PMID- 36939939
OWN - NLM
STAT- MEDLINE
DCOM- 20230322
LR  - 20230322
IS  - 1573-2959 (Electronic)
IS  - 0167-6369 (Linking)
VI  - 195
IP  - 4
DP  - 2023 Mar 20
TI  - GIS-based slope-adjusted curve number methods for runoff estimation.
PG  - 489
LID - 10.1007/s10661-023-11039-6 [doi]
AB  - Accurate estimation of surface runoff and determination of susceptible lands to 
      runoff generation in ungauged watersheds were the problems for hydrologic 
      engineering which could be predicted through a simple model such as Soil 
      Conservation Service Curve Number (SCS-CN). Due to the slope effects on this 
      method, slope adjustment for curve number was developed to improve its precision. 
      So, the main objectives of this study were to apply GIS-based slope SCS-CN 
      approaches for surface runoff estimation and compare the accuracy of three 
      slope-adjusted models including: (a) model with three empirical parameters, (b) 
      model with two parameters slope function, and (c) model with one parameter in the 
      region located in the central part of Iran. For this purpose, soil texture, 
      hydrologic soil group, land use, slope, and daily rainfall volume maps were 
      utilized. In order to provide the curve number map of the study area, land use 
      and hydrologic soil group layers built in Arc-GIS were intersected and the curve 
      number was determined. Then, three slope adjustment equations were used to modify 
      curve numbers of AMC-II by employing slope map. Finally, recorded runoff data of 
      the hydrometric station were applied to assess the performance of the models 
      through four statistical indicators of the root mean square error (RMSE), the 
      Nash-Sutcliffe efficiency (E), the coefficient of determination [Formula: see 
      text], and percent bias (PB). Land use map analysis showed that rangeland was the 
      dominant land use, whereas the soil texture map specified the greatest and 
      smallest area belonging to loam and sandy loam textures, respectively. Although 
      the runoff results showed the overestimation of large rainfall values and 
      underestimation for rainfall with less than 40 mm volume in both models, the 
      values of E (0.78), RMSE (2), PB (16), and [Formula: see text] (0.88) revealed 
      that eq. (a) with three empirical parameters was the most accurate equation. The 
      maximum percent of runoff generated by rainfall for eqs. (a), (b), and (c) were 
      68.43, 67.28, and 51.57% which showed that bareland located in south part with 
      the slope of more than 5% was susceptible to runoff generation and should be paid 
      attention to watershed management.
CI  - (c) 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.
FAU - Forootan, Elham
AU  - Forootan E
AD  - Department of Agriculture, Payame Noor University, Tehran, Iran. 
      e.forotan@pnu.ac.ir.
LA  - eng
PT  - Journal Article
DEP - 20230320
PL  - Netherlands
TA  - Environ Monit Assess
JT  - Environmental monitoring and assessment
JID - 8508350
RN  - 0 (Soil)
SB  - IM
MH  - *Water Movements
MH  - *Geographic Information Systems
MH  - Environmental Monitoring/methods
MH  - Soil
MH  - Hydrology
MH  - Rain
OTO - NOTNLM
OT  - GIS
OT  - Model accuracy
OT  - Runoff
OT  - Slope-adjusted curve number
EDAT- 2023/03/21 06:00
MHDA- 2023/03/23 06:00
CRDT- 2023/03/20 12:18
PHST- 2022/08/01 00:00 [received]
PHST- 2023/02/20 00:00 [accepted]
PHST- 2023/03/20 12:18 [entrez]
PHST- 2023/03/21 06:00 [pubmed]
PHST- 2023/03/23 06:00 [medline]
AID - 10.1007/s10661-023-11039-6 [pii]
AID - 10.1007/s10661-023-11039-6 [doi]
PST - epublish
SO  - Environ Monit Assess. 2023 Mar 20;195(4):489. doi: 10.1007/s10661-023-11039-6.