Figure 1: Four different land-use types in the South Platte River Basin. Images captured with Google Earth. (A) Pivot irrigation agriculture, (B) Medium-intensity residential development, (C) Peri-urban low intensity development, (D) High-intensity development. Growing populations in urban areas (D) are drying irrigated land (A). What are the implications of different land-use decisions with regard to water management and climate change?

Land-use, climate change, and policy – Opportunities to act locally while thinking globally

Guest Post By Benjamin Choat, Ph.D. Candidate in the Department of Civil and Environmental Engineering and Trainee in the CSU InTERFEWS Program.

Author Background

I am a PhD Candidate in Civil and Environmental Engineering at Colorado State University and am fortunate to have a Fellowship with the National Science Foundation funded program, InTERFEWS. Most of my time is spent thinking about water resources and land use from a hydrologic perspective, but you will find that this article is only tangentially related to my normal area of focus. As part of an apprenticeship I participated in with the Colorado Water Conservation Board, I was asked to explore tools that enable estimates of the return on investment to the public from ecosystem services provided by different land-uses, with an emphasis on private working lands such as farms and ranches. The following article was motivated by that effort.

Land-Use and Climate Change

Growing urban populations are accelerating land-use change (LUC) around the globe, as witnessed in the Front Range of Colorado 1–3. In recent history, we have witnessed LUC exacerbating climate change due to disturbed soils, development of greenhouse gas (GHG) producing land uses, and more4. This trend is a product of our approach to land management, however, and is not a required feature of human progress. Local decisions determine how LUC manifests with significant implications for local livability and the global challenge of climate change. The question quickly becomes one of economics and policy: How do we incentivize local decisions that benefit the decision maker (e.g., farmer, municipality, or land developer), the local community, and the global population at large?

LUC occurs due to both direct and indirect causes. For example, land may be directly developed for a new use or altered due to an indirect cause such as the transfer of water from irrigated agriculture to urban uses. In many regions of the world, urban and rural communities are in competition for water resources. This competition is intensifying due to growing urban economies and populations and declining water supply which is, at least in part, due to climate change. In most cases, the water use with the greatest economic value will win that competition and secure its water supply. An increasingly common trend in water-scarce regions is the permanent transfer of water from irrigated agriculture to municipal uses (i.e., urban and industrial uses), commonly known as buy-and-dry. Buy-and-dry has become commonplace in the South Platte River Basin of Colorado where a decline of between 131,900 and 174,400 acres (~15%-20%) of irrigated agriculture is expected by 2050. Land development will directly contribute about 6-7% of that decline, while transfer of water from agriculture to municipal uses (i.e., buy-and-dry) will drive the remainder2. Irrigated agriculture is a key economic driver of many of the more rural communities of the South Platte River Basin. So, as those irrigated acres are dried, there will be significant economic and societal impacts such as the loss or alteration of employment opportunities, the local tax base, and general experience of agrarian culture (Figure 1). Of growing importance is the question of how to help maintain rural economies that will see significant declines in irrigated agriculture.

Figure 1: Four different land-use types in the South Platte River Basin. Images captured with Google Earth. (A) Pivot irrigation agriculture, (B) Medium-intensity residential development, (C) Peri-urban low intensity development, (D) High-intensity development. Growing populations in urban areas (D) are drying irrigated land (A). What are the implications of different land-use decisions with regard to water management and climate change?

One Potential Path Forward

An ideal option would address both the desire to incentivize local land-use decisions that produce positive outcomes locally and globally and the need to maintain rural economies in the face of diminishing irrigated agriculture and a changing climate. One such option is for the public to pay private landowners for public goods or benefits that have not been historically recognized by the market. For example, if the land is used to provide some ecosystem service which benefits the public, such as water purification or carbon sequestration, then the landowner may be paid for that service. There are different methods and mechanisms for such a process to be implemented. Taking carbon for example, one approach known as cap and trade allows a certain number of emission allowances per year for a given party. If a given party needs to emit more than their allowances then they can purchase more from another party that is not using all their allowances. Another approach is simply to apply a tax for each unit of carbon emitted and/or a tax credit for each unit of carbon sequestered – commonly known as a carbon tax credit. The landowner can sell those credits to carbon producing entities (e.g., Microsoft5) as a means to offset their carbon production.

Such programs can act to benefit rural communities in multiple ways. For instance, depending on the agricultural management practice, carbon credits can be acquired while keeping agriculture in production, allowing landowners to stack the income being generated by the land while increasing resiliency to climate change6. By increasing the profitability of the land, landowners may be less likely to accept offers from municipalities for their water rights. Even if irrigated agriculture is taken out of production, carbon credits may still be attainable by ensuring the new land-use (e.g., native grasslands) is providing additional carbon sequestration and storage. The desire for agriculture carbon credit programs is quite apparent as we see the number of them rapidly increasing across the globe7–9. In early 2021, Governor Jared Polis’ office in Colorado released a roadmap for the State’s ambitions of reducing GHG production and increasing carbon sequestration and storage10. As part of that roadmap, the need to adequately quantify GHG sources and the potential of Colorado’s natural and working (e.g., farms and ranches) lands to sequester and store carbon was identified. Additionally, as the Colorado Water Conservation Board works on an updated water plan for Colorado, it has expressed interest in synergizing those efforts laid out in Polis’ roadmap with efforts to manage Colorado’s water resources. This is a substantial step and difficult task. However, if the analysis is not performed at the appropriate spatial scale or resolution of detail, it may be of little help to decision makers.


There are many challenges to the effective implementation of tax-credit or tax-funded payment programs for carbon-related ecosystem services, with two of the most significant being reasonably accurate quantification and valuation of carbon storage, sequestration, and production8,11,12. A critical but difficult step in this process is for a government employee or independent valuator to determine the return on investment (ROI) to the public under various land use scenarios. A good estimate of ROI is necessary so that it is known where funds should be directed to maximize the ROI to the public and to know how much landowners should be paid for the provided services. It is common for relevant analyses to be performed at the regional (e.g., multiple states in the U.S.A.) or national scales, which while helpful and needed, does not present actionable insight to local decision makers or stakeholders. What is needed by policy- and decision-makers at the local and sub-state scale is the ability to perform scenario analysis with relative ease that compares different land-use scenarios and the associated carbon sequestration and public ROI potentials.

One such approach, as suggested by the Intergovernmental Panel on Climate Change (IPCC; Aalde et al. 2006) is to associate different carbon storage potentials with different land-use types (Figure 2). In this way, different land-use scenarios can be compared by changing the land-use types and the associated carbon storage. Due to heightened demand and critical need, this approach has become very popular and has been widely implemented across spatial scales. Many of these studies have utilized the Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model14 or similar models15–20. Despite the scenario analysis methodology being available and robust, if the input data used is not of adequate quality, then the outputs will never be reliable. In the modeling community this is commonly referred to with a popular adage: garbage in – garbage out. Of the referenced studies, nearly all use generic land-use types such as those suggested by the IPCC which are forest land, cropland, grassland, wetlands, settlements, and other land13. While these generic land-use types may be adequate for informing relative performance between them, they are not adequate to produce reasonable estimates of carbon storage nor ROI without further disaggregating them into finer land-use types. For example, while all croplands are often considered a single land-use type under this methodology, it is well established that past land use and cropland management has significant implications for how much carbon may be sequestered by that land. Some management approaches lead to GHG production on croplands and others lead to sequestration21. Each of the six generic land-use types recommended by the IPCC may provide significantly different GHG storage potential when disaggregated into finer spatial resolution and land-use types21–24. Not only do many of these studies use generic land-use types, they also use estimates of carbon pools and sources derived from globally- or regionally-based estimates. Gately and Hutyra25 showed though, that locally-based estimates of carbon inventories differed from globally-based estimates by 50 to 250%. Therefore, using such broad land-use types when performing scenario analysis with respect to local land-use planning and making estimates of ROI, or relying on them when making relevant policy decisions, should be done with extreme caution. Even if finer resolution land-use types are used, it will always be difficult to generalize the potential of carbon storage and ROI between areas and scenarios, so locally-based estimates should always be made.

Figure 2: The South Platte River Basin of Colorado. Land Cover is from the 2016 National Land Cover Database26. Assigning different values of carbon sequestration and/or return on investment to different land cover types is one approach to comparing carbon sequestration and ROI of different land-use scenarios.


The need for analyses such as these is critically important, but hastily performing them and presenting them as science-based results leads to an entirely different set of challenges and risks. Unfortunately, the topic of climate change has been heavily politicized and used to draw yet another line in the sand between what are portrayed as ideologically divergent and mutually-exclusive political views. For those of us that are in regular contact with skeptics of human-induced climate change, it is clear that any misstep, miscommunication, or poorly made decision will be used to reinforce their view that the scientific community is incorrect in their prognosis of the problem. In order for us to adequately address climate change, we need to communicate with stakeholders clearly and honestly – and we are all stakeholders, even the skeptics. Also, if we use analyses such as these to inform policy decisions that include economic incentives and payouts, there are risks of poorly estimating ROI values of different land-use scenarios and different management practices. If we undervalue the ROI, then we will underpay the private land-owners or other relevant entities and not attain the desired responses. If we overvalue the ROI, then taxpayers or the purchasing party will carry the burden of paying for a service that is not being provided, while supplying strong talking points for those that discourage science-based decisions. The scientific community must stay vigilant in our practices as policy decisions are, or at least should be, increasingly science based. When choosing methodologies and data for our models we must place them under proper scrutiny, or we risk propagating uncertainties from previous work and undermining our own.

In Closing

The South Platte River Basin, and many other rapidly developing areas, offer excellent opportunities to integrate ecosystem services and carbon sequestration/mitigation measures into land planning. LUC represents a significant source of GHG’s4, but if properly incentivized, can also provide the opportunity to reorient land-use decisions such that the negative impacts of LUC are minimized while reversing the trend of increasing ecological degradation and GHG production. For this reorientation to occur however, without fanning the flame of false narratives or exacerbating the cultural divides observed in our state and country, we must be able to make good estimates of the ROI provided by local decisions, at fine enough spatial scales and resolution of details that are useful for land planners and policy makers22,25.

Works Cited

  1. Angel, S., Parent, J., Civco, D. L., Blei, A. & Potere, D. The dimensions of global urban expansion: Estimates and projections for all countries, 2000–2050. Progress in Planning 75, 53–107 (2011).
  2. Colorado Water Conservation Board. Colorado’s water plan. Denver Colorado (2015).
  3. United Nations, D. of E. & Social Affairs, P. D. World urbanization prospects: The 2018 revision, online edition. (Department of Economic and Social Affairs PD New York, NY, 2018).
  4. Houghton, R. A. et al. Carbon emissions from land use and land-cover change. Biogeosciences 9, 5125–5142 (2012).
  5. Plume, K. Farmers struggle to break into booming carbon-credit market. Reuters (2021).
  6. Kane, D. A., Bradford, M. A., Fuller, E., Oldfield, E. E. & Wood, S. A. Soil organic matter protects US maize yields and lowers crop insurance payouts under drought. Environ. Res. Lett. 16, 044018 (2021).
  7. Farley, J. & Costanza, R. Payments for ecosystem services: From local to global. Ecological Economics 69, 2060–2068 (2010).
  8. Van Hecken, G. & Bastiaensen, J. Payments for ecosystem services: justified or not? A political view. Environmental Science & Policy 13, 785–792 (2010).
  9. Adhikari, B. & Boag, G. Designing payments for ecosystem services schemes: some considerations. Current Opinion in Environmental Sustainability 5, 72–77 (2013).
  10. Governor Jared Polis’ Office. Colorado Greenhouse Gas Pollution Reduction Roadmap. (2021).
  11. Alexander, P., Paustian, K., Smith, P. & Moran, D. The economics of soil C sequestration and agricultural emissions abatement. SOIL 1, 331–339 (2015).
  12. Smith, P. et al. How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal. Glob Change Biol 26, 219–241 (2020).
  13. Aalde, H. et al. Generic methodologies applicable to multiple land-use categories. IPCC guidelines for national greenhouse gas inventories 4, 1–59 (2006).
  14. Sharp, R. et al. InVEST 3.8. 9. post13+ ug. ga74679f user’s guide. Natural Capital Project. (2020).
  15. Babbar, D. et al. Assessment and prediction of carbon sequestration using Markov chain and InVEST model in Sariska Tiger Reserve, India. Journal of Cleaner Production 278, 123333 (2021).
  16. Clerici, N., Cote-Navarro, F., Escobedo, F. J., Rubiano, K. & Villegas, J. C. Spatio-temporal and cumulative effects of land use-land cover and climate change on two ecosystem services in the Colombian Andes. Science of The Total Environment 685, 1181–1192 (2019).
  17. He, C., Zhang, D., Huang, Q. & Zhao, Y. Assessing the potential impacts of urban expansion on regional carbon storage by linking the LUSD-urban and InVEST models. Environmental Modelling & Software 75, 44–58 (2016).
  18. Jiang, W., Deng, Y., Tang, Z., Lei, X. & Chen, Z. Modelling the potential impacts of urban ecosystem changes on carbon storage under different scenarios by linking the CLUE-S and the InVEST models. Ecological Modelling 345, 30–40 (2017).
  19. Wang, C., Zhan, J., Chu, X., Liu, W. & Zhang, F. Variation in ecosystem services with rapid urbanization: A study of carbon sequestration in the Beijing–Tianjin–Hebei region, China. Physics and Chemistry of the Earth, Parts A/B/C 110, 195–202 (2019).
  20. Zhao, M. et al. Assessing the effects of ecological engineering on carbon storage by linking the CA-Markov and InVEST models. Ecological Indicators 98, 29–38 (2019).
  21. Denef, K., Archibeque, S. & Paustian, K. Greenhouse gas emissions from US agriculture and forestry: A review of emission sources, controlling factors, and mitigation potential. Interim report to USDA under Contract# GS-23F-8182H 53 (2011).
  22. Gurney, K. R. et al. Climate change: Track urban emissions on a human scale. Nature News 525, 179 (2015).
  23. Singh, K. K., Madden, M., Gray, J. & Meentemeyer, R. K. The managed clearing: An overlooked land-cover type in urbanizing regions? PLoS ONE 13, e0192822 (2018).
  24. Milnar, M. & Ramaswami, A. Impact of Urban Expansion and In Situ Greenery on Community-Wide Carbon Emissions: Method Development and Insights from 11 US Cities. Environ. Sci. Technol. 54, 16086–16096 (2020).
  25. Gately, C. K. & Hutyra, L. R. Large Uncertainties in Urban‐Scale Carbon Emissions. J. Geophys. Res. Atmos. 122, (2017).
  26. Dewitz, J. National Land Cover Database (NLCD) 2016 Products. US Geological Survey data release, https://doi. org/10.5066/P96HHBIE (2019).

Share this post

Share on facebook
Share on google
Share on twitter
Share on linkedin
Share on pinterest
Share on print
Share on email