Climate change is expected to have significant impacts on hydrologic regimes and freshwater ecosystems, and yet few basins have adequate numerical models to guide the development of freshwater climate adaptation strategies. Such strategies can build on existing freshwater conservation activities, and incorporate predicted climate change impacts. We illustrate this concept with three case studies. In the Upper Klamath Basin of the western USA, a shift in land management practices would buffer this landscape from a declining snowpack. In the Murray–Darling Basin of south-eastern Australia, identifying the requirements of flood-dependent natural values would better inform the delivery of environmental water in response to reduced runoff and less water. In the Savannah Basin of the south-eastern USA, dam managers are considering technological and engineering upgrades in response to more severe floods and droughts, which would also improve the implementation of recommended environmental flows. Even though the three case studies are in different landscapes, they all contain significant freshwater biodiversity values. These values are threatened by water allocation problems that will be exacerbated by climate change, and yet all provide opportunities for the development of effective climate adaptation strategies.
Effective protection and management of groundwater‐dependent ecosystems (GDEs) are hindered by inadequate information on their locations and the condition of associated groundwater supplies. We addressed this knowledge gap by developing a methodology that uses existing datasets to locate GDEs (including groundwater‐dependent springs, lakes, rivers, wetlands, and species) and assess threats to groundwater quantity and quality. Here we report on the application of this method across the US state of Oregon. Nearly 40% of watersheds in Oregon contain two or more types of GDEs – termed “GDE clusters” – indicating the widespread importance of groundwater to ecosystems. Documented problems may underestimate the threat to ecosystems from altered groundwater supply or quality. Although documented occurrences of water‐table declines are limited, high densities of permitted wells (for irrigation or other commercial purposes) pose a threat to groundwater availability in 18% of GDE clusters. Furthermore, although only 5% of GDE clusters have known groundwater contamination, our assessment indicates that 30% of GDE clusters are threatened with groundwater contamination by nitrates, 30% by industrial chemicals, and 70% by pesticides. This initial assessment of GDEs and threats to their groundwater supply highlights the ecological importance of groundwater and the need to incorporate protection of GDEs in water management policy.
A variety of aircraft remotely sensed and conventional ground-based measurements of volumetric soil water content (SW) were made over two subwatersheds (4.4 and 631 ha) of the U.S. Department of Agriculture's Agricultural Research Service Walnut Gulch experimental watershed during the 1990 monsoon season. Spatially distributed soil water contents estimated remotely from the NASA push broom microwave radiometer (PBMR), an Institute of Radioengineering and Electronics (IRE) multifrequency radiometer, and three ground-based point methods were used to define prestorm initial SW for a distributed rainfall-runoff model (KINEROS; Woolhiser et al., 1990)•at a small catchment scale (4.4 ha). At a medium catchment scale (631 ha or 6.31 km •) spatially distributed PBMR SW data were aggregated via stream order reduction. The impacts of the various spatial averages of SW on runoff simulations are discussed and are compared to runoff simulations using $W estimates derived from a simple daily water balance model. It was found that at the small catchment scale the SW data obtained from any of the measurement methods could be used to obtain reasonable runoff predictions. At the medium catchment scale, a basin-wide remotely sensed average of initial water content was sufficient for runoff simulations. This has important implications for the possible use of satellite-based microwave soil moisture data to define prestorm SW because the low spatial resolutions of such sensors may not seriously impact runoff simulations under the conditions examined. However, at both the small and medium basin scale, adequate resources must be devoted to proper definition of the input rainfall to achieve reasonable runoff simulations. 1. Introduction Passive microwave soil moisture research has focused on the basic questions involved in the data interpretation algorithm [Jackson and Schmugge, 1989]. There have been a number of efforts to develop water balance models that utilize these surface observations [Jackson, 1986; Prevot et al., 1984]; however, these have only considered a single profile and have not considered surface runoff dynamics. Engrnan and Gurney [1991] recently summarized some common viewpoints concerning remotely sensed soil moisture observations and hydrologic modeling. The general conclusion was that in order to fully utilize the information that frequent spatially distributed soil moisture observations might provide, we must reevaluate the hydrologic models themselves. The soil component of many existing models is constructed in such a way to make the model work even though soil moisture has never been available as an input variable. This element of the hydrologic cycle has thus Gurney [1991] noted, actual observations of soil moisture may offer no improvement in runoff estimation because these models do not properly incorporate this variable. This was observed by Jackson et al. [1981] in a study involving a continuous runoff simulation model. In that study they examined how repetitive surface soil moisture observations could be us...
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