Benefits and limitations of data assimilation for discharge forecasting using an event-based rainfall–runoff model

Mediterranean catchments in southern France are threatened by potentially devastating fast floods which are difficult to anticipate. In order to improve the skill of rainfall-runoff models in predicting such flash floods, hydrologists use data assimilation techniques to provide real-time updates of the model using observational data. This approach seeks to reduce the uncertainties present in different components of the hydrological model (forcing, parameters or state variables) in order to minimize the error in simulated discharges. This article presents a data assimilation procedure, the best linear unbiased estimator (BLUE), used with the goal of improving the peak discharge predictions generated by an event-based hydrological model Soil Conservation Service lag and route (SCS-LR). For a given prediction date, selected model inputs are corrected by assimilating discharge data observed at the basin outlet. This study is conducted on the Lez Mediterranean basin in southern France. The key objectives of this article are (i) to select the parameter(s) which allow for the most efficient and reliable correction of the simulated discharges, (ii) to demonstrate the impact of the correction of the initial condition upon simulated discharges, and (iii) to identify and understand conditions in which this technique fails to improve the forecast skill. The correction of the initial moisture deficit of the soil reservoir proves to be the most efficient control parameter for adjusting the peak discharge. Using data assimilation, this correction leads to an average of 12% improvement in the flood peak magnitude forecast in 75% of cases. The investigation of the other 25% of cases points out a number of precautions for the appropriate use of this data assimilation procedure

Correcting the radar rainfall forcing of a hydrological model with data assimilation: application to flood forecasting in the Lez Catchment in Southern France

The present study explores the application of a data assimilation (DA) procedure to correct the radar rain- fall inputs of an event-based, distributed, parsimonious hy- drological model. An extended Kalman filter algorithm was built on top of a rainfall-runoff model in order to assimilate discharge observations at the catchment outlet. This work fo- cuses primarily on the uncertainty in the rainfall data and considers this as the principal source of error in the sim- ulated discharges, neglecting simplifications in the hydro- logical model structure and poor knowledge of catchment physics. The study site is the 114 km2 Lez catchment near Montpellier, France. This catchment is subject to heavy oro- graphic rainfall and characterised by a karstic geology, lead- ing to flash flooding events. The hydrological model uses a derived version of the SCS method, combined with a Lag and Route transfer function. Because the radar rainfall in- put to the model depends on geographical features and cloud structures, it is particularly uncertain and results in signifi- cant errors in the simulated discharges. This study seeks to demonstrate that a simple DA algorithm is capable of ren- dering radar rainfall suitable for hydrological forecasting. To test this hypothesis, the DA analysis was applied to estimate a constant hyetograph correction to each of 19 flood events. The analysis was carried in two different modes: by assimi- lating observations at all available time steps, referred to here as reanalysis mode, and by using only observations up to 3 h before the flood peak to mimic an operational environment, referred to as pseudo-forecast mode. In reanalysis mode, the resulting correction of the radar rainfall data was then com- pared to the mean field bias (MFB), a corrective coefficient determined using rain gauge measurements. It was shown that the radar rainfall corrected using DA leads to improved discharge simulations and Nash-Sutcliffe efficiency criteria compared to the MFB correction. In pseudo-forecast mode, the reduction of the uncertainty in the rainfall data leads to a reduction of the error in the simulated discharge, but un- certainty from the model parameterisation diminishes data assimilation efficiency. While the DA algorithm used is this study is effective in correcting uncertain radar rainfall, model uncertainty remains an important challenge for flood fore- casting within the Lez catchment

Analysis and purification of ssRNA and dsRNA molecules using asymmetrical flow field flow fractionation

Robust RNA purification and analysis methods are required to support the development of RNA vaccines and therapeutics as well as RNA interference-based crop protection solutions. Asymmetrical flow field -flow fractionation (AF4) is a gentle native purification method that applies liquid flows to separate sample components based on their hydrodynamic sizes. We recently showed that AF4 can be utilized to separate RNA molecules that are shorter than 110 nucleotides (nt), but the performance of AF4 in the analysis and purification of longer RNA molecules has not been previously evaluated. Here, we studied the perfor-mance of AF4 in separation of single-stranded (ss) and double-stranded (ds) RNA molecules in the size range of 75-6400 nt. In addition, we evaluated the power of AF4 coupling to different detectors, allow-ing separation to be combined with data collection on yield as well as molecular weight ( MW ) and size distribution. We show that AF4 method is applicable in RNA purification, quality control, and analytics, and results in good recoveries of ssRNA and dsRNA molecules. In addition, our results demonstrate the utility of AF4 multidetection platforms to study biophysical properties of long RNA molecules.(c) 2022 The Author(s). Published by Elsevier B.V.This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )Peer reviewe

Evidence for Specific Genotype-Dependent Immune Priming in the Lophotrochozoan Biomphalaria glabrata Snail.

International audienceHistorically, the prevailing view in the field of invertebrate immunity was that invertebrates that do not possess acquired adaptive immunity rely on innate mechanisms with low specificity and no memory. Several recent studies have shaken this paradigm and suggested that the immune defenses of invertebrates are more complex and specific than previously thought. Mounting evidence has shown that at least some invertebrates (mainly Ecdysozoa) show high levels of specificity in their immune responses to different pathogens, and that subsequent reexposure may result in enhanced protection (recently called 'immune priming'). Here, we investigated immune priming in the Lophotrochozoan snail species Biomphalaria glabrata, following infection by the trematode pathogen Schistosoma mansoni. We confirmed that snails were protected against a secondary homologous infection whatever the host strain. We then investigated how immune priming occurs and the level of specificity of B. glabrata immune priming. In this report we confirmed that immune priming exists and we identified a genotype-dependent immune priming in the fresh-water snail B. glabrata

Evidence for an ecological cost of enhanced herbicide metabolism in Lolium rigidum

1. In some cases, evaluation of resource competitive interactions between herbicide resistant vs. susceptible weed ecotypes provides evidence for the expression of fitness costs associated with evolved herbicide-resistant gene traits. Such fitness costs impact in the ecology and evolutionary trajectory of resistant populations. 2. Neighbourhood experiments were performed to quantify competitive effects and responses between herbicide-susceptible (S) and resistant (R) Lolium rigidum individuals in which resistance is due to enhanced herbicide metabolism mediated by cytochrome P450. 3. In two-way competitive interactions between the S and R phenotypes, individuals of the S phenotype were the stronger effect competitors on both a per capita and per unit-size basis. The S phenotype also exhibited a stronger competitive response to wheat plants than did the R phenotype, displaying significantly greater (30%) above-ground biomass at the vegetative stage. When subjected to competition from wheat, R individuals produced significantly fewer reproductive tillers and allocated fewer resources to reproductive traits than individuals of the S phenotype. 4. The role of potential mechanisms underlying this resistance cost driven by traits such as plant size and tolerance to low resource availability, as well as the evolutionary implications of the results are discussed. 5. Synthesis. Evolved herbicide resistance due to enhanced-herbicide metabolism mediated by cytochrome-P450 in L. rigidum has been shown to be accompanied with an impaired ability to compete for resources. These results are consistent with the resource-based theory that predicts a negative trade-off between growth and plant defence

Involvement of the Cytokine MIF in the Snail Host Immune Response to the Parasite Schistosoma mansoni

We have identified and characterized a Macrophage Migration Inhibitory Factor (MIF) family member in the Lophotrochozoan invertebrate, Biomphalaria glabrata, the snail intermediate host of the human blood fluke Schistosoma mansoni. In mammals, MIF is a widely expressed pleiotropic cytokine with potent pro-inflammatory properties that controls cell functions such as gene expression, proliferation or apoptosis. Here we show that the MIF protein from B. glabrata (BgMIF) is expressed in circulating immune defense cells (hemocytes) of the snail as well as in the B. glabrata embryonic (Bge) cell line that has hemocyte-like features. Recombinant BgMIF (rBgMIF) induced cell proliferation and inhibited NO-dependent p53-mediated apoptosis in Bge cells. Moreover, knock-down of BgMIF expression in Bge cells interfered with the in vitro encapsulation of S. mansoni sporocysts. Furthermore, the in vivo knock-down of BgMIF prevented the changes in circulating hemocyte populations that occur in response to an infection by S. mansoni miracidia and led to a significant increase in the parasite burden of the snails. These results provide the first functional evidence that a MIF ortholog is involved in an invertebrate immune response towards a parasitic infection and highlight the importance of cytokines in invertebrate-parasite interactions

80-річчя академіка НАН України О. С. Космодаміанського

24 березня виповнилося вісімдесят років відомому вченому-механіку академіку НАН України Олександру Сергійовичу Космодаміанському

Evolutionary-thinking in agricultural weed management

Agricultural weeds evolve in response to crop cultivation. Nevertheless, the central importance of evolutionary ecology for understanding weed invasion, persistence and management in agroecosystems is not widely acknowledged. This paper calls for more evolutionarily-enlightened weed management, in which management principles are informed by evolutionary biology to prevent or minimize weed adaptation and spread. As a first step, a greater knowledge of the extent, structure and significance of genetic variation within and between weed populations is required to fully assess the potential for weed adaptation. The evolution of resistance to herbicides is a classic example of weed adaptation. Even here, most research focuses on describing the physiological and molecular basis of resistance, rather than conducting studies to better understand the evolutionary dynamics of selection for resistance. We suggest approaches to increase the application of evolutionary-thinking to herbicide resistance research. Weed population dynamics models are increasingly important tools in weed management, yet these models often ignore intrapopulation and interpopulation variability, neglecting the potential for weed adaptation in response to management. Future agricultural weed management can benefit from greater integration of ecological and evolutionary principles to predict the long-term responses of weed populations to changing weed management, agricultural environments and global climate