QbQb W2W2 T IPIP Redistribute W 0 W 1 and W 2 to Crop layers Q W1W1 ET 0, W 0, W 1, W 2 I T from 0, 1 & 2, I P A Coupled Hydrologic and Process-Based Crop.
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Presentation on theme: "QbQb W2W2 T IPIP Redistribute W 0 W 1 and W 2 to Crop layers Q W1W1 ET 0, W 0, W 1, W 2 I T from 0, 1 & 2, I P A Coupled Hydrologic and Process-Based Crop."— Presentation transcript:
QbQb W2W2 T IPIP Redistribute W 0 W 1 and W 2 to Crop layers Q W1W1 ET 0, W 0, W 1, W 2 I T from 0, 1 & 2, I P A Coupled Hydrologic and Process-Based Crop Dynamics Model for Studying Climate Change Impacts on Water Resources and Agricultural Production Kiran Chinnayakanahalli 1, Jennifer Adam 1*, Claudio Stockle 2, Roger Nelson 2 and Mike Barber 1 1 Civil and Environmental Engineering, Washington State University, PO Box 642910,Pullman, WA 99164-2910. 2 Biological Systems Engineering, Washington State University, PO Box 646120, Pullman, WA 99164-6120. Email: firstname.lastname@example.org, *email@example.com AGU Fall 2010 H53A - 0996 Agriculture is an important component of the Pacific Northwest (PNW ) economy. Agricultural commodities produced in Washington alone have an annual value over $5 billion; nationally Washington State leads the U.S. in production of apples, cherries, hops, and mint (Casola et al., 2005). The hydrology of PNW is expected to be significantly affected by climate change. The climate change-induced stress on the availability of water resources during the growing season may constrain irrigation and agricultural practices which will in turn affect crop production. To assess climate change impacts on PNW agriculture, it is essential that we understand the relationships between crop dynamics and the hydrological cycle. To accomplish this we have integrated a macro scale hydrology model, the Variable Infiltration Capacity (VIC) model, with a cropping systems model (CropSyst). Here we present details of the model integration framework that is being implemented. 1. Introduction3. Crop distribution To develop a coupled hydrology and cropping systems model to project and compare future water supply and irrigation water demand in the Columbia River Basin for improved water resources management. Objective http://www.bsyse.wsu.edu/cropsyst CropSyst is a multi-year multi-crop daily time step simulation model. The model simulates transpiration, crop canopy and root growth, dry matter production, and yield (Stockle et al., 2003). A simplified version of the CropSyst model is used for integration with VIC. Variable Infiltration Capacity (VIC) Model (Liang et al., 1994) is a spatially distributed, physically based model for simulating energy and water balance components. Here, VIC is applied at 1/16 th degree resolution (Elsner et al. 2010) 2. Model Integration VIC Crop model VIC-Crop model Integration Variables: T – Transpiration, I P – Interception capacity, I – Infiltration, Q – Runoff, Q b – Baseflow, W 0 W 1 W 2 – Volumetric water content in layers 0, 1 and 2 respectively, ET 0 – Penman Monteith reference Pot. Evap. Land cover in VIC grid cell Crop type, Soil Texture CO 2 Time Sow date- start crop growth Crop maturity, harvest Crop 1 At the beginning of each time step To Crop model: Soil water content Weather condition Irrigation water (if available and needed) From Crop model: Daily water demand Current biomass Transpiration from VIC layers Total yield, Biomass etc A spatially distributed hydrology-crop model is a useful tool for studying the impacts of climate change on water resources, agriculture and the economy of the region A coupled hydrology-crop model is developed that can simulate biomass growth, crop yield, transpiration, and irrigation water demand The results from this modeling approach are expected to help stakeholders and water resource managers plan for a changing climate Casola J. H, Kay J. E. et al. (2005) Climate Impacts on Washington's hydropower, water supply, forests, fish and agriculture, Report from Climate Impact Group, University of Washington. Elsner, M., L. Cuo, N. Voisin, J. Deems, A. Hamlet, J. Vano, K. Mickelson, S. Lee, and D. Lettenmaier (2010), Implications of 21st century climate change for the hydrology of Washington State, Climatic Change, 225-260. Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, (1994): A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophys. Res., 99 (D7), 14 415–14 428. Stockle C. O, Donatelli M, Nelson R (2003) CropSyst, a cropping systems simulation model. Eur J Agron 18:289–307 4. Conclusions 5. References VIC invokes the crop model only when the land use type is a crop. The crop type is determined by the crop distribution coverage (Section 3) When the land cover is a crop, the crop model is informed about the soil characteristics and the crop type at the beginning of the time step Depending on the management options, VIC tells the crop model when the crop growth should be started (sow date) At every time step, VIC passes on to the crop model the current soil water content, weather condition, CO 2 level, and reference potential evapotranspiration The crop model then redistributes the soil water content from VIC soil layers to its soil layers, simulates crop pheonology, and estimates crop growth, transpiration from VIC’s soil layers and water requirements VIC uses the returned transpiration to update its soil water contents (W 0, W 1 and W 2 ) VIC responds to the crop water requirements by applying the required quantity of water as irrigation water. The application of irrigation water depends on the water availability and the irrigation efficiency of the system On reaching maturity, crop model harvests the crop and returns total crop yield and biomass. The harvesting can also be controlled through management options; this feature is particularly useful for perennial crops LAND COVER USA – USDA Cropland Data Layer (CDL); Canada – derived from National Ecological Framework for Canada **Not all land cover types are shown in the legend** Crop area according to CDL 2009 in Columbia River basin (USA), km 2 x 100 Crop model is parameterized for selected crops (Legend and Figure above) Crops selection was based on their high acreage and economic value