Water governance and stakeholder engagement are receiving research attention for their role in formulating and implementing solutions to the world’s critical water challenges. The inspiration for this Special Issue came from our desire to provide a platform for sharing results and informing the global water governance community about the wealth of excellent interdisciplinary and transdisciplinary research and projects being carried out around the world. The 20 peer-reviewed papers collected in this Special Issue have been grouped into three categories: stakeholder engagement, tools for building water management and governance capacity, and perspectives on water management and governance. Following a brief summary of the papers, concluding remarks that reflect on what the papers, taken as a whole, contribute to our understanding are provided.

SummaryEpisodic streamflow events in the Upper Santa Cruz River recharge a shallow alluvial aquifer that is an essential water resource for the surrounding communities. The complex natural variability of the rainfall-driven streamflow events introduces a water resources management challenge for the region. In this study, we assessed the impact of projected climate change on regional water resources management. We analyzed climate change projections of precipitation for the Upper Santa Cruz River from eight dynamically downscaled Global Circulation Models (GCMs). Our analysis indicates an increase (decrease) in the frequency of occurrence of dry (wet) summers. The winter rainfall projections indicate an increased frequency of both dry and wet winter seasons, which implies lower chance for medium-precipitation winters. The climate analysis results were also compared with resampled coarse GCMs and bias adjusted and statistically downscaled CMIP3 and CMIP5 projections readily available for the contiguous U.S. The impact of the projected climatic change was assessed through a water resources management case study. The hydrologic framework utilized includes a rainfall generator of likely scenarios and a series of hydrologic models that estimate the groundwater recharge and the change in groundwater storage. We conclude that climatic change projections increase the uncertainty and further exacerbate the already complicated water resources management task. The ability to attain an annual water supply goal, the accrued annual water deficit and the potential for replenishment of the aquifer depend considerably on the selected management regime

This paper presents a parameter estimation approach based on hydrograph descriptors that capture dominant streamflow characteristics at three timescales (monthly, yearly, and record extent). The scheme, entitled hydrograph descriptors multitemporal sensitivity analyses (HYDMUS), yields an ensemble of model simulations generated from a reduced parameter space, based on a set of streamflow descriptors that emphasize the timescale dynamics of streamflow record. In this procedure the posterior distributions of model parameters derived at coarser timescales are used to sample model parameters for the next finer timescale. The procedure was used to estimate the parameters of the Sacramento soil moisture accounting model (SAC‐SMA) for the Leaf River, Mississippi. The results indicated that in addition to a significant reduction in the range of parameter uncertainty, HYDMUS improved parameter identifiability for all 13 of the model parameters. The performance of the procedure was compared to four previous calibration studies on the same watershed. Although our application of HYDMUS did not explicitly consider the error at each simulation time step during the calibration process, the model performance was, in some important respects, found to be better than in previous deterministic studies.

A reliable prediction of hydrologic models, among other things, requires a set of plausible parameters that correspond with physiographic properties of the basin. This study proposes a parameter estimation approach, which is based on extracting, through hydrograph diagnoses, information in the form of indices that carry intrinsic properties of a basin. This concept is demonstrated by introducing two indices that describe the shape of a streamflow hydrograph in an integrated manner. Nineteen mid-size (223–4790 km²) perennial headwater basins with a long record of streamflow data were selected to evaluate the ability of these indices to capture basin response characteristics. An examination of the utility of the proposed indices in parameter estimation is conducted for a five-parameter hydrologic model using data from the Leaf River, located in Fort Collins, Mississippi. It is shown that constraining the parameter estimation by selecting only those parameters that result in model output which maintains the indices as found in the historical data can improve the reliability of model predictions. These improvements were manifested in (a) improvement of the prediction of low and high flow, (b) improvement of the overall total biases, and (c) maintenance of the hydrograph's shape for both long-term and short-term predictions. Copyright © 2005 John Wiley & Sons, Ltd.