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Freshwater aquaculture plays an important role in the global aquaculture industry. The success of freshwater aquaculture relies on the integration of bio-ecological remediation technologies to ensure its sustainable development. This paper systematically reviews the global literatures on bio-ecological remediation of freshwater aquaculture environments from 1990 to 2021, and discusses in detail the research progress and status quo in this field using both bibliometric analysis and content analysis. Our results indicate that the number of publications per year has increased year by year, with a particularly rapid increase after 2015. Institutions and researchers from China and the USA publish the greatest number of papers and contribute the most to this field. By analyzing the research progress in this field, we also find that the protection and restoration of freshwater aquaculture environments has received attention since as early as 1990, such as the application of constructed wetlands and recirculating aquaculture systems. Recently, researchers have increasingly focused on the use of microbial communities in remediation. Furthermore, vanRijn, J's papers are of great value to the research in this field. In content analysis, the application of primary technologies, including plant selection, aquatic animals, microorganisms, and biological filtration and purification equipment, as well as ecological engineering technologies with combinations of various types of organisms, is described to improve the effectiveness and efficiency of remediation. The performance, advantages, disadvantages, or limitations and prospects of these technology applications are analyzed in detail. By comparison, ecological engineering is shown to be the best remediation technology, being most comprehensive, and well-established. Taken together, this paper composes and summarizes existing work in this field, and provides guidance for future research on the improvement of existing technologies and the development of new technologies, with the aim of enhancing remediation capability, improving ecological sustainability and ensuring economic viability.

Due to the impacts of hydrological and ecological processes on water quality, discharges from upstream catchments have induced significant pollution to the recipients. This study aims to investigate the possible pollution sources from catchments with different types of land use and landscape patterns and develop the relationships between water quality and the catchment hydro-geological and environmental variables. Data from 10 monitoring sites in Trondheim formulated the basis of the case study. Thermotolerant coliform bacteria (TCB) and total phosphorus (TP) were applied as main indicators to represent the water quality in the recipient rivers, streams and in Trondheim Fjord. Based on the GIS-oriented spatial analysis, 15 hydro-geographical and landscape parameters were selected as explanatory variables. Multiple linear regression (MLR) models were developed at catchment and river reach scales to study correlations between the explanatory variables and the response variables, TCB and TP, in rain and snow seasons. The study showed that the spatial landscape patterns resulted in differences in the concentrations of TCB and TP in the recipients. The agricultural land was shown to be the main pollution source, leading to a higher concentration of TP in streams. Buildings, roads, and other impervious areas have induced an increase in both TCB and TP. In contrast, the forest areas, lakes, river density and steep river slopes were shown to have capacity to filter incoming P-rich runoff, thus prevent pollutant conveyance and accumulation in recipients. HIGHLIGHTS A GIS-based topographical and landscape analysis was performed.; The composition and configuration of the landscape were analysed. Fifteen indicators were selected as explanatory variables.; MLR models were developed to study the relations between landscape variables and water quality indicator TCB and TP.; The agricultural land was shown to be the main pollution source.; TP is more sensitive to land use and landscape patterns than TCB.;

The effects of watershed subdivisions on hydrological simulations have not been evaluated in Arctic conditions yet. This study applied the Soil and Water Assessment Tool and the threshold drainage area (TDA) technique to evaluate the impacts of watershed subdivision on hydrological simulations at a 5,913-km2 Arctic watershed, Målselv. The watershed was discretized according to four TDA scheme scales including 200, 2,000, 5,000, and 10,000 ha. The impacts of different TDA schemes on hydrological simulations in water balance components, snowmelt runoff, and streamflow were investigated. The study revealed that the complexity of terrain and topographic attributes altered significantly in the coarse discretizations: (1) total stream length (−47.2 to −74.6%); (2) average stream slope (−68 to −83%); and (3) drainage density (−24.2 to −51.5%). The spatial density of weather grid integration reduced from −5 to −33.33% in the coarse schemes. The annual mean potential evapotranspiration, evapotranspiration, and lateral flow slightly decreased, while areal rainfall, surface runoff, and water yield slightly increased with the increases of TDAs. It was concluded that the fine TDAs produced finer and higher ranges of snowmelt runoff volume across the watershed. All TDAs had similar capacities to replicate the observed tendency of monthly mean streamflow hydrograph, except overestimated/underestimated peak flows. Spatial variation of streamflow was well analyzed in the fine schemes with high density of stream networks, while the coarse schemes simplified this. Watershed subdivisions affected model performances, in the way of decreasing the accuracy of monthly streamflow simulation, at 60% of investigated hydro-gauging stations (3/5 stations) and in the upstream. Furthermore, watershed subdivisions strongly affected the calibration process regarding the changes in sensitivity ranking of 18 calibrated model parameters and time it took to calibrate. HIGHLIGHTS The annual mean PET, ET, and lateral flow slightly decreased, while rainfall, surface runoff and water yield slightly increased with the increase of TDAs.; The fine TDAs produced finer and higher ranges of snowmelt runoff volume across the watershed.; All TDAs had similar capacities to replicate the observed tendency of monthly mean streamflow hydrograph, except overestimated/underestimated peak flows.; Spatial variation of streamflow was well analysed in the fine schemes compared to the coarse ones.; The scales of watershed subdivisions affected model performances, and sensitivity ranking of 18 calibrated model parameters in five hydrological subgroup processes (e.g. surface runoff, lateral flow, snowmelt, channel water routing, and goundwater) and time taking for calibration.;

The high-resolution Climate Forecast System Reanalysis (CFSR) data have recently become an alternative input for hydrological models in data-sparse regions. However, the quality of CFSR data for running hydrological models in the Arctic is not well studied yet. This paper aims to compare the quality of CFSR data with ground-based data for hydrological modeling in an Arctic watershed, Målselv. The QSWAT model, a coupling of the hydrological model SWAT (soil and water assessment tool) and the QGIS, was applied in this study. The model ran from 1995 to 2012 with a 3-year warm-up period (1995–1997). Calibration (1998–2007), validation (2008–2012), and uncertainty analyses were performed by the Sequential Uncertainty Fitting Version 2 (SUFI-2) algorithm in the SWAT Calibration Uncertainties Program for each dataset at five hydro-gauging stations within the watershed. The objective function Nash–Sutcliffe coefficient of efficiency for calibration is 0.65–0.82 with CFSR data and 0.55–0.74 with ground-based data, which indicate higher performance of the high-resolution CFSR data than the existing scattered ground-based data. The CFSR weather grid points showed higher variation in precipitation than the ground-based weather stations across the whole watershed. The calculated average annual rainfall by CFSR data for the whole watershed is approximately 24% higher than that by ground-based data, which results in some higher water balance components. The CFSR data also demonstrates its high capacities to replicate the streamflow hydrograph, in terms of timing and magnitude of peak and low flow. Through examination of the uncertainty coefficients P-factors (≥0.7) and R-factors (≤1.5), this study concludes that CFSR data is a reliable source for running hydrological models in the Arctic watershed Målselv. HIGHLIGHTS The high-resolution CFSR dataset has higher performance than the existing scattered ground-based dataset in terms of statistical coefficients, R2, NSE, and RSR.; The CFSR dataset has higher simulation results for some water balance components, e.g., actual evapotranspiration, lateral flow, water yield, etc., than the scattered conventional dataset.; The CFSR demonstrates its high capacities to replicate the streamflow hydrograph.; Uncertainty analysis reveals that CFSR is a reliable weather input for running hydrological models in the Arctic watershed Målselv.; The emerging and open-source QSWAT is a valuable tool for the SWAT scientific community because of its upgraded availability and functionality compared to other SWAT interfaces.;

Bioretention facilities with different inflow concentrations, growing media and plants were examined to determine whether the soil in these facilities was polluted with heavy metals and whether runoff had obvious toxic effects on plants. Using Beijing soil background value as the standard, the soils were evaluated by bioaccumulation index and single factor index. The results show that stormwater runoff containing Cu caused slight pollution in soils, and stormwater runoff containing Zn and Pb was not polluted. Nemerow comprehensive index evaluation revealed that the heavy metals content in the facilities containing vermiculite (a yellow or brown mineral found as an alteration product of mica and other minerals, used for insulation or as a moisture-retentive medium for growing plants) and perlite (a form of obsidian characterized by spherulites formed by cracking of the volcanic glass during cooling, used as insulation or in plant growth media) were higher than the standard. High influent concentration caused significantly higher heavy metals content in plants. While Pb accumulation in the two studied plants was the highest, Cu and Zn accumulation, which are essential for plant growth, was relatively low. The contents of the three heavy metals in the studied plants also exceeded their corresponding critical values.

The Arctic region is the most sensitive region to climate change. Hydrological models are fundamental tools for climate change impact assessment. However, due to the extreme weather conditions, specific hydrological process, and data acquisition challenges in the Arctic, it is crucial to select suitable hydrological model(s) for this region. In this paper, a comprehensive review and comparison of different models is conducted based on recently available studies. The functionality, limitations, and suitability of the potential hydrological models for the Arctic hydrological process are analyzed, including: (1) The surface hydrological models Topoflow, DMHS (deterministic modeling hydrological system), HBV (Hydrologiska Byråns Vattenbalansavdelning), SWAT (soil and water assessment tool), WaSiM (water balance simulation model), ECOMAG (ecological model for applied geophysics), and CRHM (cold regions hydrological model); and (2) the cryo-hydrogeological models ATS (arctic terrestrial simulator), CryoGrid 3, GEOtop, SUTRA-ICE (ice variant of the existing saturated/unsaturated transport model), and PFLOTRAN-ICE (ice variant of the existing massively parallel subsurface flow and reactive transport model). The review finds that Topoflow, HBV, SWAT, ECOMAG, and CRHM are suitable for studying surface hydrology rather than other processes in permafrost environments, whereas DMHS, WaSiM, and the cryo-hydrogeological models have higher capacities for subsurface hydrology, since they take into account the three phase changes of water in the near-surface soil. Of the cryo-hydrogeological models reviewed here, GEOtop, SUTRA-ICE, and PFLOTRAN-ICE are found to be suitable for small-scale catchments, whereas ATS and CryoGrid 3 are potentially suitable for large-scale catchments. Especially, ATS and GEOtop are the first tools that couple surface/subsurface permafrost thermal hydrology. If the accuracy of simulating the active layer dynamics is targeted, DMHS, ATS, GEOtop, and PFLOTRAN-ICE are potential tools compared to the other models. Further, data acquisition is a challenging task for cryo-hydrogeological models due to the complex boundary conditions when compared to the surface hydrological models HBV, SWAT, and CRHM, and the cryo-hydrogeological models are more difficult for non-expert users and more expensive to run compared to other models.

The Storm Water Management Model (SWMM) has been globally used for stormwater management. However, the calibration and evaluation of SWMM for historical rainfall-runoff events in partially separated and combined drainage systems is rarely reported in Norway. In this study, we employed SWMM for the Grefsen catchment in Oslo, Norway. The main problem in the Grefsen basin is combined sewer overflow. We calibrated the model parameters based on 32 rainfall-runoff events and evaluated the calibrations using four indicators: Nash-Sutcliffe efficiency, percentage bias, and continuity errors for runoff and flow. There were 32 successful calibrations using Nash-Sutcliffe efficiency, 30 successful calibrations using percentage bias, 32 successful calibrations using continuity error runoff, and four successful calibrations using continuity error flow. SWMM can well simulate the dynamics of hydrological and hydraulic systems in this catchment. Among the 124 validations, there were 88 successful simulations using Nash-Sutcliffe efficiency, 35 successful simulations using percentage bias, 124 successful simulations using continuity error for runoff, and 62 successful simulations using continuity error for flow. The results show that percentage bias and continuity error flow are the critical indicators for model calibration. This study reveals the large uncertainty caused by calibration and validation criteria, and highlights the importance of considering model computation error. [ABSTRACT FROM AUTHOR]