Generalized Storage-Reliability-Yield Equations for Rainwater Harvesting Systems

Abstract

Although rainwater harvesting (RWH) is gaining popularity as a sustainable water supply source in urban as well as rural areas, estimating required storage remains an important design challenge. This paper develops a robust, yet computationally simple equation for calculating required storage capacity for a RWH system, which is generally applicable in the United States (U.S.). A simulation model with a daily time step and a yield-after-spill algorithm is used to generate empirical Storage-Reliability-Yield (SRY) relationships for RWH systems at 232 U.S., first-order precipitation gaging stations with long daily precipitation records. A regional regression modeling approach is used to combine system parameters (daily yield, collection area, reliability) with climatic variables (e.g. standard deviation of daily rainfall) to predict required storage capacity. Nationwide regression models for fixed reliability cases (80, 90, 95, 98%) demonstrate good fits (R 2 > 0.95) between model predictions and simulated storage capacities. The fits improve (R 2 >0.97) when the nation is broken down into smaller, more climatically homogeneous regions.

Performance of a RBSN under the RCP Scenarios: A Case Study in South Korea

“…We used reliability, resiliency, and vulnerability as the performance criteria of a RBSN in this study. These performance criteria are commonly adopted for a water resources system, such as a reservoir system [11]. Reliability can be defined as the ratio of success states as follows:…”

“…If storage goes below zero, the state changes to a failure. The SRY curve method was used to calculate the required storage size for a given target reliability [11]:…”

“…The concept of rainwater harvesting is close to that of stormwater basins or reservoir systems except for on-site use. Therefore, similar approaches have been applied to determine the optimal-sizing of a rainwater storage system, such as an analytical equation for storm-water detention [10], a general storage-reliability-yield (SRY) relationship [11], and a method with different results depending on the scenario [12], or a dimensionless method [12]. On the other hand, the regional performance of RWHS has drawn great attention as it is necessary to comprehend how regional characteristics, such as social and natural components, affect the performance of a RWHS [13][14][15][16][17].…”

Performance of a Rain Barrel Sharing Network under Climate Change

“…Seo et al [31] also mentioned that the reliability is not sufficient to analyze the performance of the rain barrel sharing network (RBSN). Typically, a RBSN is considered a reservoir [17] and similar approaches of reliability have been adapted for performance analysis [32,33]. In contrast, there are no reports on the analysis of RBSN under climate change with further performance criteria except for the reliability.…”

“…The concept of RWHS is similar to that of stormwater basins or reservoir systems, and various methodologies have been applied to estimate the size of the rainwater storage. An analytical equation for storm-water detention [16], a common storage-reliability-yield (SRY) relationship concept [17], or a dimensionless methodology [18] were also used to determine the optimal size of a rainwater storage. On the other hand, a regional assessment of the performance of a RWHS has been conducted continuously to understand how societal and climatic factors interact to affect the behavior of a RWHS [19][20][21][22].…”