scholarly journals Subsurface hydrology of tile‐drained headwater catchments: Compatibility of concepts and hydrochemistry

2021 ◽  
Author(s):  
Dale R. Van Stempvoort ◽  
D. Ross MacKay ◽  
Geoff Koehler ◽  
Pamela Collins ◽  
Susan J. Brown
Keyword(s):  
Subsurface Hydrology ◽  
Headwater Catchments

Assessment of the subsurface hydrology of the UIC-NARL main camp, near Barrow, Alaska, 1993-94

1995 ◽  
Author(s):  
K.A. McCarthy ◽  
G.L. Solin
Keyword(s):  
Subsurface Hydrology

EVALUATING THE NATURAL TRANSPORT PATHWAYS OF IODINE IN HEADWATER CATCHMENTS

2017 ◽  
Author(s):  
Kristina M. Gutchess ◽  
◽  
Shannon Garvin ◽  
Li Jin ◽  
Wanyi Lu ◽  
...  
Keyword(s):  
Transport Pathways ◽  
Headwater Catchments

scholarly journals Particulate and Dissolved Organic Matter in Stormwater Runoff Influences Oxygen Demand in Urbanized Headwater Catchments

2021 ◽  
Author(s):  
Kelly M. McCabe ◽  
Erik M. Smith ◽  
Susan Q. Lang ◽  
Christopher L. Osburn ◽  
Claudia R. Benitez-Nelson
Keyword(s):  
Organic Matter ◽  
Dissolved Organic Matter ◽  
Stormwater Runoff ◽  
Oxygen Demand ◽  
Headwater Catchments

scholarly journals Development of random forest model as decision support tool in water resources management of Ogun headwater catchments

2021 ◽  
Vol 11 (7) ◽  
Author(s):  
O. O. Aiyelokun ◽  
O. A. Agbede
Keyword(s):  
Random Forest ◽  
Water Resources ◽  
Potential Evapotranspiration ◽  
Decision Support Tool ◽  
Maximum Temperature ◽  
Computational Technique ◽  
Percentage Increase ◽  
Support Tool ◽  
Headwater Catchments ◽  
Minimal Depth

AbstractWater resources cannot be effectively managed unless potential evapotranspiration is determined with high accuracy at headwater catchments. The study presents the most suitable feature combinations for building a reliable potential evapotranspiration (PET) model in the headwater catchments of Ogun River Basin, Southwest Nigeria. Using rainfall (R), wind speed (U2), sunshine hour (S), relative humidity (Rh), minimum temperature (Tmin) and maximum temperature (Tmax) as input features, a Random Forest (RF) model was developed to predict PET. Although the model yielded satisfactory results, it was subjected to the minimal depth and percentage increase in mean square error (%IncMSE). This was done to reduce the input features and to increase model accuracy. Thereafter various combinations of important input features were examined in order to establish the best combinations required to yield optimum results. The study revealed that although Tmax (%IncMSE of 652.09, p value < 0.05) and Rh (%IncMSE of 254.36, p value < 0.05) were the most important predictors of PET, a more reliable RF model was achieved when S and U2 were combined with them. Consequently, this study presents RF with a combination of four parameters (Tmax, Rh, S and U2) as an excellent computational technique for the prediction of PET in headwater catchments.

scholarly journals Production of clean water in agriculture headwater catchments: A model based on the payment for environmental services

2021 ◽  
Vol 785 ◽  
pp. 147331
Author(s):  
Teresa Cristina Tarlé Pissarra ◽  
Luís Filipe Sanches Fernandes ◽  
Fernando António Leal Pacheco
Keyword(s):  
Environmental Services ◽  
Clean Water ◽  
Headwater Catchments ◽  
Payment For Environmental Services ◽  
Model Based

Predicting critical source areas of sediment in headwater catchments

2013 ◽  
Vol 179 ◽  
pp. 41-52 ◽  
Author(s):  
Joshua Thompson ◽  
Rachel Cassidy ◽  
Donnacha G. Doody ◽  
Ray Flynn
Keyword(s):  
Critical Source Areas ◽  
Headwater Catchments ◽  
Source Areas

Potentials and constraints of different types of soil moisture observations for flood simulations in headwater catchments

2011 ◽  
Vol 60 (3) ◽  
pp. 879-914 ◽  
Author(s):  
Axel Bronstert ◽  
Benjamin Creutzfeldt ◽  
Thomas Graeff ◽  
Irena Hajnsek ◽  
Maik Heistermann ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Headwater Catchments ◽  
Different Types ◽  
Flood Simulations

scholarly journals Unravelling the role of vegetation on the different trends between climatic and hydrologic drought in headwater catchments of Spain

Anthropocene ◽  
2021 ◽  
Vol 36 ◽  
pp. 100309
Author(s):  
D. Peña-Angulo ◽  
S.M. Vicente-Serrano ◽  
F. Domínguez-Castro ◽  
I. Noguera ◽  
M. Tomas-Burguera ◽  
...  
Keyword(s):  
Headwater Catchments ◽  
Hydrologic Drought
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