A mathematical morphology approach for a qualitative exploration of drought events in space and time

Drought events occur worldwide and possibly incur severe consequences. Trying to understand and characterize drought events is of considerable importance in order to improve the preparedness for coping with future events. In this paper, we present a methodology that allows for the delineation of drought events by exploiting their spatiotemporal nature. To that end, we apply operators borrowed from mathematical morphology to represent drought events as connected components in space and time. As an illustration, we identify drought events on the basis of a 35-year data set of daily soil moisture values covering mainland Australia. We then extract characteristics reflecting the affected area, duration and intensity from the proposed representation of a drought event in order to illustrate the impact of tuning parameters in the methodology presented. Yet, this paper we refrain from comparing with other drought delineation methods

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions

Using Satellite Images for Drought Monitoring: A Knowledge Discovery Approach

The main objective of this research was to develop a new concept and approach to extract knowledge from satellite imageries for near real-time drought monitoring. The near real-time data downloaded from the Atlantic Bird satellite were used to produce the drought spatial distribution. Our results showed that approximately 40% of the observed areas exhibited negative deviation. In this study, the possibility of using the near real-time spatio-temporal Meteosat Second Generation (MSG) data for drought monitoring in food insecure areas of Ethiopia was tested, and promising results were obtained. The output of this research is expected to assist decision makers in taking timely and appropriate action in order to save millions of lives in drought-affected areas

Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences

The geometries and topologies of leaves, flowers, roots, shoots, and their arrangements have fascinated plant biologists and mathematicians alike. As such, plant morphology is inherently mathematical in that it describes plant form and architecture with geometrical and topological techniques. Gaining an understanding of how to modify plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystems is vital to modeling a future with fewer natural resources. In this white paper, we begin with an overview in quantifying the form of plants and mathematical models of patterning in plants. We then explore the fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leaves in air streams. We end with a discussion concerning the education of plant morphology synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics

Effective drought communication : using the past to assess the present and anticipate the future

Especially during drought events, it is important that water gets properly allocated and is not misused or wasted. For an effective drought management, it is thus of utmost importance to raise the awareness of water managers as well as the general public about the drought’s severity. In this paper, we provide two possible sources of information that can be used to communicate about drought events. To illustrate our approach, we make use of drought events that were identified in preceding work as connected components in space and time through the use of operators from the field of mathematical morphology and summarized in terms of characteristics such as affected area, duration and intensity. We demonstrate how these drought characteristics can be used to query for historical drought events that are most similar to an ongoing event, such that lessons learnt from the management of past events can be incorporated in the management of the ongoing event. Further, we also demonstrate how a probabilistic model describing the dependence structure between the drought characteristics is identified and how such model can serve as a basis to estimate the severity of the event. Both approaches provide information that can be used to communicate to laymen about the severity of the ongoing drought, which will help them to anticipate the future

Plant phenomics, from sensors to knowledge

Major improvements in crop yield are needed to keep pace with population growth and climate change. While plant breeding efforts have greatly benefited from advances in genomics, profiling the crop phenome (i.e., the structure and function of plants) associated with allelic variants and environments remains a major technical bottleneck. Here, we review the conceptual and technical challenges facing plant phenomics. We first discuss how, given plants’ high levels of morphological plasticity, crop phenomics presents distinct challenges compared with studies in animals. Next, we present strategies for multi-scale phenomics, and describe how major improvements in imaging, sensor technologies and data analysis are now making high-throughput root, shoot, whole-plant and canopy phenomic studies possible. We then suggest that research in this area is entering a new stage of development, in which phenomic pipelines can help researchers transform large numbers of images and sensor data into knowledge, necessitating novel methods of data handling and modelling. Collectively, these innovations are helping accelerate the selection of the next generation of crops more sustainable and resilient to climate change, and whose benefits promise to scale from physiology to breeding and to deliver real world impact for ongoing global food security efforts

Quantitative Assessment of Water Security Using a Hydrological Modeling Framework

Water scarcity and drought are major threats to water security. Quantifying and defining boundaries between these threats are necessary to properly assess water security of a region. A comprehensive assessment of water security in terms of water scarcity, water vulnerability and drought can address water policy issues related to hydrological conditions and their interactions with societal and ecosystem functioning. Therefore, study of water security can provide useful information to multiple stakeholders. The overarching goal of this thesis is to improve water security in river basins around the world. To demonstrate our proposed methods, we selected Savannah River Basin (SRB) as a case study. In addition to water security assessment of SRB, we also explored the combined as well as individual roles of climate, anthropogenic (e.g., urbanization, agriculture, water demand) and ecological elements on various aspects of water security. Realizing the importance of water security impacts on society and ecosystem, the following objectives are formulated: 1) To investigate the blue and green water security of Savannah River Basin by applying the water footprint concept. 2) To quantify the influence of climate variability and land use change on streamflow, ecosystem services, and water scarcity. 3) To assess the climate, catchment, and morphological variables control over hydrological drought of a river basin. To summarize, the results obtained from first objective shows that our proposed modeling framework can be applied to investigate spatio-temporal pattern of blue and green water footprints as well as water security at a county scale for SRB, thereby locating the emerging hot spots within the river basin. The results obtained from second objective indicate that the land use change and climate variability have a key influence (either concomitant or independent) in altering the blue (green) water and related water security over the basin. The results based on third objective demonstrate that in addition to climate variables, catchment and morphological properties significantly control short, medium and long-term duration of hydrological droughts in SRB. An integrated modeling framework was developed to achieve these objectives and additional findings are explained in detail through the following chapters

A Generalized Density-Based Algorithm for the Spatiotemporal Tracking of Drought Events

Drought events evolve simultaneously in space and time; hence, a proper characterization of an event re-quires the tracking of its full spatiotemporal evolution. Here we present a generalized algorithm for the tracking of drought events based on a three-dimensional application of the DBSCAN (density-based spatial clustering of applications with noise) clustering approach. The need for a generalized and flexible algorithm is dictated by the absence of a unanimous consensus on the definition of a drought event, which often depends on the target of the study. The proposed methodology introduces a set of six parameters that control both the spatial and the temporal connectivity between cells under drought conditions, also accounting for the local intensity of the drought itself. The capability of the algorithm to adapt to different drought definitions is tested successfully over a study case in Australia in the period 2017-20 using a set of standardized precipitation index (SPI) data derived from the ERA5 precipitation reanalysis. Insights on the possible range of variability of the model parameters, as well as on their effects on the delineation of drought events, are provided for the case of mete-orological droughts in order to incentivize further applications of the methodology