A concerted research effort to advance the hydrological understanding of tropical páramos

Hydrological Processes. 2020;1–19.

Páramos, a neotropical alpine grassland-peatland biome of the northern Andes and Central America, play an essential role in regional and global cycles of water, carbon, and nutrients. They act as water towers, delivering water and ecosystem services from the high mountains down to the Pacific, Caribbean, and Amazon regions. Páramos are also widely recognized as a biodiversity and climate change hot spots, yet they are threatened by anthropogenic activities and environmental changes. Despite their importance for water security and carbon storage, and their vulnerability to human activities, only three decades ago, páramos were severely understudied.

Increasing awareness of the need for hydrological evidence to guide sustainable management of páramos prompted action for generating data and for filling long-standing knowledge gaps. This has led to a remarkably successful increase in scientific knowledge, induced by a strong interaction between the scientific, policy, and (local) management communities. A combination of well-established and innovative approaches has been applied to data collection, processing, and analysis. In this review, we provide a short overview of the historical development of research and state of knowledge of hydrometeorology, flux dynamics, anthropogenic impacts, and the influence of extreme events in páramos. We then present emerging technologies for hydrology and water resources research and management applied to páramos.

We discuss how converging science and policy efforts have leveraged traditional and new observational techniques to generate an evidence base that can support the sustainable management of páramos. We conclude that this co-evolution of science and policy was able to successfully cover different spatial and temporal scales. Lastly, we outline future research directions to showcase how sustainable long-term data collection can foster the responsible conservation of páramos water towers.

Modelling non-stationary water ages in a tropical rainforest: A preliminary spatially distributed assessment

Hydrological Processes. 2020;1–18.

Pristine tropical forests play a critical role in regional and global climate systems. For a better understanding of the eco-hydrology of tropical “evergreen” vegetation, it is essential to know the partitioning of water into transpiration and evaporation, runoff and associated water ages. For this purpose, we evaluated how topography and vegetation influence water flux and age dynamics at high temporal (hourly) and spatial (10 m) resolution using the Spatially Distributed Tracer-Aided Rainfall-Runoff model for the tropics (STARRtropics). The model was applied in a tropical rainforest catchment (3.2 km2) where data were collected biweekly to monthly and during intensive monitoring campaigns from January 2013 to July 2018. The STARRtropics model was further developed, incorporating an isotope mass balance for evapotranspiration partitioning into transpiration and evaporation. Results exhibited a rapid streamflow response to rainfall inputs (water and isotopes) with limited mixing and a largely time invariant baseflow isotope composition. Simulated soil water storage showed a transient response to rainfall inputs with a seasonal component directly resembling the streamflow dynamics which was independently evaluated using soil water content measurements. High transpiration fluxes (max 7 mm/day) were linked to lower slope gradients, deeper soils and greater leaf area index. Overall water partitioning resulted in 65% of the actual evapotranspiration being driven by vegetation with high transpiration rates over the drier months compared to the wet season. Time scales of water age were highly variable, ranging from hours to a few years. Stream water ages were conceptualized as a mixture of younger soil water and slightly older, deeper soil water and shallow groundwater with a maximum age of roughly 2 years during drought conditions (722 days). The simulated soil water ages ranged from hours to 162 days and for shallow groundwater up to 1,200 days. Despite the model assumptions, experimental challenges and data limitation, this preliminary spatially distributed model study enhances knowledge about the water ages and overall young water dominance in a tropical rainforest with little influence of deeper and older groundwater. 

Tracing Water Sources and Fluxes in a Dynamic Tropical Environment: From Observations to Modeling

Front. Earth Sci. 8:571477. doi: 10.3389/feart.2020.571477

Tropical regions cover approximately 36% of the Earth’ s landmass. These regions are home to 40% of the world’ s population, which is projected to increase to over 50% by 2030 under a remarkable climate variability scenario often exacerbated by El Niño Southern Oscillation (ENSO) and other climate teleconnections. In the tropics, ecohydrological conditions are typically under the influence of complex land-ocean atmosphere interactions that produce a dynamic cycling of mass and energy reflected in a clear partition of water fluxes. Here, we present a review of 7 years of a concerted and continuous water stable isotope monitoring across Costa Rica, including key insights learned, main methodological advances and limitations (both in experimental designs and data analysis), potential data gaps, and future research opportunities with a humid tropical perspective. The uniqueness of the geographic location of Costa Rica within the mountainous Central America Isthmus, receiving moisture inputs from the Caribbean Sea (windward) and the Pacifi c Ocean (complex leeward topography), and experiencing strong ENSO events, poses a clear advantage for the use of isotopic variations to underpin key drivers in ecohydrological responses. In a sequential approach, isotopic variations are analyzed from moisture transport, rainfall generation, and groundwater/surface connectivity to Bayesian and rainfall-runoff modeling. The overarching goal of this review is to provide a robust humid tropical example with a progressive escalation from common water isotope observations to more complex modeling outputs and applications to enhance water resource management in the tropics.

Informe de encuesta “La Universidad de Costa Rica en la opinión pública (2019)”

Rainfall-Runoff Modeling: A Brief Overview

Reference Module in Earth Systems and Environmental Sciences, doi: 10.1016/B978-0-12-409548-9.11595-7.

This short article on rainfall-runoff modeling attempts to give a brief overview on a rather vast topic in the hydrological sciences. We, unfortunately, cannot go into details of any special branch of modeling. Nonetheless, we rather settle on introductory materials that might offer guidance for hydrology, engineering, geography and environmental science students, postgraduate students, professionals and anybody looking for hints to catch up on reading relevant literature, concepts and tendencies (for a comprehensive source in this direction we refer to Beven, 2012).

Our focus will be on rainfall-runoff modeling or how the transformation of rainfall into runoff can be simulated with different mathematical tools describing runoff generation processes. Regarding the spatial scale, most model applications are carried out at catchment scales, despite relevant global scale (Bierkens et al., 2015) or smaller scale hillslope (Anderson and Brooks, 1996 follow on from Kirkby, 1978) or even pedon-scale (Lin, 2012) modeling efforts. In terms of temporal scale, model applications range from minute-wise flood forecasting (Hapuarachchi et al., 2011; Adams and Pagano, 2016) to thousands of years reconstructing paleo-hydrometeorological conditions (Kalma and Sivapalan, 1995; Gasser, 2015). Rainfall-runoff models also often serve as input to, for example, hydraulic models (de Paiva et al., 2013) or biogeochemical models (Futter et al., 2007), which we mention but have to abstain from presenting detailed facts.

Here, based on personal and professional experiences, we describe why we use hydrological models, their advantages and challenges. We briefly outline the historical advances in rainfall-runoff model development, the type of models one encounters in the literature and the world-wide web. Furthermore, we underline the fact that all models need calibration, and how we evaluate models and attempt to assess model uncertainties. Considering the above, we lastly talk from our perspectives about some novel tendencies in rainfall-runoff model development.

With that, we hope to have provided some motivating facts about rainfall-runoff modeling as a great tool in hydrology encouraging readers to move well beyond this article.

Technical note: Uncertainty in multi-source partitioning using large tracer data sets

 Hydrol. Earth Syst. Sci., 23, 5059–5068, 2019

The availability of large tracer data sets opened up the opportunity to investigate multiple source contributions to a mixture. However, the source contributions may be uncertain and, apart from Bayesian approaches, to date there are only solid methods to estimate such uncertainties for two and three sources.We introduce an alternative uncertainty estimation method for four sources based on multiple tracers as input data. Taylor series approximation is used to solve the set of linear mass balance equations. We illustrate the method to compute individual uncertainties in the calculation of source contributions to a mixture, with an example from hydrology, using a 14-tracer set from water sources and streamflow from a tropical, high-elevation catchment. Moreover, this method has the potential to be generalized to any number of tracers across a range of disciplines.

Picture Power? The Contribution of Visuals and Text to Partisan Selective Exposure

 Media and Communication (ISSN: 2183–2439) 7(3): 12–31. doi: 10.17645/mac.v7i3.1991

Today’s high-choice media environment allows citizens to select news in line with their political preferences and avoid content counter to their priors. So far, however, selective exposure research has exclusively studied news selection based on textual cues, ignoring the recent proliferation of visual media. This study aimed to identify the contribution of visuals alongside text in selective exposure to pro-attitudinal, counter-attitudinal and balanced content. Using two experiments, we created a social media-style newsfeed with news items comprising matching and non-matching images and headlines about the contested issues of immigration and gun control in the U.S. By comparing selection behavior of participants with opposing prior attitudes on these topics, we pulled apart the contribution of images and headlines to selective exposure. Findings show that headlines play a far greater role in guiding selection, with the influence of images being minimal. The additional influence of partisan source cues is also considered. 

CRISPR/Cas9: Development and Application in Rice Breeding

Rice Science, 2019, 26(5): 265-281

Rice (Oryza sativa L.) is an important staple food crop worldwide due to its adaptability to different environmental conditions. Because of its great economic and social importance, there is a constant requirement for new varieties with improved agronomic characteristics, such as tolerance to different biotic (such as bacterium, fungus, insect and virus) and abiotic stresses (such as salinity, drought and temperature), higher yield and better organoleptic and nutritional value. Among the new genome editing technologies, the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) (CRISPR/Cas) system allows precise and specific edition in a targeted genome region. It is one of the most frequently used techniques for the study of the function of new genes and for the development of mutant lines with enhanced tolerance to biotic and abiotic stresses, herbicide resistance or improved yield. The wide varieties of applications for this technology include simple non-homologous end joining, homologous recombination, gene replacement, and base editing. In this review, we analyzed how some of these applications have been used in rice cultivars to obtain rice varieties better adapted to current environmental conditions and market requirements.

ohun: An R package for diagnosing and optimizing automatic sound event detection

ohun: An R package for diagnosing and optimizing automatic sound event detection