Featured Thesis Figure

Changes in the risk of spring frost damage for grapevines due to climate change
A case study in the Swiss Rhone Valley

Global warming does not only cause the growing phases of plants to start earlier, it also leads to a shift in the average day of year of latest frost days. Depending on the magnitude of these changes, as well as on the corresponding variances, it is not clear if risk for spring frost damage will increase or decrease. Focusing on the Swiss Rhone Valley, future risk according to the SRES A1B scenario was modelled by combining two locations, four frost indices, twelve phenology models and 16 climate model chains. The solid lines indicate the yearly means of the frost indices (i.e. the probability of a frost day after budburst (BBCH09), p(T.n<0°C), the frequency of frost days after BBCH09, f(T.n<0°C), the temperature sum of daily minimum temperature below 0 °C after BBCH09, ∑(T.n<0°C), and the temperature sum of daily mean temperatures below 2 °C after BBCH09, ∑(T.0<2°C)), the day of year (DOY) of the last frost day and of BBCH09. The shaded areas indicate the range of +/- one standard deviation around the yearly means. The broken red lines visualize the mean trends for the period 2001 to 2050. The average risk for spring frost damage is predicted to slightly decrease. This may support winemakers in their decisions regarding future grape varieties and frost damage prevention measures.
(Figure 12, page 66, from the master thesis by Michael Meier)

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Quinoa yields w.r.t. temperature and precipitation (Lampa, Arapa, and Chuquibambilla stations, Peru, years 1964 - 2012)

The potential value of seasonal climate forecasts for allocating agricultural land is estimated in this thesis. Therefore, a theoretical model was developed and applied to the region of Puno in Peru. The application relies on using statistical climate data and simulated yields for quinoa and potato crops - the Figure presents yield simulations for quinoa depending on two climatic indicators, i.e. the seasonal precipitation sum and the minimum temperature during the flowering stage. The analysis shows that the expected revenue can be increased by 4.66 % when key decisions are made with seasonal forecasts, compared to a scenario without seasonal forecasts. The positive value indicates the potential of integrating high-quality seasonal forecasts into decision-making when allocating agricultural land to specific crops.
(Figure 4, page 24, from the master thesis by Anita Frehner)

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Mean runoff of the river Thur in a present-day versus a pre-industrial climate

The thesis assesses the influence of anthropogenic greenhouse gas emissions on temperature, precipitation and runoff of the river Thur in Switzerland. To achieve this, thousands of Global Climate Model simulations with both present-day (A2000) and pre-industrial (A2000N) climate conditions are bias-corrected (from raw to corr; see Figure) and fed into a hydrological model for the river Thur. Higher mean runoff in winter and spring is formed in the present-day scenario (red colors) compared to the pre-industrial scenario (blue colors). This is mainly caused by the combination of increased precipitation and higher temperatures in winter, resulting in less snow accumulation in the present-day scenario. Therefore, more liquid water is available in the hydrological model, leading to enhanced runoff. In contrast, the present-day simulations exhibit lower runoff in summer and autumn than the pre-industrial simulations. This may be caused by the higher temperatures in the present-day scenario which enhance evapotranspiration and thus decrease the amount of water entering the hydrological model. These findings may support decision-makers in climate-related risk and adaptation management.
(Figure 5.7, page 41, from the master thesis by Regula Mülchi)

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Weak points along the main rivers of the Bernese Oberland (Switzerland).

Weak points are locations along a river bed where the channel capacity is frequently exceeded during periods of high river discharges. Hence, weak points indicate potential focii for flood protection measures. Technically, weak points are defined as cross sections of the river bed where the bank-full discharge (channel capacity) has a flood recurrence period (HQ) between 30 and 100 years (red to yellow lines). Whereas specific river sections had been analyzed in practice so far, entire watersheds of the Bernese Oberland (Switzerland) were investigated in this thesis. The highest numbers of weak points (relative to the number of measured cross sections) are found for the Simme, Weisse Lütschine and the Hasli-Aare rivers. The good news is that frequently exceeded channel capacities (<= HQ30) are located along unpopulated areas. However, the protection aim of HQ100 along populated areas is not hold along parts of the Weisse Lütschine and the Simme, and neither along the Aare within the cities of Thun and Bern. These findings provide valuable information for both national and regional watershed administration.
(Figure 3.40, page 87, from the master thesis by Danielle Huser)

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Seasonal total precipitation near Mt. Kenya, interpolated from gauge measurements during the Long Rains (March-April-May) in 1977.

The seasonal precipitation pattern in Central Kenya is highly influenced by the peculiar topography of the area, especially by Mt. Kenya (contour lines; bottom right quadrant). In this thesis, interpolations for seasonal and annual totals are obtained from rain gauge measurements (filled squares) using a combined approach of multiple linear regression with topographic predictors and ordinary kriging of residual precipitation. For the boreal spring rainy season, highest amounts of precipitation are found for the south-eastern slopes of the mountain.
Recent changes in agricultural practices and population growth have triggered conflicts between different water users, as economy and food security highly depend on rain-fed agriculture and river water discharge. In this context, the provided spatial information about rainfall can be used for water ressource allocations, for hydrological studies or to monitor trends over space and time.

(Figure 5.4, page 35, from the master thesis by Noemi Imfeld)

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Cumulative influences of various drivers on the total CO2 emissions in the US from 1997 to 2013.

During the economic recession, between 2007 and 2009, the CO2 emissions dropped by approximately 10%, where the production structure as well as the consumption volume played the most important roles in said decline. The influence of the fuel mix was more or less continuously negative over the entire time period and sums up to the strongest negative influence on the CO2 emissions from 1997 to 2013. The fuel mix describes changes in energy use from coal to gas, from coal to renewables, from oil products to renewables, etc.

(Figure 2, page 51, from the master thesis by Marius Schneider)

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