SCENARIO NERC DTP - The implications of climate and land cover change for river water quality: model development and scenario assessment.

Overview: This studentship aims to quantify the response of multiple pollutants in river-systems to projected changes in climate and land cover, and to policy instruments. This understanding is needed to improve UK water quality within the context of projected demographic, agricultural and climate change. Specifically, the project will develop a new multi-pollutant water quality model based on some of the most detailed observations of available water chemistry.
Background: UK government, devolved administrations and national environment agencies are charged with improving the chemical and ecological status of UK rivers, but it is unclear how the nine policy instruments spanning regulation, protected areas and pollution control will affect different water quality constituents in combination. Given this, new catchment-scale water quality models are needed to help assess which policy instruments and intervention measures (e.g. buffer strips, adapted land management) will improve multiple aspects of water pollution, where measures should be placed, how long the response will be, and whether climate change will confound these actions. Most water quality models have been developed for individual chemical constituents and a step change is needed to simulate multiple pollutants at appropriate scales for management.
Aims/Objectives: The overall aim is to develop a process-based, catchment-scale water quality model that simulates the response of multiple pollutants (carbon, nitrogen and phosphorous) to multiple drivers and explore credible scenarios of change. To achieve this aim, there are three objectives: (1) To develop and test a new catchment-scale water quality model that simulates the response of multiple pollutants to multiple drivers at spatial and temporal scales suitable for the assessment of a range of measures at the field and catchment scales; (2) To investigate uncertainty introduced by model structure, model parameters as well as input data (measurement uncertainty, resolution); (3) To produce modelled outcomes, with uncertainty estimates, from environmental change scenarios, including intervention measure effectiveness.
Methods/Approach: A catchment-scale multi-pollutant model will be developed (obj.1) based on two existing single-pollutant models developed at JHI, STREAM-N (Dunn et al. 2013) and JHI and Reading, SimplyP (Jackson-Blake et al. 2017), and/or the addition of C, N and P cycles into the new fully distributed, open-source, hydrological model mHM based on what has been learnt from the STREAM-N and SimplyP development (and from the INCA suite of models developed at Reading). The use of the model will allow inclusion of the relevant hydrological and biochemical processes at the spatial and temporal scales suitable for assessing the effectiveness of field scale measures. To begin the new model will be set up and parameterized for two contrasting agricultural catchments in the UK– the River Kennet (1200 km2), a lowland catchment in southern England and the Tarland Burn (A = 51 km2), in the upland fringe in northeast Scotland– by calibration and testing against observed concentrations. The model performance will be tested on different temporal (River Kennet: daily, weekly, monthly, annual; Tarland Burn: monthly and annual) and spatial (catchment outlet and tributaries) scales. Water quality data from Ireland will also be used to test the response to field-scale intervention measures. The uncertainty introduced by input data, model structure and model parameters (obj. 2) will be investigated by comparing simulation results using input data of different spatial and temporal resolution, different model structures (e.g. coupled vs. independent C, N and P processes) as well as different model parameterisations. Potential impacts of environmental change scenarios, including intervention measure effectiveness will be simulated (obj. 3) using the method defined in Skuras et al. (2013).

Skuras et al. 2014. An interdisciplinary modelling approach assessing the cost-effectiveness of agri-environmental measures on reducing nutrient concentration to WFD thresholds under climate change. Operational Research 14(2):205-224.

To hear more about this project please follow the link: https://www.youtube.com/watch?v=sxnT1LinmWM&list=PLZWYaq_mWwsEM5dH1abHjYIgU2EVaegT9&index=15

To read more about this project please follow the link: http://www.met.reading.ac.uk/nercdtp/home/available/desc/entry2018/SC201812.pdf