Measurement of Evaporation on Bare Soil and Estimating Surface Resistance

A new evaporation measuring device incorporating an evaporation chamber has been developed and checked for its accuracy. This device is unique that it uses a chamber that is completely open at one end and thereby minimizes the effect of the chamber on the natural profiles of temperature, humidity, and turbulence. It was used in estimating a newly formulated surface resistance to bare soil evaporation under dry topsoil conditions. A simple energy balance model incorporating the depth of evaporating surface, blended with a new approach for describing surface resistance was developed and successfully tested with a limited set of data obtained from a simple experiment, assuming ideal conditions. In addition to the newly formulated surface resistance, the depth of the dry soil layer was also estimated and was relatively comparable with measured value. The newly formulated surface resistance was found to be insignificant compared to the resistance imposed by the dry soil layer. The total surface resistance was modeled as a power function of soil moisture in the top 0–1 cm of soil, while the newly formulated resistance did not show any relation with the soil moisture.     

Estimating Evaporation from Bare Soil and the Crop Coefficient for the Initial Period Using Common Soils Information

The crop coefficient during the initial period (Kc?ini) varies with wetting frequency, evaporative demand, and water-holding capacity of the upper soil layer. It is possible to develop a semitheoretical integrated function to predict the average Kc?ini representing the initial period of a growing season when the soil is mostly bare and that incorporates these three factors. The function is based on a two-stage evaporation function as used in the Food and Agriculture Organization Irrigation and Drainage Paper No. 56 (FAO-56) dual crop coefficient method. Parameters in the integrated equation are soil based and can be calculated a priori without field measurements. The procedure can be used to produce graphical figures similar to that introduced in FAO-24 for Kc?ini. Similar to FAO-24, the function utilizes the mean time between wetting events and reference evapotranspiration. In this paper, the development of the procedure and figures for Kc?ini are described. Comparisons with measured evaporation and Kc?ini in southern California indicate relatively good performance by the function without calibration.     

Comparison of Measured and FAO-56 Modeled Evaporation from Bare Soil

This paper evaluates how well the FAO-56 style soil water evaporation model simulates measurements of evaporation (E) from bare soil. Seven data sets were identified from the literature and in all but one case, the individuals who took the measurements were contacted and they provided the writers with specific weather and soils data for model input. Missing weather and soils data were obtained from online sources or from the National Climatic Data Center. Simulations for three possible variations of soil data were completed and compared. The measured and the FAO-56 simulated E/ETo and cumulative evaporation trends and values were similar. Specifically, the average evaporation weighted percent difference between the measured and the simulated cumulative evaporation was between ?7.5 and ?0.5%. This evaluation suggests model accuracy of about ±15% with the use of sound weather data and a fairly generalized understanding of soil properties in the location being evaluated.     

Estimating Evaporation from Bare or Nearly Bare Soil

A model is presented that uses a daily mean evapotranspiration ETo rate to estimate energy-limited (potential or Stage 1) soil evaporation, and it also uses daily mean ETo and a soil hydraulic β factor to estimate soil hydraulic property-limited (Stage 2) evaporation. The model provides good estimates of cumulative soil evaporation on both hourly and daily bases when compared to observed soil evaporation in three field trials. Crop coefficient Kc values from cumulative hourly and cumulative daily soil evaporation estimates and ETo data were comparable. Using a soil hydraulic factor (β = 2.6) in the model gave a fair approximation for the widely used Kc curves for initial growth of crops presented in the United Nations Food and Agricultural Organization's Irrigation and Drainage Paper 24. However, using a site-specific β factor should improve soil evaporation and Kc estimates for site-specific applications.     

FAO-56 Dual Crop Coefficient Method for Estimating Evaporation from Soil and Application Extensions

Crop coefficient curves provide simple, reproducible means to estimate crop evapotranspiration (ET) from weather-based reference ET values. The dual crop coefficient (Kc) method of the Food and Agricultural Organization of the United States (FAO) Irrigation and Drainage Paper No. 56 (FAO-56) is intended to improve daily simulation of crop ET by considering separately the contribution of evaporation from soil. The dual method utilizes “basal” crop coefficients representing ET from crops having a dry soil surface and separately predicts evaporation from bare soil based on a water balance of the soil surface layer. Three extensions to the evaporation calculation procedure are described here that are intended to improve accuracy when applications warrant the extra complexity. The first extension uses parallel water balances representing the portion of the soil surface wetted by irrigation and precipitation together and the portion wetted by precipitation alone. The second extension uses three “stages” for surface drying and provides for application to deep cracking soils. The third extension predicts the extraction of the transpiration component from the soil surface layer. Sensitivity and analyses and illustrations indicate moderate sensitivity of daily calculated ET to application of the extensions. The dual Kc procedure, although relatively simple computationally and structurally, estimates daily ET as measured by lysimeter relatively well for periods of bare soil and partial and full vegetation cover.     

Methodology for Estimating Specific Yield in Shallow Water Environment Using Continuous Soil Moisture Data

A methodology for estimating specific yield in shallow water environments using continuous soil moisture data is introduced. An accurate estimate of specific yield is critical for management of water resources affecting well yields, water levels, and rates of water level decline. The study area is located in an intensive small-scale hydrologic monitoring field site in Hillsborough County, Florida. Data from four soil moisture monitoring stations were studied. The objectives of this paper are to describe a methodology to obtain precise estimates of the specific yield that can be obtained by a fitting procedure and to determine functional relationships between measured soil parameters and soil moisture storage variability. Estimated specific yield values varied from zero, when the water table was near land surface, to a maximum that was close to drainable porosity consistent with a humid shallow water environment, where sensitive ecosystems and wetlands are dependent on a seasonal hydroperiod of water table fluctuations. The results will be incorporated into regional integrated surface and ground water models that are being applied successfully in West-Central Florida.     

Estimating Evaporation Using ANFIS

Water resources engineering assessment requires simple but effective evaporation estimation procedures, especially from readily measurable meteorological factors. Unfortunately, such approaches are rather scarce in the literature. In this paper, an adaptive neural-based fuzzy inference system (ANFIS) was applied to daily meteorology data from the Lake E?irdir region in the southwestern part of Turkey. Daily evaporation, solar radiation, air and water temperatures, and relative humidity measurements were used to develop the ANFIS method, which helps to assess possible contributions that each input variable has on the evaporation estimates. Such an assessment is not possible by any conventional procedure including the Penman method. However, the Penman method daily evaporation estimations were used as output data for the verification of the ANFIS approach. Classical evaporation estimation models treat the data individually. However, ANFIS models process past data collectively and then adaptively provide estimates as new sets of data become available. In the ANFIS architecture as developed in this paper, there are four measured input variables and one output variable to estimate evaporation. The estimation results from the ANFIS model had a high coefficient of determination of 0.98 when compared with the Penman method results and a low average performance error of 4.6% among other alternatives. The average performance error is less than the practically acceptable limit of 10%.     

Estimating Soil Moisture Under Low Frequency Surface Irrigation Using Crop Water Stress Index

The present study investigated the relationship between the crop water stress index (CWSI) and soil moisture for surface irrigated cotton (Gossypium hirsutum, Delta Pine 90b) at Maricopa, Arizona during the 1998 season. The CWSI was linked to soil moisture through the water stress coefficient Ks that accounts for reduced crop evapotranspiration when there is a shortage of soil water. A stress recovery coefficient Krec was introduced to account for reduced crop evapotranspiration as the crop recovered from water stress after irrigation events. A soil water stress index (SWSI) was derived in terms of Ks and Krec. The SWSI compared reasonably well to the CWSI, but atmospheric stability correction for the CWSI did not improve comparisons. When the CWSI was substituted into the SWSI formulation, it gave good prediction of soil moisture depletion (fDEP; when to irrigate) and depth of root zone depletion (Dr; how much to irrigate). Disagreement was greatest for fDEP<0.6 because cotton is less sensitive to water stress in this range.     

Assessment of Soil Moisture Dynamics of the Nebraska Sandhills Using Long-Term Measurements and a Hydrology Model

Soil moisture, evapotranspiration, and other major water balance components were investigated for six Nebraska Sandhills locations during a 6 year period (1998–2004) using a hydrological model. Annual precipitation in the study period ranged from 330 to 580?mm. Soil moisture was measured continuously at 10, 25, 50, and 100?cm depth at each site. Model estimates of surface (0–30?cm), subsurface (30–91?cm), and root zone (0–122?cm) soil moisture were generally well correlated with observed soil moisture. The correlations were poorest for the surface layer, where soil moisture values fluctuated sharply, and best for the root zone as a whole. Modeled annual estimates of evapotranspiration and drainage beneath the rooting zone showed large differences between sites and between years. Despite the Sandhills’ relatively homogeneous vegetation and soils, the high spatiotemporal variability of major water balance components suggest an active interaction among various hydrological processes in response to precipitation in this semiarid region.     

Evaporation Research: Review and Interpretation

Literature regarding evaporation from soil, wet plant surfaces, and sprinkler droplets was examined, normalized, and interpreted. Much of the evaporation literature is difficult to compare and interpret; this paper offers comparisons and discussions of various findings by others as well as by the writers. Techniques of measuring and estimating evaporation from irrigation and rainfall are discussed. The partitioning between increased evaporation and decreased transpiration from a variety of research is quantified. Factors that impact the various forms of evaporation are listed and quantified. This review and summary will provide practitioners and researchers with theoretical and practical guidance on measurement techniques and estimates of evaporation under a wide range of conditions.     

Irrigation Scheduling for Green Bell Peppers Using Capacitance Soil Moisture Sensors

Vegetable production areas are intensively managed with high inputs of fertilizer and irrigation. The objectives of this study were to evaluate the interaction between N-fertilizer rates and irrigation scheduling using soil moisture sensor irrigation controllers (SMS) on yield, irrigation water use efficiency (IWUE) of bell pepper cultivated under plastic mulch and drip irrigation. Treatments included three irrigation scheduling and three N-rates (176, 220, and 330 kg/ha). Irrigation treatments were: SS10, water application controlled by SMS-based irrigation set at 10% volumetric water content (VWC) which was allotted five irrigation windows daily and bypassed events if the soil VWC exceeded the established threshold; SS12, threshold set at 12% VWC; and TIME, control with irrigation being applied once a day similar to grower irrigation management. Marketable yields ranged between 16 and 29 Mg/ha. The SMS treatments reduced the applied irrigation in 7 to 62% compared to TIME treatment without reducing yield. The treatments SS10 and SS12 reduced nitrate leaching by 25 to 73% compared to TIME treatment.     

Establishing Soil-Water Characteristic Curve of a Fine-Grained Soil from Electrical Measurements

Application of a pressure membrane extractor (PME) to establish soil-water characteristic curve (SWCC) of fine-grained soils, in 0–1,500 kPa range, is well established. However, this technique requires testing of several identical specimens, corresponding to same or different pressure(s), and their subsequent removal from the PME chamber for moisture content determination. This turns out to be a cumbersome process and even the results are considered less accurate, by the research fraternity. This is mainly due to the fact that removal of the specimen before equilibration time may not incorporate the influence of the applied pressure, precisely. This calls for the development of an alternate technique that can be employed for measuring the instantaneous moisture content of the specimen when it is pressurized, sequentially, without removing it from the PME chamber. In this context, the utility of electrical measurements (i.e., the voltage) across two points in the specimen for determining moisture content was investigated and its details are presented in this paper. This technique has been found to be quite promising and hence can be employed for acquisition of the data which would yield the moisture content of the specimen, without removing it from the PME chamber, easily and quickly. Validity of the methodology has been demonstrated by comparing the obtained SWCC vis-à-vis those obtained by conducting studies using a dewpoint potentiameter, WP4, and by employing the fitting function and a pedo-transfer function available in the SoilVision database.     

Mapping Root Zone Soil Moisture Using Remotely Sensed Optical Imagery

Field-based soil moisture measurements are cumbersome. Remote sensing techniques based on active or passive microwave data have limitations. This paper presents and validates a new method based on land surface energy balances using remotely sensed optical data (including thermal infrared), which allows field and landscape-scale mapping of soil moisture depth-averaged through the root zone of existing vegetation. Root zone depth can be variable when crops are emerging. The pixel-wise “evaporative fraction” (ratio of latent heat flux to net available energy) is related to volumetric soil moisture through a standard regression curve that is independent of soil and vegetation type. Validation with measured root zone soil moisture in cropped soils in Mexico and Pakistan has a root mean square error of 0.05?cm3?cm?3; the error is less than 0.07?cm3?cm?3 in 90% of cases. Consequently, soil moisture data should be presented in class intervals of 0.05?cm3?cm?3. The utility of this method is demonstrated at the field scale using multitemporal thematic mapper imagery for irrigated areas near Cortazar in Mexico, and for river basin-scale water resources distribution in Pakistan. The potential limitation is the presence of clouds and the time lag between consecutive images with field-scale resolution. With the falling price of optical satellite imagery, this technique should gain wider acceptance with river basin planners, watershed managers, and irrigation and drainage engineers.     

Data Mining Process for Integrated Evaporation Model

The purpose of this study is to develop an integrating evaporation estimation model using a data mining process for the Lakes District in the southern part of Turkey. Lakes E?irdir, Kovada, and Karaca?ren Dam are located in the Lakes District. The proposed data mining process is applied on these lakes for evaporation estimation. The daily pan evaporation data used in the data mining process are taken from State Hydraulic Works in southern Turkey. These data cover an 8-year period between 1998 and 2005 inclusively for daily pan evaporation of Lakes E?irdir, Kovada, and Karaca?ren Dam. It is known that a developed integrated daily pan evaporation model is necessary for these lakes, which are so important to the Lakes District. Therefore, a data mining model having two inputs and one output is developed. Input parameters used in the developed models for Lakes E?irdir, Kovada, and Karaca?ren Dam were daily pan evaporation values of Lakes Kovada + Karaca?ren Dam, Lakes E?irdir + Karaca?ren Dam, and Lakes E?irdir Kovada, respectively. As a result, in comparing the developed models with measured daily pan evaporation values, the REP tree model has better agreement with measured daily pan evaporation than other models. The results show the developed model was more accurate.     

Soil Moisture Flow Modeling with Water Uptake by Plants (Wheat) under Varying Soil and Moisture Conditions

A variably saturated soil moisture flow model is developed for planted soils with depth varying properties by incorporating a nonuniform macroscopic root water uptake function. The model includes spatial and temporal variation of the root density with dynamic root growth for simulating water uptake by plants along with the impact of soil moisture availability. The governing partial differential moisture flow equation integrated over the depth with a plant water uptake term is solved numerically by the implicit finite difference method using an iterative scheme. The model is first tested for barren soils for two profiles considering constant and depth varying soil characteristics under constant inflow condition. The results obtained are later tested with experimental data available in the literature. A nonuniform plant water uptake term is subsequently incorporated in the model and water uptake by wheat plants under different soil moisture availability conditions is studied. Finally, the moisture flow model is validated with field data of rain fed wheat (Triticum aestivum) using a dynamic root growth model for a layered root zone soil profile. The simulated soil moisture regime of the layered root zone shows a reasonably good agreement with the observed data.     

Performance Study of SPAW Model with Temperature-Derived ET0 as Input in Place of Pan Evaporation under Wheat Crop in a Semiarid Subtropical Climate

In this study, we have attempted to enhance the utility of soil–plant–atmosphere–water (SPAW) model that has been used successfully by various workers in different countries for soil moisture prediction under different cropping conditions. One of the major climatic inputs for SPAW model is pan evaporation, which in many places is not readily available. To address the above, and to get the benefit of this model in regions characterized by limited weather data availability, this study was undertaken using computed ET0 from air temperature by the 1985 Hargreaves equation, as one of the inputs in place of pan evaporation. For the purpose, actual air temperature collected from experimental farm area, as well as forecast air temperature collected from National Centre for Medium Range Weather Forecasting, Government of India, were used. First, the SPAW model was calibrated and its performance was evaluated under wheat, taking layerwise and profile soil moisture as the variables for comparison between the predicted and observed values. The results showed that the root-mean-square error (RMSE) varied from 0.30?to?0.58?cm for measured values ranging between 2.24 and 4.25?cm. The index of agreement (d) varied from 0.81 to 0.92 and coefficient of determination (r2) from 0.46 to 0.73 for 0–15, 15–30, 30–45, and 45–60?cm soil depths. For the whole 60?cm profile, the RMSE was 1.07?cm with d and r2 values of 0.94 and 0.85 respectively. The RMSE and d varied from 0.36?to?0.63?cm and 0.77 to 0.89 respectively when ET0 computed from actual air temperature was used in place of pan evaporation, where as when ET0 computed from forecast air temperature data was used, the corresponding values were 0.35–0.64?cm and 0.68–0.85 respectively for the four soil layers. There was a tendency of the models to underestimate when the computed ET0 was used as input in place of pan evaporation. In general, performance of the models were better at lower depths.     

Simple Equation to Estimate Reference Evapotranspiration from Evaporation Pans Surrounded by Fallow Soil

Reliable estimates of reference evapotranspiration (ET0) are key elements for efficient water resource management, and estimating ET0, based on “Class ‘A’ pan evaporation” data is common in arid climates. A pan coefficient (Kp), which depends on the distance (or fetch) of green vegetation or fallow soil around the pan (F), wind run (U), and relative humidity (RH), is used to convert from pan evaporation to ET0. Several researchers have developed models for estimating Kp values for pans surrounded by green vegetated fetch, but there is only one equation to estimate Kp values for dry fetch conditions. The equation is complex, so the objective of this research was to develop a new simple equation to estimate Kp under fallow soil fetch conditions. The new Kp equation and the more complex equation were compared with tabular values published by the United Nations Food and Agriculture Organization. The new equation performed slightly better at matching the tabular Kp values than the complex equation. The equation derivation and evaluation are presented.     

Simplified Estimation of Reference Evapotranspiration from Pan Evaporation Data in California

Evaporation pan (Ep) data are often used to estimate reference evapotranspiration (ET0) for use in water resource planning and irrigation scheduling. This paper reviews equations to estimate ET0 from Ep and provides a simpler method to make this conversion for arid climatic conditions like in California. The new method accounts for fetch differences by first adjusting the Ep rates to values expected for 100?m of grass fetch. Then it relies on an empirical relationship between ET0 and the adjusted Ep to determine Kp values; thus, eliminating the need for relative humidity and wind speed data that are often unavailable. The method is conceptually simpler, easier to code into computer applications, and within California, it gave better results than methods based on relative humidity and wind speed. However, the method might require calibration in more humid or windier climates.     

Soil Moisture Measurements: Comparison of Instrumentation Performances

It has long been recognized that reliable, robust, and automated instrumentation for the measurement of soil moisture content can be extremely useful, if not essential, in hydrological, environmental, and agricultural applications. A number of automated techniques for point measurement of soil water content have been developed to operational level over the past few decades. While each of those techniques has been individually calibrated by the gravimetric method, typically under laboratory conditions, there have been few studies that made a direct comparison between the various techniques, particularly under field conditions. This paper compares ECH2O probes, EC-5 (both sensors based on capacitance measurements, developed by Decagon Devices) and time domain reflectometer sensors (CS616 Campbell Scientific Water Content Reflectometer), with gravimetric data and with each other, under field conditions. Data were collected during two field experiments characterized by different soils and a wide range of soil moistures, resulting from irrigation/drying cycle. Results show that all the tested probes give acceptable results after being calibrated in the field. The capacitive sensors can be used in each type of soil with the same calibration equation, independently from depth, with root mean square error (RMSE) ranging between 2.5 and 3.6%. Time Domain Reflectometry probes showed a dependence on depth but a lower RMSE (1.6%).     

Prediction of Soil Composition from CPT Data Using General Regression Neural Network

Soil type is typically inferred from the information collected during a cone penetration test (CPT) using one of the many available soil classification methods. In this study, a general regression neural network (GRNN) was developed for predicting soil composition from CPT data. Measured values of cone resistance and sleeve friction obtained from CPT soundings, together with grain-size distribution results of soil samples retrieved from adjacent standard penetration test boreholes, were used to train and test the network. The trained GRNN model was tested by presenting it with new, previously unseen CPT data, and the model predictions were compared with the reference particle-size distribution and the results of two existing CPT soil classification methods. The profiles of soil composition estimated by the GRNN generally compare very well with the actual grain-size distribution profiles, and overall the neural network had an 86% success rate at classifying soils as coarse grained or fine grained.