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At least 1,675 records · Page 93Linked to original sources

USGS2017

A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing

Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying cyanoHABs in multiple water bodies and across geo-political boundaries. An assessment method was developed using MEdium Resolution Imaging Spectrometer (MERIS) imagery to quantify cyanoHAB surface area extent, transferable to different spatial areas, in Florida, Ohio, and California for the test period of 2008 to 2012. Temporal assessment was used to evaluate changes in satellite resolvable inland waterbodies for each state of interest. To further assess cyanoHAB risk within the states, the World Health Organization’s (WHO) recreational guidance level thresholds were used to categorize surface area of cyanoHABs into three risk categories: low, moderate, and high-risk bloom area. Results showed that in Florida, the area of cyanoHABs increased largely due to observed increases in high-risk bloom area. California exhibited a slight decrease in cyanoHAB extent, primarily attributed to decreases in Northern California. In Ohio (excluding Lake Erie), little change in cyanoHAB surface area was observed. This study uses satellite remote sensing to quantify changes in inland cyanoHAB surface area across numerous water bodies within an entire state. The temporal assessment method developed here will be relevant into the future as it is transferable to the Ocean Land Colour Instrument (OLCI) on Sentinel-3A/3B missions.

California, Florida, Ohio↗

USGS2022

Review of harmful algal blooms effects on birds with implications for avian wildlife in the Chesapeake Bay region

The Chesapeake Bay, along the mid-Atlantic coast of North America, is the largest estuary in the United States and provides critical habitat for wildlife. In contrast to point and non-point source release of pesticides, metals, and industrial, personal care and household use chemicals on biota in this watershed, there has only been scant attention to potential exposure and effects of algal toxins on wildlife in the Chesapeake Bay region. As background, we first review the scientific literature on algal toxins and harmful algal bloom (HAB) events in various regions of the world that principally affected birds, and to a lesser degree other wildlife. To examine the situation for the Chesapeake, we compiled information from government reports and databases summarizing wildlife mortality events for 2000 through 2020 that were associated with potentially toxic algae and HAB events. Summary findings indicate that there have been few wildlife mortality incidents definitively linked to HABs, other mortality events that were suspected to be related to HABs, and more instances in which HABs may have indirectly contributed to or occurred coincident with wildlife mortality. The dominant toxins found in the Chesapeake Bay drainage that could potentially affect wildlife are microcystins, with concentrations in water approaching or exceeding human-based thresholds for ceasing recreational use and drinking water at a number of locations. As an increasing trend in HAB events in the U.S. and in the Chesapeake Bay have been reported, additional information on HAB toxin exposure routes, comparative sensitivity among species, consequences of sublethal exposure, and better diagnostic and risk criteria would greatly assist in predicting algal toxin hazard and risks to wildlife.

Maryland, Virginia↗

USGS2025

Practical application of time-lapse camera imagery to develop water-level data for three hydrologic monitoring sites in Wisconsin during water year 2020

Using camera imagery to measure water level (camera-stage) is a well-researched area of study. Previous camera-stage studies have shown promising results when implementing this technology with tight constraints on test conditions. However, there is a need for a more comprehensive evaluation of the extensibility of camera-stage to practical applications. Therefore, the aim of this study was to test a camera-stage method under a wide variety of test conditions to better understand the successes and challenges of using this technology in real-world scenarios. In this study, this approach was tested during Water Year 2020 at three existing U.S. Geological Study (USGS) stream gaging stations in south central Wisconsin that had existing USGS water-level instrumentation. The specific reference objects tested were white pipes and a concrete wall. Since successful application of camera-stage relies on use of suitable images, all captured images in this study were visually inspected to determine suitability for application of camera-stage. Camera-stage measurements were then computed only on images deemed suitable and the results were compared with ground-truth stage values to determine the accuracy. For the purposes of this study, camera-stage values within ±0.10 ft of the actual stage were considered acceptable. One major challenge highlighted was the potential difficulty in obtaining suitable imagery, with the proportion of suitable images varying greatly between the four trials from 38 % to 92 %. The results from applying camera-stage to suitable images were encouraging though, with 79 % to 99 % of evaluated camera-stage values qualifying as acceptable among the four test trials.

Wisconsin↗

USGS2010

Impact craters on Titan

Five certain impact craters and 44 additional nearly certain and probable ones have been identified on the 22% of Titan's surface imaged by Cassini's high-resolution radar through December 2007. The certain craters have morphologies similar to impact craters on rocky planets, as well as two with radar bright, jagged rims. The less certain craters often appear to be eroded versions of the certain ones. Titan's craters are modified by a variety of processes including fluvial erosion, mass wasting, burial by dunes and submergence in seas, but there is no compelling evidence of isostatic adjustments as on other icy moons, nor draping by thick atmospheric deposits. The paucity of craters implies that Titan's surface is quite young, but the modeled age depends on which published crater production rate is assumed. Using the model of Artemieva and Lunine (2005) suggests that craters with diameters smaller than about 35 km are younger than 200 million years old, and larger craters are older. Craters are not distributed uniformly; Xanadu has a crater density 2-9 times greater than the rest of Titan, and the density on equatorial dune areas is much lower than average. There is a small excess of craters on the leading hemisphere, and craters are deficient in the north polar region compared to the rest of the world. The youthful age of Titan overall, and the various erosional states of its likely impact craters, demonstrate that dynamic processes have destroyed most of the early history of the moon, and that multiple processes continue to strongly modify its surface. The existence of 24 possible impact craters with diameters less than 20 km appears consistent with the Ivanov, Basilevsky and Neukum (1997) model of the effectiveness of Titan's atmosphere in destroying most but not all small projectiles. ?? 2009 Elsevier Inc.

Icarus↗

USGS2011

Search for and limits on plume activity on Mimas, Tethys, and Dione with the Cassini Visual Infrared Mapping Spectrometer (VIMS)

Cassini Visual Infrared Mapping Spectrometer (VIMS) observations of Mimas, Tethys, and Dione obtained during the nominal and extended missions at large solar phase angles were analyzed to search for plume activity. No forward scattered peaks in the solar phase curves of these satellites were detected. The upper limit on water vapor production for Mimas and Tethys is one order of magnitude less than the production for Enceladus. For Dione, the upper limit is two orders of magnitude less, suggesting this world is as inert as Rhea (Pitman, K.M., Buratti, B.J., Mosher, J.A., Bauer, J.M., Momary, T., Brown, R.H., Nicholson, P.D., Hedman, M.M. [2008]. Astrophys. J. Lett. 680, L65–L68). Although the plumes are best seen at ∼2.0 μm, Imaging Science Subsystem (ISS) Narrow Angle Camera images obtained at the same time as the VIMS data were also inspected for these features. None of the Cassini ISS images shows evidence for plumes. The absence of evidence for any Enceladus-like plumes on the medium-sized saturnian satellites cannot absolutely rule out current geologic activity. The activity may below our threshold of detection, or it may be occurring but not captured on the handful of observations at large solar phase angles obtained for each moon. Many VIMS and ISS images of Enceladus at large solar phase angles, for example, do not contain plumes, as the active “tiger stripes” in the south pole region are pointed away from the spacecraft at these times. The 7-year Cassini Solstice Mission is scheduled to gather additional measurements at large solar phase angles that are capable of revealing activity on the saturnian moons.

Icarus↗

USGS2017

The importance of building construction materials relative to other factors affecting structure survival during wildfire

Structure loss to wildfire is a serious problem in wildland-urban interface areas across the world. Laboratory experiments suggest that fire-resistant building construction and design could be important for reducing structure destruction, but these need to be evaluated under real wildfire conditions, especially relative to other factors. Using empirical data from destroyed and surviving structures from large wildfires in southern California, we evaluated the relative importance of building construction and structure age compared to other local and landscape-scale variables associated with structure survival. The local-scale analysis showed that window preparation was especially important but, in general, creating defensible space adjacent to the home was as important as building construction. At the landscape scale, structure density and structure age were the two most important factors affecting structure survival, but there was a significant interaction between them. That is, young structure age was most important in higher-density areas where structure survival overall was more likely. On the other hand, newer-construction structures were less likely to survive wildfires at lower density. Here, appropriate defensible space near the structure and accessibility to major roads were important factors. In conclusion, community safety is a multivariate problem that will require a comprehensive solution involving land use planning, fire-safe construction, and property maintenance.

International Journal of Disaster Risk Reduction↗

USGS2020

Variations in community evacuation potential related to average return periods in probabilistic tsunami hazard analysis

Tsunami risk management requires strategies that can address multiple sources with different recurrence intervals, wave-arrival times, and inundation extents. Probabilistic tsunami hazard analysis (PTHA) provides a structured way to integrate multiple sources, including the uncertainties due to the natural variability and limited knowledge of sources. PTHA-based products relate to specific average return periods (ARP) and while there has been considerable attention paid to ARP choice for building codes, guidance on ARP choice to support evacuation planning and related land use is lacking. We use the State of California (USA) coastal communities as a case study to explore the use of geospatial analysis and pedestrian-evacuation modeling for comparing the societal implications of tsunamis based on evacuation areas that reflect inundation from 475-year, 975-year, and 2475-year ARPs. Results demonstrate that changes in PTHA ARP had a substantial effect on the number of tax-lot parcels in PTHA evacuation areas, but not on the primary land use of these parcels or which communities had the largest number of exposed parcels. Composite PTHA maps provided high-level insights on hazard exposure and identified dominant sources; however, disaggregated PTHA outputs that reflect single source parameters (e.g., wave-arrival time) were necessary to quantify evacuation potential from local and distant tsunamis. Framing changes in ARP assumption based on changes in the number, land-use type, and potential evacuation challenges of parcels in evacuation areas can provide valuable insight on the real-world implications of which ARP to use in land use or evacuation planning.

California↗

USGS2022

Multi-hazard risk analysis for the U.S. Department of the Interior: An integration of expert elicitation, planning priorities, and geospatial analysis

An integral part of disaster risk management is identifying and prioritizing hazards and their potential impacts in a meaningful way to support risk-reduction planning. There has been considerable use and subsequent criticism of threat prioritization efforts that simply compare likelihoods and consequences of plausible threats. This article summarizes a new mixed-methods and scalable approach for prioritizing risks in a multi-hazard, multi-objective, and multi-criteria organizational context. This approach integrates (1) hazard characterizations using subject-matter-expert (SME) elicitation, (2) expressed preferences in planning priorities provided by emergency managers, and (3) quantitative estimates of asset exposure to hazards using geospatial data and geographic-information-systems (GIS) software. We demonstrate this approach with a case study designed to support multi-hazard mitigation and response planning done by the U.S. Department of the Interior (DOI) Office of Emergency Management, which required a national understanding of the risks posed by 75 natural, technological, and adversarial hazards to DOI managed and administered lands, facilities, people, revenues, and resources. Results demonstrate that hazard priorities vary depending on the asset, scale, and risk-management context, thereby making the case that “one-size-fits-all” hazard rankings have limited utility or relevance to real-world, risk mitigation and response planning. Our results suggest that recognizing the risk-management context provides greater transparency, flexibility, and relevance in comparing threats than traditional likelihood-threat matrices or the use of hazard SMEs to decide for planners which hazard scenarios are emphasized in risk planning.

International Journal of Disaster Risk Reduction↗

USGS2023

Perceptions of volcanic air pollution and exposure reduction practices on the Island of Hawai‘i: Working towards socially relevant risk communication

Kīlauea volcano, on the Island of Hawai‘i, is one of the most active volcanoes in the world. Over the past four decades it has released large amounts of volcanic gases and aerosols which form volcanic air pollution known as ‘vog’. Communities downwind of Kīlauea have been chronically or episodically exposed to this potentially harmful air pollution and have raised concerns about the hazards of vog exposure. Public health and civil protection agencies have offered a range of advice, information, and mitigation strategies for living with vog. In this mixed-methods social study, we investigate the translation of official advice into practice in Island of Hawai‘i communities and assess how risk communication could be improved by considering public input, preferences, and community relevance. Given the paucity of information on the long-term effects of chronic vog exposure, assessing the effectiveness of public health and risk communication is vital.

Hawaii↗

USGS2024

Assessing the relationship between cyanobacteria blooms and respiratory-related hospital visits: Green Bay, Wisconsin 2017–2019

Potential acute and chronic human health effects associated with exposure to cyanobacteria and cyanotoxins, including respiratory symptoms, are an understudied public health concern. We examined the relationship between estimated cyanobacteria biomass and the frequency of respiratory-related hospital visits for residents living near Green Bay, Lake Michigan, Wisconsin during 2017–2019. Remote sensing data from the Cyanobacteria Assessment Network was used to approximate cyanobacteria exposure through creation of a metric for cyanobacteria chlorophyll-a (Chl BS ). We obtained counts of hospital visits for asthma, wheezing, and allergic rhinitis from the Wisconsin Hospital Association for ZIP codes within a 3-mile radius of Green Bay. We analyzed weekly counts of hospital visits versus cyanobacteria, which was modelled as a continuous measure (Chl BS ) or categorized according to World Health Organization's (WHO) alert levels using Poisson generalized linear models. Our data included 2743 individual hospital visits and 114 weeks of satellite derived cyanobacteria biomass indicator data. Peak values of Chl BS were observed between the months of June and October. Using the WHO alert levels, 60% of weeks were categorized as no risk, 19% as Vigilance Level, 15% as Alert Level 1, and 6% as Alert Level 2. In Poisson regression models adjusted for temperature, dewpoint, season, and year, there was no association between Chl BS and hospital visits (rate ratio [RR] [95% Confidence Interval (CI)] = 0.98 [0.77, 1.24]). There was also no consistent association between WHO alert level and hospital visits when adjusting for covariates (Vigilance Level: RR [95% CI] 0.88 [0.74, 1.05], Alert Level 1: 0.82 [0.67, 0.99], Alert Level 2: 0.98 [0.77, 1.24], compared to the reference no risk category). Our methodology and model provide a template for future studies that assess the association between cyanobacterial blooms and respiratory health.

Wisconsin↗

USGS2025

Climate-Smart Siting for renewable energy expansion

A massive expansion of renewable energy (RE) is underway to meet the world’s climate goals. Although RE serves to reduce threats from climate change, it can also pose threats to species whose current and future ranges intersect with RE installations. Here, we propose a “Climate-Smart Siting” framework for addressing potential conflicts between RE expansion and biodiversity conservation. The framework engenders authentic consultation with affected and disadvantaged communities throughout and uses overlay and optimization routines to identify focal areas now and in the future where RE development poses promise and peril as species’ ranges shift in response to climate change. We use this framework to demonstrate methods, identify decision outcomes, and discuss market-based levers for aligning RE expansion with the United Nations Global Biodiversity Framework now and as climate change progresses. In the face of the climate crisis, a Climate-Smart Siting strategy could help create solutions without causing further harm to biodiversity and human communities.

iScience↗

USGS2005

A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains

Droughts are normal climate episodes, yet they are among the most expensive natural disasters in the world. Knowledge about the timing, severity, and pattern of droughts on the landscape can be incorporated into effective planning and decision-making. In this study, we present a data mining approach to modeling vegetation stress due to drought and mapping its spatial extent during the growing season. Rule-based regression tree models were generated that identify relationships between satellite-derived vegetation conditions, climatic drought indices, and biophysical data, including land-cover type, available soil water capacity, percent of irrigated farm land, and ecological type. The data mining method builds numerical rule-based models that find relationships among the input variables. Because the models can be applied iteratively with input data from previous time periods, the method enables to provide predictions of vegetation conditions farther into the growing season based on earlier conditions. Visualizing the model outputs as mapped information (called VegPredict) provides a means to evaluate the model. We present prototype maps for the 2002 drought year for Nebraska and South Dakota and discuss potential uses for these maps.

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS2018

A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2016 production. The performance of the developed strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2016 operational mapping.

Conterminous United States↗

USGS2013

Next generation of global land cover characterization, mapping, and monitoring

Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).

International Journal of Applied Earth Observation↗

USGS2019

Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine

Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used to estimate agricultural productivity as well as degree of disturbance on food security from natural disasters and political conflict. However, existing cropland extent maps over large areas (e.g., Country, region, continent, world) are derived from coarse resolution imagery (250 m to 1 km pixels) and have many limitations such as missing fragmented and\or small farms with mixed signatures from different crop types and\or farming practices that can be, confused with other land cover. As a result, the coarse resolution maps have limited useflness in areas where fields are small (<1 ha), such as in Southeast Asia. Furthermore, coarse resolution cropland maps have known uncertainties in both geo-precision of cropland location as well as accuracies of the product. To overcome these limitations, this research was conducted using multi-date, multi-year 30-m Landsat time-series data for 3 years chosen from 2013 to 2016 for all Southeast and Northeast Asian Countries (SNACs), which included 7 refined agro-ecological zones (RAEZ) and 12 countries (Indonesia, Thailand, Myanmar, Vietnam, Malaysia, Philippines, Cambodia, Japan, North Korea, Laos, South Korea, and Brunei). The 30-m (1 pixel = 0.09 ha) data from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) were used in the study. Ten Landsat bands were used in the analysis (blue, green, red, NIR, SWIR1, SWIR2, Thermal, NDVI, NDWI, LSWI) along with additional layers of standard deviation of these 10 bands across 1 year, and global digital elevation model (GDEM)-derived slope and elevation bands. To reduce the impact of clouds, the Landsat imagery was time-composited over four time-periods (Period 1: January- April, Period 2: May-August, and Period 3: September-December) over 3-years. Period 4 was the standard deviation of all 10 bands taken over all images acquired during the 2015 calendar year. These four period composites, totaling 42 band data-cube, were generated for each of the 7 RAEZs. The reference training data (N = 7849) generated for the 7 RAEZ using sub-meter to 5-m very high spatial resolution imagery (VHRI) helped generate the knowledge-base to separate croplands from non-croplands. This knowledge-base was used to code and run a pixel-based random forest (RF) supervised machine learning algorithm on the Google Earth Engine (GEE) cloud computing environment to separate croplands from non-croplands. The resulting cropland extent products were evaluated using an independent reference validation dataset (N = 1750) in each of the 7 RAEZs as well as for the entire SNAC area. For the entire SNAC area, the overall accuracy was 88.1% with a producer’s accuracy of 81.6% (errors of omissions = 18.4%) and user’s accuracy of 76.7% (errors of commissions = 23.3%). For each of the 7 RAEZs overall accuracies varied from 83.2 to 96.4%. Cropland areas calculated for the 12 countries were compared with country areas reported by the United Nations Food and Agriculture Organization and other national cropland statistics resulting in an R 2 value of 0.93. The cropland areas of provinces were compared with the province statistics that showed an R 2 = 0.95 for South Korea and R 2 = 0.94 for Thailand. The cropland products are made available on an interactive viewer at www.croplands.org and for download at National Aeronautics and Space Administration’s (NASA) Land Processes Distributed Active Archive Center (LP DAAC): https://lpdaac.usgs.gov/node/1281 .

International Journal of Applied Earth Observation↗

USGS2007

Wave field features of shallow vertical discontinuity and their application in non-destructive detection

The geotechnical integrity of critical infrastructure can be seriously compromised by the presence of fractures or crevices. Non-destructive techniques to accurately detect fractures in critical infrastructure such as dams and highways could be of significant benefit to the geotechnical industry. This paper investigates the application of shallow seismic and georadar methods to the detection of a vertical discontinuity using numerical simulations. The objective is to address the kinematical analysis of a vertical discontinuity, determine the resulting wave field characteristics, and provide the basis for determining the existence of vertical discontinuities based on the recorded signals. Simulation results demonstrate that: (1) A reflection from a vertical discontinuity produces a hyperbolic feature on a seismic or georadar profile; (2) In order for a reflection from a vertical discontinuity to be produced, a reflecting horizon below the discontinuity must exist, the offset between source and receiver (x0) must be non-zero, on the same side of the vertical discontinuity; (3) The range of distances from the vertical discontinuity where a reflection event is observed is proportional to its length and to x0; (4) Should the vertical crevice (or fracture) pass through a reflecting horizon, dual hyperbolic features can be observed on the records, and this can be used as a determining factor that the vertical crevice passes through the interface; and (5) diffractions from the edges of the discontinuity can be recorded with relatively smaller amplitude than reflections and their ranges are not constrained by the length of discontinuity. If the length of discontinuity is short enough, diffractions are the dominant feature. Real-world examples show that the shallow seismic reflection method and the georadar method are capable of recording the hyperbolic feature, which can be interpreted as vertical discontinuity. Thus, these methods show some promise as effective non-destructive detection methods for locating vertical discontinuities (e.g., fractures or crevices) in infrastructure such as dams and highway pavement. ?? 2007 Elsevier B.V. All rights reserved.

Journal of Applied Geophysics↗

USGS2015

Hydroecological condition and potential for aquaculture in lakes of the arid region of Khorezm, Uzbekistan

With >400 small (<1 ha) lakes, the arid Khorezm Province in Uzbekistan may be well-suited for aquaculture production. Developing water resources to provide a local food supply could increase fish consumption while improving the rural economy. Hydroecological (biological and physical) and chemical characteristics (including legacy pesticides ΣDDT and ΣHCH) of four representative drainage lakes in Khorezm from 2006 to 2008 were analyzed for the lakes’ capability to support healthy fish populations. Lake characteristics were categorized as “optimal” (having little or no effect on growth and development), “tolerable” (corresponding to chronic or sub-lethal toxicity) and “lethal” (corresponding to acute toxicity). Results indicate that three lakes are likely well-suited for raising fish species, with water quality meeting World Bank aquaculture guidelines. However, the fourth lake often had salinity concentrations > optimal levels for local fish species. Pesticide concentrations in water of all four lakes were within tolerable aquaculture ranges. Although water ΣDDT concentrations were >optimal limits, results from chemical analysis of fish tissues and semi-permeable membrane devices indicated that study lake ΣDDT concentrations were not accumulating in fish or posing a human health threat. Land and water management to maintain adequate lake water quality are imperative for sustaining fish populations for human consumption.

Khorezm↗

USGS2023

Satellite precipitation bias estimation and correction using in situ observations and climatology isohyets for the MENA region

The availability of reliable gridded precipitation datasets is limited around the world, especially in arid regions. In this study, we utilized observations from satellite-based precipitation data and in situ rain gauge observations to determine a suitable precipitation dataset in the Middle East & North Africa (MENA) region. First, we evaluated seven different precipitation products using rain gauge observations. The validation was conducted at the daily, monthly, and annual time scales. Results indicated a weaker correlation between in situ rain gauge observation and satellite precipitation data at the daily time step (r: 0.02 to 0.44), mainly due to the lack of range in precipitation distribution. However, the agreement between precipitation estimates and in situ gauge observations improved at monthly (r: 0.02 to 0.66) and annual time scales (r: −0.22 to 0.57), indicating greater reliability of satellite-based precipitation at monthly and annual time scales. Based on the results and dataset availability, the Multi-Source Weighted-Ensemble Precipitation (MSWEP) was deemed suitable to create a bias-corrected new precipitation dataset for the MENA region. This study highlights the benefits of an adjusted regional precipitation product for hydrologic applications in the MENA region, such as streamflow or runoff estimation, to improve the reliability of the model outputs.

West Bank↗