Linking databases of different sources and scales for groundwater research in the Urema River Basin/Central Mozambique

2006 ◽  
pp. 171-184
Author(s):  
Franziska Steinbruch ◽  
Luis Macario
Keyword(s):  
River Basin ◽  
Different Sources

Spatial characteristics of total phosphorus loads from different sources in the Lancang River Basin

2020 ◽  
Vol 722 ◽  
pp. 137863 ◽  
Author(s):  
Bingyao Zhang ◽  
Wei Ding ◽  
Bo Xu ◽  
Longfan Wang ◽  
Yu Li ◽  
...  
Keyword(s):  
River Basin ◽  
Total Phosphorus ◽  
Spatial Characteristics ◽  
Lancang River ◽  
Phosphorus Loads ◽  
The Lancang River Basin ◽  
Different Sources

Simulated nitrogen leaching patterns and adaptation to climate change in two Finnish river basins with contrasting land use and climatic conditions

2009 ◽  
Vol 40 (2-3) ◽  
pp. 177-186 ◽  
Author(s):  
Katri Rankinen ◽  
Pirkko Valpasvuo-Jaatinen ◽  
Anni Karhunen ◽  
Kaarle Kenttämies ◽  
Suvi Nenonen ◽  
...  
Keyword(s):  
Land Use ◽  
River Basin ◽  
Inorganic Nitrogen ◽  
River Basins ◽  
Water Protection ◽  
Inorganic N ◽  
Catchment Scale ◽  
Protection Measures ◽  
N Loading ◽  
Different Sources

Inorganic nitrogen (N) loading was simulated by the catchment scale INCA-N model from two large river basins with contrasting land use. The main aim was to analyze the timing and origin of inorganic N loading and the effectiveness of different water protection methods. Predicted changes in precipitation and temperature increases the nutrient load from catchments to water bodies in future climate. The total inorganic N load from the forested Simojoki river basin located in northern Finland was about 5% of that from the Loimijoki river basin in south western Finland. In the Loimijoki river basin agriculture dominated inorganic N loading. When applying realistic water protection methods (limits on manure spreading) the simulated inorganic N load from the river basin decreased by 11%. With more drastic methods (no manure spreading + catch crop) a decrease up to 34% was achieved. In the Simojoki river basin there were several equally significant sources, so suitable combinations of different water protection measures would be the most efficient way to decrease the inorganic N load. As the inorganic N load may be composed of very different sources, depending on land use in the river basin, efficient allocation of water protection measures requires detailed analysis of different sources of loading.

scholarly journals Searching for the optimal drought index and timescale combination to detect drought: a case study from the lower Jinsha River basin, China

2018 ◽  
Vol 22 (1) ◽  
pp. 889-910 ◽  
Author(s):  
Javier Fluixá-Sanmartín ◽  
Deng Pan ◽  
Luzia Fischer ◽  
Boris Orlowsky ◽  
Javier García-Hernández ◽  
...  
Keyword(s):  
River Basin ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Rainfall Anomaly ◽  
Drought Indices ◽  
Jinsha River ◽  
Basin Scale ◽  
Different Sources ◽  
Good Agreement

Abstract. Drought indices based on precipitation are commonly used to identify and characterize droughts. Due to the general complexity of droughts, the comparison of index-identified events with droughts at different levels of the complete system, including soil humidity or river discharges, relies typically on model simulations of the latter, entailing potentially significant uncertainties. The present study explores the potential of using precipitation-based indices to reproduce observed droughts in the lower part of the Jinsha River basin (JRB), proposing an innovative approach for a catchment-wide drought detection and characterization. Two indicators, namely the Overall Drought Extension (ODE) and the Overall Drought Indicator (ODI), have been defined. These indicators aim at identifying and characterizing drought events on the basin scale, using results from four meteorological drought indices (standardized precipitation index, SPI; rainfall anomaly index, RAI; percent of normal precipitation, PN; deciles, DEC) calculated at different locations of the basin and for different timescales. Collected historical information on drought events is used to contrast results obtained with the indicators. This method has been successfully applied to the lower Jinsha River basin in China, a region prone to frequent and severe droughts. Historical drought events that occurred from 1960 to 2014 have been compiled and cataloged from different sources, in a challenging process. The analysis of the indicators shows a good agreement with the recorded historical drought events on the basin scale. It has been found that the timescale that best reproduces observed events across all the indices is the 6-month timescale.

scholarly journals Impact of the Jamapa River Basin on the Gulf of Mexico

2021 ◽  
Author(s):  
María del Refugio Castañeda-Chávez ◽  
Fabiola Lango-Reynoso
Keyword(s):  
Gulf Of Mexico ◽  
River Basin ◽  
The North ◽  
Metropolitan Cities ◽  
Biological Compounds ◽  
Determining Factors ◽  
Protected Natural Area ◽  
Protected Natural Areas ◽  
Del Rio ◽  
Different Sources

The Jamapa River basin is located in the central region of the State of Veracruz, it is born in the Pico de Orizaba and connects with the Veracruz Reef System in the Gulf of Mexico, both protected natural areas. The lower part of the basin has the contribution of two important effluents, Arroyo Moreno, which is a protected natural area, strongly impacted due to municipal discharges from the metropolitan cities Veracruz-Boca del Río-Medellín. And the Estero, which is part of a complex aquatic system that discharges its waters from the Lagunar Mandinga system to the Gulf of Mexico. Currently, there is a diversity of chemical and biological compounds that the basin receives from different sources of freshwater pollution, such as industrial waste, sewage, agricultural and urban runoff, and the accumulation of sediments. The climatic seasons are the determining factors in the composition of its sediments, due to the force exerted on the bottom of the river by the increase in rainfall, the force of the winds mainly in the north wind season, where the greatest quantity of polluting materials.

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