COMPARATIVE STUDY OF OPTIMIZATION TECHNIQUES FOR IRRIGATION PROJECT PLANNING1

ABSTRACT: This study presents three optimization techniques for on‐farm irrigation scheduling in irrigation project planning: namely the genetic algorithm, simulated annealing and iterative improvement methods. The three techniques are applied to planning a 394.6 ha irrigation project in the town of Delta, Utah, for optimizing economic profits, simulating water demand, and estimating the crop area percentages with specific water supply and planted area constraints. The comparative optimization results for the 394.6 ha irrigated project from the genetic algorithm, simulated annealing, and iterative improvement methods are as follows: (1) the seasonal maximum net benefits are $113,826, $111,494, and $105,444 per season, respectively; and (2) the seasonal water demands are 3.03*10³ m³, 3.0*10³ m³, and 2.92*10³ m³ per season, respectively. This study also determined the most suitable four parameters of the genetic algorithm method for the Delta irrigated project to be: (1) the number of generations equals 800, (2) population size equals 50, (3) probability of crossover equals 0.6, and (4) probability of mutation equals 0.02. Meanwhile, the most suitable three parameters of simulated annealing method for the Delta irrigated project are: (1) initial temperature equals 1,000, (2) number of moves equal 90, and (3) cooling rate equals 0.95.     

Integrated Modular Modeling of Water and Nutrients From Point and Nonpoint Sources in the Patuxent River Watershed1

Abstract: We present a simple modular landscape simulation model that is based on a watershed modeling framework in which different sets of processes occurring in a watershed can be simulated separately with different models. The model consists of three loosely coupled submodels: a rainfall‐runoff model (TOPMODEL) for runoff generation in a subwatershed, a nutrient model for estimation of nutrients from nonpoint sources in a subwatershed, and a stream network model for integration of point and nonpoint sources in the routing process. The model performance was evaluated using monitoring data in the watershed of the Patuxent River, a tributary to the Chesapeake Bay in Maryland, from July 1997 through August 1999. Despite its simplicity, the landscape model predictions of streamflow, and sediment and nutrient loads were as good as or better than those of the Hydrological Simulation Program‐Fortran model, one of the most widely used comprehensive watershed models. The landscape model was applied to predict discharges of water, sediment, silicate, organic carbon, nitrate, ammonium, organic nitrogen, total nitrogen, organic phosphorus, phosphate, and total phosphorus from the Patuxent watershed to its estuary. The predicted annual water discharge to the estuary was very close to the measured annual total in terms of percent errors for both years of the study period (≤2%). The model predictions for loads of nutrients were also good (20‐30%) or very good (<20%) with exceptions of sediment (40%), phosphate (36%), and organic carbon (53%) for Year 1.     

Human Instability in Flood Flows1

Abstract: Loss of human stability in flood flows and consequent drowning are a high personal hazard. In this paper, we review past experimental work on human instability. The results of new experiments by the Flood Hazard Research Centre (FHRC) are also reported. These new results show that low depth/high velocity flood waters are more dangerous than suggested based on previous experimental work. It is discussed how human instability can be related to two physical mechanisms: moment instability (toppling) and friction instability (sliding). Comparison of the test results with these physical mechanisms suggests that the occurrence of instability in the tests by FHRC is related to friction instability. This mechanism appears to occur earlier than moment instability for the combination of shallow depth and high flow velocity. Those concerned to identify locations where high flood flows could be a threat to human life need to modify their hazard assessments accordingly.     

Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation1

Young, Charles A., Marisa I. Escobar‐Arias, Martha Fernandes, Brian Joyce, Michael Kiparsky, Jeffrey F. Mount, Vishal K. Mehta, David Purkey, Joshua H. Viers, and David Yates, 2009. Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation. Journal of the American Water Resources Association (JAWRA) 45(6):1409‐1423. Abstract: The rainfall‐runoff model presented in this study represents the hydrology of 15 major watersheds of the Sierra Nevada in California as the backbone of a planning tool for water resources analysis including climate change studies. Our model implementation documents potential changes in hydrologic metrics such as snowpack and the initiation of snowmelt at a finer resolution than previous studies, in accordance with the needs of watershed‐level planning decisions. Calibration was performed with a sequence of steps focusing sequentially on parameters of land cover, snow accumulation and melt, and water capacity and hydraulic conductivity of soil horizons. An assessment of the calibrated streamflows using goodness of fit statistics indicate that the model robustly represents major features of weekly average flows of the historical 1980‐2001 time series. Runs of the model for climate warming scenarios with fixed increases of 2°C, 4°C, and 6°C for the spatial domain were used to analyze changes in snow accumulation and runoff timing. The results indicated a reduction in snowmelt volume that was largest in the 1,750‐2,750 m elevation range. In addition, the runoff center of mass shifted to earlier dates and this shift was non‐uniformly distributed throughout the Sierra Nevada. Because the hydrologic model presented here is nested within a water resources planning system, future research can focus on the management and adaptation of the water resources system in the context of climate change.     

OPTIMIZATION OF INTERMITTENT PUMPING SCHEDULES FOR AQUIFER REMEDIATION USING A GENETIC ALGORITHM1

ABSTRACT: Using a genetic algorithm (GA), optimal intermittent pumping schedules were established to simulate pump‐and‐treat remediation of a contaminated aquifer with known hydraulic limitations and a water miscible contaminant, located within the Duke Forest in Durham, North Carolina. The objectives of the optimization model were to minimize total costs, minimize health risks, and maximize the amount of contaminant removed from the aquifer. Stochastic ground water and contaminant transport models were required to provide estimates of contaminant concentrations at pumping wells. Optimization model simulations defined a tradeoff curve between the pumping cost and the amount of contaminant extracted from the aquifer. For this specific aquifer/miscible contaminant combination, the model simulations indicated that pump‐and‐treat remediation using intermittent pumping schedules for each pumping well produced significant reductions in predicted contaminant concentrations and associated health risks at a reasonable cost, after a remediation time of two years.     

Water Management Decision Making in the Face of Multiple Forms of Uncertainty and Risk

In the Wasatch Range Metropolitan Area of Northern Utah, water management decision makers confront multiple forms of uncertainty and risk. Adapting to these uncertainties and risks is critical for maintaining the long‐term sustainability of the region's water supply. This study draws on interview data to assess the major challenges climatic and social changes pose to Utah's water future, as well as potential solutions. The study identifies the water management adaptation decision‐making space shaped by the interacting institutional, social, economic, political, and biophysical processes that enable and constrain sustainable water management. The study finds water managers and other water actors see challenges related to reallocating water, including equitable water transfers and stakeholder cooperation, addressing population growth, and locating additional water supplies, as more problematic than the challenges posed by climate change. Furthermore, there is significant disagreement between water actors over how to best adapt to both climatic and social changes. This study concludes with a discussion of the path dependencies that present challenges to adaptive water management decision making, as well as opportunities for the pursuit of a new water management paradigm based on soft‐path solutions. Such knowledge is useful for understanding the institutional and social adaptations needed for water management to successfully address future uncertainties and risks.     

Minimizing disruptions caused by damming and ensuring the health of downstream ecosystems

In view of the Brazilian Ten‐Year Energy Expansion Plan 2021, this article presents a discussion on environmental flow (e‐flow). The authors analyze the literature to show the evolution of publications concerning e‐flow releases from the perspective of ecosystems services preservation considering results from different case studies from throughout the world. Finally, two main recommendations are drawn regarding e‐flow are: (1) performing a holistic approach to e‐flow planning, including hydrological, hydraulic, water quality, habitat, and riparian zone considerations; and (2) installing in new structures adequate bottom outlets to allow a range of adjustable e‐flow from reservoir dams to reproduce natural flow variations.     

STOCHASTIC WATER QUALITY ANALYSIS USING RELIABILITY METHOD1

ABSTRACT: This study developed a QUAL2E‐Reliability Analysis (QUAL2E‐RA) model for the stochastic water quality analysis of the downstream reach of the main Han River in Korea. The proposed model is based on the QUAL2E model and incorporates the Advanced First‐Order Second‐Moment (AFOSM) and Mean‐Value First‐Order Second‐Moment (MFOSM) methods. After the hydraulic characteristics from standard step method are identified, the optimal reaction coefficients are then estimated using the Broyden‐Fletcher‐Goldfarb‐Shanno (BFGS) method. Considering variations in river discharges, pollutant loads from tributaries, and reaction coefficients, the violation probabilities of existing water quality standards at several locations in the river were computed from the AFOSM and MFOSM methods, and the results were compared with those from the Monte Carlo method. The statistics of the three uncertainty analysis methods show that the outputs from the AFOSM and MFOSM methods are similar to those from the Monte Carlo method. From a practical model selection perspective, the MFOSM method is more attractive in terms of its computational simplicity and execution time.     

Water Management Applications for Satellite Precipitation Products: Synthesis and Recommendations

This article is an assessment of the current state of the art and relative utility of satellite precipitation products (SPPs) for hydrologic applications to support water management decisions. We present a review of SPPs, their accuracy in diverse settings including the influence of geography, topography, and weather systems, as well as the pros and cons of their use for different water management applications. At the end of this broad synthesizing effort, recommendations are proposed for: (1) SPP developers to improve the quality, usability, and relevance of precipitation products; and (2) SPP users to improve the reliability of their predictions and hydrologic applications to better support water management.     

Upstream Sediment‐Control Dams: Five Decades of Experience in the Rapidly Eroding Dahan River Basin,Taiwan

Sedimentation is emerging as a key issue in sustainable reservoir management. One approach to controlling reservoir sedimentation is to trap sediment in hydraulic structures upstream of the reservoir. In the 1,163‐km² catchment of the Dahan River (Taiwan) over 120 “sabo” dams were built to reduce sediment yield to Shihmen Reservoir. Built in 1963 for water supply, Shihmen has lost over 40% of its 290‐Mm³ storage capacity to sedimentation. Most of these upstream structures were small, but three had capacities >9 Mm³. Field measurements and historical data from the Water Resources Agency show most smaller dams had filled with sediment by 1976. The three largest were full or nearly so by 2007, when one (Barlin Dam) failed, releasing a pulse of 7.5 Mm³, most of its 10.4 Mm³ stored sediment downstream. The Central Range of Taiwan is rapidly eroding (denudation rates 3‐6 mm/yr), so geologically high loads make sediment problems manifest sooner. Even in other environments, however, eventually small dams built upstream of large reservoirs are likely to fill themselves, creating multiple small sediment‐filled reservoirs, some located in sites inaccessible to mechanical removal. Our analysis suggests sabo dams do not offer a long‐term basis for controlling reservoir sedimentation in such a high‐sediment yield environment. Sustainable solutions must somehow pass sediment downstream, as would be accomplished by a sediment bypass around Shihmen Reservoir, as now being studied.