Selection of aquatic microbiota exposed to the herbicides flufenacet and metazachlor.

Herbicides are important, ubiquitous environmental contaminants, but little is known about their interaction with bacterial aquatic communities. Here, we sampled a protected natural freshwater habitat and characterised its microbiome in interaction with herbicides. We evolved the freshwater microbiomes in a microcosm assay of exposure (28 days) to flufenacet and metazachlor at environmental concentrations of 0.5, 5 and 50 µg L-1 . Inhibitory effects of herbicides were exemplarily assessed in cultured bacteria from the same pond (Pseudomonas alcaligenes, Paenibacillus amylolyticus and Microbacterium hominis). Findings were compared to long-term concentrations as provided by local authorities. Here, environmental concentrations reached up to 11 µg L-1 (flufenacet) and 76 µg L-1 (metazachlor). Bacteria were inhibited at minimum inhibitory concentrations far above these values; however, concentrations of 50 µg L-1 of flufenacet resulted in measurable growth impairment. While most herbicide-exposed microcosm assays did not differ from controls, Acidobacteria were selected at high environmental concentrations of herbicides. Alpha-diversity (e.g., taxonomic richness on phylum level) was reduced when aquatic microbiomes were exposed to 50 µg metazachlor or flufenacet. One environmental strain of P. alcaligenes showed resistance to high concentrations of flufenacet (50 g L-1 ). In total, this study reveals that ecologic imbalance due to herbicide use significantly impacts aquatic microbiomes.

Land use change and climate dynamics in the Rift Valley Lake Basin, Ethiopia.

Land use and climate dynamics have a pronounced impact on water resources, biodiversity, land degradation, and productivity at all scales. Thus, in this study, we present the spatio-temporal dynamics of land use change and climate aiming to provide a scientific evidence about gains and losses in major land use categories and associated drivers and significancy and homogeneity of climate change. To this end, Landsat images and historical climate data have been used to determine the dynamics. In addition, population census data and land use policy have been considered to assess the potential drivers of land use change. The spatio-temporal land use dynamics have been evaluated using transition matrix and dynamics index. Likewise, shifts in the climate data were analyzed using change point analysis and three homogenous climate zones have been identified using principal component analysis. The results show that, from 1989 to 2019, the areal percentage of agricultural land increased by 27.5%, settlement by 0.8%, and barren land 0.4% while the natural vegetation, wetland, water body, and grass land decreased by 24.5%, 1.6%, 0.5%, and 2.1%, respectively. The land use dynamics have been stronger in the first decade of the study period. An abrupt shift of climate has occurred in the 1980s. In the last four decades, rainfall shows a not significant decreasing trend. However, a significant increasing trend has been observed for temperature. Rapid population growth, agricultural expansion policy, and climate variability have been identified as the underlying drivers of land use dynamics.

Spatial and temporal assessment of human-water interactions at the Inle Lake, Myanmar: a socio-hydrological DPSIR analysis.

Freshwater resources as a key aspect of socio-economic development, provide a large number of services in human and environmental systems. Nevertheless, human appropriation of these water resources and the modification of landscapes lead to potential threats on water availability and quality from local to global scales. The Inle Lake in Myanmar is an economically, traditionally, and ecologically important freshwater ecosystem that faced severe degradation from the 2000s. In its catchment area, a Driver-Pressure-State-Impact-Response (DPSIR) framework is applied for an assessment period of 30 years from 1990 to 2020. The analysis results are complemented with a socio-hydrological survey, water quality assessment, a land use classification based on ground truth and satellite data, and hydrologic models. The resulting land use changes, - 13% forest, + 13% agriculture, and + 5% urban areas, lead to increased water yield, decreased evapotranspiration, and increased sediment yield. Together with other drivers and pressures such as climate change and anthropogenic pollution, these human activities are major threats for freshwater resources and the ecosystem. However, the existing awareness of the local population for the environmental degradation is obstructed by national and international crises and responses to negative developments can accelerate degradation if they are unplanned and short-term solutions. Our study shows that environmental degradation processes have a complex nature and can only be tackled in a coordinated way with a long-term perspective. DPSIR is a suitable approach to assess human-water dynamics and disentangle the complex interconnectedness of social and environmental systems in freshwater ecosystems, even in data-scarce regions.

Effects of the herbicides metazachlor and flufenacet on phytoplankton communities - A microcosm assay.

Agrochemicals are the main pollutants in freshwater ecosystems. Metazachlor and flufenacet are two common herbicides applied in fall (i.e., August-October) to agricultural fields in Northern Germany. High concentrations of these herbicides are often found in adjacent aquatic ecosystems. Phytoplankton are one of the highly susceptible non-targeted aquatic organismal groups for herbicides and effects on phytoplankton may initiate a chain of consequences in meta communities through trophic interactions. Few studies have focused on responses of the phytoplankton community for metazachlor and, no studies have focused on flufenacet. We studied the effects of metazachlor and flufenacet on the phytoplankton community by conducting a microcosm experiment exposing natural fall phytoplankton communities to environmentally realistic concentrations as 0 (control), 0.5, 5 and 50 µg L-1 of metazachlor and flufenacet treatments over a 4-week period. We measured changes in density, composition (i.e., in phyla and species level), taxonomic diversity indices, and functional features of phytoplankton communities as a response to herbicides. A reduction in the density of Chlorophyta species (e.g., Koliella longiseta, Selenastrum bibraianum) and Cyanobacteria species (e.g., Merismopedia tenuissima and Aphanocapsa elegans) was observed in herbicide treatments compared to controls. The phytoplankton community shifted towards a high density of species from Bacillariophyta (e.g., Nitzschia fonticola and Cyclotella meneghiniana), Miozoa (i.e., Peridinium willei), and Euglenozoa (i.e., Trachelomonas volvocina) in herbicide treatments compared to controls. Metazachlor and flufenacet showed significant negative effects on taxonomic diversity indices (e.g., species richness, the Shannon-Wiener index) and functional features (e.g., functional dispersion and redundancy) of the phytoplankton communities, with increasing herbicide concentrations. Our study provides insights into direct, selective, and irrecoverable effects of metazachlor and flufenacet on phytoplankton communities in the short-term. The comprehensive understanding of these effects of environmentally realistic herbicide concentrations on aquatic biota is essential for a sustainable management of aquatic ecosystems in agricultural areas.

Assessing the impacts of Best Management Practices on nitrate pollution in an agricultural dominated lowland catchment considering environmental protection versus economic development.

Water quality is strongly affected by nitrate inputs in agricultural catchments. Best Management Practices (BMPs) are alternative practices aiming to mitigate the impacts derived from agricultural activities and to improve water quality. Management activities are influenced by different governmental policies like the Water Framework Directive (WFD) and the Renewable Energy Sources Act (EEG). Their distinct goals can be contrasting and hamper an integrated sustainable development. Both need to be addressed in the actual conjuncture in rural areas. Ecohydrological models like the SWAT model are important tools for land cover and land use changes investigation and the assessment of BMPs implementation effects on water quality. Thus, in this study, buffer strip, fertilization reduction and alternative crops were considered as BMPs and were implemented in the SWAT model for the Treene catchment. Their efficiency in terms of nitrate loads reduction related to implementation costs at the catchment scale was investigated. The practices correspond to the catchment conditions and are based on small and mid areal changes. Furthermore, the BMPs were evaluated from the perspective of ecologic and economic policies. The results evidenced different responses of the BMPs. The critical periods in winter were addressed by most of the BMPs. However, some practices like pasture land increase need to be implemented in greater area for better results in comparison to current activities. Furthermore, there is a greater nitrate reduction potential by combining BMPs containing fertilization reduction, buffer strips and soil coverage in winter. The discussion about efficiency showed the complexity of costs stipulation and the relation with arable land and yield losses. Furthermore, as the government policies can be divergent an integrated approach considering all the involved actors is important and seeks a sustainable development.

Evaluation of Land Use, Land Management and Soil Conservation Strategies to Reduce Non-Point Source Pollution Loads in the Three Gorges Region, China.

The construction of the Three Gorges Dam in China and the subsequent impoundment of the Yangtze River have induced a major land use change in the Three Gorges Reservoir Region, which fosters increased inputs of sediment and nutrients from diffuse sources into the water bodies. Several government programs have been implemented to mitigate high sediment and nutrient loads to the reservoir. However, institutional weaknesses and a focus on economic development have so far widely counteracted the effectiveness of these programs. In this study, the eco-hydrological model soil and water assessment tool is used to assess the effects of changes in fertilizer amounts and the conditions of bench terraces in the Xiangxi catchment in the Three Gorges Reservoir Region on diffuse matter releases. With this, the study aims at identifying efficient management measures, which should have priority. The results show that a reduction of fertilizer amounts cannot reduce phosphorus loads considerably without inhibiting crop productivity. The condition of terraces in the catchment has a strong impact on soil erosion and phosphorus releases from agricultural areas. Hence, if economically feasible, programmes focusing on the construction and maintenance of terraces in the region should be implemented. Additionally, intercropping on corn fields as well as more efficient fertilization schemes for agricultural land were identified as potential instruments to reduce diffuse matter loads further. While the study was carried out in the Three Gorges Region, its findings may also beneficial for the reduction of water pollution in other mountainous areas with strong agricultural use.

Simulation of streamflow and sediment with the soil and water assessment tool in a data scarce catchment in the three gorges region, china.

The Three Gorges Region in China is currently subject to a large-scale land use change, which was induced by the construction of the Three Gorges Dam on the Yangtze River. The relocation of towns, villages, and agricultural areas is expected to affect the water balance and increase erosion rates and sediment yields in the affected catchments. Hydrologic and water quality models are frequently used to assess the impact of land use changes on water resources. In this study, the eco-hydrological Soil and Water Assessment Tool (SWAT) model is applied to the Xiangxi Catchment in the Three Gorges Region. This paper presents the calibration and validation of streamflow and sediment loads at Xingshan gauging station. The calibration of daily streamflow resulted in a satisfactory fit of simulated and observed data, which is indicated by Nash-Sutcliffe efficiency (NSE) values of 0.69 and 0.67 for the calibration (1981-1986) and validation (1988-1993) periods, respectively. In contrast, the model was not able to simulate the monthly average sediment loads correctly, as indicated by very low NSE values of 0.47 (calibration) and 0.08 (validation). This might be due to inadequate representation of spatial rainfall variability by the available climate stations, insufficient input data, uncertainties in the model structure, or uncertainties in the observed sediment loads. The discussion of these possible reasons for the incorrect prediction of sediment loads by SWAT reveals the need for further research in the field of hydrological and water quality modeling in China.

Assessment of the Environmental Fate of the Herbicides Flufenacet and Metazachlor with the SWAT Model.

This study aims to assess the environmental fate of the commonly used herbicides flufenacet and metazachlor in the Northern German Lowlands with the ecohydrological Soil and Water Assessment Tool (SWAT model) and to test the sensitivity of pesticide-related input parameters on the modeled transport dynamics. The river discharge of the Kielstau watershed was calibrated (Nash-Sutcliffe efficiency [NSE], 0.83; = 0.84) and validated (NSE, 0.76; = 0.77) for a daily time step. The environmental fate of metazachlor (NSE, 0.68; = 0.62) and flufenacet (NSE, 0.13; = 0.51) was simulated adequately. In comparison to metazachlor, the simulated flufenacet concentration and loads show a lower model efficiency due to the weaker simulation of the stream flow. The in-stream herbicide loads were less than 0.01% of the applied amount in the observed time period and thus not in conflict with European Environmental Legislation. The sensitivity analysis showed that, besides the accurate simulation of stream flow, the parameterization of the temporal and spatial distribution of the herbicide application throughout the watershed is the key factor for appropriate modeling results, whereas the physicochemical properties of the pesticides play a minor role in the modeling process.

Examining characteristics and sampling methods of phosphor dynamics in lowland catchments.

Despite over two decades since the EU Water Framework Directive have passed, achieving the desired water quality in German surface waters remains challenging, regardless of efforts to reduce phosphorus inputs and associated environmental impacts. This study aims at analyzing the characteristics governing the concentrations of four key water quality parameters (total phosphorus, orthophosphate, particulate phosphate, and suspended solids) in two lowland catchments: the 50 km2 catchment of the Kielstau, Germany, and its 7 km2 tributary, the Moorau, which are dominated by agricultural land use. To this end, different sampling methods, particularly high-resolution precipitation event-based sampling and daily mixed samples, are conducted and evaluated, and their effectiveness is compared. The identification of sources and characteristics that affect phosphorus and suspended sediment dynamics, both in general and specifically during heavy precipitation events, is one focus of the study. Over a 15-year period, increasing concentrations of these parameters were observed in daily mixed samples, exhibiting distinct seasonal patterns-higher in summer and lower in winter-consistent with lowland catchment behavior. Particularly during heavy precipitation events, the smaller catchment exhibits a more complex and less predictable response to chemical concentrations compared with the dilution effect observed in the larger catchment. The results underline the complexity of phosphorus dynamics in small catchments and emphasize the importance of event-based sampling for capturing short-term concentration peaks for all four parameters, particularly beneficial regarding measuring suspended solids. While daily mixed samples capture average phosphorus concentrations, event-based sampling is crucial for detecting short-term spikes, providing a more comprehensive understanding of phosphorus dynamics.

A spatio-temporal analysis of environmental fate and transport processes of pesticides and their transformation products in agricultural landscapes dominated by subsurface drainage with SWAT.

Pesticides are detected in surface water and groundwater, endangering the environment. In lowland regions with subsurface drainage systems, drained depressions become hotspots for transport of pesticides and their transformation products (TPs). This study focuses on detailed modelling of the degradation and transport of pesticides with different physico-chemical properties. The objective is to analyse complex hydrological transport processes, to understand the temporal and spatial dynamics of the degradation and transport of pesticides. The ecohydrological model SWAT+ simulates hydrological processes as well as agricultural management and pesticide degradation, and can therefore be used to develop pesticide loss reduction strategies. This study focuses on modelling of three pesticides (pendimethalin, diflufenican, and flufenacet), and two TPs, flufenacet-oxalic acid (FOA) and flufenacet sulfonic acid (FESA). The study area is a 100-hectare farmland in the northern German lowlands of Schleswig-Holstein that is characterized by an spacious drainage network of 6.3 km and managed according to common conventional agricultural practice. SWAT+ modelled streamflow with very good agreement between observed and simulated data during calibration and validation. Regarding pesticides, the model performance for highly mobile substances is better than for non-mobile pesticides. While the transport of the moderately to very mobile substances via tile drains played an important role in both wet and dry conditions, no transport via tile drains was modelled for the highly sorptive and non-mobile pendimethalin. In conclusion, the model can reliably represent the degradation of moderately to very mobile pesticides in small-scale tile drainage-dominated catchments, as well as surface runoff-induced peak loads. However, it has weaknesses in accounting for the subsurface transport of non-mobile substances, which can lead to an underestimation of the subsequent delivery after precipitation events and thus underestimates the total load.

Integrated modeling of global change impacts on land and water resources.

There is a common scientific understanding that global change impact analysis, mitigation, and adaptation require interdisciplinary work. Integrated modeling could help to address the challenges associated with the impacts of global change. Particularly, integrated modeling that takes feedback effects into account will allow for the derivation of climate resilient land use and land management. Here, we call for more of such integrated modeling work focusing on the interdisciplinary subject of water resources and land management. As a proof-of-concept, we tightly couple a hydrologic (SWAT) and a land use model (CLUE-s) and illustrate the benefits of this coupled land and water modeling framework (LaWaCoMo) with a scenario on cropland abandonment induced by water stress. As compared to standalone model runs of SWAT and CLUE-s for the past, LaWaCoMo performs slightly better regarding measured river discharge (PBIAS: +0.8% and +1.5% compared at two gauges) and land use change (figure of merit: +6.4% and +2.3% compared to land use maps at two points in time). We show that LaWaCoMo is suitable for global change impact analysis as it is sensitive to climate and land use inputs as well as to management decisions. Our results shed light on the importance of feedback effects between land use and hydrology to assess impacts of global change on land and water resources accurately and consistently. To facilitate that the developed methodology can serve as a blueprint for integrated modeling of global change impacts, we used two freely available models that belong to the most widely used models in their respective disciplines.

Spatial distribution of water reservoirs in the Sota catchment (Benin, West Africa) and implications for local development.

Water is an indispensable resource for human being and the environment. This study analyses spatial distribution of water reservoirs in the Sota catchment with regards to livestock density, population density, rainfall distribution and geological structure of the Sota catchment, and assessed the state of these reservoirs. To this end, the geographic coordinates of water reservoirs were collected and the updated database of reservoirs census in Benin, was used. In addition, livestock and population census database, rainfall data from 1980 to 2016 of twelve (12) stations and geological database were processed in ArcGIS for generating respectively the spatial layers of livestock, population, rainfall and geological map of the catchment. The reservoirs' state has been appreciated by documents exploration and in situ observations. Single factor Regression analysis was conducted to understand the relation of each of the factors with the spatial distribution of the reservoirs in the Sota catchment. The results reveal that Sota catchment contains 35 small water reservoirs mostly concentrated in its central western and south western part. The reservoir density is 0.0026 km-2. Most of the reservoirs are located within areas where livestock density, population density and rainfall amount is high: 51%, 46% and 86% respectively. However, no significant relation was found between reservoirs distribution and livestock density, population density, and rainfall respectively in the catchment. The basement geological structures of the Sota catchment are associated with 71% of the reservoirs' location. The reservoirs are threatened by siltation, lack of pastoral facilities, poor maintenance and management. In fact, 100%, 86%, 74%, 71%, 40%, and 34% of reservoirs are respectively subjected to the issues of: absence of waterers, siltation, deteriorated dyke, eutrophication, inexistent management committee, and drying up in dry season. For sustainable local development purposes, more attention should be paid to basin management planning for construction of new reservoirs and to reservoirs 'maintenance. Future research on the reservoirs' sustainability and monitoring surveillance are recommended.

Assessment of seasonal and spatial water quality variation in a cascading lake system in Chennai, India.

Water quality and scarcity are among the most severe problems humans have been facing in the last decades. India, as a fast-developing country, is not an exception. The surface water quality has deteriorated due to anthropogenic activities. Another factor which impacts the water quality is the heavy rainfall during monsoon season. To maintain the quality and the sustainability of water resources, there is the need to study how human activities impact water quality. We hypothesized that the water quality can be impacted by the spatial land use types and by the seasonality. In the present study, seasonal and spatial water quality regarding physical, chemical, and biological parameters from a lake cascading system was assessed monthly from July to December 2019. Land use/cover data was produced by Impact Observatory, Microsoft, and Esri based on the 10-m Sentinel-2 images. Redundancy analysis was applied to investigate the relationship between land use/cover data and water quality in the riparian of 500 and 1000 m to the lakes. Our results showed clear temporal and spatial variation of water quality in 2019, with better water quality in rainy season (Oct.-Dec.) and downstream lakes while relatively worse water quality was recorded in dry season (Jul.-Sep.) and upstream lakes. The water quality variation was explained 27.8 % and 42.7 % by the land use types within 500 m and 1000 m buffer widths, respectively. The outlet of the catchment showed exceptional results due to the impact of a dumpsite. Our findings indicate that the water quality is highly impacted by human-induced land use/cover. The land use/cover types, such as crops, woodland and urban area, show negative impacts and relate to the high level of nutrient concentrations. In opposite, grass land shows positive effects and leads to better water quality. Our study confirms that the lake water quality is distinguished in both spatial and seasonal aspects. Monsoon season improves the water quality.

Dissolved Oxygen and Water Temperature Drive Vertical Spatiotemporal Variation of Phytoplankton Community: Evidence from the Largest Diversion Water Source Area.

In order to study the vertical distribution characteristics of phytoplankton in the Danjiangkou Reservoir, the water source of the Middle Route Project of the South-North Water Diversion, seven sampling sites were set up in the Reservoir for quarterly sampling from 2017 to 2019, and water environment surveys were conducted simultaneously. The results showed that 157 species (including varieties) were identified, belonging to 9 phyla and 88 genera. In terms of species richness, Chlorophyta had the largest number of species, accounting for 39.49% of the total species. The Bacillariophyta and Cyanobacteria accounted for 28.03% and 13.38% of the total species, respectively. From the whole Danjiangkou Reservoir, the total phytoplankton abundance varied from 0.09 × 102 to 20.01 × 106 cells/L. In the vertical distribution, phytoplankton were mainly observed in the surface-thermospheric layer (I-II layer) and the bottom layer, while the Shannon-Wiener index showed a trend of gradually decreasing from the I-V layer. The Surfer model analysis showed that there was no significant stratification in the Q site's water temperature (WT) and dissolved oxygen (DO) levels in the water diversion area during the dynamic water diversion process. A canonical correspondence analysis (CCA) showed that DO, WT, pH, electrical conductivity (Cond), chemical oxygen demand (CODMn), total phosphorus (TP), ammonia nitrogen (NH4+-N), and total nitrogen (TN) had significant effects on the vertical distribution of phytoplankton (p < 0.05). A partial Mantel analysis showed that the vertical distribution of the phytoplankton community was related to WT, and the phytoplankton community structure at the other sites, except for Heijizui (H) and Langhekou (L), was affected by DO. This study has positive significance for exploring the vertical distribution characteristics of a phytoplankton community in a deep-water dynamic water diversion reservoir.

The Asymmetric Response Concept explains ecological consequences of multiple stressor exposure and release.

Our capacity to predict trajectories of ecosystem degradation and recovery is limited, especially when impairments are caused by multiple stressors. Recovery may be fast or slow and either complete or partial, sometimes result in novel ecosystem states or even fail completely. Here, we introduce the Asymmetric Response Concept (ARC) that provides a basis for exploring and predicting the pace and magnitude of ecological responses to, and release from, multiple stressors. The ARC holds that three key mechanisms govern population, community and ecosystem trajectories. Stress tolerance is the main mechanism determining responses to increasing stressor intensity, whereas dispersal and biotic interactions predominantly govern responses to the release from stressors. The shifting importance of these mechanisms creates asymmetries between the ecological trajectories that follow increasing and decreasing stressor intensities. This recognition helps to understand multiple stressor impacts and to predict which measures will restore communities that are resistant to restoration.

Distinct indicators of land use and hydrology characterize different aspects of riverine phytoplankton communities.

Given the many threats to freshwater biodiversity, we need to be able to resolve which of the multiple stressors present in rivers are most important in driving change. Phytoplankton are a key component of the aquatic ecosystem, their abundance, species richness and functional richness are important indicators of ecosystem health. In this study, spatial variables, physiochemical conditions, water flow alterations and land use patterns were considered as the joint stressors from a lowland rural catchment. A modeling approach combining an ecohydrological model with machine learning was applied. The results implied that land use and flow regime, rather than nutrients, were most important in explaining differences in the phytoplankton community. In particular, the percentage of water body area and medium level residential urban area were key to driving the rising phytoplankton abundance in this rural catchment. The proportion of forest and pasture area were the leading factors controlling the variations of species richness. In this case deciduous forest cover affected the species richness in a positive way, while, pasture share had a negative effect. Indicators of hydrological alteration were found to be the best predictors for the differences in functional richness. This integrated model framework was found to be suitable for analysis of complex environmental conditions in river basin management. A key message would be the significance of forest area preservation and ecohydrological restoration in maintaining both phytoplankton richness and their functional role in river ecosystems.

A method for detecting the non-stationarity during high flows under global change.

The sustainability of existing water resources is influenced by extreme streamflow, and climate variability and human activities are generally the major factors controlling these dynamics. However, most of previously proposed methods to determine the effects of these factors have only been developed under the assumption of stationarity. Therefore, to overcome the existing research gap, an innovative method was proposed in this study to analyze and distinguish the effects of climate variability and human activities on extreme streamflow based on the non-stationarity theory. Accordingly, a rainfall-runoff model was developed using long-term hydrological data in the watersheds of Southeast China, which cover >75,000 km2. The model proposed in this study showed an acceptable performance, as indicated by the Nash-Sutcliffe efficiency coefficient (NSE), the Kling-Gupta efficiency (KGE), and percent bias (PBIAS). The NSE, KGE, and |PBIAS| were 0.67-0.75, 0.57-0.74, and 1.22-16.79 during the calibration periods, respectively. And the NSE, KGE, and |PBIAS| were 0.69-0.77, 0.65-0.76, and 0.98-17.51 during the calibration periods, respectively. The trends of the extreme streamflow were analyzed for these watersheds at different time scales. The streamflow extremes at short time scales were found to be more sensitive to changing environment than those at longer time scales. The major factor controlling streamflow extremes at short time scales was human activities and climate change may be the dominant factor influencing streamflow extremes at long time scales. The findings of this study could provide useful insights into water management under global change conditions.

Effects of sampling strategy in rivers on load estimation for Nitrate-Nitrogen and total Phosphorus in a lowland agricultural area.

The transport of nutrients into water bodies is one of the main causes of water eutrophication. It is therefore important to estimate the loads of nutrients. Discharge and nutrient concentrations are the fundamental elements to estimate the loads of nutrients, the latter can be affected by sampling strategies. As conducting sampling campaign and laboratory analysis are both expensive, it is necessary to find the best effective sampling strategy. The aim of this paper is to show how autocorrelation and standard statistical methods can be used to test the effects of different sampling strategies on the nutrient load estimation and to find the optimal sampling strategy. The data set in this study is from the 50 km² Kielstau catchment, a UNESCO demo site for ecohydrology in Northern Germany and consists of 14 years daily values of climate, hydrology, and water quality from 2006 to 2019. We calculated the autocorrelation (AC) of discharge (Q), precipitation, Nitrate-Nitrogen (NO3-N) and total Phosphorus (Ptot). Then we tested the effects of sampling intervals from 7 to 56 days (1-8 weeks) on the nutrient loads. Our results showed a high AC of Q and NO3-N for a long period, but the AC of Ptot and precipitation decreased very fast. An increase of the sampling interval (less frequent) increased the error of estimating the concentrations and loads. Consequently, we recommend that (1) the optimal sampling strategy for nutrient load estimation in an agriculture-dominant catchment should be continuously monitoring discharge combined with periodic grabbed samples; (2) the sampling frequency for NO3-N is suggested to be monthly (every 28 days) and for Ptot weekly (every 7 days). The information will help those tasked with catchment monitoring to design appropriate sampling strategy to ensure adequate data for nutrients load estimation in lowland rivers.

Gain and retain - On the efficiency of modified agricultural drainage ponds for pesticide retention.

Drainage ponds have the potential to serve as long-term interface measures primarily for flood control, and mass retention. They are often considered as promising supplements for the mitigation of drainage pipe loads to improve the water quality in agricultural landscapes. In this study, a highly dynamic drainage pond system with non-steady inflows and groundwater interaction was modified and investigated regarding its potential for pesticide and transformation product (TP) retention. For this purpose, two 104-day monitoring campaigns were conducted before and after pond modification. Field experiments with fluorescent tracers, Uranine and Sulforhodamine-B, proved that structural modifications improved the hydraulic functionality of the ponds. The effective volume (Ɛ) increased from 20% to almost 100% in the modified pond and the mean hydraulic residence time (τ) was ten times longer. After a dry period, pesticide retention was high during slow refilling of the ponds, still TP loads posed a risk by infiltration into shallow groundwater due to the permeable ground. During wet periods, short nominal detention times together with high inflows led to rare high retention rates through peak attenuation. Moderate inflows resulted in extremely variable retention values, owing to the small pond storage capacity. Along with this, the total retention efficiency after modification reached up to 38% for mobile, 29% for sorptive pesticides, and 32% for mobile TPs. To achieve the best performances for ponds as natural landscape elements, they should be analysed for their hydrological functionality as a prerequisite and then modified for delayed pesticide and TP transport. Then, dynamic drainage ponds can utilize their full potential regarding mitigation of pesticide and TP loads in agricultural catchments.

Using integrated models to analyze and predict the variance of diatom community composition in an agricultural area.

With the growing demand of assessing the ecological status, there is the need to fully understand the relationship between the planktic diversity and the environmental factors. Species richness and Shannon index have been widely used to describe the biodiversity of a community. Besides, we introduced the first ordination value from non-metric multidimensional scaling (NMDS) as a new index to represent the community similarity variance. In this study, we hypothesized that the variation of diatom community in rivers in an agricultural area was influenced by hydro-chemical variables. We collected daily mixed water samples using ISCO auto water samplers for diatoms and for water-chemistry analysis at the outlet of a lowland river for a consecutive year. An integrated modeling was adopted including random forest (RF) to decide the importance of the environmental factors influencing diatoms, generalized linear models (GLMs) combined with 10-folder cross validation to analyze and predict the diatom variation. The hierarchical analysis highlighted antecedent precipitation index (API) as the controlling hydrological variable while water temperature, Si2+ and PO4-P as the main chemical controlling factors in our study area. The generalized linear models performed better prediction for Shannon index (R2 = 0.44) and NMDS (R2 = 0.51) than diatom abundance (R2 = 0.25) and species richness (R2 = 0.25). Our findings confirmed that Shannon index and the NMDS as an index showed good performance in explaining the relationship between stream biota and its environmental factors and in predicting the diatom community development based on the hydro-chemical predictors. Our study showed and highlighted the important hydro-chemical factors in the agricultural rivers, which could contribute to the further understanding of predicting diatom community development and could be implemented in the future water management protocol.