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<front>
<journal-meta>
<journal-id journal-id-type="publisher">HESSD</journal-id>
<journal-title-group>
<journal-title>Hydrology and Earth System Sciences Discussions</journal-title>
<abbrev-journal-title abbrev-type="publisher">HESSD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Hydrol. Earth Syst. Sci. Discuss.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1812-2116</issn>
<publisher><publisher-name></publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/hess-2017-729</article-id>
<title-group>
<article-title>Hydro-Climatic Modelling of an Ungauged Basin in Kumasi, Ghana</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Osei</surname>
<given-names>Marian Amoakowaah</given-names>
<ext-link>https://orcid.org/0000-0003-3481-7222</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Amekudzi</surname>
<given-names>Leonard Kofitse</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wemegah</surname>
<given-names>David Dotse</given-names>
<ext-link>https://orcid.org/0000-0002-0709-1465</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Preko</surname>
<given-names>Kwasi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Gyawu</surname>
<given-names>Emmanuella Serwaa</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Obiri-Danso</surname>
<given-names>Kwasi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Kwame Nkrumah University of Science and Technology, Ghana</addr-line>
</aff>
<funding-group>
<award-group id="gs1">
<funding-source></funding-source>
<award-id>none</award-id>
</award-group>
</funding-group>
<pub-date pub-type="epub">
<day>15</day>
<month>01</month>
<year>2018</year>
</pub-date>
<volume>2018</volume>
<fpage>1</fpage>
<lpage>21</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2018 Marian Amoakowaah Osei et al.</copyright-statement>
<copyright-year>2018</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://hess.copernicus.org/preprints/hess-2017-729/">This article is available from https://hess.copernicus.org/preprints/hess-2017-729/</self-uri>
<self-uri xlink:href="https://hess.copernicus.org/preprints/hess-2017-729/hess-2017-729.pdf">The full text article is available as a PDF file from https://hess.copernicus.org/preprints/hess-2017-729/hess-2017-729.pdf</self-uri>
<abstract>
<p>The Owabi catchment which is about 69&amp;thinsp;km&lt;sup&gt;2&lt;/sup&gt; provides about 20&amp;thinsp;% of water needs of the Kumasi metropolis has been in recent times prone to high anthropogenic activities that threaten water resource management.  The Soil-Water-Assessment-Tool (SWAT) was used to assess the extent of these activities on the hydrology on the catchment from 1986 to 2015. Specifically, the model simulated historic and projected stream-flow and water balance. Initial results revealed the forest and topography played  major role in water loss at the catchment as evapotranspiration and surface runoff were the dominant modulating processes. Monthly calibration/validation of the model yielded satisfactory results with NSE (0.66/0.67), &lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; (0.67/0.67), PBIAS (8.2&amp;thinsp;%/8.0&amp;thinsp;%) and RSR (0.59/0.58). Nine sensitive parameters of which the catchment slope (CN2) ranked principal were found to control runoff amounts into the river.  The model uncertainty was also quite low as the 95PPU enveloped about 50&amp;thinsp;% of the observed streamflow within a width of 0.45&amp;ndash;0.55. Furthermore, future streamflow predictions were modelled under RCP2.6, RCP4.5 and RCP8.5 climatic scenarios, and two landuse scenarios, landuse category 1 and 2 (LU1 and LU2). An increasing trend of the downscaled rainfall totals between 2021 to 2050 for all RCPs were observed. This will positively impact streamflow generation at the catchment under LU1. There is an expected deficit of streamflow amounts under LU2 relative to LU1, and a marginal reduction as compared to the baseline. In general, the model proved efficient in determining the hydrology parameters in the catchment and therefore has potential to be used for further modelling of water quality and pollution to aid effective water resource decisions at the catchment.</p>
</abstract>
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