scholarly journals Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

2013 ◽  
Vol 17 (12) ◽  
pp. 5013-5039 ◽  
Author(s):  
S. E. Thompson ◽  
M. Sivapalan ◽  
C. J. Harman ◽  
V. Srinivasan ◽  
M. R. Hipsey ◽  
...  
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Research Agenda ◽  
Water Systems ◽  
Coupled Systems ◽  
Model Data ◽  
Resources Management ◽  
Long Timescales ◽  
Insight Into

Abstract. Globally, many different kinds of water resources management issues call for policy- and infrastructure-based responses. Yet responsible decision-making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal- to century-long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle – a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges from the perspectives of hydrologic science research. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management. Fully realizing the potential of this approach will ultimately require detailed integration of social science and physical science understanding of water systems, and is a priority for the developing field of sociohydrology.

scholarly journals Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

2013 ◽  
Vol 10 (6) ◽  
pp. 7897-7961 ◽  
Author(s):  
S. E. Thompson ◽  
M. Sivapalan ◽  
C. J. Harman ◽  
V. Srinivasan ◽  
M. R. Hipsey ◽  
...  
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Research Agenda ◽  
Coupled Systems ◽  
Time Behavior ◽  
Model Data ◽  
Resources Management ◽  
Long Timescales ◽  
Insight Into

Abstract. Globally, many different kinds of water resources management issues call for policy and infrastructure based responses. Yet responsible decision making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal-to-century long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle – a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management.

Water Resources Management

2014 ◽  
pp. 180-200 ◽  
Author(s):  
Sabyasachi Nayak
Keyword(s):  
Water Management ◽  
Pilot Study ◽  
Water Resources ◽  
Water Resources Management ◽  
Social Economic ◽  
The State ◽  
Resources Management ◽  
Partnership Approach ◽  
The Impact ◽  
Insight Into

This chapter explores grassroots interventions by forging partnerships with stakeholders in improving the management of water resources at the community level. In order to gain insight into the nuances of managing water resources in partnership, a pilot study was instituted in the State of Rajasthan, India. The efficacy of the partnership approach in ensuring equitable water management is demonstrated. The analysis is supported by data collected through the administration of a questionnaire for five different stakeholders. The impact of the intervention reiterates the positive social, economic, and environmental outcomes in a more sustainable manner.

Evolutionary Bayesian Belief Networks for Participatory Water Resources Management under Uncertainty

2011 ◽  
pp. 524-539
Author(s):  
R. Farmani ◽  
D.A. Savic ◽  
H.J. Henriksen ◽  
J.L. Molina ◽  
R. Giordano ◽  
...  
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Bayesian Belief Networks ◽  
Decision Making Process ◽  
Causal Loop Diagram ◽  
Belief Networks ◽  
Trade Off ◽  
Resources Management ◽  
Conflicting Objectives

A participatory integrated (social, economic, environmental) approach based on causal loop diagram, Bayesian belief networks and evolutionary multiobjective optimisation is proposed for efficient water resources management. The proposed methodology incorporates all the conflicting objectives in the decision making process. Causal loop diagram allows a range of different factors to be considered simultaneously and provides a framework within which the contributions of stakeholders can be taken into account. Bayesian belief networks takes into account uncertainty by assigning probability to those variables whose states are not certain. The integration of Bayesian belief network with evolutionary multiobjective optimisation algorithm allows analysis of trade-off between different objectives and incorporation and acknowledgement of a broader set of decision goals into the search and decision making process. The proposed methodology is used to model decision making process for complex environmental problems, considering uncertainties, addressing temporal dynamics, uncovering discrepancies in decision analysis process (e.g. completeness or redundancy of the model based on utility function) and generating policy options that trade-off between conflicting objectives. The effectiveness of the proposed methodology is examined in several water resources management problems. The case studies include optimum water demand management, UK; management of groundwater contamination of Copenhagen source capture zone areas, Denmark and simultaneous optimum management of four overexploited aquifers in Spain. It is shown that the proposed methodology generates large number of management options that trade-off between different objectives. The remaining task is to choose, depending on the preference of decision makers, a group of solutions for more detailed analysis.

Hydrogeological Modeling and Water Resources Management: Improving the Link Between Data, Prediction, and Decision Making

2019 ◽  
Vol 55 (12) ◽  
pp. 10340-10357 ◽  
Author(s):  
Bradley Harken ◽  
Ching‐Fu Chang ◽  
Peter Dietrich ◽  
Thomas Kalbacher ◽  
Yoram Rubin
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Resources Management ◽  
Data Prediction

Operationalising uncertainty in data and models for integrated water resources management

2007 ◽  
Vol 56 (9) ◽  
pp. 1-12 ◽  
Author(s):  
M.W. Blind ◽  
J.C. Refsgaard
Keyword(s):  
Water Management ◽  
Risk Assessment ◽  
Decision Making ◽  
Water Resources ◽  
Water Resources Management ◽  
Integrated Water Resources Management ◽  
Integrated Water Management ◽  
Resources Management ◽  
Broad Objective ◽  
Parameter Values

Key sources of uncertainty of importance for water resources management are (1) uncertainty in data; (2) uncertainty related to hydrological models (parameter values, model technique, model structure); and (3) uncertainty related to the context and the framing of the decision-making process. The European funded project ‘Harmonised techniques and representative river basin data for assessment and use of uncertainty information in integrated water management (HarmoniRiB)’ has resulted in a range of tools and methods to assess such uncertainties, focusing on items (1) and (2). The project also engaged in a number of discussions surrounding uncertainty and risk assessment in support of decision-making in water management. Based on the project's results and experiences, and on the subsequent discussions a number of conclusions can be drawn on the future needs for successful adoption of uncertainty analysis in decision support. These conclusions range from additional scientific research on specific uncertainties, dedicated guidelines for operational use to capacity building at all levels. The purpose of this paper is to elaborate on these conclusions and anchoring them in the broad objective of making uncertainty and risk assessment an essential and natural part in future decision-making processes.

Seasonal variation in water storage, vertical land motion and well levels: Implications for groundwater storage change in Central Valley

2020 ◽  
Author(s):  
Susanna Werth ◽  
Manoochehr Shirzaei
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
Central Valley ◽  
Groundwater Storage ◽  
Resources Management ◽  
Groundwater Levels ◽  
Climate Research ◽  
Vertical Land Motion ◽  
Storage Change ◽  
Insight Into

<p>The establishment of the Inter-Commission Committee on "Geodesy for Climate Research" (ICCC) of the International Association of Geodesy (IAG) emphasizes on the usefulness of geodetic sensors for estimating high-resolution water mass variation, which is due to broad applications of geodetic tools ranging from water cycle studies to water resources management. As such, data from both GRACE missions continue to provide insight into the alarming rates of groundwater depletion in large aquifers worldwide. Observations of vertical land motion (VLM) from GPS and InSAR may reflect elastic responses of the Earth's crust to changes in mass load, including those in aquifers. However, above confined aquifers, VLM observations are dominated by poroelastic deformation processes. In previous works, Ojha et al. 2018 and 2019 show that GRACE-based estimates of groundwater storage change in the Central Valley, California, are consistent with those obtained by utilizing measurements of surface deformation. These studies also show that annual variations in VLM correlate well in time with groundwater levels.</p><p>Here, we investigate seasonal variations in groundwater storage by identifying how their effect is manifested in geodetic and hydrological datasets. Groundwater well observations in the Central Valley indicate maximum groundwater levels at the beginning of the year between February to April and lowest water levels in the middle of the year about July to October. Meanwhile, GRACE groundwater storage estimates peak about four months later. To get insight into the mechanisms leading to this discrepancy, we perform a Wavelet multi-resolution analysis of GRACE TWS variations and complementary groundwater, snowcap, soil moisture, and reservoir level variations. We show that the majority of the differences between wavelet spectrums at seasonal frequencies occur during drought periods when there is no supply of precipitation in the high elevations. We employ a 1D diffusion model to demonstrate that the variations in groundwater levels across the Central Valley are due to the propagation of the pressure front at recharge sites due to gradual snowmelt. Such a model could explain the different timing of peaks in groundwater time series based on satellite gravimetry compared to deformation and well observations. We also discuss that winter rains are not able to directly contribute to recharging deep aquifers in the Central Valley, whereas most of the recharge must source from lateral flow caused by differential pressure at the sites of snow-melt in the Sierra Nevada as well as from agricultural return flows.</p><p>This analysis addresses the question of how well the different geodetic signals that reflect groundwater discharge and recharge processes agree with one another and what are the possible causes of disagreements. We emphasize the need for interdisciplinary efforts for the successful integration of available geodetic and hydrological datasets to improve our ability to utilizing geodetic sensors for climate research and water resources management.</p><p>References:</p><p>Ojha, C., Werth, S., & Shirzaei, M. (2019). JGR, https://doi.org/10.1029/2018JB016083.</p><p>Ojha, C., M. Shirzaei, S. Werth, D. F. Argus, and T. G. Farr (2018), WRR, https://doi.org/10.1029/2017WR022250.</p>

Water Resources Management

2016 ◽  
pp. 15-31
Author(s):  
Sabyasachi Nayak
Keyword(s):  
Water Management ◽  
Pilot Study ◽  
Water Resources ◽  
Water Resources Management ◽  
Social Economic ◽  
The State ◽  
Resources Management ◽  
Partnership Approach ◽  
The Impact ◽  
Insight Into

This chapter explores grassroots interventions by forging partnerships with stakeholders in improving the management of water resources at the community level. In order to gain insight into the nuances of managing water resources in partnership, a pilot study was instituted in the State of Rajasthan, India. The efficacy of the partnership approach in ensuring equitable water management is demonstrated. The analysis is supported by data collected through the administration of a questionnaire for five different stakeholders. The impact of the intervention reiterates the positive social, economic, and environmental outcomes in a more sustainable manner.

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