The SPAW Model for Agricultural Field and Pond Hydrologic Simulation

Saxton, K. E.; Willey, Patrick H.

doi:10.1201/9781420037432.ch17

Cited by 83 publications

(80 citation statements)

References 10 publications

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“…[20] lists some of these land surface models, which include the Soil-Plant-Atmosphere-Water model [40,41], US Department of Agriculture Hydrograph Laboratory [42,43], Sacramento Soil Moisture Accounting Model [44], and soil vegetation atmosphere transfer schemes [45]. However, the difficulty associated with measuring physical parameters required by these models serves as an impediment for their intensive use in agricultural management [20].…”

Section: Soil Moisture Measurement and Estimationmentioning

confidence: 99%

Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines

Torres‐Rua

Ticlavilca

Bachour

et al. 2016

Water

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Spatial surface soil moisture can be an important indicator of crop conditions on farmland, but its continuous estimation remains challenging due to coarse spatial and temporal resolution of existing remotely-sensed products. Furthermore, while preceding research on soil moisture using remote sensing (surface energy balance, weather parameters, and vegetation indices) has demonstrated a relationship between these factors and soil moisture, practical continuous spatial quantification of the latter is still unavailable for use in water and agricultural management. In this study, a methodology is presented to estimate volumetric surface soil moisture by statistical selection from potential predictors that include vegetation indices and energy balance products derived from satellite (Landsat) imagery and weather data as identified in scientific literature. This methodology employs a statistical learning machine called a Relevance Vector Machine (RVM) to identify and relate the potential predictors to soil moisture by means of stratified cross-validation and forward variable selection. Surface soil moisture measurements from irrigated agricultural fields in Central Utah in the 2012 irrigation season were used, along with weather data, Landsat vegetation indices, and energy balance products. The methodology, data collection, processing, and estimation accuracy are presented and discussed.

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Section: Soil Moisture Measurement and Estimationmentioning

confidence: 99%

Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines

Torres‐Rua

Ticlavilca

Bachour

et al. 2016

Water

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“…where D 25 is the molecular diffusivity of CO 2 (1.4 × 10 −5 m 2 s −1 ) at 298 K; θ a is the proportion of soil pores filled with air; θ a = θ sat -θ w , where θ sat is the soil water content at saturation estimated to be 0.46 m 3 m −3 at the site (Saxton and Willey, 2006), b is the soil water retention parameter, determined to be equal to 6.2 in this study (Cosby et al, 1984), T 25 = 298 K and n is 1.5 (Bird et al, 2002).…”

Section: Appendix Bmentioning

confidence: 99%

Use of the isotope flux ratio approach to investigate the C18O16O and 13CO2 exchange near the floor of a temperate deciduous forest

Santos¹,

Wagner-Riddle

Lee

et al. 2012

Biogeosciences

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Abstract. Stable isotopologues of CO 2 , such as 13 CO 2 and C 18 OO, have been used to study the CO 2 exchange between land and atmosphere. The advent of new measuring techniques has allowed near-continuous measurements of stable isotopes in the air. These measurements can be used with micrometeorological techniques, providing new tools to investigate the isotope exchange in ecosystems. The objectives of this study were to evaluate the use of the isotope flux ratio method (IFR) near the forest floor of a temperate deciduous forest and to study the temporal dynamics of δ 18 O of CO 2 flux near the forest floor by comparing IFR estimates with estimates of δ 18 O of net soil CO 2 flux provided by an analytical model. Mixing ratios of 12 C 16 O 2 , 13 CO 2 and C 16 O 18 O were measured within and above a temperate deciduous forest, using the tunable diode laser spectroscopy technique. The half-hourly compositions of the CO 2 flux near the forest floor (δ 13 C F and δ 18 O F ) were calculated by IFR and compared with estimates provided by a modified Keeling plot technique (mKP) and by a Lagrangian dispersion analysis (WT analysis). The mKP and IFR δ 18 O F estimates showed good agreement (slope = 1.03 and correlation, R 2 = 0.80). The δ 13 C F estimates from the two methods varied in a narrow range of −32.7 and −23.1 ‰; the mean (± SE) mKP and IFR δ 13 C F values were −27.5 ‰ (±0.2) and −27.3 ‰ (±0.1), respectively, and were statistically identical (p > 0.05). WT analysis and IFR δ 18 O F estimates showed better correlation (R 2 = 0.37) when only turbulent periods (u * > 0.6 m s −1 ) were included in the analysis. The large amount of data captured (∼95 % of half-hour periods evaluated) for the IFR in comparison with mKP (27 %) shows that the former provides new opportunities for studying δ 18 O F dynamics within forest canopies. Values of δ 18 O F showed large temporal variation, with values ranging from −31.4 ‰ (DOY 208) to −11.2 ‰ (DOY 221). Precipitation events caused substantial variation (∼8 ‰) in δ 18 O F over a period of approximately 24 h. A diel trend of δ 18 O F was observed, with more depleted values present during the daytime. Model simulations indicate that the activity of the carbonic anhydrase enzyme was quite variable during the evaluated period. These simulations indicate that more frequent sampling of δ 18 O of soil water could improve the estimates of δ 18 O of net soil CO 2 flux.

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“…Physical soil characteristic parameters, including the soil moisture content at wilting point (% cm 3¨c m´3), soil moisture content at field capacity (% cm 3¨c m´3), soil moisture content at saturation (% cm 3¨c m´3) and the hydraulic conductivity of the saturated soil (cm¨d´1), were estimated using the module Soil-Water-CharacTeristics (SWCT) of the Soil-Plant-Air-Water (SPAW) model [38] Water-limited production levels were considered to investigate the responses of winter wheat to climatic variability in the RCP4.5 and RCP8.5 climate change scenarios because water-limited production levels represent the maximum yield obtained under rain-fed conditions. The management parameters were held constant, and the mean sowing dates for each 30-year period and conditions with no irrigation and fertilization were considered.…”

Section: The Crop Growth Modelmentioning

confidence: 99%

Projected Crop Production under Regional Climate Change Using Scenario Data and Modeling: Sensitivity to Chosen Sowing Date and Cultivar

Tao

Shen

et al. 2016

Sustainability

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Abstract:A sensitivity analysis of the responses of crops to the chosen production adaptation options under regional climate change was conducted in this study. Projections of winter wheat production for different sowing dates and cultivars were estimated for a major economic and agricultural province of China from 2021 to 2080 using the World Food Study model (WOFOST) under representative concentration pathways (RCPs) scenarios. A modeling chain was established and a correction method was proposed to reduce the bias of the resulting model-simulated climate data. The results indicated that adjusting the sowing dates and cultivars could mitigate the influences of climate change on winter wheat production in Jinagsu. The yield gains were projected from the chosen sowing date and cultivar. The following actions are recommended to ensure high and stable yields under future climate changes: (i) advance the latest sowing date in some areas of northern Jiangsu; and (ii) use heat-tolerant or heat-tolerant and drought-resistant varieties in most areas of Jiangsu rather than the currently used cultivar. Fewer of the common negative effects of using a single climate model occurred when using the sensitivity analysis because our bias correction method was effective for scenario data and because the WOFOST performed well for Jiangsu after calibration.

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The SPAW Model for Agricultural Field and Pond Hydrologic Simulation

Cited by 83 publications

References 10 publications

Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines

Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines

Use of the isotope flux ratio approach to investigate the C<sup>18</sup>O<sup>16</sup>O and <sup>13</sup>CO<sub>2</sub> exchange near the floor of a temperate deciduous forest

Projected Crop Production under Regional Climate Change Using Scenario Data and Modeling: Sensitivity to Chosen Sowing Date and Cultivar

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The SPAW Model for Agricultural Field and Pond Hydrologic Simulation

Cited by 83 publications

References 10 publications

Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines

Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines

Use of the isotope flux ratio approach to investigate the C&lt;sup&gt;18&lt;/sup&gt;O&lt;sup&gt;16&lt;/sup&gt;O and &lt;sup&gt;13&lt;/sup&gt;CO&lt;sub&gt;2&lt;/sub&gt; exchange near the floor of a temperate deciduous forest

Projected Crop Production under Regional Climate Change Using Scenario Data and Modeling: Sensitivity to Chosen Sowing Date and Cultivar

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Use of the isotope flux ratio approach to investigate the C<sup>18</sup>O<sup>16</sup>O and <sup>13</sup>CO<sub>2</sub> exchange near the floor of a temperate deciduous forest