Search Results (258)

With climate change, the spatial and temporal patterns of precipitation are altered to a certain degree, which potentially affects the grey water footprint (GWF) of total nitrogen (TN) in agriculture, thereby threatening water security in the Yangtze River Basin (YRB), the largest river in China. The current study constructs an assessment framework for climate change impacts on the GWF of agricultural TN by coupling Shared Socioeconomic Pathways (SSPs) with the InVEST model. The framework consists of four components: (i) data collection and processing, (ii) simulating the two critical indicators (L_TN and W) in the GWF model based on the InVEST model, (iii) calculating the GWF and GWF index (GI) of TN, and (iv) calculating climate change impact index on GWF of agricultural TN (CI) under two SSPs. It is applied to the YRB, and the results show the following: (i) GWFs are 959.7 and 961.4 billion m³ under the SSP1-2.6 and SSP5-8.5 climate scenarios in 2030, respectively, which are both lower than that in 2020 (1067.1 billion m³). (ii) The GI values for TN in 2030 under SSP1-2.6 and SSP5-8.5 remain at “High” grade, with the values of 0.95 and 1.03, respectively. Regionally, the water pollution level of Taihu Lake is the highest, while that of Wujiang River is the lowest. (iii) The CI values of the YRB in 2030 under SSP1-2.6 and SSP5-8.5 scenarios are 0.507 and 0.527, respectively. And the CI values of the five regions in the YRB are greater than 0, indicating that the negative effects of climate change on GWFs increase. (iv) Compared with 2020, L_TN and W in YRB in 2030 under the two SSPs decrease, while the GI of TN in YRB rises from SSP1-2.6 to SSP5-8.5. The assessment framework can provide strategic recommendations for sustainable water resource management in the YRB and other regions globally under climate change. Full article

Volcanic ash from explosive eruptions can significantly alter lake water chemistry through ash–water interactions, potentially influencing primary productivity. Alkaline (soda) lakes, mostly found in volcanic regions, are particularly sensitive due to their unique geochemical properties. However, the effects of volcanic ash on the biogeochemistry and phytoplankton dynamics of soda lakes remain poorly understood. This study presents the first nutrient release experiments using natural alkaline water from Lake Van (Türkiye) and volcanic ash from four volcanoes (Hekla, Arenal, Sakurajima, Rabaul-Tavurvur) with different compositions. Sixteen abiotic leaching experiments were conducted over contact durations ranging from 1 to 24 h. Results show rapid increases in pH (~0.4–0.5 units), enhanced silica and phosphate concentrations, and elevated levels of Na, K, Ca, Sr, and S. Nitrate and Mg were generally depleted. The low N:P ratio (~0.06) in Lake Van water indicated nitrogen limitation, partially mitigated by ash-derived inputs. Cyanobacteria dominated the phytoplankton community (95%), consistent with nitrogen fixation under low-nitrate conditions. Elevated silica may promote diatom growth, while changes in Mg/Ca ratios suggest possible impacts on carbonate precipitation and microbialite development. These findings highlight the biogeochemical and ecological relevance of volcanic ash inputs to soda lakes. Full article

In 1900, Francis Herbert Jennison’s book The Manufacture of Lake Pigments from Artificial Colours was published in London. In the early 20th century, the technical literature focussing on synthetic dyes mainly dealt with their use for dyeing. Conversely, the literature on lake pigment manufacture is less comprehensive, and Jennison’s publication was the first monograph on this topic. His book comprises descriptions of the dyes, substrates, and various methods for lake making. Practical examples complete the work: sixteen colour plates with original samples of lake pigments showcase the practical effect on colour of the different dyes and preparation methods. Herein, we present an overview of the context of Jennison’s research and delve into a selection of formulations. Green lake pigment plates were sampled and analysed by liquid chromatography coupled with spectroscopic and spectrometric detectors and by X-ray fluorescence spectroscopy to correlate the chemical composition with the recipes reported in the book. Seldom or no longer used and unexplored historical dyes were detected, along with polyphenolic compounds possibly used as precipitating agents in lake pigment formulations. Moreover, the examination of two different editions of the Jennison manuscript (i.e., the English and German books) revealed different chemical profiles corresponding to the same lake pigment formulation. This emphasizes the significance of Jennison’s book, confirming how understanding of early formulations is needed to elucidate the later ones. Full article

The Qinghai–Tibet Plateau is a key region for biodiversity conservation, where alpine grasslands are ecologically important. While previous studies have mainly addressed vegetation, ecosystem processes, and soil microbes, phyllosphere microorganisms are essential for nutrient cycling, plant health, and stress tolerance. However, their communities remain poorly understood compared to those in soil. The relative influence of host identity and environmental conditions on shaping phyllosphere microbial diversity and community assembly remains uncertain. In this study, we characterized phyllosphere bacterial and fungal communities of the phyllosphere at two alpine steppe sites with similar vegetation but climatic conditions: the Qilian Mountains (QLM) and the Qinghai Lake region (LQS). At both sites, Cyanobacteriota and Ascomycota were the predominant bacterial and fungal taxa, respectively. Microbial α-diversity did not differ significantly between the two regions, implying that host-associated mechanisms may stabilize within-site diversity. In contrast, β-diversity exhibited clear spatial differentiation. In QLM, bacterial β-diversity was significantly correlated with mean annual precipitation, while fungal α- and β-diversity were associated with soil nutrient levels (including nitrate, ammonium, available potassium, and phosphorus) and vegetation coverage. At LQS, the β-diversity of both bacterial and fungal communities was strongly influenced by soil electrical conductivity, and fungal communities were further shaped by vegetation cover. Community assembly processes were predominantly stochastic at both sites, although deterministic patterns were more pronounced in QLM. Variability in moisture availability contributed to random bacterial assembly at LQS, while increased environmental heterogeneity promoted deterministic assembly in fungal communities. The elevated diversity of microbes and plants in QLM also reinforced deterministic processes. Overall, our findings support a host–environment interaction hypothesis, indicating that host factors primarily govern α-diversity, while climatic and soil-related variables have stronger effects on β-diversity and microbial assembly dynamics. These insights advance our understanding of how phyllosphere microbial communities may respond to environmental change in alpine ecosystems. Full article

High-quality precipitation data are vital for hydrological research. In regions with sparse observation stations, reliable gridded data cannot be obtained through interpolation, while the coarse resolution of satellite products fails to meet the demands of small watershed studies. Downscaling satellite-based precipitation products offers an effective solution for generating high-resolution data in such areas. Among these techniques, machine learning plays a pivotal role, with performance varying according to surface conditions and algorithmic mechanisms. Using the Qinghai Lake Basin as a case study and rain gauge observations as reference data, this research conducted a systematic comparative evaluation of nine machine learning algorithms (ANN, CLSTM, GAN, KNN, MSRLapN, RF, SVM, Transformer, and XGBoost) for downscaling IMERG precipitation products from 0.1° to 0.01° resolution. The primary objective was to identify the optimal downscaling method for the Qinghai Lake Basin by assessing spatial accuracy, seasonal performance, and residual sensitivity. Seven metrics were employed for assessment: correlation coefficient (CC), root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R²), standard deviation ratio (Sigma Ratio), Kling-Gupta Efficiency (KGE), and bias. On the annual scale, KNN delivered the best overall results (KGE = 0.70, RMSE = 17.09 mm, Bias = −3.31 mm), followed by Transformer (KGE = 0.69, RMSE = 17.20 mm, Bias = −3.24 mm). During the cold season, KNN and ANN both performed well (KGE = 0.63; RMSE = 5.97 mm and 6.09 mm; Bias = −1.76 mm and −1.75 mm), with SVM ranking next (KGE = 0.63, RMSE = 6.11 mm, Bias = −1.63 mm). In the warm season, Transformer yielded the best results (KGE = 0.74, RMSE = 23.35 mm, Bias = −1.03 mm), followed closely by ANN and KNN (KGE = 0.74; RMSE = 23.38 mm and 23.57 mm; Bias = −1.08 mm and −1.03 mm, respectively). GAN consistently underperformed across all temporal scales, with annual, cold-season, and warm-season KGE values of 0.61, 0.43, and 0.68, respectively—worse than the original 0.1° IMERG product. Considering the ability to represent spatial precipitation gradients, KNN emerged as the most suitable method for IMERG downscaling in the Qinghai Lake Basin. Residual analysis revealed error concentrations along the lakeshore, and model performance declined when residuals exceeded specific thresholds—highlighting the need to account for model-specific sensitivity during correction. SHAP analysis based on ANN, KNN, SVM, and Transformer identified NDVI (0.218), longitude (0.214), and latitude (0.208) as the three most influential predictors. While longitude and latitude affect vapor transport by representing land–sea positioning, NDVI is heavily influenced by anthropogenic activities and sandy surfaces in lakeshore regions, thus limiting prediction accuracy in these areas. This work delivers a high-resolution (0.01°) precipitation dataset for the Qinghai Lake Basin and provides a practical basis for selecting suitable downscaling methods in similar environments. Full article

Limited surface energy and mass flux data hinder the understanding of glacier retreat mechanisms on the Qinghai–Tibet Plateau (QTP). Glaciers in the west Nyainqentanglha Range (WNR) supply meltwater to the densely populated Lhasa River basin (LRB) and Nam Co, the QTP’s second-largest endorheic lake. In this study, we used a glacier mass balance model based on the degree-day method (GMB-DDM) to understand the response of glacier changes to climate warming. The spatiotemporal variation in degree-day factors for ice (DDF_ice; plural form: DDFs_ice) was assessed to characterize the sensitivity of glacier melt to warming over 44 years in the WNR. Our results demonstrate that the GMB_DDM effectively captured the accelerated mass loss and regional heterogeneity of WNR glaciers from 2000 to 2020, particularly the intensified negative balance after 2014. Moreover, glacier ablation was more sensitive to warming in the WNR during 2000–2020 than 1976–2000, with DDF_ice increases of 21% ± 8% in the LRB and 31% ± 10% in the Nam Co basin (NCB). Increased precipitation during the ablation season and reduced glacier surface albedo can explain the increased sensitivity to warming during 2000–2020. These findings could support sustainable water resource management in the LRB, NCB, and the surrounding areas of the QTP. Full article

This study focuses on Qilu Lake to study how to mitigate the impacts of seasonal droughts and provide technical support for drought resistance decision-making in low-latitude plateau lake basins. Using the Standardized Precipitation Index (SPI), the Vegetation Condition Index (VCI), and the Temperature Condition Index (TCI) as bases, in this study, the applicability of the vegetation health index (VHI) within the basin is investigated, and the optimal weight distribution between the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI) in the VHI is determined. The VHI is then applied to analyze the correlation between drought frequency and severity within the basin. The results indicate that the method is most effective in assessing agricultural drought in the Qilu Lake Basin when the VCI and TCI are weighted at a 4:6 ratio, optimizing the VHI’s evaluative performance. The drought limit water levels of lakes are further divided into short- and long-term drought limit water levels. The short-term drought limit water level is divided into the drought warning water level and the drought emergency water level. The drought warning water level (corresponding to moderate drought conditions, with a frequency of P = 75%) ranges from 1794.53 m to 1795.11 m, while the drought emergency water level (corresponding to extreme drought conditions, with a frequency of P = 95%) ranges from 1793.94 m to 1794.31 m. These levels are set to meet the emergency water demand during droughts in the basin. The long-term drought limit water levels are calculated by accumulating the water deficits of various sectors within the watershed under different agricultural drought conditions, based on the short-term drought limit water levels. By setting the drought limit water level using this method, as well as considering the original water regulation capacity of the lake resources, when the watershed experiences drought, the scheduling method based on this drought limit water level can better alleviate the water supply pressure on various sectors in the local area. Full article

Extreme precipitation events are one of the common hazards in eastern Texas, generating a large amount of storm water. Water running off urban areas may carry non-point source (NPS) pollution to natural resources such as rivers and lakes. Urbanization exacerbates this issue by increasing impervious surfaces that prevent natural infiltration. This study evaluated the efficacy of rain gardens, a nature-based best management practice (BMP), in mitigating NPS pollution from urban stormwater runoff. Stormwater samples were collected at inflow and outflow points of three rain gardens and analyzed for various water quality parameters, including pH, electrical conductivity, fluoride, chloride, nitrate, nitrite, phosphate, sulfate, salts, carbonates, bicarbonates, sodium, potassium, aluminum, boron, calcium, mercury, arsenic, copper iron lead magnesium, manganese and zinc. Removal efficiencies for nitrate, phosphate, and zinc exceeded 70%, while heavy metals such as lead achieved reductions up to 80%. However, certain parameters, such as calcium, magnesium and conductivity, showed increased outflow concentrations, attributed to substrate leaching. These increases resulted in a higher outflow pH. Overall, the pollutants were removed with an efficiency exceeding 50%. These findings demonstrate that rain gardens are an effective and sustainable solution for managing urban stormwater runoff and mitigating NPS pollution in eastern Texas, particularly in regions vulnerable to extreme precipitation events. Full article

Riverine and lacustrine shorelines are crucial for human survival and development, but their natural and ecological environments are highly fragile and sensitive. Intensified human activities have placed unprecedented pressure on the shoreline ecosystem of the Yangtze River Basin. This study investigates the degradation of river and lake shorelines and its cascading effects on ecological service functions. Using Sentinel-2 as the primary data source, we analyzed land use/cover changes and ecosystem service values (ESV) in the Huanggang and Taihu sections of the Yangtze River from 2018 to 2022. The supervised classification results using the support vector machine (SVM) algorithm exceeded 95% accuracy. In the Huanggang section, vegetation was significantly converted into cultivated land and built-up areas (−6.17 km²), while in the Taihu section, water bodies were largely transformed into agricultural land (−3.77 km²). In this study, we quantified changes in ESV using the unit area equivalent factor method, adjusted based on net primary productivity, precipitation, and the soil conservation coefficient. The results indicate that the ESV ranking in both sections follows the order: water conservation > environmental purification > biodiversity > soil conservation. From 2018 to 2022, the ESV in the Huanggang section declined due to forest and grassland loss and an increase in bare land. In contrast, ecological restoration and habitat protection policies contributed to an improvement in ecosystem service functions in the Taihu section, with various ESV components increasing as follows: soil conservation (8.79%) > biodiversity (6.67%) > environmental purification (5.98%) > water conservation (5.52%). These findings provide valuable insights for decision-making in the protection and management of the Yangtze River Basin ecosystem. Full article

Excessive nutrient loading in freshwater is a water quality and safety concern for Indigenous communities, especially those with inadequate water treatment. Continuous nutrient monitoring efforts in collaboration with community members require cost-effective but information-rich methods. Data gathered through community-science approaches could enhance source water protection programs and can provide first-hand knowledge and expertise through reciprocal information exchange with local community members. Yet, there are still misconceptions about the validity of data gathered by community scientists. This study validates the use of two inexpensive nutrient monitoring devices (YSI 9500 Photometer and the Nutrient Smartphone App) for community-based environmental research by testing the accuracy of each device, identifying nutrient hotspots, and determining if nutrient concentrations relate to precipitation patterns in a drought-prone region of Saskatchewan within the Lake Winnipeg Basin in Canada. We found that the measurement accuracy of these devices varied depending on the compound tested, with the poorest results for nitrate (r² = 0.07) and the best results for phosphate (r² = 0.89) when using the photometer. Seasonal nutrient concentration patterns differed between the years of moderate (2019) and low (2021) precipitation, but there was no correlation between rainfall amounts and nutrient concentrations, suggesting other drivers. This study identifies the strengths and weaknesses of cost-effective nutrient testing devices, guiding continuous monitoring efforts with communities. Full article

In recent scholarship, the impact of palaeoclimate change is often understood as a main factor contributing to the fragmentation and “fall” of Rome’s empire. The various attempts at postulating disastrous effects of temperature shifts in the fifth to sixth centuries—cooling caused harvest failures, famine, political and social unrest, and disruptions in food supply—have been criticized for a good reason: compelling causal links between cooler weather conditions and decreasing agricultural productivity are missing. The socio-economic and political impact of a prolonged climate-related Late Roman drought (ca. 360–440 CE), however, has been widely overlooked. This paper aims to compare palaeoecological data from cave speleothems and lake sediments that indicate palaeoclimate and environmental change through precipitation shifts in the southern Black Sea region with the archaeological data of the urban granary in Pompeiopolis. Combining these data offers fresh insights into Roman environmental imperialism, command ecologies and economies, and the impact of climate change on Rome’s tax system that kept the network of redistributive food supply running. This archaeo-environmental approach sheds light on the ecological vulnerability of integrated economies, failures of the dysfunctional metabolic regimes of ›polis command economies‹, and the chain of cause-and-effect provoking the “fall” of Rome. Full article

Against the backdrop of climate warming leading to an increase in extreme weather events, extreme precipitation events have become more frequent, and the impact of changes in precipitation on ecosystems cannot be ignored. There is a scarcity of field in situ observational data on greenhouse gas emissions during the growing season for alpine wetlands, especially for alpine river source wetlands, which limits our understanding of the ability of alpine wetland ecosystems to convert between carbon sources and carbon sinks and also hinders our comprehension of the primary effects of extreme precipitation events on wetland ecosystems. In this study, we investigated the main greenhouse gas emission fluxes in two consecutive growing seasons (May to September) under the conditions of natural control (CK), 75% increase in precipitation (IP), and 75% decrease in precipitation (DP) through in situ field simulations of extreme precipitation in an alpine source wetland in the Qinghai Lake Basin of the Qinghai–Tibet Plateau. The results indicate the following: (1) The extreme precipitation increase (IP) treatment did not significantly increase CO₂ fluxes; it promoted CH₄ flux emissions by 168.2% and N₂O flux emissions by 178.4% over the two growing seasons. The extreme precipitation decrease treatment had a non-significant impact on CO₂ fluxes; it inhibited CH₄ emission fluxes by 96.8% and promoted N₂O emission fluxes by 137.8%. (2) During the growing season, CO₂ fluxes were 2.2% lower in the IP treatment than in the DP treatment under the two precipitation patterns; the CH₄ flux under the IP treatment is 84.1% higher than that under the DP treatment, and N₂O fluxes were 43.8% lower in the IP treatment than in the DP treatment. CH₄ fluxes were the most sensitive to precipitation changes. (3) The extreme changes in precipitation were not the main influencing factor for CO₂ fluxes, while CH₄ fluxes were primarily affected by precipitation changes. (4) During the entire growing season, IP reduced the global warming potential (GWP) by 9.03%, and DP decreased GWP by 8.40%. These results suggest that the primary driver of CO₂ fluxes in alpine river source wetlands remains temperature factors; in scenarios where extreme climate events occur frequently, both extreme increases and decreases in precipitation have inhibitory effects on the global warming potential of alpine river source wetlands. Full article

This study examines runoff variations and their drivers in the Buha and Shaliu Rivers of the Qinghai Lake Basin (1960–2016), a key ecological area in China. Abrupt changes were detected using the Mann–Kendall and cumulative anomaly methods, while the Budyko framework attributed runoff variations to dominant factors. Correlation and grey relational analyses assessed multicollinearity, and a lake water balance model with climate elasticity theory quantified the effects of climate and land surface changes on runoff components and lake levels. Results indicate that the Buha River experienced an abrupt runoff change in 2004, while the Shaliu River exhibited a change beginning in 2003. Based on the trends and abrupt change points of each factor, the study period was divided into four segments: 1960–1993, 1994–2016, 1960–2003, and 2004–2016. The correlation coefficients are significantly different in different periods. The climate elasticity coefficients were as follows: P (precipitation), 1.98; ET₀ (potential evapotranspiration), −0.98; Rn (net radiation), 0.66; T (average temperature), 0.02; U₂ (wind speed at 2 m height), 0.16; RHU (relative umidity), −0.56. The elasticity coefficient of runoff with respect to precipitation is significantly higher than that for other climate variables. Net radiation and relative humidity contribute equally to runoff, while wind speed and temperature have relatively smaller effects. In the Qinghai Lake Basin, runoff is sensitive to precipitation (0.38), potential evapotranspiration (−0.07), and the underlying surface parameter ω (−98.32). Specifically, a 1 mm increase in precipitation raises runoff by 0.38 mm, while a 1 mm rise in potential evapotranspiration reduces it by 0.07 mm. A one-unit increase in ω leads to a significant runoff decrease of 98.32 mm. According to the lake water balance model, climate contributes 88.43% to groundwater runoff, while land surface changes contribute −11.57%. Climate change and land surface changes contribute 93.02% and 6.98%, respectively, to lake water levels. This study quantitatively evaluates the impacts of climate and land surface changes on runoff, providing insights for sustainable hydrological and ecological management in the Qinghai Lake Basin. Full article

Owing to climate change and increasing resource competition, elucidating the control mechanism of cultivated land productivity stability is essential. Previous research has focused on anthropogenic or climatic factors individually, overlooking their combined effects; therefore, the “climate–anthropogenic” framework was constructed. Net primary productivity (NPP) was employed to measure the cultivated land productivity and investigate the impact of climate change and anthropogenic factors on cultivated land productivity stability in Poyang Lake from 2001 to 2022. Results revealed that NPP increased but fluctuated significantly and was higher in southern Poyang Lake than in the north. The low spatial stability distribution fluctuation area was concentrated in the periphery of Poyang Lake, the periphery and riverbank comprised the middle and high fluctuation areas, and the Ganjiang River Delta exhibited high fluctuation. Multiple linear regression analysis indicated that the stability of cultivated land productivity was positively impacted by farmland and river proximity and average patch area and that fractal dimension was positively affected and negatively impacted by low farmland proximity and average annual precipitation. Stable cultivated land production and improved utilization efficiency requires irrigation and drainage system optimization and improved adaptability to climate change. Moreover, cultivated land fragmentation should be reduced, and the resilience of cultivated land to external disturbances should be enhanced. Full article

The dynamics of shallow water areas of inland lakes is closely related to the regional ecology and economy. However, it is still a challenge to extract the natural shallow water area for inland lakes using satellite images due to their rapid changes and various human demands. Therefore, we developed a new remote sensing-based method applied in Hongze Lake (one of the largest freshwater lakes in China) to first delineate the lake from the SWIR1 band of Landsat OLI imagery using cold spots in the LISA method, and then distinguish deep and shallow water areas from the G band of Landsat OLI images using hot spots with LISA after masking the lake out, and finally extracting the natural shallow water area by masking aquatic farms out from shallow water areas using farm ridge classification from NDWI images and aggregating points of farm ridges. The results show that (1) the method of this study is efficient in extracting the natural shallow water area with limited effects from aquatic vegetation; (2) water inflow (upstream water supply and precipitation) and the area of aquatic farms, the two dominant factors for the temporal changes in natural shallow water area, contributed 38.3% (positively) and 42.2% (negatively) to the decrease in the natural shallow water area during 2013–2022 in Hongze Lake; (3) the natural shallow water area of Hongze Lake decreased significantly every April as paddy rice farms withdrew a large amount of irrigation water from Hongze Lake. Our research provides a new approach to extract the natural shallow water areas of inland lakes from satellite images and demonstrates that the upstream water supply, precipitation, and agriculture demands are the three main reasons for seasonal and temporal variations in natural shallow water areas for inland lakes. Full article