Thomas H. Marek

Design and Construction of Large Weighing Monolithic Lysimeters

ABSTRACT FOUR large, weighing, monolithic lysimeters were designed, constructed and installed at Bushland, TX. Each lysimeter has a surface area of 9 m^ and a soil depth of 2.3 m. The soil within each lysimeter is an undisturbed monolith of Pullman clay loam. Each soil monolith has a mass of approximately 45 Mg, including the container mass. The lysimeters are installed in a 20 ha field with one lysimeter located in the center of each quarter of the field. The parameters of wind disturbance, water infiltration, drainage, thermal continuity, sidewall water percolation, rooting depth, scale stability, row spacing geometry, and safety were considered in the design. A compact mechanical type weighing system and load cell was used with an overall capability of detecting mass changes equivalent to a minimum of 0.05 mm of water. Automated data acquisition and telecommunication to offsite computers were utilized.

Surface Energy Balance Based Evapotranspiration Mapping in the Texas High Plains

Agriculture on the Texas High Plains (THP) uses approximately 89% of groundwater withdrawals from the Ogallala Aquifer. Consequently, groundwater levels are declining faster than the recharge rate. Therefore, efficient agricultural water use is essential for economic viability and sustainability of the THP. Accurate regional evapotranspiration (ET) maps would provide valuable information on actual crop water use. In this study, METRIC (Mapping Evapotranspiration at High Resolution using Internalized Calibration), a remote sensing based ET algorithm, was evaluated for mapping ET in the THP. Two Landsat 5 Thematic Mapper images acquired on 27 June (DOY 178) and 29 July (DOY 210) 2005 were used for this purpose. The performance of the ET model was evaluated by comparing the predicted daily ET with values derived from soil moisture budget at four commercial agricultural fields. Daily ET estimates resulted with a prediction error of 12.7±8.1% (mean bias error ± root mean square error) on DOY 178 and -4.7±9.4% on DOY 210 when compared with ET derived from measured soil moisture through the soil water balance. These results are good considering the prevailing advective conditions in the THP. METRIC have the potential to be used for mapping regional ET in the THP region. However, more evaluation is needed under different agroclimatological conditions.

SENSITIVITY OF GRASS- AND ALFALFA-REFERENCE EVAPOTRANSPIRATION TO WEATHER STATION SENSOR ACCURACY

A sensitivity analysis was conducted to determine the relative effects of measurement errors in climate data input parameters on the accuracy of calculated reference crop evapotranspiration (ET) using the ASCE-EWRI Standardized Reference ET Equation. Data for the period of 1995 to 2008 from an automated weather station located at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas were used for the analysis. Results indicated that grass (ETos) and alfalfa (ETrs) reference crop ET were most sensitive to measurement errors in wind speed and air temperature followed by incoming shortwave (solar) radiation, and that data sensitivity was greater during the mid-summer growing season in this semi-arid region. Given the highly advective conditions of the Texas High Plains and the relative sensitivity of ET calculations to errors in wind speed, special care is recommended in siting, sensor placement, and sensor maintenance for agriculturally-based ET weather stations.

Statistical learning algorithms for identifying contrasting tillage practices with Landsat Thematic Mapper data

Tillage management practices have a direct impact on water-holding capacity, evaporation, carbon sequestration and water quality. This study examines the feasibility of two statistical learning algorithms, namely the least square support vector machine (LSSVM) and relevance vector machine (RVM), for identifying two contrasting tillage management practices using remote-sensing data. LSSVM is firmly based on statistical learning theory, whereas RVM is a probabilistic model where the training takes place in a Bayesian framework. Input to the LSSVM and RVM algorithms were reflectance values at different bandwidths and indices derived from Landsat Thematic Mapper (TM) data. Ground-truth data for this study were collected from 72 commercial production fields in two counties located in the Texas High Plains of the south-central USA. Numerous LSSVM- and RVM-based tillage models were developed and evaluated for tillage classification accuracy. The percentage correct and kappa statistic were used for the evaluation. The results showed that the best LSSVM and RVM models included the use of TM band 5 or vegetation indices that involved TM band 5, indicating sensitivity of near-infrared reflectance of crop residue cover on the surface. This is consistent with other remote-sensing models reported in the literature. Overall classification accuracies of the best LSSVM and RVM models were 87.8 and 90.2%, respectively. The corresponding kappa statistics for those models were 0.75 and 0.80, respectively. Furthermore, comparison of the best LSSVM and RVM models with the published logistic regression-based tillage models developed with the same data indicated the superiority of the RVM model over LSSVM and logistic regression models in determining contrasting tillage practices with Landsat TM data.

Evapotranspiration and Crop Coefficients for Irrigated Sunflower in the Southern High Plains

Sunflower (Helianthus annuus L.) is a diverse crop grown for oil or confectionary uses in the Southern High Plains often under irrigation. Crop water use (evapotranspiration or ET) was measured in 2009 and 2011 in two 4-ha fields using two precision 9 m2 weighing lysimeters containing 2.3-m deep monoliths of Pullman clay loam soil. The fields were irrigated with a lateral move sprinkler system with nozzles ~1.7-1.8 m above the ground and ~1.5-m apart. The sunflower ET averaged 638 mm; seed yields averaged 308 g m-2; and the lysimeter water productivity averaged 0.49 kg m-3. The crop coefficients based on the FAO-56 curve method were 0.15 for Kcbini and 1.22 for Kcbmid based on the daily ASCE Reference ET (ETos). The Kcbmid based on the ASCE taller, rougher Reference ET (ETrs) was 0.80. Using a thermal-time base (growing degree day) for the crop coefficient did not improve the crop coefficient for the diverse planting dates in these seasons.

Estimating seasonal crop ET using calendar and heat unit based crop coefficients in the Texas High Plains Evapotranspiration Network

The Texas High Plains Evapotranspiration (TXHPET) network utilizes a heat unit-based approach (growing degree day concept) in the timing of various crop growth stages along with crop coefficients for computation of crop water use with the newly standardized ASCE/EWRI reference evapotranspiration (ET) equation. Mean crop coefficients of the TXHPET network are empirically derived from measurements using the large, monolithic lysimeters located at the USDA-ARS at Bushland, TX. Average regional crop growth stages are adjusted using multi-year, in-season, recorded data from irrigated producers through the Texas Cooperative Extension’s Agri-Partner program. A comparison of the seasonal and crop stages of the TXHPET network as compared with the FAO-56 method, which utilizes date based timing for the crop growth stages, for the major crops of corn, grain sorghum and soybeans is presented. This analysis was conducted to determine if additional, producer requested crops not evaluated with weighing lysimeters would have adequate accuracy based on previously measured crops using the FAO-56 method for irrigation scheduling purposes through the TXHPET network. While there were substantial ET differences in several growth stages of the crops evaluated, the total seasonal crop ET difference as evaluated indicated that use of the calendar based FAO-56 method could provide some degree of guidance to producers irrigating crops not yet evaluated with regional weighing lysimeters.

Feasibility of Water Management Strategies for the Declining Ogallala Aquifer

BACKGROUND The Region A groundwater aquifer level in the heavily irrigated, northern region of Texas continues to decline with this portion of the Ogallala Aquifer having no appreciable rate of recharge. The new state water planning requirements warranted a feasibility analysis of water management strategies that could be potentially implemented during the next 60 years to reduce the rate of aquifer pumpage for irrigation use. The strategies proposed in Senate Bill 1 were those of ET network scheduling, changes in crop variety, irrigation equipment improvements, changes in crop type, implementation of conservation tillage methods, precipitation enhancement, and the conversion from irrigated to dryland farming.

Relationship between LAI and Landsat TM Spectral Vegetation Indices in the Texas Panhandle

Abstract: Mapping and monitoring leaf area index (LAI) is important for spatially distributed modeling of surface energy balance, evapotranspiration and vegetation productivity. Remote sensing can facilitate the rapid collection of LAI information on individual fields over large areas in a time and cost-effective manner. However, there are no LAI models available for the major summer crops in the Texas Panhandle. The main objective of this study was to develop statistical relationship between LAI and Landsat Thematic Mapper (TM) based spectral vegetation indices (SVI) for major crops in the Texas Panhandle. LAI was measured in 48 randomly selected commercial fields in Moore and Ochiltree counties. Data collection was made to coincide with Landsat 5 satellite overpasses on the study area. Numerous derivations of SVIs were examined for estimating LAI using ordinary least square regression models such as linear, quadratic, power and exponential models. The R2 values for the selected models varied from 0.76 to 0.84 with the power function model based on the normalized difference between TM bands 4 and 3 (NDVI) producing the best results. Analysis of the results indicated that the SVI-LAI models based on the simple ratio i.e. the ratio of TM bands 4 and 3, and NDVI are most sensitive to LAI.

Irrigation Water Demand Estimates for the Texas Panhandle (Region A)

Severe drought conditions occurred in Texas during the 1990’s and resulted in many water entities being forced to implement rationing programs to balance water demand with available supplies. Subsequently, the 75 th Texas Legislature mandated a review of the State’s Water Plan. As irrigation is the largest user of water in the Texas Panhandle, a critical assessment of irrigation water demand estimates was needed. Previously, the Texas Water Department Board (TWDB) had provided these projections, principally through surveys from county and regional Natural Resource Conservation Service (NRCS) personnel. To attain a more localized focus, the state was divided into 16 regions. Each region was charged to review the TWDB estimates, and either accept their statistics or formulate a methodology that would possibly be more realistic in reflecting the irrigation water demands in their region. The Texas Panhandle High Plains area was designated as Region A. It was comprised of the following 21 counties: Armstrong, Carson, Childress, Collingsworth, Dallam, Donley, Gray, Hall, Hansford, Hartley, Hemphill, Hutchinson, Lipscomb, Moore, Ochiltree, Oldham, Potter, Randall, Roberts, Sherman and Wheeler. In the past, large differences existed between the TWDB estimates and the measured drawdown in wells within the Texas Panhandle region. The alternative methodology proposed by the team and developed for Region A used calibrated crop evapotranspiration (ET) in estimating irrigation water demands for corn, cotton, grain sorghum, hay, pasture, peanuts, soybeans and wheat. Computations were based on the following: 1. Crop ET. Actual crop ET was derived from the large monolithic lysimeter facility at Bushland and obtained through the North Plains Potential Evapotranspiration Network (NPPET). 2. Monthly Effective Rainfall. A modified monthly effective rainfall was utilized from the procedure described in the NRCS National Engineering Handbook (Part 623, Chapter 2). 3. Percent Potential Evapotranspiration (PET). The percent crop PET utilized in Region A was based on Texas Agricultural Extension Service data

Crop Coefficient Development and Application to an Evapotranspiration Network

Crop coefficients derived from properly designed, operated and maintained lysimeters provide the most accurate values throughout the growing season and are critical in the computation of hourly and daily, regionally based, crop evapotranspiration (ET) values. Multi-stage crop coefficients can be derived from continuously recording lysimeters, increasing the accuracy of both daily and seasonal irrigation crop demand estimates. These crop coefficients can be used with calculated, network based, reference crop ET to develop and disseminate locally representative crop water use estimates. Subsequently, using these accurate values in estimating crop water demand results in improved validity of regional water demand models, better assessments of proposed water policy measures, and enhanced integrity with crop consultants, water districts, and agricultural producers, ultimately resulting in better (more efficient) irrigation management and water conservation.