Abstract:How much data is needed for calibration of a hydrological catchment model? In this paper we address this question by evaluating the information contained in different subsets of discharge and groundwater time series for multi-objective calibration of a conceptual hydrological model within the framework of an uncertainty analysis. The study site was a 5Ð6-km 2 catchment within the Forsmark research site in central Sweden along the Baltic coast. Daily time series data were available for discharge and several groundwater wells within the catchment for a continuous 1065-day period. The hydrological model was a sitespecific modification of the conceptual HBV model. The uncertainty analyses were based on a selective Monte Carlo procedure. Thirteen subsets of the complete time series data were investigated with the idea that these represent realistic intermittent sampling strategies. Data subsets included split-samples and various combinations of weekly, monthly, and quarterly fixed interval subsets, as well as a 53-day 'informed observer' subset that utilized once per month samples except during March and April-the months containing large and often dominant snow melt events-when sampling was once per week. Several of these subsets, including that of the informed observer, provided very similar constraints on model calibration and parameter identification as the full data record, in terms of credibility bands on simulated time series, posterior parameter distributions, and performance indices calculated to the full dataset. This result suggests that hydrological sampling designs can, at least in some cases, be optimized.

No abstract

No abstract

No abstract

A framework for ground water protection was developed and tested in the Eastern subarea of the Managua, Nicaragua, ground water system. The framework is a planning tool aimed at identifying areas with a high need for protection to aid future land‐use decisions. The basic components of the framework are vulnerability assessment, contaminant source characterization, and assignment of a protection value. The framework is developed for a geographic information system environment. The vulnerability assessment was carried out using a modified version of the DRASTIC method. The most vulnerable parts of the study area proved to be an area with a shallow ground water table coupled with shrinking/swelling clay soils, and an area where recent porous lava flows mean high recharge and low attenuation capacity. In the contaminant sources characterization, the type of contaminant, its relative concentration, mode of deposition, duration of contaminant load, and possibility for remediation were considered. The sources characterized as emitting a high potential contamination load were concentrated in a tax‐free industrial zone and three villages. The main contaminant sources were a tannery, chemical industries, and sewage water outlets. Both the ground water vulnerability and the potential contamination load were classified as high, moderate, or low. By superimposing the potential contamination load on the vulnerability map, the ground water contamination liability was evaluated by a skewed 3x3 matrix. A relative protection value of the ground water was calculated, based on classifications of available quantities, quality, sensitivity to changes in ground water level, and present or planned use. Together, these maps form an atlas to be used for ground water protection and land‐use planning.