The isotopic composition of surface water vapor flux (δ) is a quantity frequently used to investigate the local and regional water cycle. In this study, the δ determined with the Keeling method was evaluated against the flux-gradient method and the Craig-Gordon model prediction. Previous studies have shown that the choice of regression fitting methods can bias the δ intercept results and precision of the Keeling method. Here, the Keeling method was applied to high-frequency (0.2 to 1 Hz) data measured at a cropland and a lake site to test different regression methods. Results show that the Keeling method with the York’s solution (YS) and the ordinary least squares (OLS) regression produced robust estimates of δ when compared with the flux-gradient method. Increasing concentration range reduced the standard error of estimate but did not bring obvious improvement to the bias error for the YS and OLS regression. The Keeling result was better using data from two sampling heights than only one. There was evidence that the Keeling method with the OLS regression slightly outperformed the flux-gradient method during periods with small vertical vapor gradient. Results also show that the Keeling method with the geometric mean regression gave highly biased estimate of δ for the types of isotope ratio infrared spectroscopy analyzer deployed in this study. These results can inform δ calculations and future experimental designs.

Abstract: Globally, more people are impacted by extreme hydrologic events such as flooding than all other types of natural disasters combined, and the effects can be devastating. Two examples are the 2012 and 2022 floods along the Niger and Benue Rivers within the Lower Niger River Basin (LNRB) in Nigeria. Flooding within the LNRB typically occurs annually during the rainy season, however, the 2012 and 2022 flood events were of similar magnitude, had catastrophic socioenvironmental impacts, and occurred one decade apart. Limited historical gage data along the Niger and Benue Rivers precludes traditional flood frequency analysis in the LNRB. Hence, this study seeks to utilize globally available observations from satellite remote sensing to compute flood depths using the Floodwater Depth Estimation Tool (FwDETv2.1 version) implemented in Google Earth Engine. Other hydrological and physiographic characteristics of LNRB in 2012 and 2022 are also evaluated using remote sensing observations. Since the FwDET requires only globally available input data (flood inundation map and Digital Elevation Model) which favors data-sparse regions such as Nigeria, the potential for the FwDET tool to automatically quantify flood water depths, an important variable in flood frequency estimation and damage assessment, can be analyzed even when historical observations are lacking. The utility of the FwDETv2.1 for flood management and mitigation studies along global rivers with limited historical data is discussed. ReferenceIdowu, Dorcas, and Wendy Zhou. "Performance evaluation of a potential component of an early flood warning system—A case study of the 2012 flood, Lower Niger River Basin, Nigeria." Remote Sensing 11.17 (2019): 1970.Brakenridge, G. R., Kettner, A. J., Paris, S., Cohen, S., Nghiem, S. V. , River and Reservoir Watch Version 4.5, Satellite-based river discharge and reservoir area measurements, DFO Flood Observatory, University of Colorado, USA. http://floodobservatory.colorado.edu/ SiteDisplays/ 20.htm (Accessed 6 December 2023).Cohen, S.; Peter, B.G.; Haag, A.; Munasinghe, D.; Moragoda, N.; Narayanan, A.; May, S. Sensitivity of Remote Sensing Floodwater Depth Calculation to Boundary Filtering and Digital Elevation Model Selections. Remote Sens. 2022, 14, 5313. https://doi.org/10.3390/rs14215313.B. G. Peter, S. Cohen, R. Lucey, D. Munasinghe, A. Raney and G. R. Brakenridge, "Google Earth Engine Implementation of the Floodwater Depth Estimation Tool (FwDET-GEE) for Rapid and Large Scale Flood Analysis," in IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022, Art no. 1501005, doi: 10.1109/LGRS.2020.3031190.Brakenridge, G. Robert, Son V. Nghiem, and Zsofia Kugler. "Passive microwave radiometry at different frequency bands for river discharge retrievals." Earth and Space Science 10.8 (2023): e2023EA002859.Idowu, Dorcas. Assessing the Utilization of Remote Sensing and GIS Techniques for Flood Studies and Land Use/Land Cover Analysis Through Case Studies in Nigeria and the USA. Diss. Colorado School of Mines, 2021.Idowu, Dorcas, and Wendy Zhou. "Global Megacities and Frequent Floods: Correlation between Urban Expansion Patterns and Urban Flood Hazards." Sustainability 15.3 (2023): 2514.

There have always been some challenges within the remote sensing community related to the processing of contiguous spectral bands contained in hyperspectral datasets. Most approaches would resort to using averaged spectral information over wide bandwidths resulting in loss of crucial information available in those contiguous bands. The loss of information could mean a drop in the discriminative power when it comes to land cover classes with comparable spectral responses, as in the case of cultivated fields versus fallow lands. In this study, we proposed and tested three optimized novel algorithms based on Moment Distance Index (MDI) that characterizes the whole shape of the spectral curve. The image classification tests conducted on two publicly available hyperspectral data sets (AVIRIS 1992 Indian Pine and HYDICE Washington DC Mall images) showed the robustness of the optimized MDI algorithms in terms of classification accuracy. We achieved an overall accuracy of 98% and 99% for AVIRIS and HYDICE, respectively using the optimized MDI algorithms. The optimized indices were also time efficient as it avoided the process of band dimension reduction, such as those implemented by several well-known classifiers. Our results showed the potential of the optimized shape indices to discriminate between grass/pasture and grass/trees, tree and grass, and between types of tillage (corn-min and corn-notill) under object-based random forest approach. The results highlight the importance of MDI that completely utilizes the contiguous spectral bands to define the gradient of the curve and improve image classification accuracy.

A document by Nolan Roth. Click on the document to view its contents.

Tropical convective organization and associated clusters of precipitation affect the global circulation and Earth’s energy budget, but many aspects such as the power-law distribution of precipitation clusters and the relation to convective self-aggregation remain poorly understood. Here, we present a physics-informed 2D conceptual model for tropical convective organization. The model is based on the budget equation of column moist static energy (CMSE) with terms that are parameterized based on diagnosing them in a high-resolution simulation with explicit convection. The conceptual model combines a reaction-diffusion equation, where the reaction term has memory, with a temporal red noise. We find that vertical advection has a strengthening effect on CMSE perturbations, whereas horizontal advection has a mitigating effect on CMSE perturbations. The CMSE tendencies from vertical and horizontal advection terms are larger in magnitude than those from radiation and surface fluxes. The strengthening effect of vertical advection corresponds to a negative gross moist stability (GMS) at short spatiotemporal scales, but the GMS becomes positive when the convection changes from shallow to deep, killing off the growth in CMSE. The conceptual model is faithful in simulating self-aggregation in that it shows a domain-size dependence of aggregation found in many prior works, and its CMSE power spectrum matches that of the high-resolution simulation except for a shallowing of the slope at high wavenumbers. Through analyzing the conceptual model equation, we show that 1) the domain-size dependence of self-aggregation is due to a competition between the strengthening effect of vertical advection and the smoothing effect of horizontal advection, and 2) the combination of temporal red noise and diffusive horizontal advection sets the shape of the CMSE power spectrum. Furthermore, the conceptual model also reproduces power-law distributions of precipitation clusters when precipitation clusters are viewed as thresholded islands on the CMSE topography. Thus, the simple conceptual model captures and helps to explain important aspects of convective self-aggregation and tropical convective organization.

Satellite-based precipitation products (SPPs) with short latencies provide a new opportunity for flood forecasting in ungauged basins. However, the larger uncertainties associated with such near-real-time SPPs can influence the accuracy of the resulting flood forecast. Here we propose a real-time updating method, referred to as “Constrained Runoff Correction (CRC-M)” that is based on the use of multi-source SPPs. The method is based on the hypothesis that the range over different near-real-time SPPs provides insight regarding the approximate range in which the true rainfall value lies, during the current period. Accordingly, the constrained runoff correction is performed in such a way as to be consistent with this range, and with the observed value of discharge at the basin outlet. Evaluation using real-data indicates that the new method performs well, with Nash–Sutcliffe (NS) values of 0.85 and 0.91 during calibration and evaluation, respectively. The necessity and value of imposing constraints is demonstrated by comparing CRC-M against a control, referred to as “Unconstrained Runoff Correction” (URC-S). Experiments indicate that the key factors resulting in good performance are 1) wider constraint ranges, and 2) relatively reliable SPPs. Further, inclusion of redundant information may only result in slight improvements to forecast performance, and can even cause the performance to deteriorate. Overall, the CRC-M method can result in accurate and stable flood forecasts for ungauged basins, without the need for increased model complexity (i.e., the numbers of model parameters).

Partitioning evapotranspiration (ET) into evaporation (E) and transpiration (T) is essential for understanding the global hydrological cycle and improving water resource management. However, ET partitioning in various ecosystems is challenging as some assumptions are restricted to certain areas or plant types. Here, we developed a novel ET partitioning method coupling definitions of leaf and ecosystem water use efficiencies (WUEleaf and WUEeco, respectively). We used 25 eddy covariance flux sites for 196 site-years to evaluate T:ET characteristics of seven plant functional types (PFTs) at different spatiotemporal scales. The results indicated the spatiotemporal characteristics of WUEleaf and WUEeco were not consistent, resulting in T:ET variation in the seven PFTs. Deciduous broadleaf forests had the highest mean annual T:ET (0.67), followed by evergreen broadleaf forests (0.63), grasslands (0.52), evergreen needleleaf forests (0.46), and woody savanna (0.41), and C3 croplands had higher T:ET (0.65) than C4 croplands (0.48). The annual mean leaf area index (LAI) explained about 26% of the variation in T:ET, with the trend in T:ET consistent with the known effects of LAI. The overall trends and magnitude of T:ET in this study were similar to different results of ET partitioning methods globally. Importantly, this method improved T:ET estimation accuracy in vegetation-sparse and water-limited areas. Our novel ET partitioning method is suitable for estimating T:ET at various spatiotemporal scales and provides insight into the conversion of WUE at different scales.

The 2030 Agenda for Sustainable Development aims to reach 17 Sustainable Development Goals (SDGs). The 6th goal (SDGs (6) deals with water security, which refers mainly to water use effi-ciency and water stress. Indeed, water security plays an important role in water-food-energy nexus. This work aims to enhance dam performance under climate change to overcome water scarcity. The study is conducted through the multiobjective Hassan Addakhil dam in Morocco. The novelty of this work is providing hourly precipitation and evaporation data through temporal downscaling and developing a real-time dam management tool. The real-time dam management algorithm is based on a water balance equation and rule curves. The model is coupled with the Hydrologic Modeling System (HEC-HMS). This tool provides information about (i) dam storage, (ii) dam re-lease, (iii) dam evaporation, (iv) dam diversion, (v) spilled water volume, (vi) emergency spilled water volume, (vii) dam inflow, (viii) irrigation demand, (ix) irrigation shortage, (x) dam siltation, (xi) dam hydropower production, (xii) hydropower energy income. The result shows that real-time management can enhance dam management. In this sense, the dam reliability and resilience have increased respectively from 40% to 70% and from 16% to 66%. Besides, the vulnerability re-mained constant.

Lakes account for about 10% of the boreal landscape and are responsible for approximately 30% of biogenic methane emissions. However, its quantification is still of large uncertainty under changing climate conditions. Finland has the densest lake system in the world with most lakes situated in the boreal zone. This study uses a large observational dataset of lake methane concentrations to constrain its methane emissions with an extant process-based lake biogeochemical model. We found that the total current diffusive emission from Finnish lakes is 0.12±0.03 Tg CH yr and will increase by 26-59% by the end of this century. We discovered that while warming lake water and sediment temperature played an important role, the climate impact on ice-on periods was a key indicator to the degree of emission increase in the future. We concluded that these boreal lakes remain as a significant methane source under warming climate in this century.

We present new, densely sampled shear-wave splitting results from southern Minnesota and adjacent areas of neighboring states, sampling the southwestern limit of the Archean Superior Province and straddling the Proterozoic Mid-Continent Rift (MCR). The new measurements include data from the Earthscope Transportable Array (TA) as well as the Superior Province Rifting Earthscope Experiment (SPREE), yielding 99 new station-averaged measurements. The split times show a consistent decrease from 1.1 s in the NE to 0.2 s in the SW, with the lowest values being associated with the Minnesota River Valley Terrane (MRVT). From modelling and other geophysical constraints, we interpret the split time variations to represent variations in fabric strength within a thick lithosphere, rather than lithospheric thinning or a multi-layered effect, and propose that the weak fabric of the MRVT is associated with a different mechanism of formation than elsewhere in the Superior Province. The fast directions we measure range from NNE-SSW to E-W and vary on a shorter length scale than the split times, with a pattern of NE-SW splits that closely follows the axis of the MCR. We interpret this as a perturbation of the net fast direction due to anisotropy in an underplate along the rift.

Coral reefs represent an efficient natural mechanical coastal defense against ocean waves. The focus of this study is the La Saline coral reef, located in the West of La Reunion Island in the Indian Ocean. The area is microtidal and frequently exposed to Southern Ocean swell as well as cyclonic events. The objective of this paper is to provide a better understanding of the coastal defense characteristics of the reef system for a range of Southern Ocean swell events and tides. Pressure sensors were placed across the reef to measure water level fluctuations and to determine gravity wave and infragravity wave components and their transformation across the coral reef. A numerical model (XBeach surf beat), validated using field observations, was used to deepen understanding of wave transformation, wave setup and runup. Field measurements and model outputs show that as gravity waves break over the reef, the reef acts as a low-pass filter. Study results also suggest frequency-dependent dissipation of infragravity waves by bottom-friction. The resulting wave-induced setup is found to be the dominant hydrodynamic component. The setup and runup are each 95% and 71% driven by the significant wave height (HS) with which they increase, and transfer functions relating incident wave characteristics to reef system hydrodynamics are proposed. At a semi-diurnal tidal timescale, the setup and runup are in anti-phase, as the runup is highest in conditions of reduced wave dissipation on the reef flat, corresponding with high tides. These conditions also result in a lower wave setup.

Since 2011, UNESCO - Intergovernmental Oceanographic Commission (IOC) Experts Meetings and CaribeWave exercises have resulted in a variety of tsunami models of credible scenarios that would impact the Caribbean and adjacent regions. However, results generated from such scenarios were not readily available to potential users such as emergency management officials and decision makers. During the 12th Session of the Tsunami and Other Coastal Hazards Warning System for the Caribbean and Adjacent Regions (ICG/CARIBE-EWS) in May 2017, a formal recommendation was adopted for the working group on Hazard Assessment to compile the aforementioned tsunami scenarios with their associated tsunami energy plots in addition to other valuable tsunami data products from NOAA’s National Centers for Environmental Information (NCEI), and World Data Service (WDS) for Geophysics. In response to this recommendation, the Caribbean and Adjacent Regions Tsunami Sources and Models (CATSAM) map viewer was developed by NCEI/WDS and the Universidad Nacional, Costa Rica. CATSAM is intended to be a tool for modelers and hazard assessment professionals, based on the UNESCO/IOC led efforts on defining tsunami potential within the region. It provides the seismic parameters to reproduce the scenarios, as well as how they overlap with the Global Historical Tsunami Database developed and maintained by NCEI/WDS. CATSAM currently has 41 defined rupture geometries and 13 energy plots divided into 15 sub-regions. The map viewer was implemented using the ArcGIS API for JavaScript, built upon geospatial services published with ArcGIS Enterprise. While CATSAM is an initiative of the ICG/CARIBE-EWS, upcoming IOC/UNESCO Experts Meetings on tsunami sources for Pacific subregions could provide an augmented collection of tsunami scenarios for other tsunami prone areas of the world.

Each year the PRSN detects ~4,000 earthquakes within and around Puerto Rico, the Virgin Islands and the Eastern Dominican Republic. Given the seismic hazard presented by this earthquake activity it is critical to perform systematic and continuous studies aimed at understanding and mitigating the impacts of earthquakes. The major effects to a site are due to seismic wave amplification at specific frequencies caused by local unconsolidated sediments during strong ground motions. Therefore, it is important to recognize and mitigate these. The Puerto Rico Seismic Network (PRSN) at the University of Puerto Rico, Mayagüez (Recinto Universitario de Mayagüez [RUM]) and the Puerto Rico Strong Motion Program (PRSMP), in collaboration with the United States Geological Survey (USGS) are conducting a passive-source seismic experiment to investigate the potential for seismic amplification by soils in Mayagüez, Puerto Rico. The goal of this experiment is to quantify the potential soil amplification in Mayagüez, which is located in the western portion of the island. This region experienced significant damage from shaking in the 1918, 7.3 Mw earthquake offshore of western Puerto Rico, making it a prime target for a pilot study to examine soil amplification. Local soil and bedrock conditions in Mayagüez are similar to other areas of the Caribbean, so results will have implications throughout the region. For this study, eleven L-22 sensors with Reftek RT130 recorders were installed in April 2019 to collect data for a period of six months. Since this time, there have been sixty-one M3 or greater earthquakes in the region per month and six M6.5 or greater teleseisms that should provide data suitable for analysis. Data are currently being analyzed using simple spectral ratios of soil sites to bedrock sites. We will present information about the deployment, experiment goals, and preliminary results. The results of this experiment will provide data to refine future hazard mapping and ground motion models of the island.

The Pāpaku fault zone, drilled at IODP Site U1518, is an active splay fault in the frontal accretionary wedge of the Hikurangi Margin. In logging-while-drilling data, the 33 m-thick fault zone exhibits mixed modes of deformation associated with a trend of downward decreasing density, P-wave velocity and resistivity. Methane hydrate are observed from ~30-585 mbsf, including within and surrounding the fault zone. Hydrate accumulations are vertically discontinuous and occur throughout the entire logged section at low to moderate saturation in silty and sandy cm-thick layers. We argue that the hydrate distribution implies that the methane is not sourced from fluid flow along the fault but instead by local diffusion. This, combined with geophysical observations and geochemical measurements from Site U1518, suggests that the fault is not a focused migration pathway for deeply-sourced fluids and that the near-seafloor Pāpaku fault zone has little to no active fluid flow.

Equilibrium climate sensitivity (ECS) is the global temperature change expected after doubling atmospheric CO2 concentration. This Commentary reviews how Sherwood et al. (2020) used Bayesian statistics and evidence from climate-process physics, historical observations, and earlier proxies to reduce the likely range of ECS from 1.5-4.5 K to 2.6-4.1 K. They may have overestimated ECS by adding non-equilibrium short-term adjustments to the radiative forcing of greenhouse gases and by underestimating the effect of solar irradiance and aerosols. Two alternative periods during the Holocene show that forcing by agents other than CO2 was significant and requires further research.

The development of atmospheric parameterizations based on neural networks is often hampered by numerical instability issues. Previous attempts to replicate these issues in a toy model have proven ineffective. We introduce a new toy model for atmospheric dynamics, which consists in an extension of the Lorenz'63 model to a higher dimension. While neural networks trained on a single orbit can easily reproduce the dynamics of the Lorenz'63 model, they fail to reproduce the dynamics of the new toy model, leading to unstable trajectories. Instabilities become more frequent as the dimension of the new model increases, but are found to occur even in very low dimension. Training the neural network on a different learning sample, based on Latin Hypercube Sampling, solves the instability issue. Our results suggest that the design of the learning sample can significantly influence the stability of dynamical systems driven by neural networks.

Solid state convection is expected to influence the evolution and the geological activity of Ganymede [1]. The spatial distribution of tidal dissipation could influence the temperature structure of the outer ice shell and, likely, the internal processes and the geological activity. We investigate the influence of the tidal dissipation on a convective ice shell of Ganymede. We use the finite-element code ASPECT [2] to solve the Boussinesq fluid equations of the conservation of continuity, momentum and energy to simulate solid-state convection within the ice shell of Ganymede. The numerical simulations are performed in a 2-dimensional cylindrical geometry. We adopt a temperature-dependent Newtonian viscosity for the water ice, assuming diffusion creep. The spatial distribution of the tidal dissipation rate is computed adopting a Maxwellian material model [3, 4]. Preliminary results show how the convective patterns, and the thermal plumes are influenced by the spatial distribution of the tidal dissipation. We also discuss how radar sounder investigations with RIME instrument [5] on board of the ESA’s JUICE mission in combination with radio science measurements of the gravity field by 3GM experiment [6] could characterize the thermal structure of Ganymede’s ice shell.

The cycling of carbon within the earth system is intrinsically linked with major nutrients, notably nitrogen and phosphorus, due to the tendency of these elements to limit the productivity of terrestrial ecosystems. To understand the response of the carbon cycle to global change pressures, models must integrate Carbon-Nitrogen-Phosphorus cycles. Whilst such models exist, to-date these have focused on natural and semi-natural ecosystems. Agriculture results in significant modification to natural biogeochemical cycling, and currently represents approximately 37% of land-use. With the projected increase in global food demand over the 21st century, this area is expected to increase. It is therefore critical to understand and simulate biogeochemical cycling in both natural and agricultural systems, and the transition between these, to estimate ecosystem response to environmental change. In this study we present an integrated C-N-P model including both natural and agricultural temperate ecosystems. The N14CP model has been developed to include representation of both arable and grassland systems, with the inclusion of agricultural management practices such as fertilizer application, crop removal, grazing and yield estimation. The model has been tested both spatially and temporally using a range of long-term experimental sites across Northern-Europe, and applied at both local and national scales. We use the model to assess impacts of land-use change and management on long-term nutrient cycling, and discuss the implications of this for sustainable agriculture and ecosystem functioning.