scholarly journals Assessment of variability in runoff coefficients and their linkages with physiographic and climatic characteristics of two contrasting catchments

2018 ◽  
Vol 10 (3) ◽  
pp. 464-483 ◽  
Author(s):  
Priyank J. Sharma ◽  
Premlal Patel ◽  
Vinayakam Jothiprakash
Keyword(s):  
Base Flow ◽  
Base Flow Separation ◽  
Hydrogeological Properties ◽  
C Value ◽  
Spatio Temporal ◽  
Annual Water ◽  
Tapi Basin ◽  
Annual Time ◽  
Climatic Characteristics

Abstract In the present study, long-term spatio-temporal variability in runoff coefficient (C) for different drainage areas of Upper Tapi basin, India, is analysed. The Upper Tapi basin is divided into two sub-catchments, Burhanpur and Purna, which are contrasting in nature in terms of their physiographic and climatic characteristics. The digital filter algorithm has been used to separate the base flow from observed streamflow for respective drainage areas. The sensitivity of the parameters involved in base flow separation is assessed by incorporating the hydrological and hydrogeological properties of individual drainage areas. The C values are then computed at different temporal scales, namely, daily, monthly, seasonal and annual, for different drainage areas. The effects of physiographic features such as topography, geology, soil type, and land use; and climatic features such as rainfall, temperature, and evapotranspiration, on the variability of C values are further investigated. The analyses reveal that Burhanpur sub-catchment (C = 0.39) yields higher C value compared to Purna sub-catchment (C = 0.11) at annual time scale. The C values clearly highlight the diversity in response of both sub-catchments, due to their distinct physiographic and climatic characteristics, and enabled us to study the variability in annual water balance of the basin.

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

scholarly journals Climate drivers of plague epidemiology in British India, 1898–1949

2020 ◽  
Vol 287 (1928) ◽  
pp. 20200538
Author(s):  
Warren S. D. Tennant ◽  
Mike J. Tildesley ◽  
Simon E. F. Spencer ◽  
Matt J. Keeling
Keyword(s):  
Predictive Models ◽  
Control Measures ◽  
Climate Data ◽  
British India ◽  
Middle Income ◽  
Middle Income Countries ◽  
Complex Interactions ◽  
The World ◽  
Spatio Temporal

Plague, caused by Yersinia pestis infection, continues to threaten low- and middle-income countries throughout the world. The complex interactions between rodents and fleas with their respective environments challenge our understanding of human plague epidemiology. Historical long-term datasets of reported plague cases offer a unique opportunity to elucidate the effects of climate on plague outbreaks in detail. Here, we analyse monthly plague deaths and climate data from 25 provinces in British India from 1898 to 1949 to generate insights into the influence of temperature, rainfall and humidity on the occurrence, severity and timing of plague outbreaks. We find that moderate relative humidity levels of between 60% and 80% were strongly associated with outbreaks. Using wavelet analysis, we determine that the nationwide spread of plague was driven by changes in humidity, where, on average, a one-month delay in the onset of rising humidity translated into a one-month delay in the timing of plague outbreaks. This work can inform modern spatio-temporal predictive models for the disease and aid in the development of early-warning strategies for the deployment of prophylactic treatments and other control measures.

Seabird bycatch vulnerability in pelagic longline fisheries based on modelling of a long-term dataset

2021 ◽  
pp. 1-16
Author(s):  
CAN ZHOU ◽  
NIGEL BROTHERS
Keyword(s):  
Capture Event ◽  
Retrieval Rate ◽  
Competitive Environments ◽  
Global Concern ◽  
Competitive Species ◽  
Spatio Temporal ◽  
Longline Fisheries ◽  
Pelagic Longline

Summary The incidental mortality of seabirds in fisheries remains a serious global concern. Obtaining unbiased and accurate estimates of bycatch rates is a priority for seabird bycatch mitigation and demographic research. For measuring the capture risk of seabird interactions in fisheries, the rate of carcass retrieval from hauled gear is commonly used. However, reliability can be limited by a lack of direct capture observations and the substantial pre-haul bycatch losses known to occur, meaning incidence of seabird bycatch is underestimated. To solve this problem, a new measure (bycatch vulnerability) that links an observed interaction directly to the underlying capture event is proposed to represent the capture risk of fishery interactions by seabirds. The new measure is not affected by subsequent bycatch loss. To illustrate how to estimate and analyse bycatch vulnerability, a case study based on a long-term dataset of seabird interactions and capture confirmation is provided. Bayesian modelling and hypothesis testing were conducted to identify important bycatch risk factors. Competition was found to play a central role in determining seabird bycatch vulnerability. More competitive environments were riskier for seabirds, and larger and thus more competitive species were more at risk than smaller sized and less competitive species. Species foraging behaviour also played a role. On the other hand, no additional effect of physical oceanic condition and spatio-temporal factors on bycatch vulnerability was detected. Bycatch vulnerability is recommended as a replacement for the commonly used bycatch rate or carcass retrieval rate to measure the capture risk of an interaction. Combined with a normalized contact rate, bycatch vulnerability offers an unbiased estimate of seabird bycatch rate in pelagic longline fisheries.

scholarly journals Spatio-temporal associations of air pollutant concentrations, GP respiratory consultations and respiratory inhaler prescriptions: a 5-year study of primary care in the borough of Lambeth, South London

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Mark Ashworth ◽  
◽  
Antonis Analitis ◽  
David Whitney ◽  
Evangelia Samoli ◽  
...  
Keyword(s):  
Primary Care ◽  
Negative Binomial ◽  
Hospital Admissions ◽  
Air Pollutant ◽  
Respiratory Morbidity ◽  
Short Term ◽  
Short Term Exposure ◽  
Short And Long Term ◽  
Spatio Temporal

Abstract Background Although the associations of outdoor air pollution exposure with mortality and hospital admissions are well established, few previous studies have reported on primary care clinical and prescribing data. We assessed the associations of short and long-term pollutant exposures with General Practitioner respiratory consultations and inhaler prescriptions. Methods Daily primary care data, for 2009–2013, were obtained from Lambeth DataNet (LDN), an anonymised dataset containing coded data from all patients (1.2 million) registered at general practices in Lambeth, an inner-city south London borough. Counts of respiratory consultations and inhaler prescriptions by day and Lower Super Output Area (LSOA) of residence were constructed. We developed models for predicting daily PM2.5, PM10, NO2 and O3 per LSOA. We used spatio-temporal mixed effects zero inflated negative binomial models to investigate the simultaneous short- and long-term effects of exposure to pollutants on the number of events. Results The mean concentrations of NO2, PM10, PM2.5 and O3 over the study period were 50.7, 21.2, 15.6, and 49.9 μg/m3 respectively, with all pollutants except NO2 having much larger temporal rather than spatial variability. Following short-term exposure increases to PM10, NO2 and PM2.5 the number of consultations and inhaler prescriptions were found to increase, especially for PM10 exposure in children which was associated with increases in daily respiratory consultations of 3.4% and inhaler prescriptions of 0.8%, per PM10 interquartile range (IQR) increase. Associations further increased after adjustment for weekly average exposures, rising to 6.1 and 1.2%, respectively, for weekly average PM10 exposure. In contrast, a short-term increase in O3 exposure was associated with decreased number of respiratory consultations. No association was found between long-term exposures to PM10, PM2.5 and NO2 and number of respiratory consultations. Long-term exposure to NO2 was associated with an increase (8%) in preventer inhaler prescriptions only. Conclusions We found increases in the daily number of GP respiratory consultations and inhaler prescriptions following short-term increases in exposure to NO2, PM10 and PM2.5. These associations are more pronounced in children and persist for at least a week. The association with long term exposure to NO2 and preventer inhaler prescriptions indicates likely increased chronic respiratory morbidity.

scholarly journals Towards a hydrological classification of European soils: preliminary test of its predictive power for the base flow index using river discharge data

2007 ◽  
Vol 11 (4) ◽  
pp. 1501-1513 ◽  
Author(s):  
M. K. Schneider ◽  
F. Brunner ◽  
J. M. Hollis ◽  
C. Stamm
Keyword(s):  
Water Movement ◽  
Base Flow ◽  
Regression Coefficients ◽  
Northern Europe ◽  
Flow Index ◽  
Discharge Data ◽  
Base Flow Index ◽  
The Uk

Abstract. Predicting discharge in ungauged catchments or contaminant movement through soil requires knowledge of the distribution and spatial heterogeneity of hydrological soil properties. Because hydrological soil information is not available at a European scale, we reclassified the Soil Geographical Database of Europe (SGDBE) at 1:1 million in a hydrological manner by adopting the Hydrology Of Soil Types (HOST) system developed in the UK. The HOST classification describes dominant pathways of water movement through soil and was related to the base flow index (BFI) of a catchment (the long-term proportion of base flow on total stream flow). In the original UK study, a linear regression of the coverage of HOST classes in a catchment explained 79% of BFI variability. We found that a hydrological soil classification can be built based on the information present in the SGDBE. The reclassified SGDBE and the regression coefficients from the original UK study were used to predict BFIs for 103 catchments spread throughout Europe. The predicted BFI explained around 65% of the variability in measured BFI in catchments in Northern Europe, but the explained variance decreased from North to South. We therefore estimated new regression coefficients from the European discharge data and found that these were qualitatively similar to the original estimates from the UK. This suggests little variation across Europe in the hydrological effect of particular HOST classes, but decreasing influence of soil on BFI towards Southern Europe. Our preliminary study showed that pedological information is useful for characterising soil hydrology within Europe and the long-term discharge regime of catchments in Northern Europe. Based on these results, we draft a roadmap for a refined hydrological classification of European soils.

scholarly journals Imaging spatio-temporal patterns of long-term potentiation in mouse hippocampus

2003 ◽  
Vol 358 (1432) ◽  
pp. 689-693 ◽  
Author(s):  
Toshiyuki Hosokawa ◽  
Masaki Ohta ◽  
Takeshi Saito ◽  
Alan Fine
Keyword(s):  
Hippocampal Slices ◽  
Temporal Patterns ◽  
Long Term Potentiation ◽  
Optical Recording ◽  
Stratum Radiatum ◽  
High Frequency Stimulation ◽  
Optical Signals ◽  
Term Potentiation ◽  
Spatio Temporal

Spatio-temporal patterns of neuronal activity before and after the induction of long-term potentiation in mouse hippocampal slices were studied using a real-time high-resolution optical recording system. After staining the slices with voltage-sensitive dye, transmitted light images and extracellular field potentials were recorded in response to stimuli applied to CA1 stratum radiatum. Optical and electrical signals in response to single test pulses were enhanced for at least 30 minutes after brief high-frequency stimulation at the same site. In two-pathway experiments, potentiation was restricted to the tetanized pathway. The optical signals demonstrated that both the amplitude and area of the synaptic response were increased, in patterns not predictable from the initial, pretetanus, pattern of activation. Optical signals will be useful for investigating spatio-temporal patterns of synaptic enhancement underlying information storage in the brain.

scholarly journals Increasing frequency of low summer precipitation synchronizes dynamics and compromises metapopulation stability in the Glanville fritillary butterfly

2015 ◽  
Vol 282 (1806) ◽  
pp. 20150173 ◽  
Author(s):  
Ayco J. M. Tack ◽  
Tommi Mononen ◽  
Ilkka Hanski
Keyword(s):  
Population Dynamics ◽  
Population Change ◽  
Temporal Dynamics ◽  
Summer Precipitation ◽  
Life History Stage ◽  
General Effect ◽  
Spatial Synchrony ◽  
Glanville Fritillary Butterfly ◽  
Spatio Temporal

Climate change is known to shift species' geographical ranges, phenologies and abundances, but less is known about other population dynamic consequences. Here, we analyse spatio-temporal dynamics of the Glanville fritillary butterfly ( Melitaea cinxia ) in a network of 4000 dry meadows during 21 years. The results demonstrate two strong, related patterns: the amplitude of year-to-year fluctuations in the size of the metapopulation as a whole has increased, though there is no long-term trend in average abundance; and there is a highly significant increase in the level of spatial synchrony in population dynamics. The increased synchrony cannot be explained by increasing within-year spatial correlation in precipitation, the key environmental driver of population change, or in per capita growth rate. On the other hand, the frequency of drought during a critical life-history stage (early larval instars) has increased over the years, which is sufficient to explain the increasing amplitude and the expanding spatial synchrony in metapopulation dynamics. Increased spatial synchrony has the general effect of reducing long-term metapopulation viability even if there is no change in average metapopulation size. This study demonstrates how temporal changes in weather conditions can lead to striking changes in spatio-temporal population dynamics.

Stochastic Models for Actuarial Use: The Equilibrium Modelling of Local Markets

2009 ◽  
Vol 39 (1) ◽  
pp. 339-370 ◽  
Author(s):  
Robert J. Thomson ◽  
Dmitri V. Gott
Keyword(s):  
Local Market ◽  
Market Participants ◽  
Market Portfolio ◽  
One Year ◽  
The One ◽  
Mean Variance ◽  
Annual Time ◽  
Time Subject

AbstractIn this paper, a long-term equilibrium model of a local market is developed. Subject to minor qualifications, the model is arbitrage-free. The variables modelled are the prices of risk-free zero-coupon bonds – both index-linked and conventional – and of equities, as well as the inflation rate. The model is developed in discrete (nominally annual) time, but allowance is made for processes in continuous time subject to continuous rebalancing. It is based on a model of the market portfolio comprising all the above-mentioned asset categories. The risk-free asset is taken to be the one-year index-linked bond. It is assumed that, conditionally upon information at the beginning of a year, market participants have homogeneous expectations with regard to the forthcoming year and make their decisions in mean-variance space. For the purposes of illustration, a descriptive version of the model is developed with reference to UK data. The parameters produced by that process may be used to inform the determination of those required for the use of the model as a predictive model. Illustrative results of simulations of the model are given.

Predicting Human Mobility with Reinforcement-Learning-Based Long-Term Periodicity Modeling

2021 ◽  
Vol 12 (6) ◽  
pp. 1-23
Author(s):  
Shuo Tao ◽  
Jingang Jiang ◽  
Defu Lian ◽  
Kai Zheng ◽  
Enhong Chen
Keyword(s):  
Reinforcement Learning ◽  
Human Mobility ◽  
Recurrent Network ◽  
Mobility Prediction ◽  
Learning Framework ◽  
Temporal Features ◽  
Wide Range ◽  
Spatio Temporal ◽  
Historical Trajectory

Mobility prediction plays an important role in a wide range of location-based applications and services. However, there are three problems in the existing literature: (1) explicit high-order interactions of spatio-temporal features are not systemically modeled; (2) most existing algorithms place attention mechanisms on top of recurrent network, so they can not allow for full parallelism and are inferior to self-attention for capturing long-range dependence; (3) most literature does not make good use of long-term historical information and do not effectively model the long-term periodicity of users. To this end, we propose MoveNet and RLMoveNet. MoveNet is a self-attention-based sequential model, predicting each user’s next destination based on her most recent visits and historical trajectory. MoveNet first introduces a cross-based learning framework for modeling feature interactions. With self-attention on both the most recent visits and historical trajectory, MoveNet can use an attention mechanism to capture the user’s long-term regularity in a more efficient way. Based on MoveNet, to model long-term periodicity more effectively, we add the reinforcement learning layer and named RLMoveNet. RLMoveNet regards the human mobility prediction as a reinforcement learning problem, using the reinforcement learning layer as the regularization part to drive the model to pay attention to the behavior with periodic actions, which can help us make the algorithm more effective. We evaluate both of them with three real-world mobility datasets. MoveNet outperforms the state-of-the-art mobility predictor by around 10% in terms of accuracy, and simultaneously achieves faster convergence and over 4x training speedup. Moreover, RLMoveNet achieves higher prediction accuracy than MoveNet, which proves that modeling periodicity explicitly from the perspective of reinforcement learning is more effective.

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