 |
| Titel |
On inclusion of water resource management in Earth system models – Part 2: Representation of water supply and allocation and opportunities for improved modeling |
| VerfasserIn |
A. Nazemi, H. S. Wheater |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 1 ; Nr. 19, no. 1 (2015-01-07), S.63-90 |
| Datensatznummer |
250120581
|
| Publikation (Nr.) |
 copernicus.org/hess-19-63-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
| 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. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|