Mars Global Surveyor (MGS) orbiter observed a planet-encircling dust storm (PDS) in Mars year (MY) 25 from Ls=176.2-263.4°. We present an examination of Mars Orbiter Camera (MOC) dust storms and transient baroclinic eddies identified from Fast Fourier Synoptic Mapping (FFSM) of Thermal Emission Spectrometer (TES) temperatures for the first two phases of the storm: precursor, Ls=176.2- 184.7°, and expansion, Ls=184.7-193°. FFSM analysis of TES 3.7 hPa thermal data shows the presence of eastward traveling waves at 60° S with a period of about three sols. We hypothesize that these waves are transient baroclinic eddies that contributed to the initiation of precursor storms near Hellas. Integration of FFSM and MOC MY 24, 25, and 26 data shows interesting temporal and spatial associations between the evolution of eddies and storms, including: 1) comparable periodicities of travelling waves and pulses of storm activity, and 2) concurrent eastward propagation of both eddies and storms. These results suggest a causal relationship between baroclinic eddies and local storm initiation. Based on our analysis of these MGS data, we propose the following working hypothesis to explain the dynamical processes responsible for PDS initiation and expansion. Six eastward-traveling transient baroclinic eddies triggered the MY 25 precursor storms in Hellas during Ls=176.2–184.6° due to the enhanced dust lifting associated with their low-level wind and stress fields. This was followed by a seventh eddy that contributed to expansion on Ls=186.3°. Increased opacity and temperatures from dust lifting associated with the first three eddies enhanced thermal tides which supported further storm initiation and expansion out of Hellas. Constructive interference of eddies and other circulation components including sublimation flow, anabatic winds (daytime upslope), and diurnal tides may have contributed to storm onset in, and expansion out of Hellas.

Geochemical analyses applied to lake sedimentary records can reveal the history of pollution by metals and the effects of remedial efforts. Lakes provide ideal environments for geochemical studies because they have steady deposition of fine grained material suitable for fixation of pollutants. The Laurentian Great Lakes are the most studied system in this field and they have well-preserved chronological profiles. To date this important system has been considered in parts, hampering basin-wide conclusions regarding metal contamination. Therefore, we synthesized all relevant literature to create a central understanding of geochemical research to date in the Great Lakes. We also filled spatial and temporal gaps in a comprehensive geochemical analysis of 11 sediment cores collected from all five Great Lakes. Hierarchical cluster analysis of all Great Lakes samples divided the metal analytes into five functional groups: (1) carbonate elements; (2) metals and oxides with diverse natural sources, including a subgroup of analytes known to be anthropogenically enriched (Cd, Pb, Sn, Zn, and Sb); (3) common crustal elements; (4) metals related to coal and nuclear power generation; and (5) all of the rare earth elements. Two contamination indices (Igeo and EF) applied to sedimentary metals indicated that Na, Co, Mn, Cd, Pb, Ta, and Cu were the most enriched metal pollutants in this system, at some point during the Anthropocene. Land uses correlated with the metal analytes, such as increases in contaminant metals with the rise in catchment population and increases in carbonate elements (e.g. Ca) with agriculture. Certain contamination trends were observed basin-wide, such as for the atmospheric pollutant Pb, which followed a rise associated with fossil fuel combustion and a decline following the ban of leaded gasoline. Other trends were lake-specific such as recent high concentrations of Na in Lake Superior due to road salt applications and a late-20th century peak in Ca associated with algal whiting events in Lake Ontario. The Great Lakes are sensitive to environmental changes such as pollution by metals and it clear that, while there has been remedial success, results from the uppermost intervals of cores indicate ongoing problems.

Crystals within erupted volcanic rocks record geochemical and textural signatures during magmatic evolution prior to the onset of eruptions. Growth times of microlites can be derived through Crystal Size Distribution (CSD) analysis combined with well-constrained microlite growth rates, yielding petrologically-determined magma ascent timescales. Our newly developed, machine learning image processing scheme allows for the rapid generation of CSD, saving many hours of processing time, which previously involved hand-drawing the outer margins of crystals. For the present study, we examined a range of andesitic tephras from the Tongariro Volcanic Centre, New Zealand. A total of 228 plagioclase and pyroxene microlites CSDs were generated from individual tephra shards. All combined pyroxene and plagioclase microlite CSDs exhibit concave-up shapes, and similar intercepts and slopes at the smallest sizes. This implies similar growth durations of the smallest microlites of 15±9 to 28±15 (2σ) hours, regardless of the eruptive style or source, using an orthopyroxene microlite growth rate constrained from one of the samples. The orthopyroxene thermometer and the plagioclase hygrometer reveal the magmas were erupted at ~ 1079 to 1149 (±39 SEE), and H2O contents ranging from 0-0.4 to 0-1.7 wt.% (95% confidence maxima). In the absence of CO2, these results indicate shallow H2O exsolution pressures of < 240 bars, using a recent H2O-CO2 solubility model. Given the microlite residence times, shallow H2O exsolution driving microlite growth is inconsistent with the explosivity of the eruptions. Instead, our data suggest that the melts either carried large amounts of CO2, triggering earlier degassing of volatiles including H2O, or that microlite crystallisation began prior to degassing. Ongoing work investigates the H2O and CO2 contents hosted by melt inclusions in phenocrysts and microphenocrysts in these tephras to provide constraints on magma ascent rates, with implications for hazard characterization and mitigation.

Wetlands represent an essential ecosystem, providing flood control, carbon storage, and supporting biodiversity. In particular, the Everglades is a Ramsar Wetland of International Importance, supporting several threatened and endangered species of flora and fauna, and is especially important for wintering birds. Understanding and monitoring wetlands like the Everglades requires the ability to accurately identify and measure wetland extent and change in extent on short time scales. However, in situ methods are difficult given the nature of the surrounding environment, and optical methods of remote sensing are unable to see through dense vegetation. NASA’s Cyclone Global Navigation Satellite System (CYGNSS) has shown promising results using GNSS Reflectometry to identify the presence and extent of inland water. Utilizing GNSS as a signal of opportunity in an L-band passive bistatic radar, it can penetrate rain, clouds, and vegetation. Its 8-satellite constellation exhibits daily or sub-daily revisit rates, enabling the observation of dynamic changes on short time scales. In this work, we utilize a combination of CYGNSS data, ancillary information, and simulations to understand the observability of inundation beneath vegetation. Simulations were used to predict the received power using a water mask derived from Landsat imagery over the Everglades. By analyzing the differences between expected and actual received power, we identified areas of flooded vegetation. These differences were then combined with ancillary data sets to measure seasonal changes and create a seasonal map of open water and inundated vegetation throughout the Everglades network. We also investigated the ability of CYGNSS to discern and measure different vegetation types. Results were then compared with optical and radar imagery and verified with truth data from the Everglades Depth Estimation Network (EDEN) and littoral vegetation maps from the South Florida Water Management District. By leveraging CYGNSS’s high temporal frequency of observations and ability to see under vegetation, measurements of inundated vegetation and its change can complement other remote sensing and in situ methods of wetland monitoring.

The univariate statistics of potassium (K) and thorium (Th) concentrations in the oceanic and continental crust of the Earth has been recently investigated from geochemical databases and airborne radiometric surveys [1]. This study demonstrates that the frequency distributions of these elements are scale-dependent. There are right-skewed for small-scale samples (typical volume of rocks analyzed for an individual sample in a dataset) but tend to be more symmetric for large-scale samples. The right-skewed behavior of K and Th is attributed to their incompatible behavior during partial melting or fractional crystallization. The scale-dependence and evolution toward normal distributions are a direct consequence of the central limit theorem applied to K and Th concentrations. The results of the results of this study may be applied to Mars, using the Mars Odyssey global maps of K and Th concentrations [2]. In light of available K, Th concentrations at the rock-scale (in-situ samples and martian meteorites), we infer that each “pixel” of these maps reflect a right-skewed distribution of K and Th concentrations at smaller-scales, where K and Th-poor rocks, such as basalts, are spatially dominant. In turn, K, and Th-rich rocks, such as those found by Curiosity at Gale crater [3], may occur globally, though their spatial extension must be limited to account for the values reported by Mars Odyssey. The global, but sparse occurrence of K, Th-rich rocks at the surface is consistent with a buried felsic crust, outcropping at the favor of tectonic or impact events. These conclusions will be discussed in the context of the inferred constraints about the structure of the martian crust from Insight data [4]. [1] Baratoux, et al., Earth and Space Science, in press. [2] Boynton et al. JRGP, doi:10.1029/2007JE002887. [3] Sautter et al. doi:10.1038/NGEO2474. [4] Knapmeyer-Endrun et al., Science, doi: 10.1126/science.abf8966

In 2013, the Office of Science and Technology Policy (OSTP) issued a memorandum directing Federal agencies with over $100 million in annual research and development expenditures to develop a plan to support increased access to federally funded research results. In response, the US Geological Survey developed a Public Access Plan and published four new data management policies. The policies focus on review and approval of scientific data supporting scholarly conclusions, requirements for metadata, preservation, and data management planning. The new policies, in conjunction with the Public Access Plan, represent a shift in culture in how the USGS manages and provides access to its science data. The USGS recognizes that successful implementation of these new policies requires multiple pillars of support, from USGS leadership and staff buy-in, to effective tools. Active community engagement in the Bureau is stimulated through the Community for Data Integration (CDI), an open forum for community discussion and engagement, and an important component creating buy-in and contributing to the success of the new policies. Also critical are a suite of tools available to scientists to ensure their ability to implement the policies. Finally, support from leadership that manifests in the Fundamental Science Practices Advisory Council (FSPAC), a committee of representatives from across the Bureau who preside over policies and guidance is a critical component. While far from complete, the USGS has shifted its approach to science data management by engaging the community, offering tools to support policy, and providing leadership support for the quality and scientific integrity of USGS science data.

We investigate the evolution of outwardly propagating simple MHD waves in a model of the expanding solar wind using MHD simulations. In order to understand the different evolution of slow, Alfvén and fast modes, the question of wave-action conservation is re-examined theoretically. Using the fluctuation averaged Lagrangian, we discuss the conservation of total wave action and Equi-partition of wave energy for MHD waves. Results show that, even though the wave action for a simple monochromatic wave is subject to loss under resonance/degeneracy condition - conditions that can occur in the expanding solar wind in the regions where plasma ß crosses one, the total wave action possessed by all modes remains conserved, representing a wave action exchange between different degrees of freedom. The Expanding Box simulations demonstrate the results of the theoretical modeling, and reveal further details about mode-mixing, Alfvén resonance and wave steepening. All of these may help to understand the evolution of fluctuations from the inner heliosphere out to Earth orbit and beyond.

The conservation of historic cultural heritage sites is an endeavor that often brings together a diverse group of methods and interests. Castelul Corvinilor, also called Corvin’s Castle or Hunedoara Castle, in central Transylvania (Hunedoara county, Romania) is no exception. The first stone fortification of the medieval castle can be dated to the 14th century and has undergone significant expansion since the original structure was completed. The main building campaigns started in 1440 with the conversion of the fortress into a castle, followed by two more major campaigns during the 17th and 19th centuries, including restoration and remodeling of the original areas. The castle’s historical significance and touristic value make conservation an important goal for the site. This area has been the subject of limited and opportunistic (salvage) archaeological investigations, hoping to understand earlier phases of an administrative complex in the courtyard. However, the excavations did not establish a complete stratigraphy. A ground penetrating radar survey over most of the courtyard was conducted with a 500 MHz antenna, including the main courtyard area. This GPR survey of the courtyard was able to confirm some results of the archaeological excavation and located additional structures which were previously unknown. This presentation included analysis and interpretation of the data in both radargrams and depth slices. They reveal further horizons which indicate bedrock and possible reflections from structures dating to even earlier phases of the site.

Climate change is an important issue that affects all aspects of human life and the environment. Through this project, we wrote an original pop song about the local impacts and solutions to climate change in the Northeast. We used a mixed-methods evaluation to test the effectiveness of musical science communication in relation to traditional methods, to change the mindsets of college students and encourage them to take political action. Marist students responded to surveys asking about their sustainability and lifestyle choices, as well as their opinions on climate change. After watching either the traditional presentation or listening to the song, participants answered whether their stance toward climate change had changed, whether they had learned more, and whether they plan to take specific steps to make their lifestyles more sustainable. Through a Fisher Chi-Square analysis, we determined that the change in stances between the two treatments was not significant (p-value = 0.33). However, to an 84% confidence level, there were differences between the two treatments in whether students learned about climate change, and whether they were more likely to change their lifestyle. We found that the traditional science presentation was better at teaching new information (p-value = 0.08), while the song was better at convincing students to act in the future (p-value = 0.16). In summary, we found that traditional science communication is better at teaching someone about climate change, but if the goal is to convince someone to take action to do something about it, then communicating that message through music is the better option. Examples of these types of communication can be found on YouTube, https://youtu.be/gXedvKkpLGs for the song, and https://youtu.be/gbf6cTDNp18 for the traditional presentation.

Saturn’s moon Enceladus harbours a global subsurface ocean beneath its icy crust. Tidal dissipation within the moon’s core generates a substantial amount of heat which leads to ocean convection. Understanding this transport of mass and heat within the ocean is key to understand exchange processes between core, ocean and ice shell. Previous studies of ocean convection assume oceans of constant thickness and constant superadiabatic temperature gradients between the inner core and outer ice shell. However, observations indicate ocean thickness variations of up to ~20 km from equator to pole and heterogenous tidal dissipation within the core likely results in latitude-dependent temperature gradients. In this study, we analyse how heterogeneities affect circulation patterns and heat transfer in an Enceladan ocean using three-dimensional direct numerical simulations. We focus on a degree-2 meridional thickness profile with varying degree of thermal forcing to analyse the different rotating convection regimes and compare them with those of an ocean of constant thickness. Our results show that the non-uniform ocean gives rise to a latitudinally variable Rayleigh number, causing a potential decoupling of rotating convection regimes experienced locally within the ocean. As in the constant ocean thickness scenario, different regimes of convection exist, which depend on the relative influence of rotation. With increasing thermal forcing, convection moves from being restricted to equatorial regions to filling the whole fluid domain. Heat transport efficiency, as measured by the local Nusselt number, is different for the uniform and non-uniform cases and depends on the convection regime. Nusselt-Rayleigh relations are similar to those obtained for an ocean of uniform thickness, but the relevant Rayleigh number depends on the region of the domain that is convecting.

Agriculture sector is a major consumer of available fresh water. Increasing demand for fresh water in the various sectors has necessitated the use of treated waste water for irrigation. This water has marginal amount of salts which are known to affect the soil properties and crop growth. Hence a scientific approach is necessary to model the moisture uptake by plant roots under varying saline conditions. A numerical model is developed for solving the one dimensional Richards equation for moisture movement in variably saturated vadose zone. The root water uptake is incorporated in the model as the sink term as per the Ojha and Rai (1996) model, which is a non-linear root water uptake model. Combined water and salinity stress in the root water uptake is incorporated as per Feddes et al. (1978) and Mass and Hoffman (1977). Effect of varying salinity concentrations on the water uptake by plant roots and soil moisture dynamics in the root zone is studied on a 40 day period of crop growth. This is attained by providing fresh water and saline water irrigation with 15, 30 and 50 dS/m electrical conductivity. Irrigation field experiments of winter wheat crop were carried out to measure the crop parameters used in the analysis like leaf area index and root depth. The analysis to study the effect of salinity on soil water retention (SWR), hydraulic parameters and plant root water uptake was performed for silt loam (fine textured) and sandy loam (coarse textured) soils. The results show that the roots extract water at potential rate with fresh water, with no water uptake in the case of higher salinity as osmotic stress reaches permanent wilting phase. Overall, the root water uptake reduces as the concentration of salinity increases, even if there is no water stress. However, water stress was encountered at an earlier time in the case of sandy loam soil than in the case of silt loam. As the water content falls below the available moisture content, the water uptake is affected by water stress, which affects the growth and yield of crops. The results obtained from the study are useful in the better management of available water resources for irrigation practices in crop production.

Regional cycles of agricultural land expansion and abandonment have been common throughout history in many countries of the world. Following the cessation of agricultural practice, landscapes undergo the spontaneous process of ecological succession resulting in significant above and belowground changes over time. As agricultural lands are often severely depleted of soil carbon, they represent one of the land types with the highest potential to act as carbon sinks through the process of soil carbon sequestration. While best management practices for increasing soil carbon stocks through sustainable agriculture are understandably a key focus point in climate change research today, the lasting effect of the abandonment of agriculture on soil organic carbon has received relatively less attention. However, significant amounts of farmland have been abandoned across the globe in both developed and developing countries, especially over the last several decades. To better understand the ability of old agricultural lands to act as carbon sinks through time, this study compiles field and published data to perform a comprehensive meta-analysis on the impacts of this land use change on soil organic carbon dynamics. Using a chronosequence approach, three study sites in Catalonia, Spain, each with four fields representing different stages of ecological succession post-abandonment spanning roughly 60 years, were sampled at soil depths of 10, 20, and 30 cm. To determine soil carbon stocks at each site, bulk density samples were also collected. Samples were analyzed for organic carbon, nitrogen and pH. Additionally, published chrononsequence and paired-plot data from abandoned agricultural lands throughout the Mediterranean region were also compiled into a database to perform multiple regression analysis. Our findings are not only meant to test the hypothesis that abandoned fields can act as carbon sinks over time, but to also determine the rate of soil carbon stock increase and projected vulnerability in relation to a variety of environmental and land management variables, thereby highlighting the climate change mitigation value of an as of yet understudied global land use change.

Quantitative Precipitation Estimates from space-based observations represent an important dataset for understanding the Earth’s atmospheric, hydrological and energy cycles. Precipitation retrieval algorithms have been developed and refined over the last few decades and their accuracy and reliability are becoming increasingly more important for Earth’s energy budget and human activities. In particular, snowfall represents a key component of water cycle and contributes significantly to the Earth’s radiative balance. Accurately quantifying global surface snowfall is especially important since snow comprises a large percentage of the annual surface precipitation in many regions. The complexity of snowflakes particles and the nonlinear relationships between observations and retrieved variables have moved scientists to continually develop and enhance retrieval techniques. The present work aims to improve snowfall retrievals from Passive Microwave (PMW) sensors. Within the Global Precipitation Measurement (GPM) mission, the Goddard PROFiling (GPROF) algorithm snowfall retrieval has been chosen as an example of PMW precipitation product. Since previous works have demonstrated that GPROF performance strongly depends on the snowfall type, we developed a Machine Learning technique to classify snowing regime. A combined CloudSat-GPM dataset has been used to build the training dataset in which the GPM Microwave Imager (GMI) brightness temperatures (TB) are associated with a snowfall type, classifying the snowfall into three classes (‘shallow convective’, ‘deep stratiform’, ‘other’). The snowfall classification was adopted from a CloudSat classifying technique, based on snowing profiles and cloud classification. The problem is posed as a supervised learning problem, using a fully connected deep learning architecture with TB textures serving as input features. After building, optimizing and applying the classification method to existing GMI data, an evaluation exercise was undertaken to assess the classification performance. Results show that using only 20,000 GMI-CloudSat collocated snowing scenes the accuracy in retrieving the three classes has exceeded 80%. Being able to classify snowfall mode will help develop a specific setup for GPROF to improve detection and retrieval performance.

Climatic changes with warmer temperatures in mid-latitudes require the need to improve the simplified vegetation scheme of the regional climate model COSMO-CLM, which is not capable of modelling complex processes depending on temperature, water availability and day length. Thus, we have implemented the physically based Ball-Berry approach coupled with photosynthesis processes based on Farquhar and Collatz models for C3 and C4 plants in COSMO-CLM (v 5.16). The implementation of the new algorithms includes the replacement of the “one-big leaf” by a “two-big leaf” approach. We performed single column simulations with COSMO-CLM over three observational sites with C3 grass plants in Germany for the period from 1999 to 2015 (Parc, Linden and Lindenberg domain, Fig.1). Hereby, we tested three alternative formulations of the new algorithms. The first formulation (COSMO_v3.5) is based on the Community Land Model (CLM v3.5) algorithms for stomatal resistance, which depend on leaf photosynthesis, CO2 partial and vapor pressure and minimum stomatal conductance. The second one is COSMO_v4.5, which is based on the phenology algorithms of CLM v4.5 including the soil water stress function. The third one is similar to COSMO_v4.5 but with additional equations for dry leaf calculations (COSMO_v4.5e). The results revealed major differences in the annual cycle of stomatal resistance compared to the control simulation (COSMO_orig) with the original algorithm (Fig. 1). The biggest changes are from October to April when stomata are closed. The summer values of experiments are closer to measured values, than COSMO_orig. Further, changes in the stomatal resistance algorithms improve the accuracy of calculated transpiration rate and total evapotranspiration. The results indicate that changes in stomatal resistance and photosynthesis algorithms can improve the accuracy of other parameters of the COSMO-CLM model by comparing them with FLUXNET data and meteorological observations at the sites, and GLEAM datasets. Figure 1: The stomatal resistance based on COSMO-CLM experiments (a - annual cycle; b - daily values from 01.06.2011 to 15.09.2011) for: I – Parc domain, II – Linden domain, III – Lindenberg domain. This research was funded by the German Research Foundation (DFG) through grant number 401857120

Cloud microphysics plays important role on the storm dynamics. To investigate the impact of advanced microphysics schemes, using single and double moment (WSM6/WDM6) schemes, numerical simulations are conducted for a severe convective system that formed over the Korean Peninsula. Spatial rainfall distribution and pattern correlation associated with the convective system are improved in WDM6. During developing stage of the system, the distribution of total hydrometeors is larger in WDM6 compared to WSM6. Along with mixing ratio of hydrometeors (cloud, rain, graupel, snow and ice),number concentration of cloud and rainwater are also predicted in WDM6. To understand the differences in vertical representation of cloud hydrometeors between the schemes, rain number concentration (Nr) from WSM6 is also computed using particle density to compare with Nr readily available in WDM6.Varied vertical distribution, and large differences in rain number concentration, rain particle mass are evident between the schemes. Inclusion of number concentration of rain and cloud, CCN along with mixing ratio of different hydrometers have improved the storm morphology in WDM6. Inorder to investigate the cloud-aerosol interactions, numerical simulation has been conducted using an increase in CCN(aerosol) in WDM6 which has shown an improved rainfall distribution with intense hydrometer distribution. The latent heating (LH) rates of different phase change processes (condensation, evaporation, freezing, melting, sublimation and deposition) are also computed using various transformation rate terms in the microphysics modules. It is inferred that the change in aerosol has increased the LH of evaporation and freezing and affected the warming and cooling processes, cloud vertical distribution and subsequent rainfall.

Previous studies indicate significant intraseasonal (20-90 days) variability on the Indonesian Throughflow (ITF) transport produced by the Madden-Julian Oscillation (MJO). These studies, however, mostly focus on the transport through each individual strait, especially Makassar strait, and overall impacts of the MJO on ITF transport are not well understood. This study examines the intraseasonal variability of ITF transport associated with the MJO, including the transport through multiple major straits (Makassar, Lombok, Ombai, Timor) in the Indonesian Seas using a new 1/12° global HYbrid Coordinate Ocean Model (HYCOM) reanalysis. The composite analyses of oceanic and atmospheric variables are performed for the period January 2004-December 2015, in which eighteen well-defined MJO events were identified. Consistent with previous studies, large intraseasonal variability of the Makassar Strait Throughflow is identified from the analysis. In addition, the contribution of anomalous ITF transport through other straits during both active and suppressed phase of the MJO for the total transport is quantified based on the composite analysis.

InSAR time-series (InSAR-TS) analysis enables us to obtain the displacement time-series by using a number of SAR images repeatedly acquired on the area. Among the factors affecting the accuracy of the InSAR-TS analysis, this study focuses on three factors that may severely affect the signal detection limit: 1) the selection of the reference point (determining the offset in each interferogram), 2) ramp-type artifact that originate from inaccuracy in the orbit data or ionospheric disturbance, and 3) altitude-correlated tropospheric noise. Fukushima et al. (2019, Earth, Planets and Space) proposed an InSAR-TS analysis method to simultaneously solve for the displacement time-series and the error terms mentioned above as well as the error in the digital elevation model. In the proposed method, the unwrapped phase in interferograms is assumed to be composed of a linear combination of the LOS displacement, offset, planar ramp, altitude-correlated phase, and error in the used digital elevation model. A set of unwrapped small-baseline interferograms is then inverted to simultaneously obtain the displacement time-series and the parameters describing the error terms under the minimum norm condition on the displacement time-series. In this study, I applied the above-mentioned method after some updates such as introduction of the temporal constraint adopted by the NSBAS algorithm (Doin et al., 2011) and data masking, on the ALOS-2 data acquired around the Arima-Takatsuki fault zone in western Honshu, Japan. Data of four different Paths (20 and 21 from descending orbit, 127 and 128 from ascending orbit) obtained between August 2014 and March 2021 were analyzed. Some of the original interferograms contained severe noise such as a phase ramp equivalent to approximately 25 cm of LOS displacements. The average velocity field obtained by applying the method captured a relative range decrease of a few mm/year on the southern side of the fault, consistent with the results obtained from Sentinel-1 data analysis. Given the fact that the Sentinel-1 dataset had much favorable conditions (much larger number of data and much smaller ionospheric noise), the consistency in the average velocity field suggests the effectiveness of the proposed approach.

Northern Mexico is characterized by semiarid climate, where limited precipitation restricts crop production. Therefore, production needs efficient irrigation techniques. Agriculture is a high water consumption activity that in order to become more sustainable, demands knowledge of irrigation efficiencies at the regional scale. In this work we present a method to estimate irrigation efficiencies of croplands based on the crops’ water demand obtained with remote sensing data. The study site is located in an agricultural valley in northern Mexico in an area of cornfields with approximately 47,000 ha under irrigation that lies on top of an overexploited aquifer with a sustained declining water table (averaging 2m/year of drawdown). Using Landsat 8 derived imagery from the METRIC-EEFLUX site for the period between May 16 (emergence season) to Nov 24 (harvest season) during the 2017 agricultural cycle, the Crop coefficient (Kc), the reference Evapotranspiration (ET0) and the actual Evapotranspiration (Eta) were obtained. To obtain daily values of ETa in between the 16 day Landsat images interval, we used Kc obtained from its relation with a normalization of the enhanced vegetation index (EVI), and ET0 calculated using Penmann-Montheit fed with meteorological data from weather stations in the vicinity of the area. Irrigation efficiency was calculated using the quotient between ETa and water applied during the agricultural cycle measured with volumetric gauges at the outlet of the irrigation systems. For this study we monitored 5 parcels of corn with different irrigation systems: two parcels with drip irrigation, one with sprinkler irrigation and two with furrow irrigation. Results from the irrigation efficiencies ranged from 47 % to 71 % and depend on factors like parcel dimensions, irrigation schemes, scheduling and its spatial uniformity. Crop yield data is used to discuss the impacts of these factors on the irrigation efficiencies and the implications of different water use strategies for the sustainability of water resource-compromised regions. This methodology can be replicated in extensive areas requiring knowledge of irrigation efficiencies for more sustainable water management.