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Quantitatively determining in vivo achievable drug concentrations in targeted organs of animal models and subsequent target engagement confirmation is a challenge to drug discovery and translation due to lack of bioassay technologies that can discriminate drug binding with different mechanisms. We have developed a multiplexed and high-throughput method to quantify drug distribution in tissues by integrating high content screening (HCS) with U-Net based deep learning (DL) image analysis models. This technology combination allowed direct visualization and quantification of biologics drug binding in targeted tissues with cellular resolution, thus enabling biologists to objectively determine drug binding kinetics.

River pollution through the discharge of untreated sewage and industrial effluent is a perverse outcome of rapid urbanisation and economic growth across Asia. To understand the socio-spatial and seasonal inequalities in pollution risks, we designed a direct observation method to record people’s daily river use activities across dry and wet seasons, complemented by monthly monitoring of river water quality, heavy metal and biotoxicity assessment a large-scale household survey along a 25km stretch of the Turag River and Tongi Khal in Dhaka, Bangladesh. We found very high ammonia and almost zero dissolved oxygen during the low flow season, further exacerbated by heavy metals from the annual Bishwa Ijtema gathering and downstream industrial zones. Pollution exposure through domestic activities prevailed throughout the year, particularly for women and girls along low-income settlements lacking adequate water and sanitation facilities. Swimming peaked among men and children in the monsoon, risking exposure to pathogen pollution. Recognising the social inequalities in risk can support the sequencing of policy action involving short-term adaptation (improved services, education, advocacy) and long-term mitigation (effluent treatment, regulation and enforcement) responses.

With widespread, long-term historical use of plastics and the presence of microplastics in a range of new and existing products, there is rising concern about their potential impacts on freshwater ecosystems. Understanding how microplastics are transported and distributed along river systems is key to assessing impacts. Modelling the main flow dynamics, mixing, sedimentation and resuspension processes is essential for an understanding of the transport processes. We use the new, processed based, dynamic, integrated catchments (INCA) microplastics model and apply this to the whole of the freshwater catchment of the River Thames, UK, to evaluate inputs, loads and concentrations along the river system. Recent data from UK water industry studies on microplastics in effluent discharges and sewage sludge disposal has been utilised to drive the INCA microplastics model. Predicted concentrations and microplastic loads moving along the river system are shown to be significant, with a build-up of concentrations along the river, with increasing deposition on the riverbed. The potential impacts on aquatic ecosystems are evaluated and a review of policy implications is explored.

A new multibranch Integrated Catchment (INCA) model INCA-Metals has been developed to simulate the impact of tannery discharges on river systems. The model accounts for the key chemical reaction kinetic processes operating as well as sedimentation, resuspension, dilution, mixing and redistribution of pollutants in rivers downstream of tannery discharge points and for mine discharges or acid rock drainage sites. The model is dynamic and simulates the daily behaviour of hydrology and eight metals, including cadmium, mercury, copper, zinc, lead, arsenic, manganese and chromium, as well as cyanide and ammonia. The model is semi-distributed and can simulate catchments, tributaries and instream river behaviour. The model can also account for diffuse pollution from rural runoff as well as point sources from effluent and trade discharges. The model has been applied to the new Savar tannery complex on the Dhaleshwari River system in Bangladesh to assess the impacts on pollution levels in the river system and to evaluate a set of treatment scenarios for pollution control, particularly in the dry season. It is shown that the new effluent treatment plant at Savar needs to significantly improve its operation and treatment capability in order to alleviate metal pollution in the downstream Dhaleshwari River System and also protect the Meghna River System that falls in the Bay of Bengal.

Assessing the impact of climate change and population growth on river water quality is a key issue for many developing countries, where multiple and often conflicting river water uses (water supply, irrigation, wastewater disposal) are placing increasing pressure on limited water resources. However, comprehensive water quality datasets are often lacking, thus impeding a full-scale data-based river water quality assessment. Here we propose a model-based approach, using both global datasets and local data to build an evaluation of the potential impact of climate changes and population growth, as well as to verify the efficiency of mitigation measures to curb river water pollution. The upper Awash River catchment in Ethiopia, which drains the city of Addis Ababa as well as many agricultural areas, is used as a case-study. The results show that while decreases in runoff and increases in temperature due to climate change are expected to result in slightly decreased nutrient concentrations, the largest threat to the water quality of the Awash River is population growth, which is expected to increase nutrient loads by 15 to 20% (nitrate) and 30 to 40% (phosphorus) in the river by the second half of the 21st century. Even larger increases are to be expected downstream of large urban areas, such as Addis Ababa. However, improved wastewater treatment options are shown to be efficient in counteracting the negative impact of population growth and returning water pollution to acceptable levels.

International audience; The livelihoods of millions of people living in the world's deltas are deeply interconnected with the sediment dynamics of these deltas. In particular a sustainable supply of fluvial sediments from upstream is critical for ensuring the fertility of delta soils and for promoting sediment deposition that can offset rising sea levels. Yet, in many large river catchments this supply of sediment is being threatened by the planned construction of large dams. In this study, we apply the INCA hydrological and sediment model to the Mekong River catchment in South East Asia. The aim is to assess the impact of several large dams (both existing and planned) on the suspended sediment fluxes of the river. We force the INCA model with a climate model to assess the interplay of changing climate and sediment trapping caused by dam construction. The results show that historical sediment flux declines are mostly caused by dams built in PR China and that sediment trapping will increase in the future due to the construction of new dams in PDR Lao and Cambodia. If all dams that are currently planned for the next two decades are built, they will induce a decline of suspended sediment flux of 50% (47–53% 90% confidence interval (90%CI)) compared to current levels (99 Mt/year at the delta apex), with potentially damaging consequences for local livelihoods and ecosystems.

Good hygienic quality of surface waters is essential for drinking water production, irrigation of crops and recreation. Predictions of how and when microbes are transported by rivers are needed to protect downstream water users. In this study we tested the new process-based INCA-Pathogens model in the agricultural Loimijoki River basin (3138km2) in Finland, and we quantified ecosystem services of water purification and water provisioning for drinking and recreation purposes under different scenarios. INCA is a catchment scale process based model to calculate pollutant transfer from terrestrial environment and point sources to the catchment outlet. A clear gradient was observed in the numbers of faecal coliforms along the River Loimijoki. The highest bacterial counts were detected in the middle part of the main stream immediately after small industries and municipal sewage treatment plants. In terms of model performance, the INCA-Pathogen model was able to produce faecal coliform counts and seasonality both in the low pollution level sampling points and in the high pollution level sampling points. The model was sensitive to the parameters defining light decay in river water and in soil compartment, as well as to the amount of faecal coliforms in the manure spread on the fields. The modeling results showed that the number of faecal coliforms repeatedly exceeded 1000 bacteria 100ml-1. Moreover, results lead to the following conclusions: 1) Climate change does not cause a major threat to hygienic water quality as higher precipitation increases runoff and causes diluting effect in the river, 2) Intensification of agriculture is not a threat as long as animal density remains relatively low and environmental legislation is followed, 3) More intensive agriculture without environmental legislation causes a threat especially in tributaries with high field percentage and animal density, and 4) Hygienic water quality in the River Loimijoki can best be improved by improving sewage treatment. We conclude that this catchment scale model is a useful tool for addressing catchment management and water treatment planning issues.

INCA-P is a dynamic, catchment-scale phosphorus model which has been widely applied during the last decade. Since its original release in 2002, the model structure and equations have been significantly altered during several development phases. Here, we provide the first full model description since 2002 and then test the latest version of the model (v1.4.4) in a small rural catchment in northeast Scotland. The particulate phosphorus simulation was much improved compared to previous model versions, whilst the latest sorption equations allowed us to explore the potential time lags between reductions in terrestrial inputs and improvements in surface water quality, an issue of key policy relevance. The model is particularly suitable for use as a research tool, but should only be used to inform policy and land management in data-rich areas, where parameters and processes can be well-constrained. More long-term data is needed to parameterise dynamic models and test their predictions. We describe the latest version of INCA-P, a dynamic catchment phosphorus model.This is the first full description of the model structure and equations since 2002.A test application demonstrates improved model performance.New sorption equations allow the impacts of legacy soil P to be simulated over time.Model applicability and limitations are discussed.

As the scientific consensus concerning global climate change has increased in recent decades, research on potential impacts of climate change on water resources has been given high importance. However in Sub-Saharan Africa, few studies have fully evaluated the potential implications of climate change to their water resource systems. The Volta River is one of the major rivers in Africa covering six riparian countries (mainly Ghana and Burkina Faso). It is a principal water source for approximately 24 million people in the region. The catchment is primarily agricultural providing food supplies to rural areas, demonstrating the classic water, food, energy nexus. In this study an Integrated Catchment Model (INCA) was applied to the whole Volta River system to simulate flow in the rivers and at the outlet of the artificial Lake Volta. High-resolution climate scenarios downscaled from three different Global Climate Models (CNRM-CM5, HadGEM2-ES and CanESM2), have been used to drive the INCA model and to assess changes in flow by 2050s and 2090s under the high climate forcing scenario RCP8.5. Results show that peak flows during the monsoon months could increase into the future. The duration of high flow could become longer compared to the recent condition. In addition, we considered three different socio-economic scenarios. As an example, under the combined impact from climate change from downscaling CNRM-CM5 and medium+ (high economic growth) socio-economic changes, the extreme high flows (Q5) of the Black Volta River are projected to increase 11% and 36% at 2050s and 2090s, respectively. Lake Volta outflow would increase +1% and +5% at 2050s and 2090s, respectively, under the same scenario. The effects of changing socio-economic conditions on flow are minor compared to the climate change impact. These results will provide valuable information assisting future water resource development and adaptive strategies in the Volta Basin.

The Integrated Nitrogen Catchment model (INCA) was applied successfully to simulate nitrogen concentrations in the River Lee, a northern tributary of the River Thames for 1995-1999. Leaching from urban and agricultural areas was found to control nitrogen dynamics in reaches unaffected by effluent discharges and abstractions; the occurrence of minimal flows resulted in an upward trend in nitrate concentration. Sewage treatment works (STW) discharging into the River Lee raised nitrate concentrations substantially, a problem which was compounded by abstractions in the Lower Lee. The average concentration of nitrate (NO3) for the simulation period 1995-96 was 7.87 mg N l-1. Ammonium (NH4) concentrations were simulated less successfully. However, concentrations of ammonium rarely rose to levels which would be of environmental concern. Scenarios were run through INCA to assess strategies for the reduction of nitrate concentrations in the catchment. The conversion of arable land to ungrazed vegetation or to woodland would reduce nitrate concentrations substantially, whilst inclusion of riparian buffer strips would be unsuccessful in reducing nitrate loading. A 50% reduction in nitrate loading from Luton STW would result in a fall of up to 5 mg N l-1 in the reach directly affected (concentrations fell from maxima of 13 to 8 mg N l-1 , nearly a 40 % reduction), whilst a 20% reduction in abstractions would reduce maximum peaks in concentration in the lower Lee by up to 4 mg l-1 (from 17 to 13 mg N l-1, nearly a 25 % reduction),. Keywords: modelling, water quality, nitrogen, nitrate, ammonium, INCA, River Lee, River Thames, land-use.

A flexible meta-model, the Delta Dynamic Integrated Emulator Model (ΔDIEM), is developed to capture the socio-biophysical system of coastal Bangladesh as simply and efficiently as possible. Operating at the local scale, calculations occur efficiently using a variety of methods, including linear statistical emulators, which capture the behaviour of more complex models, internal process-based models and statistical associations. All components are tightly coupled, tested and validated, and their behaviour is explored with sensitivity tests. Using input data, the integrated model approximates the spatial and temporal change in ecosystem services and a number of livelihood, well-being, poverty and health indicators of archetypal households. Through the use of climate, socio-economic and governance scenarios plausible trajectories and futures of coastal Bangladesh can be explored.

Measurements have shown low levels of PCBs in water but relatively high concentrations in the resident fish of the River Thames (UK). To better understand the distribution and behaviour of PCBs in the Thames river basin and their potential risks, a level III fugacity model was applied to selected PCB congeners (PCB 52, PCB 118 and PCB 153). The modelling results indicated that fish and sediments represent environmental compartments with the highest PCB concentrations; but the greatest mass of PCBs (over 70%) is likely to remain in the soil. As emissions decline, soil could then act as a significant secondary source of PCBs with the river bed-sediment functioning as a long-term reservoir of PCBs. The predicted changes in temperature and rainfall forecast in the UK Climate Projections 2009 (UKCP09) over the next 80 years had only a modest influence on PCB fate in the model. The most significant result was a tendency for climate change to enhance the evaporation of PCBs from soil to air in the Thames catchment. (C) 2015 Elsevier B.V. All rights reserved.

Introduction to the ESPA deltas themed issue of Environmental Science: Processes & Impacts.

In glacier-fed systems climate change may have various effects over a range of time scales, including increasing river discharge, flood frequency and magnitude. This study uses a combination of empirical monitoring and modelling to project the impacts of climate change on the glacial-fed Middle Fork Toklat River, Denali National Park, Alaska. We use a regional calibration of the model HBV to account for a paucity of long term observed flow data, validating a local application using glacial mass balance data and summer flow records. Two Global Climate Models (HADCM3 and CGCM2) and two IPCC scenarios (A2 and B2) are used to ascertain potential changes in meteorological conditions, river discharge, flood frequency and flood magnitude. Using remote sensing methods this study refines existing estimates of glacial recession rates, finding that since 2000, rates have increased from 24 m per year to 68.5m per year, with associated increases in ablation zone ice loss. GCM projections indicate that over the 21(st) century these rates will increase still further, most extensively under the CGCM2 model, and A2 scenarios. Due to greater winter precipitation and ice and snow accumulation, glaciers release increasing meltwater quantities throughout the 21(st) century. Despite increases in glacial melt, results indicate that it is predominantly precipitation that affects river discharge. Three of the four IPCC scenarios project increases in flood frequency and magnitude, events which were primarily associated with changing precipitation patterns, rather than extreme temperature increases or meltwater release. Results suggest that although increasing temperatures will significantly increase glacial melt and winter baseflow, meltwater alone does not pose a significant flood hazard to the Toklat River catchment. Projected changes in precipitation are the primary concern, both through changing snow volumes available for melt, and more directly through increasing catchment runoff.

We’ve argued in this opinion paper that the hydrology community needs a hyper-resolution land surface modeling (HyRLSM) to address the water problems facing society. We strongly believe that addressing this need, as described above, will ultimately lead to a more informed and aware society that can sustain the water needs of the future., JRC.H.7-Land management and natural hazards

A generic Nutrient Export Risk Matrix (NERM) approach is presented. This provides advice to farmers and policy makers on good practice for reducing nutrient loss and, hopefully, persuades them to implement such measures. Combined with a range of nutrient transport modelling tools and field experiments, NERMs can play an important role in reducing nutrient export from agricultural land. The Phosphorus Export Risk Matrix (PERM) is presented as an example NERM. The PERM integrates hydrological understanding of runoff with a number of agronomic and policy factors into a clear problem-solving framework. This allows farmers and policy makers to visualise strategies for reducing phosphorus loss through proactive land management. The risk of pollution is assessed by a series of informed questions relating to farming intensity and practice. This information is combined with the concept of runoff management to point towards simple, practical remedial strategies which do not compromise farmers’ ability to obtain sound economic returns from their crop and livestock. Keywords: nutrients, phosphorus, export, risk, decision support, matrix

The impacts of afforestation at Plynlimon in the Severn catchment, mid-Wales, and in the Bedford Ouse catchment in south-east England are evaluated using the INCA model to simulate Nitrogen (N) fluxes and concentrations. The INCA model represents the key hydrological and N processes operating in catchments and simulates the daily dynamic behaviour as well as the annual fluxes. INCA has been applied to five years of data from the Hafren and Hore headwater sub-catchments (6.8 km2 area in total) of the River Severn at Plynlimon and the model was calibrated and validated against field data. Simulation of afforestation is achieved by altering the uptake rate parameters in the model. INCA simulates the daily N behaviour in the catchments with good accuracy as well as reconstructing the annual budgets for N release following clearfelling; a four-fold increase in N fluxes was followed by a slow recovery after re-afforestation. For comparison, INCA has been applied to the large (8380 km2) Bedford Ouse catchment to investigate the impact of replacing 20% arable land with forestry. The reduction in fertiliser inputs from arable farming and the N uptake by the forest are predicted to reduce the N flux reaching the main river system, leading to a 33% reduction in N-Nitrate concentrations in the river water. Keywords: afforestation, water quality, nitrogen, modelling, land-use change, Wales, Plynlimon, Hore, Hafren, Bedford Ouse, Severn

A regional overview of the water quality and ecology of the River Lee catchment is presented. Specifically, data describing the chemical, microbiological and macrobiological water quality and fisheries communities have been analysed, based on a division into river, sewage treatment works, fish-farm, lake and industrial samples. Nutrient enrichment and the highest concentrations of metals and micro-organics were found in the urbanised, lower reaches of the Lee and in the Lee Navigation. Average annual concentrations of metals were generally within environmental quality standards although, on many occasions, concentrations of cadmium, copper, lead, mercury and zinc were in excess of the standards. Various organic substances (used as herbicides, fungicides, insecticides, chlorination by-products and industrial solvents) were widely detected in the Lee system. Concentrations of ten micro-organic substances were observed in excess of their environmental quality standards, though not in terms of annual averages. Sewage treatment works were the principal point source input of nutrients, metals and micro-organic determinands to the catchment. Diffuse nitrogen sources contributed approximately 60% and 27% of the in-stream load in the upper and lower Lee respectively, whereas approximately 60% and 20% of the in-stream phosphorus load was derived from diffuse sources in the upper and lower Lee. For metals, the most significant source was the urban runoff from North London. In reaches less affected by effluent discharges, diffuse runoff from urban and agricultural areas dominated trends. High microbiological content, observed in the River Lee particularly in urbanised reaches, was far in excess of the EC Bathing Water Directive standards. Water quality issues and degraded habitat in the lower reaches of the Lee has led to impoverished aquatic fauna but, within the mid-catchment reaches and upper agricultural tributaries, less nutrient enrichment and channel alteration has permitted more diverse aquatic fauna. Keywords: River Lee, River Thames, water quality, nutrients, metals, ecology, hydrology, diffuse and point source pollution

Measurements of nitrate deposition and streamwater chemistry in the Tillingbourne Catchment, in Southern England, made in 1979-1982 and 1999-2001 show a 216% increase in Nitrogen leaching despite a reduction in N inputs. Both the historical and current data sets have been modelled using the Integrated Nitrogen Model in Catchments (INCA). The process-based model is shown to reproduce the historical patterns of N release from the catchment. However, modelling the increased leaching of N during recent years required an increase of the mineralisation control parameter in the model, suggesting enhanced mineralisation rates. Comparing historic and current soils data for C/N ratios shows that there has been a reduction in C/N from 38 to 26% in the humus layer and a reduction from 33 to 26% in the mineral soil horizon. This significant fall in C/N is consistent with the increase in N saturation in the H and Ah horizons of the major catchment soil. Keywords: acid deposition, recovery, nitrogen, Carbon-Nitrogen ratios, Tillingbourne, Thames, catchment studies, nutrient leaching, modelling

International audience; A new version of the Integrated Nitrogen in Catchments model (INCA) was developed and tested using flow and streamwater nitrate concentration data collected from the River Kennet during 1998. INCA is a process-based model of the nitrogen cycle in the plant/soil and in-stream systems. The model simulates the nitrogen export from different land-use types within a river system, and the in-stream nitrate and ammonium concentrations at a daily time-step. The structure of the new version differs from the original, in that soil-water retention volumes have been added and the interface adapted to permit multiple crop and vegetation growth periods and fertiliser applications. The process equations are now written in terms of loads rather than concentrations allowing a more robust tracking of mass conservation when using numerical integration. The new version is able to reproduce the seasonal dynamics observed in the streamwater nitrogen concentration data, and the loads associated with plant/soil system nitrogen processes reported in the literature. As such, the model results suggest that the new structure is appropriate for the simulation of nitrogen in the River Kennet and an improvement on the original model. The utility of the INCA model is discussed in terms of improving scientific understanding and catchment management. Keywords: modelling, water quality, nitrogen, nitrate, River Kennet, River Thames

International audience; The results of a literature study examining quantitative estimates of N2O emission rates are presented for a range of land-uses across Europe. The analysis shows that the highest N2O emission rates are for agricultural lands compared to forests and grasslands. The main factors regulating these rates are available mineral nitrogen, soil temperature, soil water content and the available labile organic compounds. These controls operate across different time-scales, all must exceed a certain threshold for N2O emission to occur. The results support the need for an emission factor function of land-use and climate within models describing nitrogen dynamics in catchments. This would allow the assessment of the net N2O emission within catchments in terms of current levels and potential changes associated with climate variability, climate change and land use change. Keywords: nitrous oxide, soil water content, inorganic N, soil temperature, ecosystems, land-use management, soil type

The INCA (Integrated Nitrogen in Catchments) model was applied to the River Tweed in the Scottish Borders, a large-scale (4400km2), spatially heterogeneous catchment, draining a wide range of agricultural land-use types, and which contributes approximately 20% of UK river flows to the North Sea. The model was calibrated for the first four years' data record (1994 to 1997) and tested over the following three years (1998 to 2000). The model calibration and testing periods incorporated a high degree of variability in climatic conditions and river flows within the Tweed catchment. The ability of the INCA model to reproduce broad-scale spatial patterns and seasonal dynamics in river flows and nitrate concentrations suggests that the processes controlling first order variability in river water nitrate concentrations have been represented successfully within the model. The tendency of the model to overestimate summer/early autumn baseflow nitrate concentrations during dry years may be linked to the operation of aquatic plant uptake effects. It is, therefore, suggested that consideration be given to incorporating a spatially and temporally variable in-stream plant uptake term for the application of INCA to lowland eutrophic rivers. Scenarios to examine possible impacts of environmental change on nitrate concentrations on the Tweed are examined. These include the effects of (i) implementing different recommendations for fertiliser use and land use change under the Nitrate Sensitive Areas (NSA) Scheme and the Scottish Code of Good Agricultural Practice, (ii) worst case scenario changes linked to a dramatic reduction in livestock numbers as a result of a crisis in UK livestock farming and (iii) changes in atmospheric nitrogen deposition. Keywords: Nitrate, nitrogen, modelling, Tweed, INCA