<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article">
 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">
    ojmh
   </journal-id>
   <journal-title-group>
    <journal-title>
     Open Journal of Modern Hydrology
    </journal-title>
   </journal-title-group>
   <issn pub-type="epub">
    2163-0461
   </issn>
   <issn publication-format="print">
    2163-0496
   </issn>
   <publisher>
    <publisher-name>
     Scientific Research Publishing
    </publisher-name>
   </publisher>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="doi">
    10.4236/ojmh.2025.152013
   </article-id>
   <article-id pub-id-type="publisher-id">
    ojmh-142065
   </article-id>
   <article-categories>
    <subj-group subj-group-type="heading">
     <subject>
      Articles
     </subject>
    </subj-group>
    <subj-group subj-group-type="Discipline-v2">
     <subject>
      Earth 
     </subject>
     <subject>
       Environmental Sciences
     </subject>
    </subj-group>
   </article-categories>
   <title-group>
    Seasonal and Spatio-Temporal Distribution of Nutrients in the Hula Valley after Drainage: C: Carbonate and Sulfate
   </title-group>
   <contrib-group>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Moshe
      </surname>
      <given-names>
       Gophen
      </given-names>
     </name>
    </contrib>
   </contrib-group> 
   <aff id="affnull">
    <addr-line>
     aMIGAL-Galilee Scientific Research Institute, Kiryat Shmona, Israel
    </addr-line> 
   </aff> 
   <pub-date pub-type="epub">
    <day>
     14
    </day> 
    <month>
     02
    </month>
    <year>
     2025
    </year>
   </pub-date> 
   <volume>
    15
   </volume> 
   <issue>
    02
   </issue>
   <fpage>
    204
   </fpage>
   <lpage>
    217
   </lpage>
   <history>
    <date date-type="received">
     <day>
      16,
     </day>
     <month>
      December
     </month>
     <year>
      2024
     </year>
    </date>
    <date date-type="published">
     <day>
      18,
     </day>
     <month>
      December
     </month>
     <year>
      2024
     </year> 
    </date> 
    <date date-type="accepted">
     <day>
      18,
     </day>
     <month>
      April
     </month>
     <year>
      2025
     </year> 
    </date>
   </history>
   <permissions>
    <copyright-statement>
     © Copyright 2014 by authors and Scientific Research Publishing Inc. 
    </copyright-statement>
    <copyright-year>
     2014
    </copyright-year>
    <license>
     <license-p>
      This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/
     </license-p>
    </license>
   </permissions>
   <abstract>
    The Hula wetland and old Lake Hula drainage were completed in 1957, and the land was converted into agricultural use. However, the adoption of inappropriate irrigation methods led to several critical concerns, including the oxidation of organic matter, frequent outbreaks of subsurface unsecured fire, soil surface subsidence and disruption of the hydrological system. Additionally, nitrogen mineralization created an accumulation of nitrate loads, which increased the risk of leaching into Lake Kinneret and deteriorating its water quality. The natural intrusion of gypsum into peat soil’s organic matter has contributed to increased levels of sulfate and calcium, enhancing soil salinization. Consequently, a reclamation project was implemented, the Hula Project (HP). The dependence of climate conditions and consequently soil moisture on Alkalinity (ALK), Total Dissolved Solids (TDS) and Sulfate (SO
    <sub>4</sub>) concentrations, Electrical Conductivity (EC), and pH properties within the Peat soil drained waters composition was documented. A temporal decline of ALk, TDS, SO
    <sub>4</sub>, EC, and, to a lesser extent, pH measures during 1994-2010 and an increase later were indicated. The nutrient migration dynamic is evaluated through spatial and temporal dimensions to confirm the dominant effect of soil wettability with negligible fluctuation of the pH values.
   </abstract>
   <kwd-group> 
    <kwd>
     Hula
    </kwd> 
    <kwd>
      Peat
    </kwd> 
    <kwd>
      EC
    </kwd> 
    <kwd>
      TDS
    </kwd> 
    <kwd>
      Alkalinity
    </kwd> 
    <kwd>
      Sulfate
    </kwd>
   </kwd-group>
  </article-meta>
 </front>
 <body>
  <sec id="s1">
   <title>1. Introduction</title>
   <p>The Hula Valley and Lake Kinneret are located in the northern part of Israel’s Syrian-African Great Rift Valley. Lake Kinneret is the only natural freshwater lake in Israel and its water quality including the cardinal impact of nutrient migrations from the Hula Valley is therefore a national concern. The total annual national water supply is 2.11 bcm (10<sup>9</sup> m<sup>3</sup>), of which 0.55 bcm is sourced from the Kinneret-Jordan water system. The area of the Kinneret drainage basin is 2730 km<sup>2</sup> and is located mostly to the north of the lake, of which the total Hula Valley is about 200 km<sup>2</sup>. Three major headwater rivers, The Hatzbani, Banyas, and Dan originate from the Hermon Mountain region and flow into the northern part of the Kinneret drainage basin. These rivers converge to form the Jordan River. Prior to the late 1950s, the Jordan River flowed through the Hula Valley through three tributaries that inflowed into the old Lake Hula. From the old Lake Hula, situated at an altitude of 61 - 68 masl (above sea level), the Jordan River flows downstream into Lake Kinneret (Mean WL 211 mbsl) for a distance of approximately 15 km. Before the drainage of the Hula wetlands and old Lake Hula, the Valley was characterized by old Lake Hula and 3500 ha of swampland. The swampy area was totally covered by water in the winter and partly covered in the summer. To the north of the swamps was an area (3200 ha) where water table levels were high in winter, thus making agricultural cultivation impossible. During the summer, when underground water levels declined, this 3200-ha land surface was efficiently cultivated. After drainage, land use was converted into agricultural management. Several processes of organic matter oxidation and the usage of inappropriate irrigation methods which enhanced soil properties deterioration initiated concerns about Kinneret water quality: Frequent outbreaks of subsurface unsecured fire; Soil surface subsidence deteriorating the hydrological system; Nitrogen mineralization has led to the accumulation of nitrates, increasing the risk of partial migration into Lake Kinneret causing deterioration of its water quality. A reclamation project was implemented, the Hula Project (HP), resuming its current 30 years of existence. The Intrusion of Gypsum into the Peat organic matter has contributed to increased levels of sulfate and calcium, enhancing soil salinization. The present study examines the impact of climate conditions and consequently soil moisture on Alkalinity (ALK), Total Dissolved Solids (TDS) and Sulfate (SO<sub>4</sub>) concentrations and Electrical Conductivity (EC), and pH properties on drained waters from the Peat Soil in the Hula Valley. The objective of the present study is to evaluate the impact of the HP on the fluctuations of Sulfate, Carbonate, Electrical Conductivity and pH in the Hula Peat soil-drained waters. The Hula Project challenges were agricultural crops improvement, prevention of soil properties devastation and Kinneret water quality protection. Nevertheless, information about Peat soil response to ecological changes aimed at management predictability was incomplete. Consequently, evaluation of temporal and seasonal distribution of nutrients (SO<sub>4</sub>, Alkalinity, TDS) and physicochemical parameters (EC, pH) are critically required.</p>
  </sec><sec id="s2">
   <title>2. Material and Methods</title>
   <sec id="s2_1">
    <title>2.1. Study Area</title>
    <fig id="fig1" position="float">
     <label>Figure 1</label>
     <caption>
      <title>Figure 1. Chart map of the Hula Project territory: Inflow and drainage water lines and Peat soil blocks regions are outlined: Ecosystem compartments are arrowed; black dots are borehole drill locations for the underground water sampling. (Modified from HPDB 1994-2019)</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId16.jpeg?20250421031334" />
    </fig>
   </sec>
   <sec id="s2_2">
    <title>2.2. Chemistry</title>
    <p>Analysis of Sulfate, Alkalinity (Carbonate), Total Dissolve Solids (TDS), Total Suspended Solids (TSS), pH, and Electrical Conductivity (EC) (Specific Conductance) was carried out on weekly and bi-weekly sampled water in Station 57: the inflow of Canal Z waters into Lake-Agmon-Hula (LAH), the optimal presentation of Peat soil drained water. Hula Valley coordinates: 33˚06'12'' North; 35˚36'33'' East. Hydrological Balance of Lake-Agmon-Hula (10<sup>6</sup> m<sup>3</sup>/year) as averaged for 2008-2018.</p>
   </sec>
   <sec id="s2_3">
    <title>2.3. Inflow</title>
    <p>From Reconstructed Jordan—2.2; Through Canal Z (101)—6. 5; From Eastern Peat soil—0.28; Rain—0.27: Total—9.2.</p>
   </sec>
   <sec id="s2_4">
    <title>2.4. Outflow</title>
    <p>Agmon effluent—5.9; Irrigation consumption—1.7; Evaporation—1.5; Total—9.2.</p>
    <p>Method of Analysis were <xref ref-type="bibr" rid="scirp.142065-1">
      [1]
     </xref>:</p>
    <p>Total Dissolved Solids—180˚C evaporation.</p>
    <p>Sulfate ( 
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
       <msubsup> 
        <mrow> 
         <mtext>
           SO 
         </mtext> 
        </mrow> 
        <mn>
          4 
        </mn> 
        <mrow> 
         <mn>
           2 
         </mn> 
         <mo>
           − 
         </mo> 
        </mrow> 
       </msubsup> 
      </mrow> 
     </math>)—Turbidimetric (BaCl<sub>2</sub>) method.</p>
    <p>Alkalinity (CaCO<sub>3</sub>)—Titration method.</p>
    <p>pH—pH meter.</p>
    <p>The data was obtained from the Hula Project Monitor Program:</p>
    <p>MIGAL-Hula Project Data Base <xref ref-type="bibr" rid="scirp.142065-2">
      [2]
     </xref>—MIGAL-Galilee Scientific Research Institute, Jewish National Fund and Israel Water Authority <xref ref-type="bibr" rid="scirp.142065-3">
      [3]
     </xref>-<xref ref-type="bibr" rid="scirp.142065-7">
      [7]
     </xref>.</p>
   </sec>
   <sec id="s2_5">
    <title>2.5. Statistical Methods</title>
    <p>Statistical evaluation included the following methods: Quadratic and Linear Regressions (w/CI 95%). Quadratic regressions (w/CI 95%) are used for modeling relationships between variable distributions with a parabolic best-fit curve, as most likely relevant to the analyses presented in this paper.</p>
   </sec>
  </sec><sec id="s3">
   <title>3. Results</title>
   <p>Results given in <xref ref-type="table" rid="table1">
     Table 1
    </xref> &amp; <xref ref-type="table" rid="table2">
     Table 2
    </xref> indicate the tight correlation between Alkalinity, Total Dissolved Solids, Electrical Conductivity, and Sulfate suggested to be dependents of soil moisture which is strongly affected by climate (rain capacity) conditions. The high correlation between EC, TDS and Alkalinity emphasizes the impact of soil moisture. The exceptionally low level of fluctuations presented by pH and TSS values is an indication of the ineffective impact of soil moisture on pH and TSS. (<xref ref-type="fig" rid="figFigures 1-16">
     Figures 1-16
    </xref>)</p>
   <table-wrap id="table1">
    <label>
     <xref ref-type="table" rid="table1">
      Table 1
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.142065-"></xref>Table 1. Grand total mean, SD, Maximal, Minimal and % of SD of the Mean (1994-2019) Nutrient concentrations measured in Station 57.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td custom-top-td acenter" width="30.37%"><p style="text-align:center">Nutrient</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="12.42%"><p style="text-align:center">Mean</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="16.31%"><p style="text-align:center">SD</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="14.32%"><p style="text-align:center">Min.</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="14.43%"><p style="text-align:center">Max.</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="12.15%"><p style="text-align:center">% SD</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td aleft" width="30.37%"><p style="text-align:left">ALK (CaCO<sub>3</sub> ppm)</p></td> 
      <td class="custom-top-td acenter" width="12.42%"><p style="text-align:center">213.2</p></td> 
      <td class="custom-top-td acenter" width="16.31%"><p style="text-align:center">148.4</p></td> 
      <td class="custom-top-td acenter" width="14.32%"><p style="text-align:center">64.7</p></td> 
      <td class="custom-top-td acenter" width="14.43%"><p style="text-align:center">527.3</p></td> 
      <td class="custom-top-td acenter" width="12.15%"><p style="text-align:center">70</p></td> 
     </tr> 
     <tr> 
      <td class="aleft" width="30.37%"><p style="text-align:left">EC (mS)</p></td> 
      <td class="acenter" width="12.42%"><p style="text-align:center">1.17</p></td> 
      <td class="acenter" width="16.31%"><p style="text-align:center">0.65</p></td> 
      <td class="acenter" width="14.32%"><p style="text-align:center">0.5</p></td> 
      <td class="acenter" width="14.43%"><p style="text-align:center">2.57</p></td> 
      <td class="acenter" width="12.15%"><p style="text-align:center">56</p></td> 
     </tr> 
     <tr> 
      <td class="aleft" width="30.37%"><p style="text-align:left">pH</p></td> 
      <td class="acenter" width="12.42%"><p style="text-align:center">7.25</p></td> 
      <td class="acenter" width="16.31%"><p style="text-align:center">0.14</p></td> 
      <td class="acenter" width="14.32%"><p style="text-align:center">7.05</p></td> 
      <td class="acenter" width="14.43%"><p style="text-align:center">7.59</p></td> 
      <td class="acenter" width="12.15%"><p style="text-align:center">2</p></td> 
     </tr> 
     <tr> 
      <td class="aleft" width="30.37%"><p style="text-align:left">SO<sub>4</sub> (ppm)</p></td> 
      <td class="acenter" width="12.42%"><p style="text-align:center">351.2</p></td> 
      <td class="acenter" width="16.31%"><p style="text-align:center">312.1</p></td> 
      <td class="acenter" width="14.32%"><p style="text-align:center">63.8</p></td> 
      <td class="acenter" width="14.43%"><p style="text-align:center">1010.4</p></td> 
      <td class="acenter" width="12.15%"><p style="text-align:center">89</p></td> 
     </tr> 
     <tr> 
      <td class="aleft" width="30.37%"><p style="text-align:left">TDS (ppm)</p></td> 
      <td class="acenter" width="12.42%"><p style="text-align:center">1086.4</p></td> 
      <td class="acenter" width="16.31%"><p style="text-align:center">711.5</p></td> 
      <td class="acenter" width="14.32%"><p style="text-align:center">365</p></td> 
      <td class="acenter" width="14.43%"><p style="text-align:center">2516</p></td> 
      <td class="acenter" width="12.15%"><p style="text-align:center">65</p></td> 
     </tr> 
     <tr> 
      <td class="custom-bottom-td aleft" width="30.37%"><p style="text-align:left">TSS (ppm)</p></td> 
      <td class="custom-bottom-td acenter" width="12.42%"><p style="text-align:center">25.2</p></td> 
      <td class="custom-bottom-td acenter" width="16.31%"><p style="text-align:center">4.92</p></td> 
      <td class="custom-bottom-td acenter" width="14.32%"><p style="text-align:center">18.48</p></td> 
      <td class="custom-bottom-td acenter" width="14.43%"><p style="text-align:center">34.9</p></td> 
      <td class="custom-bottom-td acenter" width="12.15%"><p style="text-align:center">20</p></td> 
     </tr> 
    </table>
   </table-wrap>
   <table-wrap id="table2">
    <label>
     <xref ref-type="table" rid="table2">
      Table 2
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.142065-"></xref>Table 2. Parameters of Linear Regressions in between nutrient and Sulfate (SO<sub>4</sub>), nutrients and Alkalinity (ALK) and Electrical Conductivity (EC) and Total Suspended Solids. S = Significant, NS = Not Significant. The high percentage of SD from the Mean (<xref ref-type="table" rid="table1">
       Table 1
      </xref>) confirms the impact of climate conditions variability and the adhesion linkage weakness of those nutrients to the Peat soil particles. Abrupt release of the nutrients from the soil particles into the pore waters as a response to rain or irrigation wettability.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td custom-top-td acenter" width="24.99%"><p style="text-align:center">Nutrients</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="25.01%"><p style="text-align:center">r<sup>2</sup></p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="24.99%"><p style="text-align:center">p</p></td> 
      <td class="custom-bottom-td custom-top-td acenter" width="25.01%"><p style="text-align:center">Significance</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td acenter" width="24.99%"><p style="text-align:center">ALK/SO<sub>4</sub></p></td> 
      <td class="custom-top-td acenter" width="25.01%"><p style="text-align:center">0.9854</p></td> 
      <td class="custom-top-td acenter" width="24.99%"><p style="text-align:center">&lt;0.0001</p></td> 
      <td class="custom-top-td acenter" width="25.01%"><p style="text-align:center">S</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="24.99%"><p style="text-align:center">TDS/SO<sub>4</sub></p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">0.9735</p></td> 
      <td class="acenter" width="24.99%"><p style="text-align:center">&lt;0.0001</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">S</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="24.99%"><p style="text-align:center">TSS/SO<sub>4</sub></p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">0.3671</p></td> 
      <td class="acenter" width="24.99%"><p style="text-align:center">0.0368</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">S</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="24.99%"><p style="text-align:center">EC/SO<sub>4</sub></p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">0.9835</p></td> 
      <td class="acenter" width="24.99%"><p style="text-align:center">&lt;0.0001</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">S</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="24.99%"><p style="text-align:center">pH/SO<sub>4</sub></p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">0.0928</p></td> 
      <td class="acenter" width="24.99%"><p style="text-align:center">0.3356</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">NS</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="24.99%"><p style="text-align:center">EC/ALK</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">0.9842</p></td> 
      <td class="acenter" width="24.99%"><p style="text-align:center">&lt;0.0001</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">S</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="24.99%"><p style="text-align:center">TDS/ALK</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">0.9868</p></td> 
      <td class="acenter" width="24.99%"><p style="text-align:center">&lt;0.0001</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">S</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="24.99%"><p style="text-align:center">TSS/ALK</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">0.3858</p></td> 
      <td class="acenter" width="24.99%"><p style="text-align:center">0.1115</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">NS</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="24.99%"><p style="text-align:center">pH/ALK</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">0.0985</p></td> 
      <td class="acenter" width="24.99%"><p style="text-align:center">0.6272</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">NS</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="24.99%"><p style="text-align:center">EC/TDS</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">0.9532</p></td> 
      <td class="acenter" width="24.99%"><p style="text-align:center">&lt;0.0001</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">S</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="24.99%"><p style="text-align:center">EC/TSS</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">0.9669</p></td> 
      <td class="acenter" width="24.99%"><p style="text-align:center">&lt;0.0001</p></td> 
      <td class="acenter" width="25.01%"><p style="text-align:center">S</p></td> 
     </tr> 
     <tr> 
      <td class="custom-bottom-td acenter" width="24.99%"><p style="text-align:center">TSS/TDS</p></td> 
      <td class="custom-bottom-td acenter" width="25.01%"><p style="text-align:center">0.2941</p></td> 
      <td class="custom-bottom-td acenter" width="24.99%"><p style="text-align:center">0.0685</p></td> 
      <td class="custom-bottom-td acenter" width="25.01%"><p style="text-align:center">NS</p></td> 
     </tr> 
    </table>
   </table-wrap>
   <p>The similarity of seasonal distribution of concentrations of TDS, SO<sub>4</sub>, Alkalinity, and EC, and rain capacity within the Peat soil (Station 57) drained waters is clearly shown in <xref ref-type="fig" rid="figFigures 2-6">
     Figures 2-6
    </xref>.</p>
   <fig id="fig2" position="float">
    <label>Figure 2</label>
    <caption>
     <title>Figure 2. Quadratic regression (w/95%CI) plot between annual mean (1994-2019) of rain capacity and month. Linear regression parameters (r<sup>2</sup>, p) are given (S-significant).</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId19.jpeg?20250421031337" />
   </fig>
   <fig id="fig3" position="float">
    <label>Figure 3</label>
    <caption>
     <title>Figure 3. Quadratic regression (w/95%CI) plot between annual mean (Station 57) (1994-2019) of Alkalinity (ALK) (ppm CaCO<sub>3</sub>) and month. Linear regression parameters (r<sup>2</sup>, p) are given (S-significant).</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId20.jpeg?20250421031337" />
   </fig>
   <fig id="fig4" position="float">
    <label>Figure 4</label>
    <caption>
     <title>Figure 4. Quadratic regression (w/95%CI) plot between annual mean (Station 57) (1994-2019) of Electrical Conductivity (EC) (mS) and month. Linear regression parameters (r<sup>2</sup>, p) are given (S-significant).</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId21.jpeg?20250421031338" />
   </fig>
   <fig id="fig5" position="float">
    <label>Figure 5</label>
    <caption>
     <title>Figure 5. Quadratic regression (w/95%CI) plot between annual mean (Station 57) (1994-2019) of Sulfate (SO<sub>4</sub>) concentration (ppm) and month. Linear regression parameters (r<sup>2</sup>, p) are given (S-significant).</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId22.jpeg?20250421031338" />
   </fig>
   <fig id="fig6" position="float">
    <label>Figure 6</label>
    <caption>
     <title>Figure 6. Quadratic regression (w/95%CI) plot between annual mean (Station 57) (1994-2019) of Total Dissolved Solids (TDS) concentration (ppm) and month. Linear regression parameters (r<sup>2</sup>, p) are given (S-significant).</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId23.jpeg?20250421031338" />
   </fig>
   <p>The insignificance of nonlinear seasonal distribution (monthly) relations of pH and the concentration of Total Suspended Solids (TSS) within the Peat spill drained waters (Station 57) is shown in <xref ref-type="fig" rid="fig7">
     Figure 7
    </xref> and <xref ref-type="fig" rid="fig8">
     Figure 8
    </xref>.</p>
   <p>The obvious linear significant relation between TDS and EC is confirmed in <xref ref-type="fig" rid="fig9">
     Figure 9
    </xref>. The higher the soil moisture, accompanied by salt flushing, the greater the enhancement of EC.</p>
   <p>Obvious Inverse relations of TDS and EC with TSS are consequently confirmed in <xref ref-type="fig" rid="fig9">
     Figure 9
    </xref> &amp; <xref ref-type="fig" rid="fig10">
     Figure 10
    </xref>.</p>
   <p>Results of temporal distribution given in <xref ref-type="fig" rid="figFigures 12-15">
     Figures 12-15
    </xref> indicate a decline in nutrient (Alkalinity, SO<sub>4</sub>) concentrations and EC and TDS during 1994-2009 and increase onwards. Information about distributional pattern of rain capacity and consequently intensity, presented as annual rainy days is given in <xref ref-type="fig" rid="fig16">
     Figure 16
    </xref>. The pattern similarity of temporal rain capacity and nutrient distribution is emphasized.</p>
   <fig id="fig7" position="float">
    <label>Figure 7</label>
    <caption>
     <title>Figure 7. Quadratic regression (w/95%CI) plot between annual mean (Station 57) (1994-2019) of pH and month. Linear regression parameters (r<sup>2</sup>, p) are given (NS = Not Significant).</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId24.jpeg?20250421031338" />
   </fig>
   <fig id="fig8" position="float">
    <label>Figure 8</label>
    <caption>
     <title>Figure 8. Quadratic regression (w/95%CI) plot between annual mean (Station 57) (1994-2019) of Total Suspended Solids (TSS) concentration (ppm) and month. Linear regression parameters (r<sup>2</sup>, p) are given (NS—Not significant).</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId25.jpeg?20250421031338" />
   </fig>
   <fig id="fig9" position="float">
    <label>Figure 9</label>
    <caption>
     <title>Figure 9. Linear regression (w/95%CI) plot between annual mean (Station 57) (1994-2019) of Total Dissolved Solids (TDS) concentration (ppm) and Electrical conductivity (EC) (mS).</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId26.jpeg?20250421031338" />
   </fig>
   <fig id="fig10" position="float">
    <label>Figure 10</label>
    <caption>
     <title>Figure 10. Linear regression (w/95%CI) plot between annual mean (Station 57) (1994-2019) of Total Dissolved Solids (TDS) and Total Suspended Solids (TSS) concentrations (ppm).</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId27.jpeg?20250421031337" />
   </fig>
   <fig id="fig11" position="float">
    <label>Figure 11</label>
    <caption>
     <title>Figure 11. Linear regression (w/95%CI) plot between annual mean (Station 57) (1994-2019) of Electrical Conductivity (EC) (mS) and Total Suspended Solids (TSS) concentration (ppm).</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId28.jpeg?20250421031337" />
   </fig>
   <fig id="fig12" position="float">
    <label>Figure 12</label>
    <caption>
     <title>Figure 12. Quadratic regression (w/95%CI) plot between temporal, (annual mean) (Station 57) (1994-2019) of Alkalinity (CaCO<sub>3 </sub>ppm) concentration and Years.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId29.jpeg?20250421031337" />
   </fig>
   <fig id="fig13" position="float">
    <label>Figure 13</label>
    <caption>
     <title>Figure 13. Quadratic regression (w/95%CI) plot between temporal (annual mean) (Station 57) (1994-2019) of Sulfate (SO<sub>4</sub>) concentration (ppm) and Years.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId30.jpeg?20250421031338" />
   </fig>
   <fig id="fig14" position="float">
    <label>Figure 14</label>
    <caption>
     <title>Figure 14. Quadratic regression (w/95%CI) plot between temporal (annual mean) (Station 57) (1994-2019) of Electrical Conductivity (EC) (mS) and Years.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId31.jpeg?20250421031338" />
   </fig>
   <fig id="fig15" position="float">
    <label>Figure 15</label>
    <caption>
     <title>Figure 15. Quadratic regression (w/95%CI) plot between temporal (annual mean) (Station 57) (1994-2019) of Total Dissolved Solids (TDS) concentrations (ppm) and Years.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId32.jpeg?20250421031338" />
   </fig>
   <fig id="fig16" position="float">
    <label>Figure 16</label>
    <caption>
     <title>Figure 16. Fractional Polynomial plot of total number of rainy days per annum and Years during 1994-2024.</title>
    </caption>
    <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/1630351-rId33.jpeg?20250421031338" />
   </fig>
  </sec><sec id="s4">
   <title>4. Discussion</title>
   <p>Cases of wetlands drainage aimed at extending food production land use are well known in Europe and the USA <xref ref-type="bibr" rid="scirp.142065-8">
     [8]
    </xref>-<xref ref-type="bibr" rid="scirp.142065-10">
     [10]
    </xref>. The drainage of the Hula Valley concluded the search for food production combined with the prevention of Lake Kinneret water quality. Soil Survey <xref ref-type="bibr" rid="scirp.142065-11">
     [11]
    </xref> confirmed 21% (750 ha), 34% (1200 ha), 19% (660 ha) and 26% (910 ha) of the Hula Valley soils are lacustrine marl, Peat soil, Transition Peat soil and alluvial soil respectively <xref ref-type="bibr" rid="scirp.142065-12">
     [12]
    </xref>. The Peat soil in the Hula Valley contains huge loads of Gypsum (CaSO<sub>4</sub>) and migration of 
    <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <msubsup> 
       <mrow> 
        <mtext>
          SO 
        </mtext> 
       </mrow> 
       <mn>
         4 
       </mn> 
       <mrow> 
        <mn>
          2 
        </mn> 
        <mo>
          − 
        </mo> 
       </mrow> 
      </msubsup> 
     </mrow> 
    </math>—from the Peat-Soil into Lake Kinneret might have an impact on water quality. A long period of heavy bloom-forming P. gatunenze domination was replaced by Cyanobacteria including N<sub>2</sub>-fixers in Lake Kinneret. The competitive properties of 
    <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <msubsup> 
       <mrow> 
        <mtext>
          SO 
        </mtext> 
       </mrow> 
       <mn>
         4 
       </mn> 
       <mrow> 
        <mn>
          2 
        </mn> 
        <mo>
          − 
        </mo> 
       </mrow> 
      </msubsup> 
     </mrow> 
    </math> with Molybdenum were documented <xref ref-type="bibr" rid="scirp.142065-13">
     [13]
    </xref>-<xref ref-type="bibr" rid="scirp.142065-15">
     [15]
    </xref>. In the Lake Kinneret-Hula ecosystem, enhancement or reduction of supplemental 
    <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <msubsup> 
       <mrow> 
        <mtext>
          SO 
        </mtext> 
       </mrow> 
       <mn>
         4 
       </mn> 
       <mrow> 
        <mn>
          2 
        </mn> 
        <mo>
          − 
        </mo> 
       </mrow> 
      </msubsup> 
     </mrow> 
    </math> induces strengthening or weakening competition with 
    <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <msubsup> 
       <mrow> 
        <mtext>
          MoO 
        </mtext> 
       </mrow> 
       <mn>
         4 
       </mn> 
       <mrow> 
        <mn>
          2 
        </mn> 
        <mo>
          − 
        </mo> 
       </mrow> 
      </msubsup> 
     </mrow> 
    </math> affecting suppression of N<sub>2</sub>-Fixer Cyanobacterium. Consequently, sulfate migration from the Hula Valley into Lake Kinneret might have an impact on the development of the Bloom Forming Harmful Cyanobacteria (BFHC).</p>
   <p>Previous studies have documented the high content of Gypsum (CaSO<sub>4</sub>) in the Hula Peat soil <xref ref-type="bibr" rid="scirp.142065-3">
     [3]
    </xref>-<xref ref-type="bibr" rid="scirp.142065-7">
     [7]
    </xref>. The Gypsum is significantly dissolved in water releasing free Ca<sup>2+</sup> and 
    <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <msubsup> 
       <mrow> 
        <mtext>
          SO 
        </mtext> 
       </mrow> 
       <mn>
         4 
       </mn> 
       <mrow> 
        <mn>
          2 
        </mn> 
        <mo>
          − 
        </mo> 
       </mrow> 
      </msubsup> 
     </mrow> 
    </math>. The decline of rainfall, and consequently lowered river discharge and suppression of 
    <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <msubsup> 
       <mrow> 
        <mtext>
          SO 
        </mtext> 
       </mrow> 
       <mn>
         4 
       </mn> 
       <mrow> 
        <mn>
          2 
        </mn> 
        <mo>
          − 
        </mo> 
       </mrow> 
      </msubsup> 
     </mrow> 
    </math> concentrations and loads in the Hula Valley runoffs, River Jordan and Lake Kinneret waters were documented <xref ref-type="bibr" rid="scirp.142065-16">
     [16]
    </xref>. Carbonate sources and consequently Alkalinity properties in the Peat soil are mostly from lacustrine marl sediments. The documented <xref ref-type="bibr" rid="scirp.142065-17">
     [17]
    </xref> linkage between high alkalinity and high base cations content, such as Ca<sup>2+</sup>, and Mg<sup>2+</sup>, providing suitable conditions for the precipitation of Fe is relevant to the Hula Peat soil ecosystem. The sulfate sources include the breakdown of proteins into amino acids, which releases oxidized Sulfur. Sulfate existence is dependent on aerobic conditions maintenance. Sulfide production through Anaerobic conditions development was not documented in the Hula Peat soil whilst rarely traced (7 - 8 µM) in the sediments of Lake Agmon-Hula <xref ref-type="bibr" rid="scirp.142065-18">
     [18]
    </xref>. Enhanced activity of anaerobic sulfate-reducing bacteria was observed in surface soils from P-enriched areas, which yielded 10<sup>3</sup> to 10<sup>4</sup> times higher numbers of these bacteria compared to soils from P-unimpacted sites <xref ref-type="bibr" rid="scirp.142065-19">
     [19]
    </xref>. Agricultural crops within the Hula Peat Soil land are intensively P-fertilized <xref ref-type="bibr" rid="scirp.142065-12">
     [12]
    </xref> whilst anaerobic conditions are very scarce in the surface soil layer. Therefore, reducing Sulfate to sulfide is not predicted. Frequencies of anoxic condition within the shallow layers of Hula Peat soil are presently scarce but it might be possible in deeper layers contacting crops root system. Therefore, the prediction of sulfate reductive bacteria existence and toxic sulfide production within the agricultural crops root system is negligible.</p>
   <p>The migration of Gypsum (CaSO<sub>4</sub>) derivate, the 
    <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
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        </mtext> 
       </mrow> 
       <mn>
         4 
       </mn> 
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        <mn>
          2 
        </mn> 
        <mo>
          − 
        </mo> 
       </mrow> 
      </msubsup> 
     </mrow> 
    </math> is moisture dependent, the higher the soil moisture, the higher is 
    <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
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         4 
       </mn> 
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        <mn>
          2 
        </mn> 
        <mo>
          − 
        </mo> 
       </mrow> 
      </msubsup> 
     </mrow> 
    </math> drained concentration and vice versa <xref ref-type="bibr" rid="scirp.142065-18">
     [18]
    </xref> <xref ref-type="bibr" rid="scirp.142065-20">
     [20]
    </xref>. Dryness conditions therefore initiate the decline of 
    <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <msubsup> 
       <mrow> 
        <mtext>
          SO 
        </mtext> 
       </mrow> 
       <mn>
         4 
       </mn> 
       <mrow> 
        <mn>
          2 
        </mn> 
        <mo>
          − 
        </mo> 
       </mrow> 
      </msubsup> 
     </mrow> 
    </math> migration from the Hula Valley towards Lake Kinneret.</p>
   <p>Averaged (SD) nutrient concentrations in water samples collected in Station 57 close to the beginning of Hula Project implementation (1994-1996) indicate wetting after a long period of dryness characterized by fluctuated values and percentage SD levels <xref ref-type="bibr" rid="scirp.142065-18">
     [18]
    </xref>:</p>
   <p>Ca<sup>2+</sup>—403 (SD 236) ppm.</p>
   <p>
    <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
      <msubsup> 
       <mrow> 
        <mtext>
          SO 
        </mtext> 
       </mrow> 
       <mn>
         4 
       </mn> 
       <mrow> 
        <mn>
          2 
        </mn> 
        <mo>
          − 
        </mo> 
       </mrow> 
      </msubsup> 
     </mrow> 
    </math>—997 (SD 752) ppm.</p>
   <p>Alkalinity (Carbonate)—192 (SD 61) ppm.</p>
   <p>pH—6.6 - 7.6.</p>
   <p>Results given in <xref ref-type="table" rid="table1">
     Table 1
    </xref> &amp; <xref ref-type="table" rid="table2">
     Table 2
    </xref> indicate two major geochemical components which control the EC measure of the Peat soil drained waters (Station 57): Carbonate as Alkalinity (ppm CaCO<sub>3</sub>) and Sulfate capacities. Unpredictable, negligible pH level of fluctuation was indicated. The distributional pattern similarity of seasonal (monthly) changes in nutrient concentrations (<xref ref-type="fig" rid="fig3-6">
     Figure 3-6
    </xref>) highlighted the potential of its dependence on climate conditions: rainy winter-spring and dry summer-fall months (<xref ref-type="fig" rid="fig2">
     Figure 2
    </xref>). During winter-spring time, soil moisture is high as the result of rain wettability whilst during post rainy season, summer-fall months, soil moisture declines. Water content and wettability are probably the major factors that enhance nutrient migration and consequently induce the similarity of the major nutrient distribution patterns. Moreover, the evaluation of the correlation between nutrient migrations and annual rain capacity did not indicate a temporal trend. Whereas consideration of the temporal distribution of rain capacity in terms of the number of rainy days has indicated migrated nutrient concentration enhancement through an increased number of rainy days. In other words, the rain capacity is an insufficient factor and its distribution as a number of rainy days distribution and also by intensity, is critical (<xref ref-type="fig" rid="figFigures 12-16">
     Figures 12-16
    </xref>). The dominant impact of soil moisture on nutrient migrations is a combinative effect of capacity and seasonal prolongation. The dominant impact of soil moisture on nutrient migrations in the Peat soil is also supported by the distinct relation between TDS and EC (<xref ref-type="fig" rid="fig8">
     Figure 8
    </xref>). Moreover, the complex interactions between TDS, TSS and EC are shown in <xref ref-type="fig" rid="figFigures 9-11">
     Figures 9-11
    </xref>: inverse relations between EC and TSS as well as between TSS and TDS confirm distinct positive relations between soil moisture (expressed as TDS) and EC (<xref ref-type="fig" rid="fig9">
     Figure 9
    </xref>). It is essential to note that nutrient migration in this study is evaluated using spatial and temporal measurements, whereas geochemical processes are not accounted for. An indirect confirmation of the sole impact of soil wettability is coming from the stable with negligible fluctuation of the pH values. The temporal trends of nutrient migration and their dependence on soil moisture and consequently climate changes emphasize the management implication outcome: enhancement of summer irrigation water allocation aimed at salts leaching.</p>
  </sec><sec id="s5">
   <title>5. Conclusion</title>
   <p>Quantified temporal and seasonality of climate condition of rain capacity measures as mm/annum or periodical distribution respective to the number of rainy days, and nutrient migrations from the Hula Peat soil are dependently correlated. The higher the rain capacity or temporal distributional dispersed, the higher the nutrient concentration. The ecological significance of correlative similarity between migration dynamics of Alkalinity, Sulfate, Total Dissolved Solids and Electrical Conductivity confirm mutual properties of weakness adhesion onto the peat soil particles. A common abrupt response is the increase of soil salinity. Additional irrigation water allocation to enhance salts leaching is therefore recommended.</p>
  </sec><sec id="s6">
   <title>Acknowledgements</title>
   <p>The author would like to express his sincere appreciation to Prof. D. Levanon and D. Klein for their fruitful and friendly collaboration; V. Orlov-Levin and M. Peres for providing unpublished data supply; T. Natanson and E. Yasur for their assistance in field sampling.</p>
  </sec><sec id="s7">
   <title>Author Contributions</title>
   <p>The author carried out data analysis, evaluation and the preparation of the original draft and final version.</p>
  </sec><sec id="s8">
   <title>Data Availability Statement</title>
   <p>The data presented in this study are available on request from the corresponding author.</p>
  </sec><sec id="s9">
   <title>Funding</title>
   <p>This study was supported by the MIGAL-Galilee Scientific Research Institute.</p>
  </sec>
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