Optimizing Safe Yield Policy Implementation

Abstract

The presented method enhances groundwater-mandated safe yield management. It is useful for settings that prevent sustained yield or integrated management. To protect hydraulically connected surface water rights, the Utah government's Cache Valley groundwater management plan proposes that total pumping increase not exceed 84,431 m 3 /day. To determine how best to spatially distribute additional allowable pumping, stakeholders quantified limits defining acceptable impacts on selected water resource indicators. A new simulation-optimization (S-O) algorithm used these limits while computing optimal spatially distributed perennial yield or safe yield groundwater pumping extraction strategies. The limits prevent unacceptable decreases in: head and net flow between aquifer and surface waters (rivers, surface/subsurface drains, springs, lakes). The optimization objective function maximizes weighted pumping to provide water for 18 growing municipalities. For 16 perennial yield scenarios, computed optimal pumping increases differ in protectiveness toward senior water rights, and range from 16% to 103% of the state plan-proposed increase. Implementing a protective strategy would achieve 90% of the storage changes needed to reach equilibrium within 23 years. Indicator potentiometric heads would reach equilibrium within 10-40 years. At equilibrium, an optimal Cache Valley perennial yield strategy acceptably minimizes net annual nonpumping discharges. By comparison, multi-period 20-year transient groundwater mining optimizations allow more pumping in early years. Pumping then must decline to satisfy seepage and head constraints through year 20. Adverse seepage impact would increase for years thereafter. For situations governed by safe or perennial yield policy, equilibrium-based (steady-state) optimization is very useful. It effectively develops optimal perennial yield strategies.

Multi-model groundwater-management optimization: reconciling disparate conceptual models

“…Perennialyield strategies generally are designed to be protective from year to year without much consideration of issues during a year (ASCE 1987). For perennial-yield planning, modelers often employ steady-state simulation models that compute the same equilibrium aquifer conditions as SVs computed by transient models simulated for a very long time (Peralta et al 2011). If one is simulating transient monthly pumping rates that are in harmony with a perennial-yield annual pumping strategy, heads and stored groundwater volume change during the year, but net annual storage change is virtually nil.…”

“…This cycling method has been applied to a wide range of S-O studies involving nonlinear aquifer systems and the reported optimal strategies have accurately satisfied SV constraints (Takahashi and Peralta 1995;Peralta et al 2011).…”

“…Formulations differ in the employed simulation model, and in the details of the solved optimization problem. Formulation 1 (F1) uses the USGS simulator and an optimization problem tailored for the USGS model discretization in terms of DVs and state variables (SVs) similar to parts of the perennial study Peralta et al (2011) present. F1 uses a different background well package than that used in the perennial study.…”

“…Applying reported per-capita water consumption values, the change in water demand is estimated and posed as the upper bound on pumping for respective municipalities. This study employs some bounds that differ from those Peralta et al (2011) use.…”

A Methodology to Analyse and Assess Pumping Management Strategies in Coastal Aquifers to Avoid Degradation Due to Seawater Intrusion Problems

“…As a consequence, the determination of the coastal groundwater discharges under different scenarios is important to analyze management alternatives (Zhou, 2014;Hugman et al, 2015). The classical sustainable and optimal yield concept has been extensively applied to analyze groundwater management problems (Peralta et al, 2011;Mays, 2013). It could be also applied to study sustainability in coastal aquifers management (Don et al, 2006;McCoy and Corbett, 2009;Liu and Dai, 2012;El-Kadi et al, 2014;Unsal et al, 2014;).…”