Self-organizing maps of typhoon tracks allow for flood forecasts up to two days in advance.

Typhoons are among the greatest natural hazards along East Asian coasts. Typhoon-related precipitation can produce flooding that is often only predictable a few hours in advance. Here, we present a machine-learning method comparing projected typhoon tracks with past trajectories, then using the information to predict flood hydrographs for a watershed on Taiwan. The hydrographs provide early warning of possible flooding prior to typhoon landfall, and then real-time updates of expected flooding along the typhoon's path. The method associates different types of typhoon tracks with landscape topography and runoff data to estimate the water inflow into a reservoir, allowing prediction of flood hydrographs up to two days in advance with continual updates. Modelling involves identifying typhoon track vectors, clustering vectors using a self-organizing map, extracting flow characteristic curves, and predicting flood hydrographs. This machine learning approach can significantly improve existing flood warning systems and provide early warnings to reservoir management.

Signals of stream fish homogenization revealed by AI-based clusters.

Risks of stream fish homogenization are attributable to multiple variables operating at various spatial and temporal scales. However, understanding the mechanisms of homogenization requires not only watershed-scale, but also exhaustive fish community structure shifts representing detailed local functional relationships essential to homogenization potentials. Here, we demonstrate the idea of applying AI-based clusters to reveal nonlinear responses of homogenization risks among heterogeneous hydro-chemo-bio variables in space and time. Results found that species introduction, dam isolation, and the potential of climate-mediated disruptions in hydrologic cycles producing degradation in water quality triggered shifts of community assembly and resulting structures producing detrimental conditions for endemic fishes. The AI-based clustering approach suggests that endemic species conservation should focus on alleviation of low flows, control of species introduction, limiting generalist expansion, and enhancing the hydrological connectivity fragmented by dams. Likewise, it can be applied in other geographical and environmental settings for finding homogenization mitigation strategies.

Assessing the natural and anthropogenic influences on basin-wide fish species richness.

Theory predicts that the number of fish species increases with river size in natural free-flowing rivers, but the relationship is lost under intensive exploitation of water resources associated with dams and/or landscape developments. In this paper, we aim to identify orthomorphic issues that disrupt theoretical species patterns based on a multi-year, basin-wide assessment in the Danshuei River Watershed of Taiwan. We hypothesize that multiple human-induced modifications fragment habitat areas leading to decreases of local fish species richness. We integrally relate natural and anthropogenic influences on fish species richness by a multiple linear regression model that is driven by a combination of factors including river network structure controls, water quality alterations of habitat, and disruption of channel connectivity with major discontinuities in habitat caused by dams. We found that stream order is a major forcing factor representing natural influence on fish species richness. In addition to stream order, we identified dams, dissolved oxygen deficiency (DO), and excessive total phosphorus (TP) as major anthropogenic influences on the richness of fish species. Our results showed that anthropogenic influences were operating at various spatial scales that inherently regulate the physical, chemical, and biological condition of fish habitats. Moreover, our probability-based risk assessment revealed causes of species richness reduction and opportunities for mitigation. Risks of species richness reduction caused by dams were determined by the position of dams and the contribution of tributaries in the drainage network. Risks associated with TP and DO were higher in human-activity-intensified downstream reaches. Our methodology provides a structural framework for assessing changes in basin-wide fish species richness under the mixed natural and human-modified river network and habitat conditions. Based on our analysis results, we recommend that a focus on landscape and riverine habitats and maintaining long-term monitoring programs are crucial for effective watershed management and river conservation plans.

Integrative analysis of water quality and physical habitat in the ecological design of water resources projects.

Historical approaches to water quality control are finding new challenges as ecosystem issues are addressed in comprehensive water resources management programs. Important issues include the recognition that physical habitat conditions may be more important than water quality when ecosystem sustainability is the management objective. Although past emphasis has been on the control of continuous discharges, modern watershed management recognizes that achieving ecosystem sustainability requires control of runoff events that are variable in volume, timing, and frequency. This paper will explore how physical habitat management plays a dominant role in the determination of the ecosystem sustainability. Physical habitat is the result of an eco-hydro-geomorphic systems integration. This integration recognizes that magnitude, duration, and frequency, particularly in the hydrologic system contributes to an understanding of sensitivity and vulnerability in channel networks. Other topics of discussion include the critical linkages between contaminant concentration, duration of exposure, and frequency of recurrence in a watershed setting where differing levels of habitat stability are related to landscape use. The paper will also explore ecological engineering and associated ecohydrology and ecohydraulics in the development of modern watershed management.

A multiscale conceptual framework for integrated ecogeomorphological research to support stream naturalization in the agricultural Midwest.

The complexity of fluvial systems necessitates interdisciplinary research in fluvial geomorphology and aquatic ecology to develop a fundamental understanding of interconnections among biotic and abiotic aspects of these systems. Integrated knowledge of this type is vital for environmental management of streams in human-dominated environments. A conceptual framework is presented for integrating geomorphological and ecological research on streams in East Central Illinois, USA, a glaciated low-relief agricultural landscape. The framework embodies a multiscale perspective in which a geomorphological conception of the fluvial system is used to define a hierarchy of characteristic spatial scales for exploring important linkages between stream geomorphology and aquatic ecology. The focus ecologically is on fish, because a rich body of historical information exists on fisheries in East Central Illinois and because past work has suggested that availability of physical habitat is a major factor influencing the community characteristics of fish in this human-altered environment. The hierarchy embodied in the framework includes the network, link, planform, bar unit, bar element, and bedform/grain scales. Background knowledge from past research is drawn upon to identify potential linkages between geomorphological and ecological conditions at each of these scales. The conceptual framework is useful for guiding integrated ecogeomorphological research at specific scales and across different scales. It also is helpful for illustrating how widespread human modification of streams has catastrophically altered the scalar structure of fluvial systems in East Central Illinois. Knowledge emerging from the integrated research provides a basis for environmental-management schemes directed toward stream naturalization.