Using the Crop Sequence Boundaries dataset from USDA, I isolate farm plots that have been idle at least one year in growing years 2016-2023. The CSB produces estimates of field boundaries, crop acreage, and crop rotations using satellite data in combination with other publicly available data. This data is non-confidential, and not tied to or based off of specific producer information. The CSB provides the crop reported by the Cropland Data Layer for each area defined over an 8 year period. The field boundaries defined in this analysis are based off of cropping decisions for growing years 2016-2023 . I use the crop sequence boundary layer instead of yearly CDLs because the CSB aggregates land to field level, which reduces noise and any error that is inherent in the data used to construct the CDLs . The CSB also allows me to follow the cropping decisions for a single plot of land over multiple growing seasons. This allows me to have certainty when identifying the last crop grown on a plot of fallow land. Maps showing the crops last grown on fallow land are shown in figure 7. I use data from the California Department of Water Resources to construct the bounds of the analysis . The San Joaquin Valley is composed of the San Joaquin River and Tulare Lake hydrologic regions. I combine these two areas into a layer to use as the boundary for the SJV in the rest of the analysis. Hagerty constructs mean water requirement per acre and mean revenues per acre for 19 different crop categories using data from California 2007-2018. These data are shown in Appendix 1. I assign CDL crop code values found in the CSB data to these categories. I take the constructed mean revenue and mean water needs to use in equation , nft hydroponic system the farmer’s optimization problem.
I leave A as a parameter and derive with respect to A. I solve equation for MCW to derive a ”choke price” of water per acre at which point a farmer would no longer want to plant their crop and instead will fallow their land. Crops are ordered from lowest value of MCW to highest. A low calculated value of MCW implies that the farmer cannot afford higher costs of water, and will likely make adaptations to reduce water costs. The land growing crops that have a low tolerance for rising water costs will be the first candidates for solar transition. The other ordering condition will be proximity to existing transmission lines. Transmission lines are hugely important in determining initial costs of bringing a solar farm online, and thus, planned solar projects in SJV are concentrated around existing infrastructure . Land parcels within 100 meters of high-voltage transmission lines will be preferred to those farther away.The calculated MCW values for crop categories are shown in the table below, listed from lowest value to highest value. These values represent the highest possible water cost per acre that a farmer growing a given crop would be willing to tolerate. These values are an upper bound estimates because the only costs considered in a farmer’s production function in this analysis are water costs. These values are calculated using Hagerty derived mean revenues and water needs per acre.6 In the map below, these values are represented with graduated colors representing the threshold water cost per acre values for the last crop grown in a non-fallow year on a land parcel. Farmers owning unirrigated grassland are unwilling to pay for water because they don’t use it on this kind of land. Should these lands be transitioned to solar energy generation,they would not provide any social benefit in the form of water savings, but would provide private benefit to the farmer by substantially increasing their revenues per acre. Other crops that have lower tolerances for water price shocks are safflower and alfalfa.
Safflower is not very water intensive, but does not provide much value per acre. Alfalfa, on the other hand, provides four times the revenue per acre of safflower , but has over twice the water needs per acre. Referring back to figures 2 and 3, safflower is preferred in drier years, and alfalfa grown on plots in wet years are commonly fallowed or swapped for vineyards, which have slightly lower water intensity. These kinds of farmers are the ideal targets for policy intervention to induce solar adoption. On the other end of the spectrum, truck crops like carrots and berries have extremely high tolerance for increasing water costs, as they are hugely valuable per acre, and aren’t hugely water intensive. These farmers will not likely be enticed into using their acreage for solar energy, and thus, the lands housing these crops should not be targeted by policy for land transition. Given the importance and expense of high-voltage transmission lines, I isolate plots of land that are within 100 meters of pre-existing high-voltage transmission infrastructure. These land parcels have been fallow in one or more growing season 2016-2023, and are symbolized based on the crop coverage in its last active season in figure 8. The number of single-cropped land parcels are displayed in parentheses. Such lands previously grew almonds and pistachios, grains, and tomatoes most commonly, followed by previously non-irrigated grassland. In total, there are over 30,000 acres of land identified in the SJV that have been fallow at least once out of the last eight growing seasons and are within 100m of existing high-transmission transmission lines. If the search criteria is expanded to include any farm plots within 400m of existing high-voltage transmission lines, an additional 60,000 acres qualify for solar transition. The maps of agricultural lands eligible for solar transition in the San Joaquin Valley are displayed in figure 9.
This analysis identifies over 90,000 acres of agricultural land that would benefit from solar transition. If all of the acreage identified were to produce solar energy instead of traditional crops, very little other agricultural land would need to be removed from irrigation to help the San Joaquin Valley achieve its groundwater conservation goals as set forth by SGMA. The land identified can provide 3-4x as much energy generating capacity as already exists in the San Joaquin Valley, given average generating capacity per acre in the area . The calculated threshold cost of water shows relative sensitivity to water pricing increases, as it is based on a ratio of water usage and crop value. The ordering of these values tells us which farmers are more likely to benefit privately from a solar land transition. As scarcity increases due to increased pressure from policymakers on cutting back agricultural water use, local governments may find it beneficial to target lowest-cost land transitions first, before taking more profitable agricultural land out of production. Using the calculated values of MCW , policymakers can better anticipate which farmers are more sensitive to water price shocks. These farmers growing crops that are especially sensitive may be targeted by policy interventions that incentivize investment in solar farming. Further, using existing transmission line infrastructure allows for lower input costs to bring solar farms online. Combining these two data can be a powerful way to guide land transition in the San Joaquin Valley. Future research can relax the assumption of equal water access across farmers, and allow for more nuanced production and cost functions for growers. These additions will better reflect the reality that farmers face with water, land, and other input costs. This ordering system provides a loose guide for which farmers may react to increased water prices induced by scarcity and regulation, and adding more flexibility will improve the ability to apply results to policy. This analysis aligns well with economic literature utilizing positive mathematical programming. These economic tools used in more comprehensive agricultural production models including Howitt , M´erel and Howitt , and Howitt et al. . Agriculture is a key human activity in terms of food production, hydroponic nft system economic importance and impact on the global carbon cycle. As the human population heads toward 9 billion or beyond by 2050, there is an acute need to balance agricultural output with its impact on the environment, especially in terms of greenhouse gas production. An evolving set of tools, approaches and metrics are being employed under the term “climate smart agriculture” to help—from small and industrial scale growers to local and national policy setters—develop techniques at all levels and find solutions that strike that production-environment balance and promote various ecosystem services. California epitomizes the agriculture-climate challenge, as well as its opportunities. As the United States’ largest agricultural producing state agriculture also accounted for approximately 8% of California’s greenhouse gas emissions statewide for the period 2000–2013. At the same time, California is at the forefront of innovative approaches to CSA . Given the state’s Mediterranean climate, part of an integrated CSA strategy will likely include perennial crops, such as winegrapes, that have a high market value and store C long term in woody biomass. Economically, wine production and retail represents an important contribution to California’s economy, generating $61.5 billion in annual economic impact. In terms of land use, 230,000 ha in California are managed for wine production, with 4.2 million tons of winegrapes harvested annually with an approximate $3.2 billion farm gate value.
This high level of production has come with some environmental costs, however, with degradation of native habitats, impacts to wildlife, and over abstraction of water resources. Although many economic and environmental impacts of wine production systems are actively being quantified, and while there is increasing scientific interest in the carbon footprint of vineyard management activities, efforts to quantify C capture and storage in annual and perennial biomass remain less well-examined. Studies from Mediterranean climates have focused mostly on C cycle processes in annual agroecosystems or natural systems. Related studies have investigated sources of GHGs, on-site energy balance, water use and potential impacts of climate change on productivity and the distribution of grape production. The perennial nature and extent of vineyard agroecosystems have brought increasing interest from growers and the public sector to reduce the GHG footprint associated with wine production. The ongoing development of carbon accounting protocols within the international wine industry reflects the increased attention that industry and consumers are putting on GHG emissions and offsets. In principle, an easy-to-use, wine industry specific, GHG protocol would measure the carbon footprints of winery and vineyard operations of all sizes. However, such footprint assessment protocols remain poorly parameterized, especially those requiring time-consuming empirical methods. Data collected from the field, such as vine biomass, cover crop biomass, and soil carbon storage capacity are difficult to obtain and remain sparse, and thus limit the further development of carbon accounting in the wine sector. Simple yet accurate methods are needed to allow vineyard managers to measure C stocks in situ and thereby better parameterize carbon accounting protocols. Not only would removing this data bottleneck encourage broader participation in such activities, it would also provide a reliable means to reward climate smart agriculture.Building on research that has used empirical data to compare soil and above ground C stocks in vineyards and adjacent oak woodlands in California, this study sought to estimate the C composition of a vine, including the relative contributions of its component parts . By identifying the allometric relationships among trunk diameter, plant height, and other vine dimensions, growers could utilize a reliable mechanism for translating vine architecture and biomass into C estimates. In both natural and agricultural ecosystems, several studies have been performed using allometric equations in order to estimate above ground biomass to assess potential for C sequestration. For example, functional relationships between the ground-measured Lorey’s height and above ground biomass were derived from allometric equations in forests throughout the tropics. Similarly, functional relationships have been found in tropical agriculture for above ground, below ground, and field margin biomass and C. In the vineyard setting, however, horticultural intervention and annual pruning constrain the size and shape of vines making existing allometric relationships less meaningful, though it is likely that simple physical measurements could readily estimate above ground biomass. To date, most studies on C sequestration in vineyards have been focused on soil C as sinks and some attempts to quantify biomass C stocks have been carried out in both agricultural and natural systems.