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ecoforecast-africa/streamflow_jonkershoek

Domain:

environment and energyclimate

Record type:

datasetproject
Creator:
eco
Host:
A preliminary workflow for forecasting Jonkershoek flood events # Jonkershoek streamflow and flood events ## Project Description The goal of `streamflow_jonkershoek` is to set up a project focused on forecasting flood events in the Jonkershoek valley, South Africa, for the near-term ecological forecasting course run by the African Chapter of the Ecological Forecasting Initiative, Ecoforecast Africa ( ). See . ## Data Overview Streamflow, weather and soil moisture data are from the South African Environmental Observation Network (SAEON). The project will focus on streamflow data from the Langrivier gauging weir and weather and soil moisture data from the high altitude automated weather station at Dwarsberg. These observations are part of the Jonkershoek long term study site run by the SAEON Fynbos Node ( ). The site has a long history of environmental observations, starting with a multiple catchment experiment in the 1940s. More details are available in Slingsby et al. 2021. Jonkershoek: Africa’s Oldest Catchment Experiment ‐ 80 Years and Counting. Hydrological Processes, . For this project we are focusing only on data collected since SAEON took over observations at this site and set up automated logging instruments. Using older records (back to the 1930s in some cases) requires dealing with changes in instrumentation, recording frequency, etc. The data we’ll use run from from 2011-08-24 to the near-present for streamflow, and 2013-03-03 to the near-present for weather and soil moisture. A typical v-notch weir at Jonkershoek. For the purposes of this forecast a flood is defined as an event where the stream height rises above the wall of the weir. For the Langrivier weir, this occurs when streamflow exceeds 4.076 cumecs. For live weather data and the record over the past month you can access the Dwarsberg weather station directly ### Data download and cleaning The data were downloaded from the SAEON Observations Database ( ) using the `saeonobsr` R package. To use this service you need to register for an account …

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