Search USGS⌕ Search

USGS · 70022570

From safe yield to sustainable development of water resources - The Kansas experience

Abstract

This paper presents a synthesis of water sustainability issues from the hydrologic perspective. It shows that safe yield is a flawed concept and that sustainability is an idea that is broadly used but perhaps not well understood. In general, the sustainable yield of an aquifer must be considerably less than recharge if adequate amounts of water are to be available to sustain both the quantity and quality of streams, springs, wetlands, and ground-water-dependent ecosystems. To ensure sustainability, it is imperative that water limits be established based on hydrologic principles of mass balance. To establish water-use policies and planning horizons, the transition curves of aquifer systems from ground-water storage depletion to induced recharge of surface water need to be developed. Present-day numerical models are capable of generating such transition curves. Several idealized examples of aquifer systems show how this could be done. Because of the complexity of natural systems and the uncertainties in characterizing them, the current philosophy underlying sustainable management of water resources is based on the interconnected systems approach and on adaptive management. Examples of water-resources management from Kansas illustrate some of these concepts in a real-world setting. Some of the hallmarks of Kansas water management are the formation of local ground-water management districts, the adoption of minimum streamflow standards, the use of modified safe-yield policies in some districts, the implementation of integrated resource planning by the City of Wichita, and the subbasin water-resources management program in potential problem areas. These are all appropriate steps toward sustainable development. The Kansas examples show that local decision-making is the best way to fully account for local variability in water management. However, it is imperative that public education and involvement be encouraged, so that system complexities and constraints are better understood and overly simplistic solutions avoided. (C) 2000 Elsevier Science B.V.This paper presents a synthesis of water sustainability issues from the hydrologic perspective. It shows that safe yield is a flawed concept and that sustainability is an idea that is broadly used but perhaps not well understood. In general, the sustainable yield of an aquifer must be considerably less than recharge if adequate amounts of water are to be available to sustain both the quantity and quality of streams, springs, wetlands, and ground-water-dependent ecosystems. To ensure sustainability, it is imperative that water limits be established based on hydrologic principles of mass balance. To establish water-use policies and planning horizons, the transition curves of aquifer systems from ground-water storage depletion to induced recharge of surface water need to be developed. Present-day numerical models are capable of generating such transition curves. Several idealized examples of aquifer systems show how this could be done. Because of the complexity of natural systems and the uncertainties in characterizing them, the current philosophy underlying sustainable management of water resources is based on the interconnected systems approach and on adaptive management. Examples of water-resources management from Kansas illustrate some of these concepts in a real-world setting. Some of the hallmarks of Kansas water management are the formation of local ground-water management districts, the adoption of minimum streamflow standards, the use of modified safe-yield policies in some districts, the implementation of integrated resource planning by the City of Wichita, and the subbasin water-resources management program in potential problem areas. These are all appropriate steps toward sustainable development. The Kansas examples show that local decision-making is the best way to fully account for local variability in water management. However, it is imperative that public education and involv

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M. Sophocleous. 2000. From safe yield to sustainable development of water resources - The Kansas experience. https://doi.org/10.1016/s0022-1694(00)00263-8

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Inverse modeling for post-wildfire hydrologic process understanding over snow-dominated watersheds

Wildfire-induced changes to vegetation and soil properties can alter snowpack dynamics and hydrologic processes in ways that complicate predictions of post-wildfire water availability. To better understand these effects, we coupled the Parameter ESTimation in C++ (PEST++) software with the Weather Research & Forecasting Hydrologic model (WRF-Hydro) across three burned, snow-dominated watersheds in the western United States. We incorporated three burn-severity-based land cover categories into WRF-Hydro and used an iterative Ensemble Smoother (iES) within PEST++ to estimate model parameters controlling snow accumulation and melt, infiltration, and streamflow generation. This framework supported three complementary objectives: (1) assessing parameter sensitivities under pre- and post-wildfire conditions, (2) comparing pre- and post-wildfire parameter ensembles to identify wildfire-driven shifts in hydrologic processes, and (3) using counterfactual simulations to isolate the hydrologic response to wildfire from interannual climate variability. Our findings indicate that model parameter sensitivity varied by domain and shifted following wildfire. Maximum snow albedo and snow albedo decay were most influential in the higher-elevation East Troublesome domain, while the rain-snow partitioning temperature threshold dominated in the lower-elevation Chippy Creek and Las Conchas domains. Following wildfire, streamflow sensitivity shifted away from snowpack parameters toward soil hydraulic parameters, consistent with wildfire-driven reductions in evapotranspiration and increases in soil moisture. Incorporating wildfire effects led to complex changes in simulated snowpack accumulation and streamflow timing, generally leading to earlier snowmelt freshet initiation and cessation and reduced late season flows. Simulations were more sensitive to interannual climate variations than wildfire land cover changes. These results highlight both the potential and challenges of ensemble-based inverse modeling for understanding post-wildfire hydrologic change in snow-dominated watersheds.

Colorado, Montana, New Mexico↗

Reservoir releases and land cover interact to drive event-scale nitrate export in a large agricultural basin

Understanding the drivers of nitrate export in rivers is critical for developing effective nutrient management strategies. However, few studies have explored event-scale drivers of export in large river basins with human modifications like reservoirs. Here, we analyzed nitrate concentration-discharge (C-Q) relationships from 215 events at the outlet of the Kansas River Basin, USA (155,690 km 2 ) from 2014 to 2022 to (1) characterize event-scale nitrate export behaviors in a large agricultural basin, and (2) determine how different event characteristics are linked to these behaviors. We found that C-Q behaviors varied greatly, with 60% of events producing nitrate enrichment (n = 130) and 40% of events producing nitrate dilution (n = 85). These behaviors were correlated with complex spatial interlinkages between climate and land cover: across most of the basin, nitrate enrichment was correlated with drier antecedent conditions, but in wetter areas with higher proportions of urban and forested land cover, enrichment was more strongly correlated with precipitation magnitude/intensity. This difference in hydroclimatic controls on nitrate export might be related to differential distributions of nitrate sources within these land covers. Upstream of major reservoirs, however, neither variable was strongly correlated with C-Q behavior, suggesting that nitrate attenuation within reservoirs decouples event-scale concentration signals in upstream waters from those downstream. Reservoir outflows had variable impacts on C-Q behavior, reflecting reservoir-specific variations in nitrate attenuation efficiency. Together, these results identify specific complex interactions between hydroclimate, land cover, reservoir positioning, and individual reservoir properties that control event-scale nitrate export from large basins.

Colorado, Kansas, Nebraska↗

Deep learning error post-processing improves stochastic watershed modeling

Hydrologic extremes, including floods and droughts, pose substantial societal risks that are expected to intensify with climate change. Deterministic watershed models (DWMs) remain a mainstay for modeling these extremes, but lack explicit representation of uncertainty, limiting their utility for risk-informed planning. Stochastic watershed models (SWMs) address this limitation by generating ensembles of streamflow via models of observed DWM residuals. However, most SWMs struggle with the complex dependence between DWM residuals and the underlying hydrologic state, which can complicate stochastic simulations under nonstationary climates. Deep learning (DL) models, whether used as standalone models or post-processors for process-based DWMs, offer a pathway to address this challenge by reducing conditional dependence. In this study, we evaluate SWMs applied to seven models: three process-based models (PRMS, Hymod, and HBV), their hybrid process-DL counterparts, and a pure DL DWM, focusing on daily simulations and extremes under both historical conditions and synthetic climate change scenarios. Results for a case study watershed in Massachusetts show that SWMs applied to hybrid or pure DL DWMs consistently outperform those applied to process-based DWMs. However, an SWM applied to the pure DL model exhibits weaknesses at low flows for this study basin, underscoring the value of hybrid approaches. Extending the analysis across 73 additional basins demonstrates that these improvements are robust and generalizable statewide. This work highlights the potential of a DL-enhanced stochastic watershed modeling framework to advance hydrologic risk prediction under changing climate conditions, offering a scalable methodology for integrating uncertainty into watershed modeling for long-term planning.

Journal of Hydrology↗