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USGS2016

The National Wind Erosion Research Network: Building a standardized long-term data resource for aeolian research, modeling and land management

The National Wind Erosion Research Network was established in 2014 as a collaborative effort led by the United States Department of Agriculture’s Agricultural Research Service and Natural Resources Conservation Service, and the United States Department of the Interior’s Bureau of Land Management, to address the need for a long-term research program to meet critical challenges in wind erosion research and management in the United States. The Network has three aims: (1) provide data to support understanding of basic aeolian processes across land use types, land cover types, and management practices, (2) support development and application of models to assess wind erosion and dust emission and their impacts on human and environmental systems, and (3) encourage collaboration among the aeolian research community and resource managers for the transfer of wind erosion technologies. The Network currently consists of thirteen intensively instrumented sites providing measurements of aeolian sediment transport rates, meteorological conditions, and soil and vegetation properties that influence wind erosion. Network sites are located across rangelands, croplands, and deserts of the western US. In support of Network activities, http://winderosionnetwork.org was developed as a portal for information about the Network, providing site descriptions, measurement protocols, and data visualization tools to facilitate collaboration with scientists and managers interested in the Network and accessing Network products. The Network provides a mechanism for engaging national and international partners in a wind erosion research program that addresses the need for improved understanding and prediction of aeolian processes across complex and diverse land use types and management practices.

Arizona, California, Colorado, Idaho, North Dakota↗

USGS2008

The coral reef of South Moloka'i, Hawai'i— Portrait of a sediment-threatened fringing reef

Moloka‘i, with the most extensive coral reef in the main Hawaiian Islands, is especially sacred to Hina, the Goddess of the Moon. As Hinaalo, she is the Mother of the Hawaiian people; as Hinapuku‘a, she is the Goddess of Fishermen; and in the form Hina‘opuhalako‘a, she is the Goddess who gave birth to coral, coral reefs, and all spiny marine organisms. Interdependence between the reef’s living resources, the people, and their cosmology was the basis for management of Moloka‘i’s coastal waters for over a thousand years. The ancient residents of Moloka‘i built the greatest concentration of fishponds known anywhere, but their mastery of mariculture, something needed now more than ever, was lost after near genocide from exotic Western diseases. Subsequent destruction of the native vegetation for exotic cattle, goats, pigs, sugar cane, and pineapple caused soil erosion and sedimentation on the reef flat. This masterful volume clearly documents that soil washing into the sea is the major threat to the reef today. Abandoned fishponds, choked with sediment, now act as barriers and mud traps, making damage to corals less than it would otherwise would have been. The role of mud and freshwater from land in preventing coral reef growth, clearly articulated in Charles Darwin’s first book, The Structure and Distribution of Coral Reefs, is the major theme of this book. All around the tropics, coral reefs have died from huge increases in terrestrial sedimentation that resulted from destruction of hillside forests for cash-crop agriculture and pastures in the colonial era, especially in Latin America, Asia, and the islands of the Caribbean and Indo-Pacific. It is obvious that one cannot manage the coastal zone as a unit separate from the watersheds that drain into it. Yet there has been surprisingly little comprehensive scientific study of these impacts. In this landmark volume, U.S. Geological Survey researchers and their colleagues have developed and applied a remarkably integrated approach to the reefs of Moloka‘i, combining geology, oceanography, and biology to provide an in-depth understanding of the processes that have made these reefs grow and that now limit them. They have joined old fashioned natural history of marine animals and plants with study of the geological evolution of the island, hydrology, meteorology, and land-use history, to an arsenal of new methods of remote sensing, including aerial photography, laser ranging, infrared thermal mapping, seismic reflection, in-situ instrumentation to measure chemical parameters of water quality, and direct measurements of the physical driving forces affecting them—such as wave energy, currents, sedimentation, and sediment transport. They provide a level of documentation and insight that has never been available for any reef before. A remarkable feature of this book is that it is aimed at the people of Moloka‘i to inform them of what is happening to their reef and what they might do to preserve their vital resources. The scientific data and interpretations are expressed in unusually clear and comprehensible language, free of the professional jargon that makes most technical publications impenetrable to the public that most needs to know about them, yet without loss of scientific rigor. Here readers will see clearly explained the whole path of soil loss, from the impacts of wild pigs and goats at higher elevations, deforestation of the hills for cattle pasture at lower levels, and denudation of low lands for cash crops. The resulting biological impoverishment has bared the soils, which wash away in flash storms, smothering the inshore reefs, whose growth was already limited because they had grown right up to sea level. The data in this book show that the mud doesn’t get far if it is washed into the sea during a big storm with heavy waves. Afterwards this mud keeps getting stirred up by every succeeding storm, spreading and affecting corals over wider areas until it is finally washed out of the system—and that only happens if there is no more new mud washing onto the reef. I saw this myself a few years ago in Pila‘a Bay on Kaua‘i, where a bulldozed hillside of abandoned sugar cane fields had slumped right on top of a coral reef following exceptional rains. Years later, the algae species were zoned in a way that clearly mapped the distribution of nutrients washed into the bay, most likely from fertilizers bound to the eroded soils. That pattern closely mimics, on a small scale, that shown in Moloka‘i in this volume, where the inner reef is covered with algae, zoned by species in a way that points to land-based sources of nutrients, while the outermost reef slope is still coral dominated, and the deep algae seem to indicate deep-water nutrient upwelling. What of the future? The Hawaiian Islands have been exceptionally fortunate to be spared the worst coral heatstroke death from high temperatures, at least to date. So far, the worst global warming impacts have luckily been small in this region, and the small number of people on Moloka‘i has kept population densities, and sewage pollution, low compared to the more developed islands. Nutrients from years of sugar and pineapple fertilization, and the washing of this soil onto the reefs, show clear influences on the pattern of algae on the reef. Even at very low levels of nutrients, well below that which drives algae to smother and kill coral reefs, more algae is present. Soil erosion control is therefore the key to better management of both nutrients and turbidity on Moloka‘i reefs. To that end land management actions mentioned in this book, such as suppressing wild fires and eliminating wild goats and pigs, could be made even more effective if supplemented by active erosion control using plants whose roots bind the soil effectively in place. Through all of these efforts, Hina and the people of Moloka‘i could be happy again!

Hawaii↗

USGS2024

Remote sensing of actual evapotranspiration from croplands

Agriculture accounted for the majority of human water use and for more than 90% of global freshwater consumption during the twentieth century (Hoekstra and Mekonnen, 2012; Shiklomanov, 2000). Streamflow depletion due to enhanced evapotranspiration (ET) from irrigated crops impacts freshwater ecosystems globally (Foley et al., 2005). Water scarcity limits crop production in many arid and semiarid regions, and water is likely to be a key resource limiting food production and food security in the twenty-first century (Foley et al., 2011; Vorosmarty et al., 2000). Despite this, estimates of the location and temporal dynamics of ET from croplands are often uncertain at a variety of spatial and temporal scales. Better information on ET can be useful in several applications at a range of spatial scales, including water resources, agronomy, and meteorology (e.g., Rivas and Caselles, 2004). At the scale of irrigation projects, maps of ET can assist with irrigation scheduling and demand assessment. Measurements of ET are required for monitoring plant water requirements, plant growth, and productivity, as well as for irrigation management and deciding when to carry out cultivation procedures (e.g., Consolli et al., 2006; Glenn et al., 2007; Yang et al., 2010).

Book chapter↗

USGS2011

Meteoric precipitation at Yucca Mountain, Nevada: Chemical and stable isotope analyses, 2006-09

Meteoric precipitation samples collected in 2006-09 at Yucca Mountain, Nevada, were analyzed for chemistry and stable isotope composition. Precipitation is the major source of infiltration to the unsaturated zone and of recharge to the saturated zone at Yucca Mountain. On February 28, 2005, seepage of water was observed about 40 to 80 meters below the ground surface within the Tiva Canyon Tuff in the South Ramp of the Exploratory Studies Facility tunnel within Yucca Mountain. This seepage was preceded by a 5-month period of above-average precipitation. Chemical and isotopic analysis of this seepage could not be used to estimate travel time, extent of water-rock interaction, and (or) evaporative water loss during percolation through the unsaturated zone due to the lack of corresponding chemical and isotopic analyses of precipitation inputs to the infiltration events that produced the seepage. In February 2006, collection of precipitation samples for chemical (major ions), delta oxygen-18 (&delta 18 O), and delta deuterium (&deltaD) analyses began at seven meteorological monitoring stations to provide baseline isotopic and chemical analyses. The sampling stations range in elevation from 1,131 to 1,562 meters. Each site has two collectors-one for chemical analysis and the other for isotopic analysis of precipitation. The collectors were sampled and emptied after each precipitation event. In 2006-09, 36 distinct precipitation events, with an average 3- to 4-day duration and an average 9.9 millimeters of accumulation, have been analyzed. The chemical composition of these samples of Yucca Mountain precipitation is relatively dilute but contains measurable and variable concentrations of Na + , Ca 2+ , NH + , NO 3 - , and SO 4 2- . Dust transported by typical winter storms and generated from soil carbonates is the main contributor to this precipitation chemistry. Elevated nitrate and ammonium concentrations may be linked to agriculture in the nearby Amargosa River valley to the south and west of Yucca Mountain. Cumulatively, &delta 18 O values range from 3.0 to -20.4 per mil (%o) and &deltaD values range from 10 to -14%o. Winter-season precipitation commonly has isotopically lighter compositions. The cumulative &delta18O plotted against &deltaD shows that precipitation samples define a line with slope of 6.4, less than the 8 of the Global Meteoric Water Line. This difference in slope, typical of arid environments, is chiefly the result of evaporation of falling raindrops due to warmer air temperatures. ;

Scientific Investigations Report↗

USGS2011

Enhanced transpiration by riparian buffer trees in response to advection in a humid temperate agricultural landscape

Riparian buffers are designed as management practices to increase infiltration and reduce surface runoff and transport of sediment and nonpoint source pollutants from crop fields to adjacent streams. Achieving these ecosystem service goals depends, in part, on their ability to remove water from the soil via transpiration. In these systems, edges between crop fields and trees of the buffer systems can create advection processes, which could influence water use by trees. We conducted a field study in a riparian buffer system established in 1994 under a humid temperate climate, located in the Corn Belt region of the Midwestern U.S. (Iowa). The goals were to estimate stand level transpiration by the riparian buffer, quantify the controls on water use by the buffer system, and determine to what extent advective energy and tree position within the buffer system influence individual tree transpiration rates. We primarily focused on the water use response (determined with the Heat Ratio Method) of one of the dominant species ( Acer saccharinum ) and a subdominant ( Juglans nigra ). A few individuals of three additional species ( Quercus bicolor, Betula nigra, Platanus occidentalis ) were monitored over a shorter time period to assess the generality of responses. Meteorological stations were installed along a transect across the riparian buffer to determine the microclimate conditions. The differences found among individuals were attributed to differences in species sap velocities and sapwood depths, location relative to the forest edge and prevailing winds and canopy exposure and dominance. Sapflow rates for A. saccharinum trees growing at the SE edge (prevailing winds) were 39% greater than SE interior trees and 30% and 69% greater than NW interior and edge trees, respectively. No transpiration enhancement due to edge effect was detected in the subdominant J. nigra . The results were interpreted as indicative of advection effects from the surrounding crops. Further, significant differences were document in sapflow rates between the five study species, suggesting that selection of species is important for enhancing specific riparian buffer functions. However, more information is needed on water use patterns among diverse species growing under different climatic and biophysical conditions to assist policy and management decisions regarding effective buffer design.

Forest Ecology and Management↗

USGS2011

The influence of irrigation water on the hydrology and lake water budgets of two small arid-climate lakes in Khorezm, Uzbekistan

Little is known regarding the origins and hydrology of hundreds of small lakes located in the western Uzbekistan province of Khorezm, Central Asia. Situated in the Aral Sea Basin, Khorezm is a productive agricultural region, growing mainly cotton, wheat, and rice. Irrigation is provided by an extensive canal network that conveys water from the Amu Darya River (AD) throughout the province. The region receives on average 10 cm/year of precipitation, yet potential evapotranspiration exceeds this amount by about 15 times. It was hypothesized that the perennial existence of the lakes of interest depends on periodic input of excess irrigation water. This hypothesis was investigated by studying two small lakes in the region, Tuyrek and Khodjababa. In June and July 2008, surface water and shallow groundwater samples were collected at these lake systems and surrounding communities and analyzed for δ 2 H, δ 18 O, and major ion hydrochemistry to determine water sources. Water table and lake surface elevations were monitored, and the local aquifer characteristics were determined through aquifer tests. These data and climate data from a Class A evaporation pan and meteorological stations were used to estimate water budgets for both lakes. Lake evaporation was found to be about 0.7 cm/day during the study period. Results confirm that the waters sampled at both lake systems and throughout central Khorezm were evaporated from AD water to varying degrees. Together, the water budgets and stable isotope and major ion hydrochemistry data suggest that without surface water input from some source (i.e. excess irrigation water), these and other Khorezm lakes with similar hydrology may decrease in volume dramatically, potentially to the point of complete desiccation.

Khorezm↗

USGS2022

A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan

From the Hindu Kush mountains to the Registan Desert, Afghanistan is a diverse landscape where droughts, floods, conflict, and economic market accessibility pose challenges for agricultural livelihoods and food security. The ability to remotely monitor environmental conditions is critical to support decision making for humanitarian assistance. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams provide information on hydrologic states for routine integrated food security analysis. While developed for a specific project, these data are publicly available and useful for other applications that require hydrologic estimates of the water and energy balance. These two data streams are unique because of their suitability for routine monitoring, as well as for being a historical record for computing relative indicators of water availability. The global stream is available at ∼ 1-month latency, and monthly average outputs are on a 10 km grid from 1982–present. The second data stream, Central Asia (21–56 ∘ N, 30–100 ∘ E), at ∼ 1 d latency, provides daily average outputs on a 1 km grid from 2000–present. This paper describes the configuration of the two FLDAS data streams, background on the software modeling framework, selected meteorological inputs and parameters, and results from previous evaluation studies. We also provide additional analysis of precipitation and snow cover over Afghanistan. We conclude with an example of how these data are used in integrated food security analysis. For use in new and innovative studies that will improve understanding of this region, these data are hosted by U.S. Geological Survey data portals and the National Aeronautics and Space Administration (NASA). The Central Asia data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/VQ4CD3Y9YC0R (Jacob and Slinski, 2021), and the global data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/5NHC22T9375G (McNally, 2018).

Earth System Science Data↗

USGS2017

A land data assimilation system for sub-Saharan Africa food and water security applications

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

Scientific Data↗

USGS2014

Water quality and algal community dynamics of three deepwater lakes in Minnesota utilizing CE-QUAL-W2 models

Water quality, habitat, and fish in Minnesota lakes will potentially be facing substantial levels of stress in the coming decades primarily because of two stressors: (1) land-use change (urban and agricultural) and (2) climate change. Several regional and statewide lake modeling studies have identified the potential linkages between land-use and climate change on reductions in the volume of suitable lake habitat for coldwater fish populations. In recent years, water-resource scientists have been making the case for focused assessments and monitoring of sentinel systems to address how these stress agents change lakes over the long term. Currently in Minnesota, a large-scale effort called “Sustaining Lakes in a Changing Environment” is underway that includes a focus on monitoring basic watershed, water quality, habitat, and fish indicators of 24 Minnesota sentinel lakes across a gradient of ecoregions, depths, and nutrient levels. As part of this effort, the U.S. Geological Survey, in cooperation with the Minnesota Department of Natural Resources, developed predictive water quality models to assess water quality and habitat dynamics of three select deepwater lakes in Minnesota. The three lakes (Lake Carlos in Douglas County, Elk Lake in Clearwater County, and Trout Lake in Cook County) were assessed under recent (2010–11) meteorological conditions. The three selected lakes contain deep, coldwater habitats that remain viable during the summer months for coldwater fish species. Hydrodynamics and water-quality characteristics for each of the three lakes were simulated using the CE-QUAL-W2 model, which is a carbon-based, laterally averaged, two-dimensional water-quality model. The CE-QUAL-W2 models address the interaction between nutrient cycling, primary production, and trophic dynamics to predict responses in the distribution of temperature and oxygen in lakes. The CE-QUAL-W2 models for all three lakes successfully predicted water temperature, on the basis of the two metrics of absolute mean error and root mean square error, using measured inputs of water temperature and nutrients. One of the main calibration tools for CE-QUAL-W2 model development was the vertical profile temperature data, available for all three lakes. For all three lakes, the absolute mean error and root mean square error were less than 1.0 degree Celsius and 1.2 degrees Celsius, respectively, for the different depth ranges used for vertical profile comparisons. In Lake Carlos, simulated water temperatures compared better to measured water temperatures in the epilimnion than in the hypolimnion. The reverse was true for the other two lakes, Elk Lake and Trout Lake, where the simulated results were slightly better for the hypolimnion than the epilimnion. The model also was used to approximate the location of the thermocline throughout the simulation periods, approximately April to November, in all three lake models. Deviations between the simulated and measured water temperatures in the vertical lake profile commonly were because of an offset in the timing of thermocline shifts rather than the simulated results missing thermocline shifts altogether.

Minnesota↗

USGS2011

Overview of the ARkStorm scenario

The U.S. Geological Survey, Multi Hazards Demonstration Project (MHDP) uses hazards science to improve resiliency of communities to natural disasters including earthquakes, tsunamis, wildfires, landslides, floods and coastal erosion. The project engages emergency planners, businesses, universities, government agencies, and others in preparing for major natural disasters. The project also helps to set research goals and provides decision-making information for loss reduction and improved resiliency. The first public product of the MHDP was the ShakeOut Earthquake Scenario published in May 2008. This detailed depiction of a hypothetical magnitude 7.8 earthquake on the San Andreas Fault in southern California served as the centerpiece of the largest earthquake drill in United States history, involving over 5,000 emergency responders and the participation of over 5.5 million citizens. This document summarizes the next major public project for MHDP, a winter storm scenario called ARkStorm (for Atmospheric River 1,000). Experts have designed a large, scientifically realistic meteorological event followed by an examination of the secondary hazards (for example, landslides and flooding), physical damages to the built environment, and social and economic consequences. The hypothetical storm depicted here would strike the U.S. West Coast and be similar to the intense California winter storms of 1861 and 1862 that left the central valley of California impassible. The storm is estimated to produce precipitation that in many places exceeds levels only experienced on average once every 500 to 1,000 years. Extensive flooding results. In many cases flooding overwhelms the state’s flood-protection system, which is typically designed to resist 100- to 200-year runoffs. The Central Valley experiences hypothetical flooding 300 miles long and 20 or more miles wide. Serious flooding also occurs in Orange County, Los Angeles County, San Diego, the San Francisco Bay area, and other coastal communities. Windspeeds in some places reach 125 miles per hour, hurricane-force winds. Across wider areas of the state, winds reach 60 miles per hour. Hundreds of landslides damage roads, highways, and homes. Property damage exceeds $ 300 billion, most from flooding. Demand surge (an increase in labor rates and other repair costs after major natural disasters) could increase property losses by 20 percent. Agricultural losses and other costs to repair lifelines, dewater (drain) flooded islands, and repair damage from landslides, brings the total direct property loss to nearly $ 400 billion, of which $ 20 to $ 30 billion would be recoverable through public and commercial insurance. Power, water, sewer, and other lifelines experience damage that takes weeks or months to restore. Flooding evacuation could involve 1.5 million residents in the inland region and delta counties. Business interruption costs reach $ 325 billion in addition to the $ 400 billion property repair costs, meaning that an ARkStorm could cost on the order of $ 725 billion, which is nearly 3 times the loss deemed to be realistic by the ShakeOut authors for a severe southern California earthquake, an event with roughly the same annual occurrence probability. The ARkStorm has several public policy implications: (1) An ARkStorm raises serious questions about the ability of existing federal, state, and local disaster planning to handle a disaster of this magnitude. (2) A core policy issue raised is whether to pay now to mitigate, or pay a lot more later for recovery. (3) Innovative financing solutions are likely to be needed to avoid fiscal crisis and adequately fund response and recovery costs from a similar, real, disaster. (4) Responders and government managers at all levels could be encouraged to conduct risk assessments, and devise the full spectrum of exercises, to exercise ability of their plans to address a similar event. (5) ARkStorm can be a reference point for application of Federal Emergency Management Agency (FEMA) and California Emergency Management Agency guidance connecting federal, state and local natural hazards mapping and mitigation planning under the National Flood Insurance Plan and Disaster Mitigation Act of 2000. (6) Common messages to educate the public about the risk of such an extreme disaster as the ARkStorm scenario could be developed and consistently communicated to facilitate policy formulation and transformation. These impacts were estimated by a team of 117 scientists, engineers, public-policy experts, insurance experts, and employees of the affected lifelines. In many aspects the ARkStorm produced new science, such as the model of coastal inundation. The products of the ARkStorm are intended for use by emergency planners, utility operators, policymakers, and others to inform preparedness plans and to enhance resiliency.

California↗

USGS2015

Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010

Groundwater recharge is one of the most difficult components of a water budget to ascertain, yet is an important boundary condition necessary for the quantification of water resources. In Minnesota, improved estimates of recharge are necessary because approximately 75 percent of drinking water and 90 percent of agricultural irrigation water in Minnesota are supplied from groundwater. The water that is withdrawn must be supplied by some combination of (1) increased recharge, (2) decreased discharge to streams, lakes, and other surface-water bodies, and (3) removal of water that was stored in the system. Recent pressure on groundwater resources has highlighted the need to provide more accurate recharge estimates for various tools that can assess the sustainability of long-term water use. As part of this effort, the U.S. Geological Survey, in cooperation with the Minnesota Pollution Control Agency, used the Soil-Water-Balance model to calculate gridded estimates of potential groundwater recharge across Minnesota for 1996‒2010 at a 1-kilometer (0.621-mile) resolution. The potential groundwater recharge estimates calculated for Minnesota from the Soil-Water Balance model included gridded values (1-kilometer resolution) of annual mean estimates (that is, the means for individual years from 1996 through 2010) and mean annual estimates (that is, the mean for the 15-year period 1996−2010). The Soil-Water-Balance model uses a modified Thornthwaite-Mather soil-water-balance approach, with components of the soil-water balance calculated on a daily basis. A key advantage of this approach includes the use of commonly available geographic information system data layers that incorporate land cover, soil properties, and daily meteorological data to produce temporally and spatially variable gridded estimates of potential recharge. The Soil-Water-Balance model was calibrated by using a combination of parameter estimation techniques, making manual adjustments of model parameters, and using parameter values from previously published Soil-Water-Balance models. Each calibration simulation compared the potential recharge estimate from the model against base-flow estimates derived from three separate hydrograph separation techniques. A total of 35 Minnesota watersheds were selected for the model calibration. Meteorological data necessary for the model included daily precipitation, minimum daily temperature, and maximum daily temperature. All of the meteorological data were provided by the Daymet dataset, which included daily continuous surfaces of key climatological data. Land-cover data were provided by the 2001 and 2006 National Land Cover Database: the 2001 classification was used from 1994 through 2003, and the 2006 classification was used from 2004 through 2010. Soil data used in the model included hydrologic soils group and the available soil-water capacity. These soil data were obtained from the Natural Resources Conservation Service Soil Survey Geographic (SSURGO) database and the State Soil Geographic (STATSGO) database. The statewide mean annual potential recharge rate from 1996–2010 was 4.9 inches per year. Potential recharge estimates increased from west to east across Minnesota. The mean annual potential recharge estimates across Minnesota at a 1-km resolution for the overall simulation period (1996–2010) ranged from less than 0.1 to 17.8 inches per year. Some of the lowest potential recharge rates for the simulation period were in the Red River of the North Basin of northwestern Minnesota, and generally were between 1.0 and 1.5 inches per year. The highest potential recharge rates were in northeastern Minnesota and the Anoka Sand Plain in central Minnesota. Eighty-eight percent of the potential recharge rates (by grid cell) were between 2 and 8 inches per year from 1996–2010. Only about 3 percent of all the potential recharge estimates (by grid cell) were less than 2 inches per year, and 9 percent of estimates were greater than 8 inches per year. On an annual basis, however, potential recharge rates were as high as 27.2 inches per year. The highest annual mean recharge estimate across the State was for 2010, and the lowest mean recharge estimate was for 2003. Although precipitation variability partially explained the annual differences in potential recharge estimates, precipitation alone did not account for these differences, and other factors such as antecedent moisture conditions likely were important. Also, because precipitation gradients across the State can vary from year to year, the dominant land-cover class and hydrologic soil group combinations for a particular region had a large effect on the resulting potential recharge value. During 1996–2010, April had the greatest monthly mean potential recharge compared to all other months, accounting for a mean of 30 percent of annual potential recharge in this single month.

Minnesota↗

USGS2018

Simulation of potential groundwater recharge for the glacial aquifer system east of the Rocky Mountains, 1980–2011, using the Soil-Water-Balance Model

An understanding of the spatial and temporal extent of groundwater recharge is critical for many types of hydrologic assessments involving water quality, contaminant transport, ecosystem health, and sustainable use of groundwater. Annual potential groundwater recharge was simulated at a 1-kilometer resolution with the Soil-Water-Balance (SWB) model for the glacial aquifer system east of the Rocky Mountains, from central Montana east to Maine, for calendar years 1980–2011. The SWB model used high resolution meteorological, land cover, and soil hydrology datasets that are nationally consistent and publicly available. The SWB model computed daily potential groundwater recharge as precipitation in excess of interception, runoff, evapotranspiration, and soil-water storage capacity. Daily potential recharge values within each year of the simulation were summed to produce annual potential recharge rates. Potential recharge as described in this report is water that infiltrates vertically below the plant rooting zone and is assumed to reach the water table. The calibrated SWB model in this report is called the glacial SWB model. Model calibration assumed that the area contributing to groundwater discharge equaled the surface watershed. The model was calibrated to stream base flows from 39 watersheds throughout the model domain that had hydrologic conditions appropriate for hydrograph separation. Base flows were calculated from daily streamflow records with the HYSEP local minimum hydrograph separation method The glacial SWB model reproduced the mean annual base-flow calibration targets well; the Nash-Sutcliffe efficiency coefficient was 0.94, and the root mean squared error was 1.28 inches per year. The glacial SWB model provides insight into the spatial and temporal variability in potential annual recharge across the glacial aquifer system. About 20 percent of the active model area had an average potential recharge rate of less than 1 inch per year. Total precipitation, total recharge, and recharge as a percentage of precipitation increased from west to east. A substantial amount of the recharge water (39 percent) entering the glacial aquifer system travels through developed (urbanized) and agricultural landscapes, which are known to cause water-quality impairments. Regional climatic events, such as the 1988 to 1989 drought, are apparent in the potential recharge time series. Potential recharge generally increased across the glacial aquifer system between 2001 and 2011. A comparison of the potential recharge from the glacial SWB model to previous broad-scale recharge estimates reveals several important considerations for future SWB modeling applications. Shifts in the overall distribution of potential recharge between separate models can be explained by methods used to generate base-flow calibration target datasets. Spatial patterns in potential recharge simulated by SWB models are strongly dependent on the data and assumptions used to assign model cells to hydrologic soil groups. A review of several SWB models used to estimate groundwater recharge (and not surface runoff) revealed that model results are most sensitive to input climatic data, followed by surface runoff (curve number) and root-zone depth parameters.

Scientific Investigations Report↗

USGS2019

Using the precipitation-runoff modeling system to predict seasonal water availability in the upper Klamath River basin, Oregon and California

Accurate forecasts of the streamflow expected during late spring and summer in the Upper Klamath River Basin in southern-central Oregon and northern California are used by water management agencies to balance water allocations for agriculture, aquatic habitat, and hydropower-production needs. Streamflow forecasts are also used by irrigation farmers for planning. The forecasts are typically made twice a month starting as early in the water year as December. Multiple regression equations relating real-time snowpack and precipitation conditions to seasonal streamflow volumes have been used for many years in forecasting. However, with warming temperature trends and lower snowpack, such forecasts based on historical data could become less reliable in the future. If the timing and relation of snowpack and precipitation are outside of the range of the historical data used to create the equations, the forecasts become extrapolations. Statistical forecast equations are also limited in their ability to forecast streamflow in groundwater-dominated basins having inter-annual lag. As an additional method for seasonal streamflow forecasting, a physical-process-based hydrologic model employing the Precipitation-Runoff Modeling System (PRMS) was developed in cooperation with the U.S. Bureau of Reclamation for the Upper Klamath Basin in this study. The model was calibrated for the portion of the basin draining into Upper Klamath Lake. PRMS is a deterministic, distributed-parameter, physical-process-based modeling system developed by the U.S. Geological Survey. It simulates daily streamflow, snow, solar radiation, evapotranspiration, surface-water, and groundwater processes within the basin. A model calibration and validation period for water years 2000–15 and water years 1984–99, respectively, was used. The model was calibrated and validated using measured streamflow, snowpack, evapotranspiration, and solar radiation data sets. Interpolated daily precipitation and air temperature data from 32 meteorological stations within and surrounding the Upper Klamath Basin were used as model input. Performance statistics, used to evaluate how well simulated daily streamflow matched with measured streamflow included percent bias, percent relative error, and root-mean-square error. The statistics were computed annually, monthly, for October–March, and for April–September. With the exception of the October–March period, percent bias statistics were all within plus or minus 5-percent for both the calibration and validation periods. Limitations to using the model are error in the precipitation and air temperature input time series data, which include measurement error and error in the spatial interpolation method. Other errors include measured daily streamflow data, which were adjusted for consumptive use losses to make them more closely resemble natural streamflow for calibration. The model developed for the Upper Klamath Basin can be used to forecast streamflow from the Sprague and Williamson River Basins and inflow to Upper Klamath Lake. Reliable forecasts at these locations are needed for managing water for irrigation, ecosystem health, and power production. Using the models in a forecast application requires assembling model input data sets of anticipated daily precipitation and minimum and maximum air temperature for the period after the date the forecast is made and the end of the forecasted period. These climate data sets can be based on historical or synthetic records, at the discretion of the forecaster. With the Ensemble Streamflow Prediction method, a suite of streamflow scenarios is simulated using multiple years of climate data as model input. The forecasted streamflow is determined from knowing the exceedance probabilities of the simulated streamflows. In this study, the model and the Ensemble Streamflow Prediction method were used to forecast the volume of inflow to Upper Klamath Lake for a 6-month period from April 1, 2015, to September 30, 2015, using a range of climate data sets based on El Niño Southern Oscillation (ENSO) criteria. Because 2015 was a warm phase ENSO period, climate data for 10 warm phase ENSO years from 1980 to 2010 were used as input to the model. The simulated April–September 2015 UKL inflow volume based on measured 2015 climate data was 482,000 acre-feet, which was very close to the 50th percent exceedance probability computed from 10 simulated scenarios that used warm phase ENSO climate input data from 1980–2010.

California, Oregon↗

USGS2007

Assessment of Areal Recharge to the Spokane Valley-Rathdrum Prairie Aquifer, Spokane County, Washington, and Bonner and Kootenai Counties, Idaho

A numerical flow model of the Spokane Valley-Rathdrum Prairie aquifer currently (2007) being developed requires the input of values for areally-distributed recharge, a parameter that is often the most uncertain component of water budgets and ground-water flow models because it is virtually impossible to measure over large areas. Data from six active weather stations in and near the study area were used in four recharge-calculation techniques or approaches; the Langbein method, in which recharge is estimated on the basis of empirical data from other basins; a method developed by the U.S. Department of Agriculture (USDA), in which crop consumptive use and effective precipitation are first calculated and then subtracted from actual precipitation to yield an estimate of recharge; an approach developed as part of the Eastern Snake Plain Aquifer Model (ESPAM) Enhancement Project in which recharge is calculated on the basis of precipitation-recharge relations from other basins; and an approach in which reference evapotranspiration is calculated by the Food and Agriculture Organization (FAO) Penman-Monteith equation, crop consumptive use is determined (using a single or dual coefficient approach), and recharge is calculated. Annual recharge calculated by the Langbein method for the six weather stations was 4 percent of annual mean precipitation, yielding the lowest values of the methods discussed in this report, however, the Langbein method can be only applied to annual time periods. Mean monthly recharge calculated by the USDA method ranged from 53 to 73 percent of mean monthly precipitation. Mean annual recharge ranged from 64 to 69 percent of mean annual precipitation. Separate mean monthly recharge calculations were made with the ESPAM method using initial input parameters to represent thin-soil, thick-soil, and lava-rock conditions. The lava-rock parameters yielded the highest recharge values and the thick-soil parameters the lowest. For thin-soil parameters, calculated monthly recharge ranged from 10 to 29 percent of mean monthly precipitation and annual recharge ranged from 16 to 23 percent of mean annual precipitation. For thick-soil parameters, calculated monthly recharge ranged from 1 to 5 percent of mean monthly precipitation and mean annual recharge ranged from 2 to 4 percent of mean annual precipitation. For lava-rock parameters, calculated mean monthly recharge ranged from 37 to 57 percent of mean monthly precipitation and mean annual recharge ranged from 45 to 52 percent of mean annual precipitation. Single-coefficient (crop coefficient) FAO Penman-Monteith mean monthly recharge values were calculated for Spokane Weather Service Office (WSO) Airport, the only station for which the necessary meteorological data were available. Grass-referenced values of mean monthly recharge ranged from 0 to 81 percent of mean monthly precipitation and mean annual recharge was 21 percent of mean annual precipitation; alfalfa-referenced values of mean monthly recharge ranged from 0 to 85 percent of mean monthly precipitation and mean annual recharge was 24 percent of mean annual precipitation. Single-coefficient FAO Penman-Monteith calculations yielded a mean monthly recharge of zero during the eight warmest and driest months of the year (March-October). In order to refine the mean monthly recharge estimates, dual-coefficient (basal crop and soil evaporation coefficients) FAO Penman-Monteith dual-crop evapotranspiration and deep-percolation calculations were applied to daily values from the Spokane WSO Airport for January 1990 through December 2005. The resultant monthly totals display a temporal variability that is absent from the mean monthly values and demonstrate that the daily amount and timing of precipitation dramatically affect calculated recharge. The dual-coefficient FAO Penman-Monteith calculations were made for the remaining five stations using wind-speed values for Spokane WSO Airport and other assumptions regarding

Scientific Investigations Report↗

USGS1921

Surface waters of Kansas, 1895-1919

Kansas is preeminently an agricultural state. According to the United States census of 1910, the area in farms was 43,384,799 acres, or 67,789 square miles, 83 per cent of the total area of the state —82,158 square miles. The products of these farms rank high in value among those of farms in other states, as shown by comparative statistics compiled by the United States Department of Agriculture, Bureau of Crop Estimates. For the period from 1913 to 1917 Kansas ranked ninth of the states of the United States in the value of all crops raised, exclusive of livestock; in 1919 Kansas ranked fifth. In livestock Kansas ranked sixth in 1918 and eighth in 1919. Climatic conditions have largely dominated agricultural development in Kansas. Early ventures in dry farming in western Kansas, encouraged by a succession of rainy seasons, resulted in disheartening disasters, due to the dry seasons that followed. Throughout that region the farmers have gradually utilized the surface and underground waters for irrigation to provide against this deficiency of rainfall. The floods that have occurred in the valleys of eastern" Kansas at frequent intervals during the past twenty years have been the subject of much investigation by state and Federal organizations. In 1844 and 1903 exceptionally disastrous floods occurred in the Kansas (Kaw) valley. Floods that were of lesser magnitude, but that caused widespread loss and injury to property, have occurred in other years, the most recent being the flood of 1915. Much of the cultivated land in these valleys lies along fertile river bottoms that are annually liable to overflow, and the control of the flood waters on these rivers and their tributaries is therefore one of the problems arising from unfavorable climate that demand early solution. In view of the increasing demand for water for domestic service and fire protection, the need of determining whether the supply is adequate for rapidly growing centers of population throughout the state has recently been impressed very strongly upon a great many communities. The dependability of available sources of water supply during seasons of drought is fully as important as investigations of flood problems. Practical solutions of the many local and statewide water problems, such as flood protection, flood prevention, domestic water supply, drainage, irrigation, and water power, depend largely on a thorough knowledge of certain physical data relating to water resources. Hydrologic conditions differ widely in the different drainage basins, so that long-time investigations of stream-flow phenomena in each basin, as well as long-time investigations of meteorologic conditions over the state, are essential in the formulation of comprehensive plans to meet specific water problems. The collection of long-time records of stream-flow in Kansas which is published in this volume has been prepared for the use of those who are concerned with the different phases of the utilization of water in the state.

Kansas↗

USGS2022

Getting ahead of flash drought: From early warning to early action

Flash droughts, characterized by their unusually rapid intensification, have garnered increasing attention within the weather, climate, agriculture, and ecological communities in recent years due to their large environmental and socioeconomic impacts. Because flash droughts intensify quickly, they require different early warning capabilities and management approaches than are typically used for slower-developing “conventional” droughts. In this essay, we describe an integrated research-and-applications agenda that emphasizes the need to reconceptualize our understanding of flash drought within existing drought early warning systems by focusing on opportunities to improve monitoring and prediction. We illustrate the need for engagement among physical scientists, social scientists, operational monitoring and forecast centers, practitioners, and policy-makers to inform how they view, monitor, predict, plan for, and respond to flash drought. We discuss five related topics that together constitute the pillars of a robust flash drought early warning system, including the development of 1) a physically based identification framework, 2) comprehensive drought monitoring capabilities, and 3) improved prediction over various time scales that together 4) aid impact assessments and 5) guide decision-making and policy. We provide specific recommendations to illustrate how this fivefold approach could be used to enhance decision-making capabilities of practitioners, develop new areas of research, and provide guidance to policy-makers attempting to account for flash drought in drought preparedness and response plans.

Bulletin of American Meteorological Society (BAMS)↗

USGS2019

Recognizing the Famine Early Warning Systems Network: Over 30 years of drought early warning science advances and partnerships promoting global food security

On a planet with more than 7 billion people, how do we identify the millions of drought-afflicted people who face a real threat of livelihood disruption or death without humanitarian assistance? Typically, these people are poor and heavily dependent on rainfed agriculture and livestock. Most live in Africa, Central America, or Southwest Asia. When the rains fail, incomes diminish while food prices increase, cutting off the poorest (most often women and children) from access to adequate nutrition. As seen in Ethiopia in 1984 and Somalia in 2011, food shortages can lead to famine. Yet these slow onset disasters also provide opportunities for effective intervention, as seen in Ethiopia in 2015 and Somalia in 2017. Since 1985, the US Agency for International Development's Famine Early Warning Systems Network (FEWS NET) has been providing evidence-based guidance for effective humanitarian relief efforts. FEWS NET depends on a Drought Early Warning System (DEWS) to help understand, monitor, model and predict food insecurity. Here we provide an overview of FEWS NET's DEWS using examples from recent climate extremes. While drought monitoring and prediction provides just one part of FEWS NET's monitoring system, it draws from many disciplines - remote sensing, climate prediction, agro-climatic monitoring, and hydrologic modeling. Here we describe FEWS NET's multi-agency multi-disciplinary DEWS and Food Security Outlooks. This DEWS uses diagnostic analyses to guide predictions. Mid-season droughts are monitored using multiple cutting-edge earth observing systems. Crop and hydrologic models can translate these observations into impacts. This information feeds into FEWS NET reports, helping to save lives by motivating and targeting timely humanitarian assistance.

Bulletin of the American Meteorological Society↗

USGS2024

Special topic—Eruption plumes and clouds

Introduction Explosive eruptions create plumes of volcanic ash and gas that can rise more than 30,000 feet (9.1 kilometers [km]) above sea level within minutes of eruption onset. The resulting clouds disperse under prevailing winds and may cause hazardous conditions hundreds to thousands of kilometers from the volcano, including in international airspace. Rapid detection and characterization of explosive activity is vital to mitigate the wide-ranging effects of volcanic ash. Ashfall thicknesses as small as a millimeter or so on the ground can affect infrastructure, agriculture, and air quality, requiring extensive clean-up procedures (Schuster, 1981; Warrick and others, 1981, U.S. Geological Survey, 2022). Volcanic clouds also pose substantial threats to aircraft. Since 1953, 88 encounters between airplanes and ash clouds have been documented worldwide (International Civil Aviation Organization, 2015, appendix F), resulting in aircraft damage and, in 9 cases, engine failure (Guffanti and others, 2010). In 1982, two large passenger planes suffered complete engine failure owing to eruptions in Indonesia (Global Volcanism Program, 1982) and a similar incident occurred over Alaska in 1989 (Casadevall, 1994). In all three cases, they were able to restart some engine capability and land safely once they emerged from the ash clouds, although with substantial damage (Guffanti and others, 2010). The clear threat to aviation has led to establishment of nine Volcanic Ash Advisory Centers (VAAC) around the world to monitor and rapidly disseminate information about volcanic eruptions to the aviation community. U.S. Geological Survey (USGS) volcano observatories issue the Volcano Observatory Notice for Aviation that informs of preeruptive unrest or eruptive activity. When ash-producing eruptions do occur, volcano observatories work closely with their regional VAAC to ensure consistency and accuracy in eruption onset time, cloud altitude, ash production, and duration as reported in Volcanic Ash Advisories. Explosive volcanism in the United States and Commonwealth of the Northern Mariana Islands prompts 50–100 such advisories in any given year (table J1). This collaborative effort is greatly aided by USGS detection and monitoring of eruption clouds to ensure a timely and coordinated response. To support these efforts to provide guidance on ash transport and fallout, the USGS developed the Ash3d volcanic ash dispersion model ( https://vsc-ash.wr.usgs.gov/ash3d-gui ) (Schwaiger and others, 2012). Automated simulations are run daily by the USGS for volcanoes that are in elevated states of unrest, and in response mode when eruptions occur. During eruptions, the model output is provided to local National Weather Service Weather Forecast Offices to guide them in the issuance of their information products (such as special weather statements, ashfall advisories, or ashfall warnings), as well as to State and local governments and the public. Characterization of the eruption source is needed to estimate the parameters used to initialize the Ash3d model, and by the Anchorage and Washington VAACs to initialize other dispersion models that inform forecasts for the airborne volcanic cloud. The source parameters that can be provided by observation during an eruption include eruption start time, eruption cloud height over time, and eruption duration. Other, nonobservable source parameters, such as mass eruption rate and grain-size distribution, are based on empirical correlations and study of historical deposits. The goal is to provide a time series of cloud heights, mass eruption rates, and particle-size distributions that accurately reflects current conditions. When feasible, the USGS also provides guidance on the nature of ongoing eruptions and forecasts future activity using petrologic monitoring of collected tephra samples. The aims of providing accurate observable parameters are achieved through analysis of (1) near-real-time meteorological satellite data, (2) ground-based cameras (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–G, 11 p., https://doi.org/10.3133/sir20245062g.">chapter G , this volume; Orr and others, 2024), (3) weather radar, (4) volcanic lightning detection, and (5) ground-based ash sensors and sampling. Explosive eruptions can be detected by a variety of geophysical monitoring, including infrasound (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–C, 11 p., https://doi.org/10.3133/sir20245062c.">chapter C , this volume; Lyons and others, 2024) and seismicity (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–B, 9 p., https://doi.org/10.3133/sir20245062b.">chapter B , this volume; Thelen and others, 2024). However, those methods cannot quantify the altitude, ash content, and dispersal dynamics of resulting volcanic clouds. Ideally, all available sources of monitoring data are synthesized to develop a coherent understanding of eruptive activity. The guidance summarized here provides a framework for characterizing volcanic clouds in the atmosphere and tracking the evolution of explosive eruption dynamics.

Scientific Investigations Report↗