TY - JOUR
T1 - Decision-support systems for water management
AU - Wardropper, Chloe
AU - Brookfield, Andrea
N1 - Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/7
Y1 - 2022/7
N2 - Global variability in water quantity and quality has the potential to impact most systems and sectors around the world, threatening economic stability, human health and environmental sustainability. Scientists have produced information intended to support sustainable management of water from global to local scales, which has been translated in many cases to water decision-support systems (DSS). We define water DSS as computational systems that integrate data and models on water and relevant drivers of change to aid in management decisions. Water DSS vary greatly; they target different types of water issues (e.g., water quantity or quality, groundwater or surface water or conjunctive use); cover various spatial areas (e.g., an aquifer or an international riverine system) and temporal ranges; present data in different formats (e.g., outputs of deterministic models or descriptive information targeting one decision or a larger system); and target different audiences (e.g., public water managers or water users from irrigators to well owners). Despite the proliferation of water DSS, there has been little review and evaluation of these tools beyond region-specific reviews and reviews of DSS in general. The articles in this Special Issue highlight water DSS development and use, illustrating the breadth of methods, tool uses, and opportunities for increased usability. In this Introduction, we provide a history of water DSS, describe current trends and emerging capabilities of these systems, and implications for integration in water management communication and decision-making.
AB - Global variability in water quantity and quality has the potential to impact most systems and sectors around the world, threatening economic stability, human health and environmental sustainability. Scientists have produced information intended to support sustainable management of water from global to local scales, which has been translated in many cases to water decision-support systems (DSS). We define water DSS as computational systems that integrate data and models on water and relevant drivers of change to aid in management decisions. Water DSS vary greatly; they target different types of water issues (e.g., water quantity or quality, groundwater or surface water or conjunctive use); cover various spatial areas (e.g., an aquifer or an international riverine system) and temporal ranges; present data in different formats (e.g., outputs of deterministic models or descriptive information targeting one decision or a larger system); and target different audiences (e.g., public water managers or water users from irrigators to well owners). Despite the proliferation of water DSS, there has been little review and evaluation of these tools beyond region-specific reviews and reviews of DSS in general. The articles in this Special Issue highlight water DSS development and use, illustrating the breadth of methods, tool uses, and opportunities for increased usability. In this Introduction, we provide a history of water DSS, describe current trends and emerging capabilities of these systems, and implications for integration in water management communication and decision-making.
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U2 - 10.1016/j.jhydrol.2022.127928
DO - 10.1016/j.jhydrol.2022.127928
M3 - Editorial
AN - SCOPUS:85130714296
SN - 0022-1694
VL - 610
JO - Journal of Hydrology
JF - Journal of Hydrology
M1 - 127928
ER -