. [ABSTRACT FROM AUTHOR]

The parameters of hydrological models should be determined before applying those models to estimate or predict hydrological processes. The Xin'anjiang (XAJ) hydrological model is widely used throughout China. Since the prediction in ungauged basins (PUB) era, the regionalization of the XAJ model parameters has been a subject of intense focus; nevertheless, while many efforts have targeted parameters related to runoff yield using in-site data sets, classic regression has predominantly been applied. In this paper, we employed remotely sensed underlying surface data and a machine learning approach to establish models for estimating the runoff routing parameter, namely, CS, of the XAJ model. The study was conducted on 114 catchments from the Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) data set, and the relationships between CS and various underlying surface characteristics were explored by a gradient-boosted regression tree (GBRT). The results showed that the drainage density, stream source density and area of the catchment were the three major factors with the most significant impact on CS. The best correlation coefficient (r), root mean square error (RMSE) and mean absolute error (MAE) between the GBRT-estimated and calibrated CS were 0.96, 0.06 and 0.04, respectively, verifying the good performance of GBRT in estimating CS. Although bias was noted between the GBRT-estimated and calibrated CS, runoff simulations using the GBRT-estimated CS could still achieve results comparable to those using the calibrated CS. Further validations based on two catchments in China confirmed the overall robustness and accuracy of simulating runoff processes using the GBRT-estimated CS. Our results confirm the following hypotheses: (1) with the help of large sample of catchments and associated remote sensing data, the ML-based approach can capture the nonstationary and nonlinear relationships between CS and the underlying surface characteristics and (2) CS estimated by ML from large samples has a robustness that can guarantee the overall performance of the XAJ mode. This study advances the methodology for quantitatively estimating the XAJ model parameters and can be extended to other parameters or other models. [ABSTRACT FROM AUTHOR]

High Mountain Asia (HMA), with its high altitude, widely distributed snow and frozen soil, influences the climate of the northern hemisphere and even the world through thermal balance and the water vapor cycle and is also an indicator of global climate change. The influence of HMA snow cover on its surrounding areas has always been a research hotspot. Taking the Yangtze River Basin (YRB) of China as an example, this paper analyzes the relationship between winter snow depth in HMA and drought and flood in spring and summer in the YRB in the recent 40 years by using Singular Value Decomposition (SVD). The results show that the influence of snow cover on drought and flood in spring is inversely different between eastern and western parts of HMA, while the effect in summer is consistent. When the snow depth is larger (smaller) in the east and smaller (larger) in the west in winter, the YRB is drier (wetter) in spring. When the overall snow depth in HMA is larger (smaller) in winter, the northern part of the middle and lower reaches of the YRB is drier (wetter) in summer. The results provide support for understanding the impact of HMA snow cover on the surrounding climate and some important indicators for drought and flood prediction in the YRB. [ABSTRACT FROM AUTHOR]

Research on precipitation regularity in the past 120 years is an important link in analyzing the precipitation characteristics of watersheds. This paper systematically analyzes the characteristic changes of centennial precipitation data in the Haihe River basin with the help of CRU data, PCI, SPI, and the Pearson type III curve. The results show that the spatial and temporal distribution of precipitation in the Haihe River basin has a more obvious inconsistency. The temporal distribution shows the characteristics of relatively stable in the early period and increasing fluctuation in the later period, the concentration of precipitation gradually decreases, and the overall drought level decreases. The spatial distribution shows a general pattern of gradually decreasing from southwest to northeast, the overall trend of summer precipitation changes from stable to north–south extremes, and the distribution probability of extreme precipitation events in the basin decreases from southeast to northwest, while the drought-prone area transitions from the northeast to the west and southwest of the basin. Under the influence of both climate change and human activities, the seasonal distribution of precipitation tends to be average, the area affected by extreme precipitation rises, and the arid area shifts to the inland area. [ABSTRACT FROM AUTHOR]

Land use/cover change has become an indispensable part of global eco-environmental change research. The Tarim River Basin is the largest inland river basin in China. It is also one of the most ecologically fragile areas in the country, with greening and desertification processes coexisting. This paper analyzes the evolution of land-use/cover change in the Tarim River Basin over the past 30 years based on remote sensing data. The research also explores the contribution of conversion between different land types to the ecological environment by selecting methods, such as transfer matrix and ecological contribution rate. Results indicate that grassland and barren land are the main land types in the region, accounting for 72.46% and 18.87% of the basin area, respectively. From 1990 to 2019, cropland area increased from 33,585.89 km2 to 52,436.40 km2, an increase of 56.13%, while barren land areas decreased from 781,380.57 km2 to 760,783.29 km2. Most of the land-use conversion was grassland to other land types and other land types to barren land. Since 1990, the conversion of barren land to grassland and cropland in the basin has led to ecological improvement, whereas the conversion of grassland to cropland has caused deterioration, but with a generally improving trend. It is anticipated that, over the next decade, changes in land types will involve increases in grassland and woodland area, decreases in barren land and cropland, and an overall improvement in the ecological environment in the watershed. Since agriculture and animal husbandry are the main industries in the Tarim River Basin and the land-use structure is dominated by cropland and grassland, several key measures should be implemented. These include improving land use, rationalizing the use of water and soil resources, slowing down the expansion of cropland, and alleviating the contradiction between humans and land, with the ultimate aim of achieving sustainable development of the social economy and ecological environment. [ABSTRACT FROM AUTHOR]

Landslides, a major natural geohazard, obstruct municipal constructions and may destroy villages and towns, at worst causing significant casualties and economic losses. Interferometric Synthetic Aperture Radar (InSAR) technique offers distinct advantages on landslide detection and monitoring. In this paper, a more systematic workflow is designed for InSAR study of landslides, in terms of three levels: (i) early detection on regional scale, (ii) three-dimensional (3D) surface displacement rates estimation on detailed scale, and (iii) time series analysis on long-term temporal scale. The proposed workflow is applied for landslide research on the Xiaojiang River Basin, China, using ascending and descending Sentinel-1 images acquired from March 2017 to May 2019. First, the landslide inventory has been mapped and updated using InSAR stacking method, supporting geohazard prevention on a regional scale. A total of 22 active landslides are identified, ranging from medium to super large scale. Compared with the existing inventory, three unrecorded landslides are newly detected by our approach, and five recorded landslides are detected significant expansion of their boundaries. Then, specific to a detected landslide, Baobao landslide, a Total Least Squares–Kalman Filter-based approach is presented. Two outcomes are provided for further spatial-temporal pattern analysis: 3D displacement rates, providing an intuitive insight on the spatial characteristics and sliding direction of landslide, which are analyzed to deep the understanding of its kinematic mechanism, and long-term time series, which contribute to deduce the dynamic evolution of landslide, presenting benefits in landslide forecasting. [ABSTRACT FROM AUTHOR]

Social media texts spontaneously produced and uploaded by the public contain a wealth of disaster information. As a supplementary data source for remote sensing, they have played an important role in disaster reduction and emergency response in recent years. However, social media also has certain flaws, such as insufficient location information, etc. This affects the efficiency of combining these data with remote sensing data. For flood disasters in particular, extensively flooded areas limit the distribution of social media data, which makes it difficult for these data to function as they should. In this paper, we propose a disaster reduction framework to solve these problems. We first used an approach that was based on search engine and lexical rules to automatically extract disaster-related location information from social media texts. Then, we combined the extracted information with the upload location of social media itself to construct location-pointing relationships. These relationships were used to build a new social network, which can be used in combination with remote sensing images for disaster analysis. The analysis integrated the advantages of social media and remote sensing. It can not only provide macro disaster information in the study area but can also assist in evaluating the disaster situation in different flooded areas from the perspective of public observation. In addition, the timeliness of social media data also improved the continuity and situational awareness of flood monitoring. A case study of the flood disaster in the Yangtze River Basin in China in 2020 was used to verify the effectiveness of the method described in this paper. [ABSTRACT FROM AUTHOR]

The study of gully characteristics is one of the most effective ways to explore the loess landform development in the Loess Plateau of China. However, current studies mostly focus on gullies' overall characteristics and ignore the different composition of the whole gully system. Therefore, a new perspective is provided in this paper for exploring loess landform development from the population characteristics of the gully system. Firstly, different types of gullies were extracted based on DEM and high-resolution images in three sample watersheds, including hillslope ephemeral gully, bank gully and different-level valley gully. Secondly, population characteristics from the amount, length, age structure and convergent relationship were calculated and analyzed by referring to the biological population in ecology. Finally, the development stages of loess landform in three watersheds were explored based on their population characteristics. The results showed that: (1) The population characteristics, including number density, length density, age structure and convergence, were obviously different in three sample watersheds. (2) The development differences of three watersheds were obtained by synthesizing all population characteristics: Linjiajian was the most developed and oldest watershed, followed by Yangjiaju and then Wangjiagou. (3) The comparison based on the existing soil erosion intensity map and predisposing factors proved that the findings of this paper were more reasonable than that of the traditional hypsometric integral. This research provides a new quantitative-based approach to explore the development degree of loess landform from the gully population, and is a beneficial attempt to combine geomorphology and ecology, further supplementing and improving the study of loess landform development. [ABSTRACT FROM AUTHOR]

Sunshine duration is an important variable that is widely used in atmospheric energy balance studies, analysis of the thermal loadings on buildings, climate research, and the evaluation of agricultural resources. In most cases, it is calculated using an interpolation method based on regional-scale meteorological data from field stations. Accurate values in the field are difficult to obtain without ground measurements. In this paper, a satellite-based method to estimate sunshine duration is introduced and applied over the Heihe River Basin. This method is based on hourly cloud classification product data from the FY-2D geostationary meteorological satellite (FY-2D). A new index--FY-2D cloud type sunshine factor--is proposed, and the Shuffled Complex Evolution Algorithm (SCE-UA) was used to calibrate sunshine factors from different coverage types based on ground measurement data from the Heihe River Basin in 2007. The estimated sunshine duration from the proposed new algorithm was validated with ground observation data for 12 months in 2008, and the spatial distribution was compared with the results of an interpolation method over the Heihe River Basin. The study demonstrates that geostationary satellite data can be used to successfully estimate sunshine duration. Potential applications include climate research, energy balance studies, and global estimations of evapotranspiration. [ABSTRACT FROM AUTHOR]

Understanding ecosystem services(ESs)and their interactions will help to formulate effective and sustainable land use management plans, and clarifying the balance and synergy between watershed ecosystem services can provide a basis for the regulation of the ecological environment in different regions of the watershed and the maximization of overall ecological benefits. This paper takes the Yellow River Basin as the research object and uses the Ecosystem Services and Trade Offs (InVEST)model to evaluate the water yield (WY), soil conservation (SC), carbon storage (CS) and habitat quality (HQ) of the Yellow River Basin. The paper adopts the Carnegie-Ames-Stanford Approach (CASA)model to evaluate the net primary productivity (NPP), draws the spatial distribution map of the five ecosystems, analyzes the trade-off and synergy between the five ecosystems using correlation and binary spatial correlation, and expresses it in space. In addition, it adopts self-organizing mapping (SOM) method to identify ecosystem service clusters. The results show that: (1) ES is generally higher in the upper reaches of the Yellow River, and lower in the middle reaches. (2) WY and NPP, HQ, CS and WY are trade-off relationships, and other ecosystem services are synergistic relationships. Trade-offs and synergy show obvious spatial heterogeneity. (3) The ecosystem services of the Yellow River Basin, driven by different factors, can be divided into three areas, namely WY and SC service leading functional areas, HQ and CS service leading functional areas, and NPP service leading functional areas. Finally, it discusses the driving factors of the spatial heterogeneity of the balance of the ecosystem service functions of the Yellow River Basin and the suggestions of land use management in the basin. [ABSTRACT FROM AUTHOR]

The dependence of water use efficiency (WUE) on changes in land cover types is crucial for understanding of long-term water availability and assessment of water-saving strategies. Investigating the impact of land cover types on ecosystem WUE has important implications when revealing water dynamics and land management. However, the determination of WUE and its dominant factors have always been subject to high data dependency and large calculation consumption within large basins. This paper proposes a framework for processing actual evapotranspiration (AET) and WUE calculation by coupling the Maximum Entropy Production (MEP) method with the Google Earth Engine (GEE). By employing the proposed framework and three data sources available in the GEE platform, results for actual ET and WUE from 2001 to 2020 were obtained in the Yellow River Basin (YRB). The results show that the proposed framework provides an acceptable estimation of actual ET via validation with Eddy Covariance flux sites in the YRB. The calculated WUE values varied greatly in different sub-basins within the YRB, indicating a cumulative growth rate of about 56% during the past 20 years. The dominant factor that led to these changes was the transition from Grasslands into other land-use types. Our results suggest that the use of the GEE platform coupled with the MEP method offers new possibilities for advancing understanding of water exchange and water resource management. [ABSTRACT FROM AUTHOR]

As global warming produces dramatic climate changes, water management is facing increasingly serious challenges. Given to the process of climate change and its complex effects on watershed hydrology, this paper investigates the spatial and temporal variation characteristics of major climatic factors (i.e., precipitation and temperature) over the upper Yangtze River basin (UYRB), China. The statistical analyses are based on annual and seasonal scales during 1951–2020 with a recorded period of seven decades. The Mann–Kendall nonparametric test and R/S analysis are used to record the temporal trends (past and future) of climate variables; the Pettitt test, standard normal homogeneity test and Buishand test are used to detect the homogeneity in climate series. The sensitivities of the streamflow to climatic parameters are assessed at the watershed scale, especially considering the Three Gorges Dam's (TGD) effect on changing runoff. The results of the study indicate that the annual precipitation of 29 out of 34 series indicate homogeneity, while 31 out of 34 annual mean temperature series show heterogeneity, with jump points around 1997 in the mean temperature of 20 sites. Detectable changes in precipitation were not observed during 1951–2020; however, the temperature increased significantly in the whole basin on annual and seasonal scales, except for several stations in the eastern part. The magnitude of increase in air temperature in high altitudes (Tibet Plateau) is higher than that in low altitudes (Sichuan Plain) over the last seven decades, and future temperatures continue to sharply increase in high altitudes. The TGD plays an important role in explaining the seasonal variations in streamflow at Yichang station, with streamflow experiencing a sharp increase in winter and spring (dry season) and a decrease in summer and autumn (rainy season) compared to the pre-TGD period. The streamflow variation at an annual scale is mainly regulated by climate fluctuation (variation in precipitation). During the last seven decades, increasing air temperature and decreases in rainfall and runoff signify reduced water resources availability, and the climate tends to be warmer and drier over the basin. The sensitivity of the streamflow to watershed precipitation is higher than that to temperature, with variation in annual rainfall explaining 71% of annual runoff variability. [ABSTRACT FROM AUTHOR]

Lop Nur is a famous dry lake in the arid region of China. It was an important section of the ancient "Silk Road", famous in history as the prosperous communication channel between Eastern and Western cultures. At present, there is no surface water in Lop Nur Lake basin, and on SAR (Synthetic Aperture Radar) images, it looks like an "Ear". The objective of this paper is to interpret the Lop Nur phenomenon from the perspective of scattering mechanisms. Based on field investigation and analysis of sample properties, a two-layer scattering structure is proposed with detailed explanations of scattering mechanisms. In view of the rough surface, the MIEM (Modified Integral Equation Model) was introduced to represent air-surface scattering in Lop Nur. Then, a two-layer scattering model was developed which can describe surface scattering contribution. Using polarimetric decomposition, validations were carried out, and the RMSE (root mean square error) values for the HH and VV polarizations were found to be 1.67 dB and 1.06 dB, respectively. Furthermore, according to model parametric analysis, surface roughness was identified as an apparent reason for the "Ear" feature. In addition, the polarimetric decomposition result also showed that the volume scattering part had rich texture information and could portray the "Ear" feature exactly compared with the other two parts. It is maintained that subsurface properties, mainly generating volume scattering, can determine the surface roughness under the certain climate conditions, according to geomorphological dynamics, which can help to develop an inversion technology for Lop Nur. [ABSTRACT FROM AUTHOR]

In view of the problems that have not been solved or studied in the previous studies of cascade Energy Storage Operation Chart (ESOC), based on a brief description of the composition, principle, drawing methods, and simulation methods of ESOC, the following innovative work has been done in this paper. Firstly, considering the inconsistency of inflow frequency of upstream and downstream watershed in selecting the typical dry years, a novel optimization model for selecting the overall inflow process considering the integrity of watershed was proposed, which aimed at minimizing the sum of squares of inflow frequency differences. Secondly, aiming at the influence of output coefficients (including number and values) on the results of ESOC, this paper proposed a new method to construct the initial solution of output coefficients and established an optimization model of output coefficients based on progressive optimality algorithms. Thirdly, to the optimization of ESOC with multi-year regulating reservoir, a discrete optimization model of drawdown level was constructed based on the idea of ergodic optimization. On these bases, taking the seven reservoirs in the Yalong River basin of China as an example, the typical dry years considering the inflow frequency inconsistency, the optimal output coefficients of ESOC and the optimal end-of-year drawdown level of a multi-year regulating reservoir (Lianghekou) were obtained, and compared with the previous research results, the ESOC optimized in this paper can increase the total power generation of the cascade system by 9% under the condition that the guaranteed rate did not change much. Furthermore, the difference of the optimal end-of-year drawdown levels between the cascade joint operation and single reservoir operation was discussed for the Lianghekou reservoir at the end of the case study. The obtained results were of great significance for guiding the actual operation of cascade reservoirs. [ABSTRACT FROM AUTHOR]

The terrestrial water storage anomaly (TWSA) gap between the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) is now a significant issue for scientific research in high-resolution time-variable gravity fields. This paper proposes the use of singular spectrum analysis (SSA) to predict the TWSA derived from GRACE. We designed a case study in six regions in China (North China Plain (NCP), Southwest China (SWC), Three-River Headwaters Region (TRHR), Tianshan Mountains Region (TSMR), Heihe River Basin (HRB), and Lishui and Wenzhou area (LSWZ)) using GRACE RL06 data from January 2003 to August 2016 for inversion, which were compared with Center for Space Research (CSR), Helmholtz-Centre Potsdam-German Research Centre for Geosciences (GFZ), Jet Propulsion Laboratory (JPL)'s Mascon (Mass Concentration) RL05, and JPL's Mascon RL06. We evaluated the accuracy of SSA prediction on different temporal scales based on the correlation coefficient (R), Nash–Sutcliffe efficiency (NSE), and root mean square error (RMSE), which were compared with that of an auto-regressive and moving average (ARMA) model. The TWSA from September 2016 to May 2019 were predicted using SSA, which was verified using Mascon RL06, the Global Land Data Assimilation System model, and GRACE-FO results. The results show that: (1) TWSA derived from GRACE agreed well with Mascon in most regions, with the highest consistency with Mascon RL06 and (2) prediction accuracy of GRACE in TRHR and SWC was higher. SSA reconstruction improved R, NSE, and RMSE compared with those of ARMA. The R values for predicting TWS in the six regions using the SSA method were 0.34–0.98, which was better than those for ARMA (0.26–0.97), and the RMSE values were 0.03–5.55 cm, which were better than the 2.29–5.11 cm RMSE for ARMA as a whole. (3) The SSA method produced better predictions for obvious periodic and trending characteristics in the TWSA in most regions, whereas the detailed signal could not be effectively predicted. (4) The predicted TWSA from September 2016 to May 2019 were basically consistent with Global Land Data Assimilation System (GLDAS) results, and the predicted TWSA during June 2018 to May 2019 agreed well with GRACE-FO results. The research method in this paper provides a reference for bridging the gap in the TWSA between GRACE and GRACE-FO. [ABSTRACT FROM AUTHOR]

In this paper, we consider water surface object detection in natural scenes. Generally, background subtraction and image segmentation are the classical object detection methods. The former is highly susceptible to variable scenes, so its accuracy will be greatly reduced when detecting water surface objects due to the changing of the sunlight and waves. The latter is more sensitive to the selection of object features, which will lead to poor generalization as a result, so it cannot be applied widely. Consequently, methods based on deep learning have recently been proposed. The River Chief System has been implemented in China recently, and one of the important requirements is to detect and deal with the water surface floats in a timely fashion. In response to this case, we propose a real-time water surface object detection method in this paper which is based on the Faster R-CNN. The proposed network model includes two modules and integrates low-level features with high-level features to improve detection accuracy. Moreover, we propose to set the different scales and aspect ratios of anchors by analyzing the distribution of object scales in our dataset, so our method has good robustness and high detection accuracy for multi-scale objects in complex natural scenes. We utilized the proposed method to detect the floats on the water surface via a three-day video surveillance stream of the North Canal in Beijing, and validated its performance. The experiments show that the mean average precision (MAP) of the proposed method was 83.7%, and the detection speed was 13 frames per second. Therefore, our method can be applied in complex natural scenes and mostly meets the requirements of accuracy and speed of water surface object detection online. [ABSTRACT FROM AUTHOR]

Drought poses a significant constraint on economic development. Drought assessment using the standardized precipitation index (SPI) uses only precipitation data, eliminating other redundant and complex calculation processes. However, the sparse stations in southwest China and the lack of information on actual precipitation measurements make drought assessment highly dependent on satellite precipitation data whose accuracy cannot be guaranteed. Fortunately, the Chengbi River Basin in Baise City is rich in station precipitation data. In this paper, based on the evaluation of the accuracy of IMERG precipitation data, geographically weighted regression (GWR), geographic difference analysis (GDA), and cumulative distribution function (CDF) are used to fuse station precipitation data and IMERG precipitation data, and finally, the fused precipitation data with the highest accuracy are selected to evaluate the drought situation. The results indicate that the accuracy of IMERG precipitation data needs to be improved, and the quality of CDF-fused precipitation data is higher than the other two. The drought analysis indicated that the Chengbi River Basin is in a cyclical drought and flood situation, and from October to December 2014, the SPI was basically between +1 and −1, showing a spatial pattern of slight flooding, normal conditions, and slight drought. [ABSTRACT FROM AUTHOR]

Studying the spatial representativeness of carbon flux measurement data for typical land cover types can provide important information for benchmarking Earth system models and validating multiple-scale remote sensing products. In our study, daily gross primary productivity (GPP) was firstly derived from eddy covariance observation systems and seasonal variations in field GPP were analyzed at nine flux tower sites for typical land cover types in the Heihe River Basin, China. Then, the real-time footprint distance and climate footprint distance of the field GPP were obtained by using a footprint source area model. Lastly, multiple-scale GPP products were validated at footprint scale, and the impacts (measurement height, surface roughness and turbulent state of the atmosphere) on the footprint distance of field GPP were analyzed. The results of this paper demonstrated that climate footprint distances ranged from about 500 m to 1500 m for different land cover types in the Heihe River Basin. The accuracy was higher when validating MODIS GPP products at footprint scale (R2 = 0.56, RMSE = 3.07 g C m−2 d−1) than at field scale (R2 = 0.51, RMSE = 3.34 g C m−2 d−1), and the same situation occurred in the validation of high-resolution downscaled GPP (R2 = 0.85, RMSE = 1.34 g C m−2 d−1 when validated at footprint scale; R2 = 0.82, RMSE = 1.47 g C m−2 d−1 when validated at field scale). The results of this study provide information about the footprints of field GPP for typical land cover types in arid and semi-arid areas in Northwestern China, and reveal that precision may be higher when validating multiple-scale remote sensing GPP products at the footprint scale than at the field scale. [ABSTRACT FROM AUTHOR]

Assimilation of high-resolution geostationary satellite data is of great value for precise precipitation prediction in regional basins. The operational geostationary satellite imager carried by the Himawari-8 satellite, Advanced Himawari Imager (AHI), has two additional water vapor channels and four other channels compared with its predecessor, MTSAT-2. However, due to the uncertainty in surface parameters, AHI surface-sensitive channels are usually not assimilated over land, except for the three water vapor channels. Previous research showed that the brightness temperature of AHI channel 16 is much more sensitive to the lower-tropospheric temperature than to surface emissivity, which is similar to the three water vapor channels 8–10. As a follow-up work, this paper evaluates the effectiveness of assimilating brightness temperature observations over land from both the three AHI water vapor channels and channel 16 to improve watershed precipitation forecasting through both case analysis (in the Haihe River basin, China) and batch tests. It is found that assimilating AHI channel 16 can improve the upstream near-surface atmospheric temperature forecast, which in turn affects the development of downstream weather systems. The precipitation forecasting test results indicate that adding the terrestrial observations of channel 16 to the assimilation of AHI data can improve short-term precipitation forecasting in the basin. [ABSTRACT FROM AUTHOR]

Many potential landslides occured in the Baihetan reservoir area before impoundment. After impoundment, these landslides may still slide, affecting the safe operation of the reservoir area (e.g., causing barrier lakes and floods). Identifying the locations of landslides and their distribution pattern has attracted attention in China and globally. In addition, due to the rolling terrain of the reservoir area, synthetic aperture radar (SAR) imaging will affect the interactive synthetic aperture radar (InSAR) deformation results. Only by obtaining effective deformation information can active landslides be accurately identified. Therefore, the banks of the Hulukou Xiangbiling section of the Baihetan reservoir area before impoundment in the Jinsha River Basin were studied in this paper. Using terrain data and the satellite parameters from Sentinel-1A ascending and descending orbits and ALOS PALSAR ascending orbit, the line-of-sight visibility was quantitatively analyzed, and an analysis method was proposed. Based on the SAR data visibility analysis, the small baseline subset (SBAS) technique was used to process the SAR data to acquire effective deformation. InSAR deformation data was combined with Google Earth imagery to identify 25 active landslides. After field verification, 21 active landslides (14 new) were determined. Most of the active landslides are controlled by faults, and the strata of the other landslides are relatively weak. This InSAR analysis method based on SAR data visibility can provide a reference for identifying and analyzing active landslides in other complicated terrain. [ABSTRACT FROM AUTHOR]

The vulnerability of water resources is an important criterion for evaluating the carrying capacity of water resources systems under the influence of climate change and human activities. Moreover, assessment and prediction of river basins' water resources vulnerability are important means to assess the water resources security state of river basins and identify possible problems in future water resources systems. Based on the constructed indicator system of water resources vulnerability assessment in Song-Liao River Basin, this paper uses the neighborhood rough set (abbreviated as NRS) method to reduce the dimensionality of the original indicator system to remove redundant attributes. Then, assessment indicators' standard values after dimensionality reduction are taken as the evaluation sample, and the random forest regression (abbreviated as RF) model is used to assess the water resources vulnerability of the river basin. Finally, based on data under three different future climate and socio-economic scenarios, scenario predictions are made on the vulnerability of future water resources. The results show that the overall water resources vulnerability of the Song-Liao River Basin has not improved significantly in the past 18 years, and the overall vulnerability of the Song-Liao River Basin is in the level V of moderate to high vulnerability. In the future scenario 1, the overall water resources vulnerability of the river basin will improve, and it is expected to achieve an improvement to the level III of moderate to low vulnerability. At the same time, the natural vulnerability and vulnerability of carrying capacity will increase significantly in the future, and the man-made vulnerability will increase slowly, which will deteriorate to the level V of moderate to high vulnerability under Scenario 3. Therefore, taking active measures can significantly reduce the vulnerability of nature and carrying capacity, but man-made vulnerability will become a bottleneck restricting the fragility of the overall water resources of the river basin in the future. [ABSTRACT FROM AUTHOR]

In this paper, a detailed mineralogical study on iron-rich spherules in Taihu Lake was carried out, and we present a proposed impact-related origin for these iron-rich spherules. The iron-rich spherical concretions in Taihu Lake occur in a specific silty layer formed around ~7 ka B.P., sandwiched between an upper lacustrine deposit layer and a lower hard loess layer, and they are widely distributed and are the most abundant iron-rich concretions in that specific layer in the vicinity of Taihu Lake. The spherules are typically ~0.5 to 3 mm in diameter with a shape very similar to a spherical shape but not exactly rounded and have various apparent aerodynamic shapes, such as spherical, cone, spindle, ellipsoidal, elongated and pear-shaped morphologies. SEM imaging shows that there is no central core and no concentric layers in the spherules. Iron-rich spherical concretions are similar to accretionary lapilli and have a typical colloidal structure with abundant angular quartz grains and trace fragments of clays wrapped in fine cements that are mainly goethite with minor clays and carbon particles. The typical nodule-forming mechanism in aqueous sediments does not sufficiently explain the morphology and internal features of the iron-rich spherules of Taihu Lake, whereas the aerosol formation mechanism under the airburst impact origin hypothesis of the Taihu Lake basin may be a better explanation of the unique mineralogy of the spherules. Specifically, airburst impact plumes could be the reaction chambers of the aerosol to form the accretionary lapilli with a colloidal texture for the interior, while a dense shell and semi-plastic morphological features can form in the falling processes from higher altitudes in the plume. [ABSTRACT FROM AUTHOR]

The desert-oasis ecotone, as a crucial natural barrier, maintains the stability of oasis agricultural production and protects oasis habitat security. This paper investigates the dynamic evolution of the desert-oasis ecotone in the Tarim River Basin and predicts the near-future land-use change in the desert-oasis ecotone using the cellular automata–Markov (CA-Markov) model. Results indicate that the overall area of the desert-oasis ecotone shows a shrinking trend (from 67,642 km2 in 1990 to 46,613 km2 in 2015) and the land-use change within the desert-oasis ecotone is mainly manifested by the conversion of a large amount of forest and grass area into arable land. The increasing demand for arable land for groundwater has led to a decline in the groundwater level, which is an important reason for the habitat deterioration in the desert-oasis ecotone. The rising temperature and drought have further exacerbated this trend. Assuming the current trend in development without intervention, the CA-Markov model predicts that by 2030, there will be an additional 1566 km2 of arable land and a reduction of 1151 km2 in forested area and grassland within the desert-oasis ecotone, which will inevitably further weaken the ecological barrier role of the desert-oasis ecotone and trigger a growing ecological crisis. [ABSTRACT FROM AUTHOR]

Net radiation is an important component of the earth's surface energy balance, which plays a vital role in the evolution of regional climate or climate change. The estimation of this component at regional or global scales is critical and challenging due to the sparse and limited ground-based observations. This paper made an attempt to analyze the feasibility of a remote sensing-based surface energy balance model using satellite (TERRA/MODIS) data to derive the net radiation (Rn). In the present study, MODIS data at 15 different days of the year (DOY) were utilized to visualize the spatial pattern of net radiation flux over three versatile and heterogeneous ecohydrological land surfaces (upstream, midstream, and downstream) of northwest China (Heihe river basin). The results revealed that the estimated net radiation from the satellite data agrees well with the ground-based measurements over three different surfaces, with a mean relative error of 9.33% over the upstream superstation (grasslands), 13.95% over the middle stream superstation (croplands), and 11.63% over the downstream superstation (mixed forests), where the overall relative error was 11.64% with an overall rmse of 29.36 W/m2 in the study area. The regional distribution of net radiation over the versatile land surfaces was validated well at a large scale during the five-month period and over different land surfaces. It was also observed that the spatial pattern of net radiation varies spatially over three different landscape regions during four different days of the year, which might be associated with different climatic conditions and landscape features in these regions. The overall findings of this study concluded that satellite-derived net radiation can rationally be obtained using a single-source remote sensing model over different land surfaces. [ABSTRACT FROM AUTHOR]

Surface mass variations inferred from the Global Positioning System (GPS), and observed by the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GFO) complement each other in terms of spatial and temporal coverage. This paper presents an analysis of regional surface mass variations inverted from GPS vertical displacements under different density distributions of GPS stations, and compares the GPS-derived mass variations with GRACE/GFO inversion results in spatial and temporal domains. To this end, GPS vertical displacement data from a total of 85 permanent GPS stations of the Crustal Movement Observation Network of China (CMONOC), the latest GRACE/GFO RL06 spherical harmonic (SH) solutions and GRACE RL06 mascon solutions are used to investigate surface mass variations in four regions or basins, including the Yunnan Province (YNP), Min River Basin (MRB), Jialing River Basin (JLRB), and Wu River Basin (WRB) in Southwest China. Our results showed that the spatial distributions and seasonal characteristics of GPS-derived mass change time series agree well with those from GRACE/GFO observations, especially in regions with relatively dense distributions of GPS stations (e.g., in the YNP and MRB), but there are still obvious discrepancies between the GPS and GRACE/GFO results. Scale factor methods (both basin-scaled and pixel-scaled) were employed to reduce the amplitude discrepancies between GPS and GRACE/GFO results. The results also showed that the one-year gap between the GRACE and GFO missions can be bridged by scaled GPS-derived mass change time series in the four studied regions, especially in the YNP and MRB regions (with relatively dense distributions of GPS stations). [ABSTRACT FROM AUTHOR]

The Cretaceous Era has always been a focus of geologic and palaeoenvironmental studies. Previous researchers believed that the impact of the global carbon cycle represents significant short-term global biogeochemical fluctuations, leading to the formation of a large number of organic rich sediments in the marine environment. During the Turonian, a large number of organic-rich oil shales were deposited in the lakes of the Songliao Basin in the Qingshankou Formation. How the depositional environment affected the formation of oil shales in continental lakes and the characteristics of these oil shales remain controversial. In this paper, through sampling of Qingshankou Formation strata, various testing methods are used to provide a variety of new data to study the characteristics of oil shales and palaeoenvironment evolution history in the Songliao Basin. The research of the sediments in the Qingshankou Formation in the Fuyu oilfield, Songliao Basin, via result analysis revealed that the oil shales possess an excellent oil-generation potential with moderate-high total organic carbon (TOC) levels (0.58–9.43%), high hydrogen index (HI) values (265–959 mg hydrocarbons (HC)/g TOC), high extractable organic matter (EOM) levels (2.50–6.96 mg/g TOC) and high hydrocarbon fractions (48–89%). The sources of the organic matter were mainly zooplankton, red algae and higher plants (including marine organisms). The aqueous palaeoenvironment of the Qingshankou Formation was a saline water environment with a high sulfate concentration, which promoted an increase in nutrients and stratification of the water density in the lake basin. Oxygen consumption in the bottom water layer promoted the accumulation and burial of high-abundance organic matter, thus forming the high-quality oil shales in the Qingshankou Formation. The global carbon cycle, warm-humid palaeoclimate, dynamic local biogeochemical cycling and relative passive tectonism were the most likely reasons for the TOC increase and negative δ13Corg deviation. [ABSTRACT FROM AUTHOR]

Comparative evaluation of cross-boundary wetland protected areas is essential to underpin knowledge-based bilateral conservation policies and funding decisions by governments and managers. In this paper, wetland change monitoring for the Wusuli River Basin in the cross-boundary zone of China and Russia from 1990 to 2015 was quantitatively analyzed using Landsat images. The spatial-temporal distribution of wetlands was identified using a rule-based object-oriented classification method. Wetland dynamics were determined by combining annual land change area (ALCA), annual land change rate (ALCR), landscape metrics and spatial analysis in a geographic information system (GIS). A Mann–Kendall test was used to evaluate changing climate trends. Results showed that natural wetlands in the Wusuli River Basin have declined by 5625.76 km2 in the past 25 years, especially swamp/marsh, which decreased by 26.88%. Specifically, natural wetlands declined by 49.93% in the Chinese section but increased with an ALCA of 16.62 km2/y in the Russian section during 1990–2015. Agricultural encroachment was the most important reason for the loss and degradation of natural wetlands in the Wusuli River Basin, especially in China. Different population change trends and conservation policies in China and Russia affected natural wetland dynamics. The research offers an efficient and effective method to evaluate cross-boundary wetland change. This study provides important scientific information necessary for developing future ecological conservation and management of cross-boundary wetlands. [ABSTRACT FROM AUTHOR]

Assessing water resources vulnerability is the foundation of local water resources management. However, as one of the major water systems in China, there is no existing evaluation index system that can effectively assess water resource vulnerability for the Huai River basin. To address this issue, we identified key vulnerability factors, constructed an evaluation index system, and applied such system to evaluate water resources vulnerability for the Huai River basin empirically in this paper. Specifically, our evaluation index system consists of 18 indexes selected from three different aspects: water shortage, water pollution, and water-related natural disaster. Then, the improved blind deletion rough set method was used to reduce the size of the evaluation index while keep the evaluation power. In addition, the improved conditional information entropy rough set method was employed to calculate the weights of evaluation indexes. Based on the reduced index system and calculated weights, a rough set cloud model was applied to carry out the vulnerability evaluation. The empirical results show that the Huai River basin water resources were under severe vulnerability conditions for most of the time between 2000 and 2016, and the Most Stringent Water Resources Management System (MS-WRMS) established in 2012 did not work effectively as expected. [ABSTRACT FROM AUTHOR]

The use of remote sensing to monitor surface water bodies has gradually matured. Long-term serial water change analysis and floods monitoring are currently research hotspots of remote sensing hydrology. However, these studies are also faced with some problems, such as coarse temporal or spatial resolution of some remote sensing data. In general, flood monitoring requires high temporal resolution, and small-scale surface water extraction requires high spatial resolution. The machine learning method has been proven to be effective against long-term serial surface water extraction, such as random forests (RFs). MODIS data are well suited for large-scale surface water dynamic analysis and flood monitoring because of its short return cycle and medium spatial resolution. In this paper, the Yangtze River Basin (YRB) in China was selected as the study area, and two MODIS products (MOD09A1 and MOD13Q1) and RF method were used to extract the surface water from 2000 to 2016. Considering the disadvantages of temporal or spatial resolution of these two MODIS products, this study also presents a data fusion method to combine them and get higher spatiotemporal resolution water results. Finally, 762 surface water maps from 2000 to 2016 are obtained, whose temporal and spatial resolution is every eight days and 250 m, respectively. In addition, water extent variation is analyzed and compared to observed precipitation data. The main conclusions are as follows: (1) this constructed approach for long-term serial surface water extraction based on the RF classifier is feasible, and a good fusion method is used to obtain the surface water body with higher spatiotemporal resolution; (2) the maximum area of the surface water extent is 48.53 × 103 km2, and seasonal and permanent water areas are 20.51 × 103 km2 and 28.01 × 103 km2, respectively; (3) surface water area is increasing in the YRB, such that seasonal water area decreased by 3450 km2, and the permanent water area increased by 3565 km2 in 2001–2015; (4) precipitation is the main factor causing variation in the surface water bodies, and they both show an increasing trend in 2000–2016. As such, the approach is worth referring to other remote sensing applications, and these products are very both valuable for water resource management and flood monitoring in the study area. [ABSTRACT FROM AUTHOR]

Observation schedules depend upon the accurate understanding of a single sensor’s observation capability and the interrelated observation capability information on multiple sensors. The general ontologies for sensors and observations are abundant. However, few observation capability ontologies for satellite sensors are available, and no study has described the dynamic associations among the observation capabilities of multiple sensors used for integrated observational planning. This limitation results in a failure to realize effective sensor selection. This paper develops a sensor observation capability association (SOCA) ontology model that is resolved around the task-sensor-observation capability (TSOC) ontology pattern. The pattern is developed considering the stimulus-sensor-observation (SSO) ontology design pattern, which focuses on facilitating sensor selection for one observation task. The core aim of the SOCA ontology model is to achieve an observation capability semantic association. A prototype system called SemOCAssociation was developed, and an experiment was conducted for flood observations in the Jinsha River basin in China. The results of this experiment verified that the SOCA ontology based association method can help sensor planners intuitively and accurately make evidence-based sensor selection decisions for a given flood observation task, which facilitates efficient and effective observational planning for flood satellite sensors. [ABSTRACT FROM AUTHOR]