<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "https://jats.nlm.nih.gov/nlm-dtd/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="3.0" xml:lang="en">
<front>
<journal-meta>
<journal-id journal-id-type="publisher">HESS</journal-id>
<journal-title-group>
<journal-title>Hydrology and Earth System Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">HESS</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Hydrol. Earth Syst. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1607-7938</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/hess-12-1403-2008</article-id>
<title-group>
<article-title>Constraining model parameters on remotely sensed evaporation: justification for distribution in ungauged basins?</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Winsemius</surname>
<given-names>H. C.</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>Savenije</surname>
<given-names>H. H. G.</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>Bastiaanssen</surname>
<given-names>W. G. M.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Department of Water Management, Delft, University of Technology,  Delft, The Netherlands</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>WaterWatch, Wageningen, The Netherlands</addr-line>
</aff>
<pub-date pub-type="epub">
<day>18</day>
<month>12</month>
<year>2008</year>
</pub-date>
<volume>12</volume>
<issue>6</issue>
<fpage>1403</fpage>
<lpage>1413</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2008 H. C. Winsemius et al.</copyright-statement>
<copyright-year>2008</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://hess.copernicus.org/articles/12/1403/2008/hess-12-1403-2008.html">This article is available from https://hess.copernicus.org/articles/12/1403/2008/hess-12-1403-2008.html</self-uri>
<self-uri xlink:href="https://hess.copernicus.org/articles/12/1403/2008/hess-12-1403-2008.pdf">The full text article is available as a PDF file from https://hess.copernicus.org/articles/12/1403/2008/hess-12-1403-2008.pdf</self-uri>
<abstract>
<p>In this study, land surface related parameter distributions of a conceptual
semi-distributed hydrological model are constrained by employing time
series of satellite-based evaporation estimates during the dry season
as explanatory information. The approach has been applied to the ungauged
Luangwa river basin (150 000 (km)&lt;sup&gt;2&lt;/sup&gt;) in Zambia. The information
contained in these evaporation estimates imposes compliance of the model
with the largest outgoing water balance term, evaporation, and a spatially
and temporally realistic depletion of soil moisture within the dry season.
The model results in turn provide a better understanding of the information
density of remotely sensed evaporation. Model parameters to which evaporation
is sensitive, have been spatially distributed on the basis of dominant land
cover characteristics. Consequently, their values were conditioned by means
of Monte-Carlo sampling and evaluation on satellite evaporation estimates.
The results show that behavioural parameter sets for model units with similar
land cover are indeed clustered. The clustering reveals hydrologically
meaningful signatures in the parameter response surface: wetland-dominated
areas (also called dambos) show optimal parameter ranges that reflect
vegetation with a relatively small unsaturated zone (due to the shallow
rooting depth of the vegetation) which is easily moisture stressed. The
forested areas and highlands show parameter ranges that indicate a much
deeper root zone which is more drought resistent. Clustering was consequently
used to formulate fuzzy membership functions that can be used to constrain
parameter realizations in further calibration. Unrealistic parameter ranges,
found for instance in the high unsaturated soil zone values in the highlands
may indicate either overestimation of satellite-based evaporation or model
structural deficiencies. We believe that in these areas, groundwater uptake
into the root zone and lateral movement of groundwater should be included in
the model structure. Furthermore, a less distinct parameter clustering was
found for forested model units. We hypothesize that this is due to the
presence of two dominant forest types that differ substantially in their
moisture regime. This could indicate that the spatial discretization used
in this study is oversimplified.</p>
</abstract>
<counts><page-count count="11"/></counts>
</article-meta>
</front>
<body/>
<back>
<ref-list>
<title>References</title>
<ref id="ref1">
<label>1</label><mixed-citation publication-type="other" xlink:type="simple"> Allen, R G., Pereira, L S., Raes, D., and Smith, M.: FAO Irrigation and Drainage Paper No. 56 – Crop Evapotranspiration, Tech. rep., FAO, 1998. </mixed-citation>
</ref>
<ref id="ref2">
<label>2</label><mixed-citation publication-type="other" xlink:type="simple"> Allen, R G., Tasumi, M., and Trezza, R.: Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-model, J. Irrig. Drain. Eng., 133, 380–394, \doi10.1061/(ASCE)0733-9437(2007)133:4(380), 2007. </mixed-citation>
</ref>
<ref id="ref3">
<label>3</label><mixed-citation publication-type="other" xlink:type="simple"> Bastiaanssen, W. G M., Hoekman, H H., and Roebeling, R A.: A methodology for assessment of surface resistance and soil water storage variability at mesoscale based on remote sensing measurements, in: IAHS Special Publication, 2, p 65, IAHS Press, Wallingford, USA, 1994. </mixed-citation>
</ref>
<ref id="ref4">
<label>4</label><mixed-citation publication-type="other" xlink:type="simple"> Bastiaanssen, W. G M., Menenti, M., Feddes, R A., and Holtslag, A. A M.: A remote sensing surface energy balance algorithm for land (SEBAL). Part 2. Validation, J. Hydrol., 212/213, 213–229, 1998. </mixed-citation>
</ref>
<ref id="ref5">
<label>5</label><mixed-citation publication-type="other" xlink:type="simple"> Bastiaanssen, W M., Noordman, E. J M., Pelgrum, H., Davids, G., Thoreson, B P., and Allen, R G.: SEBAL model with remotely sensed data to improve water-resources management under actual field conditions, J. J. Irrig. Drain. E-Asce, 131, 85–93, 2005. </mixed-citation>
</ref>
<ref id="ref6">
<label>6</label><mixed-citation publication-type="other" xlink:type="simple"> Bastiaanssen, W. M G., Ahmed, M D., and Chemin, Y.: Satellite surveillance of evaporative depletion across the Indus Basin, Water Resour. Res., 38, 1273–1282, 2002. </mixed-citation>
</ref>
<ref id="ref7">
<label>7</label><mixed-citation publication-type="other" xlink:type="simple"> Batjes, N H.: ISRIC-WISE derived soil properties on a 5 by 5 arc-minutes global grid (version 1.1)., Tech. rep., ISRIC – World Soil Information, Wageningen, The Netherlands, 2006. </mixed-citation>
</ref>
<ref id="ref8">
<label>8</label><mixed-citation publication-type="other" xlink:type="simple"> Beven, K J. and Binley, A M.: The future of distributed models: model calibration and uncertainty prediction, Hydrol. Proc., 6, 279–298, 1992. </mixed-citation>
</ref>
<ref id="ref9">
<label>9</label><mixed-citation publication-type="other" xlink:type="simple"> Beven, K J. and Freer, J.: Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, J. Hydrol., 249, 11–29, 2001. </mixed-citation>
</ref>
<ref id="ref10">
<label>10</label><mixed-citation publication-type="other" xlink:type="simple"> Brutsaert, W.: Evaporation into the Atmosphere, Reidel, Dordrecht, The Netherlands, 1982. </mixed-citation>
</ref>
<ref id="ref11">
<label>11</label><mixed-citation publication-type="other" xlink:type="simple"> Campo, L., Caparrini, F., and Castelli, F.: Use of multi-platform, multi-temporal remote-sensing data for calibration of a distributed hydrological model: an application in the Arno basin, Italy, Hydrol. Process., 20, 2693–2712, 2006. </mixed-citation>
</ref>
<ref id="ref12">
<label>12</label><mixed-citation publication-type="other" xlink:type="simple"> Chidumayo, E N.: Effects of climate on the growth of exotic and indigenous trees in central Zambia, J. Biogeogr., 32, 111–120, 2005. </mixed-citation>
</ref>
<ref id="ref13">
<label>13</label><mixed-citation publication-type="other" xlink:type="simple"> Farah, H O.: Estimation of regional evaporation under different weather conditions from satellite and meteorological data; A case study in the Naivasha Basin, Kenya, Ph.D. Thesis, Wageningen University, The Netherlands, 2001. </mixed-citation>
</ref>
<ref id="ref14">
<label>14</label><mixed-citation publication-type="other" xlink:type="simple"> Fenicia, F., McDonnell, J J., and Savenije, H. H G.: Learning from model improvement: On the contribution of complementary data to process understanding, Water Resour. Res., 44, W06419, \doi10.1029/2007WR006386, 2008. </mixed-citation>
</ref>
<ref id="ref15">
<label>15</label><mixed-citation publication-type="other" xlink:type="simple"> Franks, S W. and Beven, K J.: Estimation of evapotranspiration at the landscape scale: a fuzzy disaggregation approach, Water Resour. Res., 33, 2929–2938, 1997. </mixed-citation>
</ref>
<ref id="ref16">
<label>16</label><mixed-citation publication-type="other" xlink:type="simple"> Franks, S W., Gineste, P., Beven, K J., and Merot, P.: On constraining the predictions of a distributed model: The incorporation of fuzzy estimates of saturated areas into the calibration process, Water Resour. Res., 34, 787–797, 1998. </mixed-citation>
</ref>
<ref id="ref17">
<label>17</label><mixed-citation publication-type="other" xlink:type="simple"> Freer, J., Beven, K J., and Ambroise, B.: Bayesian estimation of uncertainty in runoff prediction and the value of data: An application of the GLUE approach, Water Resour. Res., 32, 2161–2173, 1996. </mixed-citation>
</ref>
<ref id="ref18">
<label>18</label><mixed-citation publication-type="other" xlink:type="simple"> Frost, P.: The Miombo in Transition: Woodlands and Welfare in Africa, chap. The ecology of miombo woodlands, 11–58, Center for International Forestry Research, 1996. </mixed-citation>
</ref>
<ref id="ref19">
<label>19</label><mixed-citation publication-type="other" xlink:type="simple"> Fuller, D O.: Canopy phenology of some mopane and miombo woodlands in eastern Zambia, Global Ecol. Biogeogr., 8, 199–209, 1999. </mixed-citation>
</ref>
<ref id="ref20">
<label>20</label><mixed-citation publication-type="other" xlink:type="simple"> Gragne, A S., Uhlenbrook, S., Mohamed, Y., and Kebede, S.: Catchment modeling and model transferability in upper Blue Nile basin, Lake Tana, Ethiopia, Hydrol. Earth Syst. Sci. Discuss., 5, 811–842, 2008. </mixed-citation>
</ref>
<ref id="ref21">
<label>21</label><mixed-citation publication-type="other" xlink:type="simple"> Herman, A., Kumar, V B., Arkin, P A., and Kousky, J V.: Objectively determined 10-day African rainfall estimates created for Famine Early Warning Systems, Int. J. Remote Sensing, 18, 2147–2159, 1997. </mixed-citation>
</ref>
<ref id="ref22">
<label>22</label><mixed-citation publication-type="other" xlink:type="simple"> Huffman, G J., Adler, R F., Bolvin, D T., Gu, G., Nelkin, E J., Bowman, K P., Hong, Y., Stocker, E F., and Wolff, D B.: The TRMM Multisatellite Precipitation Analysis (TMPA): quasi-global, multiyear,combined-sensor precipitation estimates at fine scales, J. Hydrometeor., 8, 38–55, 2007. </mixed-citation>
</ref>
<ref id="ref23">
<label>23</label><mixed-citation publication-type="other" xlink:type="simple"> Immerzeel, W W. and Droogers, P.: Calibration of a distributed hydrological model based on satellite evapotranspiration, J. Hydrol., 349, 411–424, 2008. </mixed-citation>
</ref>
<ref id="ref24">
<label>24</label><mixed-citation publication-type="other" xlink:type="simple"> Immerzeel, W W., Gaur, A., and Zwart, S J.: Integrating remote sensing and a process-based hydrological model to evaluate water use and productivity in a south Indian catchment, Agric. Water Manag., 95, 11–24, 2008. </mixed-citation>
</ref>
<ref id="ref25">
<label>25</label><mixed-citation publication-type="other" xlink:type="simple"> Jarvis, P G.: The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field, Phil. Trans. R. Soc. Lond., 273, 593–610, 1976. </mixed-citation>
</ref>
<ref id="ref26">
<label>26</label><mixed-citation publication-type="other" xlink:type="simple"> Johrar, R K.: Estimation of effective soil hydraulic parameters for water management studies in semi-arid zones, PhD Thesis, Wageningen University, The Netherlands, 2002. </mixed-citation>
</ref>
<ref id="ref27">
<label>27</label><mixed-citation publication-type="other" xlink:type="simple"> Kavetski, D., Kuczera, G., and Franks, S W.: Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory, Water Resour. Res., 42, W03407, \doi10.1029/2005WR004368, 2006. </mixed-citation>
</ref>
<ref id="ref28">
<label>28</label><mixed-citation publication-type="other" xlink:type="simple"> Kuczera, G.: Improved parameter inference in catchment models, 2, Combining different kinds of hydrologic data and testing their compatibility, Water Resour. Res., 19, 1163–1172, 1983. </mixed-citation>
</ref>
<ref id="ref29">
<label>29</label><mixed-citation publication-type="other" xlink:type="simple"> Lewis, D M.: Observations of tree growth, woodland structure and elephant damage on Colophospermum mopane in Luangwa valley, Zambia, Afr. J. Ecol., 29, 207–221, 1991. </mixed-citation>
</ref>
<ref id="ref30">
<label>30</label><mixed-citation publication-type="other" xlink:type="simple"> Lindström, G., Johansson, B., Persson, M., Gardelin, M., and Bergstrom, S.: Development and test of the distributed HBV-96 hydrological model, J. Hydrol., 201, 272–288, 1997. </mixed-citation>
</ref>
<ref id="ref31">
<label>31</label><mixed-citation publication-type="other" xlink:type="simple"> Liu, Y. and Gupta, H V.: Uncertainty in hydrologic modeling: Toward and integrated data assimilation framework, Wat. Resour. Res., 43, W07401, \doi10.1029/2006WR005756, 2007. </mixed-citation>
</ref>
<ref id="ref32">
<label>32</label><mixed-citation publication-type="other" xlink:type="simple"> LSA SAF: Validation report, Tech. Rep. SAF/LAND/IM/VR/1.6, LSA SAF, Lisboa, Portugal, 2007. </mixed-citation>
</ref>
<ref id="ref33">
<label>33</label><mixed-citation publication-type="other" xlink:type="simple"> Mohamed, Y A., Bastiaanssen, W. G M., and Savenije, H. H G.: Spatial variability of evaporation and moisture storage in the swamps of the upper Nile studied by remote sensing techniques, J. Hydrol., 289, 145–164, 2004. </mixed-citation>
</ref>
<ref id="ref34">
<label>34</label><mixed-citation publication-type="other" xlink:type="simple"> Monteith, J L.: Evaporation and surface temperature, Q. J. R. Meteorol. Soc., 107, 1–27, 1981. </mixed-citation>
</ref>
<ref id="ref35">
<label>35</label><mixed-citation publication-type="other" xlink:type="simple"> New, M., Lister, D., Hulme, M., and Makin, I.: A high-resolution data set of surface climate over global land areas, Climate research, 21, 1–25, 2002.  </mixed-citation>
</ref>
<ref id="ref36">
<label>36</label><mixed-citation publication-type="other" xlink:type="simple"> Penman, H L.: Natural evaporation from open water, bare soil and grass, Proc. Roy. Soc. London, A193, 120–145, 1948. </mixed-citation>
</ref>
<ref id="ref37">
<label>37</label><mixed-citation publication-type="other" xlink:type="simple"> Reynolds, R W.: A real-time global sea surface temperature analysis, J. Climate, 1, 75–86, 1988. </mixed-citation>
</ref>
<ref id="ref38">
<label>38</label><mixed-citation publication-type="other" xlink:type="simple"> Savenije, H. H G.: Equifinality, a blessing in disguise?, Hydrol. Process., 15, 2835–2838, 2001. </mixed-citation>
</ref>
<ref id="ref39">
<label>39</label><mixed-citation publication-type="other" xlink:type="simple"> Schuurmans, J M., Troch, P A., Veldhuizen, A A., Bastiaanssen, W. G M., and Bierkens, M. F P.: Assimilation of remotely sensed latent heat flux in a distributed hydrological model, Adv. Water Resour., 26, 151–159, \doi10.1016/S0309-1708(02)00089-1, 2003. </mixed-citation>
</ref>
<ref id="ref40">
<label>40</label><mixed-citation publication-type="other" xlink:type="simple"> Seibert, J. and McDonnell, J J.: On the dialog between experimentalist and modeler in catchment hydrology: Use of soft data for multicriteria model calibration, Wat. Resour. Res., 38, 1241, \doi10.1029/2001WR000978, 2002. </mixed-citation>
</ref>
<ref id="ref41">
<label>41</label><mixed-citation publication-type="other" xlink:type="simple"> Sivapalan, M.: Prediction in Ungauged Basins: a grand challenge for theoretical hydrology, Hydrol. Process., 17, 3163–3170, 2003. </mixed-citation>
</ref>
<ref id="ref42">
<label>42</label><mixed-citation publication-type="other" xlink:type="simple"> Son, K. and Sivapalan, M.: Improving model structure and reducing parameter uncertainty in conceptual water balance models through the use of auxiliary data, Water Resources Research, 43, W01415, \doi10.1029/2006WR005032, 2007. </mixed-citation>
</ref>
<ref id="ref43">
<label>43</label><mixed-citation publication-type="other" xlink:type="simple"> Uhlenbrook, S., Seibert, J., Leibundgut, C., and Rodhe, A.: Prediction uncertainty of conceptual rainfall-runoff models caused by problems in identifying model parameters and structure, Hydrol. Sci., 44, 779–797, 1999. </mixed-citation>
</ref>
<ref id="ref44">
<label>44</label><mixed-citation publication-type="other" xlink:type="simple"> Vaché, K B. and McDonnell, J J.: A process-based rejectionist framework for evaluating catchment runoff model structure, Wat. Resour. Res., 42, W02409, \doi10.1029/2005WR004247, 2006. </mixed-citation>
</ref>
<ref id="ref45">
<label>45</label><mixed-citation publication-type="other" xlink:type="simple"> Voogt, M.: METEOLOOK, a physically based regional distribution model for measured meteorological variables, M.Sc. Thesis, University of Technology, Delft, The Netherlands, 2006. </mixed-citation>
</ref>
<ref id="ref46">
<label>46</label><mixed-citation publication-type="other" xlink:type="simple"> Vose, R S., Schmoyer, R L., Steurer, P M., Peterson, T C., Heim, R., Karl, T R., and Eischeid, J.: The Global Historical Climatology Network: long-term monthly temperature, precipitation, sea level pressure, and station pressure data, ORNL/CDIAC-53, NDP-041, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, TN, USA, 1992. </mixed-citation>
</ref>
<ref id="ref47">
<label>47</label><mixed-citation publication-type="other" xlink:type="simple"> Wagener, T. and Gupta, H V.: Model identification for hydrological forecasting under uncertainty, Stoch. Environ. Res. Risk Assess., 19, 378–387, 2005. </mixed-citation>
</ref>
<ref id="ref48">
<label>48</label><mixed-citation publication-type="other" xlink:type="simple"> Young, P C.: Model validation, chap. Data-based mechanistic modelling and validation of rainfall-flow processes, 117–161, Wiley, Chichester, UK, 2001. </mixed-citation>
</ref>
</ref-list>
</back>
</article>