Linking Ground, Space and Knowledge: The Role of Weather Forecasting in Pastoralists\u27 Decision-Making

Changing weather patterns and decreasing land availability continue to challenge the livelihood of the pastoralists in northern Tanzania. The increasing variability of expected rains has complicated livestock management, often jeopardizing household resilience. Drought Early Warning Systems are being set up to contribute to decision-making processes at national and international levels. Nevertheless, due to the large spatial- and temporal resolution of these systems and their high uncertainties, these systems have limited value at a pastoral household level. Therefore, this paper explores what type of weather and climate information is deemed valuable for pastoral households in Longido District, Tanzania. It is based on an ethnographic study, conducted over a period of four months. It explores what weather information would be useful, the necessary scale of desired information, the required lead time of communication and, lastly, the most effective method of communicating forecast information. Following on this data, the study assessed the status of remote sensing and weather forecast modelling, exploring the question, the desired weather information can be forecast with enough skill and at a scale that is relevant to pastoral households in Longido? The ECMWF weather model was used in the assessment, revealing some optimism and scepticism concerning the status of existing information and technologies. Technological recommendations include verification of rainfall data, further research on the rainfall threshold concept, and exploring the model skill of embedded models in Tanzania. At the level of implementation , recommendations include discussing the adverse impacts of actions taken based on the forecasts and forming an implementation advisory group, which includes a comprehensive breadth of stakeholders, such as knowledgeable community members, village leaders, traditional leaders and also professionals from the field of climate sciences, rangeland ecology and anthropology

Із зали засідань Президії НАН України

На черговому засіданні Президії НАН України 13 червня 2012 року члени Президії НАН України та запрошені заслухали такі питання: Спільне засідання Президії Національної академії наук України та Колегії Державної служби статистики України «Про затвердження проекту програми перепису населення» (доповідачі — заступник голови Держстату України Н.С. Власенко та академік НАН України Е.М. Лібанова); Про наукові підходи до вирішення проблеми збереження та відтворення лісів України (доповідач — член-кореспондент НААН України В.П. Ткач); Про нагородження відзнаками НАН України та Почесними грамотами НАН України і Центрального комітету профспілки працівників НАН України (доповідач — академік НАН України В.Ф. Мачулін); Кадрові та поточні питання

Automated global water mapping based on wide-swath orbital synthetic-aperture radar

This paper presents an automated technique which ingests orbital synthetic-aperture radar (SAR) imagery and outputs surface water maps in near real time and on a global scale. The service anticipates future open data dissemination of water extent information using the European Space Agency's Sentinel-1 data. The classification methods used are innovative and practical and automatically calibrated to local conditions per 1 × 1° tile. For each tile, a probability distribution function in the range between being covered with water or being dry is established based on a long-term SAR training dataset. These probability distributions are conditional on the backscatter and the incidence angle. In classification mode, the probability of water coverage per pixel of 1 km × 1 km is calculated with the input of the current backscatter – incidence angle combination. The overlap between the probability distributions of a pixel being wet or dry is used as a proxy for the quality of our classification. The service has multiple uses, e.g. for water body dynamics in times of drought or for urgent inundation extent determination during floods. The service generates data systematically: it is not an on-demand service activated only for emergency response, but instead is always up-to-date and available. We validate its use in flood situations using Envisat ASAR information during the 2011 Thailand floods and the Pakistan 2010 floods and perform a first merge with a NASA near real time water product based on MODIS optical satellite imagery. This merge shows good agreement between these independent satellite-based water products

Influence of soil and climate on root zone storage capacity

Root zone storage capacity (Sr) is an important variable for hydrology and climate studies, as it strongly influences the hydrological functioning of a catchment and, via evaporation, the local climate. Despite its importance, it remains difficult to obtain a wellâ founded catchment representative estimate. This study tests the hypothesis that vegetation adapts its Sr to create a buffer large enough to sustain the plant during drought conditions of a certain critical strength (with a certain probability of exceedance). Following this method, Sr can be estimated from precipitation and evaporative demand data. The results of this â climateâ based methodâ are compared with traditional estimates from soil data for 32 catchments in New Zealand. The results show that the differences between catchments in climateâ derived catchment representative Sr values are larger than for soilâ derived Sr values. Using a model experiment, we show that the climateâ derived Sr can better reproduce hydrological regime signatures for humid catchments; for more arid catchments, the soil and climate methods perform similarly. This makes the climateâ based Sr a valuable addition for increasing hydrological understanding and reducing hydrological model uncertainty.Key Points:Plants develop their root systems to survive droughtsModel root zone storage capacity (Sr) can be inferred from climate recordsModel experiment shows that Sr is stronger influenced by climate than by soilPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137190/1/wrcr21890.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137190/2/wrcr21890_am.pd

Advancing catchment hydrology to deal with predictions under change

Throughout its historical development, hydrology as an earth science, but especially as a problem-centred engineering discipline has largely relied (quite successfully) on the assumption of stationarity. This includes assuming time invariance of boundary conditions such as climate, system configurations such as land use, topography and morphology, and dynamics such as flow regimes and flood recurrence at different spatio-temporal aggregation scales. The justification for this assumption was often that when compared with the temporal, spatial, or topical extent of the questions posed to hydrology, such conditions could indeed be considered stationary, and therefore the neglect of certain long-term non-stationarities or feedback effects (even if they were known) would not introduce a large error. However, over time two closely related phenomena emerged that have increasingly reduced the general applicability of the stationarity concept: the first is the rapid and extensive global changes in many parts of the hydrological cycle, changing formerly stationary systems to transient ones. The second is that the questions posed to hydrology have become increasingly more complex, requiring the joint consideration of increasingly more (sub-) systems and their interactions across more and longer timescales, which limits the applicability of stationarity assumptions. Therefore, the applicability of hydrological concepts based on stationarity has diminished at the same rate as the complexity of the hydrological problems we are confronted with and the transient nature of the hydrological systems we are dealing with has increased. The aim of this paper is to present and discuss potentially helpful paradigms and theories that should be considered as we seek to better understand complex hydrological systems under change. For the sake of brevity we focus on catchment hydrology. We begin with a discussion of the general nature of explanation in hydrology and briefly review the history of catchment hydrology. We then propose and discuss several perspectives on catchments: as complex dynamical systems, self-organizing systems, co-evolving systems and open dissipative thermodynamic systems. We discuss the benefits of comparative hydrology and of taking an information-theoretic view of catchments, including the flow of information from data to models to predictions. In summary, we suggest that these perspectives deserve closer attention and that their synergistic combination can advance catchment hydrology to address questions of change

A globally applicable framework for compound flood hazard modeling

Coastal river deltas are susceptible to flooding from pluvial, fluvial, and coastal flood drivers. Compound floods, which result from the co-occurrence of two or more of these drivers, typically exacerbate impacts compared to floods from a single driver. While several global flood models have been developed, these do not account for compound flooding. Local-scale compound flood models provide state-of-the-art analyses but are hard to scale to other regions as these typically are based on local datasets. Hence, there is a need for globally applicable compound flood hazard modeling. We develop, validate, and apply a framework for compound flood hazard modeling that accounts for interactions between all drivers. It consists of the high-resolution 2D hydrodynamic Super-Fast INundation of CoastS (SFINCS) model, which is automatically set up from global datasets and coupled with a global hydrodynamic river routing model and a global surge and tide model. To test the framework, we simulate two historical compound flood events, Tropical Cyclone Idai and Tropical Cyclone Eloise in the Sofala province of Mozambique, and compare the simulated flood extents to satellite-derived extents on multiple days for both events. Compared to the global CaMa-Flood model, the globally applicable model generally performs better in terms of the critical success index (−0.01–0.09) and hit rate (0.11–0.22) but worse in terms of the false-alarm ratio (0.04–0.14). Furthermore, the simulated flood depth maps are more realistic due to better floodplain connectivity and provide a more comprehensive picture as direct coastal flooding and pluvial flooding are simulated. Using the new framework, we determine the dominant flood drivers and transition zones between flood drivers. These vary significantly between both events because of differences in the magnitude of and time lag between the flood drivers. We argue that a wide range of plausible events should be investigated to obtain a robust understanding of compound flood interactions, which is important to understand for flood adaptation, preparedness, and response. As the model setup and coupling is automated, reproducible, and globally applicable, the presented framework is a promising step forward towards large-scale compound flood hazard modeling.</p

How much do we really know about river flooding?

Have you ever experienced rain where it rained so hard or for so long that you feared you may soon be up to your eyeballs in water? Sadly, many people in the world have witnessed this firsthand, and this is likely to increase due to climate change unless we do something to prepare for flooding disasters. Some areas are more prone to floods than others, and the people living there are more at risk. Scientists have developed computer models in an effort to map flood prone areas. Decision makers use the results from those computer models to plan for future flooding events to limit destruction and save lives. But are they accurate enough considering human lives may depend on them? To answer this question we compared the results from six computer models which simulate flood risk in Africa. The models agreed in less than 40% of the cases about where exactly it would flood and how much damage there might be

Hyperresolution information and hyperresolution ignorance in modelling the hydrology of the land surface

There is a strong drive towards hyperresolution earth system models in order to resolve finer scales of motion in the atmosphere. The problem of obtaining more realistic representation of terrestrial fluxes of heat and water, however, is not just a problem of moving to hyperresolution grid scales. It is much more a question of a lack of knowledge about the parameterisation of processes at whatever grid scale is being used for a wider modelling problem. Hyperresolution grid scales cannot alone solve the problem of this hyperresolution ignorance. This paper discusses these issues in more detail with specific reference to land surface parameterisations and flood inundation models. The importance of making local hyperresolution model predictions available for evaluation by local stakeholders is stressed. It is expected that this will be a major driving force for improving model performance in the future. Keith BEVEN, Hannah CLOKE, Florian PAPPENBERGER, Rob LAMB, Neil HUNTE