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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">Oalib</journal-id>
      <journal-title-group>
        <journal-title>Open Access Library Journal</journal-title>
      </journal-title-group>
      <issn pub-type="epub">2333-9721</issn>
      <issn pub-type="ppub">2333-9705</issn>
      <publisher>
        <publisher-name>Scientific Research Publishing</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.4236/oalib.1114545</article-id>
      <article-id pub-id-type="publisher-id">Oalib-147914</article-id>
      <article-categories>
        <subj-group>
          <subject>Article</subject>
        </subj-group>
        <subj-group>
          <subject>Biomedical</subject>
          <subject>Life Sciences</subject>
          <subject>Business</subject>
          <subject>Economics</subject>
          <subject>Chemistry</subject>
          <subject>Materials Science</subject>
          <subject>Computer Science</subject>
          <subject>Communications</subject>
          <subject>Earth</subject>
          <subject>Environmental Sciences</subject>
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          <subject>Social Sciences</subject>
          <subject>Humanities</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Impact of Climate Variability and Change on Sorghum Yield in Gedaref State, Sudan</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Hudo</surname>
            <given-names>Noah Adam</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="aff1"><label>1</label> Department of Meteorology, University of Nairobi, Nairobi, Kenya </aff>
      <author-notes>
        <fn fn-type="conflict" id="fn-conflict">
          <p>The author declares no conflicts of interest.</p>
        </fn>
      </author-notes>
      <pub-date pub-type="epub">
        <day>01</day>
        <month>12</month>
        <year>2025</year>
      </pub-date>
      <pub-date pub-type="collection">
        <month>12</month>
        <year>2025</year>
      </pub-date>
      <volume>12</volume>
      <issue>12</issue>
      <fpage>1</fpage>
      <lpage>6</lpage>
      <history>
        <date date-type="received">
          <day>04</day>
          <month>11</month>
          <year>2025</year>
        </date>
        <date date-type="accepted">
          <day>08</day>
          <month>12</month>
          <year>2025</year>
        </date>
        <date date-type="published">
          <day>11</day>
          <month>12</month>
          <year>2025</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>© 2025 by the authors and Scientific Research Publishing Inc.</copyright-statement>
        <copyright-year>2025</copyright-year>
        <license license-type="open-access">
          <license-p> This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( <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 content-type="doi" xlink:href="https://doi.org/10.4236/oalib.1114545">https://doi.org/10.4236/oalib.1114545</self-uri>
      <abstract>
        <p>Climate variability has become a major constraint to agricultural productivity in Sudan, particularly in rain-fed regions such as Gedaref State. This study analyzes the impacts of temperature and rainfall variability on sorghum yield using long-term climate data (1961-2014) and sorghum production records (1970-2007). Mann-Kendall trend tests, correlation, and multiple regression analyses were applied to assess climate-yield relationships. The FAO AquaCrop model was used to project future yield changes under changing climate conditions. Results revealed significant increases in maximum and minimum temperatures (p &lt; 0.001) and a slight, insignificant decline in rainfall. Sorghum yield was positively correlated with rainfall (r = 0.59) and negatively correlated with maximum (r = −0.34) and minimum (r = −0.31) temperatures. Regression results indicated that climatic variables explained about 30% of yield variability (p = 0.02). AquaCrop simulations suggested that by 2046, rainfall may decrease by 33% and temperature rise by 2.4˚C, leading to a 39.9% yield decline. The findings highlight the vulnerability of rain-fed sorghum to climate variability and emphasize the need for adaptation measures to safeguard food security and rural livelihoods in Sudan.</p>
      </abstract>
      <kwd-group kwd-group-type="author-generated" xml:lang="en">
        <kwd>Climate Variability</kwd>
        <kwd>Sorghum Yield</kwd>
        <kwd>AquaCrop Model</kwd>
        <kwd>Gedaref</kwd>
        <kwd>Sudan</kwd>
        <kwd>Rain-Fed Agriculture</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec1">
      <title>1. Introduction</title>
      <p>Agriculture remains central to Sudan’s economy, employing most of the population and contributing nearly 40% to the national GDP [<xref ref-type="bibr" rid="B1">1</xref>]. Sorghum is one of the country’s most important cereal crops, providing both food and income for rural households. In Gedaref State, sorghum dominates rain-fed farming systems that rely heavily on seasonal rainfall. However, increasing temperatures and rainfall variability in recent decades have threatened agricultural production [<xref ref-type="bibr" rid="B2">2</xref>][<xref ref-type="bibr" rid="B3">3</xref>].</p>
      <p>Studies from the Sahel and Horn of Africa regions have similarly shown that warming trends and erratic rainfall adversely affect crop yields [<xref ref-type="bibr" rid="B4">4</xref>]-[<xref ref-type="bibr" rid="B6">6</xref>]. Yet, few studies have quantified these effects for Gedaref. This study fills that gap by assessing long-term climate variability, examining its relationship with sorghum yield, and projecting future impacts using the AquaCrop model.</p>
    </sec>
    <sec id="sec2">
      <title>2. Materials and Methods</title>
      <sec id="sec2dot1">
        <title>2.1. Study Area</title>
        <p>Gedaref State is located in eastern Sudan between latitudes 13˚N - 15˚N and longitudes 33˚E - 36˚E. The area has a semi-arid climate with one rainy season (June-October), characterized by annual rainfall ranging from 500 to 800 mm, and mean temperatures between 25˚C and 35˚C. Soils are predominantly clay, supporting extensive sorghum cultivation under rain-fed systems. See <xref ref-type="fig" rid="fig1">Figure 1</xref><xref ref-type="fig" rid="fig1">Figure 1</xref>.</p>
        <fig id="fig1">
          <label>Figure 1</label>
          <graphic xlink:href="https://html.scirp.org/file/1114545-rId12.jpeg?20251211023809" />
        </fig>
        <p><bold>Figure 1.</bold> Map of Gedaref State, Sudan, showing the study area.</p>
      </sec>
      <sec id="sec2dot2">
        <title>2.2. Data Sources</title>
        <p>Monthly rainfall, maximum and minimum temperatures, and potential evapotranspiration (1961-2014) were obtained from the Sudan Meteorological Authority. Sorghum yield data (1970-2007) were obtained from the Ministry of Agriculture and Forests. Climate projections for 2017-2046 were derived from the NCC-CORDEX regional model, driven by the HadGEM2-ES Global Climate Model (GCM) under the RCP 4.5 scenario, which represents a medium stabilization pathway.</p>
      </sec>
      <sec id="sec2dot3">
        <title>2.3. Analytical Methods</title>
        <p>Trends in temperature and rainfall were analyzed using the Mann-Kendall test and Sen’s slope estimator. The coefficient of variation (CV) was used to assess interannual variability. Pearson correlation and multiple regression analyses determined the relationships between sorghum yield and climate variables. The FAO AquaCrop model [<xref ref-type="bibr" rid="B7">7</xref>] was used to simulate yield response under observed and projected climate conditions. The model was calibrated (R<sup>2</sup> = 0.82, RMSE = 0.41 t/ha) with historical yield data and validated through observed-simulated comparison.</p>
      </sec>
    </sec>
    <sec id="sec3">
      <title>3. Results and Discussion</title>
      <sec id="sec3dot1">
        <title>3.1. Climate Trends</title>
        <p>Both maximum and minimum temperatures and evapotranspiration increased significantly during the study period (p &lt; 0.001). Rainfall showed high variability but a weak, statistically insignificant decline. These results are consistent with regional patterns of increasing temperature and rainfall variability observed across the Sahel and East Africa [<xref ref-type="bibr" rid="B3">3</xref>][<xref ref-type="bibr" rid="B8">8</xref>]. See <xref ref-type="fig" rid="fig2">Figure 2</xref><xref ref-type="fig" rid="fig2">Figure 2</xref>.</p>
        <fig id="fig2">
          <label>Figure 2</label>
          <graphic xlink:href="https://html.scirp.org/file/1114545-rId13.jpeg?20251211023809" />
        </fig>
        <p><bold>Figure 2.</bold> Historical data trend analysis of rainfall, evapotranspiration and temperature, Gadaref area (1961-2014).</p>
      </sec>
      <sec id="sec3dot2">
        <title>3.2. Relationship between Climate and Sorghum Yield</title>
        <p>Sorghum yield was positively correlated with rainfall (r = 0.59) and negatively correlated with maximum temperature (r = −0.34) and minimum temperature (r = −0.31), see <bold>Table 1</bold>. The multiple regression model indicated that climatic factors explained 30% of yield variability (p = 0.02). See <bold>Table 1</bold>.</p>
        <p><bold>Table 1.</bold>Correlation coefficients between sorghum yield and climatic variables.</p>
        <table-wrap id="tbl1">
          <label>Table 1</label>
          <table>
            <tbody>
              <tr>
                <td>Variables</td>
                <td>Correlation Coefficient</td>
                <td>T Calculated</td>
                <td>T Tabulated</td>
                <td>Relationship Description</td>
              </tr>
              <tr>
                <td>Sorghum yield and rainfall</td>
                <td>0.59</td>
                <td>4.792</td>
                <td>1.645</td>
                <td>Significant</td>
              </tr>
              <tr>
                <td>Sorghum yield and maximum temperature</td>
                <td>−0.34</td>
                <td>−2.371</td>
                <td>1.645</td>
                <td>Significant</td>
              </tr>
              <tr>
                <td>Sorghum yield and minimum temperature</td>
                <td>−0.31</td>
                <td>−2.138</td>
                <td>1.645</td>
                <td>Significant</td>
              </tr>
              <tr>
                <td>Sorghum yield and evapotranspiration</td>
                <td>0.25</td>
                <td>1.693</td>
                <td>1.645</td>
                <td>Significant</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>Rainfall remains the dominant factor determining yield variability in Gedaref. Reduced rainfall and increased temperature shorten the crop cycle and increase soil moisture stress. Physiologically, higher maximum temperatures during flowering can induce heat stress, reducing grain set, while higher minimum temperatures can increase nighttime respiration, reducing carbohydrate accumulation. Similar trends have been reported in other semi-arid regions of Sudan and East Africa [<xref ref-type="bibr" rid="B3">3</xref>][<xref ref-type="bibr" rid="B5">5</xref>].</p>
        <p>To contextualize the regression result (30% of explained variance), non-climatic factors such as soil fertility degradation, limited fertilizer use, pest infestations, and policy constraints likely account for much of the unexplained yield variability.</p>
      </sec>
      <sec id="sec3dot3">
        <title>3.3. Projected Future Changes</title>
        <p>AquaCrop simulations projected that by 2046, rainfall may decrease by 33% while temperatures rise by 2.4˚C (mainly driven by a significant increase in minimum temperatures) (see <bold>Table 2</bold>), resulting in an estimated 39.9% reduction in sorghum yield compared to the baseline period (see <xref ref-type="fig" rid="fig3">Figure 3</xref><xref ref-type="fig" rid="fig3">Figure 3</xref>).</p>
        <p><bold>Table 2.</bold>AquaCrop simulation results showing projected yield changes.</p>
        <table-wrap id="tbl2">
          <label>Table 2</label>
          <table>
            <tbody>
              <tr>
                <td>Variables</td>
                <td>Average of Observed Data</td>
                <td>Average of Future Data (2046)</td>
                <td>Change</td>
                <td>Percentage Change</td>
              </tr>
              <tr>
                <td>Rainfall (mm)</td>
                <td>612.43</td>
                <td>409.97</td>
                <td>−202.46</td>
                <td>−33.0%</td>
              </tr>
              <tr>
                <td>Maximum temperature (˚C)</td>
                <td>36.71</td>
                <td>36.73</td>
                <td>+0.02</td>
                <td>+0.05%</td>
              </tr>
              <tr>
                <td>Minimum temperature (˚C)</td>
                <td>21.36</td>
                <td>23.75</td>
                <td>+2.39</td>
                <td>+11.2%</td>
              </tr>
              <tr>
                <td>Sorghum yield (simulated)</td>
                <td>
                </td>
                <td>—</td>
                <td>↓</td>
                <td>−39.9%</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <fig id="fig3">
          <label>Figure 3</label>
          <graphic xlink:href="https://html.scirp.org/file/1114545-rId14.jpeg?20251211023809" />
        </fig>
        <p><bold>Figure 3.</bold> Simulated sorghum yield decline under future climate scenarios.</p>
      </sec>
      <sec id="sec3dot4">
        <title>3.4. Policy Implications</title>
        <p>The results of this study underline the urgent need for climate-resilient agricultural strategies in Gedaref State. Policymakers should prioritize:</p>
        <p>Promotion of drought-tolerant sorghum varieties and climate-smart farming practices.Investment in small-scale irrigation and water harvesting systems to reduce dependence on erratic rainfall.Enhancement of agricultural extension services and farmer capacity building on climate risk management.Integration of seasonal climate forecasting into local agricultural planning.Supportive policies that encourage sustainable soil management and access to inputs (fertilisers, seeds, technology).</p>
        <p>These measures will help strengthen rural livelihoods and ensure food security under changing climate conditions.</p>
      </sec>
    </sec>
    <sec id="sec4">
      <title>4. Conclusion</title>
      <p>This study demonstrates that climate variability—especially increased temperature and reduced rainfall—significantly influences sorghum yields in Gedaref State. Climate factors accounted for roughly one-third of observed yield variability. Future projections suggest potential yield declines of about 40% by mid-century, posing a major threat to food security. Policy responses should focus on promoting climate-smart agriculture, water conservation, and resilient crop varieties to sustain productivity in rain-fed systems.</p>
    </sec>
    <sec id="sec5">
      <title>Acknowledgements</title>
      <p>The author expresses sincere gratitude to Dr. Fredrick K. Karanja, Department of Meteorology, University of Nairobi, for his valuable supervision and guidance. Appreciation is also extended to the Sudan Meteorological Authority and the Ministry of Agriculture and Forestry for providing data used in this research.</p>
    </sec>
    <sec id="sec6">
      <title>Author’s Contribution</title>
      <p>The author, Noah Adam Hudo, designed the study, collected and analyzed data, conducted modelling, interpreted results, and prepared the manuscript.</p>
    </sec>
  </body>
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