Abstract
We investigated the scaling and topology of engineered urban drainage networks (UDNs) in two cities, and further examined UDN evolution over decades. UDN scaling was analyzed using two power law scaling characteristics widely employed for river networks: (1) Hack's law of length (L)-area (A) [ L∝Ah] and (2) exceedance probability distribution of upstream contributing area (δ) [ P(A≥δ)∼aδ-e(open)]. For the smallest UDNs (<2 km2), length-area scales linearly (h ∼ 1), but power law scaling (h ∼ 0.6) emerges as the UDNs grow. While P(A≥δ) plots for river networks are abruptly truncated, those for UDNs display exponential tempering [ P(A≥δ)=aδ-e(open)exp(-cδ)]. The tempering parameter c decreases as the UDNs grow, implying that the distribution evolves in time to resemble those for river networks. However, the power law exponent e(open) for large UDNs tends to be greater than the range reported for river networks. Differences in generative processes and engineering design constraints contribute to observed differences in the evolution of UDNs and river networks, including subnet heterogeneity and nonrandom branching.
| Original language | English |
|---|---|
| Journal | Water Resources Research |
| DOIs | |
| Publication status | Accepted/In press - 2017 |
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Keywords
- Fractal
- Infrastructure
- River network
- Self-organization
- Self-similarity
- Urban drainage network
ASJC Scopus subject areas
- Water Science and Technology
Cite this
Functional Topology of Evolving Urban Drainage Networks. / Yang, Soohyun; Paik, Kyungrock; Mcgrath, Gavan S.; Urich, Christian; Krueger, Elisabeth; Kumar, Praveen; Rao, P. Suresh C.
In: Water Resources Research, 2017.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Functional Topology of Evolving Urban Drainage Networks
AU - Yang, Soohyun
AU - Paik, Kyungrock
AU - Mcgrath, Gavan S.
AU - Urich, Christian
AU - Krueger, Elisabeth
AU - Kumar, Praveen
AU - Rao, P. Suresh C.
PY - 2017
Y1 - 2017
N2 - We investigated the scaling and topology of engineered urban drainage networks (UDNs) in two cities, and further examined UDN evolution over decades. UDN scaling was analyzed using two power law scaling characteristics widely employed for river networks: (1) Hack's law of length (L)-area (A) [ L∝Ah] and (2) exceedance probability distribution of upstream contributing area (δ) [ P(A≥δ)∼aδ-e(open)]. For the smallest UDNs (<2 km2), length-area scales linearly (h ∼ 1), but power law scaling (h ∼ 0.6) emerges as the UDNs grow. While P(A≥δ) plots for river networks are abruptly truncated, those for UDNs display exponential tempering [ P(A≥δ)=aδ-e(open)exp(-cδ)]. The tempering parameter c decreases as the UDNs grow, implying that the distribution evolves in time to resemble those for river networks. However, the power law exponent e(open) for large UDNs tends to be greater than the range reported for river networks. Differences in generative processes and engineering design constraints contribute to observed differences in the evolution of UDNs and river networks, including subnet heterogeneity and nonrandom branching.
AB - We investigated the scaling and topology of engineered urban drainage networks (UDNs) in two cities, and further examined UDN evolution over decades. UDN scaling was analyzed using two power law scaling characteristics widely employed for river networks: (1) Hack's law of length (L)-area (A) [ L∝Ah] and (2) exceedance probability distribution of upstream contributing area (δ) [ P(A≥δ)∼aδ-e(open)]. For the smallest UDNs (<2 km2), length-area scales linearly (h ∼ 1), but power law scaling (h ∼ 0.6) emerges as the UDNs grow. While P(A≥δ) plots for river networks are abruptly truncated, those for UDNs display exponential tempering [ P(A≥δ)=aδ-e(open)exp(-cδ)]. The tempering parameter c decreases as the UDNs grow, implying that the distribution evolves in time to resemble those for river networks. However, the power law exponent e(open) for large UDNs tends to be greater than the range reported for river networks. Differences in generative processes and engineering design constraints contribute to observed differences in the evolution of UDNs and river networks, including subnet heterogeneity and nonrandom branching.
KW - Fractal
KW - Infrastructure
KW - River network
KW - Self-organization
KW - Self-similarity
KW - Urban drainage network
UR - http://www.scopus.com/inward/record.url?scp=85033599648&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85033599648&partnerID=8YFLogxK
U2 - 10.1002/2017WR021555
DO - 10.1002/2017WR021555
M3 - Article
AN - SCOPUS:85033599648
JO - Water Resources Research
JF - Water Resources Research
SN - 0043-1397
ER -