Model-Based Assessment of Preventive Drought Management Measures’ Effect on Droughts Severity
Abstract
:1. Introduction
2. Materials and Methods
2.1. Case of Study
2.2. Hydrological Modeling
2.2.1. Model Setup
2.2.2. Model Sensitivity Analysis and Calibration
2.2.3. Modeling PDMMs
2.3. Applying the Threshold Level Method to Analyze the Effect of PDMMs on Drought Severity
2.3.1. Setting the Thresholds to Identify Droughts
2.3.2. Identifying Drought Events and Calculating Drought Severity
2.3.3. Estimating Changes in Drought Severity
3. Results and Discussion
3.1. Sensitivity Analysis and Model Calibration
3.2. Agricultural and Hydrological Droughts in the Baseline Scenario
3.3. Effect of PDMMs on Drought Severity
3.3.1. Effect RWH Ponds on Drought Severity
3.3.2. Effect of Forest Conservation on Droughts Severity
3.3.3. Effect of Check Dams and Ponds on Droughts Severity
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Data Type | Details | Source |
---|---|---|
Digital elevation model | 5 × 5 m | Ministry of Environment and Natural Resources, El Salvador. |
Soil map | 300 × 300 m | Digital Soil Map of the World [20]. |
Land use map | 300 × 300 m | Global land cover distribution, by dominant land cover type (FGGD) [21]. |
Rainfall and temperature, daily data (2 stations) | Period 2004–2018 (15 years) | Ministry of Environment and Natural Resources, El Salvador. |
Discharge, monthly data (1 station) | Period 2004–2018 (15 years) | Ministry of Environment and Natural Resources, El Salvador. |
Criteria | RWH Ponds | Forest Conservation | Check Dams |
---|---|---|---|
Description | Designed to trap and collect runoff from a relatively small catchment area (10–500 m2) [24]. | Forest conservation aims to maintain forest cover and limit soil degradation [25]. | Small barriers constructed across channels to obstruct flow [26]. |
Annual rainfall | 200–1000 mm [27]. | NA. | Used frequently in arid or mountainous environments with ephemeral hydrology [28]. |
Topography | Steeply and mild slopes [29]. | NA. | Steep and mild slopes [30]. |
Soil type | Sandy loam, sandy clay loam, and sandy clays [29]. | NA. | On areas with coarse soil texture [28]. |
Land use compatibility | Applied in agricultural land [31]. | Land where forest is, or is planned to become, the dominant land use [25]. | Where the slope is mild and the area is sufficient to store discharge and sediment [30]. |
Parameter(s) to model the measure in SWAT | Pothole routine: POT_FR a (0.3), POT_VOLX b (20 cm), [32]. | CN2 c value of forested HRUs was reduced from the calibrated value to the recommended value for forest in good hydrological conditions [33]. | Ponds: PND_FR d (0.3), PND_PVOL e (5 × 104 m3), PND_PSA f (1 ha) [34]. |
No. of PDMM applied | 140 potholes were applied at HRU level (140 HRUs met the allocation criteria). | – | 17 ponds were applied at the subbasin level (17 subbasins met the allocation criteria). |
Measures allocation |
Parameter a | Description in SWAT | Range | Default Value | Calibrated Value |
---|---|---|---|---|
r__SOL_Z().sol | Depth from soil surface to bottom of layer (mm). | 0–3500 | Soil and layer specific | 300–1000 b |
r__SOL_BD().sol | Moist bulk density (g/cm3). | 0.9–2.5 | Soil and layer specific | 1.0–1.3 b |
r__SOL_AWC().sol | Available water capacity of the soil layer (mm H20/mm soil). | 0–1 | Soil and layer specific | 0.1–0.2 b |
r__SOL_K().sol | Saturated hydraulic conductivity (mm/h). | 0–2000 | Soil and layer specific | 8.0–45.0 b |
r__CN2.mgt | SCS runoff curve number. | 35–98 | Specific HRU | 70–85 b |
v__RCHRG_DP.gw | Deep aquifer percolation fraction. | 0–1 | 0.05 | 0.02 |
v__GWQMN.gw | Threshold depth of water in the shallow aquifer required for return flow to occur. | 0–5000 | 1000 | 4642 |
v__GW_DELAY.gw | Groundwater delay (days). | 0–500 | 31 | 4.0 |
r__ESCO.hru | Soil evaporation compensation factor. | 0–1 | 0.95 | 0.51 |
v__CH_N2.rte | Manning’s for the main channel. | −0.01–0.3 | 0.014 | 0.10 |
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Paez-Trujillo, A.; Corzo, G.A.; Maskey, S.; Solomatine, D. Model-Based Assessment of Preventive Drought Management Measures’ Effect on Droughts Severity. Water 2023, 15, 1442. https://doi.org/10.3390/w15081442
Paez-Trujillo A, Corzo GA, Maskey S, Solomatine D. Model-Based Assessment of Preventive Drought Management Measures’ Effect on Droughts Severity. Water. 2023; 15(8):1442. https://doi.org/10.3390/w15081442
Chicago/Turabian StylePaez-Trujillo, Ana, Gerald A. Corzo, Shreedhar Maskey, and Dimitri Solomatine. 2023. "Model-Based Assessment of Preventive Drought Management Measures’ Effect on Droughts Severity" Water 15, no. 8: 1442. https://doi.org/10.3390/w15081442
APA StylePaez-Trujillo, A., Corzo, G. A., Maskey, S., & Solomatine, D. (2023). Model-Based Assessment of Preventive Drought Management Measures’ Effect on Droughts Severity. Water, 15(8), 1442. https://doi.org/10.3390/w15081442