Conservation 2050 projects changes in land and water use patterns to prioritize ecological services to the year 2050.(For additional information on Conservation and Restoration opportunities refer to: <http://www.fsl.orst.edu/pnwerc/wrb/futures/cro/dwnld_cro.html>). Trends in the protection of aquatic life and native habitats result in resource conservation and restoration of river floodplain and upland habitat functions, with commensurate changes in urban, forest, and agricultural practices. The primary determinants are assumptions that conservation and restoration of native habitats and the species dependent on them will be increasingly important. Assumptions were made by citizen stakeholders with technical input from others regarding how, where, and when more conservation-oriented land and water use occur. One of the most significant assumptions is that choices will be made first regarding which areas are conservation and restoration priorities, with future land and water use minimizing adverse effects at these locations. Two tiers of conservation and restoration lands are depicted as being phased in to 2050. Tier 1 lands are managed with priority given to achieving a naturally functioning landscapes. Tier 2 lands are managed for sustainable production of goods and services compatible with habitat conservation values. The changes corresponding to these assumptions are projected in the amount, location, and pattern of urban, rural residential, agricultural, forest, and native vegetation land uses. Water uses are projected as water rights associated with changing land uses are exercised and, in this alternative, at times converted from out-of-stream (e.g., irrigation) to in-stream (e.g., providing fish habitat) uses. Operations of federal reservoirs assume natural flows are passed through the dams in March through April every year. Each broad type of land and water use is described below.
Willamette River Basin Population
Population projections for the PNWERC Alternative Futures Project for the Willamette River Basin (WRB) are based on Oregon Department of Administrative Services, Office of Economic Analysis population forecasts by county. These extend only to 2040, and PNWERC has extended the forecasts to 2050 using the regression line (rate of change.) The county forecasts have been adjusted to reflect the population within the area bounded by the Willamette River Basin based on 1990 population census blocks. The WRB's 1990 population is calculated to be 1,970,000 with 86% living within urban growth boundaries. The projected population for Plan Trend 2050, Conservation 2050 and Development 2050 is 3,900,000. In Plan Trend 2050, 93% of the population lives within urban growth boundaries; in Conservation 2050, 94% of the population lives within urban growth boundaries; and in Development 2050, 87% of the population lives within urban growth boundaries (Willamette River Basin Planning Atlas p.106).
A number of cities overlap the boundaries of two counties. County totals are combined for the purposes of calculating city and county projections where necessary.
Population forecasts for cities are based on Portland State University Center for Population Research data, supplemented by additional data from city and county governments ranging from 2020 to 2040. Where no outside sources exist, PNWERC extends the forecasts for the cities using individual city's rate of change, and matches county totals to within 1% of the DAS county total population. (details are available at: <http://www.fsl.orst.edu/pnwerc/wrb/metadata/conspop.xls>)
Assumptions regarding increased urban densities lead to 94% of the 2050 population of 3.9 million people residing inside Conservation 2050 urban growth boundaries, which have expanded 54,000 acres beyond their 1990 extent. Of the 498,000 total Conservation 2050 Urban Growth Boudary (UGB) acres, 79% are developed and more than 20% are vegetated. This UGB expansion, larger than Plan Trend's due to protection of riparian vegetation inside UGBs, is accomplished by having new homes at higher densities (9.3 homes per acre within UGBs basinwide for homes constructed 1990-2050 as compared to 4.2 homes per acre within UGBs basinwide existing in 1990), and by redeveloping 12-15% of 1990 urban residential areas at higher densities. UGBs occupy 6.8% of the basin in Conservation 2050, an average annual increase of 900 acres over 1990 conditions for the 60-year period.
Populations in unincorporated and rural residential areas were derived from county data, and calculated based on available buildable lands. (details are available at: <http://www.fsl.orst.edu/pnwerc/wrb/metadata/conspop.xls>)
Within the 253,000 acres of 1990 rural residential zones (RRZ), slightly more than 26,000 of these acres were covered by rural buildings in 1990. As UGBs expand under Conservation 2050 assumptions, some 1990 RRZs are incorporated into 2050 urban areas. This results in a decline in the number of rural structures from 1990 to 2050 in this scenario. Countering this decline, this scenario assumes new rural dwellings will be created between 1990 and 2050, and that some of these will occur outside 1990 RRZs. Approximately half of these new rural dwellings will be clustered into groups on parcels 20 acres or larger in size, in areas adjacent to 1990 RRZs and well suited as Tier 1 native habitat. The clustered patterns of these dwellings allow a larger portion of rural residential parcels to remain as native habitat, with the assumption that land developers and residential owners will respond to financial, tax, and regulatory changes encouraging this pattern of rural residential development.
A decision-making model was used to generate future representations of agricultural land cover. The model uses GIS-based spatial data sets as input to an object-oriented simulation model that computes dynamic field and basin scale attributes, and then performs a crop selection decision based on multi-attribute decision ranking. Decision constraints screened out unsuitable crops and then decision variables were used to rank the cropping system alternatives by applying the TOPSIS method (Hwang and Yoon, 1981), with the highest-ranking crop selected for the field.
This approach required the characterization of the initial agricultural system at the field-scale and the development of relative rankings of production level, profit margin, price variability, yield variability and management requirements for each of the cropping systems. The model has a yearly time-step, with special functions to integrate decadinal updates from other components such as land use change or changes in water allocation.
Conservation 2050 agricultural land use remains similar in crop mix to 1990 conditions while total agricultural land area decreases significantly. Regional increases occur in the nursery sector and in grasses that appear more frequently as filter strips near wetlands. Riparian vegetation increases along streams in agricultural areas, with priority to re-vegetating water-quality limited streams on public lands. In the privately dominated lowlands, public lands are insufficient to meet assumptions, and some lower-productivity private lands are shown as restored to natural vegetation. Of the 1.37 million acres of 1990 private agricultural land, 3.7% are restored to Tier 1 riparian areas by 2050, 1.2% are restored to bottomland forest, 1.5% to native prairie and 2.4% to wetlands. In total, 12.25% of 1990 private agricultural lands are restored to native vegetation in Conservation 2050 following assumptions that sufficient incentives will exist to sponsor such restoration. Water rights used to irrigate 1990 fields restored by 2050 to native vegetation are assumed converted to in-stream rights. The total area of land in agricultural production in Conservation 2050, defined by land use/land cover, is 1.16 million acres, a decrease of 248,000 acres from 1990 conditions. Less than a fourth of these converted 1990 agricultural acres are in urban or rural residential uses by 2050, with the balance restored to native vegetation.
Cropping Systems Selection:
The Willamette Valley supports a diverse selection of agricultural crops and management techniques. It is impossible to include all systems in our model, yet it is important to capture as much of the quality of this agricultural diversity as possible. To this end we modeled the following cropping systems for this study:
The rationale for this classification is to aggregate specific crops with similar characteristics into crop classes and, with these crop classes, into rotation systems if applicable. This allows us to capture major elements of the physical and management diversity of the agricultural system.
Creation of the Agricultural Fields Coverage: The agricultural landscape is made up of fields, considered here to be a parcel of land containing a single crop-type. The minimum area requirement for a field was 2 ha, which was used to differentiate commercially viable agricultural fields from hobby farms and gardens. Several data sources were used to define the boundaries of agricultural fields:
Manually digitized polygons
USGS Water-Resources Investigations Report 97-4268 associated data polygons
OWRD Irrigation Place of Use polygons
ODFW Land Use/Land Cover polygons
PNW-ERC Vegetation Classification, generalized to a one-acre minimum mapping unit (mmu.) and defined as discrete polygons. Taxlot parcels for selected counties
Finally, each field was assigned area-weighted averages of mean monthly precipitation (Daly et al. 1994), available water capacity per foot of depth, (Natural Resources Conservation Service Soil Survey Geographic Database) and crop production potential ranking for each crop (Berger 2002). The crop production potential rank was determined by using yield data from NRCS county soil surveys in a supervised classification scheme that assigned a crop production class (very good, good, moderate, moderately low, low, and unsuitable) to each soil-crop combination.
Irrigation Requirements: Irrigation scheduling was based on monthly intervals, as described in the Western Oregon Irrigation Guides (Smesrud et al. 1997). This document also supplied the values for evapotranspiration, management allowable depletion, and effective root depth for each of the irrigated crops. On-farm irrigation efficiency was set to 80% for Irrigated Nursery Crops and 70% for all other irrigated crops.
Initial Distribution of the Agricultural Classes: The following land-cover maps were used along with crop and field data to define the initial (circa 1990) distribution of crops within the Willamette River Basin:
Oetter et al. 2001
Klock et al. 1998
Anderson et al. 1997
The assignment of a crop class to a particular field was based on both the confidence of the crop classification for a particular map and the total crop acreage for each county in the basin.
Irrigation availability - For a given field, irrigation availability was computed for each crop prior to crop selection. If at any time during the growing season there is forecasted to be inadequate irrigation, the crop was designated as unsuitable.
Crop Suitability - For a given field, a cropping system was deemed unsuitable if the crop production rank was unsuitable.
Years-To-Conversion - For a given field, a crop would be classified as unsuitable if there was insuffienct time for it to develop a marketable yield prior to conversion to a Tier 1 restoration area.
Market Demand - For the basin, an upper bound on crop acreage for each crop was set as the maximum acreage that occurred over the area during the period 1988-1998. This value was then increased or decreased yearly by the percentage change extrapolated by market trends. If the maximum acreage for a particular cropping system had not been fulfilled the cropping system was classified as suitable, otherwise it was classified as unsuitable.
Decision Variables: The attributes used to compare suitable crops represent the economic and management attributes of the cropping systems: crop production potential, price variability, yield variability, profit margin, and management requirements. Decision weights were assigned so that profit margin was considered the most important attribute, followed by management requirements, crop productivity potential, price variability, and yield variability.
In addition to the above variables, an additional wildlife-suitability attribute (Adamus et al. 2001) was added to the Conservation 2050 decision model for Tier 2 agricultural fields. Since these fields were to be managed in a way compatible with wildlife conservation value, the quality of wildlife habitat provided by the crop was set to be of equal importance in the crop selection decision as the crop's profit margin.
Water availability within WABs was adjusted using WaterMaster allocations.
For fields undergoing conversion to Tier 1 land management, field fragmentation was assessed using the perimeter-to-area ratio and fractal dimension of a field shape. Any shape value over four standard deviations beyond the mean value for the Circa 1990 agricultural fields was taken as an indication of conversion for the entire field. These areas were assigned an increased probability for conversion to built uses or natural vegetation in subsequent iterations of other land allocation models.
Large fields (> 16 ha) were allowed to partition into different types of conservation status (Tier 1, Tier 2, none) effectively sub-dividing the fields into different management schemes. A woody or shrubby field border was placed around all Tier 2 fields, and while for each decade, 10% of the normal agricultural fields had field borders randomly placed along field boundaries.
Federal forest lands in this scenario limit harvesting to young stands on a 60-year rotation to achieve forest age structure more comparable to natural conditions. Most federally managed forest lands are in reserves. Conservation 2050 assumes National Wildlife refuge lands leased ca. 1990 for agriculture are converted to native habitat. State forest lands have approximately half the land base in reserves, with harvesting applied to young stands on a 120-year rotation. Private industrial forest lands in this scenario show 3% of holdings reaching late successional (old growth) stages by 2050 through legacy tree management, using a 65-100-year variable harvest rotation. By 2050 the percentage of coniferous industrial forest ownership older than 80 years more than doubles from 1990 levels. Private non-industrial lands are shown managed on a 150-year average rotation. Riparian zones are shown as on federal forest lands 300 feet each side all streams, state forest lands 200 feet each side all streams, and private lands 100 feet each side all streams with additional riparian vegetation in Tier 1 areas. Willamette River mainstem channel complexity increases, especially in the historically more complex southern reaches of the river. This results in more extensive floodplain forests on flood-prone lands and near major tributary junctions. With significant changes in the lower elevations, and forestlands occupying more than two-thirds of the basin, natural vegetation becomes more extensive in Conservation 2050. This alternative is organized around a set of strategic choices regarding what to conserve and restore, how much to conserve and restore, where and when to do it.
With significant changes in the lower elevations, and forestlands occupying more than two-thirds of the basin, natural vegetation becomes more extensive in Conservation 2050. This alternative is organized around a set of strategic choices regarding what to conserve and restore, how much to conserve and restore, where and when to do it. (LINK to ConsRest)
Agricultural and municipal water conservation practices result in a 10% increase over 1990 levels in in-stream water rights by 2050. This is obtained by: transfer of irrigation allotment at the time of agricultural field conversion to Tier 1, improved cultivars, enhanced irrigation efficiencies, and an 8% reduction in municipal per capita water consumption rates relative to Plan Trend 2050.
Adamus, P.R., J.P. Baker, D. White, M. Santelmann, and P. Haggerty. 2001. Terrestrial vertebrate species of the Willamette River Basin: species-habitat relationships matrix. Internal Report. U.S. Environmental Protection Agency, Corvallis, OR.
Anderson, C.W., T. M. Wood, and J. L. Morace. 1997. Distribution of dissolved pesticides and other water quality constituents in small streams, and their relation to land use, in the Willamette River Basin, Oregon. Water-Resources Investigations Report 97-4268.
Berger, P. 2002. The generation and analysis of agricultural landscapes for futures research. Ph.D. Dissertation, Oregon State University.
Daly, C., R.P. Neilson, and D.L. Phillips. 1994. A statistical-topographical model for mapping climatological precipitation over mountainous terrain. Journal of Applied Meteorology, 33:140-158.
Haralick, R.M. 1979. Statistical and structural approaches to texture. Proceedings of the IEEE 67:786-804.
Hulse, D., S. Gregory and J. Baker, editors, Willamette River Planning Atlas, Oregon State University Press, Corvallis, Oregon, 2002.
Hwang, C.L., and K.P. Yoon. 1981. Multiple attribute decision making à methods and applications: a state-of-the-art survey. New York: Springer-Verlag.
Klock, C., S. Smith, T. O'Neil, R. Goggans, and C. Barrett. 1998. Willamette Valley land use/land cover map. Oregon Department of Fish and Wildlife, Informational Report. Available at: <http://www.nwhi.org>.
Oetter, D. R., W. B. Cohen, M. Berterretche, T. K. Maiersperger, and R. E. Kennedy. 2001. Land cover mapping in an agricultural setting using multi-seasonal Thematic Mapper data. Remote Sensing of Environment 76:139-155.
Smesrud,J.K., M. Hess, and J. Selker. 1997. Western Oregon irrigation guides. EM 8713, Oregon State University Extension Service, Corvallis, OR.