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USGS2011

Field tracer investigation of unsaturated zone flow paths and mechanisms in agricultural soils of northwestern Mississippi, USA

In many farmed areas, intensive application of agricultural chemicals and withdrawal of groundwater for irrigation have led to water quality and supply issues. Unsaturated-zone processes, including preferential flow, play a major role in these effects but are not well understood. In the Bogue Phalia basin, an intensely agricultural area in the Delta region of northwestern Mississippi, the fine-textured soils often exhibit surface ponding and runoff after irrigation and rainfall as well as extensive surface cracking during prolonged dry periods. Fields are typically land-formed to promote surface flow into drainage ditches and streams that feed into larger river ecosystems. Downward flow of water below the root zone is considered minimal; regional groundwater models predict only 5% or less of precipitation recharges the heavily used alluvial aquifer. In this study transport mechanisms within and below the root zone of a fallow soybean field were assessed by performing a 2-m ring infiltration test with tracers and subsurface monitoring instruments. Seven months after tracer application, 48 continuous cores were collected for tracer extraction to define the extent of water movement and quantify preferential flow using a mass-balance approach. Vertical water movement was rapid below the pond indicating the importance of vertical preferential flow paths in the shallow unsaturated zone, especially to depths where agricultural disturbance occurs. Lateral flow of water at shallow depths was extensive and spatially non-uniform, reaching up to 10. m from the pond within 2. months. Within 1. month, the wetting front reached a textural boundary at 4-5. m between the fine-textured soil and sandy alluvium, now a potential capillary barrier which, prior to extensive irrigation withdrawals, was below the water table. Within 10. weeks, tracer was detectable at the water table which is presently about 12. m below land surface. Results indicate that 43% of percolation may be through preferential flow paths and that any water breaking through the capillary barrier (as potential recharge) likely does so in fingers which are difficult to detect with coring methods. In other areas where water levels have declined and soils have similar properties, the potential for transport of agricultural chemicals to the aquifer may be greater than previously assumed. ?? 2010 .

Journal of Hydrology↗

USGS2007

Walnut creek watershed monitoring project, Iowa: Monitoring water quality in response to prairie restoration

Land use and surface water data for nitrogen and pesticides (1995 to 1997) are reported for the Walnut Creek Watershed Monitoring Project, Jasper County Iowa. The Walnut Creek project was established in 1995 as a nonpoint source monitoring program in relation to watershed habitat restoration and agricultural management changes implemented at the Neal Smith National Wildlife Refuge by the U.S. Fish and Wildlife Service. The monitoring project utilizes a paired-watershed approach (Walnut and Squaw creeks) as well as upstream/downstream comparisons on Walnut for analysis and tracking of trends. From 1992 to 1997, 13.4 percent of the watershed was converted from row crop to native prairie in the Walnut Creek watershed. Including another 6 percent of watershed farmed on a cash-rent basis, land use changes have been implemented on 19.4 percent of the watershed by the USFWS. Nitrogen and pesticide applications were reduced an estimated 18 percent and 28 percent in the watershed from land use changes. Atrazine was detected most often in surface water with frequencies of detection ranging from 76-86 percent. No significant differences were noted in atrazine concentrations between Walnut and Squaw Creek. Nitrate-N concentrations measured in both watersheds were similar; both basins showed a similar pattern of detection and an overall reduction in nitrate-N concentrations from upstream to downstream monitoring sites. Water quality improvements are suggested by nitrate-N and chloride ratios less than one in the Walnut Creek watershed and low nitrate-N concentrations measured in the subbasin of Walnut Creek containing the greatest amount of land use changes. Atrazine and nitrate-N concentrations from the lower portion of the Walnut Creek watershed (including the prairie restoration area) may be decreasing in relation to the upstream untreated component of the watershed. The frequencies of pesticide detections and mean nitrate-N concentrations appear related to the percentage of row crop in the basins and subbasins. Although some results are encouraging, definitive water quality improvements have not been observed during the first three years of monitoring. Possible reasons include: (1) more time is needed to adequately detect changes; (2) the size of the watershed is too large to detect improvements; (3) land use changes are not located in the area of the watershed where they would have greatest effect; or (4) water quality improvements have occurred but have been missed by the project monitoring design. Longer-term monitoring will allow better evaluation of the impact of restoration activities on water quality.An overview is given on the Walnut Creek Watershed Monitoring Project established as a nonpoint source monitoring program in relation to watershed habitat restoration and agricultural management changes implemented at the Neal Smith National Wildlife Refuge by the U.S. Fish and Wildlife Services. Focus is on land use and surface water data for nitrogen and pesticides. Initial results obtained for the first three years of monitoring are discussed.

Iowa↗

USGS2013

Biochar effect on maize yield and soil characteristics in five conservation farming sites in Zambia

Biochar addition to agricultural soils can improve soil fertility, with the added bonus of climate change mitigation through carbon sequestration. Conservation farming (CF) is precision farming, often combining minimum tillage, crop rotation and residue retention. In the present farmer-led field trials carried out in Zambia, the use of a low dosage biochar combined with CF minimum tillage was tested as a way to increase crop yields. Using CF minimum tillage allows the biochar to be applied to the area where most of the plant roots are present and mirrors the fertilizer application in CF practices. The CF practice used comprised manually hoe-dug planting 10-L sized basins, where 10%–12% of the land was tilled. Pilot trials were performed with maize cob biochar and wood biochar on five soils with variable physical/chemical characteristics. At a dosage as low as 4 tons/ha, both biochars had a strong positive effect on maize yields in the coarse white aeolian sand of Kaoma, West-Zambia, with yields of 444% ± 114% ( p = 0.06) and 352% ± 139% ( p = 0.1) of the fertilized reference plots for maize and wood biochar, respectively. Thus for sandy acidic soils, CF and biochar amendment can be a promising combination for increasing harvest yield. Moderate but non-significant effects on yields were observed for maize and wood biochar in a red sandy clay loam ultisol east of Lusaka, central Zambia (University of Zambia, UNZA, site) with growth of 142% ± 42% ( p > 0.2) and 131% ± 62% ( p > 0.2) of fertilized reference plots, respectively. For three other soils (acidic and neutral clay loams and silty clay with variable cation exchange capacity, CEC), no significant effects on maize yields were observed ( p > 0.2). In laboratory trials, 5% of the two biochars were added to the soil samples in order to study the effect of the biochar on physical and chemical soil characteristics. The large increase in crop yield in Kaoma soil was tentatively explained by a combination of an increased base saturation (from <50% to 60%–100%) and cation exchange capacity (CEC; from 2–3 to 5–9 cmol/kg) and increased plant-available water (from 17% to 21%) as well as water vapor uptake (70 mg/g on maize cob biochar at 50% relative humidity).

Agronomy Journal↗

USGS2014

Analysis of projected water availability with current basin management plan, Pajaro Valley, California

The projection and analysis of the Pajaro Valley Hydrologic Model (PVHM) 34 years into the future using MODFLOW with the Farm Process (MF-FMP) facilitates assessment of potential future water availability. The projection is facilitated by the integrated hydrologic model, MF-FMP that fully couples the simulation of the use and movement of water from precipitation, streamflow, runoff, groundwater flow, and consumption by natural and agricultural vegetation throughout the hydrologic system at all times. MF-FMP allows for more complete analysis of conjunctive-use water-resource systems than previously possible with MODFLOW by combining relevant aspects of the landscape with the groundwater and surface-water components. This analysis is accomplished using distributed cell-by-cell supply-constrained and demand-driven components across the landscape within “water-balance subregions” (WBS) comprised of one or more model cells that can represent a single farm, a group of farms, watersheds, or other hydrologic or geopolitical entities. Analysis of conjunctive use would be difficult without embedding the fully coupled supply-and-demand into a fully coupled simulation, and are difficult to estimate a priori. The analysis of projected supply and demand for the Pajaro Valley indicate that the current water supply facilities constructed to provide alternative local sources of supplemental water to replace coastal groundwater pumpage, but may not completely eliminate additional overdraft. The simulation of the coastal distribution system (CDS) replicates: 20 miles of conveyance pipeline, managed aquifer recharge and recovery (MARR) system that captures local runoff, and recycled-water treatment facility (RWF) from urban wastewater, along with the use of other blend water supplies, provide partial relief and substitution for coastal pumpage (aka in-lieu recharge). The effects of these Basin Management Plan (BMP) projects were analyzed subject to historical climate variations and assumptions of 2009 urban water demand and land use. Water supplied directly from precipitation, and indirectly from reuse, captured local runoff, and groundwater is necessary but inadequate to satisfy agricultural demand without coastal and regional storage depletion that facilitates seawater intrusion. These facilities reduce potential seawater intrusion by about 45% with groundwater levels in the four regions served by the CDS projected to recover to levels a few feet above sea level. The projected recoveries are not high enough to prevent additional seawater intrusion during dry-year periods or in the deeper aquifers where pumpage is greater. While these facilities could reduce coastal pumpage by about 55% of the historical 2000–2009 pumpage for these regions, and some of the water is delivered in excess of demand, other coastal regions continue to create demands on coastal pumpage that will need to be replaced to reduce seawater intrusion. In addition, inland urban and agricultural demands continue to sustain water levels below sea level causing regional landward gradients that also drive seawater intrusion. Seawater intrusion is reduced by about 45% but it supplies about 55% of the recovery of groundwater levels in the coastal regions served by the CDS. If economically feasible, water from summer agricultural runoff and tile-drain returnflows could be another potential local source of water that, if captured and reused, could offset the imbalance between supply and demand as well as reducing discharge of agricultural runoff into the National Marine Sanctuary of Monterey Bay. A BMP update (2012) identifies projects and programs that will fund a conservation program and will provide additional, alternative water sources to reduce or replace coastal and inland pumpage, and to replenish the aquifers with managed aquifer recharge in an inland portion of the Pajaro Valley.

California↗

USGS2011

Nutrients and sediment in frozen-ground runoff from no-till fields receiving liquid-dairy and solid-beef manures

Nutrients and sediment in surface runoff from frozen agricultural fields were monitored within three small (16.0 ha [39.5 ac] or less), adjacent basins at a no-till farm in southwest Wisconsin during four winters from 2003 to 2004 through 2006 to 2007. Runoff depths and flow-weighted constituent concentrations were compared to determine the impacts of surface-applied liquid-dairy or solid-beef manure to frozen and/or snow-covered ground. Despite varying the manure type and the rate and timing of applications, runoff depths were not significantly different among basins within each winter period. Sediment losses were low (generally less than 22 kg ha −1 [20 lb ac −1 ] in any year) and any statistical differences in sediment concentrations among basins were not related to the presence or absence of manure or the amount of runoff. Concentrations and losses of total nitrogen and total phosphorus were significantly increased in basins that had either manure type applied less than one week preceding runoff. These increases occurred despite relatively low application rates. Lower concentrations and losses were measured in basins that had manure applied in fall and early winter and an extended period of time (months) had elapsed before the first runoff event. The highest mean, flow-weighted concentrations of total nitrogen (31.8 mg L −1 ) and total phosphorus (10.9 mg L −1 ) occurred in winter 2003 to 2004, when liquid-dairy manure was applied less than one week before runoff. On average, dissolved phosphorus accounted for over 80% of all phosphorus measured in runoff during frozen-ground periods. The data collected as part of this study add to the limited information on the quantity and quality of frozen-ground runoff at field edges, and the results highlight the importance of manure management decisions during frozen-ground periods to minimize nutrients lost in surface runoff.

Wisconsin↗

USGS2016

Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data

The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia, using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season (June–October), followed by a fallow during the rabi season (November–February). These cropland areas are not suitable for growing rabi -season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea ( Cicer arietinum L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary ( kharif ) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left fallow during the second ( rabi ) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during rabi season. Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3 Mha of suitable rice-fallow areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.

International Journal of Digital Earth↗

USGS2015

Remote sensing to monitor cover crop adoption in southeastern Pennsylvania

In the Chesapeake Bay Watershed, winter cereal cover crops are often planted in rotation with summer crops to reduce the loss of nutrients and sediment from agricultural systems. Cover crops can also improve soil health, control weeds and pests, supplement forage needs, and support resilient cropping systems. In southeastern Pennsylvania, cover crops can be successfully established following corn (Zea mays L.) silage harvest and are strongly promoted for use in this niche. They are also planted following corn grain, soybean (Glycine max L.), and vegetable harvest. In Pennsylvania, the use of winter cover crops for agricultural conservation has been supported through a combination of outreach, regulation, and incentives. On-farm implementation is thought to be increasing, but the actual extent of cover crops is not well quantified. Satellite imagery can be used to map green winter cover crop vegetation on agricultural fields and, when integrated with additional remote sensing data products, can be used to evaluate wintertime vegetative groundcover following specific summer crops. This study used Landsat and SPOT (System Probatoire d’ Observation de la Terre) satellite imagery, in combination with the USDA National Agricultural Statistics Service Cropland Data Layer, to evaluate the extent and amount of green wintertime vegetation on agricultural fields in four Pennsylvania counties (Berks, Lebanon, Lancaster, and York) from 2010 to 2013. In December of 2010, a windshield survey was conducted to collect baseline data on winter cover crop implementation, with particular focus on identifying corn harvested for silage (expected earlier harvest date and lower levels of crop residue), versus for grain (expected later harvest date and higher levels of crop residue). Satellite spectral indices were successfully used to detect both the amount of green vegetative groundcover and the amount of crop residue on the surveyed fields. Analysis of wintertime satellite imagery showed consistent increases in vegetative groundcover over the four-year study period and determined that trends did not result from annual weather variability, indicating that farmers are increasing adoption of practices such as cover cropping that promote wintertime vegetation. Between 2010 and 2013, the occurrence of wintertime vegetation on agricultural fields increased from 36% to 67% of corn fields in Berks County, from 53% to 75% in Lancaster County, from 42% to 65% in Lebanon County, and from 26% to 52% in York County. Apparently, efforts to promote cover crop use in the Chesapeake Bay Watershed have coincided with a rapid increase in the occurrence of wintertime vegetation following corn harvest in southeastern Pennsylvania. However, despite these increases, between 25% and 48% of corn fields remained without substantial green vegetation over the wintertime, indicating further opportunity for cover crop adoption.

Pennsylvania↗

USGS2018

A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform

Mapping high resolution (30-m or better) cropland extent over very large areas such as continents or large countries or regions accurately, precisely, repeatedly, and rapidly is of great importance for addressing the global food and water security challenges. Such cropland extent products capture individual farm fields, small or large, and are crucial for developing accurate higher-level cropland products such as cropping intensities, crop types, crop watering methods (irrigated or rainfed), crop productivity, and crop water productivity. It also brings many challenges that include handling massively large data volumes, computing power, and collecting resource intensive reference training and validation data over complex geographic and political boundaries. Thereby, this study developed a precise and accurate Landsat 30-m derived cropland extent product for two very important, distinct, diverse, and large countries: Australia and China. The study used of eight bands (blue, green, red, NIR, SWIR1, SWIR2, TIR1, and NDVI) of Landsat-8 every 16-day Operational Land Imager (OLI) data for the years 2013–2015. The classification was performed by using a pixel-based supervised random forest (RF) machine learning algorithm (MLA) executed on the Google Earth Engine (GEE) cloud computing platform. Each band was time-composited over 4–6 time-periods over a year using median value for various agro-ecological zones (AEZs) of Australia and China. This resulted in a 32–48-layer mega-file data-cube (MFDC) for each of the AEZs. Reference training and validation data were gathered from: (a) field visits, (b) sub-meter to 5-m very high spatial resolution imagery (VHRI) data, and (c) ancillary sources such as from the National agriculture bureaus. Croplands versus non-croplands knowledge base for training the RF algorithm were derived from MFDC using 958 reference-training samples for Australia and 2130 reference-training samples for China. The resulting 30-m cropland extent product was assessed for accuracies using independent validation samples: 900 for Australia and 1972 for China. The 30-m cropland extent product of Australia showed an overall accuracy of 97.6% with a producer’s accuracy of 98.8% (errors of omissions = 1.2%), and user’s accuracy of 79% (errors of commissions = 21%) for the cropland class. For China, overall accuracies were 94% with a producer’s accuracy of 80% (errors of omissions = 20%), and user’s accuracy of 84.2% (errors of commissions = 15.8%) for cropland class. Total cropland areas of Australia were estimated as 35.1 million hectares and 165.2 million hectares for China. These estimates were higher by 8.6% for Australia and 3.9% for China when compared with the traditionally derived national statistics. The cropland extent product further demonstrated the ability to estimate sub-national cropland areas accurately by providing an R 2 value of 0.85 when compared with province-wise cropland areas of China. The study provides a paradigm-shift on how cropland maps are produced using multi-date remote sensing. These products can be browsed at www.croplands.org and made available for download at NASA’s Land Processes Distributed Active Archive Center (LP DAAC) https://www.lpdaac.usgs.gov/node/1282 .

ISPRS Journal of Photogrammetry and Remote Sensing↗