Abstract. This paper presents the Australian edition of the Catchment Attributes and
Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS (Australia) comprises data for 222 unregulated catchments, combining hydrometeorological
time series (streamflow and 18 climatic variables) with 134 attributes
related to geology, soil, topography, land cover, anthropogenic influence
and hydroclimatology. The CAMELS-AUS catchments have been monitored for
decades (more than 85 % have streamflow records longer than 40 years) and
are relatively free of large-scale changes, such as significant changes in
land use. Rating curve uncertainty estimates are provided for most (75 %)
of the catchments, and multiple atmospheric datasets are included, offering
insights into forcing uncertainty. This dataset allows users globally to
freely access catchment data drawn from Australia's unique hydroclimatology,
particularly notable for its large interannual variability. Combined with
arid catchment data from the CAMELS datasets for the USA and Chile,
CAMELS-AUS constitutes an unprecedented resource for the study of arid-zone
hydrology. CAMELS-AUS is freely downloadable from https://doi.org/10.1594/PANGAEA.921850 (Fowler et al., 2020a).
From the 1980s, Indian summer monsoon rainfall (ISMR) shows a decreasing trend over north and northwest India, and there was a significant observed reduction in July over central and south India in 1982–2003. The key drivers of the changed ISMR, however, remain unclear. It was hypothesized that the large-scale irrigation development that started in the 1950s has resulted in land surface cooling, which slowed large-scale atmospheric circulation, exerting significant influences on ISMR. To test this hypothesis, a fully coupled model, the CESM v1.0.3, was used with a global irrigation dataset. In this study, spatially varying irrigation-induced feedback mechanisms are investigated in detail at different stages of the monsoon. Results show that soil moisture and evapotranspiration increase significantly over India throughout the summertime because of the irrigation. However, 2-m air temperature shows a significant reduction only in a limited region because the temperature change is influenced simultaneously by surface incoming shortwave radiation and evaporative cooling resulting from the irrigation, especially over the heavily irrigated region. Irrigation also induces a 925-hPa northeasterly wind from 30°N toward the equator. This is opposite to the prevailing direction of the Indian summer monsoon (ISM) wind that brings moist air to India. The modeled rainfall in the irrigated case significantly decreases up to 1.5 mm day−1 over central and north India from July to September. This paper reveals that the irrigation can contribute to both increasing and decreasing the surface temperature via multiple feedback mechanisms. The net effect is to weaken the ISM with the high spatial and temporal heterogeneity.
, a genus of potentially harmful cyanobacteria, is known to proliferate in stratified freshwaters due to its capability to change cell density and regulate buoyancy. In this study, a trajectory model was developed to simulate the cell density change and spatial distribution of cells with nonuniform colony sizes. Simulations showed that larger colonies migrate to the near-surface water layer during the night to effectively capture irradiation and become heavy enough to sink during daytime. Smaller-sized colonies instead took a longer time to get to the surface. Simulation of the diurnally varying population profile matched the observed pattern in the field when the radii of the multisized colonies were in a beta distribution. This modeling approach is able to take into account the history of cells by keeping track of their positions and properties, such as cell density and the sizes of colonies. It also serves as the basis for further developmental modeling of phytoplanktons that are forming colonies and changing buoyancy.
Abstract. This paper presents the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS comprises data for 222 unregulated catchments, combining hydrometeorological timeseries (streamflow and 18 climatic variables) with 134 attributes related to geology, soil, topography, land cover, anthropogenic influence, and hydroclimatology. The CAMELS-AUS catchments have been monitored for decades (more than 85 % have streamflow records longer than 40 years) and are relatively free of large scale changes, such as significant changes in landuse. Rating curve uncertainty estimates are provided for most (75 %) of the catchments and multiple atmospheric datasets are included, offering insights into forcing uncertainty. This dataset, the first of its kind in Australia, allows users globally to freely access catchment data drawn from Australia's unique hydroclimatology, particularly notable for its large interannual variability. Combined with arid catchment data from the CAMELS datasets for the USA and Chile, CAMELS-AUS constitutes an unprecedented resource for the study of arid-zone hydrology. CAMELS-AUS is freely downloadable from https://doi.pangaea.de/10.1594/PANGAEA.921850 (Fowler et al., 2020a).
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