VIC-CropSyst: A regional-scale modeling platform to simulate the
nexus of climate, hydrology, cropping systems, and human decisions

Malek, Keyvan; Stöckle, Claudio O.; Chinnayakanahalli, K.; Nelson, Roger; Liu, Mingliang; Rajagopalan, K.; Barik, M. G.; Adam, J. C.

doi:10.5194/gmd-2016-294

Cited by 3 publications

(9 citation statements)

References 89 publications

(154 reference statements)

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“…In the coupled model, VIC and CropSyst share several variables that Malek, Stockle, et al. (2017) have presented in detail. Some of the variables shared from the VIC side are soil moisture, soil temperature, and soil properties (such as soil water potential, potential evapotranspiration, irrigation timing and amount, air temperature, precipitation, and relative humidity).…”

Section: Methodsmentioning

confidence: 99%

“…The model can also simulate how agricultural management decisions feedback to water systems and vice versa. More detail is provided in the original paper that introduces VIC‐CropSyst (Malek, Stockle, et al., 2017). In addition, Malek, Adam, Stöckle, and Peters (2018) also added a mechanistic irrigation module to the VIC‐CropSyst that can estimate the amount and timing of irrigation.…”

Section: Methodsmentioning

confidence: 99%

“…However, they have also been used and compared against observations at smaller scale. VIC‐CropSyst has been used in several regional studies (Barik et al., 2017; Malek, McClure, et al., 2017; Malek, Adam, Stockle, Brady, et al., 2018; Malek, Adam, Stöckle, Peters, 2018; Malek et al., 2020; Malek, Stockle, et al., 2017; Rajagopalan et al., 2018) and has been compared against observations at farm scale (two flux tower sites in Mead Nebraska and Fermi National Laboratory in Illinois). The simulated variables that were compared with observations (Malek, Stockle, et al., 2017), include Evapotranspiration (ET), soil moisture, yield, LAI, and irrigation demand, and the results showed that the model can capture both hydrologic and crop‐related processes.…”

Section: Methodsmentioning

confidence: 99%

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Diagnostic Framework for Evaluating How Parametric Uncertainty Influences Agro‐Hydrologic Model Projections of Crop Yields Under Climate Change

Karimi

Reed

Malek

et al. 2022

Water Resources Research

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Despite the prevalence of climate change assessments of crop yields, there are significant limits to our understanding of how parametric uncertainty in the underlying agro‐hydrologic models as well as the stationarity assumptions tacit to their commonly employed calibration procedures are influencing projections. This study addresses this knowledge gap by clarifying how parametric uncertainty in agro‐hydrologic models influences yield projections under changing future climate. We focus on rain‐fed winter wheat systems in the drylands of United States Pacific Northwest. We use a tightly coupled agro‐hydrologic model, VIC‐CropSyst, as a representative of this class of models. Our contributed diagnostic global sensitivity analysis framework identifies differences in how influential factors (e.g., temperature during early growth stages or the growing degree‐day required to reach peak leaf area index) vary across zones during historical and future periods. Our results show that the dominant parametric controls for yield projection and their sensitivities change subject to agro‐climatic zones and differences in the specific temperature‐precipitation trends in future climate scenarios. Our results also indicate that the stationarity assumptions tacit to using historical observations to calibrate agro‐hydrologic model parameters and their subsequent use in future yield projections may introduce significant bias. Employing the stationarity assumption in future projections problematically ignores how shifts in climate influence the relative dominance of underlying agro‐hydrologic processes in the model. This study's contributed diagnostic exploratory modeling framework has promise for advancing our understanding of how calibration, parametric uncertainties, and climate induced changes in the dominance of model biophysical processes shape crop yield projections.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Diagnostic Framework for Evaluating How Parametric Uncertainty Influences Agro‐Hydrologic Model Projections of Crop Yields Under Climate Change

Karimi

Reed

Malek

et al. 2022

Water Resources Research

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“…Hydrologic models are also integrating and improving upon vegetation dynamics, allowing the models to better predict water demand and crop yields, which drive irrigation, in future climate and policy scenarios. For example, integration of crop growth and irrigation modules in the Variable Infiltration Capacity model (VIC-CropSyst) improved hydrologic simulations in agricultural watersheds (Malek et al, 2017). HydroGeoSphere recently incorporated on-demand irrigation into their modeling framework, which triggers groundwater extraction during the user-defined growing season when the pressure head at a specified location and depth declines below a prescribed level.…”

Section: Numerical Modelsmentioning

confidence: 99%

Quantifying Streamflow Depletion from Groundwater Pumping: A Practical Review of Past and Emerging Approaches for Water Management

Zipper¹,

Farmer²,

Brookfield³

et al. 2022

Preprint

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Groundwater pumping can cause reductions in streamflow (‘streamflow depletion’) that must be quantified for conjunctive management of groundwater and surface water resources. However, streamflow depletion cannot be measured directly and is challenging to estimate because pumping impacts are masked by streamflow variability due to other factors. Here, we conduct a management-focused review of analytical, numerical, and statistical models for estimating streamflow depletion and highlight promising emerging approaches. Analytical models are easy to implement, but include many assumptions about the stream and aquifer. Numerical models are widely used for streamflow depletion assessment and can represent many processes affecting streamflow, but have high data, expertise, and computational needs. Statistical approaches are a historically underutilized tool due to difficulty in attributing causality, but emerging causal inference techniques merit future research and development. We propose that streamflow depletion-related management questions can be divided into three broad categories (attribution, impacts, and mitigation) that influence which methodology is most appropriate. We then develop decision criteria for method selection based on suitability for local conditions and the management goal, actionability with current or obtainable data and resources, transparency with respect to process and uncertainties, and reproducibility.

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“…Continuing improvements in process-based models (Stockle et al, 1994(Stockle et al, , 2003Adam et al, 2015;Malek et al, 2016) and experimental work (Haile-Mariam et al, 2008;Brown and Huggins, 2012;Chi et al, 2016;Waldo et al, 2016) provide important insights and the capability to produce regionallyrelevant estimates of mitigation potential of agricultural GHG reduction strategies. However, published estimates of the GHG reduction potential of the region are still incomplete due to the heterogeneity of the region's agroecosystems.…”

Section: Climate Mitigation Opportunitiesmentioning

confidence: 99%

Northwest U.S. Agriculture in a Changing Climate: Collaboratively Defined Research and Extension Priorities

Yorgey

Hall

Allen

et al. 2017

Front. Environ. Sci.

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In order for agricultural systems to successfully mitigate and adapt to climate change there is a need to coordinate and prioritize next steps for research and extension. This includes focusing on "win-win" management practices that simultaneously provide short-term benefits to farmers and improve the sustainability and resiliency of agricultural systems with respect to climate change. In the Northwest U.S., a collaborative process has been used to engage individuals spanning the research-practice continuum. This collaborative approach was utilized at a 2016 workshop titled "Agriculture in a Changing Climate," that included a broad range of participants including university faculty and students, crop and livestock producers, and individuals representing state, tribal and federal government agencies, industry, nonprofit organizations, and conservation districts. The Northwest U.S. encompasses a range of agro-ecological systems and diverse geographic and climatic contexts. Regional research and science communication efforts for climate change and agriculture have a strong history of engaging diverse stakeholders. These features of the Northwest U.S. provide a foundation for the collaborative research and extension prioritization presented here. We focus on identifying research and extension actions that can be taken over the next 5 years in four areas identified as important areas by conference organizers and participants: (1) cropping systems, (2) livestock systems, (3) decision support systems to support consideration of climate change in agricultural management decisions; and (4) partnerships among researchers and stakeholders. We couple insights from the workshop and a review of current literature to articulate current scientific understanding, and priorities recommended by workshop participants that target existing knowledge Yorgey et al.Priorities for U.S. Northwest Agriculture in a Changing Climate gaps, challenges, and opportunities. Priorities defined at the Agriculture in a Changing Climate workshop highlight the need for ongoing investment in interdisciplinary research integrating social, economic, and biophysical sciences, strategic collaborations, and knowledge sharing to develop actionable science that can support informed decision-making in the agriculture sector as the climate changes.

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VIC-CropSyst: A regional-scale modeling platform to simulate the nexus of climate, hydrology, cropping systems, and human decisions

Cited by 3 publications

References 89 publications

Diagnostic Framework for Evaluating How Parametric Uncertainty Influences Agro‐Hydrologic Model Projections of Crop Yields Under Climate Change

Diagnostic Framework for Evaluating How Parametric Uncertainty Influences Agro‐Hydrologic Model Projections of Crop Yields Under Climate Change

Quantifying Streamflow Depletion from Groundwater Pumping: A Practical Review of Past and Emerging Approaches for Water Management

Northwest U.S. Agriculture in a Changing Climate: Collaboratively Defined Research and Extension Priorities

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