HydroBlocks:a field-scale resolving land surface model for application over continental extents

Land surface spatial heterogeneity plays a significant role in the water, energy, and carbon cycles over a range of temporal and spatial scales. Until now, the representation of this spatial heterogeneity in land surface models has been limited to over simplistic schemes due to computation and environmental data limitations. This study introduces HydroBlocks—a novel land surface model that represents field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs). HydroBlocks is a coupling between the Noah-MP land surface model and the Dynamic TOPMODEL hydrologic model. The HRUs are defined by clustering proxies of the drivers of spatial heterogeneity using high-resolution land data. The clustering mechanism allows for each HRU's results to be mapped out in space, facilitating field-scale application and validation. The Little Washita watershed in the United States is used to assess HydroBlocks’ performance and added benefit from traditional land surface models. A comparison between the semi-distributed and fully distributed versions of the model suggests that using 1000 HRUs is sufficient to accurately approximate the fully distributed solution. A preliminary evaluation of model performance using available in-situ soil moisture observations suggests that HydroBlocks is generally able to reproduce the observed spatial and temporal dynamics of soil moisture. Model performance deficiencies can be primarily attributed to parameter uncertainty. HydroBlocks’ ability to explicitly resolve field-scale spatial heterogeneity while only requiring an increase in computation of one to two orders of magnitude when compared to existing land surface models is encouraging—ensemble field-scale land surface modeling over continental extents is now possible

Coupling virtual watersheds with ecosystem services assessment: A 21st century platform to support river research and management

The demand for freshwater is projected to increase worldwide over the coming decades, resulting in severe water stress and threats to riverine biodiversity, ecosystem functioning and services. A major societal challenge is to determine where environmental changes will have the greatest impacts on riverine ecosystem services and where resilience can be incorporated into adaptive resource planning. Both water managers and scientists need new integrative tools to guide them towards the best solutions that meet the demands of a growing human population but also ensure riverine biodiversity and ecosystem integrity. Resource planners and scientists could better address a growing set of riverine management and risk mitigation issues by (1) using a “Virtual Watersheds” approach based on improved digital river networks and better connections to terrestrial systems; (2) integrating Virtual Watersheds with ecosystem services technology (ARtificial Intelligence for Ecosystem Services: ARIES), and (3) incorporating the role of riverine biotic interactions in shaping ecological responses. This integrative platform can support both interdisciplinary scientific analyses of pressing societal issues and effective dissemination of findings across river research and management communities. It should also provide new integrative tools to identify the best solutions and trade-offs to ensure the conservation of riverine biodiversity and ecosystem services

Domestic Water Demand During Droughts in Temperate Climates: Synthesising Evidence for an Integrated Framework

In the upcoming years, as the population is growing and ageing, as lifestyle changes create the need for more water and as fewer people live in each household, the UK water sector will have to deal with challenges in the provision of adequate water services. Unless critical action is taken, every area in the UK may face a supply-demand gap by the 2080s. Extreme weather events and variations that alter drought and flood frequency add to these pressures. However, little evidence is available about householders’ response to drought and there are few if any studies incorporating this evidence into models of demand forecasting. The present work lays the groundwork for modelling domestic water demand response under drought conditions in temperate climates. After discussing the current literature on estimating and forecasting domestic water consumption under both ‘normal’ and drought conditions, this paper identifies the limited ability of current domestic demand forecasting techniques to include the many different and evolving factors affecting domestic consumption and it stresses the need for the inclusion of inter and intra household factors as well as water use practices in future demand forecasting models