| 1. |
|
|
| 2. |
|
|
| 3. |
- Kiem, Anthony S., et al.
(författare)
-
Natural hazards in Australia: droughts
- 2016
-
Ingår i: Climatic Change. - : Springer Nature. - 0165-0009 .- 1573-1480. ; 139:1, s. 37-54
-
Tidskriftsartikel (refereegranskat)abstract
- Droughts are a recurrent and natural part of the Australian hydroclimate, with evidence of drought dating back thousands of years. However, our ability to monitor, attribute, forecast and manage drought is exposed as insufficient whenever a drought occurs. This paper summarises what is known about drought hazard, as opposed to the impacts of drought, in Australia and finds that, unlike other hydroclimatic hazards, we currently have very limited ability to tell when a drought will begin or end. Understanding, defining, monitoring, forecasting and managing drought is also complex due to the variety of temporal and spatial scales at which drought occurs and the diverse direct and indirect causes and consequences of drought. We argue that to improve understanding and management of drought, three key research challenges should be targeted: (1) defining and monitoring drought characteristics (i.e. frequency, start, duration, magnitude, and spatial extent) to remove confusion between drought causes, impacts and risks and better distinguish between drought, aridity, and water scarcity due to over-extractions; (2) documenting historical (instrumental and pre-instrumental) variation in drought to better understand baseline drought characteristics, enable more rigorous identification and attribution of drought events or trends, inform/evaluate hydrological and climate modelling activities and give insights into possible future drought scenarios; (3) improving the prediction and projection of drought characteristics with seasonal to multidecadal lead times and including more realistic modelling of the multiple factors that cause (or contribute to) drought so that the impacts of natural variability and anthropogenic climate change are accounted for and the reliability of long-term drought projections increases.
|
|
| 4. |
- Sivakumar, Bellie, et al.
(författare)
-
Catchment classification framework in hydrology: challenges and directions
- 2015
-
Ingår i: Journal of Hydrologic Engineering. - 1084-0699. ; 20:1
-
Tidskriftsartikel (refereegranskat)abstract
- The past few decades have witnessed the development of numerous catchment models, often with increasing structural complexity and mathematical sophistication. While such models have certainly provided a better understanding of catchments and associated processes, they are also often catchment-specific, region-specific, or process-specific. Serious concerns on this modeling trend have been increasingly raised in recent times and, consequently, the need for a generic catchment classification framework in hydrology has been emphasized. There have indeed been some attempts to advance the idea of such a classification framework. Such studies have investigated different ways of developing a framework, including river morphology, river regimes, hydroclimatic factors, landscape and land use parameters, hydrologic similarity indexes, hydrologic signatures, ecohydrologic factors, geostatistical properties, entropy, nonlinear and chaotic properties, data mining, and other relevant characteristics and methods. Although useful in their own ways, these studies are largely inadequate for a generic classification framework. In addition to the limitations that exist in each of the different forms, a coherent effort to bring these disparate forms together for a workable classification is also missing. This study highlights the challenges that the existing approaches pose in the development of a generic classification framework. It argues for an appropriate basis, a suitable methodology, and key components for such a framework. In particular, it discusses the vital role of system complexity as an appropriate basis for the classification framework and the potential of nonlinear dynamics, networks, and other modern concepts of complex systems science for assessing system complexity. The study also offers a three-step procedure for formulation and verification of a catchment classification framework.
|
|
