1. |
- Al-Madhlom, Qais, et al.
(author)
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Seepage Velocity : Large Scale Mapping and the Evaluation of Two Different Aquifer Conditions (Silty Clayey and Sandy)
- 2020
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In: Hydrology. - Switzerland : MDPI. - 2306-5338 .- 2306-5338. ; 7:3
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Journal article (peer-reviewed)abstract
- Seepage velocity is a very important criterion in infrastructure construction. The planning of numerous large infrastructure projects requires the mapping of seepage velocity at a large scale. To date, however, no reliable approach exists to determine seepage velocity at such a scale. This paper presents a tool within ArcMap/Geographic Information System (GIS) software that can be used to map the seepage velocity at a large scale. The resultant maps include both direction and magnitude mapping of the seepage velocity. To verify the GIS tool, this study considered two types of aquifer conditions in two regions in Iraq: silty clayey (Babylon province) and sandy (Dibdibba in Karbala province). The results indicate that, for Babylon province, the groundwater flows from the northwest to southeast with a seepage velocity no more than 0.19 m/d; for the Dibdibba region, the groundwater flows from the west to the east with a seepage velocity not exceeding 0.27 m/d. The effectiveness of the presented tool in depicting the seepage velocity was thus demonstrated. The accuracy of the resultant maps depends on the resolution of the four essential maps (groundwater elevation head, effective porosity, saturated thickness, and transmissivity) and locations of wells that are used to collect the data.
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2. |
- Awad, Ahmed, et al.
(author)
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Evaluation of the DRAINMOD Model’s Performance Using Different Time Steps in Evapotranspiration Computations
- 2022
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In: Hydrology. - : MDPI. - 2306-5338. ; 9:2
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Journal article (peer-reviewed)abstract
- The DRAINMOD model is a superior tool used to predict the changes in farmland water balance under different agricultural drainage layouts, fields, weather conditions, and management practices. In the present study, we assessed the sensitivity of the DRAINMOD predictions in farmland water balance to the time step (hourly or daily) in daily evapotranspiration (ET0 ) computations for 12-hectares of farmland located at the lower reaches of the Yangtze River basin. The model was calibrated and validated and then was applied twice under two sets of daily ET0 values, computed using the standardized ASCE Penman–Monteith model (one using the hourly time step (HTS) and the other using the daily time step (DTS)). Regarding daily computed ET0 values, results show that abrupt diurnal changes in the weather always result in significant differences between daily ET0 values when computed based on DTS and HTS. DRAINMOD simulations show that such differences between daily computed ET0 values affected the model’s predictions of the “water fate” in the study area; e.g., adopting HTS rather than DTS resulted in a 4.8% increase, and a 3.1% and 1% decrease in the models’ cumulative predictions of runoff, drainage, and infiltration, respectively. Therefore, for a particular study area, it is critical to pay attention when deciding the best time step in ET0 computations to ensure accurate DRAINMOD simulations, thereby ensuring better utilization of agricultural water alongside high agricultural productivity.
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3. |
- Dimple, Dimple, et al.
(author)
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Determining the Hydrological Behaviour of Catchment Based on Quantitative Morphometric Analysis in the Hard Rock Area of Nand Samand Catchment, Rajasthan, India
- 2022
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In: Hydrology. - : MDPI. - 2306-5338. ; 9:2
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Journal article (peer-reviewed)abstract
- India’s water resources are under tremendous pressure due to elevated demand for various purposes. The over-exploitation of these valuable resources has resulted in an imbalance in the watershed ecology. The application of spatial analysis tools in studying the morphological behaviour of watersheds has increased in recent decades worldwide due to the accessibility of the geospatial database. A morphometric analysis of a river basin is vital to determine the hydrological behaviour to develop effective management. Under the current study, morphological behaviour of Nand Samand catchment in the hard rock region was evaluated employing remote sensing (RS) and geographical information system (GIS) tools. The Nand Samand catchment (Rajasthan State, India) has an area of 865.18 km2 with the highest and lowest elevations of 1318 m and 570 m above mean sea level, respectively. This study utilises a 30 m high-spatial-resolution ASTER imagery digital elevation model for delineating the catchment. The drainage network is assessed using a GIS method, and morphometric parameters like linear, areal, and relief aspects were calculated. Results were obtained for parameters viz., basin length of 82.66 km, constant channel maintenance equal to 0.68 km, stream frequency of 2.11 km−2, drainage density of 1.48 km−1, and length overflow of 0.34 km. Form factor of 0.13, and the circulatory ratio of 0.28 showed that an elongated shape characterises the study area. The results would help understand the relationship between hydrological variables and geomorphological parameters for better decision-making. The techniques used could effectively help to perform better drainage basin and channel network morphometric analyses. The found morphometric characteristics will be helpful in understanding the Nand Samand catchment and similar areas in India in order to better guide the decision-makers in providing adequate policy to the development of the region
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4. |
- Ewaid, Salam Hussein, et al.
(author)
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Development and Evaluation of a Water Quality Index for the Iraqi Rivers
- 2020
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In: Hydrology. - Switzerland : MDPI. - 2306-5338. ; 7:3
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Journal article (peer-reviewed)abstract
- Water quality evaluation is fundamental for water resources management. Water quality index (WQI) is an accurate and easily understandable method for assessing water quality for different purposes. In this study, the Iraqi water quality index (Iraq WQI) was constructed to be used to evaluate the Iraqi rivers for drinking. For this purpose, some statistical techniques, experts’ advice, literature reviews, and authors’ experience were used. First, the principal component analysis (PCA) method and the modified Delphi method were used to select the most influential water quality parameters and their relative weights. Second, the quality curves of selected parameters were drawn to calculate the WQI scores basing on the water quality standards. Of twenty-seven parameters, six parameters were chosen to be within the index depending on their effect on water quality in order to reflect the specific characteristics of the Iraqi waters. The Iraq WQI was applied to the Tigris River within Baghdad as a case study and for some sites on other Iraqi rivers, and gave acceptable results. Results revealed that the statistical techniques used in this paper can be applied in all Iraqi rivers considering their specific characteristics. Based on the reliability of the Iraq WQI, there is no longer a need to use Indices designed for water for other countries.
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5. |
- Feiccabrino, James, et al.
(author)
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Meteorological Knowledge Useful for the Improvement of Snow Rain Separation in Surface Based Models
- 2015
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In: Hydrology. - : MDPI AG. - 2306-5338. ; 2:4, s. 266-288
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Journal article (peer-reviewed)abstract
- An accurate precipitation phase determination—i.e., solid versus liquid—is of paramount importance in a number of hydrological, ecological, safety and climatic applications. Precipitation phase can be determined by hydrological, meteorological or combined approaches. Meteorological approaches require atmospheric data that is not often utilized in the primarily surface based hydrological or ecological models. Many surface based models assign precipitation phase from surface temperature dependent snow fractions, which assume that atmospheric conditions acting on hydrometeors falling through the lower atmosphere are invariant. This ignores differences in phase change probability caused by air mass boundaries which can introduce a warm air layer over cold air leading to more atmospheric melt energy than expected for a given surface temperature, differences in snow grain-size or precipitation rate which increases the magnitude of latent heat exchange between the hydrometers and atmosphere required to melt the snow resulting in snow at warmer temperatures, or earth surface properties near a surface observation point heating or cooling a shallow layer of air allowing rain at cooler temperatures or snow at warmer temperatures. These and other conditions can be observed or inferred from surface observations, and should therefore be used to improve precipitation phase determination in surface models.
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6. |
- Hamdan, Ahmed Naseh Ahmed, et al.
(author)
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Rainfall-runoff modeling using the hec-hms model for the al-adhaim river catchment, northern iraq
- 2021
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In: Hydrology. - : MDPI AG. - 2306-5338. ; 8:2
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Journal article (peer-reviewed)abstract
- It has become necessary to estimate the quantities of runoff by knowing the amount of rainfall to calculate the required quantities of water storage in reservoirs and to determine the likelihood of flooding. The present study deals with the development of a hydrological model named Hydrologic Engineering Center (HEC-HMS), which uses Digital Elevation Models (DEM). This hydrological model was used by means of the Geospatial Hydrologic Modeling Extension (HEC-GeoHMS) and Geographical Information Systems (GIS) to identify the discharge of the Al-Adhaim River catchment and embankment dam in Iraq by simulated rainfall-runoff processes. The meteorological models were developed within the HEC-HMS from the recorded daily rainfall data for the hydrological years 2015 to 2018. The control specifications were defined for the specified period and one day time step. The Soil Conservation Service-Curve number (SCS-CN), SCS Unit Hydrograph and Muskingum methods were used for loss, transformation and routing calculations, respectively. The model was simulated for two years for calibration and one year for verification of the daily rainfall values. The results showed that both observed and simulated hydrographs were highly correlated. The model’s performance was evaluated by using a coefficient of determination of 90% for calibration and verification. The dam’s discharge for the considered period was successfully simulated but slightly overestimated. The results indicated that the model is suitable for hydrological simulations in the Al-Adhaim river catchment.
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7. |
- Lundberg, Angela, et al.
(author)
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Spatiotemporal Variations in Snow and Soil Frost : A Review of Measurement Techniques
- 2016
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In: Hydrology. - : MDPI AG. - 2306-5338. ; 3:3
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Journal article (peer-reviewed)abstract
- Large parts of the northern hemisphere are covered by snow and seasonal frost. Climate warming is affecting spatiotemporal variations of snow and frost, hence influencing snowmelt infiltration, aquifer recharge and river runoff patterns. Measurement difficulties have hampered progress in properly assessing how variations in snow and frost impact snowmelt infiltration. This has led to contradicting findings. Some studies indicate that groundwater recharge response is scale dependent. It is thus important to measure snow and soil frost properties with temporal and spatial scales appropriate to improve infiltration process knowledge. The main aim with this paper is therefore to review ground based methods to measure snow properties (depth, density, water equivalent, wetness, and layering) and soil frost properties (depth, water and ice content, permeability, and distance to groundwater) and to make recommendations for process studies aiming to improve knowledge regarding infiltration in regions with seasonal frost. Ground-based radar (GBR) comes in many different combinations and can, depending on design, be used to assess both spatial and temporal variations in snow and frost so combinations of GBR and tracer techniques can be recommended and new promising methods (auocostics and self potential) are evolving, but the study design must be adapted to the scales, the aims and the resources of the study. View Full-Text
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8. |
- Mehdizadeh, Saeid, et al.
(author)
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Establishing Coupled Models for Estimating Daily Dew Point Temperature Using Nature-Inspired Optimization Algorithms
- 2022
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In: Hydrology. - : MDPI AG. - 2306-5338. ; 9:1
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Journal article (peer-reviewed)abstract
- Potential of a classic adaptive neuro-fuzzy inference system (ANFIS) was evaluated in the current study for estimating the daily dew point temperature (Tdew). The study area consists of two stations located in Iran, namely the Rasht and Urmia. The daily Tdew time series of the studied stations were modeled through the other effective variables comprising minimum air temperature (Tmin), extraterrestrial radiation (Ra), vapor pressure deficit (VPD), sunshine duration (n), and relative humidity (RH). The correlation coefficients between the input and output parameters were utilized to determine the most effective inputs. Furthermore, novel hybrid models were proposed in this study in order to increase the estimation accuracy of Tdew. For this purpose, two optimization algorithms named bee colony optimization (BCO) and dragonfly algorithm (DFA) were coupled on the classic ANFIS. It was concluded that the hybrid models (i.e., ANFIS-BCO and ANFIS-DFA) demonstrated better performances compared to the classic ANFIS. The full-input pattern of the coupled models, specifically the ANFIS-DFA, was found to present the most accurate results for both the selected stations. Therefore, the developed hybrid models can be proposed as alternatives to the classic ANFIS to accurately estimate the daily Tdew.
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9. |
- Wang, Ling, et al.
(author)
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Effect of Observation Errors on the Timing of the Most Informative Isotope Samples for Event-Based Model Calibration
- 2018
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In: HYDROLOGY. - : MDPI. - 2306-5338. ; 5:1
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Journal article (peer-reviewed)abstract
- Many studies have shown that isotope data are valuable for hydrological model calibration. Recent developments have made isotope analyses more accessible but event sampling still involves significant time and financial costs. Therefore, it is worth to study how many isotope samples are needed for hydrological model calibration and what the most informative sampling times are. In this study, we used synthetic data to investigate how systematic errors in the precipitation, streamflow and the isotopic composition of precipitation affect the information content of stream isotope samples for model calibration. The results show that model performance improves significantly when two or three isotope samples are used for calibration and that the most informative samples are taken on the falling limb. However, when there are errors in the rainfall isotopic composition, rising limb samples are more informative. Data errors caused the most informative samples to be more clustered and to occur earlier in the event compared to error free data. These results provide guidance on when to sample events for model calibration and thus help to reduce the cost and effort in obtaining useful data for model calibration.
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10. |
- Zanchi, Giuliana, et al.
(author)
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A Hydrological Concept including Lateral Water Flow Compatible with the Biogeochemical Model ForSAFE
- 2016
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In: Hydrology — Open Access Journal. - : MDPI AG. - 2306-5338. ; 3:1
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Journal article (peer-reviewed)abstract
- The study presents a hydrology concept developed to include lateral water flow in the biogeochemical model ForSAFE. The hydrology concept was evaluated against data collected at Svartberget in the Vindeln Research Forest in Northern Sweden. The results show that the new concept allows simulation of a saturated and an unsaturated zone in the soil as well as water flow that reaches the stream comparable to measurements. The most relevant differences compared to streamflow measurements are that the model simulates a higher base flow in winter and lower flow peaks after snowmelt. These differences are mainly caused by the assumptions made to regulate the percolation at the bottom of the simulated soil columns. The capability for simulating lateral flows and a saturated zone in ForSAFE can greatly improve the simulation of chemical exchange in the soil and export of elements from the soil to watercourses. Such a model can help improve the understanding of how environmental changes in the forest landscape will influence chemical loads to surface waters.
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11. |
- Alawsi, Mustafa A., et al.
(author)
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Drought Forecasting: A Review and Assessment of the Hybrid Techniques and Data Pre-Processing
- 2022
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In: Hydrology. - : MDPI. - 2306-5338. ; 9:7
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Research review (peer-reviewed)abstract
- Drought is a prolonged period of low precipitation that negatively impacts agriculture, animals, and people. Over the last decades, gradual changes in drought indices have been observed. Therefore, understanding and forecasting drought is essential to avoid its economic impacts and appropriate water resource planning and management. This paper presents a recent literature review, including a brief description of data pre-processing, data-driven modelling strategies (i.e., univariate or multivariate), machine learning algorithms (i.e., advantages and disadvantages), hybrid models, and performance metrics. Combining various prediction methods to create efficient hybrid models has become the most popular use in recent years. Accordingly, hybrid models have been increasingly used for predicting drought. As such, these models will be extensively reviewed, including preprocessing-based hybrid models, parameter optimisation-based hybrid models, and hybridisation of components combination-based with preprocessing-based hybrid models. In addition, using statistical criteria, such as RMSE, MAE, NSE, MPE, SI, BIC, AIC, and AAD, is essential to evaluate the performance of the models.
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12. |
- Gabr, Mohamed Elsayed, et al.
(author)
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Proposing a Wetland-Based Economic Approach for Wastewater Treatment in Arid Regions as an Alternative Irrigation Water Source
- 2023
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In: Hydrology. - : MDPI. - 2306-5338. ; 10:1
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Journal article (peer-reviewed)abstract
- Point and nonpoint wastewater sources have a detrimental, negative effect on agriculture, soil, surface, and groundwater supplies. In this research, a wastewater treatment system made up of a sedimentation tank, a horizontal subsurface flow constructed wetland (HSSF-CW), a vertical subsurface flow constructed wetland (VF-CW), and a storage tank was proposed, designed, and cost estimated. Small populations in underdeveloped nations with dry and semi-arid climates can use the treatment system as an affordable construction, maintenance, and operational solution for wastewater treatment. The system will protect agricultural lands and groundwater from pollution. The system can service 6000 capita and has a wastewater discharge of 780 m3/d in the developing arid region in El-Moghra Oasis western desert of Egypt, where the 1.5 million acres used for the land reclamation project based on groundwater irrigation. The relaxed tanks in a series model based on the areal loading rates and background pollutants concentrations (P-K-C*) was utilized to size the HSSF and VF-CWs. The results indicated that the HSSF-CW design treatment surface area was 2375 m2, and the hydraulic surface loading (q) and hydraulic retention time (RT) were 0.33 m/d and 0.55 d, respectively, and utilizing Phragmites australis and Papyrus for the biological treatment. The expected overall cumulative removal efficiencies were 96.7, 70, and 100% for the biological oxygen demand (BOD), total phosphors (TP), and fecal coliforms (FC), respectively. The VF-CW indicates that there was a 2193 m2 design treatment surface area, q = 0.36 m/d, and RT of 0.63 d. The expected BOD, TP, and FC removal efficiencies were 75, 33.3, and 92.7%, respectively. In order to simplify the design stages and the cost estimation, design and investment cost curves were established for a population range from 500 to 9000. The total monthly water loss due to evapotranspiration for the HSSF and VF-CWs indicates a range from 3.7 to 8.5%, respectively. The total investment cost analysis for the proposed system corresponding to 780 m3/d wastewater discharge of indicates a total investment cost of EUR 146,804 and EUR 24.46/per-capita equivalent (P.E). This approach can be used by decision makers in the Mediterranean region and Middle Eastern countries to improve the water quality using social and economic criteria, leading to the effective implementation of ecological restoration projects as a low-cost treatment system and adding a nonconventional water source that can be used in irrigation.
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13. |
- Kareem, Baydaa Abdul, et al.
(author)
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Applicability of ANN Model and CPSOCGSA Algorithm forMulti-Time Step Ahead River Streamflow Forecasting
- 2022
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In: Hydrology. - : MDPI. - 2306-5338. ; 9:10
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Journal article (peer-reviewed)abstract
- Accurate streamflow prediction is significant when developing water resource management and planning, forecasting floods, and mitigating flood damage. This research developed a novel methodology that involves data pre-processing and an artificial neural network (ANN) optimised with the coefficient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA-ANN) to forecast the monthly water streamflow. The monthly streamflow data of the Tigris River at Amarah City, Iraq, from 2010 to 2020, were used to build and evaluate the suggested methodology. The performance of CPSOCGSA was compared with the slim mold algorithm (SMA) and marine predator algorithm (MPA). The principal findings of this research are that data pre-processing effectively improves the data quality and determines the optimum predictor scenario. The hybrid CPSOCGSA-ANN outperformed both the SMA-ANN and MPA-ANN algorithms. The suggested methodology offered accurate results with a coefficient of determination of 0.91, and 100% of the data were scattered between the agreement limits of the Bland–Altman diagram. The research results represent a further step toward developing hybrid models in hydrology applications.
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14. |
- Malekmohammadi, Bahram, et al.
(author)
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Environmental Risk Assessment of Wetland Ecosystems Using Bayesian Belief Networks
- 2023
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In: Hydrology. - : MDPI AG. - 2306-5338. ; 10:1
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Journal article (peer-reviewed)abstract
- Wetlands are valuable natural capital and sensitive ecosystems facing significant risks from anthropogenic and climatic stressors. An assessment of the environmental risk levels for wetlands’ dynamic ecosystems can provide a better understanding of their current ecosystem health and functions. Different levels of environmental risk are defined by considering the categories of risk and the probability and severity of each in the environment. Determining environmental risk levels provides a general overview of ecosystem function. This mechanism increases the visibility of risk levels and their values in three distinct states (i.e., low, moderate, and high) associated with ecosystem function. The Bayesian belief network (BBN) is a novel tool for determining environmental risk levels and monitoring the effectiveness of environmental planning and management measures in reducing the levels of risk. This study develops a robust methodological framework for determining the overall level of risks based on a combination of varied environmental risk factors using the BBN model. The proposed model is adopted for a case study of Shadegan International Wetlands (SIWs), which consist of a series of Ramsar wetlands in the southwest of Iran with international ecological significance. A comprehensive list of parameters and variables contributing to the environmental risk for the wetlands and their relationships were identified through a review of literature and expert judgment to develop an influence diagram. The BBN model is adopted for the case study location by determining the states of variables in the network and filling the probability distribution tables. The environmental risk levels for the SIWs are determined based on the results obtained at the output node of the BBN. A sensitivity analysis is performed for the BBN model. We proposed model-informed management strategies for wetland risk control. According to the BBN model results, the SIWs ecosystems are under threat from a high level of environmental risk. Prolonged drought has been identified as the primary contributor to the SIWs’ environmental risk levels.
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15. |
- Mohammadi, Babak
(author)
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Modeling Various Drought Time Scales via a Merged Artificial Neural Network with a Firefly Algorithm
- 2023
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In: Hydrology. - : MDPI AG. - 2306-5338. ; 10:3
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Journal article (peer-reviewed)abstract
- Drought monitoring and prediction have important roles in various aspects of hydrological studies. In the current research, the standardized precipitation index (SPI) was monitored and predicted in Peru between 1990 and 2015. The current study proposed a hybrid model, called ANN-FA, for SPI prediction in various time scales (SPI3, SPI6, SPI18, and SPI24). A state-of-the-art firefly algorithm (FA) has been documented as a powerful tool to support hydrological modeling issues. The ANN-FA uses an artificial neural network (ANN) which is coupled with FA for Lima SPI prediction via other stations. Through the intelligent utilization of SPI series from neighbors’ stations as model inputs, the suggested approach might be used to forecast SPI at various time scales in a meteorological station with insufficient data. To conduct this, the SPI3, SPI6, SPI18, and SPI24 were modeled in Lima meteorological station using other meteorological stations’ datasets in Peru. Various error criteria were employed to investigate the performance of the ANN-FA model. Results showed that the ANN-FA is an effective and promising approach for drought prediction and also a multi-station strategy is an effective strategy for SPI prediction in the meteorological station with a lack of data. The results of the current study showed that the ANN-FA approach can help to predict drought with the mean absolute error = 0.22, root mean square error = 0.29, the Pearson correlation coefficient = 0.94, and index of agreement = 0.97 at the testing phase of best estimation (SPI3).
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16. |
- Raza, Ali, et al.
(author)
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Misconceptions of Reference and Potential Evapotranspiration: A PRISMA-Guided Comprehensive Review
- 2022
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In: Hydrology. - : MDPI. - 2306-5338. ; 9:9
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Research review (peer-reviewed)abstract
- One of the most important parts of the hydrological cycle is evapotranspiration (ET). Accurate estimates of ET in irrigated regions are critical to the planning, control, and regulation of agricultural natural resources. Accurate ET estimation is necessary for agricultural irrigation scheduling. ET is a nonlinear and complex process that cannot be calculated directly. Reference evapotranspiration (RET) and potential evapotranspiration (PET) are two primary forms of ET. The ideas, equations, and application areas for PET and RET are different. These two terms have been confused and used interchangeably by researchers. Therefore, terminology clarification is necessary to ensure their proper use. The research indicates that PET and RET concepts have a long and distinguished history. Thornthwaite devised the original PET idea, and it has been used ever since, although with several improvements. The development of RET, although initially confused with that of PET, was formally defined as a standard method. In this study, the Preferred Reporting Item for Systematic reviews and Meta-Analysis (PRISMA) was used. Equations for RET estimation were retrieved from 44 research articles, and equations for PET estimation were collected from 26 studies. Both the PET and RET equations were divided into three distinct categories: temperature-based, radiation-based, and combination-based. The results show that, among temperature-based equations for PET, Thornthwaite's (1948) equation was mentioned in 12,117 publications, whereas among temperature-based equations for RET, Hargreaves and Samani's (1985) equation was quoted in 3859 studies. Similarly, Priestley (1972) had the most highly cited equation in radiation-based PET equations (about 6379), whereas Ritchie (1972) had the most highly cited RET equations (around 2382) in radiation-based equations. Additionally, among combination-based PET equations, Penman and Monteith's (1948) equations were cited in 9307 research studies, but the equations of Allen et al. (1998) were the subject of a significant number of citations from 23,000 publications. Based on application, PET is most often applied in the fields of hydrology, meteorology, and climatology, whereas RET is more frequently utilized in the fields of agronomy, agriculture, irrigation, and ecology. PET has been used to derive drought indices, whereas RET has been employed for single crop and dual crop coefficient approaches. This work examines and describes the ideas and methodologies, widely used equations, applications, and advanced approaches associated with PET and RET, and discusses future enhancements to increase the accuracy of ET calculation to attain accurate agricultural irrigation scheduling. The use of advanced tools such as remote sensing and satellite technologies, in addition to machine learning algorithms, will help to improve the accuracy of PET and RET estimates. Researchers will be able to distinguish between PET and RET in the future with the use of the study's results.
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17. |
- Valencia, Jhon B., et al.
(author)
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Predictive Assessment of Climate Change Impact on Water Yield in the Meta River Basin, Colombia : An InVEST Model Application
- 2024
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In: Hydrology. - 2306-5338. ; 11:2
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Journal article (peer-reviewed)abstract
- This paper presents a hydrological assessment of the 113,981 km2 Meta River basin in Colombia using 13 global climate models to predict water yield for 2050 under two CMIP6 scenarios, SSP 4.5 and SSP 8.5. Despite mixed performance across subbasins, the model was notably effective in the upper Meta River subbasin. This study predicts an overall increase in the basin's annual water yield due to increased precipitation, especially in flatter regions. Under the SSP 4.5, the Meta River basin's water flow is expected to rise from 5141.6 m3/s to 6397.5 m3/s, and to 6101.5 m3/s under the SSP 8.5 scenario, marking 24% and 19% increases in water yield, respectively. Conversely, the upper Meta River subbasin may experience a slight decrease in water yield, while the upper Casanare River subbasin is predicted to see significant increases. The South Cravo River subbasin, however, is expected to face a considerable decline in water yield, indicating potential water scarcity. This study represents a pioneering large-scale application of the InVEST-AWY model in Colombia using CMIP6 global climate models with an integrated approach to produce predictions of future water yields.
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