Browsing by Author "Gaona, Gabriel V."

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Development and assessment of seasonal rainfall forecasting models for the bani and the Senegal basins by identifying the best predictive teleconnection
    (2022) Khaliduo Mamadou, Baá
    The high variability of rainfall in the Sahel region causes droughts and floods that affect millions of people every year. Several rainfall forecasting models have been proposed, but the results still need to be improved. In this study, linear, polynomial, and exponential models are developed to forecast rainfall in the Bani and Senegal River basins. All three models use Atlantic sea surface temperature (SST). A fourth algorithm using stepwise regression was also developed for the precipitation estimates over these two basins. The stepwise regression algorithm uses SST with covariates, mean sea level pressure (MSLP), relative humidity (RHUM), and five El Niño indices. The explanatory variables SST, RHUM, and MSLP were selected based on principal component analysis (PCA) and cluster analysis to find the homogeneous region of the Atlantic with the greatest predictive ability. PERSIANN-CDR rainfall data were used as the dependent variable. Models were developed for each pixel of 0.25° × 0.25° spatial resolution. The second-order polynomial model with a lag of about 11 months outperforms all other models and explains 87% of the variance in precipitation over the two watersheds. Nash–Sutcliffe efficiency (NSE) values were between 0.751 and 0.926 for the Bani River basin and from 0.175 to 0.915 for the Senegal River basin, for which the lowest values are found in the driest area (Sahara). Results showed that the North Atlantic SST shows a more robust teleconnection with precipitation dynamics in both basins.
  • Thumbnail Image
    Item
    Spatially distributed tracer-aided modelling to explore DOC dynamics, hot spots and hot moments in a tropical mountain catchment
    (2023) Crespo Sánchez, Patricio Javier; Pesántez Jiménez, Juan Fernando; Birkel, Christian; Mosquera, Giovanny M.; Célleri Alvear, Rolando Enrique; Jiménez Zamora, Enma Lucrecia; Murray, Desneiges S.; Arciniega Esparza, Saul; Gaona, Gabriel V.
    Tracer-aided rainfall-runoff modelling is a promising tool for understanding catchment hydrology, particularly when tracers provide information about coupled hydrological-biogeochemical processes. Such models allow for predicting the quality and quantity of water under changing climatic and anthropogenic conditions. Here, we present the Spatially-distributed Tracer-Aided Rainfall-Runoff model with a coupled biogeochemi- cal reactive tracer module (STARR-DOC) to simulate dissolved organic carbon (DOC) dynamics and sources. The STARR-DOC model was developed and tested for a humid high Andean ecosystem (páramo) using high-resolution hourly DOC and hydrometeo- rological data to simulate hourly discharge and DOC at a fine spatial (10 10 m) resolution. Overall, the model was able to acceptably reproduce discharge (KGE 0.45) and stream DOC (KGE 0.69) dynamics. Spatially distributed DOC simulations were independently compared using point DOC measurements for different soil types across the catchment, which allowed for identifying DOC production hot spots and hot moments. Results showed higher hydrological connectivity between slopes and valleys with increasing precipitation. Wetter conditions also favoured DOC production (wet month = 82 mg L 1, dry month = 5 mg L 1) and transport to the stream network (DOC concentrations: during events 15 mg L 1 , during baseflows 4 mg L 1 ). Our results also suggest that minor changes in meteorological conditions directly affect páramo soil water dynamics and biogeochemistry. Knowledge of when and where DOC production in mountain catchments is greatest is important for water managers to understand when they make decisions about water security, especially considering climate change predictions for the Andean region