Academic literature on the topic 'IHACRES'

This paper introduces a new rainfall runoff model called ERM (Effective Rainfall routed by Muskingum method), which has been developed based on the popular IHACRES model. The IHACRES model consists of two main components to transfer rainfall to effective rainfall and then to streamflow. The second component of the IHACRES model is a linear unit hydrograph which has been replaced by the classic and well-known Muskingum method in the ERM model. With the effective rainfall by the first component of the IHACRES model, the Muskingum method is used to estimate the quick flow and slow flow separately. Two different sets of input data (temperature or evapotranspiration, rainfall and observed streamflow) and genetic algorithm (GA) as an optimization scheme have been selected to compare the performance of IHACRES and ERM models in calibration and validation. By testing the models in three different catchments, it is found that the ERM model has better performance over the IHACRES model across all three catchments in both calibration and validation. Further studies are needed to apply the ERM on a wide range of catchments to find its strengths and weaknesses.

The identification of unit hydrographs and component flows from rainfall, evapotranspiration and streamflow data (IHACRES) model has been proven to be an efficient yet basic model to simulate rainfall–runoff processes due to the difficulty in obtaining the comprehensive data required by physical models, especially in data-scarce, semi-arid regions. The success of a calibration process is tremendously dependent on the objective function chosen. However, objective functions have been applied largely in over daily and monthly scales and seldom over sub-daily scales. This study, therefore, implements the IHACRES model using ‘hydromad’ in R to simulate flood events with data limitations in Zhidan, a semi-arid catchment in China. We apply objective function constraints by time aggregating the commonly used Nash–Sutcliffe efficiency into daily and hourly scales to investigate the influence of objective function constraints on the model performance and the general capability of the IHACRES model to simulate flood events in the study watershed. The results of the study demonstrated the advantage of the finer time-scaled hourly objective function over its daily counterpart in simulating runoff for the selected flood events. The results also indicated that the IHACRES model performed extremely well in the Zhidan watershed, presenting the feasibility of the use of the IHACRES model to simulate flood events in data scarce, semi-arid regions.

Rainfall–runoff models are not perfect, and the suitability of a model structure depends on catchment characteristics and data. It is important to investigate the pros and cons of a rainfall–runoff model to improve both its high- and low-flow simulation. The production and routing components of the GR4J and IHACRES models were combined to create two new models. Specifically, the GR_IH model is the combination of the production store of the GR4J model and the routing store of the IHACRES model (vice versa in the IH_GR model). The performances of the new models were compared to those of the GR4J and IHACRES models to determine components improving the performance of the two original models. The suitability of the parameters was investigated with sensitivity analysis using 40 years’ worth of spatiotemporally different data for five catchments in Australia. These five catchments consist of two wet catchments, one intermediate catchment, and two dry catchments. As a result, the effective rainfall production and routing components of the IHACRES model were most suitable for high-flow simulation of wet catchments, and the routing component improved the low-flow simulation of intermediate and one dry catchments. Both effective rainfall production and routing components of the GR4J model were suitable for low-flow simulation of one dry catchment. The routing component of the GR4J model improved the low- and high-flow simulation of wet and dry catchments, respectively, and the effective rainfall production component improved both the high- and low-flow simulations of the intermediate catchment relative to the IHACRES model. This study provides useful information for the improvement of the two models.

The modelling of Indragiri Hilir drainage basin is very necessary, considered by Indragiri Hilir area which sometimes overflows into residential areas and disturbs residents' activities. Conceptual analysis of water discharge through the Ihacres software could help to analyze the flow of Indragiri Hilir drainage basin. Rainfall-runoff modeling is used to predict runoff values, one of which is the IHACRES model. The IHACRES model produces nonlinear loss module parameters and linear hydrograph module units. AWLR that will be used is Kuantan Rengat station, Rain Data that will be used are from Tembilahan station and climatology from Air Molek station. Determination of the success of the model used equation R2 and R to calculate the deviation that occurs. The calibration, verification and simulation phase starts in 2010-2015. The result of conceptual analysis of water discharge of Indragiri Hilir drainage basin, In the calibration stage of the IHACRES Model, the best scheme is scheme 2 with R2 value 0.861 and R value 0.864. While the verification phase is carried out with the following year the best scheme is scheme 3 with the highest R2 value with R2 -2,550 and R-value 1,603 and the simulation scheme is the best scheme 5 with R2-1,904 and R-1,341.

The imbalance that occurs between the availability of water and the water needs needed in Indragiri Hilir requires a conseptual review and evaluation. The all-time distribution of water availability is greatly influenced by the distribution of rain throughout the year. Conceptual analysis of water discharge with the help of IHACRES software can help analyze DAS indragiri Hilir discharge. Rainfall-runoff modeling is used to predict the value against the runoff, using the IHACRES model. The IHACRES model produces nonlinear loss module parameters and linear unit hydrograph modules. AWLR will be used, namely Bt. Kuantan Rengat station, Rain Data which will be used from Tembilahan station and climatology used from Air Molek station. Determination of success in the model used the equations R2 and R to calculate the deviation that occurs. The calibration, verification and simulation phases begin in 2010-2015. The results of conceptual analysis of water discharge in Indragiri Hilir watershed, mainstay discharge results for irrigation purposes with a probability of 80% maximum discharge occurred in February by 4.33 m3 / s and minimum discharge occurred in April by 0.34 m3/s. Overall availability of water on site is available throughout the year. but it cannot be used for hydropower needs because the available discharge may be affected by tidal factors. Ketidakseimbangan yang terjadi antara ketersediaan air dan kebutuhan air yang diperlukan di Indragiri Hilir memerlukan peninjauan dan evaluasi yang konseptual. Distribusi ketersedian air sepanjang waktu sangat dipengaruhi oleh distribusi hujan sepanjang tahun . Analisis konseptual debit air dengan bantuan software IHACRES dapat membantu menganalisis debit DAS indragiri hilir. Pemodelan rainfall-runoff digunakan untuk memprediksi nilai terhadap runoff salah satunya yaitu menggunakan model IHACRES. Model IHACRES menghasilkan parameter nonlinier loss module dan linier unit hydrograph module. AWLR akan digunakan yaitu stasiun Bt. Kuantan Rengat, Data Hujan yang akan digunakan yaitu dari stasiun Tembilahan dan klimatologi yang digunakan dari stasiun Air Molek. Penentuan keberhasilan pada model digunakan persamaan R2 dan R untuk menghitung simpangan yang terjadi. Tahap kalibrasi, verifikasi dan simulasi dimulai tahun 2010-2015. Hasil analisis konseptual debit air pada DAS Indragiri Hilir, hasil debit andalan untuk keperluan irigasi dengan probabilitas 80% debit maksimum terjadi pada bulan Februari sebesar 4,33 m3/s dan debit minimum terjadi pada bulan April sebesar 0,34 m3/s. Secara keseluruhan ketersediaan air di lokasi tersedia sepanjang tahun. tetapi tidak bisa digunakan untuk kebutuhan PLTA karena debit yang tersedia mungkin dipengaruhi faktor pasang surut

With increasing stress on water resources in Jordan, application of rainfall-runoff models can be part of the solution to manage and sustain the water sector. In this paper, the metric conceptual IHACRES model is applied to the Wadi Dhuliel arid catchment, north-east Jordan. Rainfall-runoff data from 19 storm events during 1986 to 1992 have been used in this study. Flood estimation was performed on the basis of daily scales and storm events scales. The model was extended for snowfall in order to cope with such extreme events. Although the best performance of the IHACRES model on a daily basis is poor, the performance on storm events scale showed a good agreement between observed and simulated streamflow. Apart from model parameter values, the principal reasons for IHACRES model success in this region are thought to be based on antecedent soil moisture conditions, rainfall duration and rainfall intensity before and during each storm. The model outputs were likely to be sensitive when the monitored flood was relatively small. The optimum parameter values were influenced by the length of calibration data and event specific changes.

Hydrologic models are essential tools for understanding hydrologic processes, such as precipitation, which is a fundamental component of the water cycle. For an improved understanding and the evaluation of different precipitation datasets, especially their applicability for hydrologic modelling, three kinds of precipitation products, CMADS, TMPA-3B42V7 and gauge-interpolated datasets, are compared. Two hydrologic models (IHACRES and Sacramento) are applied to study the accuracy of the three types of precipitation products on the daily streamflow of the Lijiang River, which is located in southern China. The models are calibrated separately with different precipitation products, with the results showing that the CMADS product performs best based on the Nash–Sutcliffe efficiency, including a much better accuracy and better skill in capturing the streamflow peaks than the other precipitation products. The TMPA-3B42V7 product shows a small improvement on the gauge-interpolated product. Compared to TMPA-3B42V7, CMADS shows better agreement with the ground-observation data through a pixel-to-point comparison. The comparison of the two hydrologic models shows that both the IHACRES and Sacramento models perform well. The IHACRES model however displays less uncertainty and a higher applicability than the Sacramento model in the Lijiang River basin.

Water supply availability has significant impacts on the biggest base for commodity grain production: The Sanjiang Plain in northeast China. The SWAT (soil and water assessment tool) model and IHACRES (identification of unit hydrographs and component flows from rainfall, evapotranspiration and streamflow data) model were used for modelling streamflow variability in the upper Naoli River watershed to determine the applicability of hydrological models to the marsh rivers. Both the SWAT and IHACRES models were suitable for streamflow simulation, having R2 (coefficient of determination) and NS (Nash–Sutcliffe) values greater than 0.7, and PBIAS (percent bias) smaller than 25%. The IHACRES model was easy to use, with less data-preparation, and was found to be a better choice for runoff simulation in a watershed less affected by human activity. The simulation result was better in primeval times, i.e., 1956–1966, than the period 1967–2005, when its performance was found to be unfavorable. In contrast, the complex, processes-based SWAT model was found to be more appropriate for simultaneously simulating streamflow variability. In addition, the effects of land use change and human activities in the watershed—where agricultural activities are intensive—were evaluated. The study found that the SWAT model was potentially suitable for water resource planning and management.

The Wadi Dhuliel catchment/ North east Jordan, as any other arid area has distinctive hydrological features with limited water resources. The hydrological regime is characterized by high variability of temporal and spatial rainfall distributions, flash floods, absence of base flow, and high rates of evapotranspiration. The aim of this Ph.D. thesis was to apply lumped and distributed models to simulate stream flow in the Wadi Dhuliel arid catchment. Intensive research was done to estimate the spatial and temporal rainfall distributions using remote sensing. Because most rainfall-runoff models were undertaken for other climatic zones, an attempt was made to study limitations and challenges and improve rainfall-runoff modeling in arid areas in general and for the Wadi Dhuliel in particular. The thesis is divided into three hierarchically ordered research topics. In the first part and research paper, the metric conceptual IHACRES model was applied to daily and storm events time scales, including data from 19 runoff events during the period 1986-1992. The IHACRES model was extended for snowfall in order to cope with such extreme events. The performance of the IHACRES model on daily data was rather poor while the performance on the storm events scale shows a good agreement between observed and simulated streamflow. The modeled outputs were expected to be sensitive when the observed flood was relatively small. The optimum parameter values were influenced by the length of a time series used for calibration and event specific changes. In the second research paper, the Global Satellite Mapping of Precipitation (GSMaP_MVK+) dataset was used to evaluate the precipitation rates over the Wadi Dhuliel arid catchment for the period from January 2003 to March 2008. Due to the scarcity of the ground rain gauge network, the detailed structure of the rainfall distribution was inadequate, so an independent from interpolation techniques was used. Three meteorological stations and six rain gauges were used to adjust and compare with GSMaP_MVK+ estimates. Comparisons between GSMaP_MVK+ measurements and ground rain gauge records show distinct regions of correlation, as well as areas where GSMaP_MVK+ systematically over- and underestimated ground rain gauge records. A multiple linear regression (MLR) model was used to derive the relationship between rainfall and GSMaP_MVK+ in conjunction with temperature, relative humidity, and wind speed. The MLR equations were defined for the three meteorological stations. The ‘best’ fit of the MLR model for each station was chosen and used to interpolate a multiscale temporal and spatial distribution. Results show that the rainfall distribution over the Wadi Dhuliel is characterized by clear west-east and north-south gradients. Estimates from the monthly MLR model were more reliable than estimates obtained using daily data. The adjusted GSMaP_MVK+ dataset performed well in capturing the spatial patterns of the rainfall at monthly and annual time scales, while daily estimation showed some weakness for light and moderate storms. In the third research paper, the HEC-HMS and IHACRES rainfall runoff models were applied to simulate a single streamflow event in the Wadi Dhuliel catchment that occurred in 30-31.01.2008. Both models are considered suitable for arid conditions. The HEC-HMS model application was done in conjunction with the HEC-GeoHMS extension in ArcView 3.3. Streamflow estimation was performed on hourly data. The aim of this study was to develop a new framework of rainfall-runoff model applications in arid catchment by integrating a re-adjusted satellite derived rainfall dataset (GSMaP_MVK+) to determine the location of the rainfall storm. Each model has its own input data sets. HEC-HMS input data include soil type, land use/land cover map, and slope map. IHACRES input data sets include hourly rainfall and temperature. The model was calibrated and validated using observed stream flow data collected from Al-Za’atari discharge station. IHACRES shows some weaknesses, while the flow comparison between the calibrated streamflow results agrees well with the observed streamflow data of the HEC-HMS model. The Nash-Sutcliffe efficiency (Ef) for both models was 0.51, and 0.88 respectively. The application of HEC-HMS model in this study is considered to be satisfactory.

Water resources management in the Pilbara region of Western Australia is vital to industry, economy and the environment. This dissertation has aimed to develop a comprehensive hydrological and hydrogeological assessment of water resources in the Yandi mine area located in the Weeli Wolli Creek catchment in the Pilbara. Water resources in this area have become increasingly vulnerable due to growing demand. Climate conditions, geology and hydrogeology, streamflow and the groundwater system of the study area were assessed. Lumped, data-driven and numerical models were employed to develop an understanding of the available surface water and groundwater resources. Three equations were derived showing the rainfall-runoff relationship within Weeli Wolli Creek catchment and subsequent modelling was undertaken for more hydrology system evaluation. Artificial Neural Networks (ANNs) and IHACRES models were used to simulate the Marillana Creek streamflow discharge, upstream of Yandi. The results suggested that ANN models perform better for a complex catchment hydrological system, compared to IHACRES model. A VISUAL MODFLOW model was used to investigate the groundwater system and its trend in the Yandi area. The model helped to understand the groundwater responses to future development with various pumping strategies and climate conditions. The scenario analysis assisted identification of zones vulnerable to a significant decline in groundwater level in response to dewatering. The analysis indicated that the maximum water level drawdown of 25m occurred in the aquifer from maximum annual pumping of 23GL. With respect to groundwater yield in particular, abstraction has a more direct impact on the groundwater system compared to climate change. The recharge into the groundwater was estimated from the fluctuations of groundwater level, groundwater modelling and water balance method. The estimated recharge from these methods was comparable and consistent within 3 to 5% of rainfall. This suggests that direct rainfall infiltration is less, compared to localised infiltration. Two new equations, applicable to Australian conditions, were developed to estimate potential evapotranspiration (ET0). These equations form a part of the water balance equation for groundwater recharge estimation. An artificial intelligent model, based on the Honey-Bee Mating Optimization algorithm (HBMO), was introduced to calibrate the new ET0 equations. The newly developed equations had better performances than available popular equations. The results of this study showed that the water resources in Yandi are considerably affected by progressing activities and their associated water requirements. A combination of multiple water assessments and modellings suggested that it is feasible to predict future access to surface water as a function of its influencing factors such as climate condition and mining activities. Scenario analysis in groundwater assessment suggested possible alternative future dewatering strategies in the Yandi mine area. The possible groundwater level recovery time is estimated to be one hundred years, which indicates this resource may not be a reliable option in future. Hydrological water balance analysis also indicated that the available surface water volume would decrease to half upon cease of discharge due to closure of mines in the study area, which is controversial condition for future water management. This research can lead to the implementation of a sustainable water resources plan, and development of appropriate strategies.

Existing terrestrial carbon accounting models have mainly investigated atmosphere-vegetationsoil stocks and fluxes but have largely ignored the hydrological flux of organic carbon. It is generally assumed that biomass and soil carbon are the only relevant pools in a landscape ecosystem. However, recent findings have suggested that significant amounts of organic carbon can dissolve (dissolved organic carbon or DOC) or particulate (particulate organic carbon or POC) in water and enter the hydrological flux at the catchment scale. A significant quantity of total organic carbon (TOC) sequestered through photosynthesis may be exported from the landscape through the hydrological flux and stored in downstream stocks.¶ This thesis presents a catchment-scale case study investigation into the export of organic carbon through a river system in comparison with carbon that is produced by vegetation through photosynthesis. The Cotter River Catchment was selected as the case study. It is a forested catchment that experienced a major wildfire event in January 2003. The approach is based on an integration of a number of models. The main input data were time series of in-stream carbon measurements and remotely sensed vegetation greenness. The application of models to investigate diffuse chemical substances has dramatically increased in the past few years because of the significant role of hydrology in controlling ecosystem exchange. The research firstly discusses the use of a hydrological simulation model (IHACRES) to analyse organic carbon samples from stream and tributaries in the Cotter River Catchment case study. The IHACRES rainfall-runoff model and a regionalization method are used to estimate stream-flow for the 75 sub-catchments. The simulated streamflow data were used to calculate organic carbon loads from concentrations sampled at five locations in the catchment.¶ The gross primary productivity (GPP) of the vegetation cover in the catchment was estimated using a radiation use efficiency (RUE) model driven by MODIS TERRA data on vegetation greenness and modeled surface irradiance (RS). The relationship between total organic carbon discharged in-stream and total carbon uptake by plants was assessed using a cross-correlation analysis.¶ The IHACRES rainfall-runoff model was successfully calibrated at three gauged sites and performed well. The results of the calibration procedure were used in the regionalization method that enabled streamflow to be estimated at ungauged locations including the seven sampling sites and the 75 sub-catchment areas. The IHACRES modelling approach was found appropriate for investigating a wide range of issues related to the hydrological export of organic carbon at the catchment scale. A weekly sampling program was implemented to provide estimates of TOC, DOC and POC concentrations in the Cotter River Catchment between July 2003 and June 2004. The organic carbon load was estimated using an averaging method.¶ The rate of photosynthesis by vegetation (GPP) was successfully estimated using the radiation use efficiency model to discern general patterns of vegetation productivity at sub-catchment scales. This analysis required detailed spatial resolution of the GPP across the entire catchment area (comprising 75 sub-catchment areas) in addition to the sampling locations. Important factors that varied at the catchment scale during the sampling period July 2003 – June 2004, particularly the wildfire impacts, were also considered in this assessment. ¶ The results of the hydrologic modelling approach and terrestrial GPP outcome were compared using cross correlation and regression analysis. This comparison revealed the likely proportion of catchment GPP that contributes to in-stream hydrological flux of organic carbon. TOC Load was 0.45% of GPP and 22.5 - 25% of litter layer. As a result of this investigation and giving due consideration to the uncertainties in the approach, it can be concluded that the hydrological flux of organic carbon in a forested catchment is a function of gross primary productivity.

Research Doctorate - Doctor of Philosophy (PhD)
Water resources management relies on hydrological (or rainfall runoff (R-R)) models. These models are typically used with an implicit assumption that hydrological processes and catchment characteristics are stationary. However, state-of-the-art R-R and eco-hydrological models (including the Australian Water Resources Assessment (AWRA) and the Source modelling platform) have been found to overestimate runoff during multi-year droughts in Southeast Australia (SEA), especially when calibrated during non-dry epochs. Therefore, it is necessary to identify the reasons why R-R models fail to realistically simulate runoff in catchments associated with non-stationarity in climate and/or catchment conditions. In this thesis, mechanisms governing both the annual and seasonal scale non-stationarity in R-R relationships were evaluated for two heterogeneous catchments in the SEA. The mechanisms evaluated were selected from the literature and were categorised into endogenous and exogenous (climate associated) catchment mechanisms. The results show that groundwater (GW) table (and associated surface water (SW)-GW interactions), baseflow (sub-surface water flow) and Leaf Area Index (LAI) (a proxy for vegetation cover) are the main endogenous catchment mechanisms which govern R-R non stationarity at both annual and seasonal scales. For exogenous catchment mechanisms, maximum temperature (T_max), rainfall and potential evapotranspiration (ET₀) are found to be the most influential on R-R non-stationarity at annual and seasonal scales. These insights into important endogenous and exogenous catchment mechanisms were then supplemented by an investigation into which R-R model performs best under hydroclimatic variability and non-stationarity for the two study catchments in SEA. Multiple criteria analysis was used to decide on three R-R models (a conceptually lumped model (IHACRES), a process-based semi-distributed model (HEC-HMS) and a fully-distributed model (SWATgrid)) to compare under contrasting hydroclimatic conditions (Average1, Average2, Dry1, Dry2, Wet1 and Wet2 conditions). The models were calibrated for the Average1, Dry1 and Wet1 epochs and validated for Average2, Dry2 and Wet2 epochs for each calibration epochs. It was found that while SWATgrid model realistically simulates runoff at the smaller catchment for calibration/validation during the Average1 and Wet1 epochs. None of the models realistically simulate runoff under any climatic epoch in the larger catchment. This highlights the knowledge gap already mentioned, that existing R-R models do not realistically simulate runoff in catchments associated with non-stationarity in hydroclimatic conditions. In theory, a semi- or fully-distributed R-R model should account for mechanisms governing non-stationarity in R-R relationships. However, this is obviously not happening and it is hypothesised that a reason for this is the lack of realistic representation of SW-GW interactions in current R-R models. Therefore, in order to address this, a linked SW-GW modelling approach was developed and tested in the two study catchments. The linked SW-GW modelling approach couples a SW (or R-R) model (which is SWATgrid as it was identified to be the best performing model under hydroclimatic variability) and a GW model (MODFLOW, chosen based on multiple criteria analysis). First, SWATgrid was calibrated using its integrated GW approach of lumped baseflow components (stand-alone SWATgrid) and MODFLOW was calibrated under steady state condition with its integrated recharge calculation scheme. This was followed by the linked SW-GW approach simulation, where, the lumped baseflow estimation was replaced by the detailed GW flow estimation by MODFLOW and the recharge calculation of MODFLOW was replaced by the comprehensive recharge estimation by the SWATgrid model. The findings show that for both study catchments the linked SW-GW modelling approach results in more realistic runoff simulation under hydroclimatic variability compared to the stand-alone SWATgrid model. The findings of this thesis emphasise the importance of the identification of mechanisms governing R-R non-stationarity at both annual and seasonal scales. Also, it is recommended that, for arid/semi-arid catchments that have experienced, or are projected to experience, non-stationarity in R-R relationships (e.g. during multi-year droughts), a linked SW-GW modelling approach, such as that presented here, be employed. Otherwise, runoff estimates will continue to be unrealistic, especially during droughts and especially given projections of a hotter and drier future for much of SEA. These findings have direct implications for current and future water resources management in Australia, and anywhere else which experiences, or is projected to experience, non-stationarity in R-R relationships. Furthermore, the insights gained also contribute to the aims of the International Association of Hydrological Sciences decade (2013-2022) Panta Rhei, which focusses on improving our capability to make predictions of water resources dynamics to support sustainable societal development in a changing environment.

Existing terrestrial carbon accounting models have mainly investigated atmosphere-vegetationsoil stocks and fluxes but have largely ignored the hydrological flux of organic carbon. It is generally assumed that biomass and soil carbon are the only relevant pools in a landscape ecosystem. However, recent findings have suggested that significant amounts of organic carbon can dissolve (dissolved organic carbon or DOC) or particulate (particulate organic carbon or POC) in water and enter the hydrological flux at the catchment scale. A significant quantity of total organic carbon (TOC) sequestered through photosynthesis may be exported from the landscape through the hydrological flux and stored in downstream stocks.¶ This thesis presents a catchment-scale case study investigation into the export of organic carbon through a river system in comparison with carbon that is produced by vegetation through photosynthesis. The Cotter River Catchment was selected as the case study. It is a forested catchment that experienced a major wildfire event in January 2003. The approach is based on an integration of a number of models. The main input data were time series of in-stream carbon measurements and remotely sensed vegetation greenness. The application of models to investigate diffuse chemical substances has dramatically increased in the past few years because of the significant role of hydrology in controlling ecosystem exchange. The research firstly discusses the use of a hydrological simulation model (IHACRES) to analyse organic carbon samples from stream and tributaries in the Cotter River Catchment case study. The IHACRES rainfall-runoff model and a regionalization method are used to estimate stream-flow for the 75 sub-catchments. The simulated streamflow data were used to calculate organic carbon loads from concentrations sampled at five locations in the catchment.¶ ...