4 research outputs found
Environmental flow assessment for intermittent rivers supporting the most poleward mangroves
Abstract
The most vulnerable and dynamic ecosystems in terms of response to climate change and fluctuations in hydrological conditions are mangroves, particularly those located on the edge of their latitudinal range limits. The four primary Iranian mangrove forest sites: Nayband, Qeshm, Gabrik, and Govatr, located in the northern part of the Persian Gulf and the Gulf of Oman already exist near the limit of their tolerance to extreme temperature, precipitation, and salinity. Due to extreme climate conditions at these locations, the mangrove trees are usually smaller and less dense as compared with mangroves closer to the equator complicating their monitoring and mapping efforts. Despite the growing attention to the ecological benefits of mangrove forests and their importance in climate change mitigation, there are still a few studies on these marginal mangroves. Therefore, we investigated whether the variation in mangrove ecosystem health is related to the changes in physical parameters and differs between estuarine and sea-side locations. We developed a comprehensive database on NDVI values, associated rainfall, temperature, and river flow based on in-situ and remote sensing measurements. By understanding the normal hydrologic patterns that control the distribution and growth of mangroves in arid and semi-arid regions, we are questioning the need for environmental flow allocation to restore mangrove ecosystem health. This brings us to the second gap in the literature and the need for further studies on Environmental Flow assessment for intermittent and ephemeral rivers. Alike other mangroves studied, forests showed greenness seasonality, positively correlated with rainfall, and negatively correlated with temperature. As there was no clear difference between estuarine and marine sites, freshwater influence in the form of river flow, unlike temperature, cannot be considered a major limiting factor. Nevertheless, during prolonged droughts mangroves could benefit from the recommended allocation of Environmental Flow during the cold period (November–March)
RiTiCE:River flow Timing Characteristics and Extremes in the Arctic region
Abstract
(1) Background: river ice has a significant impact on nearly 66% of rivers in the Northern Hemisphere. Ice builds up during winter when the flow gradually reduces to its lowest level before the spring melt is initiated. Ice-induced floods can happen quickly, posing a risk to infrastructure, hydropower generation, and public safety, in addition to ecological repercussions from the scouring and erosion of the riverbeds.
(2) Methods: we used the annual daily hydrograph to develop a RiTiCE tool that detects the break-up date and develops indices to analyze timing characteristics of extreme flow in the Tana and Tornio Rivers.
(3) Results: the study showed that low-flow periods in two rivers had a significant trend with a confidence level of 95%. Additionally, it was observed that the occurrence date of seasonal 90-day low- and high-flow periods occurred earlier in recent years. Conversely, the Tana River showed a negative trend in its annual minimum flow over the century, which is the opposite of what happened with the Tornio River.
(4) Conclusions: the method can be used to detect the date when the river ice breaks up in a given year, leading to a better understanding of the river ice phenomenon
Factors affecting the presence of Arctic charr in streams based on a jittered binary genetic programming model
Abstract
Arctic charr is one of the fish species most sensitive to climate change but studies on their freshwater habitat preferences are limited, especially in the fluvial environment. Machine learning methods offer automatic and objective models for ecohydrological processes based on observed data. However, i) the number of ecological records is often much smaller than hydrological observations, and ii) ecological measurements over the long-term are costly. Consequently, ecohydrological datasets are scarce and imbalanced. To address these problems, we propose jittered binary genetic programming (JBGP) to detect the most dominant ecohydrological parameters affecting the occurrence of Arctic charr across tributaries within the large subarctic Teno River catchment, in northernmost Finland and Norway. We quantitatively assessed the accuracy of the proposed model and compared its performance with that of classic genetic programming (GP), decision tree (DT) and state-of-the-art jittered-DT methods. The JBGP achieves the highest total classification accuracy of 90% and a Heidke skill score of 78%, showing its superiority over its counterparts. Our results showed that the dominant factors contributing to the presence of Arctic charr in Teno River tributaries include i) a higher density of macroinvertebrates, ii) a lower percentage of mires in the catchment and iii) a milder stream channel slope