The Drought Monitor

There is a need for improved drought monitoring and assessment methods in the United States. Drought is the most costly natural disaster [Federal Emergency Management Agancy (FEMA 1995; Wilhite 2000)], but it is often neglected by developers of assessment and forecast products. Drought is more nebulous than other disasters and does not lend itself to traditional assessments or forecast methods. Its relatively slow onset and the complexity of its impacts are reasons for the new assessment methodology. Improvements in drought monitoring and forecasting techniques will allow for better preparation, lead to better management practices, and reduce the vulnerability of society to drought and its subsequent impacts. The Drought Monitor (additional information available online at http://drought.unl/edu/dm) was created with the goal of tracking and displaying the magnitude and spatial extent of drought and its impacts across the United States. The Drought Monitor is produced weekly and classifies drought severity into four major categories, with a fifth category threshold assigned to locations on a map are determined from a number of indicators, or tools, blended with subjective interpretation

An integrated molecular and conventional breeding scheme for enhancing genetic gain in maize in Africa

Open Access Journal; Published online: 06 Nov 2019Maize production in West and Central Africa (WCA) is constrained by a wide range of interacting stresses that keep productivity below potential yields. Among the many problems afflicting maize production in WCA, drought, foliar diseases, and parasitic weeds are the most critical. Several decades of efforts devoted to the genetic improvement of maize have resulted in remarkable genetic gain, leading to increased yields of maize on farmers’ fields. The revolution unfolding in the areas of genomics, bioinformatics, and phenomics is generating innovative tools, resources, and technologies for transforming crop breeding programs. It is envisaged that such tools will be integrated within maize breeding programs, thereby advancing these programs and addressing current and future challenges. Accordingly, the maize improvement program within International Institute of Tropical Agriculture (IITA) is undergoing a process of modernization through the introduction of innovative tools and new schemes that are expected to enhance genetic gains and impact on smallholder farmers in the region. Genomic tools enable genetic dissections of complex traits and promote an understanding of the physiological basis of key agronomic and nutritional quality traits. Marker-aided selection and genome-wide selection schemes are being implemented to accelerate genetic gain relating to yield, resilience, and nutritional quality. Therefore, strategies that effectively combine genotypic information with data from field phenotyping and laboratory-based analysis are currently being optimized. Molecular breeding, guided by methodically defined product profiles tailored to different agroecological zones and conditions of climate change, supported by state-of-the-art decision-making tools, is pivotal for the advancement of modern, genomics-aided maize improvement programs. Accelerated genetic gain, in turn, catalyzes a faster variety replacement rate. It is critical to forge and strengthen partnerships for enhancing the impacts of breeding products on farmers’ livelihood. IITA has well-established channels for delivering its research products/technologies to partner organizations for further testing, multiplication, and dissemination across various countries within the subregion. Capacity building of national agricultural research system (NARS) will facilitate the smooth transfer of technologies and best practices from IITA and its partners

Machine learning paradigms for modeling spatial and temporal information in multimedia data mining

Multimedia data mining and knowledge discovery is a fast emerging interdisciplinary applied research area. There is tremendous potential for effective use of multimedia data mining (MDM) through intelligent analysis. Diverse application areas are increasingly relying on multimedia under-standing systems. Advances in multimedia understanding are related directly to advances in signal processing, computer vision, machine learning, pattern recognition, multimedia databases, and smart sensors. The main mission of this special issue is to identify state-of-the-art machine learning paradigms that are particularly powerful and effective for modeling and combining temporal and spatial media cues such as audio, visual, and face information and for accomplishing tasks of multimedia data mining and knowledge discovery. These models should be able to bridge the gap between low-level audiovisual features which require signal processing and high-level semantics. A number of papers have been submitted to the special issue in the areas of imaging, artificial intelligence; and pattern recognition and five contributions have been selected covering state-of-the-art algorithms and advanced related topics. The first contribution by D. Xiang et al. “Evaluation of data quality and drought monitoring capability of FY-3A MERSI data” describes some basic parameters and major technical indicators of the FY-3A, and evaluates data quality and drought monitoring capability of the Medium-Resolution Imager (MERSI) onboard the FY-3A. The second contribution by A. Belatreche et al. “Computing with biologically inspired neural oscillators: application to color image segmentation” investigates the computing capabilities and potential applications of neural oscillators, a biologically inspired neural model, to gray scale and color image segmentation, an important task in image understanding and object recognition. The major contribution of this paper is the ability to use neural oscillators as a learning scheme for solving real world engineering problems. The third paper by A. Dargazany et al. entitled “Multibandwidth Kernel-based object tracking” explores new methods for object tracking using the mean shift (MS). A bandwidth-handling MS technique is deployed in which the tracker reach the global mode of the density function not requiring a specific staring point. It has been proven via experiments that the Gradual Multibandwidth Mean Shift tracking algorithm can converge faster than the conventional kernel-based object tracking (known as the mean shift). The fourth contribution by S. Alzu’bi et al. entitled “3D medical volume segmentation using hybrid multi-resolution statistical approaches” studies new 3D volume segmentation using multiresolution statistical approaches based on discrete wavelet transform and hidden Markov models. This system commonly reduced the percentage error achieved using the traditional 2D segmentation techniques by several percent. Furthermore, a contribution by G. Cabanes et al. entitled “Unsupervised topographic learning for spatiotemporal data mining” proposes a new unsupervised algorithm, suitable for the analysis of noisy spatiotemporal Radio Frequency Identification (RFID) data. The new unsupervised algorithm depicted in this article is an efficient data mining tool for behavioral studies based on RFID technology. It has the ability to discover and compare stable patterns in a RFID signal, and is appropriate for continuous learning. Finally, we would like to thank all those who helped to make this special issue possible, especially the authors and the reviewers of the articles. Our thanks go to the Hindawi staff and personnel, the journal Manager in bringing about the issue and giving us the opportunity to edit this special issue

Conceptual modelling to assess how the interplay of hydrological connectivity, catchment storage and tracer dynamics controls nonstationary water age estimates

Acknowledgements We would like to gratefully acknowledge the data provided by SEPA, Iain Malcolm. Mark Speed, Susan Waldron and many MSS staff helped with sample collection and lab analysis. We thank the European Research Council (project GA 335910 VEWA) for funding and are grateful for the constructive comments provided by three anonymous reviewers.Peer reviewedPostprin

Agricultural drought in the Claromecó river basin, Buenos Aires province, Argentina

The dry and wet periods affecting the Claromecó Creek Basin in the south of the Province of Buenos Aires were analysed applying Palmer’s Model. Palmer’s Drought Severity Index was calculated regionally for five towns for the 1904-1999 period. Both the rate corresponding to the drying of soil humidity and the regional climatic rates were taken into account. On analysing the conditions featured in each decade and during the period as a whole, it was found that whereas droughts prevailed 42.7% of the time, wet conditions predominated 35.5%, and during theremaining 21.8% of the time conditions were normal. Drought periods lasted longer than wet ones - an average of 16 to 19 months as opposed to a maximum of 11 months. The harshest droughts affecting regional farming were registered in 1962/63 (with an 80% loss of the wheat crop, the worst harvest ever), 1995/96 and 1998/99.Se aplica el modelo de Palmer para analizar los episodios secos y húmedos de la cuenca hidrográfica del arroyo Claromecó, localizada al sur de la provincia de Buenos Aires, Argentina. El Índice de Severidad de Sequía de Palmer es calculado en cinco localidades y para el período 1904-1999, desarrollando explícitamente las rectas que representan la tasa del secado de la humedad del suelo y los coeficientes climáticos regionales. Se analizan los períodos secos y húmedos por décadas y para el periodo total. Durante el período analizado el 42,7 % se caracterizó por condiciones de sequía de distinta intensidad, el 32,7 % con condiciones húmedas y el resto con condiciones normales. Los episodios mas largos observados corresponden a las sequías, con máximos entre 16 y 19 meses mientras que los máximos periodos húmedos no superan los 11 meses. El impacto de las peores sequías en la economía agrícola regional se registró en los años 1962/63 (con la mayor pérdida en la cosecha de trigo, 80 %), 1995/96 y 1998/99.Fil: Carbone, Maria Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Scian, Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Piccolo, Maria Cintia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentin

Guidelines for the scoping and environmental assessment of water resources projects. The environment and water resources projects - Volume 2

In its role as protector of the water environment, the Environment Agency requires significant water resources abstraction applications and schemes such as drought orders, drought permits, time limited licences, and river transfers to be environmentally assessed leading to the production of an environmental report or statement. This may not take the form of a formal Environmental Assessment, but is required to provide environmental information to support applications. (See Volume 1 - Guidance for Scoping and Environmental Assessment for Water Resources Projects in North East Region). This second volume concentrates on the environmental monitoring component of environmental assessments

Xylem surfactants introduce a new element to the cohesion-tension theory

Vascular plants transport water under negative pressure without constantly creating gas bubbles that would disable their hydraulic systems. Attempts to replicate this feat in artificial systems almost invariably result in bubble formation, except under highly controlled conditions with pure water and only hydrophilic surfaces present. In theory, conditions in the xylem should favor bubble nucleation even more: there are millions of conduits with at least some hydrophobic surfaces, and xylem sap is saturated or sometimes supersaturated with atmospheric gas and may contain surface-active molecules that can lower surface tension. So how do plants transport water under negative pressure? Here, we show that angiosperm xylem contains abundant hydrophobic surfaces as well as insoluble lipid surfactants, including phospholipids, and proteins, a composition similar to pulmonary surfactants. Lipid surfactants were found in xylem sap and as nanoparticles under transmission electron microscopy in pores of intervessel pit membranes and deposited on vessel wall surfaces. Nanoparticles observed in xylem sap via nanoparticle-tracking analysis included surfactant-coated nanobubbles when examined by freeze-fracture electron microscopy. Based on their fracture behavior, this technique is able to distinguish between dense-core particles, liquid-filled, bilayer-coated vesicles/liposomes, and gas-filled bubbles. Xylem surfactants showed strong surface activity that reduces surface tension to low values when concentrated as they are in pit membrane pores. We hypothesize that xylem surfactants support water transport under negative pressure as explained by the cohesion-tension theory by coating hydrophobic surfaces and nanobubbles, thereby keeping the latter below the critical size at which bubbles would expand to form embolisms

Large Area Crop Inventory Experiment (LACIE). LACIE integrated drought plan

There are no author-identified significant results in this report