Population and income are key drivers of land value for developed uses. As population and earning potential increase, demand for developed urban land also increases, transitioning land away from agricultural and forest uses while also driving up land value. Understanding future population and income growth is paramount to anticipating shifts in land use and the resulting impacts on water.
The land-use team developed modeling components within Willamette Envision to simulate how land moves among agricultural, forest, and urban uses in the Willamette Valley. Future population and income growth in the region were assumed to be determined by forces outside the model, and thus, like climate change, were external to any actions by individuals or policy makers in the basin. Our model also represented the value of land in agricultural and forest uses, which is determined by site-specific factors such as slope, elevation, and access to water for irrigation. Within the model, relative values of land in different uses determined changes in land use over time. Urban growth boundaries (UGBs), an integral part of the land-use planning system in Oregon, constrained where development can occur and were adjusted periodically as a city’s population grew.
In the Reference Case scenario, the area of developed land increases by 54% between 2010 and 2100, and the areas of land in agriculture and forest decrease by 8% and 1%, respectively. Much of the future development is projected to occur in the Portland Metropolitan Area.
The land-use team simulated how land moves among agricultural, forest, and urban uses. These transitions are a function of economic returns to alternative uses, which are determined themselves by site characteristics such as farm rents, distances to cities, and population and income of cities. Returns to land and land-use transitions also are influenced by urban growth boundaries (UGBs), the land use planning lines that restrict development. Here we provide a brief explanation of land-use change modeling in Willamette Envision. For a more detailed explanation refer to Jaeger et al. (2016) and Bigelow (2015).
During a model run, Willamette Envision simulates land-use changes annually at the scale of parcels (referred to as Integrated Decision Units or IDUs within Willamette Envision). Growth in population and income increase the returns to developed uses relative to forest and farm uses, while agricultural land values are influenced by the availability of water for irrigation. We derived functions that estimate the economic returns to each land use from historical data for the Willamette Valley (Bigelow, 2015). In response to changes in the relative returns to different uses, IDUs may shift among agricultural, forest, and urban uses as the model runs. Land-use changes in the model are governed by probabilistic equations estimated with historical data from the National Resources Inventory (NRI).
To account for zoning rules under Oregon’s land-use planning system, the model treats land inside and outside of UGBs differently. Land outside of UGBs can move between undeveloped uses (i.e., ag-to-forest and forest-to-ag transitions are allowed), but transitions to developed use are not allowed. For IDUs inside of UGBs, all of the transitions are allowed, but development is treated as irreversible (i.e., once a forest or agricultural IDU is developed, it cannot return to its original use). Given the irreversibility of development, it follows that, over time, the share of developed land within each UGB will increase. To mimic the land-use planning process, we allowed for UGBs to expand once the developed share became sufficiently large. Once a specified threshold is exceeded, a UGB expansion will be triggered. UGB expansions occurred in a way that approximated rules under the land-use planning system. For example, land zoned for Exclusive Farm Use and Forest Conservation will be brought inside of UGBs only when other opportunities are exhausted. In the case of the Portland Metropolitan Area, priority is given to areas designated as urban reserves.
Willamette Envision treats population and income growth as external drivers, forces that are determined outside of the model and can be varied for different modeling scenarios. The population and income projections adopted for the Reference Case and many other WW2100 modeling scenarios, were based on forecasts from the Oregon Office of Economic Analysis (2011; OEA) and Woods and Poole Economics, Inc. (2011). The OEA forecasts population for each county to 2050, while Woods and Poole forecast mean household total personal income to 2040 (in inflation-adjusted dollars). We used linear extrapolation to 2100, which implied diminishing growth rates over time for both variables (Fig.1). Projected county population was allocated to areas within UGBs and rural residential zones based on population percentages in the 2010 Census. Rural residential zones were allowed population growth until they reached a density of one household for every two acres of land. Once these areas were full, all new population was added within UGBs. All cities within a county were assumed to have the projected mean household income.
Over the period 2010 to 2100, population is projected to increase in every county in the Willamette Basin, although the increases in absolute terms are largest for Washington, Multnomah, and Clackamas counties (Fig. 1). The basin population is projected to increase by 3.05 million people, a gain of 111%.
Figure 1. Willamette Water 2100 population and income projections.
In the Reference Case scenario, the area of land in developed use increases from 334,921 acres to 516,053 acres between 2010 and 2100, an increase of 54% (Fig. 2). These increases are mirrored by declines in agricultural land (117,751 acres or -8%) and forest land (63,376 acres or -1%).
Much of the increase in developed land is projected to occur in the Portland Metropolitan Area (Fig. 3). This reflects the relatively large increases in population forecasted for the three Metro counties.
The inflation-adjusted value of land in developed uses increases through the basin, but reaches the highest levels in the Portland Metropolitan Area (Fig. 4). The average value of land in agriculture declines by 8% between 2010 and 2100, and the forest value remains relatively constant.
Population densities (the ratio of population to developed land area) are projected to increase in Salem, but remain relatively constant in the other cities in the basin. Population growth has competing effects on densities, raising the level of population but also the area of developed land. In addition, the area of developed land consumed per household increases over time.
Figure 2. Projected land-use change in the Willamette Basin for the Reference Case scenario.
Figure 3. Projected urbanization patterns for the Reference Case scenario.
Figure 4. Projected values of developed land for the Reference Case scenario.
Figure 5. Projected population densities for the Reference Case scenario.
Figure 6. Projected developed land area for the Reference Case and two alternative scenarios.
Population and income growth in the Reference Case scenario raise the demand for urban land in the Willamette Basin, which raises the value of developed land over agricultural and forest land. This increases the area of developed land by 54% between 2010 and 2100, while decreasing agricultural and forest land areas by -8% and -1%, respectively. The land-use planning system determines where this future urbanization can occur. We project that the largest increases in developed area will occur within the Portland Metropolitan Area.
Bigelow D.P., Plantinga A.J., Lewis D.J., Langpap C. (2017). How Does Urbanization Affect Water Withdrawals? Insights from an Econometric-Based Landscape Simulation. Land Economics. 93:413-436. http://dx.doi.org/10.3368/le.93.3.413
Bigelow, D.P. (2015). How do population growth, land-use regulations, and precipitation patterns affect water use? A fine-scale empirical analysis of landscape change. PhD Dissertation. Oregon State University. http://hdl.handle.net/1957/56105
Note: We conducted a statistical analysis of land values using data collected from assessor offices in Benton, Lane, Marion, and Washington counties. Details are provided in Bigelow (2015). The land-use transition model was adapted from the estimates in Lewis et al. (2012).
Andrew Plantinga, UC Santa Barbara - Bren School of Environmental Science & Management (lead)
Daniel Bigelow, PhD Student, OSU Applied Economics (graduated: 2015)
Bigelow, D.P. (2015). How do population growth, land-use regulations, and precipitation patterns affect water use? A fine-scale empirical analysis of landscape change. PhD Dissertation. Oregon State University.
Jaeger et. al. (2016). Scarcity amid abundance: Water, climate change, and the policy role of regional system models. Manuscript in preparation.
Lewis, D. J., Plantinga, A. J., Nelson, E., & Polasky, S. (2011). The efficiency of voluntary incentive policies for preventing biodiversity loss. Resource and Energy Economics, 33(1), 192-211.
Oregon Office of Economic Analysis. (2011). Forecasts of Oregon's County Populations and Components of Change, 2010 – 2050, Salem, Oregon.
Woods and Poole Economics, Inc. (2011). 2011 Idaho, Washington, and Oregon State Profile. Washington, DC. https://www.woodsandpoole.com
Webpage authors: D. Bigelow, A. Plantinga
Last updated: September 2016