This package contains the supplementary information (SI) of chapter 4 of the dissertation of Frederik T. Weiss with the Dissertation No. ETH 27434 (defended: 24th February, 2021), entitled: "Pesticides in a tropical Costa Rican stream catchment: from monitoring and risk assessment to the identification of possible mitigation options". Generally within this thesis the supplementary information (SI) is divided into three parts (SI A, SI B, SI C). For each chapter, SI A section contains background information/data for the reader with quick and easy access added directly after each main chapter. SI B contains raw data, further processed data for analysis, and figures of processed data presented as Excel files. SI C combines the R scripts with information and commands utilized for the statistical analysis. The abstract of chapter 4 reads as follows: "Finding targeted strategies to mitigate entry of pesticides into surface waters in areas of intense agriculture is challenging. This holds especially true in little studied areas with very distinct topographic characteristics and unconventional field cultivation practices, such as in the tropical Tapezco river catchment in Costa Rica. Within this catchment, areas with steep slopes are used for intense horticultural farming of mainly vegetables. This is exclusively done by a farming practice similar to contour farming, the practice of tilling land with furrows along parallel lines of consistent elevation in order to conserve rainwater and to prevent soil losses by erosion. At the same time, slope-directed paths are implemented to act as drainage system to avoid stagnant water on the fields during heavy rain events, though as well connecting the fields directly with the streams, which enable a fast pesticide transport. Indeed, a significant contamination of streams with pesticides and pesticide transformation products (PPTP) throughout the Tapezco river catchment has been confirmed, leading to considerable toxicological risks to aquatic communities, urgently calling for effective mitigation strategies to reduce PPTP inputs. To identify how PPTP are transported from horticultural areas into streams of the Tapezco river catchment, different PPTP transportation pathways were considered. The first investigated pathway was via handling practices of pesticides by farmers and field workers, where inappropriate handling was proposed to lead to sporadically distributed pesticide inputs unrelated to hydrology. The second studied pathway was surface run-off. Typically, heavy precipitation events are found to be important drivers for the surface-based transport of pesticides into the streams. Thus, such pesticide inputs can be assumed to correlate positively with water levels in the receiving streams. Surface run-off is additionally favored by the slope-directed paths on the fields, which directly connect fields with the streams. Therefore, the influence of prevalent topographical and hydrological variables on PPTP inputs via surface run-offs were studies within this thesis. The third potential investigated input pathway was the leaching of pesticides into the ground from where pesticides can enter streams via exfiltration through river banks. This path would be expected to lead to a constant input that is negatively correlated with water levels. To investigate the role of these pathways in transporting PPTP into the streams, pesticide peaks unrelated to hydrology were identified based on measured environmental concentrations (MEC) of PPTP and compared with water level time series. Survey data about pesticide handling practices were evaluated additionally. Temporal PPTP distributions were investigated during three sampling periods (ΔT1, Δ2a, Δ2b) within 2015 and 2016 and spatial trends were studied at eight sub-catchment (SC) sites. In addition, knowledge on the topography (share of horticultural land, share of forest in the 100 m stream buffer zone, average slopes of the horticultural fields) and hydrology (median water level factors) was considered. These variables were referred to as explanatory variables while 20-, 50- and 80-percentiles of MEC were considered dependent variables. The explanatory and dependent variables were correlated via linear regression modelling for identifying the most important determinants of PPTP transport. There, 20-percentiles represent a scenario with low precipitations, no or low surface run-offs and low PPTP inputs; 50-percentiles a scenario with medium precipitations, resulting in medium surface run-offs and PPTP inputs; and 80-percentiles a scenario with high precipitations, heavy surface run-offs and high PPTP inputs into streams. With a focus on potential mitigation measures achieving the highest effectiveness for reducing risks to aquatic biota, analyses were performed on a sub-set of PPTP that dominated the risks to aquatic organisms, along with three transformation products (TP) to calculate TP/PPTP ratios as a measure of pesticide residence time. The correlation analysis of the PPTP input pathways was again based on eight SC sites. The input of three pesticides were very likely due to inappropriate handling. For five additional pesticides, the input via inappropriate handling seemed probable. Temporal exposure trends were observed by comparing the MEC during the sampling period with reduced precipitation (ΔT1, in 2015) with the MEC detected at periods with normal precipitations (Δ2a, Δ2b, in 2016). In addition, spatial trends were investigated by conducting a cluster analysis with the MEC PPTP data (20-, 50- and 80-percentiles) among the different sites. Particularly the pesticide distributions at SC2 and SC3 were different compared to other sites (SC1, SC4, SC6, SC7 and SC8). However, except for the 20-percentile scenario, the pesticide distribution at SC5 was similar compared to that at SC2 and SC3, forming one sub-cluster. Linear regression models helped to find relationships between two explanatory variables, namely, the share of forest in the buffer zone, and mean slopes of horticultural fields, and the dependent variable, MEC percentiles in streams. For five PPTP, boscalid, diazinon, diuron-desdimethyl, linuron and prometryn + terbutryn the percentile concentrations decreased significantly with increasing share of forest in 100 m river buffer zone considering all scenarios. With regard to the horticultural mean slope, for cyhalothrin and thiamethoxam, the percentile concentrations increased with increasing mean slopes of the horticultural areas for all three scenarios. A high share of forest in the buffer zone worked generally as barrier for input via surface run-off, but not for all PPTP. For the fungicide, carbendazim, increased average slopes did not favor the input into the streams and inputs were low even at sites with horticultural areas with a high mean slope (80 percentile scenario). By analyzing groundwater samples it became apparent that, especially in SC with horticultural fields with low average slopes, a leaching of PPTP into groundwater and further transport into the streams via exfiltration might be possible. Based on this assessment, three avenues for mitigating input of PPTP into the streams could be deduced: to provide training workshops for better handling as well as biobeds for proper disposal; to avoid cultivation of crops in high need insecticides on steep slopes; and to establish forested buffer zones between the fields and the streams."

This dataset shows Near Surface Nitrate Susceptibility. Pollution Impact Potential (PIP) maps were generated separately for nitrate and phosphate to rank critical source areas (CSAs) relative to one another from diffuse agriculture for both the groundwater and surface water receptor. The PIP maps are generated by the EPA Catchment Characterisation Tool (CCT). The CCT delineates the CSAs displayed in the PIP maps by overlaying the hydro(geo)logically susceptible areas (the likelihood of nutrient transfer due to soil and geological properties along the near surface and/or subsurface pathway) with nitrate or phosphate loadings. The nitrate and phosphate PIP maps for the surface water receptor combine the contribution from both the subsurface pathway and the near surface pathway while the groundwater receptor maps only consider the contribution from the groundwater pathway. Surface Water Receptor Nitrate PIP map shows the relative pollution impact potential to surface water along the subsurface and near surface pathways due to nitrate loading. This map should be used to evaluate nutrient impact at the waterbody, subcatchment or catchment scale (at a resolution of less than 1:20,000). Pollution impact potential (PIP) maps rank the CSAs in descending order of risk (where Rank 1 is the highest risk) and are available for the surface water receptor for nitrate and phosphate, and the groundwater receptor for nitrate. Local pressure data has been used to generate the maps in agricultural areas where available. For urban, forestry and the remaining agricultural areas, regional sources of pressure data have been used; these areas are marked 'using regional loadings' on the PIP maps.

Static timetables, stop locations, and route shape information in General Transit Feed Specification (GTFS) format for all operators, including regional, trackwork and transport routes not available in realtime feeds. Returns ZIP file containing CSV files **Please note:** due to the large file size, the API explorer will not work for this resource, ie. 'EXPLORE API' function. To use this dataset please download the zip file using the 'DOWNLOAD' button below or use cURL to get directly. TfNSW GTFS Pathways extension as part of the GTFS Timetables Complete bundle released 2 June 2023.

The vast supply of geothermal energy stored throughout the Earth and the exceedingly long time required to dissipate that energy makes the world's geothermal energy supply nearly limitless. As such, this resource holds the potential to provide a large supply of the world's energy demands; however, like all natural resources, it must be utilized in an appropriate manner if it is to be sustainable. Understanding sustainable use of geothermal resources requires thorough characterization efforts aimed at better understanding subsurface properties. The goal of this work is to understand which critical subsurface properties exert the most influence on sustainable geothermal production as a means to provide targeted future resource characterization strategies. Borehole temperature and reservoir pressure data were analyzed to estimate reservoir thermal and hydraulic properties at an active geothermal site. These reservoir properties then served as inputs for an analytical model which simulated net power production over a 30-year period. The analytical model was used to conduct a sensitivity analysis to determine which parameters were most critical in constraining the sustainability of a geothermal reservoir. Modeling results reveal that the number of preferential flow pathways (i.e. fractures) used for heat transport provides the greatest impact on geothermal reservoir sustainability. These results suggest that early and pre-production geothermal reservoir exploration would achieve the greatest benefit from characterization strategies which seek to delineate the number of active flow pathways present in the system.