Water and Climate Change Inter-dependencies - workshop at Bonn Climate Conference

The UN-Water Expert Group on Water and Climate Change hosted a technical workshop at the margins of the Bonn Climate Conference on 14 June 2023, entitled Water and Climate Change Inter-Dependencies.


Aktuelle Projekte 

Water supply in times of climate change — Tracer tests to identify the catchment area of an Alpine karst spring, Tyrol, Austria 

Climate change and glacial retreat are changing the runoff behavior of Alpine springs and streams. For example, in the extremely dry and hot summer of 2018, many springs used for drinking water supply lost up to 50 percent of their average discharge; a few springs have even run dry. 
In order to ensure drinking water supply in the future, springs featuring large and constantly sufficient discharge rates will have to be identified and tapped. 
A case study was undertaken at the Tuxbachquelle because catchment area and temporal variation of physicochemical and hydrochemical properties were previously unknown. Tracer tests with uranine proved a hydraulic connection between this karst spring and a stream a few kilometers uphill. At low runoff, uranine needed about 4½ hours from the sink to the spring, whereas at high runoff more than four days was required. It became evident that discharge, electrical conductivity, temperature, and turbidity of the Tuxbachquelle respond within a few hours to precipitation events. The water quality and an examination of the water balance resulted in a significantly larger catchment area. It is assumed that widely karstified calcite marble subterraneously drains a considerable part of the Tuxertal (Tux Valley), including some active rock glaciers. 

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Rafael Schäffer, Ingo Sass & Claus-Dieter Heldmann (2020) Water supply in times of climate change—Tracer tests to identify the catchment area of an Alpine karst spring, Tyrol, Austria, 
Arctic, Antarctic, and Alpine Research, 52:1, 70-86, DOI: 10.1080/15230430.2020.1723853 

To link to this article: https://doi.org/10.1080/15230430.2020.1723853 

Adaptability and adaptations of California’s water supply system to dry climate warming

Economically optimal operational changes and adaptations for California’s water supply system are examined for a dry form of climate warming (GFDL CM2.1 A2) withyear 2050 water demands and land use. Economically adaptive water management for thisclimate scenario is compared to a similar scenario with the historical climate. The effects of population growth and land use alone are developed for comparison. Compared with the historic hydrology, optimized operations for the dry climate warming scenario raise water scarcity and total operation costs by $490 million/year with year 2050 demands. 
Actual costs might be somewhat higher where non-economic objectives prevail in water management. The paper examines the economical mix of adaptation, technologies, policies, and operational changes available to keep water supply impacts to such modest levels. Results from this screening model suggest promising alternatives and likely responses and impacts. Optimized operations of ground and surface water storage change significantly with climate.
Dry-warm climate change increases the seasonal storage range of surface reservoirs and aquifers. Surface reservoir peak storage usually occurs about a month earlier under dry-warm climate change.

Climatic Change
DOI 10.1007/s10584-007-9355-z

Urban Water Demand Prediction for a City That Suffers from Climate Change and Population Growth: Gauteng Province Case Study

The proper management of a municipal water system is essential to sustain cities andsupport the water security of societies. Urban water estimating has always been a challenging task for managers of water utilities and policymakers. 
This paper applies a novel methodology that includes data pre-processing and an Artificial Neural Network (ANN) optimized with the Backtracking Search Algorithm (BSA-ANN) to estimate monthly water demand in relation to previous water consumption. Historical data of monthly water consumption in the Gauteng Province, South Africa, for the period2007–2016, were selected for the creation and evaluation of the methodology. Data pre-processing techniques played a crucial role in the enhancing of the quality of the data before creating theprediction model. The BSA-ANN model yielded the best result with a root mean square error and a coefficient of efficiency of 0.0099 mega liters and 0.979, respectively. Moreover, it proved more efficientand reliable than the Crow Search Algorithm (CSA-ANN), based on the scale of error. Overall, this paper presents a new application for the hybrid model BSA-ANN that can be successfully used to predict water demand with high accuracy, in a city that heavily suffers from the impact of climate change and population growth.

Water 2020,12, 1885;