Journal of Irrigation and Drainage Engineering

Estimation of evapotranspiration (ET) from any given crop is essential for agricultural water consumption analyses, hydrologic modeling, understanding vegetation response to climatic changes, and related studies. Even though it is a simplification of the complex physiological and surface energy balance relationships in accurately estimating ET, crop coefficient ($K_c$)-based estimation of crop ET is one of the widely used approaches. This study developed and evaluated crop-specific (maize and soybean) $K_c$ versus normalized difference vegetation index (NDVI) relationships using satellite imagery data and observed crop ET fluxes. These models were used to estimate spatiotemporal $K_c$ of maize and soybean using multiplatform satellite imagery to aid in computation of crop ET across these scales. Crop ET was characterized spatially (across the entire Great Plains) and temporally (1982–2013) and direction and magnitudes of trends were quantified. The study area comprises of 9 states and 834 counties, representing a total land area of $\mathrm{2,307,410}{\mathrm{km}}^2$, which is approximately 30% of the terrestrial area of the United States. The coefficient of determination ($R^2$), Nash-Sutcliffe modeling efficiency (NSE), and root mean square difference (RMSD) for $K_c$-NDVI models were 0.93, 87.5%, and 0.172, respectively, for maize and 0.76, 75%, and 0.20 for soybean, respectively, which denotes acceptable accuracy. Monthly and growing season maize and soybean ET was computed on a county basis for the study period using the developed monthly $K_c$ values and reference ET, which was determined across 800 sites in the region. Maize ET in the region varied from 242 mm in Park County, Wyoming, to 942 mm in San Jacinto County, Texas. Soybean ET ranged from a minimum of 367 mm in Baca County, Colorado, to a maximum of 753 mm in Creek County, Oklahoma. The regional average magnitude of growing season maize and soybean ET was 651 and 564 mm, respectively. Spatial and temporal variability and trends in county-scale monthly and growing season maize and soybean ET were investigated for the period 1982 to 2013. For the majority of the maize and soybean growing counties, increasing trends in crop ET were detected, despite decreasing trends in reference ET. The significant positive trends in maize ET over the region ranged from 1.48 to $3.86\mathrm{mm}{\text{year}}^{-1}$, with an average of $2.65\mathrm{mm}{\text{year}}^{-1}$. For soybean, the significant positive trends varied from 0.88 to $4.13\mathrm{mm}{\text{year}}^{-1}$, with an average of $2.1\mathrm{mm}{\text{year}}^{-1}$. The analyses presented in this study inspire the use of satellite-derived indices to monitor crop development and water use to evaluate regional magnitudes of spatial and temporal ET. Furthermore, the spatial and temporal trend analysis for county-scale crop ET can be instrumental to make informed assessments, decisions, and forecasts about agroecosystem water resources management policy in the Great Plains region by state and federal agencies, producers, and other water resources associated professionals.

Cover crops are incorporated into row crop production systems as rotational crops because of their potential contributions to soil and water conservation. However, extremely limited data and information exist in the literature in terms of their water use (i.e., evapotranspiration) rates, especially in the midwestern United States. The primary objective of this research study was to investigate the impact of cover-crop mixtures on soil-water dynamics and measure, analyze, and compare the magnitude and trend of weekly, monthly, and seasonal evapotranspiration (ET) rates from different surface covers, including (1) mixture of cover crops (CC) without maize residue, (2) bare soil, (3) cover crops with maize residue (SCCC), and (4) only seed maize residue (SC) without cover crops. Extensive field research was conducted in three cover-crop growing seasons (2012–2013, 2013–2014, and 2014–2015) in three center pivot-irrigated large-scale seed maize cover-crop rotation production fields (F1, F2, and F3) near Beaver Crossing, Nebraska. The ${\mathrm{ET}}_a$ during 2012–2013 (dry year) was lower in the CC treatment than bare soil and was significantly higher ($P<0.05$) in the 2013–2014 and 2014–2015 growing seasons (above average years). In 2013–2014 and 2014–2015, SCCC ${\mathrm{ET}}_a$ was significantly lower ($P<0.05$) than those in the CC only treatment. Cumulative ${\mathrm{ET}}_a$ for CC only and SCCC treatments for the 2012–2013 cover-crop growing season was 135 and 142 mm, respectively, while it was 267 and 237 mm, respectively, in the 2013–2014 season, and 417 and 381 mm, respectively, in the 2014–2015. The SCCC and SC only treatments were compared to quantify the potential impact of cover crops on water use. While there were cases when SCCC treatment had lower ${\mathrm{ET}}_a$ values than SC only treatment, when the values from all three fields (F1, F2, and F3) are averaged, results indicated that cover crops did not have positive or negative impact on reducing or increasing evaporative losses when incorporated as a rotational crop in the soil, climate, and management conditions presented in this research study. For example, in the 2012–2013 season the three field average ${\mathrm{ET}}_a$ values for the SCCC and SC only were essentially the same (142 and 145 mm, respectively); in the 2013–2014 season they were exactly the same (237 mm); and in the 2014–2015 season they were 381 and 367 mm, respectively [SCCC treatment had significantly greater ${\mathrm{ET}}_a$ (14 mm) than the SC only treatment], indicating that the cover crops did not have impact in reducing evaporative losses. Substantial interseasonal variations were observed in terms of impact of the same surface covers on ${\mathrm{ET}}_a$ in the field. Soil-water storage (SWS) was significantly lower ($P<0.05$) in CC treatment than the bare soil during the 2013–2014 and 2014–2015 seasons and significantly higher in 2012–2013. Surface cover’s influence on SWS for the next season’s crop and ET rates in a maize cover-crop rotation system can vary substantially, depending on the current year’s climatic conditions, especially air temperature (influence on evaporative losses), precipitation (influence on soil-water availability), growth, and water use of the cover crops.

Cover crops have been gaining attraction in agriculture as rotational crops because of their potential benefits in various soil characteristics and soil-water functions. The knowledge about cover-crop water use in terms of examining the water availability for the next field crop is very important for developing and implementing sustainable agricultural management strategies. Crop coefficients for estimating water use for cover crops are among one of the least available coefficients of any cropping systems. In this study single (normal) and basal grass-reference ($K_{co}$ and $K_{\text{cbo}}$) and alfalfa-reference ($K_{cr}$ and $K_{\text{cbr}}$) crop coefficients were developed as a function of cumulative growing degree days (CGDD) for (1) cover-crop mixes (CC) only, (2) seed maize cover-crop rotation (SCCC), (3) seed maize residue without cover crop (SC), and (4) bare soil. The research was conducted for three cover-crop growing seasons (2012–2013, 2013–2014, and 2014–2015) on three center pivot–irrigated seed maize cover-crop rotation fields (F1, F2, and F3) near Beaver Crossing, Nebraska. Single and basal crop coefficients were developed from the ${\mathrm{ET}}_a$ data and estimated grass-reference and alfalfa-reference evapotranspiration (${\mathrm{ET}}_0$ and ${\mathrm{ET}}_r$). The $K_{co}$ and $K_{cr}$ values exhibited interannual variability for the same months and treatments between the years. The $K_{co}$ and $K_{cr}$ varied from 0.0 to 1.8 and 0.0 to 1.2, respectively, in the 2012–2013 season; from 0.0 to 2.3 and 0.0 to 1.7, respectively, in the 2013–2014 season; and from 0.0 to 2.3 and 0.0 to 1.7 in the 2014–2015 cover-crop growing season. On average, the cover crop $K_{\text{cbo}}$ and $K_{\text{cbr}}$ values fluctuated between 0.0 to 1.6 and 0.0 to 1.5, respectively. In general, depending on the treatment, maximum $K_c$ and $K_{cb}$ values occurred at CGDD between approximately 980 and 1,300°C (end of October), which then gradually decreased in the winter months. Minimum $K_c$ values usually occurred at CGDD of approximately 200°C. The $K_c$ and $K_{cb}$ curves presented in this study are among first cover crop $K_c$ values and can be used to estimate cover crop ${\mathrm{ET}}_a$ for particular cover-crop mixtures that are similar to those used in this research and grown under climatic conditions similar to the research area.

The mesh-free method, moving particle semi-implicit method (MPS), has become a useful numerical tool in simulating free-surface flows. Broad-crested weirs are considered as a common hydraulic structure and have been experimentally investigated in the literature. As the free-surface flow, the broad-crested weir flow is investigated from the numerical perspective by using MPS in this study. The numerical method is first validated by a broad-crested weir flow and subsequently applied to simulate various configurations of broad-crested weirs. In the simulations, a set of flow discharges and upstream face slopes are investigated. The flow characteristics, including free-surface profiles, locations of the critical depth, velocity distributions, and the discharge coefficient, are studied. The numerical results show good agreement with experimental measurements, and the method is capable of being extended to further investigate alternative flow configurations.

The expansion of irrigated agriculture is required to feed the ever-increasing world population. On the other hand, the expansion of irrigated agriculture causes waterlogging and salinization problems in semiarid and arid regions where more than three-fourths of the world’s population reside. These problems of irrigated agriculture have direct and indirect effects on crop growth and yield. When waterlogging and salinization occur together, the harm to plant growth and yield is more serious and usually the decline in the yield is much higher at the higher salinity levels. An overview of the various aspects of waterlogging and salinity problems and their impact on the sustainability of irrigated agriculture is provided in this paper. Past research is grouped into the mechanism of waterlogging and salinity, plant response to waterlogging and salinity, and the effects of salinity and waterlogging on crop yield. Conclusions are presented that could be useful to the stakeholders.

The development of irrigated agriculture causes waterlogging and salinization problems in agricultural areas due to intensive seepage into the groundwater. These problems can be controlled by either implementing preventive measures or by adopting remedial measures. This paper provides an overview of various measures and their suitability and limitations for the management of waterlogging and salinity problems. The role of drainage systems in controlling the twin problems is provided. The increased conjunctive use of groundwater in mitigating the twin problems is discussed. The lining of canal networks is also presented. Finally, the role of biodrainage in controlling the aforementioned problems and some conclusions are presented.

Quantification and analysis of field variability are important initial steps in delineating potential variable-rate irrigation (VRI) management zones within an agricultural field. This study seeks to utilize variability in soil physical and chemical properties and in field elevation across a 27-ha field at the Alberta Irrigation Technology Centre (AITC) in southern Alberta, Canada, to define site-specific management zones. All geospatial data were collected during the 2013 and 2014 growing seasons. A stepwise multivariate regression approach was used to investigate how multiple measured parameters affect wheat yield. An unsupervised clustering algorithm, fuzzy c-means, was used to delineate the irrigation management zones. Fuzziness performance index (FPI) and normalized classification entropy (NCE) were used as verification criteria to determine the optimal number of management zones. Results revealed that soil electrical conductivity (EC) and field elevation were better suited for management zone delineation. Three management zones were identified based on the verification criteria using EC and field elevation variables. Measured crop yield differences corresponding to the three noncontiguous management zones were significant. The study area was categorized as low, medium, and high productive zones. The maximum wheat yield ($4.80\mathrm{t}{\mathrm{ha}}^{-1}$) was attained in the high-productivity zone; the lowest ($2.22\mathrm{t}{\mathrm{ha}}^{-1}$), in the low-productivity zone.

For many large irrigation systems, distributing water equitably is a stated management objective. Canal operations plans specify which canal to operate at what discharge for each irrigation interval to achieve the stated objective. In this study, a function of the Gini index is incorporated in to an integer program that can develop a canal operations plan. In contrast with earlier canal operations planners that minimize inequity, the operations planner presented herein does not constrain the discharge in a canal to a binary integer. Rather, the user can define an allocation cost function that in turn defines the preferred operational range of discharge over which any canal should be operated for any interval. The operations planner can also be modified to permit spillages. The model is applied to a secondary canal in Pakistan, and the sensitivity of the results to operational range and permissible spillage are explored. An engineering application of the model is presented.

This study revisits the stability of hydromechanical gates for upstream water surface regulation, also known as AMIL gates. AMIL gates are used in irrigation canals, where they are often installed in series. From the regulation perspective, instabilities are undesired because they generate waves and fluctuations in the discharge. A mathematical model for an AMIL gate is described as a nonlinear dynamical system, which permits analyzing the dynamic interaction between the local water level and the gate position. The feedback effect of the gate on the water level is introduced by considering a storage volume of length $l$. In the derived model, waves are simplified to fluctuations of the flat water surface of the storage volume. Although previous studies used the same model, none has clarified the sensitivity of the model to the parameter $l$. The role of this parameter is investigated and it is calibrated with experimental measurements. The precision of the regulation is described by the decrement, the range of the water level around the target level. Based on the mathematical model, a relationship for calibration of the gate and precision of regulation is presented. The subsequent stability analysis of the dynamical system focuses on five control parameters and sheds light on their influence on the gate behavior. Hopf bifurcations are identified, which separate stable equilibrium solutions from stable periodic solutions. Further work might consider the implications of the periodic solutions on gates that work in series, as well as envision the innovative use of such gates outside of the domain of irrigation canals to obtain dynamic environmental flows in hydropower systems.

Due to increased occurrence and intensity of agricultural droughts in humid Mediterranean regions, monitored irrigation is becoming an increasingly inevitable element of agricultural practice. To determine the impact of different irrigation regimes on olive tree (Olea europaea L.) growth and crop yield, and of the olive oil production and biophenol content, a 3-year study was conducted in an olive grove located in a relatively humid region of southwestern Slovenia. The mean olive production from trees under full irrigation (replacement of 100% crop evapotranspiration) was significantly higher than those that were only rain fed or were under deficit irrigation (replacement of 33 and 66% crop evapotranspiration). There were no significant differences in total biophenol contents of the olive oil across these irrigation treatments. These irrigation effects can be explained according to the levels of precipitation throughout the growing season. Despite the positive effects of rainfall on these parameters, the mean olive oil yield of the rain-fed olives was about 30% lower than that for the deficit irrigation treatments.

Hydrological processes such as evaporation and evapotranspiration (ET) are affected by air humidity. Air humidity is commonly expressed as relative humidity (RH) or dew point temperature ($T_{\text{dew}}$) and is required for the determination of evaporation from water or soil surfaces and ET from cropped areas. However, the availability of humidity data is sometimes an issue. In cases in which RH data are not available, air humidity on a daily basis can be estimated by using daily maximum and minimum temperatures along with the dew point temperature. Guidelines from an international organization recommend the use of a dew point temperature slightly less than the daily minimum temperature for daily computations, when its measurements are not available. In this study, the daily average dew point temperature ($T_{{\mathrm{dew}}_{\mathrm{mean}}}$) was taken as $k°\mathrm{C}$ less than the daily minimum temperature. Thus, daily RH data (maximum, minimum, and mean RH) were generated from daily maximum and minimum temperatures for Roorkee Station (India) during 2012–2016. Four different values of $k$ ($k=0$, 1, 2, 3) were used for determining the actual vapor pressure values used in RH estimation. Daily RH values determined using different values of $k$ were compared with observed RH data. It was observed that for the nonsummer months, having an average value of daily mean RH greater than 60% (January–March and July–December), $k=0$ resulted in minimum error in RH estimation. However, during the summer months, having an average value of daily mean RH less than 60% (April–June), $k=3$ provided relatively better estimates of RH. During the summer months, large errors occurred in the estimation of maximum and minimum RH values using this approach; hence, mean RH values that are relatively better estimated during these periods should be used for hydrological applications. Further, linear $T_{\text{dew}}$-RH relationships (with and without parabolic correction) have been assessed to determine daily $T_{{\mathrm{dew}}_{\mathrm{mean}}}$ values. These relationships have been found to provide more accurate estimates of $T_{{\mathrm{dew}}_{\mathrm{mean}}}$ and actual vapor pressure on a daily basis than the FAO-56 vapor pressure models when only daily ${\mathrm{RH}}_{\text{mean}}$ data are available (instead of ${\mathrm{RH}}_{\text{max}}$ and ${\mathrm{RH}}_{\text{min}}$ data) along with daily temperature data.

In the agricultural irrigation system, agricultural water availability and demand are significantly affected by seasonal variations. Additionally, agricultural land use in arid regions largely depends on water availability rather than on arable land resources only. Thus, in this study, a two-stage stochastic chance-constrained fractional programming (TSCFP) model is developed to address the agricultural cultivation–scale problem under uncertainty. In the developed model, techniques of chance-constrained programming (CCP) and two-stage stochastic programming (TSP) are jointly incorporated into the linear fractional programming (LFP) optimization framework. The model balances the conflicting objectives of two aspects by transforming the problem into a ratio-based problem that reflects land-use efficiency and also analyzes the trade-offs among efficiency, constraint violations, and policy scenarios. The model is applied to determine the agricultural cultivation scale of Linze County in Gansu Province of northwest China, where managers must consider the conflicting objectives of economic benefit and irrigated crop area under stochastic inputs. By providing four scenarios of preregulated irrigation targets, optimal solutions are obtained. The appropriate agricultural cultivation scale in Linze County for the current circumstances are 10,961, 13,171, 15,490, and 16,855 ha under four scenarios. Therefore, the results offer decision support for decision makers to obtain the optimal agricultural cultivation scale under different predetermined irrigation targets and different probabilities of violation.

Conjugate flow depth is of high practical importance and should be accurately determined in hydraulic design projects. Quantifying the hydraulic jump phenomenon is an application of specific force relation. This relation has a simple analytical solution only for the horizontal rectangular channels. The power-law section is very versatile and allows suitable modeling for both artificial and natural channels. These channels are used in irrigation and drainage projects. No explicit solution is available in the technical literature for the conjugate depth in general power-law channels for the exponent parameter $1\le n\le 2$. For this channel, the conjugate depth is currently obtained by trial and error procedures. Numerical solutions of the conjugate depth problems can always be established, though such numerical solutions are devoid of any physical interpretation. In contrast, an explicit solution involves all the input variables in functional form; and thus the dependence of the conjugate flow depth on each input variable can be interpreted. This study presents accurate explicit solutions that can be used to calculate the conjugate depths of open channels with power-law sections. If the initial depth of the hydraulic jump is known, the sequent depth can be determined using the proposed solution with a maximum error less than 0.35%. Inversely, if sequent depth is known, the initial depth can be determined with a maximum error less than 0.55%. The generic results presented in this research for power-law channels can be applied to its special forms such as rectangular, triangular, and parabolic channels. The proposed direct solutions are general, simple, accurate, and useful for studying the power-law channels.

The end depth of a free overfall (also known as the brink depth) provides a good hint about how to measure discharge ($Q$). This technical note details two theoretical approaches for computing end depth ratio (EDR) and end depth discharge (EDD) relationships based on the equations of momentum and energy for inverted semicircular channel cross sections. Direct solutions of $Q$ from a known end depth are provided. Available experimental data and previous studies were used to verify the proposed relationships for both approaches.