| publications-1691 |
PEER REVIEWED ARTICLE |
2011 |
Qin H.P., Su Q., Khu S.T. |
An integrated model for water management in a rapidly urbanizing catchment |
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10.1016/j.envsoft.2011.07.003 |
Data Management & Analytics |
Irrigation Systems |
|
No abstract available |
908448 |
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| publications-1692 |
PEER REVIEWED ARTICLE |
|
Wang W.W., Zhao Z.J., Qin H.P. |
Hydrological Effect Assessment of Low Impact Development for Urbanized Area Based on SWMM. |
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Data Management & Analytics |
Irrigation Systems |
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No abstract available |
908448 |
|
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| publications-1693 |
|
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Li C., Qin H.P., Zhang, Y.Y., Wang, W.W. |
Algae growth simulation of reclaimed wastewater recycled to landscape water body in different seasons. |
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Data Management & Analytics |
Irrigation Systems |
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No abstract available |
908448 |
|
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| publications-1694 |
|
|
Zheng Y., Qin H.P. |
Multi-objective programming for water pollution control in a tidal river based on GA |
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Uncategorized |
Uncategorized |
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No abstract available |
908448 |
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| publications-1695 |
PEER REVIEWED ARTICLE |
2012 |
C. Ji, A. Munjiza, J.J.R. Williams |
A novel iterative direct-forcing immersed boundary method and its finite volume applications |
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10.1016/j.jcp.2011.11.010 |
Data Management & Analytics |
River Basins |
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No abstract available |
909457 |
|
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| publications-1696 |
Peer reviewed articles |
2019 |
I. Colin Prentice; I. Colin Prentice; Belinda E. Medlyn; Belinda E. Medlyn; Shuangxi Zhou; Shuangxi Zhou |
Bridging Drought Experiment and Modeling: Representing the Differential Sensitivities of Leaf Gas Exchange to Drought |
Frontiers in Plant Science, Vol 9 |
10.3389/fpls.2018.01965 |
Data Management & Analytics |
Irrigation Systems |
|
No abstract available |
787203 |
|
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| publications-1697 |
Peer reviewed articles |
2023 |
Alexander Strehz, Joost Brombacher, Jelle Degen, Thomas Einfalt |
Feasibility of Downscaling Satellite-Based Precipitation Estimates Using Soil Moisture Derived from Land Surface Temperature |
Atmosphere |
10.3390/atmos14030435 |
Simulation & Modeling |
Wastewater Treatment Plants |
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For many areas, satellite-based precipitation products or reanalysis model data represent the only available precipitation information. Unfortunately, the resolution of these datasets is generally too coarse for many applications. A very promising downscaling approach is to use soil moisture due to its clear physical connection to precipitation. We investigate the feasibility of using soil moisture derived from land surface temperature in this context. These data are more widely available in the required resolution compared to other soil moisture data. Rain gauge-adjusted radar data from Namoi serves as a spatial reference dataset for two objectives: to identify the most suitable globally available precipitation dataset and to explore the precipitation information contained in the soil moisture data. The results show that these soil moisture data cannot be used to downscale satellite-based precipitation data to a high resolution because of cloud cover interference. Therefore, the Integrated Multi-satellitE Retrievals for GPM (IMERG) late data represents the best precipitation dataset for many areas in Australia that require timely precipitation information, according to this study. |
870344 |
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| publications-1698 |
Peer reviewed articles |
2022 |
Joost Brombacher, Isadora Rezende de Oliveira Silva, Jelle Degen, Henk Pelgrum |
A novel evapotranspiration based irrigation quantification method using the hydrological similar pixels algorithm |
Agricultural Water Management |
10.1016/j.agwat.2022.107602 |
Simulation & Modeling |
Natural Water Bodies |
|
No abstract available |
870344 |
|
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| publications-1699 |
Peer reviewed articles |
2022 |
Ignacio FuentesJose PadarianR. Willem Vervoort |
Spatial and Temporal Global Patterns of Drought Propagation |
Frontiers |
10.3389/fenvs.2022.788248 |
IoT & Sensors |
Uncategorized |
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Drought is the most expensive natural hazard and one of the deadliest. While drought propagation through standardised indices has been extensively studied at the regional scale, global scale drought propagation, and particularly quantifying the space and time variability, is still a challenging task. Quantifying the space time variability is crucial to understand how droughts have changed globally in order to cope with their impacts. In particular, better understanding of the propagation of drought through the climate, vegetation and hydrological subsystems can improve decision making and preparedness. This study maps spatial temporal drought propagation through different subsystems at the global scale over the last decades. The standardised precipitation index (SPI) based on the gamma distribution, the standardised precipitation evapotranspiration index (SPEI) based on the log-logistic distribution, the standardised vegetation index (SVI) based on z-scores, and the standardised runoff index (SRI) based on empirical runoff probabilities were quantified. Additionally, drought characteristics, including duration, severity and intensity were estimated. Propagation combined the delay in response in the subsystems using drought characteristics, and trends in time were analysed. All these were calculated at 0.05 to 0.25 arc degree pixels. In general, drought propagates rapidly to the response in runoff and streamflow, and a with longer delay in the vegetation. However, this response varies spatially across the globe and depending on the observation scale, and amplifies progressively in duration and severity across large regions from the meteorological to the agricultural/ecological and hydrologic subsystems, while attenuating in intensity. Significant differences exist between major Köppen climate groups in drought characteristics and propagation. Patterns show intensification of drought severity and propagation affecting vegetation and hydrology in regions of southern South America, Australia, and South West Africa. |
870344 |
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| publications-1700 |
Peer reviewed articles |
2022 |
Ignacio FuentesJose PadarianRutger Willem Vervoort |
Towards near real-time national-scale soil water content monitoring using data fusion as a downscaling alternative |
Journal of Hydrology |
10.1016/j.jhydrol.2022.127705 |
Uncategorized |
Uncategorized |
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No abstract available |
870344 |
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