Nitrogen emissions along the Colorado Front Range: Response to population growth, land and water use change, and agriculture
No abstract available.
Book chapter↗
SEARCH · Search USGS
Results for “Agriculture”
Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Impact of land use and land cover change on the water balance of a large agricultural watershed: Historical effects and future directions
Over the last century, land use and land cover (LULC) in the United States Corn Belt region shifted from mixed perennial and annual cropping systems to primarily annual crops. Historical LULC change impacted the annual water balance in many Midwestern basins by decreasing annual evapotranspiration (ET) and increasing streamflow and base flow. Recent expansion of the biofuel industry may lead to future LULC changes from increasing corn acreage and potential conversion of the industry to cellulosic bioenergy crops of warm or cool season grasses. In this paper, the Soil and Water Assessment Tool (SWAT) model was used to evaluate potential impacts from future LULC change on the annual and seasonal water balance of the Raccoon River watershed in west‐central Iowa. Three primary scenarios for LULC change and three scenario variants were evaluated, including an expansion of corn acreage in the watershed and two scenarios involving expansion of land using warm season and cool season grasses for ethanol biofuel. Modeling results were consistent with historical observations. Increased corn production will decrease annual ET and increase water yield and losses of nitrate, phosphorus, and sediment, whereas increasing perennialization will increase ET and decrease water yield and loss of nonpoint source pollutants. However, widespread tile drainage that exists today may limit the extent to which a mixed perennial‐annual land cover would ever resemble pre‐1940s hydrologic conditions. Study results indicate that future LULC change will affect the water balance of the watershed, with consequences largely dependent on the future LULC trajectory.
Water Resources Research↗
Thresholds of flow-induced bed disturbances and their effects on stream metabolism in an agricultural river
Storm-driven flow pulses in rivers destroy and restructure sediment habitats that affect stream metabolism. This study examined thresholds of bed disturbances that affected patch- and reach-scale sediment conditions and metabolism rates. A 4 year record of discharge and diel changes in dissolved oxygen concentrations (ΔDO) was analyzed for disturbances and recovery periods of the ΔDO signal. Disturbances to the ΔDO signal were associated with flow pulses, and the recovery times for the ΔDO signal were found to be in two categories: less than 5 days (30% of the disturbances) or greater than 15 days (70% of the disturbances). A field study was performed during the fall of 2007, which included a storm event that increased discharge from 3.1 to 6.9 m 3 /s over a 7 h period. During stable flow conditions before the storm, variability in patch-scale stream metabolism values were associated with sediment texture classes with values ranging from −16.4 to 2.3 g O 2 2 /d (negative sign indicates net respiration) that bounded the reach-averaged rate of −5.6 g O 2 2 /d. Hydraulic modeling of bed shear stresses demonstrated a storm-induced flow pulse mobilized approximately 25% of the bed and reach-scale metabolism rates shifted from −5 to −40 g O 2 2 /d. These results suggest that storm-induced bed disturbances led to threshold behavior with respect to stream metabolism. Small flow pulses resulted in partial-bed mobilization that disrupted stream metabolism by increased turbidity with short recovery times. Large flow pulses resulted in full-bed mobilization that disrupted stream metabolism by destroying periphyton habitats with long recovery times.
Water Resources Research↗
Possible anthropogenic enhancement of precipitation in the Sahel-Sudan Savanna by remote agricultural irrigation
The local climatic impacts of historical expansion of irrigation are substantial, but the distant impacts are poorly understood, and their governing mechanisms generally have not been rigorously analyzed. Our experiments with an earth-system model suggest that irrigation in the Middle East and South Asia may enhance rainfall in a large portion of the Sahel-Sudan Savanna (SSS) to an extent comparable and opposite to its suppression by other anthropogenic climate drivers during the last several decades. The enhancement arises through a reduction in the meridional gradient of moist static energy from the Sahara Desert to the tropical rainforests. An implication of this study is that remote irrigation is a possible factor affecting the risk of drought and famine and, thus, future water security in the SSS region.
Geophysical Research Letters↗
Conjunctive use of groundwater and surface water for irrigated agriculture: Risk aversion
In examining the South Platte system in Colorado where surface water and groundwater are used conjunctively for irrigation, we find the actual installed well capacity is approximately sufficient to irrigate the entire area. This would appear to be an overinvestment in well capacity. In this paper we examine to what extent groundwater is being developed as insurance against periods of low streamflow. Using a simulation model which couples the hydrology of a conjunctive stream aquifer system to a behavioral-economic model which incorporates farmer behavior in such a system, we have investigated the economics of an area patterned after a reach of the South Platte Valley in Colorado. The results suggest that under current economic conditions the most reasonable groundwater pumping capacity is a total capacity capable of irrigating the available acreage with groundwater. Installing sufficient well capacity to irrigate all available acreage has two benefits: (1) this capacity maximizes the expected net benefits and (2) this capacity also minimizes the variation in annual income: it reduces the variance to essentially zero. As pumping capacity is installed in a conjunctive use system, the value of flow forecasts is diminished. Poor forecasts are compensated for by pumping groundwater.
Colorado↗
Use of qualitative and quantitative information in neural networks for assessing agricultural chemical contamination of domestic wells
A neural network analysis of agrichemical occurrence in groundwater was conducted using data from a pilot study of 192 small-diameter drilled and driven wells and 115 dug and bored wells in Illinois, a regional reconnaissance network of 303 wells across 12 Midwestern states, and a study of 687 domestic wells across Iowa. Potential factors contributing to well contamination (e.g., depth to aquifer material, well depth, and distance to cropland) were investigated. These contributing factors were available in either numeric (actual or categorical) or descriptive (yes or no) format. A method was devised to use the numeric and descriptive values simultaneously. Training of the network was conducted using a standard backpropagation algorithm. Approximately 15% of the data was used for testing. Analysis indicated that training error was quite low for most data. Testing results indicated that it was possible to predict the contamination potential of a well with pesticides. However, predicting the actual level of contamination was more difficult. For pesticide occurrence in drilled and driven wells, the network predictions were good. The performance of the network was poorer for predicting nitrate occurrence in dug and bored wells. Although the data set for Iowa was large, the prediction ability of the trained network was poor, due to descriptive or categorical input parameters, compared with smaller data sets such as that for Illinois, which contained more numeric information.
Journal of Hydrologic Engineering↗
Multiple agricultural cropland products of South Asia developed using Landsat-8 30 m and MODIS 250 m data using machine learning on the Google Earth Engine (GEE) cloud and spectral matching techniques (SMTs) in support of food and water security
Cropland products are of great importance in water and food security assessments, especially in South Asia, which is home to nearly 2 billion people and 230 million hectares of net cropland area. In South Asia, croplands account for about 90% of all human water use. Cropland extent, cropping intensity, crop watering methods, and crop types are important factors that have a bearing on the quantity, quality, and location of production. Currently, cropland products are produced using mainly coarse-resolution (250–1000 m) remote sensing data. As multiple cropland products are needed to address food and water security challenges, our study was aimed at producing three distinct products that would be useful overall in South Asia. The first of these, Product 1, was meant to assess irrigated versus rainfed croplands in South Asia using Landsat 30 m data on the Google Earth Engine (GEE) platform. The second, Product 2, was tailored for major crop types using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m data. The third, Product 3, was designed for cropping intensity (single, double, and triple cropping) using MODIS 250 m data. For the kharif season (the main cropping season in South Asia, Jun–Oct), 10 major crops (5 irrigated crops: rice, soybean, maize, sugarcane, cotton; and 5 rainfed crops: pulses, rice, sorghum, millet, groundnut) were mapped. For the rabi season (post-rainy season, Nov–Feb), five major crops (three irrigated crops: rice, wheat, maize; and two rainfed crops: chickpea, pulses) were mapped. The irrigated versus rainfed 30 m product showed an overall accuracy of 79.8% with the irrigated cropland class providing a producer’s accuracy of 79% and the rainfed cropland class 74%. The overall accuracy demonstrated by the cropping intensity product was 85.3% with the producer’s accuracies of 88%, 85%, and 67% for single, double, and triple cropping, respectively. Crop types were mapped to accuracy levels ranging from 72% to 97%. A comparison of the crop-type area statistics with national statistics explained 63–98% variability. The study produced multiple-cropland products that are crucial for food and water security assessments, modeling, mapping, and monitoring using multiple-satellite sensor big-data, and Random Forest (RF) machine learning algorithms by coding, processing, and computing on the GEE cloud.
GIScience & Remote Sensing↗
Do the quality and quantity of honey bee-collected pollen vary across an agricultural land use gradient?
Pollen is the source of protein for most bee species, yet the quality and quantity of pollen is variable across landscapes and growing seasons. Understanding the role of landscapes in providing nutritious forage to bees is important for pollinator health, particularly in areas undergoing significant land-use change such as in the Northern Great Plains (NGP) region of the United States where grasslands are being converted to row crops. We investigated how the quality and quantity of pollen collected by honey bees ( Apis mellifera L. [Hymenoptera: Apidae]) changed with land use and across the growing season by sampling bee-collected pollen from apiaries in North Dakota, South Dakota, and Minnesota, USA, throughout the flowering season in 2015–2016. We quantified protein content and quantity of pollen to investigate how they varied temporally and across a land-use gradient of grasslands to row crops. Neither pollen weight nor crude protein content varied linearly across the land-use gradient; however, there were significant interactions between land use and sampling date across the season, particularly in grasslands. Generally, pollen protein peaked mid-July while pollen weight had two maxima in late-June and late-August. Results suggest that while land use itself may not correlate with the quality or quantity of pollen resources collected by honey bees among our study apiaries, the nutritional landscape of the NGP is seasonally dynamic, especially in certain land covers, and may impose seasonal resource limitations for both managed and native bee species. Furthermore, results indicate periods of qualitative and quantitative pollen dearth may not coincide.
Minnesota, North Dakota, South Dakota↗
Agricultural management affects evolutionary processes in a migratory songbird
Hay harvests have detrimental ecological effects on breeding songbirds, as harvesting results in nest failure. Importantly, whether harvesting also affects evolutionary processes is not known. We explored how hay harvest affected social and genetic mating patterns, and thus, the overall opportunity for sexual selection and evolutionary processes for a ground-nesting songbird, the Savannah sparrow (Passerculus sandwichensis). On an unharvested field, 55% of females were in polygynous associations, and social polygyny was associated with greater rates of extra-pair paternity (EPP). In this treatment, synchrony explained variation in EPP rates, as broods by more synchronous females had more EPP than broods by asynchronous females. In contrast, on a harvested field, simultaneous nest failure caused by haying dramatically decreased the overall incidence of EPP by increasing the occurrence of social monogamy and, apparently, the ability of polygynous males to maintain paternity in their own nests. Despite increased social and genetic monogamy, these haying-mediated changes in mating systems resulted in greater than twofold increase in the opportunity for sexual selection. This effect arose, in part, from a 30% increase in the variance associated with within-pair fertilization success, relative to the unharvested field. This effect was caused by a notable increase (+110%) in variance associated with the quality of social mates following simultaneous nest failure. Because up to 40% of regional habitat is harvested by early June, these data may demonstrate a strong population-level effect on mating systems, sexual selection, and consequently, evolutionary processes. ?? 2008 The Authors.
Molecular Ecology↗
Movements of wintering Dunlin Calidris alpina and changing habitat availability in an agricultural wetland landscape
Few studies have assessed how the dynamics of wetland bird movements relate to changing resource availability, particularly at more than one spatial scale. Within western Oregon's Williamette Valley, we examined winter resident Dunlin Calidris alpina movements in relation to a decrease in availability of preferred shorebird foraging habitat from early to late winter of 1999-2000. By tracking movements of 15 (early winter) and 12 (late winter) radiomarked individuals, we calculated home ranges and characterized presence/absence of a preference for shorebird foraging habitat during each winter period. Between periods, we compared: (1) percentage of shorebird habitat in home ranges to its availability in the landscape (regional preference), (2) percentage of radio locations in shorebird habitat to its availability within home ranges (local preference) and (3) relative use of roost sites. Concurrent with a 75% decrease in available shorebird habitat from early to late winter, average home range sizes increased by a factor of 3.8. At a regional scale, home ranges in early winter included a significantly greater percentage of shorebird foraging habitat than was available in the wider landscape. However, by late winter, the percent of shorebird habitat in home ranges did not match availability in the landscape. At the local scale, for both winter periods Dunlin were located in shorebird foraging habitat more often than expected given availability of habitat within home ranges [Correction added after online pub-lication 23 May 2008: sentence amended]. An increase in the number of roosts used from early to late winter implies possible reliance on additional sites in late winter for foraging opportunities. Results suggest that wet, unvegetated habitat is sought by Dunlin throughout winter, but individuals could not select home ranges in late winter that fully compensated for seasonal loss of habitat. ?? 2008 The Authors.
Ibis↗
Effects of agricultural nutrient management on nitrogen fate and transport in Lancaster County, Pennsylvania
Nitrogen inputs to, and outputs from, a 55-acre site in Lancaster County, Pennsylvania, were estimated to determine the pathways and relative magnitude of loads of nitrogen entering and leaving the site, and to compare the loads of nitrogen before and after the implementation of nutrient management. Inputs of nitrogen to the site were manure fertilizer, commercial fertilizer, nitrogen in precipitation, and nitrogen in ground-water inflow; and these sources averaged 93, 4, 2, and 1 percent of average annual nitrogen additions, respectively. Outputs of nitrogen from the site were nitrogen in harvested crops, loads of nitrogen in surface runoff, volatilization of nitrogen, and loads of nitrogen in ground-water discharge, which averaged 37, less than 1,25, and 38 percent of average annual nitrogen removals from the site, respectively. Virtually all of the nitrogen leaving the site that was not removed in harvested crops or by volatilization was discharged in the ground water. Applications of manure and fertilizer nitrogen to 47.5 acres of cropped fields decreased about 33 percent, from an average of 22,700 pounds per year (480 pounds per acre per year) before nutrient management to 15,175 pounds of nitrogen per year (320 pounds per acre per year) after the implementation of nutrient management practices. Nitrogen loads in ground-water discharged from the site decreased about 30 percent, from an average of 292 pounds of nitrogen per million gallons of ground water before nutrient management to an average of 203 pounds of nitrogen per million gallons as a result of the decreased manure and commercial fertilizer applications. Reductions in manure and commercial fertilizer applications caused a reduction of approximately 11,000 pounds (3,760 pounds per year, 70 pounds per acre per year) in the load of nitrogen discharged in ground water from the 55-acre site during the three-year period 1987-1990.
Water Resources Bulletin↗
Geology and ground water resources of the Matanuska Valley agricultural area, Alaska
No abstract available.
Alaska↗
Bacterial oxidation of methyl bromide in fumigated agricultural soils
The oxidation of [ 14 C]methyl bromide ([ 14 C]MeBr) to 14 CO 2 was measured in field experiments with soils collected from two strawberry plots fumigated with mixtures of MeBr and chloropicrin (CCl 3 NO 2 ). Although these fumigants are considered potent biocides, we found that the highest rates of MeBr oxidation occurred 1 to 2 days after injection when the fields were tarped, rather than before or several days after injection. No oxidation of MeBr occurred in heat-killed soils, indicating that microbes were the causative agents of the oxidation. Degradation of MeBr by chemical and/or biological processes accounted for 20 to 50% of the loss of MeBr during fumigation, with evasion to the atmosphere inferred to comprise the remainder. In laboratory incubations, complete removal of [ 14 C]MeBr occurred within a few days, with 47 to 67% of the added MeBr oxidized to 14 CO 2 and the remainder of counts associated with the solid phase. Chloropicrin inhibited the oxidation of MeBr, implying that use of this substance constrains the extent of microbial degradation of MeBr during fumigation. Oxidation was by direct bacterial attack of MeBr and not of methanol, a product of the chemical hydrolysis of MeBr. Neither nitrifying nor methane-oxidizing bacteria were sufficiently active in these soils to account for the observed oxidation of MeBr, nor could the microbial degradation of MeBr be linked to cooxidation with exogenously supplied electron donors. However, repeated addition of MeBr to live soils resulted in higher rates of its removal, suggesting that soil bacteria used MeBr as an electron donor for growth. To support this interpretation, we isolated a gram-negative, aerobic bacterium from these soils which grew with MeBr as a sole source of carbon and energy.
California↗
Fifty-years of advances in hyperspectral remote sensing of agriculture and vegetation-Summary, insights, and highlights of Volume IV
No abstract available.
Book chapter↗
Fifty-years of advances in hyperspectral remote sensing of agriculture and vegetation: Summary, insights, and highlights of volume III
The goal of this summary chapter is twofold. The first is to provide the reader an overview of the content of the preceding chapters. This they can read at the very beginning, before moving on to individual chapters in detail. Alternatively, they may read it at the very end to refresh their memory and to summarize the contents of the Volume. Second, this summary provides the editors’ perspective, bringing in their rich collective experience and expertise to guide the reader. We have kept the summaries brief and illustrative, so that the reader can quickly gather essential initial knowledge and guidance. The in-depth details can be found in the individual chapters.
Book chapter↗
Fifty years of advances in hyperspectral remote sensing of agriculture and vegetation—Summary, insights, and highlights of volume II
No abstract available.
Book chapter↗
Agricultural drought monitoring in Kenya using evapotranspiration derived from remote sensing and reanalysis data
No abstract available.
Book chapter↗
Use of multispectral Ikonos imagery for discriminating between conventional and conservation agricultural tillage practices
There is a global concern about the increase in atmospheric concentrations of greenhouse gases. One method being discussed to encourage greenhouse gas mitigation efforts is based on a trading system whereby carbon emitters can buy effective mitigation efforts from farmers implementing conservation tillage practices. These practices sequester carbon from the atmosphere, and such a trading system would require a low-cost and accurate method of verification. Remote sensing technology can offer such a verification technique. This paper is focused on the use of standard image processing procedures applied to a multispectral Ikonos image, to determine whether it is possible to validate that farmers have complied with agreements to implement conservation tillage practices. A principal component analysis (PCA) was performed in order to isolate image variance in cropped fields. Analyses of variance (ANOVA) statistical procedures were used to evaluate the capability of each Ikonos band and each principal component to discriminate between conventional and conservation tillage practices. A logistic regression model was implemented on the principal component most effective in discriminating between conventional and conservation tillage, in order to produce a map of the probability of conventional tillage. The Ikonos imagery, in combination with ground-reference information, proved to be a useful tool for verification of conservation tillage practices.
Photogrammetric Engineering and Remote Sensing↗