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The objective of this project is to investigate remote sensing requirements for irrigation scheduling to define future systems. Temperature-based crop stress indicators have been developed that could be used for irrigation management. This viewgraph presentation describes an experiment to use airborne and satellite thermal imagery to evaulate the water requirements of irrigated crops.
NASA's White Sands Test Facility has six core environmental compliance capabilities: remote hazardous testing of reactive, explosive and toxic materials and fluids; hypergolic fluids materials and systems testing; oxygen materials and system testing; hypervelocity impact testing; flight hardware processing; and, propulsion testing. The facility's permit status and challenges are reviewed. Historic operations and practices dating from the 1960s through the early 1980s resulted in contamination of the facility's groundwater. An environmental restoration effort has been employed to protect public health and the health of the workforce. The restoration seeks to properly handle hazardous materials and waste processes; determine the nature and extent of the contamination; stop the migration of contaminated groundwater; stabilize the plume front which has been assessed as the greatest risk to public health; and, clean-up the environment to restore it to preexisting conditions. The Plume Front Treatment System is operational and seeks to stop the westward movement of the plume to protect drinking water and irrigation well. Specifically, the treatment system will extract contaminated water from the aquifer, remove chemical using the best available technology, and return (inject) the treated water back to the aquifer. The Mid-Plume Interception Treatment System also seeks to stop the migration of containment, as well as to evaluate new technologies to accelerate cleanup, such as bioremediation.
Agriculture yields are susceptible to changes in future temperature, precipitation, and other Earth system factors. Future changes to these physical Earth system attributes and their effects on agricultural yields are highly uncertain. United States agricultural producers will be affected by such changes whether they occur domestically or internationally (via international commodity markets). How important to U.S. agriculture are domestic changes due to climate compared to those occurring externally? Here we show that potential direct impacts to United States agriculture have financial impacts on U.S. producers that are roughly similar in magnitude but opposite in sign to impacts on U.S. producers due to changes in other parts of the world. This finding is robust across application of a wide range of potential future crop yield impacts applied to a multi-sector global integrated assessment model. Therefore, when examining country-specific impacts, it is necessary to model both the domestic and international impacts.
In this study, we explore opportunities to optimize food-energy-water (FEW) resources by closing nutrient loops in arid-land rivers. Specifically, we evaluate source and sink behavior of nitrogen as nitrate (NO 3 -N) in three characteristic channels in the Middle Rio Grande Basin (Delivery and Drain channels associated with agriculture and the main channel of the Rio Grande). All three channels are located downstream of a large wastewater treatment plant that is the main contributor of nutrients to this reach of the Rio Grande. We used a mass balance approach paired with stable isotope analysis to determine sources and processing of NO 3 -N within the channels over time (a year) and through space (along ~15 to 50 km reaches). Results indicated the growing season was an important period of sink behavior for the Delivery channel and the Rio Grande, but the Drain channel was a year-round source. Stable isotope analysis of 15 N and 18 O found a distinct nitrate signature in the Drain associated with biological processing, as well as Rio Grande sites impacted by agricultural outflow, but no equivalent signature was present in the Delivery channel. Based on our findings, we provide recommendations to help close nutrient loops in the study system and analogous aridland irrigation networks by 1) minimizing loss during the transfer of nutrients from wastewater facilities to agricultural areas, and 2) minimizing enrichment to downstream aquatic ecosystems by sequestering nutrients that escape the nutrient loop.
Soil moisture can also influence the concentration of atmospheric trace gases by moderating the emission of nitrogen oxides (NOx = NO + NO2) from agricultural fields. Human activities can play an important role in controlling the available soil moisture depending on irrigation demand and agricultural management. To further complicate matters, nitrogen fertilizer use has also been found to be a significant source of NOx emissions in agricultural areas. In fact, some of the highest emissions have been reported from fertilized soils in high-temperature agricultural regions, such as the Imperial Valley of California. Since NO2 is an important precursor to ozone formation in the troposphere, which is a leading cause of premature death in humans, it is critical to understand how natural and anthropogenic factors contribute to NOx emissions in these areas. O3 pollution is also a growing threat to global food security due to its detrimental impacts on crop production. This work uses a suite of satellite, ground-based, and model data to investigate how agricultural soil NOx emissions from natural (rainfall) and anthropogenic factors (irrigation, nitrogen fertilizer) govern air quality over California. We evaluate the capabilities of using SMAP retrievals and SMAP Land Information System (LIS) output for monitoring irrigation activities over the major agricultural areas of California by conducting intensive analyses of soil moisture and precipitation data. High-resolution trace gas observations from the new generation TROPOspheric Monitoring Instrument (TROPOMI) sensor are used to characterize and monitor the variability of trace gases and air quality conditions associated with soil NOx emissions. We also synthesize satellite, ground-based, and agriculture data to estimate the separate contributions from rainfall, irrigation, and nitrogen fertilizer practices on soil NOx emissions and associated air quality conditions. Finally, unprecedented hourly trace gas retrievals from the NASA Tropospheric Emissions: Monitoring of Pollution (TEMPO) geostationary satellite sensor are used to monitor the diurnal evolution of NO2 and O3 concentrations from soil NOx emissions.
Ionic silver (Ag+) is being investigated as a residual biocide for use in spacecraft potable water systems on future crewed missions. In addition to providing clean water to the crew and other life support system functions, the potable water is used to irrigate space crop production units such as the Vegetable Production System (Veggie) and the Advanced Plant Habitat (APH). We have evaluated the impact of different concentrations of Ag+ biocide solutions in comparison to a control in both substrate (arcillite-based) and substrate-less (hydroponics-based) growth set ups. Here, we provide evidence that increasing the concentration of silver in the irrigation water impacts the root zone microbiome in both setups, with plant growth and elemental nutrient content also affected in the hydroponic set up. This suggests a need for a silver removal step to achieve acceptable silver levels in irrigation water before application to space crops in a substrate-less hydroponics system. This removal step is also recommended for a substrate-based system, although it is not as critical as in a hydroponics system.
Studies have shown that irrigated agriculture has substantial effects on local to regional hydrologic and atmospheric processes. These effects include increased evapotranspiration and near surface humidity, decreased air and ground temperature, augmented downwind precipitation, enhanced recharge, depletion of source water stocks, and overall changes to the regional water budget. However, developers of global offline and coupled modeling systems have been slow to incorporate irrigation. This presentation will describe progress towards simulating irrigation worldwide in the Land Information System (LIS) and Global Land Data Assimilation System (GLDAS). We have developed and refined the ability to simulate sprinkler irrigation, furrow irrigation, paddy irrigation, and drip irrigation. We have reconciled multiple global and national irrigation, land cover, and crop type databases in an effort to (1) distinguish irrigated and rainfed agriculture, (2) simulate the proper distribution of crops (as sub-grid tiles) in each model grid pixel, and (3) apply the most likely irrigation method in each tile based on the crop type and country or state level information on the relative usage of sprinkler, flood, and drip irrigation. Using agricultural water withdrawal data, as available, for calibration and evaluation, we show that the implemented approach is promising but that much fine tuning remains to be done. In particular, irrigation model parameters that produce good results in one location often produce less satisfying results in others.
Approximately 70% of Minnesota's irrigation is with center pivot distribution systems whose diagnostic appearance on remotely sensed imagery is a circular pattern which can be readily identified on LANDSAT MSS band imagery. Fields irrigated with traveling guns, laterals, booms, or cornering systems either result in angular field patterns or obscure the circular patterns normally visible on imagery. The IDMS system at Goddard was used to develop a LANDSAT digital classification of the Sherburne County area, which located fields regardless of shape, and was not dependent of visual interpretation. Ground truth collection and classification attempts are described in an effort to inventory all wells in the area.
Land surface models have facilitated the estimation of soil moisture over a range of spatiotemporal scales. However, limitations in model parameterization and under-representation of anthropogenic processes restrict their ability to estimate local-scale soil moisture variability, especially over irrigated areas. Assimilation of satellite-based soil moisture retrievals into land surface models can be a viable approach to overcome these constraints, specially over highly irrigated countries such as India, where such applications are rare. Additionally, large-scale validation of modeled soil moisture has been limited over India till now due to lack of a representative station network. By assimilating Soil Moisture Active Passive (SMAP)-based estimates into the state-of-the-art Indian Land Data Assimilation System (ILDAS) and combining with a new soil moisture station network of more than 200 stations, this study demonstrates improved soil moisture estimations and capture of irrigation signals over the region. The Noah-MP land surface model is forced by multiple local and global meteorological datasets and Ensemble Kalman Filter (EnKF) is used for assimilation of soil moisture. Comparison of open-loop and data assimilated soil moisture against station soil moisture data shows relative spatial mean improvement of 0.0178 in correlation and 0.0029 m3/m3 in RMSE. Further statistical comparison with in-situ data has also shown better results over most of the stations, as evident from improved correlations and reduced unbiased RMSE after assimilation. Finally, the climatology of soil moisture over the different irrigation fractions reveals that data assimilated outputs over irrigated grid cells tend to have higher soil moisture during dry winter season, demonstrating the ability to capture irrigation signals. These findings quantify the value of data assimilation in improving soil moisture estimates and the ability to capture unmodeled processes such as irrigation, which lays the science groundwork for upcoming space missions such as NASA ISRO Synthetic Aperture Radar (NISAR).
This is the AmeriFlux version of the carbon flux data for the site US-UR6 Napi - UCRB. Site Description - This site is located in Farmington, New Mexico, within a flat terrain and irrigated by a center pivot system. The region has a semi-arid climate, with warm summers and mild winters. The area is predominantly covered by alfalfa, which thrives in the irrigated conditions.
This is the AmeriFlux version of the carbon flux data for the site US-UR8 Yellow Jacket - UCRB. Site Description - This site is located in Yellow Jacket, Colorado, on a moderate slope. The area is irrigated using a center pivot system, with alfalfa being the dominant vegetation. The region experiences a temperate climate, characterized by cool to mild temperatures throughout the year and substantial annual precipitation, creating favorable conditions for agricultural activities.
U.S. water demand varies sharply by sector and region as land use, population, weather patterns, and economic activity co-evolve. High-resolution water demand data is required to capture these dynamics, support integrated energy-water-land modeling, and local-to-regional water scarcity assessments. This dataset contains gridded (1/8 degree), monthly, multi-sector water demand dataset for the contiguous United States (CONUS) covering 1980-2100 across eight future scenarios of human-Earth system change. The dataset covers irrigation, thermoelectric, municipal (public-supply and domestic), livestock, manufacturing, and mining demands, separately for withdrawals and consumption, and includes per-cell renewable vs. non-renewable water source attributions. The dataset is validated against the latest USGS 2010-2020 water-use data for the three largest water demand sectors (Domestic, Electricity, and Irrigation), with correlations ranging from 0.73-0.95 at the HUC6 scale. The two datasets largely agree on an aggregate basis with per-sector bias falling within +/-7%, but they disagree on the spatial allocation of water with individual HUC6 basins having normalized RMSE from 68-171% and median absolute percent difference from 37-86%. This dataset advances prior global products by combining state-resolved sectoral demands from GCAM-USA, future power-plant siting from the CERF model, and scenario-consistent high-resolution climate and population forcing data across the eight scenarios.
The author has identified the following significant results. A large potential irrigation area with water delivery system in place was identified from ERTS-1 imagery. The site is in the Sahara Desert. Color additive change detection imagery was used to assess ground water potentials in the Savannah in conjunction with a major US AID-Mali livestock sector initiative. The potential capacity to map laterite deposits in the Inland Delta from space was established with the help of aerial and ground surveys. A color composite of the Inland Delta could have saved French biogeographers 3 5/6 man-years of professional field work had it been available, according to the man who prepared a plant community map of part of the southern Inland Delta.
Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology and growth. However, future projections, especially at the global scale, do not consider any agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models (GGCMs) contributing to the AgMIP-Gridded project to quantify the impacts and adaptation potential of field crops under increasing temperature. We study how uniform warming scenarios up to 6 K affect the productivity and growing period duration of five major crops. The design of the experiment aims at understanding adaptation measures targeted to temperature-driven impacts and therefore leaves out changes in any other climate variable. We find that, without adaptation the dominant effect of temperature increase is to shorten the growing period and to reduce yields and production, consistently across crops and regions. We then test the potential of two agronomic measures to contrast warming-induced yield reduction, assuming that (i) cultivars with adjusted phenology would be used to regain the reference growing period duration; (ii) rainfed systems would be converted to irrigated. Despite substantial uncertainties in model parametrization and little agreement in spatial patterns, at the global aggregation, model results are robust. We find that up to 3 K of temperature increase, production losses could be fully compensated by maintaining the original crop growing period. Irrigation would also compensate production losses, but would not reduce the temperature impacts. Across regions, the model ensemble estimates larger adaptation potentials from unchanged growing periods in continental and temperate regions, than in tropical and arid regions, where also irrigation has respectively little effects and availability.
High-throughput, field-based characterization of root systems for hundreds of genotypes in thousands of plots is necessary for breeding and identifying loci underlying variation in root traits and their plasticity. We designed a large-scale sampling of root pulling force, the vertical force required to extract the root system from the soil, in a maize diversity panel under differing irrigation levels for two growing seasons. We then characterized the root system architecture of the extracted root crowns. We found consistent patterns of phenotypic plasticity for root pulling force for a subset of genotypes under differential irrigation, suggesting that root plasticity is predictable. Using genome-wide association analysis, we identified 54 SNPs as statistically significant for six independent root pulling force measurements across two irrigation levels and four developmental timepoints. For every significant GWAS SNP for any trait in any treatment and timepoint we conducted post hoc tests for genotype-by-environment interaction, using a mixed model ANOVA. We found that 8 of the 54 SNPs showed significant GxE. Candidate genes underlying variation in root pulling force included those involved in nutrient transport. Although they are often treated separately, variation in the ability of plant roots to sense and respond to variation in environmental resources including water and nutrients may be linked by the genes and pathways underlying this variation. While functional validation of the identified genes is needed, our results expand the current knowledge of root phenotypic plasticity at the whole plant and gene levels, and further elucidate the complex genetic architecture of maize root systems.
Abstract This study investigates the role of the land surface on the precipitation produced by an elevated mesoscale convective system (MCS) in Iowa between 24–25 June 2015 during the Plains Elevated Convection at Night (PECAN) field campaign. Previous studies have shown a strong effect of low‐level atmospheric moisture on the location of this MCS. A series of semi‐idealized and realistic simulations with irrigation are conducted to understand the effect of moisture perturbations on the MCS precipitation displacement. In general, numerical simulations place the MCS east of the observed location. Adding moisture directly in the low‐level atmosphere in the semi‐idealized experiments reduces this displacement error. However, experiments with perturbed soil moisture result in drying over Iowa induced by moisture flux divergence from cooler low‐level temperatures and higher surface pressure, causing the MCS to move further to the east. The irrigation impact on low‐level moisture is highly dependent on the length of simulation period. Shorter simulations on the order of days generate similar drying over Iowa but the opposite is found for month‐long simulations. Despite the lack of low‐level moistening in the perturbed soil moisture and short‐term irrigation experiments, the sensitivity to low‐level moisture is similar in all runs. More low‐level moisture generates a more convectively unstable environment with less inhibition and a lower level of free convection that leads to more rapid MCS development and a change in MCS location.
In support of the mission of the US Department of Energy Water Power Technologies Office to promote domestic next-generation hydropower growth, this study provides a first-of-its-kind assessment of the hydropower development potential on existing water conduits nationwide. This study evaluates the potential for conduit hydropower development in the municipal, agricultural, and industrial sectors across the United States. The research team developed systematic methods to evaluate conduit hydropower capacity potential (MW) and energy generation potential (GWh/year) at four categories of conduits across the United States. They include the following: (1) Water supply pipelines for municipal and industrial uses, (2) Wastewater discharge conduits from municipal and industrial systems, (3) Agricultural water conduits including irrigation canals and ditches in the 17 western states that rely heavily on irrigation, and (4) Thermoelectric power plant cooling water discharge conduits. For each type of conduit, the team developed and implemented a method to estimate hydraulic head and annual water flows—and the hydropower potential—based on analyses of satellite imagery, topography, and existing data sets on water systems and power plants. These methods support a consistent, replicable estimate of conduit hydropower potential across 3 sectors and all 50 states, aggregated at the county and state levels. The assessment was conducted at the reconnaissance level, considering resources that could be available for development at the state and national levels using present-day assumptions about conduit hydropower technology.
Irrigation rapidly expanded during the 20 th century, affecting climate via water, energy, and biogeochemical changes. Previous assessments of these effects predominantly relied on a single Earth System Model, and therefore suffered from structural model uncertainties. Here we quantify the impacts of historical irrigation expansion on climate by analysing simulation results from six Earth system models participating in the Irrigation Model Intercomparison Project (IRRMIP). Results show that irrigation expansion causes a rapid increase in irrigation water withdrawal, which leads to less frequent 2-meter air temperature heat extremes across heavily irrigated areas (≥4 times less likely). However, due to the irrigation-induced increase in air humidity, the cooling effect of irrigation expansion on moist-heat stress is less pronounced or even reversed, depending on the heat stress metric. In summary, this study indicates that irrigation deployment is not an efficient adaptation measure to escalating human heat stress under climate change, calling for carefully dealing with the increased exposure of local people to moist-heat stress.