From drought to flood: A water balance analysis of the Tuolumne River basin during extreme conditions (2015–2017)

The degree to which the hydrologic water balance in a snow-dominated headwater catchment is affected by annual climate variations is difficult to quantify, primarily due to uncertainties in measuring precipitation inputs and evapotranspiration (ET) losses. Over a recent three-year period, the snowpack in California's Sierra Nevada fluctuated from the lightest in recorded history (2015) to historically heaviest (2017), with a relatively average year in between (2016). This large dynamic range in climatic conditions presents a unique opportunity to investigate correlations between annual water availability and runoff in a snow-dominated catchment. Here, we estimate ET using a water balance approach where the water inputs to the system are spatially constrained using a combination of remote sensing, physically based modelling, and in-situ observations. For all 3 years of this study, the NASA Airborne Snow Observatory (ASO) combined periodic high-resolution snow depths from airborne Lidar with snow density estimates from an energy and mass balance model to produce spatial estimates of snow water equivalent over the Tuolumne headwater catchment at 50-m resolution. Using observed reservoir inflow at the basin outlet and the well-quantified snowmelt model results that benefit from periodic ASO snow depth updates, we estimate annual ET, runoff efficiency (RE), and the associated uncertainty across these three dissimilar water years. Throughout the study period, estimated annual ET magnitudes remained steady (222 mm in 2015, 151 mm in 2016, and 299 mm in 2017) relative to the large differences in basin input precipitation (547 mm in 2015, 1,060 mm in 2016, and 2,211 mm in 2017). These values compare well with independent satellite-derived ET estimates and previously published studies in this basin. Results reveal that ET in the Tuolumne does not scale linearly with the amount of available water to the basin, and that RE primarily depends on total annual snowfall proportion of precipitation.     

Assessment of Geogenic and Anthropogenic Pollution Sources Using an Aquatic Plant Along the Sonora River Basin: Insights from Elemental Concentrations and Pb Isotope Signatures

Natural Resources Research - Mining is an important activity in Mexico; however, despite its economic benefits, it carries potential environmental risks, including mine spills. On August 6,...     

Notes on fossil remains from the Early Cretaceous Lohan Cura Formation, Neuquén Province, Argentina

In this contribution, we describe an association of fossil remains collected in the locality of Cerro de Los Leones, approximately 8 km southwest of the town of Picún Leufú, Neuquén Province, Argentina, from different levels of the Albian Cullín Grande Member, Lohan Cura Formation. The fossils include pelecypodan (Neocorbicula dinosauriorum, Neocorbicula pehuenchensis, and genus indet.) and gastropodan (Physa wichmanni) molluscs, a mesoeucrocodylian, possible pterosaurs, theropods, and sauropods. The sedimentary environment at Cerro de los Leones is characterized by fluvial deposits corresponding to a sandy meandering fluvial system. The most fossiliferous levels (located in the lower part of the exposed sequence) were developed in a distal flood plain and flood basin areas. Sedimentological and paleopedological features suggest semi-arid conditions during the deposition of the Cullín Grande Member. Despite the fragmentary nature of the specimens described here, the new information provided from the Albian assemblages of the Lohan Cura Formation at the Cerro de Los Leones locality provides a broader panorama of the composition of terrestrial faunas during the Early Cretaceous in Patagonia.     

Invariant sets and polhodes in the rigid body problem

In this work we will describe the sets in the rigid body phase space where the energy and angular momentum are constant, and it will turn out that in nontrivial cases they will simply take the form of cartesian products of the polhodes byS ¹. These sets are important for the global study of said geodesic mechanical system for being invariant under Euler's equations (energy and momentum are constant along their solutions).To motivate from something more familiar in celestial mechanics, we will begin to relate the problem to Smale's study of the planarn-body problem (Smale, 1970) and Easton's study of the planar 3-body problem (Easton, 1971), exemplifying in particular with the central force problem.In the last Sections 4 and 5, we extent our methods to give results for generalized solids on Lie groups, mentioning the further extensions to transitive mechanical systems.Proceedings of the Sixth Conference on Mathematical Methods in Celestial Mechanics held at Oberwolfach (West Germany) from 14 to 19 August, 1978.This work was partially supported by the Consejo Nacional de Ciencia y Tecnología (México) under grant PNCB-049.     

Simulated Urban Climate Response to Historical Land Use Modification in the Basin of Mexico

Numerical simulations of thermal field variation due to land use changes, such as the reduction of the lacustrine system and the growth of the urban area, in the Basin of Mexico are presented. It is shown that the historically recorded warming in the basin could be attributed, not only to the growth of the urban area, but more importantly to the drastic reduction in the lacustrine system that existed in the basin.     

Caribbean hurricanes: interannual variability and prediction

Climatic conditions that affect the interannual variability of Caribbean hurricanes are studied. Composite meteorological and oceanographic reanalysis fields are constructed for active and inactive seasons since 1979, and differences are calculated for spring and summer periods to provide guidance in statistical analysis. Predictors are extracted for areas exhibiting high contrast between active and inactive seasons, and intercomparisons are made. Zonal winds north of Venezuela exhibit westerly anomalies prior to active years, so coastal upwelling and the north Brazil current are diminished. Rainfall increases in the Orinoco River basin, creating a fresh warm plume north of Trinidad. The predictor time series are regressed onto an index of Caribbean hurricanes, and multivariate algorithms are formulated. It is found that atmospheric kinematic and convective predictors explain only ??20% of hurricane variance at 3?C5-month lead time. Subsurface ocean predictors offer higher levels of explained hurricane variance (42%) at 3?C5-month lead time, using 1?C200-m-depth-averaged temperatures in the east Pacific and southern Caribbean. We place the statistical results in a conceptual framework to better understand climatic processes anticipating Caribbean hurricanes.     

Estimating net radiation at surface using artificial neural networks: a new approach

This study describes the results of artificial neural network (ANN) models to estimate net radiation (R _n), at surface. Three ANN models were developed based on meteorological data such as wind velocity and direction, surface and air temperature, relative humidity, and soil moisture and temperature. A comparison has been made between the R _n estimates provided by the neural models and two linear models (LM) that need solar incoming shortwave radiation measurements as input parameter. Both ANN and LM results were tested against in situ measured R _n. For the LM ones, the estimations showed a root mean square error (RMSE) between 34.10 and 39.48?W?m^?2 and correlation coefficient (R ²) between 0.96 and 0.97 considering both the developing and the testing phases of calculations. The estimates obtained by the ANN models showed RMSEs between 6.54 and 48.75?W?m^?2 and R ² between 0.92 and 0.98 considering both the training and the testing phases. The ANN estimates are shown to be similar or even better, in some cases, than those given by the LMs. According to the authors?? knowledge, the use of ANNs to estimate R _n has not been discussed earlier, and based on the results obtained, it represents a formidable potential tool for R _n prediction using commonly measured meteorological parameters.