An Algebra for Spatiotemporal Data: From Observations to Events

Recent technological advances in geospatial data gathering have created massive data sets with better spatial and temporal resolution than ever before. These large spatiotemporal data sets have motivated a challenge for Geoinformatics: how to model changes and design good quality software. Many existing spatiotemporal data models represent how objects and fields evolve over time. However, to properly capture changes, it is also necessary to describe events. As a contribution to this research, this article presents an algebra for spatiotemporal data. Algebras give formal specifications at a high‐level abstraction, independently of programming languages. This helps to develop reliable and expressive applications. Our algebra specifies three data types as generic abstractions built on real‐world observations: time series, trajectory and coverage. Based on these abstractions, it defines object and event types. The proposed data types and functions can model and capture changes in a large range of applications, including location‐based services, environmental monitoring, public health, and natural disasters.     

Climate change in the Paraná state,Brazil: responses to increasing atmospheric CO 2 in reference evapotranspiration

The hydrological variable evapotranspiration (ET) is challenging to estimate because it cannot be measured directly in natural environments (except in small plots). The uncertainties associated with the models used for its prediction have increased under climate change conditions. We studied the influence of stomatal resistance on ET estimates using the Penman-Monteith method as projected by three general circulation models in two emission scenarios (RCP4.5 and RCP8.5) for future climates throughout the twenty-first century (2010–2039, 2040–2069, and 2070–2099). We also investigated the probable ET rate changes in relation to the current (30 years average, 1980–2009) climate conditions for the Paraná state in the southern region of Brazil. The results were regionalized to help policymakers assess climate change impacts and design adaptation measures. ET increases of up to 15% were found in future climate conditions, which may lead to a significant increase in the water demand for agricultural crops. However, we believe that plant morphophysiological changes may occur under atmospheric CO2 enrichment conditions and that a possible reduction in stomatal conductance will result in lower ET increases than those obtained with the traditional Penman-Monteith method. When considering future climate scenarios, we propose the equation be adjusted to consider stomatal resistance as a function of CO2 concentrations.     

Impact of spatial correlation of ground motions on seismic damage for residential buildings in Bucharest,Romania

Natural Hazards - This paper focuses on the investigation of seismic risk for residential buildings situated in Bucharest, the capital city of Romania. With a population of nearly 2 million...     

Non-ENSO interannual rainfall variability in central Chile during austral winter

The first principal component (PC1) of seasonal rainfall anomalies in central Chile during winter (June–August) is used to analyze the circulation anomalies related to wet and dry conditions, when near-normal or neutral SST anomalies are observed in the equatorial Pacific, i.e., during non-ENSO conditions. Eight wet and eight dry winter seasons were defined as the upper and lower terciles of PC1 for 24 non-ENSO winters in the period 1958–2000. Unlike the single process attributed to ENSO, during non-ENSO winter seasons, there are several sources triggering or modifying the propagation of the stationary waves that impact the rainfall regime in central Chile. Unfortunately, the multiple processes that seem to be involved in the modulation of the interannual rainfall variability in central Chile, as seen in this work, limit the predictability of rainfall during non-ENSO conditions.     

Parameter identification of minifrac numerical tests using a gradient boosting-based proxy model and genetic algorithm

In recent years, the petroleum industry has devoted considerable attention to studying fluid flow inside fracture channels due to the discovery of naturally fractured reservoirs. The behavior prediction of these reservoirs is a well-known challenging task, in which the initial stage consists of identifying reservoir hydromechanical parameters. This work proposes an artificial intelligence-based approach to identify hydromechanical parameters from borehole injection pressure curves acquired through minifrac tests. This approach combines proxy modeling with a stochastic optimization algorithm to match observed and predicted borehole pressure curves. Therefore, a gradient boosting-based proxy model is built to predict borehole pressure curves, considering a proper strategy to develop time series modeling. Moreover, a Bayesian optimization algorithm is applied to compute the gradient boosting hyperparameters. In this optimization scenario, this paper proposes an appropriate objective function established from the assumed time series prediction strategy and the k-fold cross-validation. Finally, a genetic algorithm is adopted to identify unknown hydromechanical parameters, solving an inverse problem. Based on the proposed workflow, a study of the importance of the hydromechanical parameters is developed. To assess the methodology applicability, the approach is employed to identify parameters in synthetic and field minifrac tests. The results present how this approach can adequately identify hydromechanical parameters of hydraulic fracturing problems.     

Glacial oscillations during the Bølling–Allerød Interstadial–Younger Dryas transition in the Ruda Valley,Central Pyrenees

The Upper Garonne Basin included the largest glacial system in the Pyrenees during the last glacial cycle. Within the long-term glacial retreat during Termination-1 (T-1), glacier fluctuations left geomorphic evidence in the area. However, the chronology of T-1 glacial oscillations on the northern slopes of the Central Pyrenees is still poorly constrained. Here, we introduce new geomorphological observations and a 12-sample dataset of ¹⁰Be cosmic-ray exposure ages from the Ruda Valley. This U-shaped valley, surrounded by peaks exceeding 2800 m a.s.l., includes a sequence of moraines and polished surfaces that enabled a reconstruction of the chronology of the last deglaciation. Following the maximum ice extent, warmer conditions prevailing at ~15–14 ka, during the Bølling–Allerød (B–A) Interstadial, favoured glacial retreat in the Ruda Valley. Within the B–A, glaciers experienced two phases of advance/stillstand with moraine formation at 13.5 and 13.0 ka. During the early Younger Dryas (YD), glacial retreat exposed the highest surfaces of the Saboredo Cirque (~2300–2350 m) at 12.7 ka. Small glaciers persisted only inside the highest cirques (~2470 m), such as in Sendrosa Cirque, with moraines stabilising at 12.6 ka. The results of this work present the most complete chronology for Pyrenean glacial oscillations from the B–A to the YD.