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The water management of the Colorado River is at a tipping point. This paper describes water management strategies in the Mexican portion of the Colorado River Basin considering water scarcity scenarios. A water allocation model was constructed representing current and future water demands and supply. The Colorado River system in Mexican territory is used as a case study, and all its water demands are characterized [Irrigation District Rio Colorado (DR-014), Mexicali, San Luis Rio Colorado, Tecate, Tijuana-Rosarito, and Ensenada]. Individual strategies were run by subsystem and then their impact was analyzed systemwide. Performance criteria and a performance-based sustainability index were evaluated to identify water stressors and management strategies to improve water supply for agricultural, urban, and environmental users. Analysis of results shows that the irrigation district (DR-014) is the most affected user due to water cuts because it has the lowest priority and, thus, any reduction in Colorado River allocations affects them directly. A range of water management strategies was investigated, including a no-action scenario. The current system depends on the long-term aquifer overdraft to supply water demand. The reduction of the cultivated area was the strategy that increased the sustainability index the most for DR-014. Agricultural to urban transfers, water use efficiency, wastewater reuse, and desalination are prime possibilities to improve the current water supply in the coastal zone (Tijuana, Rosarito, Ensenada). This research shows the spectrum of possible outcomes that could be expected, ranging from systemwide effects of inaction to the implementation of a portfolio of water management strategies. [ABSTRACT FROM AUTHOR]

Basin-wide cooperation is an approach to resolve water disputes and improve the resilience of transboundary river basins to extreme droughts under climate change. However, the effectiveness of cooperation among various stakeholders has disputes in moving from theoretical research to practical application. This paper aims at developing basin-wide water resources management strategies to improve cooperation effectiveness in the Lancang-Mekong River Basin (LMB). An interdisciplinary physically based integrated hydroeconomic water system model is developed for strategy evaluation, and is shown to have good performance in reproducing historical events. First of all, we find that agricultural benefits in downstream countries are primarily affected by hydrological conditions, without significant impacts from reservoir construction. Second, the cooperative action—three-phase emergency water supply—by upstream reservoirs discharge can alleviate the agricultural drought of downstream countries, and it is further improved by better spatial and temporal water reallocation among different stakeholders. Last but not least, we characterize the cooperation effectiveness under different hydrological conditions by two indicators (i.e., incremental benefit and cooperation efficiency). They show two opposite trends: from extremely high-flow years to extremely low-flow years, the incremental benefit brought by basin-wide cooperation increases by nearly six times, whereas the cooperation efficiency (measured by how many times benefits are gained by downstream from upstream unit loss) decreases by 80 percent. This study provides guidance and support for transboundary basin cooperation and sustainable management. [ABSTRACT FROM AUTHOR]

Currently, point measurement and remote sensing technique are two frequently used methods to study the spatial-temporal distribution and pattern of soil moisture. However, point measurement is known as cost-intensive and time-consuming, whereas remote sensing is limited in precision to describe spatial and temporal characteristics of soil moisture especially for deep layer soil. This study introduced a method to map farmland soil moisture using a distributed hydrological model (MOD CYCLE) combined with the kriging interpolation method (KIM) at the regional scale. Handan City in the North China Plain was chosen as the study area to verify the method. According to the result, there is a significant consistency relationships between observed soil moisture data collected, respectively, from 12 monitoring stations and simulated results in this paper. The maximum relative error coefficient is as low as 8.8%, and even the minimum correlation coefficient is more than 0.66, which shows a good reliability and feasibility of this method. Moreover, the authors also analyzed the spatial characteristics of the soil moisture and assessed the drought vulnerability in the study area based on the soil moisture distribution map. Meanwhile, this paper also summarized a series of suggestions that could cope with agricultural water scarcity and ensure the sustainable development of grain production in this study area. [ABSTRACT FROM AUTHOR]

Water markets represent a favorable means to reallocate water resources. With global changes in water consumption patterns and caps, water rights trading has become an appropriate method to reallocate water between agriculture and industry in water-rich regions. This paper analyzed the economic benefits of water trading in water-rich regions, with reference to a case study of southern China. Based on a regional input–output table, the economic benefits that water trading brings to the regional economy were quantified, including related economic benefits, indirect economic benefits, and cumulative economic benefits. The results showed that water trading yields significant economic benefits for the regional economy because of the accompanying technological and economic connections established among different sectors. This study provides a reference point for water rights trading policies in water-rich regions. [ABSTRACT FROM AUTHOR]

Water dependencies and agricultural expansion have led to a remarkable increase in water demand. Proper management of water supply and demand is a crucial challenge in planning for sustainable development. Because the prevailing water allocation system in developing countries is based on low tariffs, particularly in the agricultural sector, a robust accounting cannot be implemented. The objective of this paper is to investigate the economic value of a change from gravity to drip irrigation using groundwater resources. It is implemented in the Rafsanjan plain, in central Iran, where the irrigation practices lead to unsustainable use of groundwater. In this area, the allocator (water authority board) is a governmental agency that can receive funding from other governmental agencies to affect water use policies. Considering the benefits accrued to the allocator and farmers (benefit for all agricultural water uses), the optimal investment in converting gravity irrigation systems to drip irrigation is determined. An economic framework is proposed with two simulation models [Water Evaluation and Planning (WEAP) and Vensim] to evaluate the dynamics of the water use benefits. According to the results, with expenditures of $65 million/year over a 25-year horizon, the discounted benefit to allocator and farmers in the year 2011 would be $60.48 and $911.9 million, respectively. The framework outlined can provide a mechanism to allocate water in a more precise way as well as to determine the economic value of water in the agricultural sector. The proposed methodology can be applied to other geographic settings. [ABSTRACT FROM AUTHOR]

The agricultural sector is the main victim of drought and efficient water planning, and management is the best strategy to reduce drought pressures on this sector. One operational approach is the application of real-time models to help water managers decide on mitigation measures, such as deficient irrigation or reducing cropped areas using the new incoming information (for example, recorded inflows and precipitation). The present paper introduces a real-time modeling approach for optimal water allocation during a drought. The model includes two main components: forecasting and optimization modules. The forecasting module uses a recurrent neural network technique to forecast annual inflows that is updated as monthly climate and hydrological data are introduced to the model. The optimization module allocates water among the irrigation units and their crops by considering growing stage, sensitivity to water stress at different stages, available/forecasted water, and previous decisions about water release. The model was tested for the 1999 drought of the Zayandeh Rud irrigation system. Traditional operating procedures were shown to produce 42% loss whereas the proposed method would have reduced loss to 12%. [ABSTRACT FROM AUTHOR]

This paper evaluates the performances of two long-term prediction approaches for streamflow and riverine total dissolve solids (TDS) and compares their results with observed data and with short-term predicted values. The future values predicted by the first, long-term, prediction approach (Approach 1) depend on data corresponding to time steps prior to the prediction time step. The future values predicted by the second, long-term, prediction approach (Approach 2) depend on data comprised within the observational period. Each long-term prediction approach calculates streamflow and TDS over a 12-month period ranging from April through March (Scheme 1) and by agricultural water year (December through November, Scheme 2). Genetic programming (GP) is implemented for long-term prediction. Prediction is applied to the streamflow and TDS of the Karoon River in southwestern Iran. The long-term Approach 1 was found to be more accurate than the long-term Approach 2 judged by the values of several diagnostic statistics. The root mean square error (RMSE), correlation coefficient (R2), and Nash-Sutcliffe efficiency (E) statistics of long-term predictions of streamflow and TDS with Approach 1 are lower than those obtained with the long-term prediction Approach 2 for April-March and for the agricultural water-year predictions. It is concluded that prediction of the Karoon River's streamflow and TDS is best accomplished using GP in combination with the long-term prediction Approach 1. [ABSTRACT FROM AUTHOR]

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal. [ABSTRACT FROM AUTHOR]

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal. [ABSTRACT FROM AUTHOR]

This paper addresses the impact of climate change on the volume of inflow to a reservoir and the volume of downstream water demand by considering three climate change scenarios in an East Azerbaijan river basin. The HadCM3 model was used to estimate possible scenarios of temperature and rainfall for the period 2026-2039 under an emission scenario (A2). A hydrological model (IHACRES) was first calibrated for the basin; and then, a monthly time series of future temperatures and rainfall were entered into IHACRES. In addition, a 14-year time series of monthly runoff was simulated for 2026-2039. Modeling results indicated that the average long-term annual runoff volume decreased by 0.7% relative to the base period (1987-2000). However, by assuming a nonchanging cultivation area, the average long-term annual water demand volume for crops increased by 16%. Both simulation and optimization models of reservoir operation were used. The simulation of reservoir performance in the delivery of water demand was implemented according to the standard operating policy (SOP) and by using the water evaluation and planning (WEAP) model. The three aforementioned climate change scenarios were then introduced to the WEAP, and the reservoir performance indexes (reliability, vulnerability, and resiliency) were calculated. Results showed that indexes would change in the future relative to the base. Next, for the optimal operation of the reservoir with a water supply for agricultural and environmental purposes, the minimization of total squared deficiencies in the allocation to these purposes was determined for each month and climate change scenario by the using LINGO Version 11.0 software [nonlinear programming (NLP)] algorithm. Results showed that the indexes would change. [ABSTRACT FROM AUTHOR]

Sprinkler irrigation is one of the advanced water-saving irrigation technologies, which has a significant effect for the development of agriculture. Sprinklers are designed to rotate in a circle. In practice, sprinklers can also be used to generate electric power by attaching a generator (dynamo) to its rotating head. Thus, the sprinklers can be converted into a turbine. Hydropower generation from a sprinkler system is theoretically discussed in textbooks on fluid mechanics. Therefore, the aim of this paper is to evaluate theoretical considerations and experimental results of hydropower generation from a sprinkler system. In this study, hydropower generation from a sprinkler system is simply tested with a practical application. The results indicate that a sprinkler irrigation device is capable for hydropower generation, i.e., electrical energy can be produced using sprinkler devices. Hence, the generated energy can be used for energy requirements (e.g., remote-controlled electric sprinkler, lighting, and other uses). If sprinkler devices are technological redesigned for both irrigation and power generation, they will generate low-cost electricity for energy requirements. Also, hydropower can be produced from sprinkler head series in center pivot sprinkler irrigation type. [ABSTRACT FROM AUTHOR]

Although Clément methodology is the most commonly used model for obtaining the design flow rate in on-demand irrigation networks, studies have shown that the Clément methodology does not always fit properly. A new stochastic methodology is proposed in this paper [random daily demand curve (RDDC)], in order to achieve a more accurate design flow. Results from Clément and the proposed RDDC methodology are compared to measured flow data in an on-demand irrigation network located in Tarazona de La Mancha (Albacete, Spain). RDDC is shown to have a better fit with the measured data compared to the Clément methodology, which underestimated the design flow by 35%–40%. RDDC methodology avoids the problem of using average opening hydrant probability, resulting in a better estimation of the network behavior. [ABSTRACT FROM AUTHOR]

The present approach adopted for suggesting alternative sustainable land use comprises taking into consideration present land use/land cover, soils, slope, and geomorphology. However, this paper deals with watershed management from a different perspective, by stressing the development of the watershed for agriculture activities; first, by implementing soil and water conservation works. The next step is to suggest alternative sustainable land uses based on soil and water conservation measures, groundwater prospects, land capability, and present land use/land cover in the area. The new approach is found to be very useful, as it takes into consideration basic factors necessary for the overall development and management of the watershed, and ensures stoppage of further degradation of the resources through appropriate soil conservation measures and land uses. [ABSTRACT FROM AUTHOR]

Due to the complex feedback cycle relationship among water resources, energy, and food, the agricultural water management mode and concept with a single object or two objects as the core can no longer meet the inherent requirements of the coordinated, sustained, and healthy development of economy and society. A two-stage multiobjective decision-making method based on a θ -dominance evolutionary algorithm (θ -DEA) is proposed for the optimization of agricultural systems with a water-energy-food nexus. First, the Pareto noninferior solution set of the model is obtained by the evolutionary algorithm based on θ -DEA. Then, the economic benefit and carbon emission of each solution are evaluated, and the optimal solution is selected by using the multiobjective decision-making method based on interval-valued hesitant fuzzy sets and the technique for order preference by similarity to ideal solution (TOPSIS). Through a case study of the Hetao Irrigation District (HID), the best optimization results are obtained when the carbon footprint is 4.16×109 kg CO2 eq, and the economic benefit is 8.09×109 yuan. The example shows that the model can well select the optimal allocation solution of water resources, which not only has high economic benefits and low pollution discharge but also meets the subjective wishes of decision-makers. The model has good practicability and stability. [ABSTRACT FROM AUTHOR]

The article presents a study on conjunctive management of surface and ground water resources using conflict resolution approach conducted by Hamid R. Safavi, and others. Topics discussed include impact of urbanization, increasing irrigation demand, and climate-change on the sustainability of water resources; need to efficiently utilize the agricultural water; and issues related to drought in arid and semiarid regions.

This paper aims at developing generalized higher-order synaptic neural (GHSN), i.e., generalized quadratic synaptic neural (GQSN) and generalized cubic synaptic neural (GCSN), reference evapotranspiration () models corresponding to various methods. The GHSN models (GHSNs) were developed using pooled climate data of different locations under four agroecological regions (semiarid, arid, subhumid, and humid) in India. The inputs for the development of GHSNs include daily climate data of minimum and maximum air temperatures, minimum and maximum relative humidity, wind speed, solar radiation, and pan evaporation with different combinations, and the target consists of estimated by one of the methods. Comparisons of developed GHSNs with the generalized first-order neural network, i.e., generalized linear synaptic neural (GLSN) models, were made to test the relative merits of one model over the other. Comparisons were also made between GHSNs and conventional methods. Based on the comparisons, it is concluded that the GHSNs along with GLSN models performed better than their conventional methods. Comparison of GHSNs and GLSN models among themselves reveals that the GQSN followed by GCSN models performed superior to the GLSN for almost all regions. The GHSNs corresponding to one of the methods ranked first and GHSNs corresponding to another method ranked second for all regions. For semiarid and arid regions, the GHSNs corresponding to one of the methods ranked third and for subhumid and humid regions the GHSNs corresponding to another method ranked third. Further, GHSNs were applied to model development and model testing locations to test the generalizing capability. The testing results suggest that the GQSN followed by GLSN models have a better generalizing capability than GCSN for almost all regions. [ABSTRACT FROM AUTHOR]

This study investigated rice irrigation water use in the University of Arkansas Rice Research Verification Program between the years of 2003 and 2012. Annual irrigation water use averaged 763 mm (30.0 in.) over 10 years. A significant (40%) water savings was found for rice grown using a zero-grade irrigation system [486 mm (19.1 in.)] compared to contour-levee or straight-levee systems. No differences in irrigation water use were found between contour-levee systems [814 mm (32.1 in.)] and straight-levee systems [822 mm (32.4 in.)]. Surface water irrigators used significantly less irrigation water [624 mm (24.6 in.)] than groundwater well fields [786 mm (30.7 in.)] and cost US $77.51 less per hectare (US$31.37 less per acre) to operate. Diesel pumps cost significantly more [$88.38=acre ($218.29=ha)] to operate than electric pumps [$58.69=acre (145.96=ha)] (P = 0.02), although fields that used diesel as an energy source averaged 152 mm (6.0 in.) less irrigation water than electric pumps. Arkansas producers implementing the multiple-inlet water delivery practice on contour-levee or straightlevee systems, irrespective of soil type, did not realize a water savings but did realize improved yields. These results are in contrast to those in earlier studies and suggest that an educational effort may be necessary if the field research-proven multiple-inlet water savings are to be realized. [ABSTRACT FROM AUTHOR]

A proposed stochastic dynamic programming (SDP) method with uncertainties in stream flow and water demand is developed to calculate optimal reservoir operation rules. The SDP method extends the classic SDP method that considers only one uncertainty in its operation rules. Time series of reservoir inflow and agricultural water demand for the Aydoghmoush Reservoir in eastern Azarbayejan, Iran, were obtained from meteorological data, available climate parameters, hydrologic data, and crop water demand. The application of the developed SDP with two uncertainties was evaluated with operation rules corresponding to four different scenarios, and optimal reservoir releases were determined for a drought year. Reservoir operation results were evaluated with different performance indices. This study's results demonstrate the advantage of considering uncertainties in reservoir inflow and water demand with the SDP method. The developed SDP method has general applicability under a range of climatic conditions, and the calculated operation rules cover the expected ranges of streamflow and water demand during the operating years. [ABSTRACT FROM AUTHOR]

Treated wastewater reuse (TWWR) offers a promising solution for farm crop and turf irrigation while also mitigating the environmental pressures resulting from effluent disposal in the environment. Most attention is devoted to ensuring that treatments are safe for human health. Nevertheless, the treatment may be incomplete or some pathogens resulting from biofilm development may be dispersed through the system. Therefore, end-users must take specific precautions and implement practices to prevent any unintended dispersal of contaminants transported by the water, in particular when using sprinkler irrigation practices. To generate data to evaluate dissemination hazards, and thereby facilitate risk calculation, a sprinkler was operated in (windy) field conditions and the wetted area drift as well as the transport of small particles downwind was measured within a perimeter 4 times the sprinkler range. The volumes collected at such distances on the ground and along the wind axis remained below 0.5 mLm-2 h-1, and below 4 mLh-1 perm² of vertical section, for winds of 5 ms-1, and below 0.25 and 1.4 mLh-1 perm² of vertical section for winds of 3 ms-1. The measurement method, based on the use of fluorescent dye, is proposed along with an empirical model that can be used to estimate the volumes of potentially contaminated water that can escape from the wetted zone under wind influence for the specific sprinkler used. [ABSTRACT FROM AUTHOR]

The effective scheduling of irrigation requires knowledge of a crop's consumptive water use according to its metabolic activities. Conversely, to know a crop's consumptive water use, one must know its exact evapotranspiration (ET) rate. Although the United Nations' Food and Agricultural Organization (FAO) has recommended using the standard Penman-Monteith method to determine crop ET (ETcrop), the method's intricacies render it impractical to use in the field in predicting agricultural and irrigation requirement-based water needs. The present study investigated the use of a new approach, extreme learning machines (ELMs), for estimating ETcrop using climatic variables such as temperature, relative humidity, rainfall, sunshine hours, and wind speed. ELM is a single, hidden layer, feed-forward network that provides a unified learning platform with widespread types of feature mappings. It can also be applied in regression. This study compares results obtained using the standard Penman-Monteith method, ELM, artificial neural networks (ANNs), genetic programming (GP), and support vector machines (SVMs). Results suggest that ELM can predict ET more quickly and accurately than all other techniques tested. An ELM with sigmoid transfer function predicted ET with greater accuracy than a hard limit transfer function. [ABSTRACT FROM AUTHOR]

A biobjective programming model is developed with fuzzy inputs in response to the complexity of conflicting objectives and uncertainties in irrigation water allocation systems. The model is capable of increasing agricultural water productivity and meanwhile reducing irrigation water shortage, compromising the concerns of both agricultural decision makers and farmers. Moreover, the developed model adequately considers the fuzzy uncertainties in parameters, constraints, and objective functions. The potential of the developed model is shown by applying to a real case study in northwest China. Results show alternative decisions for irrigation water allocation under different flow levels, and indicate that the effectiveness of the trading program is explicitly affected by uncertainties expressed as fuzziness. Comparison with a commonly used model for irrigation water allocation demonstrates the feasibility and applicability of the developed model, which is helpful for the development of water-saving high-efficiency agriculture. [ABSTRACT FROM AUTHOR]

This study proposes a factorial two-stage irrigation system optimization model (FTIM) for supporting agricultural irrigation water-resource management under uncertainty. The FTIM incorporates fractional factorial design, two-stage stochastic programming (TSP), interval linear programming (ILP), and interval probability and is applied to agricultural water allocation. The FTIM can take full advantage of conventional two-stage optimization approaches to tackle uncertainties presented as intervals, to investigate potential interactions among input parameters and their influences on system performance, and to enhance applicability to dual uncertainties expressed as interval probabilities. The proposed FTIM approach is for the first time applied to a hypothetical case study of water resource allocation in an agricultural irrigation problem. The results indicate that the effects of parameters on the objective function are evaluated quantitatively, which can help decision makers screen out significant parameters, analyze their interactions in model response, and identify possible schemes with maximized net system benefit. Especially for the study problem, the most positive significant factor affecting total net benefits is water quality at a medium flow; penalties resulting from undelivered water and benefit rates of onion farms in both periods have negative effects. [ABSTRACT FROM AUTHOR]

In this study, a model predictive control (MPC) system is developed for the goldfield and agricultural water system (GAWS) east of Perth in Western Australia. As part of the study, four months' water quality and hydraulic data of the system were collected for the development of the MPC system. Two artificial neural network (ANN) models are developed to model the relationships between the control variable, the ammonia dosing rate at the source, and the controlled variables, the total chlorine and free ammonia levels at a designated location (Goomalling pump station) in the network five days later. A two-step process based on both mutual information (MI) and partial mutual information (PMI) is used to select appropriate inputs for the total chlorine and free ammonia models. The total chlorine and free ammonia ANN models perform well, with validation Nash-Sutcliffe efficiencies of 0.84 and 0.62, respectively, and validation root mean square errors (RMSE) of 0.1320 and 0.0106 mg=L, respectively. A real-number coded genetic algorithm is then used to find the optimal ammonia dosing rate to achieve the target total chlorine and free ammonia levels at the modeled location. The results demonstrate that the developed MPC system can control the total chlorine and free ammonia levels at Goomalling pump station to be close to their target values by adjusting the ammonia dosing rates at Mundaring pump stations. The errors in the MPC system are mainly due to the relatively weak relationship between the control and controlled variables for this particular system. [ABSTRACT FROM AUTHOR]

Coupling the unsteady open-channel flow equations of surface irrigation with the equation of variably saturated porous media flow is a computationally complex problem because of the dependence of infiltration on surface-flow depths. Several models of this coupled process have been developed, all of which solve the surface and subsurface flow iteratively at each time step of the surface-flow solution. This study presents an alternative strategy, in which stand-alone surface and subsurface-flow models are used to conduct the calculations sequentially and iteratively at the time level of the irrigation event. At each iteration, the subsurface-flow results are computed using the surface-flow depths generated by the surface-flow model at the current iteration. Infiltration results computed at selected computational nodes are fitted to an empirical infiltration function, and then fed back to the surface-flow model. The proposed strategy, labeled external iterative coupling, was prototyped for border and basin irrigation systems using the WinSRFR and HYDRUS-1D models. The proposed procedure produced irrigation performance results comparable to those generated with an internally coupled model, even when using a single representative location to calibrate the empirical infiltration equation used by the surface-flow model. In comparison with models that iterate at each time step, the proposed coupling strategy reduces the computational effort and improves convergence. The approach provides a practical alternative for coupling existing and future surface and subsurface flow models. [ABSTRACT FROM AUTHOR]

The hydrant pressure head in an on-demand water distribution system can be subject to high fluctuation depending on the discharge flowing inside the pipes, with consequent impacts on the performance of on-farm irrigation systems. In this work, an Italian water distribution system was analyzed using the AKLA model at upstream discharges of 1,200 and 600 L·s-1 to estimate the range of hydrant pressure variation. A computer model was developed, calibrated, and used to evaluate the performance of a drip irrigation system by relating the on-farm network with the hydrant characteristic curve at a certain operating status. The flow regulator within the hydrant played an important role in stabilizing the performance of the network at hydrant pressures higher than 27 m. At lower hydrant pressures, to apply the same amount of water, irrigation time must be extended by 17 and 95% for pressure heads of 20 and 12 m, respectively. These approaches described have great utility to ensure adequate irrigation management when water is delivered by pressurized on-demand systems. [ABSTRACT FROM AUTHOR]