This study estimated the water balance of Lake Titicaca using an integrated modeling framework that considers natural hydrological processes and net irrigation consumption. The proposed approach was implemented at a daily scale for a period of 35 years. This framework is able to simulate lake water levels with good accuracy over a wide range of hydroclimatic conditions. The findings demonstrate that a simple representation of hydrological processes is suitable for use in poorly-gauged regions.

Reference evapotranspiration (ET0) is an essential parameter for hydrological modeling, irrigation planning and for studying the impacts of climate change on water resources. This work evaluate 20 alternative methods of estimating ET0 in order to adapt them to the climatic context of the 3 mains basins of Senegal where very little climate data is available. The methods of Valiantzas 1, Doorenboss & Pruitt and Penman are the most robust for the estimation of ET0 in this context.

The analyze of the trends of ET0 at the scale of the Senegal, Gambia and Casamance river basins using reanalyze data of NASA/POWER over 1984–2019 shows that ET0 increases significantly in 32% of the Senegal basin and decreases in less than 1% of it. In the Casamance and Gambia basins, the annual ET0 drops by 65% and 18%, respectively. Temperature and relative humidity show an increasing trend over all basins while wind speed and radiation decrease, confirming the so-called "evaporation paradox".

This dataset provides a set of hydrometric indices for about 1500 stations across Africa with daily discharge data. These indices represent mean flow characteristics and extremes (low flows and floods), allowing us to study the long-term evolution of hydrology in Africa and support the modeling efforts that aim at reducing the vulnerability of African countries to hydro-climatic variability.

Interpolation methods accounting for elevation dependency from scattered gauges result in inaccurate inputs for snow-hydrological models. Altitudinal gradients of temperature and precipitation can be successfully inferred using an inverse snow-hydrological modelling approach. This approach can significantly improve the simulation of snow cover and streamflow dynamics through more parsimonious parametrization.