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At least 109 records · Page 6

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↗

Reanalysis of Water Withdrawal for Irrigation, Electric Power, and Public Supply Sectors in the Conterminous United States, 1950–2016

Accurately measuring water use by the economy is essential for developing reliable models of water resource availability. Indeed, these models rely on retrospective analyses that provide insights into shifting human population demands and adaptions to water shortages. However, accurate, methodologically consistent, empirically authentic, and spatiotemporally comprehensive historical datasets for water withdrawals are scarce. Herein, we present a reanalysis of annual resolution (1950–2016) historical data set on irrigation, electric power, and public supply water withdrawal within the conterminous United States (US) at the county-level, and, for power plants, at the site-level. To estimate electric power water use, we synthesized a historically comprehensive list of generators and historic patterns in generation across fuels, prime movers, and cooling technologies. Irrigation water use estimation required building a crop-demand model that utilized historical information on irrigated acreage for crops and golf courses, stage-specific crop water demand, and climate information. To estimate public water supply use, we developed a random forest model constructed from information on population, infrastructure, climate, and land cover. These estimates generally agree with total county and state water use information provided by the US Geological Survey (USGS) water use circular and estimates generated from independent studies for specific years. However, we also observed discrepancies between our estimates and USGS data that appear to be caused by inconsistencies in the methods used by the USGS's primary data sources at the state level over decades of data collection, highlighting the importance of reanalysis to yield spatiotemporally consistent and intercomparable estimates of water use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

IrrigationViz: A Geospatial Visualization Application to Facilitate Irrigation Modernization

Irrigation water delivery infrastructure, such as canals and pipelines, are essential to agriculture in the Western U.S., yet many of these systems are reaching the end of their useful lives. Reinvestment can achieve a wide variety of benefits, from water conservation to energy savings or renewable energy generation. Modernization requires significant planning, design, and implementation funding which can be a challenge for many irrigation districts. Here, this paper introduces IrrigationViz, a web-based mapping application designed to help irrigation districts visualize and generate high-level cost and benefit estimates for infrastructure modernization projects. These estimates can help water managers identify projects that benefit from additional engineering resources and ultimately obtain funding. IrrigationViz includes map interactions, graphs, and visualization components to facilitate planning and communication to stakeholders and funders. IrrigationViz combines user-provided information about a water-delivery system with public datasets and basic engineering formulas to generate estimates of the benefits of reinvestment. Estimates include the amount of water seepage in earthen canals, potential hydropower generation associated with replacing a canal with a pressurized pipe, and pipe size recommendations. We found that hydropower generation estimates compared favorably with real world projects, but seepage loss estimates showed high variability relative to on-the-ground measurements

99 - GENERAL AND MISCELLANEOUS↗

Review of Irrigation Modernization and Conduit Hydropower Funding and Support Programs

This memo reviews and evaluates existing funding mechanisms that support off-farm irrigation modernization and conduit hydropower projects. Irrigation modernization projects, both on and off-farm, can be challenging to move through planning, permitting, development and installation processes and some evidence indicates that funding mechanisms can be a barrier to successful deployments. This memo is important because access to equitably and efficiently deployed project planning and development funding may be a key pre-requisite to increasing the pace and scale of irrigation modernization project deployments that incorporate hydropower. We evaluated an array of federal and state funding programs and took a close look at Energy Trust of Oregon’s funding mechanisms due to the organization’s apparent success in increasing the pace and scale of modernization in its state.

13 HYDRO ENERGY↗

Integrated Water-Power System Resilience Analysis in a Southeastern Idaho Irrigation District: Minidoka Case Study

This study investigates the joint water–power system resilience of an irrigation district in southeastern Idaho. Irrigation districts face difficulties in the delivery of water to farmers under drought conditions, during equipment failures, or unplanned infrastructure disruptions. The resilience of interconnected water and power systems can be better analyzed and understood through an integrated approach, using a model that connects the dependencies between the two halves of the system. Using a multi-agent system model capturing both water and power system components, as well as their linkages, we capture the interdependencies of these systems and highlight opportunities for improvement when faced with disruptions. Through simulation scenarios, we examine the system resilience using system performance, quantified as the percentage of met demand of the power and water system, when subjected to drought water year, an unforeseen water demand increase, power outage and dam failure. Scenario results indicate that the effects of low flow years are mostly felt in the power system; unexpected increases in water demand marginally impact irrigation system performance; dams and pumps present vulnerabilities of the system, causing substantial unmet demand during disruptions. Noting the interdependencies between the water–power system halves while leveraging an integrated simulation allows for an insightful analysis of the system impacts during disruptions.

13 HYDRO ENERGY↗

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↗

INTEGRATION OF CONDUIT HYDROPOWER AND BATTERIES INTO IRRIGATION INFRASTRUCTURE

Irrigation districts, ditch companies, and other agricultural water providers across the West operate and maintain canals, ditches, and reservoirs that store and deliver water for agricultural production, municipal needs, and other purposes. Co-locating energy generation and storage with this infrastructure provides opportunities to improve resilience and reduce energy costs. This memo discusses two case studies of co-located infrastructure and their contexts. The first case study discusses the development of an integrated microgrid, hydropower, solar, and battery storage project in North Unit Irrigation District (NUID) in Oregon. The second case study discusses the development of a battery storage project in Tulelake Irrigation District (TID) in northern California. Together, these two projects demonstrate the potential for co-located energy and water infrastructure.

13 - HYDRO ENERGY↗

Creating a Training Dataset for Semantic Segmentation of Canal Networks for Irrigation Modernization

Canal infrastructure has provided critical irrigation water to the western United States for over a century. To continue providing vital water resources to the semi-arid West, irrigation systems must undergo maintenance and modernization. Many canal companies are resource-constrained, and because funding opportunities often require detailed knowledge of existing infrastructure, they can struggle to secure financial capital. We address this problem by creating training data for a semantic segmentation deep learning model to map canal networks throughout the western United States. To create a diverse and robust training dataset, we labelled 1-m NAIP imagery with the locations of no canals, wet canals, and dry/vegetated canals. Since creating these datasets is time consuming, we first developed a preprocessing methodology to identify canals within our four study areas. We used NAIP imagery and provided canal centerline data to buffer, standardize, and cluster the imagery, automating the labeling process as much as possible. However, this still required manual cleaning and manual classification of canal type. Challenges arose when canals were interrupted (e.g., road culverts or piped sections) or when nearby features shared similar characteristics (e.g., irrigated fields, trees, and shadows). Combining automated preprocessing with manual refinement produced four detailed canal masks to be used in the semantic segmentation model developed by Richard Tapia.

13 - HYDRO ENERGY↗

Modeling potential air temperature reductions yielded by cool roofs and urban irrigation in the Kansas City Metropolitan Area

In this work, we evaluate two mitigation strategies for urban heat island (UHI) in the Kansas City Metropolitan Area (KCMA). Using the Weather Research and Forecasting (WRF) model, we assess the potential benefits of reflective “cool” roofs and urban irrigation on air temperature in typical summer conditions between 2011 and 2015, and during six of the strongest historical heat waves from 2005 to 2016. Under the typical summer conditions, we simulate 2-m air temperature for 10 summer weeks, finding average daytime (07:00–19:00 local time) temperature reductions of 0.08 and 0.28 °C for cool roofs and urban irrigation, respectively. During the six heat-wave episodes, we find daytime temperature reductions of 0.02 and 0.26 °C for the two scenarios, similar to those under typical summer conditions. Our results suggest that urban irrigation can be more efficient than cool roofs in mitigating UHI in metropolitan regions where the majority of the land cover is comprised of areas with low urban (i.e., non-vegetated) fractions. Finally, we find the alteration of surface conditions due to enhanced roof albedos influences precipitation within the WRF simulation, in particular during the heat waves. Further research would be necessary to determine the robustness of this last finding.

54 ENVIRONMENTAL SCIENCES↗

Unlocking aquifer sustainability through irrigator-driven groundwater conservation

Groundwater depletion caused by intensive pumping for irrigated agriculture is a global threat to economies, food security, and ecosystems. Pumping reductions are required to confront this threat, but their implementation is a “wicked” problem due to interlinked hydrological, social, and economic factors. In the US High Plains Aquifer, an irrigator-led conservation effort known as the Sheridan 6 Local Enhanced Management Area (SD-6 LEMA) is a rare example of successful collective action in agricultural-groundwater systems. In its first decade, the area has exceeded water use reduction goals and decreased depletion rates by over 50% without significantly affecting net income. In this Perspective, we highlight factors underlying the SD-6 LEMA’s effectiveness, and identify transferable governance tenets for other groundwater dependent regions striving for sustainable management of groundwater resources. These tenets include flexibility through multi-year allocations, regulatory oversight to support the irrigators’ plans, and a strong scientific foundation for sustainable agricultural-groundwater systems.

54 ENVIRONMENTAL SCIENCES↗

Irrigation Modernization Decision Support Engine

Irrigation systems are some of the oldest existing infrastructure in the United States. Increasing demands on water resources in combination with the age of these systems has resulted in a need to invest in the modernization of irrigation systems. Modernization activities are difficult to quantify, requiring expertise across multiple different domain areas. Traditionally, the scoping of a modernization project takes several years and requires significant financial investment before the potential of the project can be determined. The Irrigation Modernization Decision Support Engine allows a user to build out different scenarios. These scenarios allow for a course estimation of a project’s potential and the associated costs and benefits of pursuing the scenario. The design of the Decision Support Engine also allows for the easy sharing between different stakeholders, allowing for increased communication and understanding.

Elliott, ShilohN.↗

AmeriFlux FLUXNET-1F US-CS1 Central Sands Irrigated Agricultural Field

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CS1 Central Sands Irrigated Agricultural Field. This is the FLUXNET version of the carbon flux data for the site US-CS1 Central Sands Irrigated Agricultural Field produced by applying the standard ONEFlux (1F) software. Site Description - Heartland Farms Center-Pivot Irrigated Potato Field

Desai, Ankur↗

AmeriFlux FLUXNET-1F US-CS3 Central Sands Irrigated Agricultural Field

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CS3 Central Sands Irrigated Agricultural Field. This is the FLUXNET version of the carbon flux data for the site US-CS3 Central Sands Irrigated Agricultural Field produced by applying the standard ONEFlux (1F) software. Site Description - Heartland Farms Center-Pivot Irrigated Potato Field

Desai, Ankur↗

AmeriFlux FLUXNET-1F US-CS4 Central Sands Irrigated Agricultural Field

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CS4 Central Sands Irrigated Agricultural Field. This is the FLUXNET version of the carbon flux data for the site US-CS4 Central Sands Irrigated Agricultural Field produced by applying the standard ONEFlux (1F) software. Site Description - Heartland Farms Center-Pivot Irrigated Potato Field

Desai, Ankur↗

AmeriFlux FLUXNET-1F US-CS5 Central Sands Irrigated Agricultural Field

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CS5 Central Sands Irrigated Agricultural Field. This is the FLUXNET version of the carbon flux data for the site US-CS5 Central Sands Irrigated Agricultural Field produced by applying the standard ONEFlux (1F) software. Site Description - Heartland Farms Center-Pivot Irrigated Potato Field

Desai, Ankur↗