Journal of Irrigation and Drainage Engineering

Optimal utilization of limited water resources is important due to the continuously increasing demand for it. This study was aimed at devising a model and a preference index for allocating limited land and water resources at the Mirpurkhas subdivision of the Jamrao irrigation scheme in Sindh, Pakistan. The deterministic linear programming (DLP) model formulated was set to the minimum and maximum area constraints and applied for different scenarios (at levels of 100, 70, 60, and 50% of existing water supply), in an effort to find the optimum conditions of land area allocation. Emphasis was given to the cultivation of vegetable, banana, and oilseed crops during times of shortages of water. Upon optimization with the DLP model, the proposed preference index was found to be an effective guide in equitable distribution among the competing command areas through the resulting competitive and conflict-free allocating of the resources. The model cum index that was developed is proposed to be adopted while formulating the policy regarding land and water resources allocation during reduced canal flows at the Mirpurkhas subdivision of the Jamrao irrigation scheme at Sindh, Pakistan.

Two regionalized models for the distributed estimation of daily reference evapotranspiration, the temperature-based Hargreaves (HE) and the radiation-based Makkink (MK) equations, are applied in Southern Italy during the years 2007 and 2008. Spatially distributed meteorological inputs, such as air temperature and incoming solar radiation, were derived from geostatistical interpolation of ground data and from the Land Surface Analysis Satellite Application Facility (LSA-SAF) surface radiation product, respectively. Comparison of the latter with 83,394 daily measurements provided by 128 weather stations shows a not negligible seasonal error in daily solar radiation that is corrected by means of a periodic equation. A preliminary local calibration of the MK coefficient highlights its strong dependency on the interactions between moist winds from the Atlantic Ocean and orographic obstructions, leading to two western and eastern subzones. Hence, a regionalization of the MK-adjusted coefficient was performed following a procedure similar to the one already used by the authors in a previous work for the HE coefficient. Application of both regionalized models and their comparison with Penman-Monteith estimates derived from the same stations leads to average whole-year absolute errors of approximately $0.5\mathrm{mm}{\mathrm{d}}^{-1}$, further showing the great potential of the MK method in terms of informative content and less dependence on the site density of a ground-based monitoring network. Overall, discussing pros and cons of both regionalized models, it is shown that their integrated use in southern Italy is possible and advisable.

Thick-walled concrete orifices are widely used to control outflow rates from stormwater detention basins. There are limited data on stage-discharge relationships for such orifices, particularly for low head and partially full conditions that are relevant to extended detention applications for water quality control. This paper presents laboratory and field testing of stage-discharge relationships for concrete orifices under such conditions. Steady-state and transient drainage curve experiments were conducted in a horizontal flume, and a detention basin with a multistage concrete outlet structure was instrumented to collect drawdown data in the field. For fully submerged conditions, the orifice equation with single-valued discharge coefficient ($C_d$) does not fit the experimental data, and a model is proposed with $C_d$ increasing nonlinearly from $\sim 0.55$ to $\sim 0.65$ as submergence increases. For partially submerged conditions, an equivalent rectangular weir model provided good fit to the laboratory and field data. The effect of four different orifice models on basin drawdown time was investigated through simulation of a series of synthetic basin and outlet structure configurations. The details of how partially full orifice flow is modeled are important to simulated basin drawdown times; in particular, both linearly interpolated tabular stage-discharge data and other widely-used detention basin software can significantly underestimate drawdown times.

In this study, smart irrigation controllers were targeted toward single-family potable water customers in Orange County, Florida with excessive landscape irrigation patterns. Out of five treatments, four treatments received either an evapotranspiration controller (ET) or soil moisture sensor (SMS) controller, installed by a contractor, but two technology treatments included an educational program (+Pgm) component. The fifth treatment was a comparison treatment (MO) with no interventions to their normal irrigation scheduling methods. After 22 months of evaluation, both +Pgm treatments reduced irrigation application, ranging from 21 to 52%. However, none of the treatments performed with high efficiency in all seasons. Only a few treatments were able to maintain irrigation totals within a gross irrigation requirement (GIR) range from 60 to 100% efficiency. The technology treatments that participated in the customized educational program were more likely to achieve additional reductions in irrigation application compared with the technology only treatments. Additionally, there was higher consistency in efficient irrigation application by the SMS technology than the ET technology. The SMS+Pgm was the most efficient regardless of soil type with weekly irrigation for SMS+Pgm averaging 11–13 mm per week in the flatwoods locations and water savings of 34–52% across all seasons. In the sand locations, weekly irrigation averaged 16–22 mm for ET+Pgm, SMS, and SMS+Pgm, resulting in very little difference among these treatments. Dry season water savings for these three treatments was 4–35% with increased savings of 21–43% in the wet seasons. The ET controllers may require technological advancement combined with additional educational opportunities to achieve the same consistency of water savings as the SMS. Additional irrigation reduction is possible with both controllers tested here in most cases and may be achieved with education or additional customized programming and setup.

An experiment has been conducted to investigate the salt evolution process in soil and the response of crops to continuous irrigation with saline water under no artificial drainage from 2006 to 2013. A total of five salinity levels of saline water included 1.3, 3.4, 7.1, 10.6, and $14.1\mathrm{dS}/\mathrm{m}$, denoted as F1, F2, F3, F4, and F5. Results indicate that salt accumulation was significantly accelerated with the increased ratio of irrigation amount to precipitation (I/P), which was caused by higher annual irrigation times and irrigation quota, but soil salinity was reduced with the decline of I/P. Compared with initial soil salinity in 2006, final soil salinity in 2013 was decreased by 8.7 and 10.1% in the F1 and F2 treatments, but was increased by 7.3, 24.5, and 65.2% in the F3, F4, and F5 treatments. The peak salt values in the soil profile demonstrated a tendency to move up with the increasing salinity of irrigation water, suggesting that salt accumulated more readily in higher salinity treatments. Cotton yield in salinity treatments was close to that of fresh water (F1) when irrigation water salinity was below $7.1\mathrm{dS}/\mathrm{m}$, but reduced when irrigation water salinity was over $7.1\mathrm{dS}/\mathrm{m}$. The salt tolerance of forage rye was lower than that of cotton, and the relative forage rye yield dropped as soil salinity increased over the experimental years. Therefore, irrigation water salinity must be lower than $7.1\mathrm{dS}/\mathrm{m}$ in cotton monoculture to keep the cotton yield close to that of freshwater treatment and reduce soil salt accumulation.

Two new mathematical forms of the nonlinear Muskingum model called NL4 and NL5, involving four and five parameters, respectively, can be used in river flood routing. The accuracy of the estimation of the Muskingum model parameters is essential for flood routing. This paper proposes a novel hybrid algorithm, based on the shuffled frog leaping algorithm (SFLA) and Nelder-Mead simplex (NMS), for the estimation of parameters of two new nonlinear Muskingum models. The proposed methodology is applied by considering minimization of the sum of the square deviation (SSD) between observed and routed outflows in (1) experimental, (2) real, and (3) multimodal examples. Results show that the SSD is 0.91, 3.97, and 4.44% smaller (better) than pertinent values obtained by the genetic algorithm-generalized reduced gradient (GA-GRG) method in experimental, real, and multimodal examples, respectively.

Rapid population increases, along with water resources deficiency, have made agricultural experts and researchers use various management techniques to improve water productivity. The term, “more crop per drop” has since came to the center of attention. One of the primary objectives in Iranian national agricultural policies is providing food security, which can be reached via this approach. There is a crucial need for improvements in production of rain-fed agriculture since there are huge rainfed cultivated areas that suffer from low yields. Hence, in this research, supplemental irrigation and sowing dates, which are two effective factors on productivity of rainfed lentils in Qazvin Plain, are investigated. The treatments included two sowing dates and four irrigation levels. The sowing dates were April 4 and April 14, and the irrigation treatments were: no irrigation, single irrigation at seedling stage, single irrigation at pod filling stage, and double irrigation at both of these stages. A factorial experiment in a completely randomized block design with three replications was conducted in agricultural research field of Imam Khomeini International University for two cropping seasons in 2011–2012. The results showed that the effects of the two factors on grain yield and biomass were highly significant at the 1% level, both separately and simultaneously. The sowing date of April 4 led to a rise in yield components. Although the double irrigation treatment with $\mathrm{1,329.4}\mathrm{kg}/\mathrm{ha}$ had the most grain yield, the single irrigation treatment at seedling stage with the irrigation water productivity of $1.878\mathrm{kg}/{\mathrm{m}}^3$ was the best approach when water productivity was considered. In summary, the results indicated that single irrigation at the seedling stage had better water productivity than the double irrigation treatment. This conclusion is consistent with the production functions and other research results.

This paper provides direct solution or iteration procedures to the following four types of submerged flow problems for rectangular sluice gates: (1) find discharge per unit width ($q$) for given gate opening ($a$), gate upstream water depth ($H_1$), and tailwater depth ($y_t$); (2) find $H_1$ for given $q$, $a$, and $y_t$; (3) find $y_t$ for given $q$, $a$, and $H_1$; and (4) find $a$ for given $q$, $H_1$, and $y_t$. The paper also provides procedures to distinguish flow state (free flow or submerged flow) for given values of three of the four variables ($q$, $a$, $H_1$, and $y_t$).