View
216
Download
2
Category
Tags:
Preview:
Citation preview
Hydro-Economic decision support to enhance catchment management
BENNIE GROVÉDEPARTMENT OF AGRICULTURAL
ECONOMICS
INTRODUCTION
• South Africa is a water scarce country • National Water Act (1998)
– Ecological Water Requirements (EWR)• National Water Resources Strategy
– a number of the South African catchments to be in situation of being over-allocated
• Before issuing water licenses to address imbalances, water managers have to reconsider – catchment scale operating rules,– water conservation and demand management options,– water augmentations alternatives and – the level and necessity of water curtailments
to determine the most viable option.
OBJECTIVES
• The main objective of this research is to develop a Decision Support System (DSS) to help water managers test various catchment scale water management scenarios impact on irrigation farming profitability and livelihoods.
• Achieving the object requires an integrated hydro-economic modelling framework.
RESEARCH AREA
• Crocodile East catchment South Africa– Highly over-allocated– Instream flow requirement
• Ecology• International flows to Mozambique
• Water needs to be re-allocated
OVER ALLOCATION IN SOUTH AFRICA
CrocodileCatchment is in
The Nkomati WMA
ECOLOGICAL SENSITIVE AREA: KRUGER NATIONAL PARK
INTEGRATED SET OF MODELS
• MIKE-BASIN– reconcile irrigation water demand with catchment water availability
• for given catchment operating rules– Daily input requirements
• Catchment hydrology• Water demand
• Optimisation model– Maximises total farm gross margins– Water availability
• Operating rules– Dated production functions (water use optimisation)
• Weekly• State contingent• Irrigation technology specific (Distribution unifromity) • Multiple fields
– Results are used to evaluate • Profitability (REO)• Livelihood (ability to generate cashflows)
• MIKE BASIN Irrigation– Information to generate irrigation technology specific dated production functions
(daily)
MODELLING DIFFICULTY
MIKE BASIN
OPTIMISATION
MIKE BASIN Irrigation Model
Daily Irrigation Outputs
(ET, ES, EOP, DP, RO, AI)
Weekly Irrigation inputs to SKELETON
(ET, ES, EOP, DP, RO, AI)
Optimsation Model
Optimised Weekly Farm Demand Profile
Disaggregate to Daily Farm Demand Profile
MIKE BASIN without the irrigation model, Demand node representing farm
Catchment water availability and water available to the farm from all sources
Weekly water available limit
RESULTS
• Profitability– ROE > ROA
• Financial sustainability• Indicates profitable employment of foreign capital• Do not need to use own capital to meet interest
payments• Reported as probability to achieve financial
sustainability• Livelihood objective
– Determine whether enough cash is generated to cover living expenses
-0.3 -0.25 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.150
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
S150 BE
Return on Equity (Fraction)
Cum
ulati
ve P
roba
bilit
y
-0.3 -0.25 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.150
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
S150 BE
Return on Equity (Fractioin)
Cum
ulati
ve P
roba
bilit
y
29% : ROE < 0%
65% : ROE >= 7.66%
6% : 0 <= ROE < 7.66%
-0.3 -0.25 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.150
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
S150 BE
Return on Equity (Fractioin)
Cum
ulati
ve P
roba
bilit
y
29% : ROE < 0%
65% : ROE >= 7.66%
6% : 0 <= ROE < 7.66%
PROFITABILITY ANALYSIS
KD_NO_09_S100
KD_NO_09_SD100
KD_NO_09_S150
KD_NO_09_SD150 _
KD_NO_12_S100
KD_NO_12_SD100
KD_NO_12_S150
KD_NO_12_SD150 _
KD_Pres_
12_S100
KD_Pres_
12_SD100
KD_Pres_
12_S150
KD_Pres_
12_SD150 _
MD_Pre
s_12_S1
00
MD_Pre
s_12_SD
100
MD_Pre
s_12_S1
50
MD_Pre
s_12_SD
150 _
MD_CC_12_S1
00
MD_CC_12_SD
100
MD_CC_12_S1
50
MD_CC_12_SD
150 _
MVD_Pre
s_12_S1
00
MVD_Pre
s_12_SD
100
MVD_Pre
s_12_S1
50
MVD_Pre
s_12_SD
150 _
MVD_CC_12_S1
00
MVD_CC_12_SD
100
MVD_CC_12_S1
50
MVD_CC_12_SD
1500
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
RoE: Below Zero RoE: Above Zero and Below RoA RoE: Above RoA
Cum
ulati
ve P
roba
bilit
y
0.9 vs 1.2
KD_NO_09_S100
KD_NO_09_SD100
KD_NO_09_S150
KD_NO_09_SD150 _
KD_NO_12_S100
KD_NO_12_SD100
KD_NO_12_S150
KD_NO_12_SD150 _
KD_Pres_
12_S100
KD_Pres_
12_SD100
KD_Pres_
12_S150
KD_Pres_
12_SD150 _
MD_Pre
s_12_S1
00
MD_Pre
s_12_SD
100
MD_Pre
s_12_S1
50
MD_Pre
s_12_SD
150 _
MD_CC_12_S1
00
MD_CC_12_SD
100
MD_CC_12_S1
50
MD_CC_12_SD
150 _
MVD_Pre
s_12_S1
00
MVD_Pre
s_12_SD
100
MVD_Pre
s_12_S1
50
MVD_Pre
s_12_SD
150 _
MVD_CC_12_S1
00
MVD_CC_12_SD
100
MVD_CC_12_S1
50
MVD_CC_12_SD
1500
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
RoE: Below Zero RoE: Above Zero and Below RoA RoE: Above RoA
Cum
ulati
ve P
roba
bilit
y
No vs Present
KD_NO_09_S100
KD_NO_09_SD100
KD_NO_09_S150
KD_NO_09_SD150 _
KD_NO_12_S100
KD_NO_12_SD100
KD_NO_12_S150
KD_NO_12_SD150 _
KD_Pres_
12_S100
KD_Pres_
12_SD100
KD_Pres_
12_S150
KD_Pres_
12_SD150 _
MD_Pre
s_12_S1
00
MD_Pre
s_12_SD
100
MD_Pre
s_12_S1
50
MD_Pre
s_12_SD
150 _
MD_CC_12_S1
00
MD_CC_12_SD
100
MD_CC_12_S1
50
MD_CC_12_SD
150 _
MVD_Pre
s_12_S1
00
MVD_Pre
s_12_SD
100
MVD_Pre
s_12_S1
50
MVD_Pre
s_12_SD
150 _
MVD_CC_12_S1
00
MVD_CC_12_SD
100
MVD_CC_12_S1
50
MVD_CC_12_SD
1500
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
RoE: Below Zero RoE: Above Zero and Below RoA RoE: Above RoA
Cum
ulati
ve P
roba
bilit
y
Class C - all farms infeasible
KD_NO_09_S100
KD_NO_09_SD100
KD_NO_09_S150
KD_NO_09_SD150 _
KD_NO_12_S100
KD_NO_12_SD100
KD_NO_12_S150
KD_NO_12_SD150 _
KD_Pres_
12_S100
KD_Pres_
12_SD100
KD_Pres_
12_S150
KD_Pres_
12_SD150 _
MD_Pre
s_12_S1
00
MD_Pre
s_12_SD
100
MD_Pre
s_12_S1
50
MD_Pre
s_12_SD
150 _
MD_CC_12_S1
00
MD_CC_12_SD
100
MD_CC_12_S1
50
MD_CC_12_SD
150 _
MVD_Pre
s_12_S1
00
MVD_Pre
s_12_SD
100
MVD_Pre
s_12_S1
50
MVD_Pre
s_12_SD
150 _
MVD_CC_12_S1
00
MVD_CC_12_SD
100
MVD_CC_12_S1
50
MVD_CC_12_SD
1500
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
RoE: Below Zero RoE: Above Zero and Below RoA RoE: Above RoA
Cum
ulati
ve P
roba
bilit
y
Montrose
KD_NO_09_S100
KD_NO_09_SD100
KD_NO_09_S150
KD_NO_09_SD150 _
KD_NO_12_S100
KD_NO_12_SD100
KD_NO_12_S150
KD_NO_12_SD150 _
KD_Pres_
12_S100
KD_Pres_
12_SD100
KD_Pres_
12_S150
KD_Pres_
12_SD150 _
MD_Pre
s_12_S1
00
MD_Pre
s_12_SD
100
MD_Pre
s_12_S1
50
MD_Pre
s_12_SD
150 _
MD_CC_12_S1
00
MD_CC_12_SD
100
MD_CC_12_S1
50
MD_CC_12_SD
150 _
MVD_Pre
s_12_S1
00
MVD_Pre
s_12_SD
100
MVD_Pre
s_12_S1
50
MVD_Pre
s_12_SD
150 _
MVD_CC_12_S1
00
MVD_CC_12_SD
100
MVD_CC_12_S1
50
MVD_CC_12_SD
1500
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
RoE: Below Zero RoE: Above Zero and Below RoA RoE: Above RoA
Cum
ulati
ve P
roba
bilit
y
Present vs Class C
KD_NO_09_S100
KD_NO_09_SD100
KD_NO_09_S150
KD_NO_09_SD150 _
KD_NO_12_S100
KD_NO_12_SD100
KD_NO_12_S150
KD_NO_12_SD150 _
KD_Pres_
12_S100
KD_Pres_
12_SD100
KD_Pres_
12_S150
KD_Pres_
12_SD150 _
MD_Pre
s_12_S1
00
MD_Pre
s_12_SD
100
MD_Pre
s_12_S1
50
MD_Pre
s_12_SD
150 _
MD_CC_12_S1
00
MD_CC_12_SD
100
MD_CC_12_S1
50
MD_CC_12_SD
150 _
MVD_Pre
s_12_S1
00
MVD_Pre
s_12_SD
100
MVD_Pre
s_12_S1
50
MVD_Pre
s_12_SD
150 _
MVD_CC_12_S1
00
MVD_CC_12_SD
100
MVD_CC_12_S1
50
MVD_CC_12_SD
1500
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
RoE: Below Zero RoE: Above Zero and Below RoA RoE: Above RoA
Cum
ulati
ve P
roba
bilit
y
Present vs Class C
LIVELIHOOD ANALYSIS
KD_NO_09_S100
KD_NO_09_SD100
KD_NO_09_S150
KD_NO_09_SD150 0
KD_NO_12_S100
KD_NO_12_SD100
KD_NO_12_S150
KD_NO_12_SD150 0
KD_Pres_
12_S100
KD_Pres_
12_SD100
KD_Pres_
12_S150
KD_Pres_
12_SD150 0
MD_Pre
s_12_S1
00
MD_Pre
s_12_SD
100
MD_Pre
s_12_S1
50
MD_Pre
s_12_SD
150 0
MD_CC_12_S1
00
MD_CC_12_SD
100
MD_CC_12_S1
50
MD_CC_12_SD
150 0
MVD_Pre
s_12_S1
00
MVD_Pre
s_12_SD
100
MVD_Pre
s_12_S1
50
MVD_Pre
s_12_SD
150 0
MVD_CC_12_S1
00
MVD_CC_12_SD
100
MVD_CC_12_S1
50
MVD_CC_12_SD
1500
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
NCF: Below Zero NCF: Above Zero
Cum
ulati
ve P
roba
bilit
y
CONCLUSIONS
• MVD greatest potential– Cost of dam not included
• Class C is a no go scenario• Investigate enforcing EWR based on present flow
regime• Stimulate dialogue
THANK YOU
BENNIE GROVÉDEPARTMENT OF AGRICULTURAL
ECONOMICS
Recommended