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At least 55 records · Page 3

Global irrigation contribution to wheat and maize yield

Irrigation is the largest sector of human water use and an important option for increasing crop production and reducing drought impacts. However, the potential for irrigation to contribute to global crop yields remains uncertain. Here, we quantify this contribution for wheat and maize at global scale by developing a Bayesian framework integrating empirical estimates and gridded global crop models on new maps of the relative difference between attainable rainfed and irrigated yield (ΔY). At global scale, ΔY is 34 ± 9% for wheat and 22 ± 13% for maize, with large spatial differences driven more by patterns of precipitation than that of evaporative demand. Comparing irrigation demands with renewable water supply, we find 30–47% of contemporary rainfed agriculture of wheat and maize cannot achieve yield gap closure utilizing current river discharge, unless more water diversion projects are set in place, putting into question the potential of irrigation to mitigate climate change impacts.

Irrigation↗

Irrigation Characterization Improved by the Direct Use of SMAP Soil Moisture Anomalies Within a Data Assimilation System

Prior soil moisture data assimilation (DA) efforts to incorporate human management features such as agricultural irrigation has only shown limited success. This is partly due to the fact that observational rescaling approaches for bias correction used in soil moisture DA systems are less effective when unmodeled processes such as irrigation are the dominant source of systematic biases. In this article, we demonstrate an alternative approach, i.e. anomaly correction for overcoming this limitation. Unlike the rescaling approaches, the proposed method does not scale remote sensing soil moisture retrievals to the model climatology, but it extracts the temporal variability information from the retrievals. The study demonstrates this approach through the assimilation of soil moisture retrievals from the Soil Moisture Active Passive mission into the Noah land surface model. The results demonstrate that DA using the anomaly correction method can better capture the effect of irrigation on soil moisture in agricultural areas while providing comparable performance to the DA integrations using rescaling approaches in non-irrigated areas. These findings emphasize the need to reduce inconsistencies between remote sensing and the models so that assimilation methods can employ information from remote sensing more directly to develop representations of unmodeled processes such as irrigation.

soil moisture↗

Monitoring irrigated land acreage using LANDSAT imagery: An application example

A demonstration of the utility of LANDSAT imagery for quickly and cheaply estimating irrigated land area was conducted in the Klamath River basin of Oregon. LANDSAT color composite images, at 1:250,000 scale and acquired on two dates during the 1975 growing season, were interpreted. Irrigated lands were delineated manually, and the irrigated area was estimated, based on dot-grid sampling of the manually delineated lands. The image interpretation estimate of irrigated area was then adjusted by a comparison of interpretation results with ground data on 45 sample plots, each 2.6 square kilometers in size. Two interpreters independently estimated the irrigated area. Their adjusted estimates were 115,000 hectares and 108,000 hectares respectively, with corresponding 95 percent confidence intervals of + or - 7,880 hectares and + or - 14,000 hectares.

Draeger, W. C.↗

Irrigation mapping in western Kansas using Landsat. I - Key parameters

The procedure used in the identification and mapping of irrigated lands in six counties of western Kansas is presented and key considerations for the identification of irrigated lands during the project are discussed. The procedure involved the compilation of a field-by-field map of irrigated lands on the basis of multi-date Landsat band 5 imagery, the entry of map data into a computer, and the retrieval of the data in the form of maps, tables and statistics. Comparison of the positional results of the image interpretation with statistical data for a single county was used to verify the mapping procedure, as accuracies of from 80-100% were obtained, depending on the type of crop. Considerations relevant to the identification of irrigated land on the basis of remote sensing data include the form of the final data, irrigation practices in the area, the soil moisture budget, the number and kinds of crops, the crop calendar, and the availability of usable imagery.

Poracsky, J.↗

Irrigated lands assessment for water management: Technique test

A procedure for estimating irrigated land using full frame LANDSAT imagery was demonstrated. Relatively inexpensive interpretation of multidate LANDSAT photographic enlargements was used to produce a map of irrigated land in California. The LANDSAT and ground maps were then linked by regression equations to enable precise estimation of irrigated land area by county, basin, and statewide. Land irrigated at least once in California in 1979 was estimated to be 9.86 million acres, with an expected error of less than 1.75% at the 99% level of confidence. To achieve the same level of error with a ground-only sample would have required 3 to 5 times as many ground sample units statewide. A procedure for relatively inexpensive computer classification of LANDSAT digital data to irrigated land categories was also developed. This procedure is based on ratios of MSS band 7 and 5, and gave good results for several counties in the Central Valley.

Wall, S. L.↗

Possible Link Between Irrigation in the U.S. High Plains and Increased Summer Streamflow in the Midwest

We have previously presented evidence that higher rates of evapotranspiration (ET) associated with irrigation in the U.S. High Plains has likely caused an increased downwind precipitation (P). July P over the Midwest increased by 20%-30% from the pre-irrigation period (1900-1950) to the post-irrigation (1950-2000) period. In this study, we test the hypothesis that the increased July P has had hydrologic consequences, possibly increasing groundwater storage and streamflow. Seasonal analyses of hydrologic variables over Illinois suggest that the water table and streamflow response lags P - ET by 1-2 months, indicating August and September as the months when the increased July P may be detected. We analyzed long-term observations of water table depth at 10 wells in Illinois and streamflow at 46 gauges in Illinois-Ohio basins. The Mann-Kendal test for trends suggests field significant increases in groundwater storage and streamflow in August-September over the period of irrigation expansion. Examination of soil moisture response to present-day above-normal July P suggests that the increased July P can reach the water table in normal to wet years. Mann-Kendall tests suggest that there has been no change in pan evaporation and atmospheric vapor pressure deficit. This implies that soil water availability is the driver of changes in ET, and the increased P may have possibly increased ET. Other studies in the literature give further evidence of increased ET due to increased P. By ruling out a reduction in ET, we suggest that the observed increase in groundwater storage and streamflow in the Midwest is linked to the increased July precipitation attributed to High Plains irrigation. We note that the increases in late summer streamflow are rather small when placed in the context of seasonal dynamics, but they are conceptually important in that they point to a different cause of change.

Kustu, M. Deniz↗

Characterizing the Effects of Irrigation in the Middle East and North Africa Using Remotely Sensed Vegetation and Water Cycle Observations

A majority of the countries in the Middle East and North Africa (MENA) region suffer from water scarcity due in part to widespread rainfall deficits, unprecedented levels of water demand, and the inefficient use of renewable freshwater resources. Since a majority of the water withdrawal in the MENA is used for irrigation, there is a desperate need for improved understanding of irrigation practices and agricultural water use in the region. Here, satellite-derived irrigation maps and crop-type agricultural data are applied to the Land Data Assimilation System for the MENA region (MENA LDAS), designed to provide regional, gridded fields of hydrological states and fluxes relevant for water resources assessments. Within MENA-LDAS, the Catchment Land Surface Model (CLSM) simulates the location, timing, and amount of water applied through agricultural irrigation practices over the region from 2002-2012. In addition to simulating the irrigation impact on evapotranspiration, soil moisture, and runoff, we also investigate regional changes in terrestrial water storage (TWS) observed from the Gravity Recovery and Climate Experiment (GRACE) and simulated by CLSM.

Bolten, John↗

Global Response Patterns of Major Rainfed Crops to Adaptation by Maintaining Current Growing Periods and Irrigation

Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology, growth, and evapotranspiration. However, future projections typically do not consider the effects of agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models to quantify the impacts and adaptation potential of field crops under increasing temperature up to 6 K, accounting for model uncertainty. We find that without adaptation, the dominant effect of temperature increase is to shorten the growing period and to reduce grain yields and production. We then test the potential of two agronomic measures to combat warming-induced yield reduction: (i) use of cultivars with adjusted phenology to regain the reference growing period duration and (ii) conversion of rainfed systems to irrigated ones in order to alleviate the negative temperature effects that are mediated by crop evapotranspiration. We find that cultivar adaptation can fully compensate global production losses up to 2 K of temperature increase, with larger potentials in continental and temperate regions. Irrigation could also compensate production losses, but its potential is highest in arid regions, where irrigation expansion would be constrained by water scarcity. Moreover, we discuss that irrigation is not a true adaptation measure but rather an intensification strategy, as it equally increases production under any temperature level. In the tropics, even when introducing both adapted cultivars and irrigation, crop production declines already at moderate warming, making adaptation particularly challenging in these areas.

Minoli, Sara↗

Evapotranspiration Based Irrigation Trials Examine Water Requirement, Nitrogen Use, and Yield of Romaine Lettuce in the Salinas Valley

Cool season vegetables require adequate soil moisture to assure that maximum yield and quality are achieved. On California’s central coast, where the majority of cool season vegetables are produced in the US, long-term overpumping of irrigation water has reduced groundwater levels and led to environmental degradation. Two evapotranspiration (ET) based irrigation field trials were performed near Salinas CA (USA) to determine if ET-based irrigation scheduling could conserve water while producing romaine lettuce (cv. Sun Valley) of commercially viable yield. Sprinklers were used for seed germination and crop establishment. Four drip irrigation treatments were then imposed using a randomized complete block design with six replications. The CropManage decision support model was used to estimate the full (100%) crop water requirement based mainly on ET replacement. Other treatments included 50% 75% and 150% of the full water requirement. The 100% treatment received 185 mm of water in 2015 and 247 mm in 2016, both of which were well below prior guidance and grower reports. Yields from the 100% and 150% treatments were not significantly different and were similar to industry average, while yields were significantly lower for the 50% and 75% treatments. The 100% treatment had the highest water use efficiency, and the 100% and 150% treatments together had the highest nitrogen recovery efficiency. Irrigation of romaine near the 100% ET replacement level can potentially reduce environmental impacts associated with nitrate leaching and surface runoff.

CropManage decision support system↗

Impacts of Irrigation on Daily Extremes in the Coupled Climate System

Widespread irrigation alters regional climate through changes to the energy and water budgets of the land surface. Within general circulation models, simulation studies have revealed significant changes in temperature, precipitation, and other climate variables. Here we investigate the feedbacks of irrigation with a focus on daily extremes at the global scale. We simulate global climate for the year 2000 with and without irrigation to understand irrigation-induced changes. Our simulations reveal shifts in key climate-extreme metrics. These findings indicate that land cover and land use change may be an important contributor to climate extremes both locally and in remote regions including the low-latitudes.

Climate↗

Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

land data↗

Integrating Water Supply Constraints into Irrigated Agricultural Simulations of California

Simulations of irrigated croplands generally lack key interactions between water demand from plants and water supply from irrigation systems. We coupled the Water Evaluation and Planning system (WEAP) and Decision Support System for Agrotechnology Transfer (DSSAT) to link regional water supplies and management with field-level water demand and crop growth. WEAP-DSSAT was deployed and evaluated over Yolo County in California for corn, rice, and wheat. WEAP-DSSAT is able to reproduce the results of DSSAT under well-watered conditions and reasonably simulate observed mean yields, but has difficulty capturing yield interannual variability. Constraining irrigation supply to surface water alone reduces yields for all three crops during the 1987-1992 drought. Corn yields are reduced proportionally with water allocation, rice yield reductions are more binary based on sufficient water for flooding, and wheat yields are least sensitive to irrigation constraints as winter wheat is grown during the wet season.

Agriculture; Irrigation; Water Resources Managemen↗

Estimation of irrigated land using Landsat digital data

Techniques developed by the University of California and NASA for the utilization of multitemporal Landsat digital data in estimating and mapping irrigated land are presented. Three dates of Landsat were registered to each other and to a USGS 7.5 minute quadrangle map base for approximately 1.9 million acres of land. Other data registered include county boundaries, land use stratification, and digitized ground data. To identify irrigated land, an indicator was used which consisted of the ratio of MSS Band 7 to MSS Band 5 (the 7/5 ratio). A threshold 7/5 irrigated land value was determined for each date, as actively growing land generally has a higher 7/5 ratio than other cover classes. An estimate of irrigated land was determined by Landsat classification with ground data, at a relative standard error of + or - 7.98% at the 95% confidence interval. Mapping evaluation reveals a 94% accuracy, a 7.4% omission rate, and a 6.3% commission rate. In addition, a sample unit size evaluation recommends a 1-1 1/2 square mile sample range.

Brown, C. E.↗

Results of an irrigated lands assessment for water management in California

Periodic assessment of existing and future demands for water within California is one responsibility of the California Department of Water Resources (CDWR). The California Irrigated Lands Assessment for Water Management Project represented a 5-year joint research effort between the NASA and the CDWR with technical support from the University of California (UC) at Berkeley and at Santa Barbara. The objectives were: (1) to develop and demonstrate procedures for providing highly precise, timely, estimates of irrigated area on a statewide basis using Landsat sensor data, and (2) to develop, through research with small demonstration sites, a procedure for the inventory and mapping of crop groups on a regional basis. Both manual and computer-assisted analyses were investigated. This paper highlights the statewide irrigated lands inventory where a procedure for statewide estimation of irrigated land using full frame Landsat MSS imagery and sampled ground data was successfully demonstrated. The statewide estimate of 3 990 112 hectares was within + or - 1.32 percent relative standard error at the 95-percent Confidence Interval, well within the design goal. This procedure represents a new capability for obtaining near-real time data on changes in agricultural water use throughout the state.

Bauer, E. H.↗

Understanding Land-Atmosphere Interactions in Agricultural Areas through Improved Modeling and Monitoring of Irrigation

Irrigation increases soil moisture and evapotranspiration, often leading to cooler and more humid conditions over and downwind of irrigated areas. These changes can affect the evolution of the planetary boundary layer and ultimately influence the development of clouds and precipitation. It is for this reason that there has been a push to include irrigation processes in weather and climate models. This presentation will discuss recent efforts to model irrigation impacts in NASA’s land surface and coupled models, via both improved parameterizations and the incorporation of satellite data from platforms such as SMAP, MODIS, and ECOSTRESS. This work underscores the need to consider human water management impacts when analyzing or predicting components of the water and energy cycles, and the critical roles that NASA observations and models play in this assessment.

Patricia Lawston Parker↗

CropManage Application for Vineyard Irrigation Decision-Support

CropManage is a free web-application developed by U.C. Cooperative Extension to support evapotranspiration based irrigation scheduling and nutrient management for major specialty crops. Prescribed phenology curves are used to develop daily estimates of canopy cover within a given field, based on days since planting (annual crops) or budbreak (trees, vines). These curves are modulated by a MaxCan parameter representing seasonal maximum canopy cover. Crop development observations can be used to adjust for such factors as weather anomalies or non-standard agronomic practice, as needed. Canopy cover is converted to crop coefficient and combined with reference evapotranspiration to derive daily water consumption. Guidance on crop water requirement is then conveyed to users in terms of system runtime issued on-demand for a given date, largely based on total evapotranspiration since last irrigation event. In this study, CropManage was adapted to vineyards by adding modules accounting for early-season soil moisture depletion and cover crop presence. A crop stress parameter was added to accommodate deficit irrigation practice, allowing the user to specify percentage departure from full water requirement along with start/stop dates. An initial verification exercise was performed on three winegrape vineyards located in California’s Central Coast (2020), North Coast (2020) and Central Valley (2019). Daily crop evapotranspiration was monitored by eddy-covariance fluxtowers. MaxCan was measured by ground and satellite observation. Stress regime was specified by grower practice where available, otherwise stress levels were inferred from applied water records. Mean absolute error and mean bias error of modeled cumulative evapotranspiration were computed with respect to the eddy covariance measurements collected throughout the growing season. Results indicate the modified CropManage water management module performs reasonably well for winegrape. Additional effort is planned to modify the nutrient module for vineyard use.

CropManage↗

Improved alternate wetting and drying irrigation increases global water productivity

Rice is the staple food for half of the world’s population but also has the largest water footprint among cereal crops. Alternate wetting and drying (AWD) is a promising irrigation strategy to improve paddy rice’s water productivity—defined as the ratio of rice yield to irrigation water use. However, its global adoption has been limited due to concerns about potential yield losses and uncertainties regarding water productivity improvements. Here, using 1,187 paired field observations of rice yield under AWD and continuous flooding to quantify AWD effects (ΔY), we found that variation in ΔY is predominantly explained by the lowest soil water potential during the drying period. We estimate that implementing a soil water potential-based AWD scheme could increase water productivity across 37% of the global irrigated rice area, particularly in India, Bangladesh and central China. These findings highlight the potential of AWD to promote more sustainable rice production systems and provide a pathway toward the sustainable intensification of rice cultivation worldwide.

Irrigation↗

Investigation of remote sensing to detect near-surface groundwater on irrigated lands

The application of remote sensing techniques was studied for detecting areas with high water tables in irrigated agricultural lands. Aerial data were collected by the LANDSAT-1 satellite and aircraft over the Kansas/Bostwick Irrigation District in Republic and Jewell Counties, Kansas. LANDSAT-1 data for May 12 and August 10, 1973, and aircraft flights (midday and predawn) on August 10 and 11, 1973, and June 25 and 26, 1974, were obtained. Surface and water table contour maps and active observation well hydrographs were obtained from the Bureau of Reclamation for use in the analysis. Results of the study reveal that LANDSAT-1 data (May MSS band 6 and August MSS band 7) correlate significantly (0.01 level) with water table depth for 144 active observation wells located throughout the Kansas/Bostwick Irrigation District. However, a map of water table depths of less than 1.83 meters prepared from the LANDSAT-1 data did not compare favorably with a map of seeped lands of less than 1.22 m (4 feet) to the water table. Field evaluation of the map is necessary for a complete analysis. Analysis of three fields on a within or single-field basis for the 1973 LANDSAT-1 data also showed significant correlation results.

Ryland, D. W.↗