Evaluation of Surface Water Resource Availability under the Impact of Climate Change in the Dhidhessa Sub-Basin, Ethiopia
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area Description
2.2. Methodology
2.2.1. Data Collection and Use
Meteorological, Hydrological, and Topographical Data
2.3. Basin Future Climate Change Scenario and the Selected Model
Bias Correction
2.4. Hydrological Component of the SWAT Model
2.4.1. Surface Runoff
2.4.2. Peak Discharge
- Qpeak is peak runoff rate (m3/s),
- C is the runoff coefficient,
- i is the rainfall intensity (mm/hr.),
- Sub-basin area (km2) and 3.6 is conversion factor.
2.4.3. Water Yield
2.5. Evaluation of the SWAT Model Performance
2.5.1. Coefficient of Determination (R2)
- Oi denotes observed flow discharge at the time i,
- Omean denotes average observed flow discharge,
- Pi denotes simulated flow discharge at the time i,
- R2 provides the strength of relation between observed and simulated values. Its value ranges from 0 to 1, a value close to 0 means very low correlation whereas a value close to 1 represents high correlation between observed and simulated discharge.
2.5.2. Simulation Coefficient of Nash—Sutcliffe (NSE)
2.5.3. Percentage Bias (PBIAS)
3. Results and Discussion
3.1. Hydro-Meteorological Database Results
3.1.1. Test Analysis of Rainfall Trends in the Study Area
3.1.2. Test Temperature Trend Analysis on the Study Area
3.1.3. Stream Flow Trends Test Analysis over the Study Area
3.2. Hydrological Modeling Result
Sensitivity Analysis
3.3. Hydrological Model Calibration and Validation (SWAT)
3.3.1. Calibration Model
3.3.2. Validation Model
3.4. Evaluation of Surface Water Availability in the Present Climate
3.4.1. Monthly, Yearly, and Yearly Climate
3.4.2. Water Balance Components of the Baseline Period (1991–2020)
3.4.3. Monthly, Seasonal, and Annual Stream Flow under Current Climate
3.5. Scenarios for Future Climate Change Signals
3.6. Impact of Climate Change on Future Surface Water Availability
3.6.1. Future Components of the Water Balance
3.6.2. Future Monthly Mean Flow
3.7. Monthly Flow for RCP Scenario
3.7.1. Average Seasonal and Yearly Flows in the Future Climate
3.7.2. Analysis of Uncertainties
- (1)
- internal variability of the climate system
- (2)
- uncertainty in future greenhouse gas,
- (3)
- the translation of these emissions into climate change by GCMs/RCMs,
- (4)
- hydrological model uncertainty,
- (5)
- uncertainty from insufficient field data at all scales ([37]), and
- (6)
- uncertainty of downscaling techniques [38].
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Station Name | Zone | Station Elevation | Latitude | Longitude | Data Coverage | % of Missing Rainfall | % of Missing Temp. (°C) |
---|---|---|---|---|---|---|---|
Agaro | Jimma | 1666 | 7.85 | 36.6 | 1991–2020 | 22 | 22.5 |
Arjo | East wollega | 2565 | 8.75 | 36.5 | 1991–2020 | 21 | 37.5 |
Bedele | Illubabor | 2011 | 8.45 | 36.33 | 1991–2020 | 21 | 17.5 |
Didhessa | East wollega | 1310 | 9.38 | 36.1 | 1991–2020 | 20 | 46 |
Nekemte | East wollega | 2080 | 9.08 | 36.46 | 1991–2020 | 21 | 20.5 |
NES | PBIAS | R2 | Classification |
---|---|---|---|
0.75 < NES ≤ 1 | PBIAS ≤ ±10 | 0.75 < R2 ≤ 1 | Very good |
0.6 < NES ≤ 0.75 | ±10 ≤ PBIAS ≤ ±15 | 0.6 < R2 ≤ 0.75 | Good |
0.36 < NES ≤ 0.6 | ±15 ≤ PBIAS ≤ ±25 | 0.5 < R2 ≤ 0.6 | Satisfactory |
0.00 < NES ≤ 0.36 | ±25 ≤ PBIAS ≤ ±50 | 0.25 < R2 ≤ 0.5 | Bad |
NES ≤ 0.00 | ±50 ≤ PBIAS | R2 ≤ 0.25 | Inappropriate |
RF (1991–2020) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
Month | Agaro | Arjo | Bedele | Dhidhessa | Nekemte | |||||
Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | |
January | −1.0 | −2.7 | 2.3 | 0.9 | 1.8 | 1.1 | 0.0 | −0.8 | 2.8 | 1.2 |
February | −0.4 | −1.1 | 2.4 | 1.8 | 0.4 | 0.7 | 0.0 | 1.2 | 1.0 | 1.6 |
March | −0.5 | −71.0 | −1.6 | −1.6 | −0.2 | −0.3 | 0.2 | 0.5 | −2.2 | −1.0 |
April | −2.6 | −1.7 | −3.3 | −2.0 | −0.8 | −0.5 | −0.1 | −0.2 | −2.8 | −1.3 |
May | 1.7 | 0.8 | −5.7 | −2.3 | −3.2 | −1.0 | 3.0 | 1.1 | −7.0 | −2.2 |
June | −4.7 | −3.6 | −3.6 | −1.0 | −4.5 | −1.7 | −1.0 | −0.6 | −12.8 | −2.2 |
July | −5.5 | −2.1 | −2.7 | −0.6 | −4.1 | −2.0 | 2.3 | 0.8 | −16.4 | −1.2 |
August | −4.7 | −1.4 | 4.3 | 2.3 | −9.0 | −2.9 | 2.4 | 1.0 | 1.6 | 0.8 |
September | −3.6 | −1.3 | 10.6 | 1.9 | 1.5 | 0.7 | 2.2 | 0.8 | 4.6 | 1.3 |
October | −2.7 | −1.2 | 5.7 | 1.6 | 5.8 | 2.3 | −0.3 | −0.1 | 8.9 | 0.7 |
November | 0.2 | 0.0 | 10.5 | 0.9 | 9.1 | 1.0 | 0.8 | 1.3 | 11.4 | 1.7 |
December | −0.3 | −1.3 | 7.4 | 1.6 | 3.4 | 2.7 | 0.1 | 0.5 | 6.1 | 1.9 |
summer | −5.0 | −2.3 | −0.7 | 0.3 | −5.9 | −2.2 | 1.2 | 0.4 | −9.2 | −0.9 |
Spring | −2.0 | −0.8 | 8.9 | 1.5 | 5.5 | 1.3 | 0.9 | 0.7 | 8.3 | 1.3 |
winter | −0.6 | −1.7 | 4.0 | 1.4 | 1.9 | 1.5 | 0.0 | 0.3 | 3.3 | 1.6 |
Autumn | −0.5 | −24.0 | −3.5 | −2.0 | −1.4 | −0.6 | 1.0 | 0.5 | −4.0 | −1.5 |
Annual | −2.0 | −7.2 | 2.2 | 0.3 | 0.0 | 0.0 | 0.8 | 0.5 | −0.4 | 0.1 |
Tmax (1991–2020) | ||||||||||
Month | Agaro | Arjo | Bedele | Dhidhessa | Nekemte | |||||
Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | |
January | 0.0 | 0.3 | −0.2 | −0.4 | −0.2 | −2.2 | −0.1 | −2.1 | 0.0 | 1.0 |
February | 0.0 | 0.1 | −0.3 | −1.7 | −0.1 | −1.7 | −0.1 | −1.4 | −0.1 | 0.6 |
March | 0.0 | −0.2 | −0.3 | −1.9 | −0.2 | −3.4 | 0.0 | −0.7 | −0.1 | 0.2 |
April | 0.0 | 0.7 | −0.2 | −1.7 | −0.1 | −1.1 | 0.0 | 0.0 | 0.0 | 0.6 |
May | 0.0 | 0.0 | −0.1 | −2.0 | 0.0 | 0.8 | 0.2 | 1.9 | 0.1 | 2.1 |
June | 0.1 | 1.2 | 0.0 | 0.7 | 0.1 | 1.0 | 0.2 | 1.3 | 0.3 | 2.9 |
July | 0.2 | 0.9 | 0.1 | 2.2 | 0.1 | 2.5 | 0.1 | 0.4 | 0.2 | 1.3 |
August | 0.3 | 2.6 | 0.1 | 1.5 | 0.0 | 0.3 | 0.1 | 1.4 | 0.1 | 2.2 |
September | 0.2 | 0.2 | 0.0 | 0.5 | −0.1 | −1.5 | 0.0 | −0.8 | 0.0 | 1.1 |
October | 0.1 | 0.5 | 0.0 | 0.3 | −0.1 | −2.1 | −0.1 | −1.3 | 0.0 | −0.1 |
November | 0.2 | 0.9 | −0.1 | −0.5 | −0.1 | −3.5 | −0.1 | −2.3 | 0.0 | −0.1 |
December | 0.0 | 0.5 | −0.1 | −1.3 | −0.2 | −1.1 | −0.1 | −2.4 | −0.1 | −1.1 |
summer | 0.2 | 1.5 | 0.1 | 1.5 | 0.1 | 1.2 | 0.1 | 1.1 | 0.2 | 2.1 |
Spring | 0.2 | 0.5 | 0.0 | 0.1 | −0.1 | −2.4 | −0.1 | −1.5 | 0.0 | 0.3 |
Autumn | 0.0 | 0.3 | −0.2 | −1.1 | −0.2 | −1.7 | −0.1 | −2.0 | −0.1 | 0.2 |
winter | 0.0 | 0.2 | −0.2 | −1.9 | −0.1 | −1.2 | 0.0 | 0.4 | 0.0 | 1.0 |
Annual | 0.1 | 0.6 | −0.1 | −0.4 | −0.1 | −1.0 | 0.0 | −0.5 | 0.0 | 0.9 |
Tmin (1991–2020) | ||||||||||
Month | Agaro | Arjo | Bedele | Dhidhessa | Nekemte | |||||
Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | Sen’s Slope | Z–Value | |
January | 0.0 | −0.1 | 0.1 | 1.8 | 0.0 | 0.6 | 0.2 | 1.8 | 0.0 | 1.8 |
Feb | 0.0 | −0.1 | 0.0 | 0.6 | −0.1 | −2.0 | 0.2 | 1.9 | 0.0 | −0.5 |
Mar | 0.0 | 0.3 | −0.1 | −0.9 | −0.1 | −2.0 | 0.0 | 0.5 | −0.1 | −1.5 |
Apr | 0.0 | −0.2 | −0.1 | −1.1 | −0.1 | −1.8 | −0.1 | −0.1 | −0.1 | −0.7 |
May | 0.0 | 0.4 | 0.0 | −1.9 | −0.1 | −2.0 | −0.1 | −0.5 | −0.1 | −1.0 |
Jun | 0.0 | 0.0 | 0.0 | 1.2 | 0.0 | 0.0 | −0.1 | −0.8 | 0.1 | 2.2 |
Jul | 0.0 | 0.5 | 0.1 | 2.7 | 0.0 | −0.1 | −0.1 | −2.8 | 0.1 | 3.4 |
Aug | 0.0 | −0.1 | 0.0 | 1.4 | 0.0 | −1.0 | −0.1 | −2.2 | 0.0 | 1.1 |
September | 0.1 | 0.5 | 0.1 | 1.7 | 0.0 | −2.2 | −0.1 | −1.9 | 0.0 | 2.9 |
October | 0.1 | 0.1 | 0.1 | 0.5 | 0.0 | −0.7 | −0.1 | −1.3 | 0.0 | 1.2 |
November | 0.0 | −0.3 | 0.1 | 0.7 | 0.0 | 0.4 | 0.0 | −0.4 | 0.0 | 0.6 |
December | 0.0 | −0.1 | 0.1 | 0.7 | 0.1 | 1.9 | 0.1 | 0.8 | 0.0 | 1.1 |
summer | 0.0 | 0.2 | 0.0 | 1.8 | 0.0 | −0.4 | −0.1 | −1.9 | 0.1 | 2.3 |
Spring | 0.0 | 0.1 | 0.1 | 1.0 | 0.0 | −0.8 | −0.1 | −1.2 | 0.0 | 1.6 |
Autumn | 0.0 | −0.1 | 0.1 | 1.0 | 0.0 | 0.2 | 0.1 | 1.5 | 0.0 | 0.8 |
winter | 0.0 | 0.2 | −0.1 | −1.3 | −0.1 | −2.0 | −0.1 | 0.0 | −0.1 | −1.1 |
Annual | 0.0 | 0.1 | 0.0 | 0.6 | 0.0 | −0.7 | 0.0 | −0.4 | 0.0 | 0.9 |
Parameter Name | Fitted Value | Min Value | Max Value | t-Stat | p-Value |
---|---|---|---|---|---|
1: A_ CN2.mgt | 0.1 | 0.1 | 0.2 | 0.2 | 0.9 |
2: V__ALPHA_BF.gw | 0.5 | 0.4 | 0.5 | −1.2 | 0.2 |
3: V_GW_DELAY.gw | 471.3 | 340.6 | 488.6 | 13.8 | 0 |
4: V_GWQMN.gw | −33.2 | −39 | 10.7 | −0.9 | 0.4 |
5: V_ESCO.hru | 0.9 | 0.8 | 1 | 2 | 0.1 |
6: V_GW_REVAP.gw | 0.1 | 0.1 | 0.1 | −0.2 | 0.8 |
7: V_OV_N.hru | 0.3 | 0.3 | 0.4 | −1.2 | 0.2 |
8: V_ _SFTMP.bsn | −2.6 | −3.9 | −2.6 | −0.5 | 0.6 |
9: A_SLSUBBSN.hru | −20.8 | −31 | −18 | −0.3 | 0.8 |
I0: A__SOL_ AWC(…).sol | 0 | 0 | 0 | −1.4 | 0.2 |
11: A_SOL_K(…).sol | 0 | 0 | 0 | 0.1 | 1 |
12: V_SURLAG.bsn | −3 | −4.5 | −1.9 | 0.9 | 0.4 |
13: V_RCHRG_DP.gw | 1 | 1 | 1.3 | −0.2 | 0.8 |
14: R_LAT_TTIME.hru | 0.3 | −0.2 | 0.6 | 1.1 | 0.3 |
15: R_CH_ N2.rte | 0 | 0 | 0.1 | 0.1 | 0.9 |
16: R_CANMX.hru | 0.7 | 0.5 | 0.8 | 0.6 | 0.6 |
17: R_RFINC(…).sub | −0.6 | −0.6 | −0.3 | 0 | 1 |
18: R_ CNCOEF.bsn | 1.2 | 1.2 | 1.3 | −0.6 | 0.6 |
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Merga, D.D.; Adeba, D.; Regasa, M.S.; Leta, M.K. Evaluation of Surface Water Resource Availability under the Impact of Climate Change in the Dhidhessa Sub-Basin, Ethiopia. Atmosphere 2022, 13, 1296. https://doi.org/10.3390/atmos13081296
Merga DD, Adeba D, Regasa MS, Leta MK. Evaluation of Surface Water Resource Availability under the Impact of Climate Change in the Dhidhessa Sub-Basin, Ethiopia. Atmosphere. 2022; 13(8):1296. https://doi.org/10.3390/atmos13081296
Chicago/Turabian StyleMerga, Damtew Degefe, Dereje Adeba, Motuma Shiferaw Regasa, and Megersa Kebede Leta. 2022. "Evaluation of Surface Water Resource Availability under the Impact of Climate Change in the Dhidhessa Sub-Basin, Ethiopia" Atmosphere 13, no. 8: 1296. https://doi.org/10.3390/atmos13081296