Assessing water availability in the Oroua River Catchment : a thesis presented in partial fulfillment of the requirements for a Master Degree in Applied Science (Agricultural Engineering), Massey University

The study estimated the 1993-1998 natural flows as well as their corresponding reliabilities along Kiwitea Stream and Oroua River upstream of the old Kawa Wool station. These estimates could present a baseline condition for assessing the hydrologic capability of the catchment for the existing rights and the amount of streamflow still available for additional rights. The study demonstrated that water availability modeling could be a useful tool in water resource management and planning for the Oroua catchment. The "usual" or high river flow allocation management for the Oroua River wherein a right may abstract water up to its permitted rates could be modeled in WRAP. The results of the simulation based on full abstraction of permitted rates suggested that on a monthly basis, there was enough flow physically available to meet all consented abstraction rights including the minimum flow requirement at Almadale and Spur Road stations throughout the 1993- 1998 simulation period. The study had identified an apparent shortcoming of the WRAP model in simulating the MWRC's water allocation schemes at times of low river flow wherein water rights are either restricted or curtailed whenever the flow reached the set monthly flow threshold and the minimum flow level. The WRAP program was lacking of a mechanism or algorithm that will allow a water diversion target to vary depending on a gauged flow at other locations. The study demonstrated that the criteria stipulated in the Oroua Catchment Water Allocation Regional Plan for rostering abstraction at times of low river flow could be accounted in WRAP water availability modeling using a weighted ranked priority scheme. The results of simulation apportioning the combined maximum abstraction rates for irrigation purposes, based on prior use and natural upstream-to-downstream location among irrigation rights, indicated a minimal increase in the utilization of available water of the Oroua River. Thus, with increased water use as a management objective, such options would not be an attractive alternative. To facilitate relevant hydrologic and institutional water availability and reliability assessment of the Oroua River, it is recommended that a modification be made in the WRAP program to include mechanism or algorithms that will allow automatic change of diversion target as a function of gauged flow. Also, a shorter computational interval, such as weekly or daily, would yield more relevant results for real-time water management for the Oroua River. For future simulation or modeling studies for the Oroua River, there is a need to have an actual streamflow measurement or gauging station downstream of the river for validation purposes. There is also a need to have data on actual abstractions and discharges to the Oroua River and its tributaries

Assessing the Risk of 100-year Freshwater Floods in the Lamprey River Watershed of New Hampshire Resulting from Changes in Climate and Land Use

What is the coastal resource issue the project sought to address? Both the magnitude and frequency of freshwater flooding is on the rise in seacoast NH and around much of New England. In the Great Bay watershed, this is the result of two primary causes: 1) increases in impervious surface stemming from a three-to-four fold increase in developed land since 1962; and 2) changing rainfall patterns in part exemplified by a doubling in the frequency of extreme weather events that drop more than 4 inches of precipitation in less than 48 hours (Wake et al., 2011) over the same time period. Moreover, the size of the 100-year precipitation event in this region has increased 26% from 6.3 inches to 8.5 inches from the mid 1950’s to 2010 (NRCC and NRCS, 2012). One consequence is the occurrence of three 100-year floods measured on the Lamprey River at Packers Falls since 1987, and a fourth if the three days of flooding in March of 2010 had occurred instead in two days (Figure 1). Flooding events are expected to continue to increase in magnitude and frequency as land in the watershed is further developed and climate continues to change in response to anthropogenic forcing (e.g., Hayhoe et el., 2007; IPCC, 2007; Karl et al., 2009). Land use management strategies, in particular low impact development (LID) zoning requirements, are one strategy that communities can employ for increased resiliency to flooding with the greatest influence in urban environments

Effective and efficient algorithm for multiobjective optimization of hydrologic models

Practical experience with the calibration of hydrologic models suggests that any single-objective function, no matter how carefully chosen, is often inadequate to properly measure all of the characteristics of the observed data deemed to be important. One strategy to circumvent this problem is to define several optimization criteria (objective functions) that measure different (complementary) aspects of the system behavior and to use multicriteria optimization to identify the set of nondominated, efficient, or Pareto optimal solutions. In this paper, we present an efficient and effective Markov Chain Monte Carlo sampler, entitled the Multiobjective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm, which is capable of solving the multiobjective optimization problem for hydrologic models. MOSCEM is an improvement over the Shuffled Complex Evolution Metropolis (SCEM-UA) global optimization algorithm, using the concept of Pareto dominance (rather than direct single-objective function evaluation) to evolve the initial population of points toward a set of solutions stemming from a stable distribution (Pareto set). The efficacy of the MOSCEM-UA algorithm is compared with the original MOCOM-UA algorithm for three hydrologic modeling case studies of increasing complexity

Impacts of Remotely Sensed Land Use Data on Watershed Hydrologic Change Assessment

Urbanization affects the stream system of a watershed. Increased urbanization alters the land cover and surface characteristics, the stream channel characteristics, and pollutant load of a stream system by increasing the amount of impervious surface. Once rural, forest, or wetland areas are changed to streets, highways, parking lots, sidewalks, and building rooftops. This results in large volumes of runoff being generated for an intense storm over a relatively short time period. As a result, sensitive ecosystems are likely to be damaged by increased urbanization. Projecting the impact of land use changes on a watershed scale often requires the use of remote sensing data to derive the required inputs on land cover and the related amount of impervious surface. Such forecasts are then used to devise alternative land use and stormwater control policies. One critical question that arises then is the impact of land use/land cover (LULC) mapping error on the resulting hydrologic model projections. In this research, we developed a methodology to assess those impacts. The Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model was used to estimate the peak hydrograph for a baseline land use condition and then used to estimate the impact of LULC mapping accuracy levels on those forecasts. The Big Darby Creek Watershed located near Columbus, Ohio, which is experiencing increased urbanization, was selected to map LULC, calibrate a hydrologic model, and assess the hydrologic change due to LULC mapping error. The resulting analysis showed that modest changes in land cover classification did not produce significant impacts on the hydrologic modeling results in rural basins. However, the hydrologic changes are noticeable in urbanizing watersheds. The framework developed in this paper can be used for future modeling efforts to understand the hydrological impact of LULC change in a watershed at a large scale

Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling

Compositional data, such as soil texture, are hard to deal with in the geosciences as standard statistical methods are often inappropriate to analyse this type of data. Especially in sensitivity analysis, the closed character of the data is often ignored. To that end, we developed a method to assess the local sensitivity of a model output with resect to a compositional model input. We adapted the finite difference technique such that the different parts of the input are perturbed simultaneously while the closed character of the data is preserved. This method was applied to a hydrologic model and the sensitivity of the simulated soil moisture content to local changes in soil texture was assessed. Based on a high number of model runs, in which the soil texture was varied across the entire texture triangle, we identified zones of high sensitivity in the texture triangle. In such zones, the model output uncertainty induced by the discrepancy between the scale of measurement and the scale of model application, is advised to be reduced through additional data collection. Furthermore, the sensitivity analysis provided more insight into the hydrologic model behaviour as it revealed how the model sensitivity is related to the shape of the soil moisture retention curve

Toward improved identifiability of hydrologic model parameters: The information content of experimental data

We have developed a sequential optimization methodology, entitled the parameter identification method based on the localization of information (PIMLI) that increases information retrieval from the data by inferring the location and type of measurements that are most informative for the model parameters. The PIMLI approach merges the strengths of the generalized sensitivity analysis (GSA) method [Spear and Hornberger, 1980], the Bayesian recursive estimation (BARE) algorithm [Thiemann et al., 2001], and the Metropolis algorithm [Metropolis et al., 1953]. Three case studies with increasing complexity are used to illustrate the usefulness and applicability of the PIMLI methodology. The first two case studies consider the identification of soil hydraulic parameters using soil water retention data and a transient multistep outflow experiment (MSO), whereas the third study involves the calibration of a conceptual rainfall-runoff model

Fox River Watershed Investigation: Stratton Dam to the Illinois River: Phase II Blackberry Creek and Poplar Creek Hydrologic and Water Quality Simulation Models: Executive Summary

Fox River Study Group, Inc.published or submitted for publicationis peer reviewe