| 1. |
- Canedo, Claudia, et al.
(författare)
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Role of hydrological studies for the development of the TDPS system
- 2016
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Ingår i: Water. - : MDPI AG. - 2073-4441. ; 8:4
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Forskningsöversikt (refereegranskat)abstract
- The South American Altiplano in the Andes is, aside from Tibet, the most extensive high plateau on Earth. This semiarid area represents important water resources storages, including the Lakes Titicaca and Poopó located in the northern and central Altiplano, respectively. The two lake basins and the southern saltpans constitute a large watershed, called the Lake Titicaca, Desaguadero River, Lake Poopó, and Coipasa Salt Flat System (TDPS hydrologic system). The Altiplano climate, topography, and location determine the TDPS hydrologic functioning. Scarce data and high spatial variability represent challenges to correctly simulate the TDPS water budget. Consequently, there is an important need to improve the understanding of the water resources in current and future climate over the area. The paper provides a comprehensive state-of-the-art regarding current knowledge of the TDPS hydro-socioeconomic system and summarizes the data needs to improve the current hydrological understanding.
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| 2. |
- Pham, Quoc Bao, et al.
(författare)
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Prediction of lake water-level fluctuations using adaptive neuro-fuzzy inference system hybridized with metaheuristic optimization algorithms
- 2023
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Ingår i: Applied water science. - : Springer Science and Business Media LLC. - 2190-5487 .- 2190-5495. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Lakes help increase the sustainability of the natural environment and decrease food chain risk, agriculture, ecosystem services, and leisure recreational activities locally and globally. Reliable simulation of monthly lake water levels is still an ongoing demand for multiple environmental and hydro-informatics engineering applications. The current research aims to utilize newly developed hybrid data-intelligence models based on the ensemble adaptive neuro-fuzzy inference system (ANFIS) coupled with metaheuristics algorithms for lake water-level simulation by considering the effect of seasonality on Titicaca Lake water-level fluctuations. The classical ANFIS model was trained using three metaheuristics nature-inspired optimization algorithms, including the genetic algorithm (ANFIS-GA), particle swarm optimizer (ANFIS-PSO), and whale optimization algorithm (ANFIS-WOA). For determining the best set of the input variables, an evolutionary approach based on several lag months has been utilized prior to the lake water-level simulation process using the hybrid models. The proposed hybrid models were investigated for accurately simulating the monthly water levels at Titicaca Lake. The ANFIS-WOA model exhibited the best prediction performance for lake water-level pattern measurement in this study. For the best scenario (the inputs were Xt-1,Xt-2,Xt-3,Xt-4,Xt-12) the ANFIS-WOA model attained root mean square error (RMSE ≈ 0.08 m), mean absolute error (MAE ≈ 0.06 m), and coefficient of determination (R2≈ 0.96). Also, the results showed that long-term seasonal memory for this lake is suitable input for lake water-level models so that the long-term dynamic memory of 1-year time series for lake water-level data is the best input for estimating the water level of Titicaca Lake.
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| 3. |
- Pillco Zolá, Ramiro, et al.
(författare)
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Modelling Lake Titicaca's daily and monthly evaporation
- 2019
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Ingår i: Hydrology and Earth System Sciences. - : Copernicus GmbH. - 1027-5606 .- 1607-7938. ; 23:2, s. 657-668
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Tidskriftsartikel (refereegranskat)abstract
- Lake Titicaca is a crucial water resource in the central part of the Andean mountain range, and it is one of the lakes most affected by climate warming. Since surface evaporation explains most of the lake's water losses, reliable estimates are paramount to the prediction of global warming impacts on Lake Titicaca and to the region's water resource planning and adaptation to climate change. Evaporation estimates were done in the past at monthly time steps and using the four methods as follows: water balance, heat balance, and the mass transfer and Penman's equations. The obtained annual evaporation values showed significant dispersion. This study used new, daily frequency hydro-meteorological measurements. Evaporation losses were calculated following the mentioned methods using both daily records and their monthly averages to assess the impact of higher temporal resolution data in the evaporation estimates. Changes in the lake heat storage needed for the heat balance method were estimated based on the morning water surface temperature, because convection during nights results in a well-mixed top layer every morning over a constant temperature depth. We found that the most reliable method for determining the annual lake evaporation was the heat balance approach, although the Penman equation allows for an easier implementation based on generally available meteorological parameters. The mean annual lake evaporation was found to be 1700 mm year. This value is considered an upper limit of the annual evaporation, since the main study period was abnormally warm. The obtained upper limit lowers by 200 mm yearĝ'1, the highest evaporation estimation obtained previously, thus reducing the uncertainty in the actual value. Regarding the evaporation estimates using daily and monthly averages, these resulted in minor differences for all methodologies.
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