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USGS2022

Nearshore bathymetric changes along the Alaska Beaufort Sea coast and possible physical drivers

Erosion rates along Alaska's Beaufort Sea coast, among the highest in the world, are negatively impacting communities, industrial and military infrastructure, and wildlife habitat. Decreasing maximal winter ice extent and increasing summer open water duration and extent in the Beaufort Sea may be making the coast more vulnerable to destructive storm waves than during recent, colder, icier decades. Previous studies of Beaufort Sea coastal change have been limited to subaerial analyses of the shoreline. Here we describe nearshore seafloor change by comparing post-World War II (WWII) (1945-53) bathymetry data to recently acquired (1985–2018) bathymetry data and relate the observed seafloor change to adjacent shoreline change near Utqiagvik, within Stefansson Sound, and immediately west of Barter Island and Kaktovik. Within the Utqiagvik region, seabed erosion was generally highest (>1.0 m of loss) offshore of Point Barrow and along the eastern end of the Tapkaluk Islands, while there were lesser amounts of deposition (<0.5 m of gain) within the protected waters of Elson Lagoon. Sedimentation was generally highest offshore of Point Barrow, in a region of converging currents, and on the landward side of the barrier islands and spits fronting Elson Lagoon, which is likely related to a regional trend of westerly sediment transport and landward migration of the barrier islands. Within Stefansson Sound, perhaps the most notable changes from post-WWII bathymetry data compared to recent data are a switch from mixed, low erosion and deposition in 1997 to low deposition (<0.5 m) in 2018 east of the Boulder Patch, a switch from low erosion in 1997 to neutral depth change in 2018 in the channel between the north and south Boulder Patch areas, and higher deposition from 1997 to 2018 landward of the rapidly retreating barrier islands along the Sound's northern border. At Barter Island, high erosion near north-facing shorelines and high deposition near west-facing shorelines generally matched shoreline changes. One of our goals is to identify possible processes responsible for the depth changes we quantified. Using simple metrics that relate sediment characteristics with modeled waves and non-wave induced currents, we show that sediment resuspension and transport by both wave and non-wave driven currents likely contribute to the overall patterns of change within the ∼13 m isobath along the open coast, and that the influence of wave action affecting sediment transport is expanding seaward.

Alaska↗

USGS2008

Abyssal ostracods from the South and Equatorial Atlantic Ocean: Biological and paleoceanographic implications

We report the distribution of ostracods from ???5000 m depth from the Southeast and Equatorial Atlantic Ocean recovered from the uppermost 10 cm of minimally disturbed sediments taken by multiple-corer during the R/V Meteor DIVA2 expedition M63.2. Five cores yielded the following major deep-sea genera: Krithe, Henryhowella, Poseidonamicus, Legitimocythere, Pseudobosquetina, and Pennyella. All genera are widely distributed in abyssal depths in the world's oceans and common in Cenozoic deep-sea sediments. The total number of ostracod specimens is higher and ostracod shell preservation is better near the sediment-water interface, especially at the 0-1 cm core depths. Core slices from ???5 to 10 cm were barren or yielded a few poorly preserved specimens. The DIVA2 cores show that deep-sea ostracod species inhabit corrosive bottom water near the carbonate compensation depth (CCD) even though their calcareous valves are rarely preserved as fossils in sediment cores due to postmortem dissolution. Their occurrence at great water depths may partially explain the well-known global distributions of major deep-sea taxa in the world's oceans, although further expeditions using minimal-disturbance sampling devices are needed to fill geographic gaps. ?? 2008 Elsevier Ltd. All rights reserved.

Deep-Sea Research Part I: Oceanographic Research P↗

USGS2025

Refining the earthquake history of south-central Alaska through lake records

The Alaska–Aleutian subduction zone (AASZ) is one of the world's most seismically active plate boundaries and the source of the 1964 M w 9.2 Great Alaska earthquake–the second largest instrumentally recorded earthquake in the world. Understanding the nature and frequency of such earthquakes is necessary for seismic and tsunami hazard assessment, but instrumental and historical records that span less than 150 years are too short to allow a statistically reliable analysis of earthquake recurrence times. This calls for studies of evidence of past earthquakes, extending the earthquake catalog further back in time. Subduction-zone paleoseismology in south-central Alaska is predominantly based on coastal evidence of land-level changes and tsunamis generated by megathrust earthquakes and preserved in the geological record. A complementary approach is lacustrine paleoseismology, which is still a relatively young discipline in Alaska. However, globally, lake basins are well-established high-resolution and continuous recorders of paleoseismic activity along subduction zones, relying on the identification of underwater landslide deposits and turbidites generated by seismic shaking. As a result, lake basins not only register ground shaking from megathrust earthquakes, but also from intraslab and crustal earthquakes, which are typically not accompanied by significant land-level changes. In this review paper, we combine coastal and lacustrine paleoseismology approaches to refine the south-central Alaskan earthquake history by comparing the paleoseismic records from two lakes (i.e., Eklutna Lake, located in the Chugach Mountain Range, and Skilak Lake, situated on the Kenai Peninsula) with the coastal and crustal earthquake catalog in Alaska. The resulting age ranges of all known megathrust earthquakes involving the Alaskan megathrust between the Kodiak and Prince William Sound (PWS) sections are more precise and accurate for the last 1.3 kyrs BP than the previously published age ranges from coastal records. As a result, this study supports the following key conclusions: (1) The 1964 CE earthquake was an exceptionally strong and unique event in the last 2000 years, rupturing the PWS, Kenai, Barren Islands, and Kodiak sections simultaneously. (2) The high-resolution and seasonal markings of the varved lake records now disentangle for the first time closely timed earthquakes, which was not possible based on the coastal evidence alone. (3) No persistent megathrust rupture boundaries exist. So, the possibility of a full rupture of the entire eastern AASZ, from PWS to Semidi cannot be excluded. (4) The rupture pattern in the eastern AASZ reveals superimposed cycles of multi-asperity ruptures (1964 earthquake) and clustered complementary partial ruptures, or rupture cascades. (5) The PWS section hosts the largest asperity in the eastern AASZ. (6) The shaking record of megathrust earthquakes indicates a time-dependent (quasiperiodic) behavior for the study area, but the observation of complementary clusters means that the hazards will not drop to zero but instead may even increase for a neighboring section. (7) The time-independent behavior of intraplate earthquakes implies that the intraslab hazard did not decrease following the 2016 and 2018 earthquakes. This study utilizes an integrated approach for subduction zone paleoseismology as a solution for unraveling recurrence and rupture patterns in Alaska, which can be applied worldwide.

Alaska↗

USGS2019

Optimal spatial allocation of control effort to manage invasives in the face of imperfect detection and misclassification

Imperfect detection and misclassification errors are often ignored in the context of invasive species management. Here we present an approach that combines spatially explicit models and an optimization technique to design optimal search and destroy strategies based on noisy monitoring observations. We focus on two invasive plants, melaleuca ( Melaleuca quinquenervia ) and Old World climbing fern ( Lygodium microphyllum ), which continue to cause important damages to the Everglades ecosystem. We present a methodological framework that combines Hidden Markov Random Field (HMRF, initially developed for image analysis) and linear programming to optimally search for invasive species. A benefit of this approach is that it accounts for the spatial structure of the system by using a spatially explicit modeling approach (i.e. HMRF), and does not require repeated visits to model the probability of occurrence of species. We found on simulated cases that our approach can lead to substantial improvements in control efficiency when compared to state of the art model-free approaches. For example, in the case of the old world fern, simulations showed that the optimal strategy would allow managers to control up to 34% more sites than with model-free approaches that ignored misclassification and imperfect detection. For melaleuca it was possible to control up to 20% more sites. The vast increase in imagery data obtained from different sources (e.g. unmanned aerial systems, and satellite) provides great opportunities to improve management of natural resources by applying modern computational methods such as the one we present. Our approach can substantially increases the efficiency of invasive species control by accounting for imperfect detection, misclassification error and the spatial structure of the system. Our approach is applicable to other systems and problems, for example it could be applied to the control of plant pathogens, or optimal extraction of resources (e.g. minerals or biological resources).

Ecological Modelling↗

USGS2007

Monitoring mangrove forest dynamics of the Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000

Mangrove forests in many parts of the world are declining at an alarming rate—possibly even more rapidly than inland tropical forests. The rate and causes of such changes are not known. The forests themselves are dynamic in nature and are undergoing constant changes due to both natural and anthropogenic forces. Our research objective was to monitor deforestation and degradation arising from both natural and anthropogenic forces. We analyzed multi-temporal satellite data from 1970s, 1990s, and 2000s using supervised classification approach. Our spatio-temporal analysis shows that despite having the highest population density in the world in its periphery, areal extent of the mangrove forest of the Sundarbans has not changed significantly (approximately 1.2%) in the last ∼25 years. The forest is however constantly changing due to erosion, aggradation, deforestation and mangrove rehabilitation programs. The net forest area increased by 1.4% from the 1970s to 1990 and decreased by 2.5% from 1990 to 2000. The change is insignificant in the context of classification errors and the dynamic nature of mangrove forests. This is an excellent example of the co-existence of humans with terrestrial and aquatic plant and animal life. The strong commitment of governments under various protection measures such as forest reserves, wildlife sanctuaries, national parks, and international designations, is believed to be responsible for keeping this forest relatively intact (at least in terms of area). While the measured net loss of mangrove forest is not that high, the change matrix shows that turnover due to erosion, aggradation, reforestation and deforestation was much greater than net change. The forest is under threat from natural and anthropogenic forces leading to forest degradation, primarily due to top-dying disease and over-exploitation of forest resources.

Estuarine, Coastal and Shelf Science↗

USGS2016

Bayesian estimation of magma supply, storage, and eruption rates using a multiphysical volcano model: Kīlauea Volcano, 2000–2012

Estimating rates of magma supply to the world's volcanoes remains one of the most fundamental aims of volcanology. Yet, supply rates can be difficult to estimate even at well-monitored volcanoes, in part because observations are noisy and are usually considered independently rather than as part of a holistic system. In this work we demonstrate a technique for probabilistically estimating time-variable rates of magma supply to a volcano through probabilistic constraint on storage and eruption rates. This approach utilizes Bayesian joint inversion of diverse datasets using predictions from a multiphysical volcano model, and independent prior information derived from previous geophysical, geochemical, and geological studies. The solution to the inverse problem takes the form of a probability density function which takes into account uncertainties in observations and prior information, and which we sample using a Markov chain Monte Carlo algorithm. Applying the technique to Kīlauea Volcano, we develop a model which relates magma flow rates with deformation of the volcano's surface, sulfur dioxide emission rates, lava flow field volumes, and composition of the volcano's basaltic magma. This model accounts for effects and processes mostly neglected in previous supply rate estimates at Kīlauea, including magma compressibility, loss of sulfur to the hydrothermal system, and potential magma storage in the volcano's deep rift zones. We jointly invert data and prior information to estimate rates of supply, storage, and eruption during three recent quasi-steady-state periods at the volcano. Results shed new light on the time-variability of magma supply to Kīlauea, which we find to have increased by 35–100% between 2001 and 2006 (from 0.11–0.17 to 0.18–0.28 km 3 /yr), before subsequently decreasing to 0.08–0.12 km 3 /yr by 2012. Changes in supply rate directly impact hazard at the volcano, and were largely responsible for an increase in eruption rate of 60–150% between 2001 and 2006, and subsequent decline by as much as 60% by 2012. We also demonstrate the occurrence of temporal changes in the proportion of Kīlauea's magma supply that is stored versus erupted, with the supply “surge” in 2006 associated with increased accumulation of magma at the summit. Finally, we are able to place some constraints on sulfur concentrations in Kīlauea magma and the scrubbing of sulfur by the volcano's hydrothermal system. Multiphysical, Bayesian constraint on magma flow rates may be used to monitor evolving volcanic hazard not just at Kīlauea but at other volcanoes around the world.

Hawai'i↗

USGS2006

Concentration and distribution of sixty-one elements in coals from DPR Korea

Fifty coal samples (28 anthracite and 22 lignites) were collected from both main and small coal mines in DPR Korea prioritized by resource distribution and coal production. The concentrations of 61 elements in 50 coal samples were determined by several multielement and element-specific techniques, including inductively coupled plasma atomic emission spectrometry (ICP-AES), and inductively coupled plasma mass spectrometry (ICP-MS), ion chromatogram (IC), cold-vapor atomic absorption spectrometry (CV-AAS), and hydride generation atomic absorption spectrometry (HGAAS). The ranges, arithmetic means and geometric means of concentrations of these elements are presented. A comparison with crustal abundances (Clarke values) shows that some potentially hazardous elements in the coals of DPR Korea are highly enriched Li, B, S, Cl, Zn, As, Se, Cd, Sn, Sb, W, Te, Hg, Ag, Pb, and La, Ce, Dy, Tm, Ge, Mo, Cs, Tl, Bi, Th and U are moderately enriched. A comparison of ranges and means of elemental concentrations in DPR Korea, Chinese, and world coals shows the ranges of most elements in DPR Korea coals are very close to the ranges of world coals. Arithmetic means of most elements in DPR Korea coals are close to that of American coals. Most elements arithmetic means are higher in Jurassic and Paleogene coals than coals of other ages. In DPR Korea coals, only seven elements in early Permian coals are higher than other periods: Li, Zn, Se, Cd, Hg, Pb, and Bi. Only five elements B, As, Sr, Mo, W in Neogene coals have arithmetic means higher than others. SiO2 and Al2O 3 in ashes are more than 70% except six samples. The correlation between ash yields and major elements from high to low is in the order of Si>Al>Ti>K>Mg>Fe>Na>Ca>P>S. Most elements have high positive correlation with ash (r>0.5) and show high inorganic affinity. ?? 2005 Elsevier Ltd. All rights reserved.

Fuel↗

USGS2007

Automated classifications of topography from DEMs by an unsupervised nested-means algorithm and a three-part geometric signature

An iterative procedure that implements the classification of continuous topography as a problem in digital image-processing automatically divides an area into categories of surface form; three taxonomic criteria–slope gradient, local convexity, and surface texture–are calculated from a square-grid digital elevation model (DEM). The sequence of programmed operations combines twofold-partitioned maps of the three variables converted to greyscale images, using the mean of each variable as the dividing threshold. To subdivide increasingly subtle topography, grid cells sloping at less than mean gradient of the input DEM are classified by designating mean values of successively lower-sloping subsets of the study area (nested means) as taxonomic thresholds, thereby increasing the number of output categories from the minimum 8 to 12 or 16. Program output is exemplified by 16 topographic types for the world at 1-km spatial resolution (SRTM30 data), the Japanese Islands at 270 m, and part of Hokkaido at 55 m. Because the procedure is unsupervised and reflects frequency distributions of the input variables rather than pre-set criteria, the resulting classes are undefined and must be calibrated empirically by subsequent analysis. Maps of the example classifications reflect physiographic regions, geological structure, and landform as well as slope materials and processes; fine-textured terrain categories tend to correlate with erosional topography or older surfaces, coarse-textured classes with areas of little dissection. In Japan the resulting classes approximate landform types mapped from airphoto analysis, while in the Americas they create map patterns resembling Hammond's terrain types or surface-form classes; SRTM30 output for the United States compares favorably with Fenneman's physical divisions. Experiments are suggested for further developing the method; the Arc/Info AML and the map of terrain classes for the world are available as online downloads.

Geomorphology↗

USGS2024

Pliocene Model Intercomparison Project Phase 3 (PlioMIP3) – Science plan and experimental design

The Pliocene Model Intercomparison Project (PlioMIP) was initiated in 2008. Over two phases PlioMIP has helped co-ordinate the experimental design and publication strategy of the community, which has included an increasing number of climate models and modelling groups from around the world. It has engaged with palaeoenvironmental scientists to foster new data synthesis supporting the construction of new model boundary conditions, as well as to facilitate new data-model comparisons. The work has advanced our understanding of Pliocene climates and environments, enhanced our knowledge regarding the ability of complex climate and Earth System models to accurately simulate climate change, and helped to refine our estimates of how sensitive the climate system is to forcing conditions. In this community protocol paper, we outline the scientific plan for PlioMIP Phase 3 (PlioMIP3). This plan provides the required guidance to participating modelling groups from around the world to successfully set up and perform PlioMIP3 climate model experiments. The project is open to new participants from the scientific community (both from the climate modelling and geosciences communities). In PlioMIP3, we retain the PlioMIP2 Core experiments ( Eoi 400 , E 280 ) and extend the Core requirements to include either an experiment focussed on the Early Pliocene or an alternative Late Pliocene simulation (or both). These additions (a) allow a comparison of Early and Late Pliocene warm intervals and help build research connections and synergy with the MioMIP (Miocene Model Intercomparison Project - also known as DeepMIP-Miocene) and PlioMioVAR projects (Pliocene-Miocene Variability Working Group), and (b) create an alternative time slice simulation for 3.205 Ma (MIS KM5c) through removal of some of the largest palaeogeographic differences introduced between PlioMIP1 and 2 resulting in minimal land-sea mask variations from the modern. In addition, we present ten optional experiments designed to enhance our assessment of climate sensitivity and to explore the uncertainty in greenhouse gas-related forcing. For the first time, we introduce orbital sensitivity experiments into the science plan, as well as simulations incorporating dynamic vegetation-climate feedbacks and an experiment designed to examine the potential significance of East Antarctic Ice Sheet boundary condition uncertainty. These changes enhance palaeo-to-future scientific connections and enable an exploration of the significance of palaeogeographic uncertainties on climate simulations.

Global and Planeatary Change↗

USGS2015

Rare earth elements in sedimentary phosphate deposits: Solution to the global REE crisis?

The critical role of rare earth elements (REEs), particularly heavy REEs (HREEs), in high-tech industries has created a surge in demand that is quickly outstripping known global supply and has triggered a worldwide scramble to discover new sources. The chemical analysis of 23 sedimentary phosphate deposits (phosphorites) in the United States demonstrates that they are significantly enriched in REEs. Leaching experiments using dilute H 2 SO 4 and HCl, extracted nearly 100% of their total REE content and show that the extraction of REEs from phosphorites is not subject to the many technological and environmental challenges that vex the exploitation of many identified REE deposits. Our data suggest that phosphate rock currently mined in the United States has the potential to produce a significant proportion of the world's REE demand as a byproduct. Importantly, the size and concentration of HREEs in some unmined phosphorites dwarf the world's richest REE deposits. Secular variation in phosphate REE contents identifies geologic time periods favorable for the formation of currently unrecognized high-REE phosphates. The extraordinary endowment, combined with the ease of REE extraction, indicates that such phosphorites might be considered as a primary source of REEs with the potential to resolve the global REE (particularly for HREE) supply shortage.

Gondwana Research↗

USGS2025

Cyanotoxin and domoic acid occurrence, relation with salinity, and potential recreational health risks in U.S. coasts in the 2015 US EPA National Coastal Condition Assessment

In the first nationwide study of cyanotoxins in U.S. estuaries, algal toxins, cyanotoxins, chlorophyll, and salinity were measured in samples collected during the National Coastal Condition Assessment 2015. Anatoxin-a (ANAA), cylindrospermopsin (CYLS), domoic acid (DMAC), and microcystins (MCs) were detected by LC/MS/MS in 0.6, 0.9, 8.3, and 2.0 % of samples with mean concentrations of detections of 0.13, 0.13, 0.53, and 0.49 µg/L, respectively. MCs by ELISA were also evaluated, and 4.0 % of samples had measurable MCs with a mean of 0.78 µg/L. While ANAA and CYLS were detected south of 40° latitude, MCs by ELISA and DMAC occurred nationwide. Results were compared to freshwater recreational health thresholds from the World Health Organization and US Environmental Protection Agency to evaluate potential recreational exposure to MCs and CYLS since marine thresholds do not currently exist. Cyanotoxins were categorized using the 2021 World Health Organization Alert Level Framework for recreational exposure with 99.4, 99.1, 94.7, 98.0, and 44.7 % of samples being at the Vigilance Level for ANAA, CYLS, MCs (ELISA and LC/MS/MS), and chlorophyll, respectively with the remaining samples at Alert Level 1. Chlorophyll had 19.9 and 9.9 % of samples at Alert Level 1 and Alert Level 2, respectively. All cyanotoxins were below US EPA health advisory thresholds. ANAA, CYLS, DMAC, and MCs by ELISA were detected in samples with a wide range of salinities, while MCs by LC/MS/MS only occurred in samples with salinity <5 part per thousand (PPT). The source of cyanotoxins is likely a combination of inland transport and in situ estuarine production.

contiguous United States↗

USGS2013

Modeling rain-fed maize vulnerability to droughts using the standardized precipitation index from satellite estimated rainfall—Southern Malawi case study

During 1990s, disaster risk reduction emerged as a novel, proactive approach to managing risks from natural hazards. The World Bank, USAID, and other international donor agencies began making efforts to mainstream disaster risk reduction in countries whose population and economies were heavily dependent on rain-fed agriculture. This approach has more significance in light of the increasing climatic hazard patterns and the climate scenarios projected for different hazard prone countries in the world. The Famine Early Warning System Network (FEWS NET) has been monitoring the food security issues in the sub-Saharan Africa, Asia and in Haiti. FEWS NET monitors the rainfall and moisture availability conditions with the help of NOAA RFE2 data for deriving food security status in Africa. This paper highlights the efforts in using satellite estimated rainfall inputs to develop drought vulnerability models in the drought prone areas in Malawi. The satellite RFE2 based SPI corresponding to the critical tasseling and silking phases (in the months of January, February, and March) were statistically regressed with drought-induced yield losses at the district level. The analysis has shown that the drought conditions in February and early March lead to most damage to maize yields in this region. The district-wise vulnerabilities to drought were upscaled to obtain a regional maize vulnerability model for southern Malawi. The results would help in establishing an early monitoring mechanism for drought impact assessment, give the decision makers additional time to assess seasonal outcomes, and identify potential food-related hazards in Malawi.

International Journal of Disaster Risk Reduction↗

USGS2025

Comparing SMART and ELECTRE methods for multi-criteria decision analysis: A case study evaluating conservation strategies

Tradeoffs are part of the inherent challenge of making decisions. Defaulting to a prevalent method can mask methodological variation and potential improvement in decision quality. We applied and compared methods for multi-criteria decision analysis (MCDA) in real-world environmental planning. Decision makers at a global conservation organization formed teams to review and prioritize the allocation of resources across a set of existing strategies across seven teams. Each team evaluated and rated strategies based on a common scale composed of weighted objectives and criteria. Sensitivity analysis included implementing two different MCDA methods, varying strategy ratings, and using two different criteria weighting techniques. The MCDA methods were SMART (Simple Multi-Attribute Rating Technique) and ELECTRE (ELimination and Choice Expressing The REality). We tested user satisfaction between methods, overall rankings between methods, and whether MCDA improved the decision-making process. The methods did not differ in most comparisons, although participants were more likely to use the SMART method in future tradeoff decisions. We found evidence of rank correlation between methods. Lastly, the teams’ final recommendations were consistent with MCDA results. This study highlights the advantages and disadvantages of MCDA in real-world applications.

Environmental and Sustainability Indicators↗

USGS2017

Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

The automation of agricultural mapping using satellite-derived remotely sensed data remains a challenge in Africa because of the heterogeneous and fragmental landscape, complex crop cycles, and limited access to local knowledge. Currently, consistent, continent-wide routine cropland mapping of Africa does not exist, with most studies focused either on certain portions of the continent or at most a one-time effort at mapping the continent at coarse resolution remote sensing. In this research, we addressed these limitations by applying an automated cropland mapping algorithm (ACMA) that captures extensive knowledge on the croplands of Africa available through: (a) ground-based training samples, (b) very high (sub-meter to five-meter) resolution imagery (VHRI), and (c) local knowledge captured during field visits and/or sourced from country reports and literature. The study used 16-day time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) composited data at 250-m resolution for the entire African continent. Based on these data, the study first produced accurate reference cropland layers or RCLs (cropland extent/areas, irrigation versus rainfed, cropping intensities, crop dominance, and croplands versus cropland fallows) for the year 2014 that provided an overall accuracy of around 90% for crop extent in different agro-ecological zones (AEZs). The RCLs for the year 2014 (RCL2014) were then used in the development of the ACMA algorithm to create ACMA-derived cropland layers for 2014 (ACL2014). ACL2014 when compared pixel-by-pixel with the RCL2014 had an overall similarity greater than 95%. Based on the ACL2014, the African continent had 296 Mha of net cropland areas (260 Mha cultivated plus 36 Mha fallows) and 330 Mha of gross cropland areas. Of the 260 Mha of net cropland areas cultivated during 2014, 90.6% (236 Mha) was rainfed and just 9.4% (24 Mha) was irrigated. Africa has about 15% of the world’s population, but only about 6% of world’s irrigation. Net cropland area distribution was 95 Mha during season 1, 117 Mha during season 2, and 84 Mha continuous. About 58% of the rainfed and 39% of the irrigated were single crops (net cropland area without cropland fallows) cropped during either season 1 (January-May) or season 2 (June-September). The ACMA algorithm was deployed on Google Earth Engine (GEE) cloud computing platform and applied on MODIS time-series data from 2003 through 2014 to obtain ACMA-derived cropland layers for these years (ACL2003 to ACL2014). The results indicated that over these twelve years, on average: (a) croplands increased by 1 Mha/yr, and (b) cropland fallows decreased by 1 Mha/year. Cropland areas computed from ACL2014 for the 55 African countries were largely underestimated when compared with an independent source of census-based cropland data, with a root-mean-square error (RMSE) of 3.5 Mha. ACMA demonstrated the ability to hind-cast (past years), now-cast (present year), and forecast (future years) cropland products using MODIS 250-m time-series data rapidly, but currently, insufficient reference data exist to rigorously report trends from these results.

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS2007

Joint inversion of high-frequency surface waves with fundamental and higher modes

Joint inversion of multimode surface waves for estimating the shear (S)-wave velocity has received much attention in recent years. In this paper, we first analyze sensitivity of phase velocities of multimodes of surface waves for a six-layer earth model, and then we invert surface-wave dispersion curves of the theoretical model and a real-world example. Sensitivity analysis shows that fundamental mode data are more sensitive to the S-wave velocities of shallow layers and are concentrated on a very narrow frequency band, while higher mode data are more sensitive to the parameters of relatively deeper layers and are distributed over a wider frequency band. These properties provide a foundation of using a multimode joint inversion to define S-wave velocities. Inversion results of both synthetic data and a real-world example demonstrate that joint inversion with the damped least-square method and the singular-value decomposition technique to invert high-frequency surface waves with fundamental and higher mode data simultaneously can effectively reduce the ambiguity and improve the accuracy of S-wave velocities. ?? 2007.

Journal of Applied Geophysics↗

USGS2008

Generation of a pseudo-2D shear-wave velocity section by inversion of a series of 1D dispersion curves

Multichannel Analysis of Surface Waves utilizes a multichannel recording system to estimate near-surface shear (S)-wave velocities from high-frequency Rayleigh waves. A pseudo-2D S-wave velocity (vS) section is constructed by aligning 1D models at the midpoint of each receiver spread and using a spatial interpolation scheme. The horizontal resolution of the section is therefore most influenced by the receiver spread length and the source interval. The receiver spread length sets the theoretical lower limit and any vS structure with its lateral dimension smaller than this length will not be properly resolved in the final vS section. A source interval smaller than the spread length will not improve the horizontal resolution because spatial smearing has already been introduced by the receiver spread. In this paper, we first analyze the horizontal resolution of a pair of synthetic traces. Resolution analysis shows that (1) a pair of traces with a smaller receiver spacing achieves higher horizontal resolution of inverted S-wave velocities but results in a larger relative error; (2) the relative error of the phase velocity at a high frequency is smaller than at a low frequency; and (3) a relative error of the inverted S-wave velocity is affected by the signal-to-noise ratio of data. These results provide us with a guideline to balance the trade-off between receiver spacing (horizontal resolution) and accuracy of the inverted S-wave velocity. We then present a scheme to generate a pseudo-2D S-wave velocity section with high horizontal resolution using multichannel records by inverting high-frequency surface-wave dispersion curves calculated through cross-correlation combined with a phase-shift scanning method. This method chooses only a pair of consecutive traces within a shot gather to calculate a dispersion curve. We finally invert surface-wave dispersion curves of synthetic and real-world data. Inversion results of both synthetic and real-world data demonstrate that inverting high-frequency surface-wave dispersion curves - by a pair of traces through cross-correlation with phase-shift scanning method and with the damped least-square method and the singular-value decomposition technique - can feasibly achieve a reliable pseudo-2D S-wave velocity section with relatively high horizontal resolution. ?? 2008 Elsevier B.V. All rights reserved.

Journal of Applied Geophysics↗

USGS2011

Analysis of group-velocity dispersion of high-frequency Rayleigh waves for near-surface applications

The Multichannel Analysis of Surface Waves (MASW) method is an efficient tool to obtain the vertical shear (S)-wave velocity profile using the dispersive characteristic of Rayleigh waves. Most MASW researchers mainly apply Rayleigh-wave phase-velocity dispersion for S-wave velocity estimation with a few exceptions applying Rayleigh-wave group-velocity dispersion. Herein, we first compare sensitivities of fundamental surface-wave phase velocities with group velocities with three four-layer models including a low-velocity layer or a high-velocity layer. Then synthetic data are simulated by a finite difference method. Images of group-velocity dispersive energy of the synthetic data are generated using the Multiple Filter Analysis (MFA) method. Finally we invert a high-frequency surface-wave group-velocity dispersion curve of a real-world example. Results demonstrate that (1) the sensitivities of group velocities are higher than those of phase velocities and usable frequency ranges are wider than that of phase velocities, which is very helpful in improving inversion stability because for a stable inversion system, small changes in phase velocities do not result in a large fluctuation in inverted S-wave velocities; (2) group-velocity dispersive energy can be measured using single-trace data if Rayleigh-wave fundamental-mode energy is dominant, which suggests that the number of shots required in data acquisition can be dramatically reduced and the horizontal resolution can be greatly improved using analysis of group-velocity dispersion; and (3) the suspension logging results of the real-world example demonstrate that inversion of group velocities generated by the MFA method can successfully estimate near-surface S-wave velocities.

Journal of Applied Geophysics↗

USGS2006

Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrologic models and in land surface parameterization schemes of atmospheric models. The MOPEX science strategy involves three major steps: data preparation, a priori parameter estimation methodology development, and demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrologic basins in the United States (US) and in other countries. This database is being continuously expanded to include more basins in all parts of the world. A number of international MOPEX workshops have been convened to bring together interested hydrologists and land surface modelers from all over world to exchange knowledge and experience in developing a priori parameter estimation techniques. This paper describes the results from the second and third MOPEX workshops. The specific objective of these workshops is to examine the state of a priori parameter estimation techniques and how they can be potentially improved with observations from well-monitored hydrologic basins. Participants of the second and third MOPEX workshops were provided with data from 12 basins in the southeastern US and were asked to carry out a series of numerical experiments using a priori parameters as well as calibrated parameters developed for their respective hydrologic models. Different modeling groups carried out all the required experiments independently using eight different models, and the results from these models have been assembled for analysis in this paper. This paper presents an overview of the MOPEX experiment and its design. The main experimental results are analyzed. A key finding is that existing a priori parameter estimation procedures are problematic and need improvement. Significant improvement of these procedures may be achieved through model calibration of well-monitored hydrologic basins. This paper concludes with a discussion of the lessons learned, and points out further work and future strategy. ?? 2005 Elsevier Ltd. All rights reserved.

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