Open Water Surface Research Articles

Influence of modeling conditions on the estimation of the dry deposition velocity of aerosols on highly inhomogeneous surfaces

An approach to estimating the dry deposition velocity of aerosol particles on the surfaces of Arctic regions, where snow-covered surfaces, open water surface, tundra and coniferous forest predominate, is proposed and numerically investigated. Optimal modeling conditions are proposed, taking into account the characteristic sizes and densities of aerosol particles involved in transport in the planetary boundary layer, and the interaction of air flows with the surface through the parameter u*, calculated using the WRF-ARW model. The proposed approach is compared with other known models and experimental data. The dependence of the dry deposition velocity obtained by the proposed approach on the diameter, density of aerosol particles and dynamic velocity u* for the surfaces in the Far North is estimated.

Potential associations between Schistosoma mansoni infection and physico-chemical characteristics and water-related human activities in Côte d'Ivoire: a cross-sectional study.

Schistosomiasis remains a public health problem, particularly in sub-Saharan Africa. The disease is intimately connected to poverty and environmental factors. Our research was readily embedded into a multi-country schistosomiasis oversampling study. The aim of the study presented here was to determine the prevalence of Schistosoma mansoni and to investigate the role of water body characteristics and water-related human activities in disease transmission. In August and September 2022, a cross-sectional study was conducted in the western part of Côte d'Ivoire. Stool and urine samples were collected from 1602 and 1729 children aged 5-14years, respectively, in 65 villages in the health districts of Biankouma, Ouaninou and Touba. Additionally, data were collected from direct observation of water-related activities at water bodies and interviews conducted with community leaders and health workers. The prevalence and risk factors for Schistosoma infection were assessed using generalised estimating equation models. The prevalence ofS.mansoni and S.haematobium were 27.4% (95% confidence interval [CI] 21.5-34.3%) and 0.1% (95% CI 0.03-0.5%), respectively. Low prevalence of soil-transmitted helminths was observed with 2.4%, 0.4% and 0.2% for hookworm, Trichuris trichiura and Ascaris lumbricoides, respectively. At the health district level, we found S.mansoni prevalence of 34.4% (95% CI 25.0-45.3%), 34.3% (95% CI 24.0-46.2%) and 16.3% (95% CI 9.5-26.6%) for Biankouma, Ouaninou and Touba, respectively. Female and male participants were at a similar risk of infection (29.0% vs. 26.0%, odds ratio [OR]: 1.18, 95% CI 0.92-1.50). Children aged 9-14years showed a higher prevalence than their younger counterparts aged 5-8years (34.5% vs. 22.7%, OR: 1.80, 95% CI 1.42-2.27). High infection prevalence was observed in villages where children were washing clothes and dishes at open surface water sites and pursued recreational activities (e.g. swimming and playing in the water). The temperature, total dissolved solids and pH of water samples showed no significant association with S.mansoni infection at the village unit. Human water-related activities such as washing clothes and playing in the water are risk factors for S.mansoni transmission. Hence, preventive chemotherapy should be combined with information, education and communication to avoid or reduce the frequency of water exposure in children as part of a comprehensive package of interventions towards elimination of schistosomiasis as a public health problem.

Dynamic monitoring of open-surface water bodies in the middle reaches of the Tarim River based on the GEE cloud platform

ABSTRACT This study innovatively utilizes the Google Earth Engine (GEE) cloud platform, combined with a multispectral index rule set, to address the challenges of extracting open-surface water bodies in the middle reaches of the Tarim River Basin (MROTR). To overcome the limitations of traditional index methods, particularly the reduced extraction accuracy caused by mixed pixels in arid environments, this research integrates indices such as MNDWI, NDVI, and EVI for automated water extraction, significantly enhancing the precision of water body delineation. By analyzing the spatiotemporal changes in open-surface water area (SWA) from 1990 to 2022, a notable increase in SWA was observed following the implementation of ecological gate-controlled water management, while a decreasing trend was identified within an 8-km range from the riverbanks. The results show a 93.7% accuracy in surface water identification and an SWA growth rate of 12.47 km2/year, with 96% of this growth attributed to seasonal water areas. Runoff loss decreased by 8.53% in the S1 and S2 regions but increased by 7.76% in the S3 and S4 regions. The mixed index rule method proved effective for large-scale water detection, offering new insights for managing arid region water resources.

Pathways of exposure to Vibrio Cholerae in an urban informal settlement in Nairobi, Kenya.

Cholera is a diarrhoeal disease caused by Vibrio cholerae (V. cholerae) bacterium, with strains belonging to serogroups 01 and 0139 causing a huge proportion of the disease. V. cholerae can contaminate drinking water sources and food through poor sanitation and hygiene. This study aimed to identify environmental routes of exposure to V. cholerae within Mukuru informal settlement in Nairobi. We collected nine types of environmental samples (drinking water, flood water, open drains, surface water, shaved ice, raw produce, street food, soil, and public latrine swabs) over 12 months. All samples were analysed for V. cholerae by culture and qPCR, then qPCR-positive samples were quantified using a V. cholerae DNA standard. Data about the frequency of contact with the environment was collected using behavioural surveys. Of the 803 samples collected, 28.5% were positive for V. cholerae by qPCR. However, none were positive for V. cholerae by culture. V. cholerae genes were detected in majority of the environmental water samples (79.3%), including open drains, flood water, and surface water, but were only detected in small proportions of other sample types. Vibrio-positive environmental water samples had higher mean V. cholerae concentrations [2490-3469 genome copies (gc) per millilitre (mL)] compared to drinking water samples (25.6 gc/mL). Combined with the behavioural data, exposure assessment showed that contact with surface water had the highest contribution to the total V. cholerae exposure among children while ingestion of municipal drinking water and street food and contact with surface water made substantial contributions to the total V. cholerae exposure for adults. Detection of V. cholerae in street food and drinking water indicates possible risk of exposure to toxigenic V. cholerae in this community. Exposure to V. cholerae through multiple pathways highlights the need to improve water and sanitation infrastructure, strengthen food hygiene practices, and roll out cholera vaccination.

Global WaterPack - The development of global surface water over the past 20 years at daily temporal resolution

Open surface water across the globe is essential for many life forms and is an important source for human settlements, agriculture, and industry. The presence and variation in time and space is influenced by different natural conditions (e.g. climate, topography, geology) and human use (e.g. irrigation, flood protection). The information on the spatial and temporal distribution of open surface water is fundamental for many disciplines and is also required as an essential parameter for hydrological and climatological modelling. Here, we present a dataset derived from satellite earth observation, which is based on more than 6.3 million single MODIS products with a volume of approx. 300 TB. The resulting dataset reflects the situation of open surface water on a global scale for each day over the time period from 2003 to 2022 at a spatial resolution of 250 m. The dataset enables the analysis of the development of lake and reservoir surface areas, freezing cycles, and inundation areas.

Urban heat island patterns in garden cities: Putrajaya as a case study

The garden-city model, characterised by sprawling urban expansion and extensive open spaces, features green and water surfaces alongside substantial road networks, large parking lots and unshaded lands. This diverse landscape contributes to uneven air temperature distribution within the city. Our study investigated urban heat island (UHI) patterns in various urban environments within Putrajaya, focusing on rural, business, residential and near-water areas. Atmospheric data were collected over a year. Putrajaya exhibits two distinct UHI patterns: cool-day-hot-night in residential zones and hot-noon-temperate-elsewhere in impermeable areas. Business areas display alternating patterns based on seasonal climatic conditions and anthropogenic factors. The efficacy of artificial water bodies as a UHI countermeasure in garden cities depends on the size of the water body and the nature of the surrounding land cover. Shaded and green areas exhibit UHI intensities limited to 3°C, while impermeable areas, regardless of proximity to water surfaces, experience UHI up to 6°C. Overall, the garden-city model tends to restrict UHI variations within −1 to 3°C compared to −2 to 4°C in nearby Kuala Lumpur.

Analysis of heavy metals and pathogen levels in vegetables cultivated using selected water bodies in urban areas of the Greater Accra Metropolis of Ghana

Open-surfaced water sources have been used to irrigate vegetable farms in cities. Open-surface water often contains unmonitored concentrations of health-threatening contaminants that pose health risks, especially when used to produce vegetables for human consumption. However, information on levels of heavy metals and faecal coliform bacteria in such vegetables in selected sites, especially in Greater Accra Metropolitan Area (GAMA) of Ghana is rare. This study examines the levels of heavy metals and faecal coliform in two vegetables-lettuce and bell pepper - that were cultivated using open-surface wastewater from drains and constructed reservoirs at different locations of the GAMA. Using concurrent mixed methods, questionnaires were administered to 67 vegetable farmers, followed by the collection of vegetable samples from three urban farm sites, Haatso and Dzorwulu and Weija irrigation scheme site (WISS) for laboratory analysis. The concentrations of Lead (Pb), Mercury (Hg) and Cadmium (Cd) were determined using atomic absorption spectroscopy after microwave digestion of the vegetables while total faecal coliform was quantified using MacConkey-Endo broth method. The results from all three sites showed that the concentrations of Cd (=0.001 μg/mg) and Pb (=0.005 μg/mg) in lettuce were within the World Health Organization's (WHO) permissible levels. However, the Hg (≥0.309 μg/mg) and faecal coliform (>5 count/100 ml) in the vegetables from all three sites exceeded the WHO permissible limits. Therefore, consumers of vegetables from such urban farms are exposed to health risks associated with Hg and faecal coliforms. There is the need to intensify education on the health risks of consuming vegetables produced from open-surface water sources from the observed sites. The enforcement of existing phytosanitary standards to enhance food safety and the quality of urban vegetables is also recommended.

Research on the hydrodynamic performance of propellers under oblique flow conditions

The phenomenon of oblique water inflow is widespread in the operation of thrusters, which will cause adverse effects on the hydrodynamic performance of thrusters. In order to investigate the hydrodynamic performance and stress variation of the propeller in oblique flow, based on computational fluid dynamics theory, this paper takes the DTMB4119 propeller as the research object and conducts numerical simulation research on the propeller in oblique flow by solving the RANS equation. By calculating the open water performance curve and surface pressure distribution of the propeller, the rationality of the numerical method and the meshing are verified. Considering the flow field information such as velocity, oblique flow angles, flow line distribution, and pressure distribution, the changes in hydrodynamic characteristics of the propeller are simulated and analyzed. The results show that the uneven distribution of pressure on the propeller blade surface increases with a decrease in the advance coefficient. The force pulsation amplitude of a single blade increases with an increase in oblique flow angles. With the increase in oblique flow angles, the thrust, torque, and efficiency of the propeller show different increasing trends. With the increase in propeller advance coefficient, propeller thrust and torque decrease gradually, and propeller efficiency increases gradually. By using mature propellers, this paper has more reference value for studying the flow field around the ship hull and the hydrodynamic performance of propellers in the process of ship maneuvering.

Automatic mapping of 500 m daily open water body fraction in the American continent using GOES-16 ABI imagery

Timely and large-area monitoring of terrestrial water bodies using remote sensing data is essential to protect water resource security for humans and ecosystems. Although efforts have been made to monitor inter-monthly water bodies at the regional, continental and global scales, surface open water bodies may experience rapid changes within a short duration. At the same time, the data gaps caused by the long revisit frequencies of satellite sensor imaging systems and the extremely cloudy and rainy weather in certain areas mean that a suitable operational method for recording such rapid changes over large areas does not yet exist. The recently launched operational geostationary satellite sensor GOES-16 ABI can provide multi-scale optical images every 10 min in the Americas, and it has great potential to provide a new solution for timely open surface water monitoring. In this research, a framework based on a multi-scale non-linear mixture model (NLMM) was proposed for the automatic estimation of 500 m daily open water body fraction maps across the full extent of the American continent from GOES-16 ABI imagery. Specifically, an exterior spectral library was created firstly from many pairs of training GOES-16 ABI images and 500 m water body fraction maps derived from Landsat images, and an inherited interior pure spectral library was then derived from a pair of the testing GOES-16 ABI image and the corresponding pure water and non-water (i.e., vegetation and soil/rock substrate) fractions extracted from the monthly water recurrence dataset. Furthermore, a synthetic interior mixed spectral library was built finally based on the linear and non-linear mixtures of randomly selected pure endmembers of water and non-water (i.e., vegetation and soil/rock substrate) in the testing image. All the exterior and interior pure and synthetic mixed spectral libraries were employed jointly in the NLMM machine learning method for estimating daily water body fractions with GOES-16 ABI images. Experiments show that the integration of all three different spectral libraries produced 500 m open water body fraction maps with the greatest accuracies. Compared to traditional linear spectral unmixing and a water index thresholding method, the proposed method produced more accurate results both quantitatively and visually. Moreover, the proposed method can produce time-series daily 500 m open water body fraction maps with minimal cloud coverage for the full extent of the Americas by combining dense GOES-16 ABI images at half-hour intervals, opening up great possibilities for near real-time rapid open water body changes monitoring, such as flooding and drought, over large areas, even with a high frequency of cloud cover.

Spatiotemporal Dynamics and Driving Factors of Small and Micro Wetlands in the Yellow River Basin from 1990 to 2020

Comprehending the spatiotemporal dynamics and driving factors of small and micro wetlands (SMWs) holds paramount significance in their conservation and sustainable development. This paper investigated the spatiotemporal evolution and driving mechanisms of SMWs in the Yellow River Basin, utilizing buffer zones, overlay analysis, and the Geodetector model based on Landsat satellite images and an open-surface water body dataset from 1990 to 2020. The results revealed that (1) from 1990 to 2020, SMWs in the Yellow River Basin exhibited an overall pattern of fluctuation reduction. The total area decreased by approximately 1.12 × 105 hm2, with the predominant decline occurring in the 0–1 hm2 and 1–3 hm2 size categories. In terms of spatial distribution, SMWs in Qinghai and Gansu decreased significantly, while the SMWs in Inner Mongolia, Henan, and Shandong gradually increased. (2) From 1990 to 2020, SMWs were mostly converted into grassland and cropland, with some transformed into impervious water surface and barren, and only a small percentage converted into other land types in the Yellow River basin. (3) The alterations in SMWs were influenced by factors, with their interplay exhibiting nonlinear or bilinear enhancement. Among these factors, annual precipitation, elevation, and potential evapotranspiration were the primary natural factors influencing the changes in the distribution of SMWs. On the other hand, land use cover type, gross domestic product (GDP), and road distance were the main anthropogenic factors.

Влияние изменения климата на формирование границ природных зон на водосборах бассейна реки Асса-Талас

Based long-term climate data, a research database has been created for eight meteorological stations located in various natural-geographical zones of the Assa-Talas river basin; a linear-correlation model of climate indicators has been obtained, allowing to determine the rate of increase in the sums of air temperatures, radiation balance, evaporation from the open water surface or from excessively moistened soil during the biologically active period of the year, annual precipitation, natural moisture coefficient and hydrothermal dryness index, which perform important environment-forming and ecological functions. The results of the study showed that in general, in all natural-geographical zones of the Assa-Talas river basin, the sum of air temperatures, radiation balance, evaporation and hydrothermal dryness index have a positive growth rate, and annual precipitation and the coefficient of natural moisture are negative, contributing to the formation of a positive rate an increase in the deficit of water consumption of agricultural land and a shift in the boundaries of natural zones, which is a signal of the safety of agricultural activities.

DeepAqua: Semantic segmentation of wetland water surfaces with SAR imagery using deep neural networks without manually annotated data

Deep learning and remote sensing techniques have significantly advanced water surface monitoring; however, the need for annotated data remains a challenge. This is particularly problematic in wetland detection, where water extent varies over time and space, demanding multiple annotations for the same area. In this paper, we present DeepAqua, a deep learning model inspired by knowledge distillation (a.k.a. teacher–student model) to generate labeled data automatically and eliminate the need for manual annotations during the training phase. We utilize the Normalized Difference Water Index (NDWI) as a teacher model to train a Convolutional Neural Network (CNN) for segmenting water from Synthetic Aperture Radar (SAR) images. To train the student model, we exploit cases where optical- and radar-based water masks coincide, enabling the detection of both open and vegetated water surfaces. DeepAqua represents a significant advancement in computer vision techniques for water detection by effectively training semantic segmentation models without any manually annotated data. Experimental results show that DeepAqua outperforms other unsupervised methods by improving accuracy by 3%, Intersection Over Union by 11%, and F1-score by 6%. This approach offers a practical solution for monitoring wetland water extent changes without the need of ground truth data, making it highly adaptable and scalable for wetland monitoring.

A contrarian growth: The spatiotemporal dynamics of open-surface water bodies on the northern slope of Kunlun Mountains

Identifying and monitoring open-surface water bodies are significant for understanding regional water resource distribution and evolving trends. This understanding carries profound value for comprehensively assessing the effects of climate change and human social activities on water resources and maintaining water security. This study pioneers’ improvements in surface water detection rules with the central aim of constructing a Method with Enhanced Impurity Control, specifically tailored for complex environmental scenarios (OA = 98.97 % ± 0.06). This is achieved by incorporating intricate exponential constraints and targeted data masks. Our analysis is grounded in the examination of 21,709 preprocessed high-quality images, covering the period from 1990 to 2021 across the northern slope of the Kunlun Mountains. Through this comprehensive study, we have gleaned insightful results regarding the spatiotemporal dynamics of open-surface water bodies. In the past 32 years, the surface water body area on the northern slope of the Kunlun Mountains has exhibited a significantly increasing trend. Specifically, the size of permanent water bodies expanded by 71.03 % (with a 95 % confidence interval: ± 27.73 %), while the area of seasonal water bodies grew by a substantial 170.63 % (with a 95 % confidence interval: ± 17.50 %). Open-surface water bodies display discernible spatiotemporal differences. Stable and continuous permanent water bodies are predominantly in mountainous areas, whereas seasonal water bodies with pronounced fluctuations are chiefly found in desert-oasis areas. Climate change is the dominant factor that affects the changes of water bodies on the surface of mountain regions, while human social activities also have a significant impact on desert-oasis areas. The improved methodology adopted in this study offers a robust and scalable framework that can be tailored for studying changes in open-surface water bodies in intricate environments. We performed a comprehensive analysis of the changes and drivers of open-surface water bodies on the north side of the Kunlun Mountains over time and space. This work is aimed at providing data support for scientifically appraising the development potential of water resources in Southern Xinjiang and addressing the disparity between water resource supply and demand.

Application of Gated Recurrent Unit Neural Network for Flood Extraction from Synthetic Aperture Radar Time Series

Floods are a sudden and influential natural disaster, and synthetic aperture radar (SAR) can image the Earth’s surface almost independently of time and weather conditions, making it particularly suitable for extracting flood ranges in time. Platforms such as Google Earth Engine (GEE) can provide a large amount of SAR data and preprocess it, providing powerful assistance for real-time flood monitoring and time series analysis. However, the application of long-term series data combined with recurrent neural networks (RNNs) to monitor floods has been lacking in current research, and the accuracy of flood extraction in open water surfaces remains unsatisfactory. In this study, we proposed a new method of near real-time flood monitoring with a higher accuracy. The method utilizes SAR image time series to establish a gated recurrent unit (GRU) neural network model. This model was used to predict normal flood-free surface conditions. Flood extraction was achieved by comparing and analyzing the actual flood surface conditions with the predicted conditions, using a parameter called Scores. Our method demonstrated significant improvements in accuracy compared to existing algorithms like the OTSU algorithm, Sentinel-1 Dual Polarized Water Index (SDWI) algorithm, and Z-score algorithm. The overall accuracy of our method was 99.20%, which outperformed the Copernicus Emergency Management Service (EMS) map. Importantly, our method exhibited high stability as it allowed for fluctuation within the normal range, enabling the extraction of the complete flood range, especially in open water surfaces. The stability of our method makes it suitable for the flood monitoring of future open-access SAR data, including data from future Sentinel-1 missions.

Introducing a new floodplain scheme in ORCHIDEE (version 7885): validation and evaluation over the Pantanal wetlands

Abstract. Adapting and improving the hydrological processes in land surface models are crucial given the increase in the resolution of the climate models to correctly represent the hydrological cycle. The present paper introduces a floodplain scheme adapted to the higher-resolution river routing of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model. The scheme is based on a sub-tile parameterisation of the hydrological units – a hydrological transfer unit (HTU) concept – based on high-resolution hydrologically coherent digital elevation models, which can be used for all types of resolutions and projections. The floodplain scheme was developed and evaluated for different atmospheric forcings and resolutions (0.5∘ and 25 km) over one of the world's largest floodplains: the Pantanal, located in central South America. The floodplain scheme is validated based on the river discharge at the outflow of the Pantanal which represents the hydrological cycle over the basin, the temporal evolution of the water mass over the region assessed by the anomaly of total water storage in the Gravity Recovery And Climate Experiment (GRACE), and the temporal evaluation of the flooded areas compared to the Global Inundation Extent from Multi-Satellites version 2 (GIEMS-2) dataset. The hydrological cycle is satisfactorily simulated; however, the base flow may be underestimated. The temporal evolution of the flooded area is coherent with the observations, although the size of the area is underestimated in comparison to GIEMS-2. The presence of floodplains increases the soil moisture up to 50 % and decreases average temperature by 3 ∘C and by 6 ∘C during the dry season. The higher soil moisture increases the vegetation density, and, along with the presence of open-water surfaces due to the floodplains, it affects the surface energy budget by increasing the latent flux at the expense of the sensible flux. This is linked to the increase in the evapotranspiration related to the increased water availability. The effect of the floodplain scheme on the land surface conditions highlights that coupled simulations using the floodplain scheme may influence local and regional precipitation and regional circulation.

Estimating water surface evaporation losses under floating coverage: Modeling and Application

In arid and semiarid regions, floating covers can effectively reduce water surface evaporation to save water. However, the physical process of water surface evaporation greatly changes under floating coverage, and the open water surface evaporation estimation models cannot accurately quantify the water surface evaporation under floating coverage. A novel combination model for estimating water surface evaporation was developed, which can accurately estimate the water surface evaporation under floating coverage. (1) In view of the influence of the size and shape of the pore water formed by floating covers on the wind function in the water surface evaporation process, a wind function with the fetch of the evaporating water surface and wind speed as independent variables was established, and the calculation model of the aerodynamic term was modified. (2) Aiming at the influence of the variations in the energy consumed by water evaporation and water temperature stratification on the estimation of water surface evaporation under floating coverage, the energy balance equation and equilibrium temperature of the water body under floating coverage were established, and the calculation model of the radiation term was modified. Finally, the established evaporation combination model was verified by an experiment on water surface evaporation covered by spheres. The results showed that the estimation model established could accurately quantify the water surface evaporation under floating coverage. For arid and semiarid areas, the new evaporation estimation model can effectively help in decision-making for water surface evaporation prevention and water savings and promote water resource management.

Phycoremediation of crude oil polluted water from selected water sources in Ogoniland, Rivers State, Nigeria.

Crude oil exploitation in the Niger Delta, particularly in Ogoniland, brought environmental devastation occasioned by petroleum pollution, as farmlands and water sources were destroyed. This study was designed to remediate crude oil contaminated water obtained from water sources in Ogoniland using two green algal species. Thirty water samples were collected from eight different water sources. The samples were analysed for total petroleum hydrocarbon (TPH) using gas chromatography/flame ionization detector (GC/FID). Algal samples were collected from Ogba River and at wetland in Military Hospital Benin, Edo State, Nigeria. The algal samples were identified, screened, optimized and grown in Bold basal medium. Results obtained from the determination of TPH showed that the infiltrated pond (Exc) sample site had the highest concentration among all the sites sampled with 198.8329 μg/L, R2 with 134.1296 μg/L, R1 with 108.9394 μg/L, R3 with 105.8011 μg/L, R4 with 98.442 8 μg/L, the hand-dug wells (Wll) had 9.6586 μg/L while the borehole (Bhl) had the lowest with 1.8310 μg/L. It was deduced that pollution of water sources was principally because of pollutants washed from the soil environment into the open surface water sources via run-off rather than through the seepage from the underground aquifers, incriminating illegal oil mining and artisanal refining. Results obtained from the analysis of algal growth medium indicated that the two algal species were able to absorb the hydrocarbon contaminants, albeit at different rates, corresponding with the algal growth rate. Analysis of algal biomass after 4 weeks of remediation showed that from the initial 10.27 μg/20 mL added to the growth medium, the highest TPH mean value of 0.490 μg/20 mL was extracted from Ulothrix zonata (F.Weber & Mohr) Kützing biomass grown in Exc compared to 0.344 μg/20 mL of TPH extracted from Chlorella sorokiniana Shihira & R.W.Krauss grown in the same sample site. Also, Ulothrix zonata had higher TPH yield 0.023 μg/20 mL in Bhl compared to Chlorella sorokiniana 0.021 μg/20 mL of TPH from the same water source. This result indicated Ulothrix zonata had superior TPH phycoremediation ability to Chlorella sorokiniana. While the present study calls for deployment of the algal species for field trial, it is strongly recommended that crude oil pollution should be discouraged.

Land–Water Transition Zone Monitoring in Support of Drinking Water Production

Water utilities often use extended open surface water reservoirs to produce drinking water. Biotic and abiotic factors influence the water level, leading to alterations in the concentration of the dissolved substances (in cases of flood or drought), entry of new pollutants (in case of flooding) or reduction in the availability and inflow speed of water to the treatment plant (in case of drought). Spaceborne image analysis is considered a significant surrogate for establishing a dense network of sensors to monitor changes. In this study, renowned inundation mapping techniques are examined for their adaptability to the inland water reservoirs’ conditions. The results, from the Polyphytos open surface water reservoir in northern Greece, showcase the transferability of the workflows with overall accuracies exceeding—in cases—98%. Hydroperiod maps generated for the area of interest, along with variations in the water surface extent over a four-year period, provide valuable insights into the reservoir’s hydrological patterns. Comparison among different inundation mapping techniques for the surface water extent and water level reveal challenges and limitations, which are related to the spatial resolution, the data take frequency and the influence of the landscape synthesis beyond the water reservoir boundaries.

The performance of SPEI integrated remote sensing data for monitoring agricultural drought in the North China Plain

Agricultural drought is significantly affecting sustainable crop production. One of climate-based drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) calculated by the difference between precipitation and potential evapotranspiration (PET), is being more and more widely employed to characterize the spatio-temporal pattern of agricultural drought. However, substantial uncertainties exist in the current PET methods due to unrealistic configurations of the heterogeneity of crop surface characteristics or complicated parameterization scheme. In this study, standard Penman–Monteith (PM) model is modified and derived by meteorological factors and leaf area index (LAI) and albedo data based on remote sensing. Then, the modified SPEI was calculated by the monthly difference between precipitation and PM model integrated remote sensing data (referred as PMRS) over the North China Plain (NCP) between 1982 and 2016. Comparing with the FAO56 reference evapotranspiration (referred as PMRC) and a simplified version of standard PM over open-water surface (referred as PMOW), this study examines how well the PMRS-SPEI captures drought evolution and impacts on crop growth and yield over the NCP in order to evaluate its performance in agricultural drought monitoring. The comparison of SPEIs based on three evapotranspiration equations with soil water moisture in root depth shows that a 6-month lag can be used as the optimum time scale over the NCP. Additionally, the correlation of PMRS-SPEI performs better than PMRC-SPEI and PMOW-SPEI. For typical drought events, PMRS-SPEI6 shows remarkable smaller (larger) severe drought values between April and June (August and October) and a shorter (longer) recovery period in the growing season for wheat (maize). Comparing to PMRC-SPEI6 and PMOW-SPEI6, the PMRS-SPEI6 shows better performance when examining the Vegetation Health Index and Composite Index of Crop Yield Reduction. Additionally, climate-induced crop yield correlates with PMRS-SPEI6 better than PMOW-SPEI6 and PMRC-SPEI6, particularly in the emergence and filling stages for winter wheat, and silking stage for summer maize. These results demonstrate that integrating remotely sensed data can enhance the agricultural drought monitoring accuracy of SPEI.

Interactions of hydrology, geochemistry, and biodiversity in woodland ponds located in riverine floodplains: case study from Scotland

The Gore Glen pond is located in the forested floodplain of the Gore River, in the Mid-Lothian region near Edinburgh, Scotland. This work has considered in detail the hydrology, hydrochemistry, and biodiversity of the pond together with all their interactions and in addition interactions with the adjacent Gore River. It is important as it is one of few studies considering all these issues for a pond located in a riverine floodplain. This work shows the pond is connected to the Gore River for discharge events in the river larger than a 1 in 5-year return period. For these events, the pond acts as an online storage feature and will attenuate the flow, thus contributing towards the mitigation of downstream flooding. These large events are also a potential source of the large amount of sediments, as well as adsorbed chemicals, accumulated in the pond. The open water surface of the pond is covered by duckweed, Lemna minor, for most of the year, and that has profound implications for the hydrobiological community and biogeochemical cycling. The system is characterised by nutrient release from sediments due to the extensive hypolimnion anoxia in the summer/autumn period caused by the decomposition of organic matter. Algae are mostly represented by epiphytic diatoms and the cyanobacterium Microcystis, but their development appears to be constrained by light penetration. The eutrophic conditions are also conducive for the population of Difflugia (Protozoa, Rhizopoda). This work improves our understanding of the ecological relations of testate amoebae—an important group which has recently been used as biological indicators for the analysis of paleoecological relationships and paleogeographical reconstructions.