To determine plausible groundwater recharge rates on early Mars, we develop analytic and numerical solutions for an unconfined steady-state aquifer beneath the southern highlands. We show that the aquifer’s mean hydraulic conductivity, $K$, is the primary constraint on the plausible magnitude of mean steady recharge, $r$. By restricting groundwater upwelling to Arabia Terra, using a mean hydraulic conductivity of, $K$ ${\sim}10^{-7}$ m/s, and varying shoreline elevations and recharge distributions, the mean recharge must be order of $10^{-2}$ mm/yr. Recharge for other values of $K$ can be estimated as $r$ ${\sim}10^{-5}\,K$. Our value is near the low end of previous recharge estimates and two orders-of-magnitude below the smallest precipitation estimates. This suggests that, for a steady hydrologic cycle, most precipitation forms runoff, not groundwater recharge. It is also plausible the transient aquifer response to recharge is sufficiently slow that no upwelling occurs prior to cessation of climatic excursions causing precipitation.

The usefulness of extended records of streamflow from tree-ring based hydrologic reconstructions seems obvious- a longer record provides a broader range of the variability of extremes and allows recent and/or ongoing events to be evaluated in a long-term context. The information from these centuries-long records may have clear implications for water resource management, but it is often unclear exactly how this information can be applied to management. In this presentation, I will discuss some of the challenges I have observed that are involved in using streamflow reconstructions in management decisions. These range from issues related to an agency’s capacity to use new types of data to mismatches between what is needed (e.g., daily resolution, a network of gage inputs) and what reconstruction data provide. The skillfulness of a streamflow reconstruction also has a bearing on its perceived credibility in terms of useable data. In spite of these challenges, there is a variety of ways that these data have been used by water resource managers in the western US. The uses are often not immediately evident, but can take the form of, for example, sensitively assessment, awareness raising, and shifts in prior assumptions. Relationship building between researchers and resource managers can yield mutual respect and understanding that lead to both interesting research questions and relevant and valuable information, even if the application to management is not tangible or immediate.

The biogeochemical cycles of iron (Fe) and manganese (Mn) in lakes and reservoirs have predictable seasonal trends, largely governed by stratification dynamics and redox conditions in the hypolimnion. However, short-term (i.e., sub-weekly) trends in Fe and Mn cycling are less well-understood, as most monitoring efforts focus on longer-term (i.e., monthly to yearly) time scales. The potential for elevated Fe and Mn to degrade water quality and impact ecosystem functioning, coupled with increasing evidence for high spatiotemporal variability in other biogeochemical cycles, necessitates a closer evaluation of the short-term Fe and Mn cycling dynamics in lakes and reservoirs. We adapted a UV-visible spectrophotometer coupled with a multiplexor pumping system and PLSR modeling to generate high spatiotemporal resolution predictions of Fe and Mn concentrations in a drinking water reservoir (Falling Creek Reservoir, Vinton, VA, USA) equipped with a hypolimnetic oxygenation (HOx) system. We quantified hourly Fe and Mn concentrations during two distinct transitional periods: reservoir turnover (Fall 2020) and initiation of the HOx system (Summer 2021). Our sensor system was able to successfully predict mean Fe and Mn concentrations as well as capture sub-weekly variability, ground-truthed by traditional grab sampling and laboratory analysis. During fall turnover, hypolimnetic Fe and Mn concentrations began to decrease more than two weeks before complete mixing of the reservoir occurred, with rapid equalization of epilimnetic and hypolimnetic Fe and Mn concentrations in less than 48 hours after full water column mixing. During the initiation of hypolimnetic oxygenation in Summer 2021, we observed that Fe and Mn were similarly affected by physical mixing in the hypolimnion, but displayed distinctly different responses to oxygenation, as indicated by the rapid oxidation of soluble Fe but not soluble Mn. This study demonstrates that Fe and Mn concentrations are highly sensitive to shifting DO and stratification and that their dynamics can substantially change on hourly to daily time scales in response to these transitions.

Searches for phosphine in Venus’ atmosphere have sparked a debate. Cordiner et al. 2022 analyse spectra from the Stratospheric Observatory For Infrared Astronomy (SOFIA) and infer <0.8 ppb of PH3. We noticed that spectral artefacts arose mainly from inessential calibration-load signals. By-passing these signals allows simpler post-processing, and 6.5σ detection of 1 ppb of PH3 at ~75 km altitude (just above the clouds). Compiling six phosphine results would suggest the abundance inverts: decreasing above the clouds but rising again in the mesosphere from some unexplained source. However, no such extra source is needed if phosphine is undergoing destruction by sunlight (photolysis), as it does on Earth. Low values/limits were found where the viewed part of the super-rotating Venusian atmosphere had passed through sunlight, while the high values are from views moving into sunlight. We suggest Venusian phosphine is indeed present, and so merits further work on models of its origins.

Dynamic influences on summertime seasonal United States rainfall variability are not well understood. A major cause of moisture transport is the Great Plains low-level jet (LLJ). Using observations and a dry atmospheric general circulation model, this study explored the distinct and combined impacts of two prominent atmospheric teleconnections - the East Asian monsoon (EAM) and North Atlantic subtropical high (NASH) - on the Great Plains LLJ in the summer. Separately, a strong EAM and strong western NASH are linked to a strengthened LLJ and positive rainfall anomalies in the Plains/ Midwest. Overall, NASH variability is more important for considering the LLJ impacts, but strong EAM events amplify western NASH-related Great Plains LLJ strengthening and associated rainfall signals. This occurs when the EAM-forced Rossby wave pattern over North America constructively interferes with low-level wind field, providing upper-level support for the LLJ and increasing mid- to upper-level divergence.

The petrophysical properties of rocks are a strong and an effective indicator of the extent of the susceptibility of the rocks themselves to building and construction operations above and above them. As these tests are conclusive evidence that such rocks will not have a landslide or semi-collapse, and from here we focus in this scientific proposal paper on them practically in a manner of step-by-step, to make it easier for the specialist to understand the well. These properties are an assistant to the geologist and civil engineer in the field of work, as they work to provide actual numbers of the rocks, or in other words, the process of converting rocks into mere numbers that speak for themselves effectively and feasibly, such properties are sufficient.

The end-Permian mass extinction event resulted in the loss of approximately 80% to 90% of marine animal species due to drastic changes in climate. Because warming was a major factor in the extinction, it has been theorized the organisms that did survive were able to do so because they moved to higher latitudes and this hypothesis is consistent with tetrapod data. We hypothesized that this relationship holds true for marine mollusks and arthropods as well. Using Changhsingian (Late Permian) and Induan (Early Triassic) data from the Paleobiology Database, we extracted occurrences of classes Bivalvia, Cephalopoda, Gastropoda, and Ostracoda, which had 2433, 395, 379, and 1717 genus occurrences, respectively. Then, we used the paleolatitude data for each genus occurrence to characterize the latitude distribution of each class before and after the Permian/Triassic transition. We compared the paleolatitude medians before and after the mass extinction for each class to quantify the latitude shift for each class: 23.18° for Bivalvia, 37.45° for Cephalopoda, 29.82° for Gastropoda, and 6.29° for Ostracoda. This finding indicates that each individual class had a different latitudinal shift, with all classes exhibiting a poleward shift north. We also conducted Welch t-tests to compare the differences in latitudinal ranges and found that they were significant (Bivalvia: p < 2.2e-16, Cephalopoda: p = 3.83e-6, Gastropoda: p < 2.2e-16, Ostracoda: p = 0.0030). In addition, we ran multiple randomized models to compare them with our original results and found a significant difference between them via the Kolmogorov-Smirnov test, which means that the northward migration could be a biological response. Moreover, the results of our study show that the overall latitudinal range of most classes contracted after the extinction event, with the exception of the Cephalopoda class.

Persistent warming and water cycle change due to anthropogenic climate change modifies the temperature and salinity distribution of the ocean over time. This ‘forced’ signal of temperature and salinity change is often masked by the background internal variability of the climate system. Analysing temperature and salinity change in watermass-based coordinate systems has been proposed as an alternative to traditional Eulerian (e.g., fixed-depth, zonally-averaged) co-ordinate systems. The impact of internal variability is thought to be reduced in watermass co-ordinates, enabling a cleaner separation of the forced signal from background variability - or a higher ‘signal-to-noise’ ratio. Building on previous analyses comparing Eulerian and water-mass-based one-dimensional coordinates, here we recast two-dimensional co-ordinate systems - temperature-salinity (𝑇 − 𝑆), latitude-longitude and latitude-depth - onto a directly comparable equal-volume framework. We compare the internal variability, or ‘noise’ in temperature and salinity between these remapped two-dimensional co-ordinate systems in a 500 year pre-industrial control run from a CMIP6 climate model. We find that the median internal variability is lowest (and roughly equivalent) in 𝑇 − 𝑆 and latitude-depth space, compared with latitude-longitude co-ordinates. A large proportion of variability in 𝑇 − 𝑆 and latitude-depth space can be attributed to processes which operate over a timescale greater than 10 years. Overall, the signal-to-noise ratio in 𝑇 − 𝑆 co-ordinates is roughly comparable to latitude-depth co-ordinates, but is greater in regions of high historical temperature change. Conversely, latitude-depth co-ordinates have greater signal-to-noise ratio in regions of historical salinity change. Thus, we conclude that the climatic temperature change signal can be more robustly identified in watermass-co-ordinates.

Mesoscale eddies are abundant in the global oceans and known to affect marine biogeochemistry. Understanding their cumulative impact on the air-sea carbon dioxide (CO2) flux is likely important for quantifying the ocean carbon sink. Here, observations and Lagrangian tracking are used to estimate the air-sea CO2 flux of 67 long lived (i.e. > 1 year) mesoscale eddies in the South Atlantic Ocean over a 16 year period. We find that anticyclonic eddies originating from the Agulhas retroflection and cyclonic eddies originating from the Benguela upwelling act as net CO2 sinks over their lifetimes. In combination, the eddies significantly enhanced the CO2 sink into the South Atlantic Ocean by 0.08 ± 0.01%. Although this modification appears small, long lived eddies account for just ~0.4% of global ocean eddies and eddy activity is increasing; therefore, explicitly resolving eddy processes within all models used to assess the ocean carbon sink would appear critical.

The interaction of Io with the co-rotating magnetosphere of Jupiter is known to produce Alfven wings that couple the moon to Jupiter's ionosphere. We present first results from a new numerical model to describe the propagation of these Alfven waves in this system. The model is cast in magnetic dipole coordinates and includes a dense plasma torus that is centered around the centrifugal equator. Results are presented for two density models, showing the dependence of the interaction on the magnetospheric density. Model results are presented for the case when Io is near the centrifugal and magnetic equators as well as when Io is at its northernmost magnetic latitude. The effect of the conductance of Jupiter's ionosphere is considered, showing that a long auroral footprint tail is favored by high Pedersen conductance in the ionosphere. The current patterns in these cases show a U-shaped footprint due to the generation of field-aligned current on the Jupiter-facing and Jupiter-opposed sides of Io, which may be related to the structure in the auroral footprint seen in the infrared by Juno. A model for the development of parallel electric fields is introduced, indicating that the main auroral footprints of Io can generate parallel potentials of up to 100 kV.

Ingenious use of multisource satellite observations to accurately invert global and regional subsurface thermohaline structure is essential for understanding ocean interior processes, but extremely challenging. This study proposes a new method from the sea surface information inverting daily subsurface temperature (ST) based on generative adversarial network (GAN) model in China’s marginal seas. The proposed GAN-based model can project the STs from sea surface information (SLA, SSTA, SST) with a high resolution of 1/12°. A traditional regression-based model, Modular Ocean Data Assimilation System (MODAS), is set up the same experiments for the sake of comparison. The results show that the averaged RMSE results are less than 1.45°C in upper 200m and the highest averaged R2 of 0.97 at the 70m level, which are better than that of MODAS. Errors analysis and typical oceanographic phenomena analysis results show the superiority of the proposed GAN-based model in this study. This study can provide high-precision daily ST data from sea surface information, which can be expanded to further studies on the ocean interior variation characteristics.

Within the Charlotte, North Carolina, to Atlanta, Georgia, megaregion (Charlanta), the Atlanta metropolitan area has been shown to augment proximal cloud-to-ground (CG) lightning occurrence. Although numerous studies have documented this “urban lightning effect” (ULE) with regard to CG lightning, relatively few have investigated urban effects on distributions of total lightning (TL). Moreover, there has yet to be a study of the ULE using TL observations from the Geostationary Lightning Mapper (GLM). In an effort to fill this gap, we investigated spatial distributions of TL around the cities of Atlanta, GA, Greenville, SC, and Charlotte, NC, using GLM data collected during the warm seasons of 2018–2021. Analyses reveal augmentation of total lightning intensity and frequency over the major cities of Atlanta and Charlotte, with a diminished urban signal over the smaller city of Greenville. This work also demonstrated the potential efficacy of the emerging satellite-based TL climatology in ULE studies.

There is no doubt anymore that Earth Observation (EO) is contributing toward meeting the Sustainable Development Goals and addressing environmental challenges. Digital Earth Africa’s objective is to make freely available an EO data cube for all of Africa that democratizes the capacity to process and analyse satellite data. It allows to track changes across Africa in unprecedented detail and will provide data on a vast number of issues, including soil and coastal erosion, agriculture, forest and desert development, water quality, and changes to human settlements. To realise full benefits of an advanced Platform like Digital Earth Africa, Digital Earth Africa has co-designed and co-developed with five institutions namely the Regional Centre For Mapping Of Resources For Development (RCMRD, Kenya), Centre de Suivi Écologique (Senegal), l’observatoire du Sahara et du Sahel (Tunisia), AFRIGIST (Nigeria) and AGRHYMET (Niger). This was meant to ensure it meets end-users needs, this program has been developed by the future deliverers of the program. From the trainers’ perspective, the program is built to consider the recent changes in teaching approaches and methodologies including pedagogy that emerged from a Covid-19, and post Covid-19, pandemic world. On the end-user side, the curriculum covered a wide spectrum of topics, from understanding satellite images, python scripting in the JupyterLab environment to identifying solutions to SDGs challenges through use cases, available in English and French. Digital Earth Africa’s Gender Equity, Diversity and Social Inclusion principles strategy (GEDSI) is imprinted as a watermark across the whole program. It prioritises gender equality, diversity, and social inclusion so that women, people with disabilities and marginalised individuals and communities have the same opportunities to benefit from EO data. In addition, Digital Earth Africa started live virtual sessions, to stay connected with end users, who have developed impactive stories in their communities. Digital Earth Africa seeks to support the capacity development of individuals, academic and governmental institutions, and private sector organisations to empower present and next generation of decision makers to drive toward a sustainable future, leaving on one and place behind.

The Hunga Tonga-Hunga Ha’apai (HTHH) volcanic eruption in January 2022 injected extreme amounts of water vapor (H2O) and a moderate amount of the aerosol precursor (SO2) into the Southern Hemisphere (SH) stratosphere. The H2O and aerosol perturbations have persisted and resulted in large-scale SH stratospheric cooling, equatorward shift of the Antarctic polar vortex, and slowing of the Brewer-Dobson circulation associated with a substantial ozone reduction in the SH winter midlatitudes. Chemistry-climate model simulations forced by realistic HTHH inputs of H2O and SO2 reproduce the observed stratospheric cooling and circulation effects, demonstrating the observed behavior is due to the volcanic influences. Furthermore, the combination of aerosol transport to polar latitudes and a cold polar vortex enhances springtime Antarctic ozone loss, consistent with observed polar ozone behavior in 2022.

Natural aerosols and their interactions with clouds remain an important uncertainty within climate models, especially at the poles. Here, we study the behavior of sea salt aerosols (SSaer) in the Arctic and Antarctic within 12 climate models from CMIP6. We investigate the driving factors that control SSaer abundances and show large differences based on the choice of the source function, and the representation of aerosol processes in the atmosphere. Close to the poles, the CMIP6 models do not match observed seasonal cycles of surface concentrations, likely due to the absence of wintertime SSaer sources such as blowing snow. Further away from the poles, simulated concentrations have the correct seasonality, but have a positive mean bias of up to one order of magnitude. SSaer optical depth is derived from the MODIS data and compared to modeled values, revealing good agreement, except for winter months. Better agreement for AOD than surface concentration may indicate a need for improving the vertical distribution, the size distribution and/or hygroscopicity of modeled polar SSaer. Source functions used in CMIP6 emit very different numbers of small SSaer, potentially exacerbating cloud-aerosol interaction uncertainties in these remote regions. For future climate scenarios SSP126 and SSP585, we show that SSaer concentrations increase at both poles at the end of the 21st century, with more than two times mid-20th century values in the Arctic. The pre-industrial climate CMIP6 experiments suggest there is a large uncertainty in the polar radiative budget due to SSaer.

Permafrost-affected ecosystems are prone to warming and thawing, which can increase the availability of subsurface nitrogen (N) with consequences for otherwise N-limited tundra vegetation. Here, we show that the upper permafrost of the Tibetan Plateau is subject to thawing and that the upper permafrost zone is rich in ammonium. Furthermore, a five-year 15N tracer experiment showed that long-rooted plant species were able to utilize 15N-labeled N at the permafrost table and far below the main root zone. A 20 years survey is used here to document that long-rooted plant species had a competitive advantage at sites subject to warming and that both plant composition and growth were significantly correlated with permafrost thawing and changes in nitrogen availability. Our experiment documents a clear feedback mechanism of climate warming, which releases plant–available N favoring long-rooted plants and explains important changes in plant composition and growth across sites on the Tibetan Plateau.

• Frictional ruptures initiate via a characteristic nucleation process that triggers dynamic rupture essentially • Nucleation replaces the concept of a ‘static friction coefficient’ • The nucleation process possesses unique characteristic general properties • Nucleation details depend on local topography

NASA’s Planetary Data System (PDS)* contains data collected by missions to explore our solar system. This includes Lunar Reconnaissance Orbiter (LRO), which has collected as much data as all other planetary missions combined. Currently, PDS offers no way to search lunar images based on content. Working with the PDS Cartography and Imaging Sciences Node (IMG), we develop LROCNet, a deep learning (DL) classifier for imagery from LRO’s Narrow Angle Cameras (NACs). Data we get from NACs are 5km swaths, at nominal orbit, so we perform a saliency detection step to find surface features of interest. A detector developed for Mars HiRISE (Wagstaff et al, 2021) worked well for our purposes, after updating based on LROC image resolution. We use this detector to create a set of image chipouts (small cutouts) from the larger image, sampling the lunar globe. The chipouts are used to train LROCNet. We select classes of interest based on what is visible at the NAC resolution, consulting with scientists and performing a literature review. Initially, we had 7 classes: fresh crater, old crater, overlapping craters, irregular mare patches, rockfalls and landfalls, of scientific interest, and none. Using the Zooniverse platform, we set up a labeling tool and labeled 5,000 images. We found that fresh crater made up 11% of the data, old crater 18%, with the vast majority none. Due to limited examples of the other classes, we reduced our initial class set to: fresh crater (with impact ejecta), old crater, and none. We divided the images into train/validation/test set making sure no image swaths span multiple sets and fine tuned pre-trained DL models. VGG-11, a standard DL model, gives the best performance on the validation set, with an overall accuracy of 82% on the test set. We had 83% label agreement in our human label study; labeling was difficult as there is no clear class boundary. Our DL model accuracy is similar to human labelers. 64% of fresh craters, 80% old craters, and 86% of the none class are classified correctly. Predictions from this model will be integrated with IMG’s Atlas, allowing users to interactively search classes of interest. *https://pds-imaging.jpl.nasa.gov Copyright © 2022, California Institute of Technology. U.S. Government sponsorship acknowledged.

We show the global dynamics of spatial cross-correlation of Pc2 wave activity can track the evolution of the 2015 St. Patrick’s Day geomagnetic storm for an 8 hour time window around onset. The global spatially coherent response is tracked by forming a dynamical network from 1 second data using the full set of 100+ ground-based magnetometer stations collated by SuperMAG and Intermagnet. The pattern of spatial coherence is then captured by a few network parameters which in turn track the evolution of the storm. At onset IMF B_z>0 and Pc2 power increases, we find a global response with stations being correlated over both local and global distances. Following onset, whilst B_z>0, the network response is confined to the day-side. When IMF B_z<0, there is a strong local response at high latitudes, consistent with the onset of polar cap convection driven by day-side reconnection. The spatially coherent response as revealed by the network grows and is maximal when both SME and SMR peak, consistent with an active electrojet and ring-current. Throughout the storm there is a coherent response both in stations located along lines of constant geomagnetic longitude, between hemispheres, and across magnetic local time. The network does not simply track the average Pc2 wave power, however is characterized by network parameters which track the evolution of the storm. This is a first study to parameterize global Pc2 wave correlation and offers the possibility of statistical studies across multiple events to detailed comparison with, and validation of, space weather models.

Melt ponds forming on Arctic sea ice in summer significantly reduce the surface albedo and impact the heat and mass balance of the sea ice. Their seasonal development features fast and local changes in fractions of surface types demonstrating the necessity of improving melt pond fraction (MPF) products. We present a renewed method to extract MPF from Sentinel-2 satellite imagery, which is evaluated by MPF products from higher resolution satellite and helicopter-borne imagery. The analysis of melt pond evolution during the MOSAiC campaign in summer 2020, shows a split of the Central Observatory (CO) into a level ice and a highly deformed part, the latter of which exhibits exceptional early melt pond formation compared to the vicinity. Average CO MPFs amount to 17 % before and 23 % after the major drainage. Arctic-wide analysis of MPF for years 2017-2021 shows a consistent seasonal cycle in all regions and years.

In a context of climate change, the stakes surrounding water availability are getting higher. Decomposing and quantifying the effects of climate on discharge allows to better understand their impact on water resources. We propose a methodology to separate the effect of change in annual mean of climate variables from the effect of intra-annual distribution of precipitations. It combines the Budyko framework with outputs from a Land Surface Model (LSM). The LSM is used to reproduces the behavior of 2134 reconstructed watersheds over Europe between 1902 and 2010, with climate inputs as the only source of change. We fit to the LSM outputs a one parameter approximation to the Budyko framework. It accounts for the evolution of annual mean in precipitation (P) and potential evapotranspiration (PET). We introduce a time-varying parameter in the equation which represents the effect of long-term variations in the intra-annual distribution of P and PET. To better assess the effects of changes in annual means or in intra-annual distribution of P, we construct synthetic forcings fixing one or the other. The results over Europe show that the changes in discharge due to climate are dominated by the trends in the annual averages of P. The second main climate driver is PET, except over the Mediterranean area where changes in intra-annual variations of P have a higher impact on discharge than trends in PET. Therefore the effects of changes in intra-annual distribution of climate variables are not to be neglected when looking at changes in annual discharge.

Estimating the three geophysical variables significant wave height (SWH), sea surface height, and wind speed from satellite altimetry continues to be challenging in the coastal zone because the received radar echoes exhibit significant interference from strongly reflective targets such as mud banks, sheltered bays, ships etc. Fully focused SAR (FF-SAR) processing exhibits a theoretical along-track resolution of up to less than half a metre. This suggests that the application of FF-SAR altimetry might give potential gains over unfocused SAR (UF-SAR) altimetry to resolve and mitigate small-scale interferers in the along-track direction to improve the accuracy and precision of the geophysical estimates. The objective of this study is to assess the applicability of FF-SAR-processed Sentinel-6 Michael Freilich (S6-MF) coastal altimetry data to obtain SWH estimates as close as possible to the coast. We have developed a multi-mission FF-SAR processor and applied the coastal retracking algorithm CORALv2 to estimate SWH. We assess different FF-SAR and UF-SAR processing configurations, as well as the baseline Level-2 product from EUMETSAT, by comparison with the coastal, high-resolution SWAN-Kuststrook wave model from the Deltares RWsOS North Sea operational forecasting system. This includes the evaluation of the correlation, the median offset, and the percentage of cycles with high correlation as a function of distance to the nearest coastline. Moreover, we analyse the number of valid records and the L2 noise of the records. The case study comprises five coastal crossings of S6-MF that are located along the Dutch coast and the German coast along the East Frisian Islands in the North Sea. We find that the FF-SAR-processed dataset with a Level-1b posting rate of 140 Hz shows the greatest similarity with the wave model. We achieve a correlation of ~0.8 at 80% of valid records and a gain in precision of up to 29% of FF-SAR vs UF-SAR for 1-3 km from the coast. FF-SAR shows, for all cycles, a high correlation of greater than or equal to 0.8 for 1-3 km from the coast. We estimate the decay of SWH from offshore at 30 km to up to 1 km from the coast to amount to 26.4%+-3.1%.

The question “what arrests an earthquake rupture?” sits at the heart of any potential prediction of earthquake magnitude. Here, we use a one-dimensional, thin-elastic-strip, minimal model, to illuminate the basic physical parameters that control the arrest of large ruptures. The generic formulation of the model allows for wrapping various earthquake arrest scenarios into the variations of two dimensionless variables $\bar \tau_k$ (initial pre-stress on the fault) and $\bar d_c$ (fracture energy), valid for both in-plane and antiplane shear loading. Our continuum model is equivalent to the standard Burridge-Knopoff model, with an added characteristic length scale, $H$, that corresponds to either the thickness of the damage zone for strike-slip faults or to the thickness of the downward moving plate for subduction settings. We simulate the propagation and arrest of frictional ruptures and derive closed-form expressions to predict rupture arrest under different conditions. Our generic model illuminates the different energy budget that mediates crack- and pulse-like rupture propagation and arrest. It provides additional predictions such as generic stable pulse-like rupture solutions, stress drop independence of the rupture size, the existence of back-propagating fronts, and predicts that asymmetric slip profiles arise under certain pre-stress conditions. These diverse features occur also in natural earthquakes, and the fact that they can all be predicted by a single minimal framework is encouraging and pave the way for future developments of this model.

The uncontrolled rapid population growth in our regions and strong industrialization are putting pressure on natural resources, accelerating climate change and desertification. This study aims to follow the evolution of land use in the N’ZI watershed. Three images from Landsat 4 & 5 (1986), Landsat 7 (2000), and Landsat 8 (2020) were used to carry out this study. Remote sensing and geographic information systems (GIS) were used to monitor land cover as a whole. Various treatments were performed using Envi 5.1 and ArcGIS 10.4.1 software programs. The results showed that changes took place during the periods of 1986-2000, 2000-2020, and 1986-2020. The results of the analysis showed the regression of water surfaces from -64.95% to -52.47% during the period of2000-2020 and 1986-2020, on the other hand, there is a great increase in bare-ground dwellings (373.63%) and low-cover soils (10.60%). These progressions were due to the destruction of forests -86.93%, savannas -3.97%, and agricultural areas -9.30% between 1986 and 2020