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Grupo cantosdelmundo-2020

Público·31 miembros

Dj Models Arah 111 116 Zip

Climate - Climate inputs from the regionally downscaled projections from the MIROC5 global climate model with the RCP 8.5 emissions scenario. Projections are in the middle of the range of possible changes predicted by a suite of global climate models that perform well for the Pacific Northwest. Annual mean temperature in the Willamette River Basin (WRB) increases 4C (7.5F) over the century. Climate input data was selected and downscaled through a multi-step process.

dj models arah 111 116 zip


Crop choice and irrigation - Crop types are set annually based on land characteristics, water rights and irrigation decision, crop prices, and climate. Crop types are limited to hay, grass seed, corn, pasture, wheat, clover, fallow, and other crops. Lands in orchards, vineyards and tree farms remain in those land cover types and do not change throughout the simulation and are largely not irrigated. On lands with water rights, the decision to irrigate is made annually based on land characteristics, climate (including June precipitation), and energy price. The price of wheat ($64 per ton), grass seed ($5 per bushel), and energy are held constant (in real terms). Irrigation diversions are limited by water right and constrained to legal limits including a max irrigation rate 1/80th cfs per acre and duty 2.5 acre-feet per acre. About two thirds of acres with water rights are irrigated in an average year; the result is that about 280,000 acres are irrigated at the simulation start. Crop and irrigation models are interdependent. Some crops are always irrigated and some crops are never irrigated.

Blue shading indicates the future climate scenarios. These scenarios include different assumptions about future climate, but left all other assumptions the same as in the Reference Case scenario. The purpose of the future climate scenarios was to compare the range of possible outcomes, given uncertainty about future climate conditions. Along with the mid-range assumptions of the Reference Case, the HighClim and LowClim scenarios represent the range of possible future climates projected by a suite of global climate models determined to perform well for the Pacific Northwest (Rupp et. al., 2013).

The graph above shows projected temperature changes from a historical baseline (mean of 1950-2005) for the Willamette Basin. The red and orange shaded areas indicate the range of projections derived from 40 global climate simulations. While the amount of warming varies between models and global carbon emissions scenarios, all project a warming climate. For modeling in Willamette Water 2100, we selected three climate scenarios to span the range of climate projections for the basin. We used output from these three scenarios to drive watershed modeling in Willamette Envision, and explore the effect of a changing climate on the water system. The heavy pink and blue lines indicate the amount of warming in these three climate scenarios: low change (pink; called the LowClim Scenario) and moderate change (bright blue; called the Reference Scenario) and high change (dark blue; called the HighClim Scenario). For more information about climate change projections for the Willamette Basin, link to the Future Climate page on this website.

Climate change is one of the external drivers in Willamette Envision. Daily weather data, such as temperature and precipitation, become input variables for biophysical and human systems modeling components as they simulate land and water system changes over the 21st century. Although every projection made by global climate models indicates a warmer climate, the range of plausible projections is wide, and how they will play out in the Willamette River Basin climate is unknown. To account for the large uncertainty in projected climate, the WW2100 project selected three representative scenarios (High Climate Change, Reference, and Low Climate Change) spanning the range of projections in temperature while including variability in precipitation changes. The WW2100 team then used the daily weather conditions predicted by these three scenarios as model forcings for WW2100 simulations. This page describes the process that we, as the WW2100 climate team, used to select and process data from global climate models so that it could be used as input variables for Willamette Envision. It also summarizes key characteristics of future climate conditions predicted by these models.

Figure 1. A depiction of the climate model assessment work done for WW2100. Models are listed at the bottom. On the left are meteorological measures, including temperature and precipitation. The graph depicts a relative error, in this case how well the models compare relative to each other when matched against actual historical measures for the Northwest. Here warm colors depict higher degrees of error and cooler colors less error. The models are organized from left (least error) to right (most error). (Image Source: Rupp et al., 2013)

To find their subset of scenarios, the team conducted a sensitivity analysis in the Willamette River Basin that allowed them to select three representative GCMs from the 33 CMIP5 climate models for which future climate scenarios were available (from the 41 GCMs evaluated in the first step).

From this, we then used these derived sensitivities to draw contours of constant summertime streamflow change on a scatter plot of temperature and precipitation changes in GCM output. With the contours as guides, the team selected GCMs and accompanying RCPs with the objective of spanning a wide range of warming (high, middle, and low) while also spanning a wide range of hydrological impact. Where multiple models were available to choose from in each category (high, middle, low), the team chose one of the better performing GCMs according to the model ranking discussed above.

Figure 7. Changes in mean monthly precipitation for the period 2050-2099 from the period 1950-1999. Output for the majority of climate models run done for WW2100 are showing a tendency toward wetter winters and drier summers. The October-to-October time frame shows the water year, which runs from 1 October to 30 September of any given year. Here, the zero line represents historical climate. Note: the tendency to rise above the zero line (get wetter) in winter and to drop below the zero line in summer (get drier).

The forest modeling team developed component models for Willamette Envision that simulate how upland forests will age and change through time, given forest type, climate conditions, and disturbance by wildfire and harvest. Here we provide a brief explanation of forest modeling in Willamette Envision. For full details on methods and results from WW2100 forest modeling studies, refer to Turner et al. (2015, 2016).

The initial condition of the landscape, which classifies different species of vegetation, and state and transition models (STMs) were based on work from the Integrated Landscape Assessment Project (ILAP) (Halofsky et al., 2014; INR, 2013). Boundaries for land ownership and protection status were from the US Geological Survey (GAP, 2014).

Dynamic global vegetation models (DGVMs) driven by the latest downscaled climate data could provide resource managers with guidance on what type of vegetation to replant after a disturbance. Our results support the conclusion that climate change will become an increasing influence on forest management decisions throughout the 21st century. The projected increase in the risk of fire points to investments in fire management.

Willamette River Basin residents and businesses alike depend on a sustainable source of clean water for continued well being and livelihood. To anticipate future urban water demands, the WW2100 economics team developed a modeling component for Willamette Envision that projects residential and nonresidential urban water demand as a function of factors such as water price, income, population, and population density. Demand for each urban area is modeled in aggregate, with models based on empirical economic research studies and data from major urban areas in the basin. As Willamette Envision runs, the estimated water demand is met by diversions of water from surface and groundwater sources, consistent with existing municipal water rights. WW2100 water demand modeling suggest an increase in urban water use within the basin over the century, mainly due to population growth. The projections indicate that per capita consumption, which has been declining for the past 20 years because of price increases and a range of urban water conservation programs, will stabilize at between 80 and 100 gallons per day, before rising gradually due to growth in per capita income.

Many Willamette Basin metropolitan areas have multiple water providers that divert water from multiple sources. Many water providers also buy and sell water between municipalities. Willamette Envision does not model these complex arrangements and instead models water demand for each metro area in aggregate. We used water-use reports from recent years to apportion urban water demand among water rights that have been used most by each metro area. As demand grows, the model allows for additional water to be made available by diverting water from the Willamette mainstem.

The crop choice model estimates the probability of growing each of seven crop types or groups for the modeled year. The empirical model is estimated at the parcel level based on observed cropping patterns in recent years. The model estimates the crop observed as a function of IDU characteristics including soil quality (land capability class), elevation, and the presence of an irrigation water right, as well as varying attributes, crop prices and expected water availability (for those IDUs with irrigation water rights). Given the estimated probabilities for each IDU, the simulation models determine the crop for each IDU in each year with a random draw reflecting these estimated probabilities. No evidence of crop choices being correlated across years (i.e., a crop rotation schedule) were found in the data or in interviews with farmers or agricultural extension personnel. The resulting modeled values are interpreted as the probabilities for each crop to be grown. For perennial crops (orchards, vineyards, tree crops), a fixed set of IDUs is permanently assigned.

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