A Single Law to Describe Atmospheric Nitrogen Bulk Deposition versus Rainfall Amount: Inputs at the Seine River Watershed Scale

2004 ◽  
Vol 155 (1-4) ◽  
pp. 339-354 ◽  
Author(s):  
B. Garban ◽  
A. Motelay-Massei ◽  
H. Blanchoud ◽  
D. Ollivon
Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2392
Author(s):  
Liang ◽  
Jiao ◽  
Dang ◽  
Cao

Obtaining practical thresholds for erosive rainfall plays a crucial role in calculating rainfall erosivity and predicting water erosion. Nevertheless, the study of thresholds on subwatershed and watershed scales remains scarce. Given this, we presented the critical rainfall that generated the outflows of subwatersheds and watersheds as the threshold of sediment-generating rainfall. On the basis of the observation of twelve nested topographical units at the Peijiamaogou watershed in the Loess Plateau of China, we fitted regression relationships between rainfall indexes (rainfall amount, maximum 30-min intensity, maximum 60-min intensity, rainfall amount multiply maximum 30-min intensity, and rainfall amount multiply maximum 60-min intensity) and the proportion of cumulative sediment yield to the total sediment yield. We determined the thresholds of sediment-generating rainfall and explored the variabilities of thresholds across different spatial scales. Moreover, the covering area proportion (CAP) with rainfall indexes higher than the thresholds was also employed as thresholds at the subwatershed and watershed scales. The thresholds of CAP for P and I30 were 50.5% and 47.6% at the subwatershed scale, while 31.0% and 30.3% at the watershed scale. The thresholds of P and I30 at the subwatershed scale were higher than those of hillslope scale, while the threshold of I30 at the watershed scale was smaller compared to the other scales. In general, I30 was viewed as the best threshold among single rainfall indexes across different spatial scales, while P was not recommended as a practical threshold. This study can improve the prediction accuracy of water erosion across different spatial scales and develop the spatial scale effect of sediment yield in the loess hilly areas.


Chemosphere ◽  
2020 ◽  
Vol 239 ◽  
pp. 124773 ◽  
Author(s):  
Kai Yu ◽  
Yanhua Duan ◽  
Peng Liao ◽  
Lin Xie ◽  
Qianqian Li ◽  
...  

2009 ◽  
Vol 43 (26) ◽  
pp. 4087-4094 ◽  
Author(s):  
Juan M. González Benítez ◽  
J. Neil Cape ◽  
Mathew R. Heal ◽  
Netty van Dijk ◽  
Alberto Vidal Díez

2012 ◽  
Vol 344 (8) ◽  
pp. 396-405 ◽  
Author(s):  
Nicolas Fritier ◽  
Nicolas Massei ◽  
Benoit Laignel ◽  
Alain Durand ◽  
Bastien Dieppois ◽  
...  

2001 ◽  
Vol 3 (6) ◽  
pp. 671-680 ◽  
Author(s):  
Farhad Nadim ◽  
Michael M. Trahiotis ◽  
Snieguole Stapcinskaite ◽  
Christopher Perkins ◽  
Robert J. Carley ◽  
...  

2013 ◽  
Vol 42 (1) ◽  
pp. 251-274 ◽  
Author(s):  
Tingting Liu ◽  
Nathaniel H. Merrill ◽  
Arthur J. Gold ◽  
Dorothy Q. Kellogg ◽  
Emi Uchida

This study spatially quantifies hydrological ecosystem services and the production of ecosystem services at the watershed scale. We also investigate the effects of stressors such as land use change, climate change, and choices in land management practices on production of ecosystem services and their values. We demonstrate the approach in the Beaver River watershed in Rhode Island. Our key finding is that choices in land use and land management practices create tradeoffs across multiple ecosystem services and the extent of these tradeoffs depends considerably on the scenarios and ecosystem services being compared.


Fact Sheet ◽  
2012 ◽  
Author(s):  
David M. Bjerklie ◽  
Lauren E. Hay ◽  
Steven L. Markstrom

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247907
Author(s):  
Taylor Maavara ◽  
Erica R. Siirila-Woodburn ◽  
Fadji Maina ◽  
Reed M. Maxwell ◽  
James E. Sample ◽  
...  

There is a growing understanding of the role that bedrock weathering can play as a source of nitrogen (N) to soils, groundwater and river systems. The significance is particularly apparent in mountainous environments where weathering fluxes can be large. However, our understanding of the relative contributions of rock-derived, or geogenic, N to the total N supply of mountainous watersheds remains poorly understood. In this study, we develop the High-Altitude Nitrogen Suite of Models (HAN-SoMo), a watershed-scale ensemble of process-based models to quantify the relative sources, transformations, and sinks of geogenic and atmospheric N through a mountain watershed. Our study is based in the East River Watershed (ERW) in the Upper Colorado River Basin. The East River is a near-pristine headwater watershed underlain primarily by an N-rich Mancos Shale bedrock, enabling the timing and magnitude of geogenic and atmospheric contributions to watershed scale dissolved N-exports to be quantified. Several calibration scenarios were developed to explore equifinality using >1600 N concentration measurements from streams, groundwater, and vadose zone samples collected over the course of four years across the watershed. When accounting for recycling of N through plant litter turnover, rock weathering accounts for approximately 12% of the annual dissolved N sources to the watershed in the most probable calibration scenario (0–31% in other scenarios), and 21% (0–44% in other scenarios) when considering only “new” N sources (i.e. geogenic and atmospheric). On an annual scale, instream dissolved N elimination, plant turnover (including cattle grazing) and atmospheric deposition are the most important controls on N cycling.


FLORESTA ◽  
2019 ◽  
Vol 49 (2) ◽  
pp. 171
Author(s):  
Natalia Gomes de Souza Mendes ◽  
Roberto Avelino Cecílio ◽  
Sidney Sara Zanetti ◽  
Cleber Assis dos Santos

ThThe present paper analyzed the relationship between streamflow and rainfall at the stream of Itapemirim River Watershed (BHRI). The minimum streamflow with duration of seven days (Q7), the average annual streamflow (Qmed) and the annual maximum streamflow (Qmax) of 11 BHRI’s sub-basins were determined. Trends in rainfall and streamflow series were analyzed with Mann-Kandall and Pettitt nonparametric tests. Regression analysis between rainfall and streamflow were established. Results showed no trends on rainfall and Q7 series. Trends in Qmed were found only at one sub-basin and trends in Qmax were found in two sub-basins. The total rainfall was correlated with the streamflow of all the sub-basins. It has been found that annual rainfall amount (Pa) explained considerably variations in Qmed and Q7. Rainfall amounts of the rainiest month (Pmax) showed good correlation to Qmax.


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