Drinking water safety improvement and future challenge of lakes and reservoirs.

To meet the Sustainable Development Goal (SDG) target 6.1, China has undertaken significant initiatives to address the uneven distribution of water resources and to enhance water quality. Since 2000, China has invested heavily in the water infrastructure of numerous reservoirs, with a total storage capacity increase of 4.704 × 1011 m3 (an increase of 90.8%). These reservoirs have significantly enhanced the available freshwater resources for drinking water. Concurrently, efforts to improve water quality in lakes and reservoirs, facilitated by nationwide water quality monitoring, have been successful. As a result, an increasing lakes and reservoirs are designated as centralized drinking water sources (CDWSs) in China. Among the 3,441 CDWSs across all provinces, 40.8% are sourced from lakes and reservoirs, 32.6% from rivers, and 26.6% from groundwater in 2023. Notably, from 2016 to 2023, the percentage of lakes and reservoirs categorized as CDWSs has increased consistently across all 29 provinces. This progress has enabled 561.4 million urban residents to access improved drinking water sources in 2022, compared to 303.4 million in 2004. Our findings underscore the pivotal role of water infrastructure construction and water quality improvement jointly promoting lakes and reservoirs as vital drinking water sources. Nevertheless, the nationwide occurrence of algal blooms has surged by 113.7% from the 2000s to the 2010s , which is a considerable challenge to drinking water safety. Fortunately, algal blooms have been markedly alleviated in past four years. However, it is still crucial to acknowledge that lakes and reservoirs face the challenges of algal blooms, and associated toxic microcystin and odor compounds.

A national-scale assessment on the spatial and temporal variations in water color for urban lakes in China.

Monitoring the variations of lake water quality is essential for urban water security and sustainable eco-environment health. However, it is challenging to investigate the water quality of urban lakes at large scales due to the need for large-amount in situ data with diverse optical properties for developing the remote sensing inversion algorithms. Forel-Ule Index (FUI), a proxy of quantifying water color, whose calculation does not require in situ data of specific properties, can comprehensively reflect water quality conditions. However, the spatial and temporal distribution of water color in Chinese urban lakes is still poorly understood. To fill this research gap, this study investigated the spatial distribution of water color in 523 urban lakes (area > 0.5 km2) in China using the FUI derived from the high-quality Multi-Spectral Instrument (MSI) data onboard Sentinel-2 during the ice-free period (April-October) from 2019 to 2022. The monthly and seasonal variation patterns of water color in urban lakes were also analyzed. Our results show that green domain is the most common color of urban lakes, with about 86 % of urban lakes in China being green, and non-green lakes accounting for only 14 % of the total number of lakes. The monthly variation of FUI in urban lakes across the country and multiple geographic regions is basically the same. The monthly average FUI first increases, then decreases, and then rebounds. We also found that the seasonal variation of water color in most urban lakes in southern and northern China is opposite. This study helps to comprehensively understand the spatial and temporal variation of water color and quality of urban lakes in China, providing key basic information for the protection and governance of urban lakes.

Increasing cascade dams in the upstream area reduce nutrient inputs to the Three Gorges Reservoir in China.

The upstream cascade dams play an essential role in the nutrient cycle in the Yangtze. However, there is little quantitative information on the effects of upstream damming on nutrient retention in the Three Gorges Reservoir (TGR) in China. Here, we aim to assess the impact of increasing cascade dams in the upstream area of the Yangtze on Dissolved Inorganic Nitrogen and Phosphorus (DIN and DIP) inputs to the TGR and their retention in the TGR and to draw lessons for other large reservoirs. We implemented the Model to Assess River Inputs of Nutrients to seAs (MARINA-Nutrients China-2.0 model). We ran the model with the baseline scenario in which river damming was at the level of 2009 (low) and alternative scenarios with increased damming. Our scenarios differed in nutrient management. Our results indicated that total water storage capacity increased by 98 % in the Yangtze upstream from 2009 to 2022, with 17 new large river dams (>0.5 km3) constructed upstream of the Yangtze. As a result of these new dams, the total DIN inputs to the TGR decreased by 15 % (from 768 Gg year-1 to 651 Gg year-1) and DIP inputs decreased by 25 % (from 70 Gg year-1 to 53 Gg year-1). Meanwhile, the molar DIN:DIP ratio in inputs to the TGR increased by 13 % between 2009 and 2022. In the future, DIN and DIP inputs to the TGR are projected to decrease further, while the molar DIN:DIP ratio will increase. The Upper Stem contributed 39 %-50 % of DIN inputs and 63 %-84 % of DIP inputs to the TGR in the past and future. Our results deepen our knowledge of nutrient loadings in mainstream dams caused by increasing cascade dams. More research is needed to understand better the impact of increased nutrient ratios due to dam construction.

Fine-scale monitoring of lake ice phenology by synthesizing remote sensed and climatologic features based on high-resolution satellite constellation and modeling.

Lake ice, as a crucial component of the cryosphere, serves as a sensitive indicator of climate change. Fine-scale monitoring of spatiotemporal patterns in lake ice phenology holds significant importance in scientific research and environmental management. However, the rapid and dynamic nature of the freeze-thaw process of lake ice poses challenges to existing methods, resulting in their limited application in small lakes. In this study, we propose a novel approach of investigating ice phenology of lakes in various sizes. We conducted a case study in Hoh Xil, known for its vulnerability to climate change and a wide distribution of small lakes, to analyze the ice phenology of 372 lakes (>1 km2) during 2017-2021. Firstly, ensemble machine-learning model was developed for lake ice identification from Landsat-8/9 and Sentinel-2 A/B imagery. The accuracy evaluation reveals the overall good performance for ice extraction results based on Landsat-8/9 (97.03 %) and Sentinel-2 A/B (96.89 %). Next, the XGBoost models were employed to reconstruct ice coverages on unobserved dates for the freezeup and breakup periods, respectively. Totally, 744 XGBoost models were constructed for the study lakes, and the majority of them perform well. Based on the reconstructed daily ice coverage, phenology parameters could be extracted for examining the spatiotemporal characteristics of ice cover and possible relationships with lake sizes and terrains. From early-October to early-November, the Hoh Xil lakes freeze from the northwest to the southeast, while the breakup period starts in late-March and lasts until late-June. Moreover, the results indicate relatively small variability in freezeup-end dates among lakes, but significant differences in breakup dates, showing a greater sensitivity to temperature variations. Furthermore, ice phenology in small lakes exhibit stronger consistency with subtle climatic fluctuations. The results highlight the significant role of ice phenology in small lakes, as they dominate the overall tendency of ice phenology in Hoh Xil.

Satellites reveal hotspots of global river extent change.

Rivers are among the most diverse, dynamic, and productive ecosystems on Earth. River flow regimes are constantly changing, but characterizing and understanding such changes have been challenging from a long-term and global perspective. By analyzing water extent variations observed from four-decade Landsat imagery, we here provide a global attribution of the recent changes in river regime to morphological dynamics (e.g., channel shifting and anabranching), expansion induced by new dams, and hydrological signals of widening and narrowing. Morphological dynamics prevailed in ~20% of the global river area. Booming reservoir constructions, mostly skewed in Asia and South America, contributed to ~32% of the river widening. The remaining hydrological signals were characterized by contrasting hotspots, including prominent river widening in alpine and pan-Arctic regions and narrowing in the arid/semi-arid continental interiors, driven by varying trends in climate forcing, cryospheric response to warming, and human water management. Our findings suggest that the recent river extent dynamics diverge based on hydroclimate and socio-economic conditions, and besides reflecting ongoing morphodynamical processes, river extent changes show close connections with external forcings, including climate change and anthropogenic interference.

High-resolution circa-2020 map of urban lakes in China.

Urban lakes provide important ecological services to local communities, such as flood mitigation, biodiversity, and recreation. With rapid urbanization, urban lakes are significantly affected by socio-economic development and urgently need attention. Yet there is still a lack of datasets that include tiny urban lakes on a global or national scale. This study aims to produce a high-resolution circa-2020 map of urban lakes (≥0.001 km2) in China. The 10-m-resolution Sentinel-2 imagery and a simple but robust water extraction method was used to generate waterbodies. The accuracy of this national-scale dataset was evaluated by comparing it with manually sampled urban units, with the average accuracy of 81.85% in area and 93.35% in count. The database totally inventories 1.11 × 106 urban lakes in China, with a net area of ~2.13 × 103 km2. Overall, the spatial distribution of urban lakes in China showed strongly heterogeneous characteristics. This dataset will enhance our understanding of the distribution pattern of China's urban lakes and contribute to better ecological and environmental management as well as sustainable urban development planning.

A comprehensive data set of physical and human-dimensional attributes for China's lake basins.

Lakes provide water-related ecosystem services that support human life and production. Nevertheless, climate changes and anthropogenic interventions remarkably altered lake and basin hydrology in recent decades, which pose a significant threat to lacustrine ecosystems. Therefore, assessments of lacustrine ecosystems require the spatial and temporal characteristics of key physical and human-dimensional attributes for lakes and lake basins. To facilitate stakeholders obtaining comprehensive data of lake basins in China, we compiled the comprehensive data set for China's lake basins (CODCLAB) mostly from publicly available data sources based on spatial analysis and mathematical statistics methods in this study. The CODCLAB is available in three data formats, including raster layers (Level 1) in "tiff" format, vector shapefiles (Level 2), and attribute tables (Level 3). It covers 767 lakes (>10 km2) in China and their basin extent associating with 34 variables organized into five categories: Hydrology, Topography, Climate, Anthropogenic, and Soils. This unique database will provide basic data for research on the physical processes and socioeconomic activities related to these lakes and their basins in China and expect to feed a broad user community for their application in different areas.

Smart City + IoT Standardization Application Practice Model and Realization of Key Technologies.

Smart city gathers heterogeneous information, which requires a unified data access and collection mechanism. In this paper, based on the computing framework of IoT put forward to satisfy urban sensing network data acquisition, transmission, and computing technology system, according to the function requirements of IoT gateway, we put forward the method of building software system and hardware system and the urban perception network middleware architecture that can meet the demand of M2M, which can realize dynamic management of cognitive resources. It also supports ubiquitous services over HTTP. This is of great significance for providing intelligent services with diversity of solvers, controllers, and computing terminals. This paper focuses on how to comprehensively apply intelligent sensing, wireless transmission, data mining, and other technologies of the Internet of Things to associate data with typical application examples such as vehicle sensing and positioning technology and urban security sensor application. These typical applications can effectively solve the practical problems in urban operation and management, meet the needs of the expansion of the concept of Internet of things in urban management and the continuous deepening of management, and improve the scientific and intelligent level of urban operation and management.

Remote sensing estimation of the flood storage capacity of basin-scale lakes and reservoirs at high spatial and temporal resolutions.

The flood storage of lakes and reservoirs plays an important role in flood regulation and control in floodplains. However, the flood storage capacity of lakes and reservoirs is ineffectively quantified at the basin scale due to the limited access to in-situ data and poor quality of optical satellite images in flooding seasons. To address this, taking a typical floodplain basin (the Poyang Lake basin) in the Yangtze as a study case, radar satellite data combined with measured bathymetry and digital elevation model data were utilized to reconstruct the time series of the water inundation area and water storage change of all lakes and reservoirs larger than 1 km2 during the once-in-a-generation flood event that occurred in 2020 (termed as the 2020 flood event hereafter). Results show that the flood storage capacity of Poyang Lake can reach the maximum at 12.18 Gt, and that for other lakes and reservoirs within the basin is approximately 2.95 Gt. It indicates a total flood-storage capacity of 15.13 Gt for the basin-scale lakes and reservoirs, approximately accounting for 45.02% of the terrestrial water storage change of the basin. The storage capacity of Poyang Lake was approximately four times larger than the entirety of other lakes and reservoirs in the basin despite that its maximum water inundation area is in the proportion of 2.58 times other water bodies. This finding indicates that the Poyang Lake provided the dominant contribution to flood storage among all the lakes and reservoirs in the basin. This study introduced a remote sensing approach to quantify the flood storage capacity of basin-scale lakes and reservoirs at high spatial and temporal resolutions during the flood event, which could fill the insufficiently-quantified knowledge about dynamics of lakes and reservoirs in areas lacking full-covered in-situ data records. This study also helps to offer a quantitative basis to improve flood forecasting and control for the public authority, stakeholders, and decision-makers.

Satellite and UAV-based remote sensing for assessing the flooding risk from Tibetan lake expansion and optimizing the village relocation site.

Climate change in recent decades led to the remarkable expansions for most lakes in endorheic basins of the Tibetan Plateau (TP). Enlarged lake inundation areas may pose adverse effects and potential threats on the local human living environment, especially for high-risk villages adjacent to rapidly expanding lakes. Taking a rapidly expanding lake, Angzi Co in the central TP as a study case, we investigated the flooding risk of lake growth on the local living environment and proposed an optimized solution of village relocation selection on the basis of satellite and unmanned aerial vehicle (UAV) remote sensing. The detection of spatiotemporal variations of Angzi Co using optical and altimetric satellite observations revealed a significant area and water level increase by 81.28 km2 and 5.78 m, respectively, from 2000 to 2020. We also assessed the vertical accuracy of multi-source digital elevation model (DEM) products using Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) altimetry data and further examined the flooding risk and potential influences of lake expansion on adjacent settlements (Guozha Village). Results indicated that UAV-DEM achieves excellent advantages in depicting details of lake shoreline variations and simulating potential submergence regions, followed by Advanced Land Observing Satellite World 3D DEM (AW3D DEM). Moreover, assuming that Angzi Co maintains the water level at a growth rate of 0.29 m/a (the average change rate during 2000-2020), the village will be submerged in approximate 10 years based on our assessment. Furthermore, we designed an optimal relocation site southwest of Guozha Village and approximately 3 km away based on the GIS-MVDA method and field investigations. An initial remote sensing-based approach for assessing the flooding risk from dramatic lake expansions in the TP and optimizing the village relocation site was proposed in this study to provide an essential scientific reference for formulating risk mitigation solutions under future climate change scenarios.

An Effective Low-Cost Remote Sensing Approach to Reconstruct the Long-Term and Dense Time Series of Area and Storage Variations for Large Lakes.

Inland lakes are essential components of hydrological and biogeochemical water cycles, as well as indispensable water resources for human beings. To derive the long-term and continuous trajectory of lake inundation area changes is increasingly significant. Since it helps to understand how they function in the global water cycle and how they are impacted by climate change and human activities. Employing optical satellite images, as an important means of lake mapping, has been widely used in the monitoring of lakes. It is well known that one of the obvious difficulties of traditional remote sensing-based mapping methods lies in the tremendous labor and computing costs for delineating the large lakes (e.g., Caspian Sea). In this study, a novel approach of reconstructing long-term and high-frequency time series of inundation areas of large lakes is proposed. The general idea of this method is to obtain the lake inundation area at any specific observation date by referring to the mapping relationship of the water occurrence frequency (WOF) of the selected shoreline segment at relatively slight terrains and lake areas based on the pre-established lookup table. The lookup table to map the links of the WOF and lake areas is derived from the Joint Research Centre (JRC)Global Surface Water (GSW) dataset accessed in Google Earth Engine (GEE). We select five large lakes worldwide to reconstruct their long time series (1984-2018) of inundation areas using this method. The time series of lake volume variation are analyzed, and the qualitative investigations of these lake changes are eventually discussed by referring to previous studies. The results based on the case of North Aral Sea show that the mean relative error between estimated area and actually mapped value is about 0.85%. The mean R2 of all the five lakes is 0.746, which indicates that the proposed method can produce the robust estimates of area time series for these large lakes. This research sheds new light on mapping large lakes at considerably deducted time and labor costs, and be effectively applicable in other large lakes in regional and global scales.

A Global Assessment of Terrestrial Evapotranspiration Increase Due to Surface Water Area Change.

Surface water, which is changing constantly, is a crucial component in the global water cycle, as it greatly affects the water flux between the land and the atmosphere through evaporation. However, the influences of changing surface water area on the global water budget have largely been neglected. Here we estimate an extra water flux of 30.38 ± 15.51 km3/year omitted in global evaporation calculation caused by a net increase of global surface water area between periods 1984-1999 and 2000-2015. Our estimate is at a similar magnitude to the recent average annual change in global evapotranspiration assuming a stationary surface water area. It is also comparable to the estimated trends in various components of the hydrological cycle such as precipitation, discharge, groundwater depletion, and glacier melting. Our findings suggest that the omission of surface water area changes may cause considerable biases in global evaporation estimation, so an improved understanding of water area dynamics and its atmospheric coupling is crucial to reduce the uncertainty in the estimation of future global water budgets.

Long-term surface water changes and driving cause in Xiong'an, China: from dense Landsat time series images and synthetic analysis.

China's government statement recently reported the plan of constructing Xiong'an New Area, which aims to phase out some extra capital functions from Beijing and to explore an innovative urban development mode with the priority in eco-environmental protection. The New Area is located in the semi-arid North China Plain (NCP) and is home to NCP's largest natural freshwater wetland, Baiyangdian Lake. A comprehensive realization of surface water dynamics would be crucial for policy-makers to outline a sustainable environment development strategy for New Area. In this study, we used a total of 245 time slices of cloud-free Landsat images to document the continuous changes of water bodies within Xiong'an City during 1984-2016 and to provide detailed evidence of water presence and persistency states and changes under the influences of climate change and human actions. Our results reveal that the New Area water body areas varied dramatically during the past 33 years, ranging from 0.44 km2 in April 1988 to 317.85 km2 in February 1989. The change of surface water area was not characterized by a monotonically decreasing tendency. The evolution processes can be divided into four sub-stages: the first extreme desiccation in mid-1980s, the wet stage with the most extensive inundation areas and strong inter-annual fluctuations from late-1988 to late 1999, another desiccation stage in early 2000s, and the overall recovering stage between 2007 and 2016. We also mapped the maximum water inundation extents and frequencies of all-season, pre-wet season (February-May) and post-wet season (September-December) for the 33 years and different sub-periods. Although there is good agreement between time series of surface water area evolution in the New Area and station-based precipitation and evaporation variations, multiple lines of evidences reviewed in previous research indicate that the degraded Baiyangdian Lake was also tightly associated with human activities from various aspects, including dam construction, groundwater extraction, agricultural irrigation, etc. We highlighted the current status of exploring the driving mechanism of surface water changes and existing problems, and then offer recommendations.

Grazing exclusion by fencing non-linearly restored the degraded alpine grasslands on the Tibetan Plateau.

Resilience is an important aspect of the non-linear restoration of disturbed ecosystems. Fenced grassland patches on the northern Tibetan Plateau can be used to examine the resistance and resilience of degraded alpine grasslands to grazing and to a changing climate. To examine the non-linearity of restoration, we used moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) as a proxy for productivity during a ten-year restoration by fencing. Degraded alpine grasslands exhibited three restoration trajectories: an equilibrium in meadows, a non-linear increase across steppes, and an abrupt impulse in desert-steppes following a slight increase in productivity. Combined with weather conditions, the ten-year grazing exclusion has successfully enhanced the NDVI on the most degraded steppes, but did not do so efficiently on either meadows or desert-steppes. Warming favors the NDVI enhancement of degraded meadows, but higher temperatures limited the restoration of degraded steppes and desert-steppes. Precipitation is necessary to restore degraded alpine grasslands, but more precipitation might be useless for meadows due to lower temperatures and for desert-steppes due to limitations caused by the small species pool. We suggest that detailed field observations of community compositional changes are necessary to better understand the mechanisms behind such non-linear ecological restorations.

Recent Changes in Land Water Storage and its Contribution to Sea Level Variations.

Sea level rise is generally attributed to increased ocean heat content and increased rates glacier and ice melt. However, human transformations of Earth's surface have impacted water exchange between land, atmosphere, and ocean, ultimately affecting global sea level variations. Impoundment of water in reservoirs and artificial lakes has reduced the outflow of water to the sea, while river runoff has increased due to groundwater mining, wetland and endorheic lake storage losses, and deforestation. In addition, climate-driven changes in land water stores can have a large impact on global sea level variations over decadal timescales. Here, we review each component of negative and positive land water contribution separately in order to highlight and understand recent changes in land water contribution to sea level variations.