GROUND WATER QUALITY PREDICTION USING CLIMATIC INDICES¹

Abstract

Drought affects the quality of ground water in certain aquifers used by municipalities in Kansas. Water quality changes occur as a function of the amount of water available for recharge and hence to dilute more mineralized ground waters. Several measures of meteorological drought, including the Palmer Index and Eagleman Aridity Index, were correlated with water quality data to determine the degree of association. Several locations showed sharp delinces in water quality as the drought progressed. These relationships can be used to predict possible variations in present and future well‐water supplies in locations subject to drought induced water quality deterioration.

THE POTENTIAL EFFECTS OF GLOBAL WARMING ON THE PRIMARY PRODUCTIVITY OF A SUBALPINE LAKE1

“…As we have demonstrated for Castle Lake, lake primary production and related water quality characteristics can also be projected to change with climate. Since ground water (e.g., McGregor et al, 1988) and streamwater quality (Minns and Johnson, 1979;Lewis and Grant, 1979;Meyer et al, 1981) can also be influenced by the timing and magnitude of annual precipitation, we predict that water quality changes under conditions of doubled atmospheric CO2 would be widespread and ubiquitous. We suggest that integrated records of stream, ground water, and lake water quality could be investigated to derive empirical relationships between climate and water quality for entire watershed systems.…”

ECTACI: European Climatology and Trend Atlas of Climate Indices (1979–2017)

“…The aridity/continentality indices are widely used in the ecology and agriculture sectors, due to the importance of plant‐available water, for example, BI, JCI, KOI, PiCI, MAI, and MOI (Baltas, 2007; Creed et al, 2014). In addition, there are studies indicating that climate change will increase aridity globally as the rising temperatures drive up rates of evapotranspiration (Dai, 2011), so different aridity indices are applied, such as CMD, UAI, ETo, and EAI (Chiew et al, 1995; Girvetz & Zganjar, 2014; Huang et al, 2016; McGregor et al, 1988). Most studies on cloudiness and radiation use data from surface solar radiation or sunshine indices, for example, SSD, SSP, and CC (Sanchez‐Lorenzo et al, 2008, 2015; Stjern et al, 2009; Wild, 2009).…”