Status of climate and water resources at Saguaro National Park: Water year 2019

Climate and hydrology are major drivers of ecosystems. They dramatically shape ecosystem structure and function, particularly in arid and semi-arid ecosystems. Understanding changes in climate, groundwater, and water quality and quantity is central to assessing the condition of park biota and key cultural resources. The Sonoran Desert Network collects data on climate, groundwater, and surface water at 11 National Park Service units in south-ern Arizona and New Mexico. This report provides an integrated look at climate, groundwater, and springs conditions at Saguaro National Park (NP) during water year 2019 (October 2018–September 2019). Annual rainfall in the Rincon Mountain District was 27.36" (69.49 cm) at the Mica Mountain RAWS station and 12.89" (32.74 cm) at the Desert Research Learning Center Davis station. February was the wettest month, accounting for nearly one-quarter of the annual rainfall at both stations. Each station recorded extreme precipitation events (>1") on three days. Mean monthly maximum and minimum air temperatures were 25.6°F (-3.6°C) and 78.1°F (25.6°C), respectively, at the Mica Mountain station, and 37.7°F (3.2°C) and 102.3°F (39.1°C), respectively, at the Desert Research Learning Center station. Overall temperatures in WY2019 were cooler than the mean for the entire record. The reconnaissance drought index for the Mica Mountain station indicated wetter conditions than average in WY2019. Both of the park’s NOAA COOP stations (one in each district) had large data gaps, partially due to the 35-day federal government shutdown in December and January. For this reason, climate conditions for the Tucson Mountain District are not reported. The mean groundwater level at well WSW-1 in WY2019 was higher than the mean for WY2018. The water level has generally been increasing since 2005, reflecting the continued aquifer recovery since the Central Avra Valley Storage and Recovery Project came online, recharging Central Arizona Project water. Water levels at the Red Hills well generally de-clined starting in fall WY2019, continuing through spring. Monsoon storms led to rapid water level increases. Peak water level occurred on September 18. The Madrona Pack Base well water level in WY2019 remained above 10 feet (3.05 m) below measuring point (bmp) in the fall and winter, followed by a steep decline starting in May and continuing until the end of September, when the water level rebounded following a three-day rain event. The high-est water level was recorded on February 15. Median water levels in the wells in the middle reach of Rincon Creek in WY2019 were higher than the medians for WY2018 (+0.18–0.68 ft/0.05–0.21 m), but still generally lower than 6.6 feet (2 m) bgs, the mean depth-to-water required to sustain juvenile cottonwood and willow trees. RC-7 was dry in June–September, and RC-4 was dry in only September. RC-5, RC-6 and Well 633106 did not go dry, and varied approximately 3–4 feet (1 m). Eleven springs were monitored in the Rincon Mountain District in WY2019. Most springs had relatively few indications of anthropogenic or natural disturbance. Anthropogenic disturbance included spring boxes or other modifications to flow. Examples of natural disturbance included game trails and scat. In addition, several sites exhibited slight disturbance from fires (e.g., burned woody debris and adjacent fire-scarred trees) and evidence of high-flow events. Crews observed 1–7 taxa of facultative/obligate wetland plants and 0–3 invasive non-native species at each spring. Across the springs, crews observed four non-native plant species: rose natal grass (Melinis repens), Kentucky bluegrass (Poa pratensis), crimson fountaingrass (Cenchrus setaceus), and red brome (Bromus rubens). Baseline data on water quality and chemistry were collected at all springs. It is likely that that all springs had surface water for at least some part of WY2019. However, temperature sensors to estimate surface water persistence failed...

Intercomparison of thermal–optical carbon measurements by Sunset and Desert Research Institute (DRI) analyzers using the IMPROVE_A protocol

Thermal–optical analysis (TOA) is a class of methods widely used for determining organic carbon (OC) and elemental carbon (EC) in atmospheric aerosols collected on filters. Results from TOA vary not only with differences in operating protocols for the analysis, but also with details of the instrumentation with which a given protocol is carried out. Three models of TOA carbon analyzers have been used for the IMPROVE_A protocol in the past decade within the Chemical Speciation Network (CSN). This study presents results from intercomparisons of these three analyzer models using two sets of CSN quartz filter samples, all analyzed using the IMPROVE_A protocol with reflectance charring correction. One comparison was between the Sunset model 5L (Sunset) analyzers and the Desert Research Institute (DRI) model 2015 (DRI-2015) analyzers using 4073 CSN samples collected in 2017. The other comparison was between the Sunset and the DRI model 2001 (DRI-2001) analyzers using 303 CSN samples collected in 2007. Both comparisons showed a high degree of inter-model consistency in total carbon (TC) and the major carbon fractions, OC and EC, with a mean bias within 5 % for TC and OC and within 12 % for EC. Relatively larger and diverse inter-model discrepancies (mean biases of 5 %–140 %) were found for thermal subfractions of OC and EC (i.e., OC1–OC4 and EC1–EC3), with better agreement observed for subfractions with higher mass loadings and smaller within-model uncertainties. Optical charring correction proved critical in bringing OC and EC measurements by different TOA analyzer models into agreement. Appreciable inter-model differences in EC between Sunset and DRI-2015 (mean bias ±SD of 21.7 %±12.2 %) remained for ∼5 % of the 2017 CSN samples; examination of these analysis thermograms revealed that the optical measurement (i.e., filter reflectance and transmittance) saturated in the presence of strong absorbing materials on the filter (e.g., EC), leaving an insufficient dynamic range for the detection of carbon pyrolysis and thus no optical charring correction. Differences in instrument parameters and configuration, possibly related to disagreement in OC and EC subfractions, are also discussed. Our results provide a basis for future studies of uncertainties associated with the TOA analyzer model transition in assessing long-term trends of CSN carbon data. Further investigations using these data are warranted, focusing on the demonstrated inter-model differences in OC and EC subfractions. The within- and inter-model uncertainties are useful for model performance evaluation.

Comparación de Índices de Vegetación con imágenes Landsat usando la computación en la nube: zona Pampa de Majes-Siguas, Arequipa Perú (Periodo: Jun 1984 a Nov 2018)

El objetivo del presente trabajo fue la obtención de índices de vegetación usando las imágenes satelitales Landsat en el tope de la atmosfera (TOA). La extensión de inuencia del Proyecto Especial Autoridad del Majes (AUTODEMA), que abarca las Pampas de Majes - Siguas, en Arequipa - Perú, desde 1984 hasta 2018. Para lo cual se hizo uso de la aplicación de computación en la nube ClimateEngine en la base de datos de Google Earth Engine (GEE), a escala Petabyte (PB). Se usó la herramienta llamada Climate Engine desarrollada por investigadores de la Universidad de Idaho y Desert Research Institute - DRI. Permitiendo el procesamiento vía web las imágenes satelitalesde la Misión Landsat, extraer valores de las diversas bandas, dentro de un grillado, para poder determinar los Índices de Vegetación tales como NDVI, NDWI, SAVI, GNDVI, obteniendo una serie de tiempo dentro delaextensión de estudio del AUTODEMA y poder estimar la cantidad y el grado de desarrollo de las especies vegetalessembradas y su impacto en el uso del agua mediante transvase desde la cuenca del rio Camaná hacia las Pampas de Majes-Siguas, ampliando la frontera agrícola.

Additions to the “Martian Flora”: new botanical records from the Mars Desert Research Station, Utah

The Mars Desert Research Station (MDRS) is a Mars-simulation campus set in a Martian planetary analogue in southern Utah. Despite a long history of astrobiology research, collections-based taxonomic inventories of the macro-level biodiversity around the station are relatively new. This study serves to add to the initial vascular plant list published for the station in 2016, where 39 species were recorded for MDRS. Here we report 40 new species, two new taxa recorded only to genus and two species re-identified from our 2016 fieldwork, bringing the total number of taxa in the "Martian" flora to 79 species and two taxa recorded to genus.

Determinación del Relieve 3D de la Superficie de Marte usando un UAV

Determinación del Relieve 3D de la Superficie de Marte usando un UAV Mars Surface 3D relief using a UAV Drone, UAV, Marte, relieve 3D, procesamiento de imagen, fotogrametría. Universidad Tecnológica del Perú, Lima 001 DOI: https://doi.org/10.33017/RevECIPeru2015.0005/ Resumen En este artículo se presenta el desarrollo de un UAV (Quadcopter) para la determinación del relieve en 3D de la superficie del planeta Marte, el propósito de esta investigación es proveer una herramienta moderna y confiable a los tripulantes en futuras exploraciones espaciales, los cuales tendrán la oportunidad de enviar al equipo para realizar el reconocimiento y mapeo de un área específica. El objetivo del desarrollo de este dispositivo es asegurar la integridad física de las personas en cualquier misión de investigación y exploración de lugares desconocidos, ya que podrá ser monitoreado remotamente y brindar información relevante previa a la exploración humana lo que dará una mejor visión del terreno a investigar. Este proyecto fue desarrollado en el programa de experimentación y simulación en el MDRS (Mars Desert Research Station) organizado por The Mars Society, estación ubicada en el desierto de Utah, Estados Unidos, en este lugar se desarrolló también la simulación de supervivencia marciana. El desarrollo del equipo constó de dos etapas principales, la primera parte se enfocó en el análisis de hardware y software para el Quadcopter, se seleccionaron las diferentes piezas, el frame principal y los parámetros de control para un vuelo estable, la segunda parte se orientó a la creación del algoritmo para el procesamiento de las imágenes y la determinación del relieve en 3D, todo ello desarrollado en Matlab. En la estación de investigación MDRS se desarrollaron las simulaciones, pruebas de vuelo y toma de datos. El Quadcopter puede ser piloteado usando un control remoto para mapear diversas zonas, además de ello, gracias al GPS con el que cuenta, tiene la capacidad de establecer puntos en el aire para realizar un recorrido predeterminado y mapear una región definida. El principio que se emplea en el procesamiento de imágenes es la fotogrametría, la cual emplea fotografías digitales, mediante las cuales se realiza un reconocimiento de patrones y puntos de referencia para poder determinar la superficie fotografiada en 3D. Una cámara GoPro fue utilizada para la recolección de imágenes ya que brinda fotografías de buena calidad además de ser resistente a ambientes adversos como el polvo y a humedad. Las zonas contiguas a la estación en el Desierto de Utah fueron los lugares de experimentación, lo cual sirvió para poder calibrar los parámetros de control de vuelo del Quadcopter y los del algoritmo para el procesamiento de imágenes en Matlab. Los resultados obtenidos durante las primeras pruebas fueron óptimos, lo que demuestra que los métodos utilizados son los adecuados, pero aún no se han alcanzado resultados precisos, ya que se tiene un porcentaje de error mayor al esperado. Actualmente se viene trabajando en el mejoramiento del hardware del Quadcopter y en el programa de procesamiento de imágenes para obtener mejores resultados. Este trabajo es un aporte a la literatura científica en el área de exploración espacial, ya que este tema no ha sido muy desarrollado, se espera que esta investigación sirva como base para el desarrollo de nuevos aparatos relacionados a este contenido. Palabras clave: Drone, UAV, Marte, relieve 3D, procesamiento de imagen, fotogrametría. Abstract In this article its presented the development of an UAV (Quadcopter) about 3D relief obtainment of Mars surface, the purpose of the research it to provide a modern and reliable tool to crewmembers on future space explorations, which will have the opportunity of send this machine to perform recognizing and mapping mission of an specific area. The main objective about the development of this device is to ensure the phisic integrity of people in any research mission or exploration mission of unknown places. It could be driven remotely and receive precise relevant information previously to the human exploration, which give a better vision of the researched area. This project was developed in the simulation program at MDRS (Mars Desert Research Station) organized by The Mars Society, the station is located in Utah desert in the USA. In that place was performed the simulation of mars survival. The development of the entire project consisted into two main stages, the first part was focused on hardware and software analysis of the Quadcopter. It was selected the main components, main frame and control parameters for a stable flight. The second part was oriented to the creation of an image processing algorithm and 3D relief obtaining, which was built on Matlab. On the Research Station the simulations, flight proofs and data collection were performed. The Quadcopter could be operated using a remote controller for mapping many zones, also it is provided of a GPS unit, which allow to set points in the air and follow a given range recording a defined region. The principle used in image processing is called photogrammetry, which use digital photos. Then, patterns and reference points are recognized to define the photographed surface into a 3D model. A GoPro camera was used to get pictures because this kind of devices are very resistant to dust and humidity also it gives high quality photos, important for the subsequent analysis. Close places to the station in the Utah desert were experimentation places. It helped to calibrate control flight parameters of quadcopter and image processing parameters on Matlab. Reached results during first tests were optimum, which demonstrate that methods used are correct, but precise results haven’t reached yet, because there is an average error percentage. Currently it’s been working on the improvement of the Quadcopter hardware and in the image processing program to get better results. This work is a contribution to the scientific literature in the space exploration field. This specific topic was not well developed, so it’s hoped that it serve as base for many new projects and the development of innovative devices related to this. Keywords: Drone, UAV, Mars, 3D relief, image processing, photogrammetry.