Ecohydrology & Hydrobiology最新文献

In this study, the agro-hydrological model Soil and Water Assessment Tool + (SWAT+) is used to simulate runoff in an uncontrolled agricultural catchment with paddy fields irrigated by plots submersion. The objectives are to evaluate the ability of this new, improved version of the SWAT model to reproduce the flows in a complex catchment and to analyse the evolution of these flows over the historical period 1986-2020 (35 years). Sensitivity analysis, calibration and validation were carried out with monthly flow data. The decision tables for irrigation operations and reservoir water release were filled in the SWAT+ Editor to establish the reservoir water balance. The Mann-Kendall trend test with the threshold of the standard normal statistic = 1.96, was applied to the time series of flows to the Nanan Reservoir. The results reveal that SWAT+ is more sensitive to eight parameters, including the new CN3_SWF parameter (-0.04329), which gave the user control of the soil saturation level. Good performances were obtained during calibration and validation, respectively: NSE (0.78; 0.69); R² (0.81; 0.70); PBIAS (-18.58; -23.9) and RSR (0.47; 0.56), with a tendency to slightly overestimate flows. The analysis shows that flows to the Nanan Reservoir are highly variable yearly, with a non-significant upward trend (|Z|=1.3<1.96) from 1986 to 2020. The water balance reveals that the runoff inflow generated will compensate for water withdrawals for irrigation of the Nanan paddy scheme during this period. Furthermore, this study provides a methodological framework for SWAT+ reservoir model calibration in an uncontrolled catchment.

The present study focused on the abundance of bacteria in the sand of marine beaches on the southern Baltic Sea coast which differed in the level of anthropogenic pressure. The results showed that the maximum (17.60·10⁶cells · g⁻¹dw.) bacterial abundance was noted on the beach characterized by the highest level of anthropogenic pressure and minimum (10.48·10⁶cells · g⁻¹dw.) on the beach located in the Słowiński National Park. Generally, differences were found in the studied abundance and biomass of bacteria in all investigated beaches in their horizontal profile. The maximum (18.81–23.52·10⁶cells · g⁻¹dw.) density of bacteria was recorded in the dry zones, i.e., dune and the middle part of the beach, and the minimum (9.04–10.52·10⁶cells · g⁻¹dw.) in the wet zones, i.e., under seawater surface and at the waterline. The differences in the abundance of bacteria were found between the surface and subsurface sand layers in the studied beaches. Usually, the highest (19.60·10⁶cells · g⁻¹dw.) number of bacterial cells was determined in the surface sand layer, while with an increasing depth their number decreased. A seasonal variation in bacterial abundance was also documented in the studied beaches. This study resulted in increased knowledge on marine bacteriopsammon abundance, which, as a secondary producer, plays a very important role as the main link between primary producers and higher trophic levels of benthic food webs in marine ecosystems.

Oil spills are a serious pollution problem in water ecosystems, causing significant damage to living things and the environment. The demand for devices to handle oil remediation is increasing due to the frequent occurrence of oil spills. To date, numerous works have been reported to address this pollution problem, but most of them do not utilize Internet of Things (IoT) technology. Having an IoT system of this kind would improve operational efficiency by providing real-time data, alerts, and notifications of oil pollution through monitoring systems. This study presents the development of an IoT-based automatic oil-water separator device to support an oil pollution monitoring system in water ecosystems. The built device consists of sensors, a microcontroller, and an actuator, with the capability to automatically detect oil pollution and perform water-oil separation. The device incorporates a monitoring system. The water-oil separation was carried out by applying semi-permeable membrane nanotechnology. Moreover, the device has undergone a series of oily-water separation experiments to simulate oil pollution, achieving an oil separation efficiency of 62.8% (on average) with good repeatability. Additionally, the automatic device is developed with IoT pairing with a website application for an online monitoring system. Users can monitor the process using a personal computer or smartphone via the web/mobile application at any time and from any place. It is of interest to explore this further since it offers an effective and implementable method to solve oil pollution problems in real-world applications.

The anthropogenic activities along with climate change have adversely exploited the freshwater wetland ecosystems. The environmental health of wetlands may be analysed with the application of mathematical models considering its hydrodynamics, water quality, and ecology characteristics. However, it is observed that the models have a lesser range of applications on freshwater wetlands than that of lakes and rivers in dealing with major problems, such as eutrophication and urbanization. This may be associated with the complexity of the system, data scarcity and absence of information regarding boundary conditions. Hence, the aim of this study is to highlight certain aspects of various mathematical models applied to freshwater wetlands including their different features, limitations, parameters considered, accessibility, and area of application. From the detailed analysis of their inherent features and application strategies, a decision making framework is also developed to aid the modellers and provide a holistic support in the selection of the most suitable models.

Climate change is causing serious problems in various economic sectors in particular involving water management. For this reason, it is extremely important to conduct research to identify climate change trends and better understand them. This study was carried out in the Dim Stream basin in the Western Mediterranean region (Turkey), which is particularly vulnerable to climate change. The study used flow data from two flow observation stations (FOS) and meteorological records such as wind speed, average flow, precipitation, temperature, evaporation, radiation, and relative humidity for 1984-2017. These data showed the changes between flow and hydrometeorological variables using linear regression analysis, coefficient of variation, t-test and correlation analysis. It has been determined that there has been a rapid decrease in the average flow of the FOS number 09-006 since 1995 and the average flow of the FOS number 09-013 since 1999. Also, it was demonstrated that the average relative humidity (RH_ave), average temperature (T_ave), average precipitation (Pave), total precipitation (Pt) and maximum precipitation (P_max) meteorological variables were most affected by climate change in the basin. Furthermore, it was found that the most changes were Qy_ave (67.60%), T_min (48.23%), P_max (36.43%), P_ave (33.91%), P_t (33.90%), and RH_ave (2.63%) in FOS numbered 09-013. Moreover, it was concluded that climate change variability had developed trends towards a rapid decrease in the flow values at the flow observation stations in Dim Stream. These results show that plans and measures for the efficient and sustainable management of water resources in this region must be implemented immediately.

Land consolidation projects (LCP) has been applied in various countries to decrease land fragmentation, to give field road and to create more appropriate regular parcel shapes besides many benefits to farmers. Moreover, LCP help to decrease the cost of irrigation system establishment. Türkiye aims to modernize open irrigation systems into pressurized systems with LCPs to save water due to climate change and global warming. However, previously published studies on the effect of LCP on designing pressurized irrigation network are not adequate. In this study, Eymir Village LCP in Türkiye was chosen as the material to investigate how can LCP affect the cost of the establishment of a pressurized irrigation system. In this context, two similation of irrigation systems are designed with help of geographic information systems (GIS) and are analyzed by COPAM (Combined Optimization and Performance Analysis Model) to optimize the hydraulic performance. Results show that land consolidation proved to be an effective tool to solve spatial problems related to improving the irrigation systems, technical problems related to the performance of the networks, and the equity of services (guaranteeing 98% satisfaction of users). And, it has the most important effect on the economic feasibility of pressurized irrigation network establishment whose cost can be decreased by 13.6% by LCP.

Pharmaceuticals are unique class of water pollutants due to their ability to modify the physiological effects of living organisms at low doses. Intensive use in healthcare as well as insufficient removal in conventional wastewater treatment processes make pharmaceuticals ubiquitous in the aquatic environment. The study aimed to assess the load of selected non–steroidal anti–inflammatory drugs (NSAIDs) in the influent and effluent from the wastewater treatment plant (WWTP) in Słupsk. Samples were collected in the period between May and September 2021. Once taken samples were filtered and the analytes were extracted using solid phase extraction (SPE) and then analyzed using the ultra–high performance liquid chromatography. Ibuprofen (IBU), salicylic acid (SA), acetylsalicylic acid (ASA), naproxen (NPX), ketoprofen (KET), and diclofenac (DIC) were found in raw and treated wastewater. Detected concentration ranged from 1.656 μg L^–1 to 25.912 μg L^–1 in the influent, and from 0.676 µg L^–1 to 10.484 µg L^–1 in the effluent. Removal was incomplete and its efficiency ranged between 57.3 % and 81.4 %. The ecotoxicological assessment was performed using a set of certified test organisms including marine bacteria (Aliivibrio fscheri), freshwater crustaceans (Daphnia magna), and freshwater plants (Lemna minor). Toxic concentrations ranged from 4.50 to 18.82 mg L^–1 for marine bacteria after 30 min of exposure, from 27.11 to 74.77 mg L^–1 for crustaceans after 48 h of exposure, and from 10.70 to 29.67 mg L^–1 for aquatic plants after 7 days of exposure. Studied pharmaceuticals were mostly classified as toxic or harmful to test organisms.

The golden alga Prymnesium parvum plays a key role in harmful algal blooms (HABs) worldwide, including the massive fish kills that occurred in the Oder river (Poland and Germany) in 2022. However, studies addressing this ecological disaster have to date focused mainly on the physicochemical parameters of the water, and overlooked the overall impact that environmental samples could have on aquatic organisms other than fish. Therefore, the present study evaluated the toxicological effect of the bloom by subjecting samples of the river water to microbiotests comprising organisms from two trophic levels: producers (Pseudokirchneriella subcapitata), and consumers (Daphnia magna and Thamnocephalus platyurus). In addition, the study examined the relative concentrations of prymnesins and the physicochemical parameters of the water samples, and 18S rRNA gene sequencing was used to examine eukaryotic assemblages in the samples. Among the tested organisms, D. magna was found to be most sensitive to the water samples from the disaster, with a maximum mortality of 90 % after 24 h. The 18S rRNA gene analysis found a high level of P. parvum in the tested samples during the ecological disaster (up to 9.2 %) compared to one month later (0.1 %). Our data indicates a notable increase in P. parvum and prymnesin level around the time of the ecological disaster in the Oder River in 2022, and that this may have played a part in its occurrence; in addition, D. magna may be an effective bioindicator for identifying the risk of P. parvum blooms to invertebrates.

In Punjab, Pakistan, the “Warabandi” principle guides the distribution of surface water in tertiary canal networks to each farm. The allocated amount is proportional to farm size and provided according to a predetermined schedules in a 7-day fixed rotation. Limited canal water and rigid rotations of the Warabandi-guided water allocation led to unsustainable pumping of groundwater and relatively low field application efficiency. Using both site monitoring and modelling, we assessed cotton irrigation scheduling under current practices and the planning options in the context of the Warabandi principle. The farming practices of two raised-bed furrow cotton fields were intensively monitored at the Mungi distributary canal command area in Punjab. The AquaCrop model was parameterized and validated using 2019 and 2020 datasets and then applied to assess four irrigation scheduling scenarios. Scenario 1 reflects the current irrigation practice under canal water and groundwater use, while for scenarios 2, 3, and 4, solely canal water was considered and irrigation followed a fixed rotation of 7-days, 14-days, and targeted intervals, respectively. According to simulations’ outputs, scenarios 2, 3, and 4 resulted in better performance compared to the current practices in both fields by reducing percolation substantially up to 90% below the root zone and lowered soil evaporation by up to 27% enebling similar yields ∼2.2 ton/ha raw cotton and higher water productivity. Under the frame conditions of Warabandi, scenario 4 was a promising option for introducing more flexible and demand-oriented irrigation at the farm level targeting cotton's water-stress sensitive growth stages by adapting irrigation application to rainfall events and refilling the soil slightly below field capacity level during each irrigation event to reduce percolation. The study delivered detailed information about cotton irrigation scheduling for on-farm water management, considering a bottom-up approach in Punjab.

Extreme meteorological and hydrological phenomena, including high air temperatures and rainstorms, are becoming increasingly dangerous, causing floods and inundations, as well as long periods without precipitation, which lead to droughts. Green roofs may be one of the possible measures providing solutions to these problems. Rainfall, runoff and water quality data from three different intensive green roof models covered with wildflower meadows (WFs) over 20 months have been analysed to establish the extent to which the type of drainage layer affects hydrological performance. The field experiment was conducted at the Warsaw University of Life Sciences Water Centre park from November 2019 to November 2021. The monitoring of the quality and quantity of runoff was carried out on three models of green roofs incorporating wildflower meadows with drainage layers of 2 cm (WF 1) and 4 cm (WF 2) of polypropylene mat, as well as 6 cm of chalcedony (WF 3), in an urbanized area under moderate climate conditions. The model with the 4 cm polypropylene mat drainage layer retained approx. 6 % more rainwater compared to the model with the one made of chalcedony, and 4 % more than the one with the 2 cm polypropylene mat. Phosphates were detected in most of the leachates from all the wildflower-covered green roof models at 0 ÷ 0.459 mg PO4-P/L, 0 ÷ 0.402 mg PO4-P/L, and 0÷0.360 mg PO4-P/L for WF 1, WF 2 and WF 3. This may suggest that the type of drainage layer was not an important source of phosphates in the leachates.