scholarly journals Towards understanding hydroclimatic change in Victoria, Australia – why was the last decade so dry?

2009 ◽  
Vol 6 (5) ◽  
pp. 6181-6206 ◽  
Author(s):  
A. S. Kiem ◽  
D. C. Verdon-Kidd

Abstract. Since the mid-1990s Victoria, located in southeast Australia, has experienced severe drought conditions characterized by streamflow that is the lowest on record in many areas. While severe decreases in annual and seasonal rainfall totals have also been observed, this alone does not seem to explain the observed reduction in flow. In this study, we investigate the large-scale climate drivers for Victoria and demonstrate how these modulate the regional scale synoptic patterns, which in turn alter the way seasonal rainfall totals are compiled and the amount of runoff per unit rainfall that is produced. The hydrological implications are significant and illustrate the need for robust hydrological modelling, which takes into account insights into physical mechanisms that drive regional hydroclimatology, in order to properly understand and quantify the impacts of climate change (natural and/or anthropogenic) on water resources.

2010 ◽  
Vol 14 (3) ◽  
pp. 433-445 ◽  
Author(s):  
A. S. Kiem ◽  
D. C. Verdon-Kidd

Abstract. Since the mid-1990s the majority of Victoria, Australia, has experienced severe drought conditions (i.e. the "Big Dry") characterized by streamflow that is the lowest in approximately 80 years of record. While decreases in annual and seasonal rainfall totals have also been observed, this alone does not seem to explain the observed reduction in flow. In this study, we investigate the large-scale climate drivers for Victoria and demonstrate how these modulate the regional scale synoptic patterns, which in turn alter the way seasonal rainfall totals are compiled and the amount of runoff per unit rainfall that is produced. The hydrological implications are significant and illustrate the need for robust hydrological modelling, that takes into account insights into physical mechanisms that drive regional hydroclimatology, in order to properly understand and quantify the impacts of climate change (natural and/or anthropogenic) on water resources.


2019 ◽  
Vol 11 (22) ◽  
pp. 6463 ◽  
Author(s):  
Li ◽  
Yin ◽  
Zhang ◽  
Croke ◽  
Guo ◽  
...  

The Beijing-Tianjin-Hebei (Jingjinji) region is the most densely populated region in China and suffers from severe water resource shortage, with considerable water-related issues emerging under a changing context such as construction of water diversion projects (WDP), regional synergistic development, and climate change. To this end, this paper develops a framework to examine the water resource security for 200 counties in the Jingjinji region under these changes. Thus, county-level water resource security is assessed in terms of the long-term annual mean and selected typical years (i.e., dry, normal, and wet years), with and without the WDP, and under the current and projected future (i.e., regional synergistic development and climate change). The outcomes of such scenarios are assessed based on two water-crowding indicators, two use-to-availability indicators, and one composite indicator. Results indicate first that the water resources are distributed unevenly, relatively more abundant in the northeastern counties and extremely limited in the other counties. The water resources are very limited at the regional level, with the water availability per capita and per unit gross domestic product (GDP) being only 279/290 m3 and 46/18 m3 in the current and projected future scenarios, respectively, even when considering the WDP. Second, the population carrying capacity is currently the dominant influence, while economic development will be the controlling factor in the future for most middle and southern counties. This suggests that significant improvement in water-saving technologies, vigorous replacement of industries from high to low water consumption, as well as water from other supplies for large-scale applications are greatly needed. Third, the research identifies those counties most at risk to water scarcity and shows that most of them can be greatly relieved after supplementation by the planned WDP. Finally, more attention should be paid to the southern counties because their water resources are not only limited but also much more sensitive and vulnerable to climate change. This work should benefit water resource management and allocation decisions in the Jingjinji region, and the proposed assessment framework can be applied to other similar problems.


2021 ◽  
Vol 13 (9) ◽  
pp. 1837
Author(s):  
Eve Laroche-Pinel ◽  
Sylvie Duthoit ◽  
Mohanad Albughdadi ◽  
Anne D. Costard ◽  
Jacques Rousseau ◽  
...  

Wine growing needs to adapt to confront climate change. In fact, the lack of water becomes more and more important in many regions. Whereas vineyards have been located in dry areas for decades, so they need special resilient varieties and/or a sufficient water supply at key development stages in case of severe drought. With climate change and the decrease of water availability, some vineyard regions face difficulties because of unsuitable variety, wrong vine management or due to the limited water access. Decision support tools are therefore required to optimize water use or to adapt agronomic practices. This study aimed at monitoring vine water status at a large scale with Sentinel-2 images. The goal was to provide a solution that would give spatialized and temporal information throughout the season on the water status of the vines. For this purpose, thirty six plots were monitored in total over three years (2018, 2019 and 2020). Vine water status was measured with stem water potential in field measurements from pea size to ripening stage. Simultaneously Sentinel-2 images were downloaded and processed to extract band reflectance values and compute vegetation indices. In our study, we tested five supervised regression machine learning algorithms to find possible relationships between stem water potential and data acquired from Sentinel-2 images (bands reflectance values and vegetation indices). Regression model using Red, NIR, Red-Edge and SWIR bands gave promising result to predict stem water potential (R2=0.40, RMSE=0.26).


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