Abstract
Abstract. Human water use has significantly increased during the recent past. Water withdrawals from surface and groundwater sources have altered terrestrial discharge and storage, with large variability in time and space. These withdrawals are driven by sectoral demands for water, but are commonly subject to supply constraints, which determine water allocation. Water supply and allocation, therefore, should be considered together with water demand and appropriately included in Earth system models to address various large-scale effects with or without considering possible climate interactions. In a companion paper, we review the modeling of demand in large-scale models. Here, we review the algorithms developed to represent the elements of water supply and allocation in land surface and global hydrologic models. We note that some potentially important online implications, such as the effects of large reservoirs on land–atmospheric feedbacks, have not yet been fully investigated. Regarding offline implications, we find that there are important elements, such as groundwater availability and withdrawals, and the representation of large reservoirs, which should be improved. We identify major sources of uncertainty in current simulations due to limitations in data support, water allocation algorithms, host large-scale models as well as propagation of various biases across the integrated modeling system. Considering these findings with those highlighted in our companion paper, we note that advancements in computation and coupling techniques as well as improvements in natural and anthropogenic process representation and parameterization in host large-scale models, in conjunction with remote sensing and data assimilation can facilitate inclusion of water resource management at larger scales. Nonetheless, various modeling options should be carefully considered, diagnosed and intercompared. We propose a modular framework to develop integrated models based on multiple hypotheses for data support, water resource management algorithms and host models in a unified uncertainty assessment framework. A key to this development is the availability of regional-scale data for model development, diagnosis and validation. We argue that the time is right for a global initiative, based on regional case studies, to move this agenda forward.
Highlights
The water cycle is fundamental to the functioning of the Earth system and underpins the most basic needs of human society
Current simulation-based algorithms are heavily influenced by the work of Hanasaki et al (2006), which was initially proposed for global routing models but extended to global hydrologic models (GHMs) (Hanasaki et al, 2008a, 2010) and land surface models (LSMs) (Pokhrel et al, 2012a, b)
Throughout our survey, we highlighted the importance of including water supply and allocation in conjunction with water demand in models that are relevant to Earth system modeling and/or required for understanding large-scale hydrological responses, with both online and offline implications
Summary
The water cycle is fundamental to the functioning of the Earth system and underpins the most basic needs of human society. As noted in our companion paper (hereafter referred to as Nazemi and Wheater, 2015), the current scale of human activities significantly perturbs the terrestrial water cycle, with local, regional and global implications Such disturbances affect both hydrological functioning and land–atmospheric interactions, and should be explicitly represented in large-scale models. Considering that almost all major river systems in the Northern Hemisphere (except for the arctic and subarctic regions) are dammed (e.g., Meybeck, 2003; Nilsson et al, 2005), it can be argued that accurate simulation of continental and global runoff is impossible without considering the effects of reservoirs Such hydrologic impacts and associated environmental consequences can be studied through offline LSMs or GHMs. There are, important land-surface implications associated with reservoir operation that require online simulations.
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