scholarly journals Smooth regional estimation of low-flow indices: physiographical space based interpolation and top-kriging

2011 ◽  
Vol 15 (3) ◽  
pp. 715-727 ◽  
Author(s):  
S. Castiglioni ◽  
A. Castellarin ◽  
A. Montanari ◽  
J. O. Skøien ◽  
G. Laaha ◽  
...  
Keyword(s):  
Spatial Interpolation ◽  
Central Italy ◽  
Low Flow ◽  
Flow Index ◽  
Ungauged Basins ◽  
Low Flows ◽  
Interpolation Techniques ◽  
Point Data ◽  
Leave One Out ◽  
Low Flow Index

Abstract. Recent studies highlight that spatial interpolation techniques of point data can be effectively applied to the problem of regionalization of hydrometric information. This study compares two innovative interpolation techniques for the prediction of low-flows in ungauged basins. The first one, named Physiographical-Space Based Interpolation (PSBI), performs the spatial interpolation of the desired streamflow index (e.g., annual streamflow, low-flow index, flood quantile, etc.) in the space of catchment descriptors. The second technique, named Topological kriging or Top-kriging, predicts the variable of interest along river networks taking both the area and nested nature of catchments into account. PSBI and Top-kriging are applied for the regionalization of Q355 (i.e., a low-flow index that indicates the streamflow that is equalled or exceeded 355 days in a year, on average) over a broad geographical region in central Italy, which contains 51 gauged catchments. The two techniques are cross-validated through a leave-one-out procedure at all available gauges and applied to a subregion to produce a continuous estimation of Q355 along the river network extracted from a 90m elevation model. The results of the study show that Top-kriging and PSBI present complementary features. Top-kriging outperforms PSBI at larger river branches while PSBI outperforms Top-kriging for headwater catchments. Overall, they have comparable performances (Nash-Sutcliffe efficiencies in cross-validation of 0.89 and 0.83, respectively). Both techniques provide plausible and accurate predictions of Q355 in ungauged basins and represent promising opportunities for regionalization of low-flows.

scholarly journals Geostatistical regionalization of low-flow indices: PSBI and Top-Kriging

2010 ◽  
Vol 7 (5) ◽  
pp. 7231-7261 ◽  
Author(s):  
S. Castiglioni ◽  
A. Castellarin ◽  
A. Montanari ◽  
J. O. Skøien ◽  
G. Laaha ◽  
...  
Keyword(s):  
Spatial Interpolation ◽  
Central Italy ◽  
Low Flow ◽  
Flow Index ◽  
Ungauged Basins ◽  
Low Flows ◽  
Index Flood ◽  
Point Data ◽  
Leave One Out ◽  
Continuous Estimation

Abstract. Recent studies highlight that geostatistical interpolation, which has been originally developed for the spatial interpolation of point data, can be effectively applied to the problem of regionalization of hydrometric information. This study compares two innovative geostatistical approaches for the prediction of low-flows in ungauged basins. The first one, named Physiographic-Space Based Interpolation (PSBI), performs the spatial interpolation of the desired streamflow index (e.g., annual streamflow, low-flow index, flood quantile, etc.) in the space of catchment descriptors. The second technique, named Topological kriging or Top-Kriging, predicts the variable of interest along river networks taking both the area and nested nature of catchments into account. PSBI and Top-Kriging are applied for the regionalization of Q355 (i.e., the streamflow that is equalled or exceeded 355 days in a year, on average) over a broad geographical region in central Italy, which contains 51 gauged catchments. Both techniques are cross-validated through a leave-one-out procedure at all available gauges and applied to a subregion to produce a continuous estimation of Q355 along the river network extracted from a 90 m DEM. The results of the study show that Top-Kriging and PSBI present complementary features and have comparable performances (Nash-Sutcliffe efficiencies in cross-validation of 0.89 and 0.83, respectively). Both techniques provide plausible and accurate predictions of Q355 in ungauged basins and represent promising opportunities for regionalization of low-flows.

scholarly journals Hydrological characterization of watersheds in the Blue Nile Basin, Ethiopia

2011 ◽  
Vol 15 (1) ◽  
pp. 11-20 ◽  
Author(s):  
S. G. Gebrehiwot ◽  
U. Ilstedt ◽  
A. I. Gärdenas ◽  
K. Bishop
Keyword(s):  
Land Use ◽  
Soil Type ◽  
Low Flow ◽  
Flow Index ◽  
Nile Basin ◽  
Grazing Land ◽  
Blue Nile ◽  
Low Flows ◽  
Blue Nile Basin ◽  
Low Flow Index

Abstract. Thirty-two watersheds (31–4350 km2), in the Blue Nile Basin, Ethiopia, were hydrologically characterized with data from a study of water and land resources by the US Department of Interior, Bureau of Reclamation (USBR) published in 1964. The USBR document contains data on flow, topography, geology, soil type, and land use for the period 1959 to 1963. The aim of the study was to identify watershed variables best explaining the variation in the hydrological regime, with a special focus on low flows. Moreover, this study aimed to identify variables that may be susceptible to management policies for developing and securing water resources in dry periods. Principal Component Analysis (PCA) and Partial Least Square (PLS) were used to analyze the relationship between five hydrologic response variables (total flow, high flow, low flow, runoff coefficient, low flow index) and 30 potential explanatory watershed variables. The explanatory watershed variables were classified into three groups: land use, climate and topography as well as geology and soil type. Each of the three groups had almost equal influence on the variation in hydrologic variables (R2 values ranging from 0.3 to 0.4). Specific variables from within each of the three groups of explanatory variables were better in explaining the variation. Low flow and low flow index were positively correlated to land use types woodland, dense wet forest and savannah grassland, whereas grazing land and bush land were negatively correlated. We concluded that extra care for preserving low flow should be taken on tuffs/basalts which comprise 52% of the Blue Nile Basin. Land use management plans should recognize that woodland, dense wet forest and savannah grassland can promote higher low flows, while grazing land diminishes low flows.

Non-Newtonian oscillatory boundary layer, a numerical approach

1986 ◽  
Vol 51 (6) ◽  
pp. 1240-1258 ◽  
Author(s):  
Ondřej Wein ◽  
Václav Sobolík
Keyword(s):  
Numerical Approach ◽  
Stress Fields ◽  
Low Flow ◽  
Flow Index ◽  
Differential Formulation ◽  
Oscillatory Boundary Layer ◽  
Flow Enhancement ◽  
Pseudoplastic Liquid ◽  
Oscillating Plate ◽  
Low Flow Index

Differential schemes have been constructed by using the integro-differential formulation of the equation of motion in stresses. The problem of periodic flow of the purely-viscous non-Newtonian liquid on a harmonically oscillating plate has been solved numerically for extremally high values of the Reynolds number. The velocity and stress fields as well as estimates of the flow enhancement E are given for the quasi-oscillatory regime, Fr → ∞, for the pseudoplastic liquid with the extremally low flow index, n = 0.15.

scholarly journals Which objective function to calibrate rainfall–runoff models for low-flow index simulations?

2017 ◽  
Vol 62 (7) ◽  
pp. 1149-1166 ◽  
Author(s):  
Florine Garcia ◽  
Nathalie Folton ◽  
Ludovic Oudin
Keyword(s):  
Objective Function ◽  
Low Flow ◽  
Flow Index ◽  
Rainfall Runoff ◽  
Low Flow Index

A Principal Component Regression Method for Estimating Low Flow Index

2010 ◽  
Vol 24 (11) ◽  
pp. 2553-2566 ◽  
Author(s):  
Saeid Eslamian ◽  
Mehdi Ghasemizadeh ◽  
Monireh Biabanaki ◽  
Mansoor Talebizadeh
Keyword(s):  
Principal Component Regression ◽  
Principal Component ◽  
Regression Method ◽  
Low Flow ◽  
Flow Index ◽  
Low Flow Index

scholarly journals Estimating Baseflow and Baseflow Index in Ungauged Basins Using Spatial Interpolation Techniques: A Case Study of the Southern River Basin of Thailand

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3113
Author(s):  
Pakorn Ditthakit ◽  
Sarayod Nakrod ◽  
Naunwan Viriyanantavong ◽  
Abebe Debele Tolche ◽  
Quoc Bao Pham
Keyword(s):  
Spatial Interpolation ◽  
Water Resource Management ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Filter Method ◽  
Ungauged Basins ◽  
Calibration And Validation ◽  
Distance Weighting ◽  
Interpolation Techniques

This research aims to estimate baseflow (BF) and baseflow index (BFI) in ungauged basins in the southern part of Thailand. Three spatial interpolation methods (namely, inverse distance weighting (IDW), kriging, and spline) were utilized and compared in regard to their performance. Two baseflow separation methods, i.e., the local minimum method (LM) and the Eckhardt filter method (EF), were investigated. Runoff data were collected from 65 runoff stations. These runoff stations were randomly selected and divided into two parts: 75% and 25% for the calibration and validation stages, respectively, with a total of 36 study cases. Four statistical indices including mean absolute error (MAE), root mean squared error (RMSE), correlation coefficient (r), and combined accuracy (CA), were applied for the performance evaluation. The findings revealed that monthly and annual BF and BFI calculated by EF were mostly lower than those calculated by LM. Furthermore, IDW gave the best performance among the three spatial interpolation techniques by providing the highest r-value and the lowest MAE, RMSE, and CA values for both the calibration and validation stages, followed by kriging and spline, respectively. We also provided monthly and annual BF and BFI maps to benefit water resource management.

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