Temporal characteristics and trends of nitrogen loadings in lake Taihu, China and its influencing mechanism at multiple timescales.

Climate warming impact on excessive nitrogen (N) load in sediment favours cyanobacterial blooms in eutrophic waters. The nitrate (NO3--N) and ammonium (NH4+-N) are two forms of N loads that contribute to algae blooms. However, little attention is paid to the impact of environmental factors on N loads variations at different time scales. This paper used a well-calibrated and validated EFDC model to investigate the temporal patterns and trends of ammonium and nitrate from June 2016 to June 2017. This paper presented the relationship and effects between these variations and environmental factors using data from satellite and reanalysis-based observations obtained for six meteorological parameters. The relationship and effects between these variations and environmental factors were also examined at different timescales (i.e., daily, monthly and seasonal scales). Model calibration results indicated that measured values reasonably matched simulated values. The validation results revealed that relative error (RE) values were within an acceptable range. The REs of ammonium at East Taihu (S12) and Xu Lake (S23) sampling sites were 55.83% and 57.61%, while that of nitrate was 24.37% (S12) and 41.08%, respectively. The daily analysis of NH4+-N and NO3--N variations was 7.318 ± 3.876 (g/m2/day) and 0.0275 ± 0.222 (g/m2/day), respectively. The monthly analysis showed NH4+-N and NO3-N range from 2.04 to 12.04 (g/m2/day) and 0.0008 to 0.064 (g/m2/day), respectively. The magnitude NH4+-N and NO3--N varied and showed distinct inter-monthly variations. , The relationship between sediment fluxes and meteorological parameters showed the magnitude of correlation coefficient (r) and strength of correlation varied significantly. At daily scales, the relationship of NH4+-N and NO3--N had a significant positive correlation with all meteorological parameters. At monthly, the correlation coefficient (r) of NH4+-N and NO3-N were heterogenous. At daily and monthly scales, air temperature and wind speed are the main drivers affecting sediment N loads' dynamics; however, the influence of relative humidity, precipitation, and evaporation on N loads are smaller. The study demonstrates the contribution of meteorological conditions to the magnitude and timing of N loadings variability in water bodies. The findings provide more insight into lake ecosystem protection and environmental remediation.

A sediment diagenesis model on sediment oxygen demand in managing eutrophication on Taihu, China.

Blue-green algae (CyanoHABs), photosynthetic bacteria that create a harmful aquatic environment, have been a trending issue on Taihu for over a decade. CyanoHABs adapt to varying climatic changes, which explains why the problem on Taihu still thrives. One major drive that keeps the algae is Sediment Oxygen Demand (SOD). In this paper, seasonal and spatial variations of SOD that contribute immensely to nutrient growth in Lake Taihu were done using the Environmental Fluid Dynamics Code (EFDC). The results were analyzed based on Nitrogenous SOD (NSOD) and Total SOD (TSOD). Summer results ranged from - 0.05754 to - 0.0826 (- 0.75658 to - 0.83902) (g/m2/day) and Winter values ranged from - 0.3022 to - 0.40171 (- 1.34486 to - 1.48856) (g/m2/day) indicate a gradual decrease in NSOD (TSOD) values respectively. Relatively higher values in summer are attributed to warmer surface water which sets up thermal stratification to increase the internal loading of nitrogen. Lower winter values are related to inverse stratification, where lower oxygen concentration decreases the SOD to trigger ammonium accumulation in the water column. NSOD (TSOD) values for Autumn results ranged from - 0.1039 to - 0.24786 (- 0.96251 to - 1.39454) (g/m2/day) and Spring values of - 0.43019 to - 0.35959 (- 1.48297 to - 0.54089) (g/m2/day). Transition seasons (i.e., Autumn and Spring) results are impacted by wind mixing that allows dissolved oxygen and nutrients in the whole water column. However, spring values depict a gradual increase in SOD value attributed to spring turnover and gradual stratification, which decrease nutrient concentration. In contrast, decreasing SOD values in autumn are related to mixing, but temperature decreases tend to increase nutrient concentrations. Carbonaceous sediment oxygen demand (CSOD), due to sulfide oxidation, presents high values from the difference between TSOD and NSOD. Based on the high values of CSOD, it is highly recommended that more research on eutrophic Taihu lakes would consider delving into CSOD.

Comparison of Missing Data Infilling Mechanisms for Recovering a Real-World Single Station Streamflow Observation.

Reconstructing missing streamflow data can be challenging when additional data are not available, and missing data imputation of real-world datasets to investigate how to ascertain the accuracy of imputation algorithms for these datasets are lacking. This study investigated the necessary complexity of missing data reconstruction schemes to obtain the relevant results for a real-world single station streamflow observation to facilitate its further use. This investigation was implemented by applying different missing data mechanisms spanning from univariate algorithms to multiple imputation methods accustomed to multivariate data taking time as an explicit variable. The performance accuracy of these schemes was assessed using the total error measurement (TEM) and a recommended localized error measurement (LEM) in this study. The results show that univariate missing value algorithms, which are specially developed to handle univariate time series, provide satisfactory results, but the ones which provide the best results are usually time and computationally intensive. Also, multiple imputation algorithms which consider the surrounding observed values and/or which can understand the characteristics of the data provide similar results to the univariate missing data algorithms and, in some cases, perform better without the added time and computational downsides when time is taken as an explicit variable. Furthermore, the LEM would be especially useful when the missing data are in specific portions of the dataset or where very large gaps of 'missingness' occur. Finally, proper handling of missing values of real-world hydroclimatic datasets depends on imputing and extensive study of the particular dataset to be imputed.

Future Changes in Simulated Evapotranspiration across Continental Africa Based on CMIP6 CNRM-CM6.

The main goal of this study was to assess the interannual variations and spatial patterns of projected changes in simulated evapotranspiration (ET) in the 21st century over continental Africa based on the latest Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) provided by the France Centre National de Recherches Météorologiques (CNRM-CM) model in the Sixth Phase of Coupled Model Intercomparison Project (CMIP6) framework. The projected spatial and temporal changes were computed for three time slices: 2020-2039 (near future), 2040-2069 (mid-century), and 2080-2099 (end-of-the-century), relative to the baseline period (1995-2014). The results show that the spatial pattern of the projected ET was not uniform and varied across the climate region and under the SSP-RCPs scenarios. Although the trends varied, they were statistically significant for all SSP-RCPs. The SSP5-8.5 and SSP3-7.0 projected higher ET seasonality than SSP1-2.6 and SSP2-4.5. In general, we suggest the need for modelers and forecasters to pay more attention to changes in the simulated ET and their impact on extreme events. The findings provide useful information for water resources managers to develop specific measures to mitigate extreme events in the regions most affected by possible changes in the region's climate. However, readers are advised to treat the results with caution as they are based on a single GCM model. Further research on multi-model ensembles (as more models' outputs become available) and possible key drivers may provide additional information on CMIP6 ET projections in the region.

Spatial Distribution and Environmental Significance of Phosphorus Fractions in River Sediments and Its Influencing Factor from Hongze and Tiaoxi Watersheds, Eastern China.

This study explored the spatial distribution of phosphorus fractions in river sediments and analyzed the relationship between different phosphorus fractions and their environmental influence on the sediments within different watersheds in Eastern China. River sediments from two inflow watersheds (Hongze and Tiaoxi) to Hongze and Taihu Lake in Eastern China were analyzed by the sequential extraction procedure. Five fractions of sedimentary phosphorus, including freely sorbed phosphorus (NH4Cl-P), redox-sensitive phosphorus (BD-P), bound phosphorus metal oxide (NaOH-P), bound phosphorus calcium (HCl-P), and residual phosphorus (Res-P) were all analyzed. The orders of rankings for the P fractions of the rivers Anhe and Suihe were HCl-P > NaOH-P > BD-P > NH4Cl-P and HCl-P > BD-P > NaOH-P > NH4Cl-P, respectively. For the rank order of the Hongze watershed, HCl-P was higher while the NH4Cl-P contents were significantly lower. The rank order for the Dongtiaoxi River was NaOH-P > HCl-P > BD-P > NH4Cl-P, and that of Xitiaoxi River was NaOH-P > BD-P > HCl-P > NH4Cl-P. Compared with the phosphorus forms of the Tiaoxi watershed, NaOH-P contents were significantly higher compared to HCl-P, which was significantly higher in the Hongze watershed. In comparison, NH4Cl-P contents were significantly lower in both. Variations may be attributed to differential discharge of the P form in the watershed due to land-use changes and urban river ambient conditions.

A Sediment Diagenesis Model of Seasonal Nitrate and Ammonium Flux Spatial Variation Contributing to Eutrophication at Taihu, China.

Algal blooms have thrived on the third-largest shallow lake in China, Taihu over the past decade. Due to the recycling of nutrients such as nitrate and ammonium, this problem has been difficult to eradicate. Sediment flux, a product of diagenesis, explains the recycling of nutrients. The objective was to simulate the seasonal spatial variations of nitrate and ammonium flux. In this paper, sediment diagenesis modeling was applied to Taihu with Environmental Fluid Dynamics Code (EFDC). Latin hypercube sampling was used to create an input file from twelve (12) nitrogen related parameters of sediment diagenesis and incorporated into the EFDC. The results were analyzed under four seasons: summer, autumn, winter, and spring. The concentration of NH4-N in the sediment-water column increased from 2.744903 to 22.38613 (g/m3). In summer, there was an accumulation of ammonium in the water column. In autumn and winter, the sediment was progressively oxidized. In spring, low-oxygen conditions intensify denitrification. This allows algal blooms to continue to thrive, creating a threat to water quality sustainability. The sediment diagenesis model, coupled with water quality measured data, showed an average relative error for Total Nitrogen (TN) of 38.137%, making the model suitable. Future studies should simulate phosphate flux and measure sediment fluxes on the lake.

Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions.

The identification of unit hydrographs and component flows from rainfall, evapotranspiration and streamflow data (IHACRES) model has been proven to be an efficient yet basic model to simulate rainfall-runoff processes due to the difficulty in obtaining the comprehensive data required by physical models, especially in data-scarce, semi-arid regions. The success of a calibration process is tremendously dependent on the objective function chosen. However, objective functions have been applied largely in over daily and monthly scales and seldom over sub-daily scales. This study, therefore, implements the IHACRES model using 'hydromad' in R to simulate flood events with data limitations in Zhidan, a semi-arid catchment in China. We apply objective function constraints by time aggregating the commonly used Nash-Sutcliffe efficiency into daily and hourly scales to investigate the influence of objective function constraints on the model performance and the general capability of the IHACRES model to simulate flood events in the study watershed. The results of the study demonstrated the advantage of the finer time-scaled hourly objective function over its daily counterpart in simulating runoff for the selected flood events. The results also indicated that the IHACRES model performed extremely well in the Zhidan watershed, presenting the feasibility of the use of the IHACRES model to simulate flood events in data scarce, semi-arid regions.

Spatial variations in and environmental significance of nitrogen forms in river sediments from two different watersheds in eastern China.

Nitrogen is considered an essential nutrient element limiting water productivity, and its distribution in sediments directly affects its release potential. This study aimed to analyse the spatial characteristics, distribution, and influence of nitrogen forms in two different river catchments situated in eastern China. Using sequential extraction methods, the study divided sediment nitrogen into four forms, namely, an ion-exchangeable form (IEF-N), weak acid-extractable form (WAEF-N), strong alkali-extractable form (SAEF-N), and strong oxidant-extractable form (SOEF-N). The results for the two catchments showed significant differences in the physicochemical properties as well as variations in space. The mean proportion of total transferable nitrogen (TTN) in the Anhe, Suihe, Dongtiaoxi, and Xitiaoxi rivers accounted for 50.64%, 32.87%, 34.63%, and 40.45%, respectively. The results also revealed a higher total TTN in the Hongze watershed than in the Tiaoxi watershed. The order of mean TTN in sediments from the Hongze watershed was SOEF-N > SAEF-N > IEF-N > WAEF-N, whereas that for the Tiaoxi watershed was SOEF-N > SAEF-N > WAEF-N > IEF-N. The distribution of nitrogen forms in the sediments was significantly impacted by the sediment composition and environmental factors, as shown by correlation and redundancy analysis (RDA).

High Spatial Resolution Simulation of Sunshine Duration over the Complex Terrain of Ghana.

In this paper, we propose a remote sensing model based on a 1 × 1 km spatial resolution to estimate the spatio-temporal distribution of sunshine percentage (SSP) and sunshine duration (SD), taking into account terrain features and atmospheric factors. To account for the influence of topography and atmospheric conditions in the model, a digital elevation model (DEM) and cloud products from the moderate-resolution imaging spectroradiometer (MODIS) for 2010 were incorporated into the model and subsequently validated against in situ observation data. The annual and monthly average daily total SSP and SD have been estimated based on the proposed model. The error analysis results indicate that the proposed modelled SD is in good agreement with ground-based observations. The model performance is evaluated against two classical interpolation techniques (kriging and inverse distance weighting (IDW)) based on the mean absolute error (MAE), the mean relative error (MRE) and the root-mean-square error (RMSE). The results reveal that the SD obtained from the proposed model performs better than those obtained from the two classical interpolators. This results indicate that the proposed model can reliably reflect the contribution of terrain and cloud cover in SD estimation in Ghana, and the model performance is expected to perform well in similar environmental conditions.