Item talk:Q226822

{

 "@context": "http://schema.org/",
 "@type": "WebPage",
 "additionalType": "Project",
 "url": "https://www.usgs.gov/centers/western-geographic-science-center/science/global-crop-water-productivity-and-savings",
 "headline": "Global Crop Water Productivity and Savings through waterSMART (GCWP)",
 "datePublished": "May 6, 2024",
 "author": [
   {
     "@type": "Person",
     "name": "Adam J. Oliphant",
     "url": "https://www.usgs.gov/staff-profiles/adam-j-oliphant",
     "identifier": {
       "@type": "PropertyValue",
       "propertyID": "orcid",
       "value": "0000-0001-8622-7932"
     }
   },
   {
     "@type": "Person",
     "name": "Daniel J Foley",
     "url": "https://www.usgs.gov/staff-profiles/daniel-j-foley",
     "identifier": {
       "@type": "PropertyValue",
       "propertyID": "orcid",
       "value": "0000-0002-2051-6325"
     }
   },
   {
     "@type": "Person",
     "name": "Itiya P Aneece",
     "url": "https://www.usgs.gov/staff-profiles/itiya-p-aneece",
     "identifier": {
       "@type": "PropertyValue",
       "propertyID": "orcid",
       "value": "0000-0002-1201-5459"
     }
   }
 ],
 "description": [
   {
     "@type": "TextObject",
     "text": "(a) areas of croplands (more crop per unit area); and"
   },
   {
     "@type": "TextObject",
     "text": "1. Increasing crop water productivity,"
   },
   {
     "@type": "TextObject",
     "text": "We will perform a comprehensive assessment of the state-of-art of crop water productivity (CWP; \u201ccrop per drop\u201d) research worldwide using remote sensing and non-remote sensing methods and approaches based on existing research and meta-analysis. A peer-reviewed journal article will be published based on this work. Then, the study will develop and publish three unique models for CONUS:"
   },
   {
     "@type": "TextObject",
     "text": "Given the above context, there are several novel objectives that will be achieved by this waterSMART project for 2001-2025 time-period using multisensory remote sensing high resolution imagery (30 m or better), machine learning, and cloud computing. These objectives are:"
   },
   {
     "@type": "TextObject",
     "text": "These models and products by this research team are intended to compliment the CONUS products from USDA and other USGS groups. These studies will be conducted considering the factors such as the global irrigated and rainfed croplands (Figure 2), and Koppen-Geiger climate classification (Figure 3) and taking major world crops such as wheat, rice, barley, corn, soybeans, cotton, potatoes, sugarcane, pulses, alfalfa, etc. into consideration."
   },
   {
     "@type": "TextObject",
     "text": "Such approaches can potentially save massive quantities of water that could be used to replenish existing surface and ground water reservoirs and/or help create new \u201cwater banks\u201d. We will study these separately for rainfed and irrigated croplands. Growing fewer water consuming crops and/or increasing water productivity in rainfed croplands will help recharge groundwater and/or fill existing or new small ponds or reservoirs throughout the cropland areas. These are \u201cnew green water banks\u201d (water saved from rainfed croplands). It may also help retain water in the reservoirs which can then be used for alternative uses. These are termed \u201cnew blue water banks\u201d (water saved from irrigated croplands)."
   },
   {
     "@type": "TextObject",
     "text": "1. Percentage of cropland areas under medium or low crop water productivity."
   },
   {
     "@type": "TextObject",
     "text": "waterSMART intends to place technical information and tools in the hands of stakeholders, allowing them to answer two primary questions about water availability:"
   },
   {
     "@type": "TextObject",
     "text": "Subsequently, the water that could be saved will be modeled for different scenarios, including:"
   },
   {
     "@type": "TextObject",
     "text": "The waterSMART (Sustain and Manage America\u2019s Resources for Tomorrow) project places technical information and tools in the hands of stakeholders that allow them to answer pertinent questions regarding water availability. Two goals  of waterSMART are to 1) establish water availability and its use  based on an understanding of the past and present water users and to 2) project water availability and use scenarios into the future taking into consideration climate variability and change. Given that worldwide about 90% of all human water use goes toward producing food through agriculture, the focus of this component of the waterSMART project will be to establish crop water productivity (\u201ccrop per drop\u201d) of the world\u2019s leading agricultural crops (e.g., wheat, rice, barley, corn, soybeans, cotton, potatoes, pulses, alfalfa) and to determine how much water can be saved by improving crop water productivity. Initially, our primary focus study area is the United States of America (USA). Subsequently, we plan to expand this globally once the methods and approaches mature. The approach and methods involve multi-sensor remote sensing data utilization using machi"
   },
   {
     "@type": "TextObject",
     "text": "This increased food production per unit of water or increasing water productivity (or \u201cmore crop per drop\u201d; kg/m3) is expected to lead to a \u201cblue revolution\u201d in agriculture making a major contribution to global food security in the twenty-first century. In this project we will study the current and the past water consuming patterns of the crops by modeling and mapping crop water productivity in California\u2019s Central Valley and other places in the United States. This will allow us to quantify historical and current water use by crops in study areas. Water savings in the study areas can then be determined by understanding and establishing:"
   },
   {
     "@type": "TextObject",
     "text": "2. Quantum of water used by each crop for each level of water productivity."
   },
   {
     "@type": "TextObject",
     "text": "This project is targeted to demonstrate: (a) scientific advances in understanding, modeling, and mapping cropland fallows and crop water productivity (\u201ccrop per drop\u201d) through advanced remote sensing data; (b) methodological advances in crop-by-crop water use/ET modeling and automated machine learning algorithms for cropland fallows, crop water use, and crop water productivity in cloud computing; (c) societal benefits made by clear demonstration of opportunities for water savings by modeling, mapping, and pin-pointing areas of low and high water productivity and thus contributing to food security. It should help in \u201cunderstanding variability of agricultural water use and characterizing short and long-term imbalances between agricultural water supplies and agricultural water requirements.\u201d"
   },
   {
     "@type": "TextObject",
     "text": "3. Growing second season crops with low water consuming, short season crops that still provide rich nutrition and economic value (e.g., lentil, chickpea, fava bean, in place of certain proportion of rice fields)."
   },
   {
     "@type": "TextObject",
     "text": "It is important to note the connectivity between the waterSMART and the National Water Census. WaterSMART is a Department of the Interior (DOI) initiative on water conservation. It includes activities in: Bureau of Reclamation, United States Geological Survey, and the Office of the Assistant Secretary for Water and Science. The National Water Census is an integral part of the U.S. Geological Survey\u2019s Science Strategy to conduct an ongoing assessment of the nation\u2019s water resources. The project envisions expanding to other countries of the world, especially to areas of the world where agriculture is a major activity and tied to water and food security of the country, region, and the world. This expansion will depend on opportunities and resource availability."
   },
   {
     "@type": "TextObject",
     "text": "Nominal 30 m products for 2001-2025 will then be generated for CONUS using ACFA, ACA, and CWPM\u2019s. Next, the study will \u201cpin-point\u201d cropland areas with low and high CWP. These maps and models will provide precise locations from where we can save water and by how much. Spatial representations will pinpoint \u201chotspots\u201d across the regions where water availability will be severely limited in the future. Scenarios will then be developed that determine how much water (and where) can be saved via improved CWP, and/or the planting of water saving, short duration crops. The scenario outcomes would identify where \"new water\" would be generated and/or the opportunities for replenishment of existing water resources- both surface and ground water. These scenario analyses will be conducted separately for rainfed and irrigated crops to establish \u201cgreen water\u201d savings (from rainfed croplands), and \u201cblue water\u201d savings (from rainfed croplands). We will nominate several new or existing reservoirs for this new water as well as establish where and how much of this will be below ground. The research will analyze potential reductions in applied water, which allow farmers and water agencies to remove less water from streams, improving stream quality and ecosystem health, while reducing pumping, delivery, and treatment costs. We will show, through improved CWP in irrigated croplands, various quanta of \u201cnew water\u201d that becomes available for alternative uses like urban, industrial, riparian restoration, and re-forestation. Once CWP maps are produced at different resolutions for the representative areas and extrapolated to larger areas using the best models, we will build spatial models for each of the 3 WP study river basins in GEE cloud that will simulate \u201cnew water\u201d saved through various scenarios such as improved WP and re-allocation of crops (e.g., growing wheat instead of rice). Users will be able to view and query, compare scenario maps, and generate customized maps from the website. All data and products will be made available through USGS global croplands data portal (e.g., www.croplands.org; LP DAAC). Finally, scenario analysis will allow us to compare existing water use based on existing normal water productivity of various existing crops. This will allow us to suggest alternative pathways."
   },
   {
     "@type": "TextObject",
     "text": "Since nearly 80-90% of all human water use globally is consumed by agricultural croplands to produce food, it is of great importance to understand, model, map, and monitor agricultural croplands and their water use. In California, 80% of all water used by humans is for irrigated croplands; about 250 different crops are grown on about 10 million acres, using 41,922 million cubic meters of water of the 53,019 million cubic meters diverted from surface waters or pumped from groundwater (California Department of Water Resources). There are three significant advances envisaged in this project:"
   },
   {
     "@type": "TextObject",
     "text": "2. Growing less water consuming crops (e.g., wheat in place of rice) in some areas."
   },
   {
     "@type": "TextObject",
     "text": "(b) quantities of water (more crop per unit of water)."
   }
 ],
 "funder": {
   "@type": "Organization",
   "name": "Western Geographic Science Center",
   "url": "https://www.usgs.gov/centers/western-geographic-science-center"
 },
 "about": [
   {
     "@type": "Thing",
     "name": "Science Technology"
   },
   {
     "@type": "Thing",
     "name": "Climate"
   },
   {
     "@type": "Thing",
     "name": "Environmental Health"
   },
   {
     "@type": "Thing",
     "name": "Geology"
   },
   {
     "@type": "Thing",
     "name": "Energy"
   },
   {
     "@type": "Thing",
     "name": "Water"
   },
   {
     "@type": "Thing",
     "name": "Information Systems"
   },
   {
     "@type": "Thing",
     "name": "Methods and Analysis"
   }
 ]

}