Impacts of high inter-annual variability of rainfall on a century of extreme hydrologic regime of northwest Australia
Bibliographic record
Abstract
Abstract. Long-term hydrologic records provide crucial reference baselines of natural variability that can be used to evaluate potential changes in hydrologic regimes and their impacts. However, there is a dearth of studies of the hydrologic regimes for tropical drylands where intraseasonal and interannual variability in magnitude and frequency of precipitation are extreme. Here, we sought to identify the main hydroclimatic determinants of the strongly episodic flood regime of a large catchment in the semi-arid, subtropical northwest of Australia and to establish the background of hydrologic variability for the region over the last century. We used a monthly sequence of satellite images to quantify surface water expression on the Fortescue Marsh, the largest water feature of inland northwest Australia, from 1988 to 2012. We used this sequence together with instrumental rainfall data to build a statistical model with multiple linear regression and reconstruct monthly history of floods and droughts since 1912. We found that severe and intense regional rainfall events, as well as the sequence of recharge events both within and between years, determine surface water expression on the floodplain (i.e. total rainfall, number of rain days and carried-over inundated area; R2adj = 0.79; p value < 0.001, ERMSP = 56 km2). The most severe reconstructed inundation over the last century was in March 2000 (1000 km2), which is less than the 1300 km2 area required to overflow to the adjacent catchment. The Fortescue Marsh was completely dry for 32% of all years, for periods of up to four consecutive years. Extremely wet years (seven of the 100 years) caused the Marsh to remain inundated for up to 12 months; only 25% of years (9% of all months) had floods of greater than 300 km2. The prolonged, severe and consecutive yearly inundations between 1999 and 2006 were unprecedented compared to the last century. While there is high inter-annual variability in the system, if the frequency and intensity of extreme rainfall events for the region were to increase (or be similar to 1999–2006), surface water on the Marsh will become more persistent, in turn impacting its structure and functioning as a wetland.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".