Using multi‐criteria analysis as a tool to select the feasible measures for sustainable development of brackish water shrimp culture in Quang Tri Province

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Using multi‐criteria analysis as a tool to select the feasible measures for sustainable development of brackish water shrimp culture in Quang Tri Province

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  VNU    Journal   of   Science,   Earth   Sciences   24   (2008)   66 ‐ 78   66   Using   multi ‐ criteria   analysis   as   a   tool   to   select   the   feasible   measures   for   sustainable   development   of    brackish   water   shrimp   culture   in   Quang   Tri   Province   Nguyen   Tien   Giang 1, *  ,   Tran   Anh   Phuong 1  ,   Tran   Ngoc   Anh 1  ,   Nguyen   Thanh   Son 1  ,   Nguyen   Truong   Khoa 2   1   College   of    Science,   VNU    2   Department   of    Natural   Resources   and   Environment   of    Quang   Tri   Province   Received   7    July   2008;   received   in   revised   form   23   August   2008   Abstract.   In   recent   years,    brackish   water   shrimp   culture   in   Quang   Tri   Province   has   developed   rapidly.   Thanks   to   this   development,   lives   of   many   local   farmers   have    been   improved,   contributing   considerably   to   the   poverty   alleviation   goal.   However,   together   with   this   positive   impact,   policy ‐ makers   and   shrimp   farmers   are   facing   several   issues   such   as   spread   of   shrimp’s   diseases,   water   pollution   and   salinity   intrusion.   For   the   purpose   of   sustainable   development,   it   is   necessary   to   search   for   and   implement   those   measures   which   can   solve   effectively   these   emerging   problems.   This   paper   presents   the   results   on   the   application   of   a   multi ‐ criteria   analysis   method   to   selecting   the   most   feasible   measures   to   these   problems.   The   MCA   results   suggest   the   four   most   feasible   measures   and   pinpoint   that   the   combined   option:   sedimentation   reservoir   &   reservoir   with   culture   plus   improved   feeding   and   water   management   as   the  ʺ  best ʺ option.   Keywords:   Shrimp   culture;   Multi ‐ criteria   analysis;   Feasible   measures;   Sustainable   development;   Quang   Tri   Province.   1.   Introduction *   Quang   Tri   Province   is   located   in   the   Central   Vietnam.   The   province   is    bounded   on   the   north    by   Quang   Binh   Province,   on   the   south    by   Thua   Thien   Hue   Province,   on   the   west    by   Laos   Republic   and   on   the   east    by   the   sea   (Fig.1).   The   Province   includes   10   administrative   units:   two   towns   and   8   districts,   in   which   Dong   Ha   is   the   provincial   capital.   _______ *   Corresponding   author.   Tel.:   84 ‐ 4 ‐ 2173940.   E ‐ mail:   giangnt@vnu.vn   As   regards   topography,   Quang   Tri   has   all   types   of   topography:   mountains,   hills,   plains   and   coastal   sand   dune   with   two   main   river   systems:   Thach   Han   and   Ben   Hai.   Lying   in   the   tropical   monsoon   region,   the   average   temperature   of   Quang   Tri   is   ranging   from   20 0 C   to   25 0   C,   in   which   the   highest   and   lowest   temperature   usually   happens   on    July   and    January,   respectively.   Quang   Tri   has   a   total   annual   rainfall   of   about   2000 ‐ 2700   mm,    but   the   rainfall   is   rather   unequally   distributed   over   time   and   space.   The   rainy   season   starts   in   September,   ends   in    Nguyen   Tien   Giang   et   al.   /   VNU     Journal   of    Science,   Earth   Sciences   24   (2008)   66 ‐ 78   67  January   and   accounts   for   75%   to   85%   of   the   total   yearly   rainfall,   whereas   the   dry   season   lasts   up   to   6   months,   from   February   to    July   and   occupies   only   15 ‐ 25%   of   the   total   rainfall.   Fig.   1.   Quang   Tri   Province.   Quang   Tri   has   75   km   of   coastal   line   and   two   river   mouths,   namely   Cua   Tung   and   Cua   Viet.   In   recent   years,   there   has    been   a   rapid   development   of    brackish   pond   area   in   the   province.   As   shown   in   Fig.   2,   the   total   area   of    brackish   water   shrimp   culture   has   increased   approximately   4   times,   from   251   ha   in   2000   to   902.5   ha   in   2007.   According   to   the   provincial   aquaculture   development   plan   [6],   the   total   area   in   2010   would    be   1,889   ha,   which   doubles   the   present’s   value.   Thank   to   this   development,   the    brackish   pond   culture   has   improved   remarkably   the   quality   of   life   for   many   farmers   in   the   province,   contributing   positively   to   the   poverty   alleviation.   However,   during   the   development   process,   the   local   farmers   and   authorities   have    been   facing   some   problems   such   as   water   pollution,   salinity   intrusion   and   the   spread   of   shrimp’s   diseases.   This   leads   to   the   demand   for   seeking   and   implementing   measures   to   solve   the   conflicts    between   economic   goal   and   its   negative   impacts,   especially   in   the   future,   when   the   province   has   the   plan   to   develop   the   aquaculture   to    be   the   key   sector   of   local   economics   [6].   02004006008001000120014001600180020002000 2001 2002 2003 2004 2005 2006 2007 2010 Year       A   r   e   a    (   h   e   c   t   a   r   s   )   Fig.   2.   The   development   of    brackish   pond   area   in   Quang   Tri   Province.   In   order   to   have   feasible   sets   of   measures   for   the   above ‐ stated   problem,   a   Multi ‐ Criteria   Analysis   (MCA)   method   was   used   and   its   results   are   presented   in   the   next   sections.   This   paper   is   divided   into   5   sections.   Section   1   is   involved   with   the   problem   statement.   Section   2   is   devoted   to   the   overview   of   the   MCA   methods.   Section   3   describes   step    by   step   the   application   of   the   MCA   method   using   pair ‐ wise   comparison   and   its   results   to   the   problem   of    brackish   water   shrimp   culture   in   Quang   Tri   Province.   Subsequently,   sections   4   and   5   present   some   discussions,   conclusions   on   the   results   and   the   research   outlook.   2.   Methodology   2.1.   Framework    for   multi ‐ criteria   analysis   Any   decision   problem   can    be   structured   into   three   major   phases:   intelligence   which   examines   the   existence   of   a   problem   or   the   opportunity   for   change;   design   which   Quang Tri Province  Nguyen   Tien   Giang   et   al.   /   VNU     Journal   of    Science,   Earth   Sciences   24   (2008)   66 ‐ 78   68 determines   the   alternatives;   and   choice   which   decides   the    best   alternative   [10].   MCA   is   an   effective   tool   used   in   a   decision   process.   The   major   elements   involved   in   decision   making   process   using   a   MCA   method   can    be   viewed   systematically   in   a   framework   (Fig.   3).   Fig.   3.   Framework   for   multi ‐ criteria   analysis.   2.2.   Problem   definition   A   decision   problem   is   the   difference    between   the   desired   and   existing   state   of   the   real   world.   It   is   a   gap   recognized    by   the   stakeholders   (decision   makers,   scientists   and/or   farmers).   Any   decision   making   process    begins   with   the   recognition   and   the   definition   of   the   problem.   This   stage   is   in   the   intelligence   phase   of   decision   making   and   it   involves   in   searching   the   decision   environment   for   conditions,   obtaining,   processing   and   examining   the   raw   data   to   identify   the   problems.   2.3.   Constraints   After   the   problem   has    been   defined,   constraints   (or    boundary   conditions)   of   this   problem   have   to    be   determined   for   the   following   two   reasons:  ‐ The   studied   problems   are   usually   complicate,   they   are   relating   to   many   aspects   and   sectors.   Therefore,   it   is   impossible   to   take   into   account   all   these   effects   in   practice.  ‐ On   the   other   hand,   for   solving   a   problem,   many   measures   would    be   suggested.   The   responsibility   of   the   scientists   is   to   screen   among   these   alternatives   the   feasible   measures    based   on   applicability   and   suitability   for   the   local   conditions.   2.4.   Evaluation   criteria   After   the   problem   and   its   constraints   have    been   determined,   the   set   of   evaluation   criteria   should    be   designated   [2].   This   stage   involves   specifying   a   comprehensive   set   of   objectives   that   reflects   all   concerns   relevant   to   the   decision   problem   and   measures   for   achieving   those   objectives.   2.5.   Criterion   weights   Criteria   weighting   is   one   of   the   most   important   steps   in   the   decision   making   process.   A   weight   can    be   defined   as   a   value   assigned   to   an   evaluation   criterion   which   indicates   its   importance   relative   to   other   criteria   under   consideration.   Assigning   weights   of   importance   to   evaluation   criteria   accounts   for:   (i)   the   changes   in   the   range   of   variation   for   each   evaluation   criterion   and   (ii)   the   different   degrees   of   importance    being   attached   to   these   ranges   of   variation   [3].   Based   on   this   general   direction,   a   number   of   methods   have    been   developed   and   applied.   Each   of   them   has   its   own   advantages   and   disadvantages.   Table   1   summarizes   some   these   methods   and   their   features.   In   comparison   with   the   ranking   and   rating   methods,   pairwise   comparison   and   trade ‐ off   analysis   methods    both   have   more   precise   and   objective   underlying   theory.   Problem   Definition   ConstraintsAlternativesPairwise   comparison   matrix   Decision   Maker’sPreferences   Decision   Matrix   Select   feasible   measures   Criterion   WeightsEvaluation   Criteria  Nguyen   Tien   Giang   et   al.   /   VNU     Journal   of    Science,   Earth   Sciences   24   (2008)   66 ‐ 78   69 Table   1.   Methods   for   determining   criterion   weights   [8,   9]   Methods/Features   Ranking   Rating   Pairwise   comparison   Trade ‐ off   analysis   Number   of    judgments   n   n   n(n ‐ 1)/2   <n   Response   scale   Ordinal   Interval   Ratio   Interval   Hierarchical   Possible   Possible   Yes   Yes   Underlying   theory   None   None   Statistical/   heuristic   Axiomatic/   deductive   Ease   of   use   Very   easy   Very   easy   Easy   Difficult   Trustworthiness   Low   High   High   Medium   Precision   Approximations   Not   precise   Quite   precise   Quite   precise   Software   availability   Spreadsheets   Spreadsheets   Expert   Choice   Logical   Decision   However,   when   it   comes   to   the   ease   of   use,   pairwise   comparison   is   much    better   than   the   trade ‐ off   analysis.   For   these   reasons,   pairwise   comparison   method   was   applied   in   this   study.   The   following   paragraphs   introduce   this   method.   The   method   involves   pairwise   comparisons   to   create   a   ratio   matrix.   It   takes   pairwise   comparisons   as   input   and   produced   relative   weights   as   output.   The   pairwise   comparison   method   involves   two   main   steps:  ‐ Development   of   a   pairwise   comparison   matrix:   the   method   uses   a   scale   with   values   range   from   1   to   9.   The   possible   values   are   presented   in   Table   2.   Table   2.   Scale   for   pairwise   comparison   [12]   Intensity   of   importance   Definition   1   Equal   importance   2   Equal   to   moderately   importance   3   Moderate   importance   4   Moderate   to   strong   importance   5   Strong   importance   6   Strong   to   very   strong   importance   7   Very   strong   importance   8   Very   to   extremely   strong   importance   9   Extreme   importance   ‐ Computation   of   the   weights:   the   computation   of   the   weights   involves   three   steps.   The   first   one   is   summation   of   the   values   in   each   matrix   column.   Next,   each   element   in   the   matrix   should    be   divided    by   its   column   total   (the   resulting   matrix   is   referred   to   as   the   normalized   pairwise   comparison   matrix).   In   the   third   step,   computation   of   the   average   of   the   elements   in   each   row   of   the   normalized   matrix   should    be   made   which   includes   dividing   the   sum   of   normalized   scores   for   each   row    by   the   number   of   criteria.   These   averages   provide   an   estimate   of   the   relative   weights   of   the   criteria    being   compared.   The   advantage   of   this   method   is   that   only   two   criteria   have   to    be   considered   at   a   time,   it   can    be   implemented   in   a   spreadsheet   environment   [3].   One   of   the   disadvantages   is   that   the   relative   importance   of   evaluation   criteria   is   determined   without   considering   the   scales   on   which   the   criteria   are   measured.   Another   disadvantage   is   the   large   amount   of   pairwise   comparisons   if   many   criteria   exist.   2.6.   Determination   of    alternatives   Based   on   the   constraints   and   objectives   of   the   problem   and   the   relating   sectors,   the   measures   or   combinations   of   measures   to   solve   the   problem   is   to    be   suggested.   These   measures   can    be   the   ones   that   have    been    being   applied   elsewhere   having   features   or   new   technologies   that   are   firstly   considered.   Then,   scores   for   these   measures   with   respect   to   different   criteria   will    be   assessed   after   expert   consultation.    Nguyen   Tien   Giang   et   al.   /   VNU     Journal   of    Science,   Earth   Sciences   24   (2008)   66 ‐ 78   70 2.7.   Selection   of    the    feasible   measures   The   final   stage   in   the   decision   making   process   is   to   estimate   the   scores   for   each   of   the   alternatives   and   choose   the   most   suitable   measures   for   the   objectives   and   conditions   of   the   study.   Two   factors   used   to   determine   these   scores   are   scores   for   the   measures   with   respect   to   different   criteria   and   weights   of   the   criteria.   The   measures   with   highest   scores   will    be   selected   to   solve   the   problem.   3.   Application   of   MCA   to   selecting   feasible   measures   for   sustainable   development   of   brackish   water   shrimp   culture   in   Quang   Tri   Province   3.1.   Current   and    future    problem   During   the   last   couple   of   years,   the   spread   of   shrimp   diseases   occurred   frequently   in   the   study   area.   These   diseases   are   spread    by    brackish   water,   which   is   taken   in   and   out   without   proper   pretreatment   and   post   treatment    by   the   shrimp   farmers.   The   river   water   has   a   tendency   to    be   polluted   due   to   the   wastewater   from   the   shrimp   farms   and   from   other   sectors   such   as   industry   and   agriculture.   Another   problem   for   the   shrimp   farmers   is   to   keep   a   decent   salinity   rate   for   growing    black   tiger   shrimps   ( Penaeus   monodon ).   This   salinity   rate   changes   considerably   over   time    because   of   the   tidal   regime.   Only   at   certain   periods   water   with   the   appropriate   salinity   rate   can    be   taken   in    by   the   farmers.   3.2.   Boundary   conditions   There   are   several    boundary   conditions   that   need   to    be   mentioned   related   to   the   problems   and   possible   solutions   of   the   wastewater   problems   near   shrimp   ponds.   These   are:   (i)   Spatial    boundaries:   the   location   of   the   shrimp   farms   has   to   stay   nearby   the   river   estuaries;   The   available   space   for   a   production   pond   remains   0.5 ‐ 1   ha.   (ii)   Social    boundaries:   the   standard   of   living   for   the   farmers   should   not    be   lowered.   (iii)   Ecological    boundaries:   the   water   quality   in   the   ponds   should    be   improved   to   the   needed   standards   for    black   tiger   shrimps;   Water   quality   in   the   river   and   in   the   estuaries   should    be   improved;   No   measures   may   have   negative   effects   on   the   environment.   Measures   suggested   should   meet   these    boundaries,   otherwise   they   will    be   removed.   3.3.   Objectives   Shrimp   farmers   want   to   make   their   living;   they   need   to   maintain   their   families.   Also    because   of   the   relative   large   initial   investment   costs   they   are   in   debt   and   have   to   repay   the    banks   in   short   terms.   The   local   government   wants   a   growing   economy   in   Quang   Tri,   and   shrimp   farming   is   a   great   opportunity   for   the   people   living   in   the   lower   parts   of   the   province    because   of   its   unique    brackish   environment.   After   all   requirements   of   all   factors   are   taken   into   account,   the   study   comes   to   conclude   that   the   major   objective   for   MCA   is   to   achieve   a   more   stable   economic   environment.   In   trying   to   achieve   this   goal,   sub ‐ goals   can    be   reached   like:   +   Better   water   quality   in   the   rivers   and   estuaries;   +   Better   water   quality   in   the   shrimp   ponds;   +   Better   well    being   of   farmers   and   their   families   /   the   communities;   +   Better   functioning   of   all   the   land   uses   in   the   surroundings.  
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