the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Jul 2026
Brief communication: Anomalous low-discharge conditions increase algal bloom risk in Central European rivers
Abstract. Hydrological extremes have significant implications for riverine eutrophication as evidenced by algal (phytoplankton) blooms in European rivers during recent drought years. To assess how discharge conditions modulate nutrient-induced phytoplankton growth, we systematically analyze multi-year discharge, total phosphorus, and phytoplankton-indicating chlorophyll a data from 30 monitoring sites across Germany. We show that negative discharge anomalies consistently correspond to positive anomalies in measured chlorophyll a relative to the maximum possible chlorophyll a at the given phosphorus level. Further, we found increased algal bloom risk under below-normal discharge conditions, underlining the future challenges for water quality and eutrophication management under intensifying hydrological extremes.
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Status: open (until 07 Oct 2026)
- RC1: 'Comment on egusphere-2026-3240', Anonymous Referee #1, 03 Sep 2026 reply
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- 1
The manuscript is interesting, but several issues need to be addressed.
1) The Q–alpha_realized relationship may partly reflect TP behavior. Since alpha_realized is proportional to Chl-a/TP, changes in TP with discharge could produce the observed relationship. The authors need to test Chl-a directly while controlling for TP.
2) The bloom analysis does not seem to control for confounding factors. Bloom frequency is compared across discharge classes, but TP, season, and station seem to strongly influence blooms. A regression or mixed-effects analysis can better isolate the discharge effect.
3) Using interpolated Chl-a values to identify blooms needs justification as interpolation can smooth peaks and change threshold exceedances. The bloom analysis should be checked using the original observations.
4) Multiple correlation tests are conducted without correction, so the number of significant station-level correlations may be overstated. A multiple-testing correction or a test of the overall cross-station effect is needed.
5) Since the metric alpha_realized is based on Chl-a/TP and TP includes phosphorus that may not be available to phytoplankton, a higher alpha_realized does not necessarily mean that phytoplankton are using phosphorus more efficiently. This needs to be clarified and discussed.
6) Low-discharge anomalies do not necessarily indicate drought. Low flows may also reflect river regulation, reservoir or gate operations, or water withdrawals. These factors are not considered, so the drought and climate-change interpretation should be revised.
7) The figures are generally well designed, but there are a few issues. For Figure 2, the caption says monthly medians are “subtracted” to obtain the anomalies, while Eqs. (4–5) define the anomalies as log ratios / differences of logarithms. The caption should match the equations. In Figure 3, the bloom fractions are presented without uncertainty/error estimates, making the apparent differences look definitive not statistically.
8) There seem to be a few careless mistakes. In Line 135 “shrinking our save operation space”, save" might be "safe." In Eqs. 4-5 the base of the logarithm is not specified. In Figure 3g, 19.6% - 15.3% = 4.3 % and not 4.6 % as stated in the text "the absolute differences (4.6% and 5.5%)" (Line 118).