Figure - uploaded by Cole Haden Smith
Content may be subject to copyright.
Source publication
The purpose of this document is to provide verification of critical RMC-BestFit computations. Software verification involves comparison of the numerical solution generated by the code with one or more analytical solutions, or with other numerical solutions. Verification ensures that the software accurately solves the equations that constitute the m...
Citations
... Three hydrological years, i.e., wet year (WY), normal year (NY), and dry year (DY), corresponding to precipitation frequencies of 25%, 50% and 75%, respectively, were determined with annual precipitation data from Linhe National Meteorological Station of 63 years (from 1957 to 2019). The precipitation frequency was analyzed by using the Pearson type III distribution curve (Bobée and Ashkar, 1991;Smith, 2020). Then, the years 1994, 1981, and 1999 were selected as the typical years of WY, NY, and DY, respectively (Table 4). ...
Unreasonable irrigation water saving and salinity control practices (IWS-SCPs) have resulted in a shallow groundwater table, severe soil salinization and low water use efficiency in the upper Yellow River basin (YRB), Northwest China. In our study, a framework was developed by coupling the agro-hydrological model, i.e., AHC (Agro-Hydrological & chemical and Crop systems simulator) with a decision-making method, i.e., VIKOR (VlseKriterijuska Optimizacija I Komoromisno Resenje), and then a comprehensive evaluation index was calculated to assess the IWS-SCPs for maize and sunflower in the upper YRB. The AHC model was calibrated and validated with two years of field measured data, and then it was used to perform the simulations of agro-hydrological processes corresponding to the designed scenarios considering the irrigation depth and groundwater table depth (GWD) under the conditions of different hydrological years and degrees of soil salinization. The simulated crop yield, soil salinity variation, and crop water productivity were used as the evaluation indicators to search for appropriate IWS-SCPs of the target crops. The results showed that the recommended IWS-SCPs for maize were those with GWDs between 2.1 − 2.3 m and irrigation depths approximately 10% lower for non-saline soils in wet years and 10% higher than the present irrigation for slightly and moderately saline soils in normal and dry years. Whereas, the IWS-SCPs with GWD between 1.5 − 2.2 m and an irrigation depth of approximately 10 − 30% lower than the present situation could be recommended for sunflower in wet years and normal years regardless of saline soils and in dry years of non-saline soils. The developed framework and the obtained results are expected to provide a decision tool and implications for improving irrigation efficiency and salinity control in the arid upper YRB as well as other areas with similar climate conditions and shallow groundwater.
... Future efforts may endeavor to develop reliability quantification tools that are readily accessible to a large user base and incorporate the methods presented in this analysis. For example, numerous packages have emerged for conducting nonstationary flood frequency analysis that provides the capability of quantifying confidence intervals in magnitude-frequency estimates (e.g., Guilleland & Katz, 2011;Smith, 2020). Similar applications for quantifying reliability might provide decision-makers a valuable tool for floodplain management. ...
Recent catastrophic flood events, increasing flood losses, and climate change challenge current reliability estimates defined by the probability that flood levels will not exceed protection measures over a planning horizon. These estimates depict an expected reliability that mask uncertainty in streamflow and the capacity of river channels and floodplains. We described reliability as a random variable whose distribution depends on uncertainty and nonstationarity in annual maximum flood (AMF) distributions and flow capacity uncertainty. Numerical experiments quantified the impacts of nonstationarity and variance in AMFs and flow capacity uncertainty on estimates of flood protection reliability, thereby providing the first examination of their interacting effects. The distribution of reliability along a regulatory floodplain boundary was quantified through a bootstrap scheme that accounts for nonstationarity and uncertainty in AMFs and flow capacity uncertainty. Results indicated that accounting for uncertainty in flow capacity substantially reduces reliability compared to estimates based solely on flood likelihood; the divergence is greater in the presence of nonstationary AMFs. The distribution of reliability along the regulatory floodplain boundary was spatially heterogeneous due to within‐reach variation in flow capacity uncertainty. Quantifying the distribution of reliability for flood protection measures enables transparent communication and selection of a desired confidence level that is commensurate with a contextually appropriate risk tolerance. Similarly, we show that a desired level of confidence in reliability can be specified to estimate a design flood protection level. These results reveal how the combined impacts of uncertainty and nonstationarity can impact reliability estimates and confidence in those estimates.
