This page has only limited features, please log in for full access.
Using the parameters associated with the best-fit simulation (i.e., the simulation with the highest objective function value) to represent a calibrated hydrological model is inadequate. The reason is that the calibrated models best objective function value is usually not significantly different from the next best value or the values after that. This non-uniqueness of the objective function values causes a problem because the best solution's parameters are often significantly different from the next best set of parameters. Therefore, only using the best simulation parameters as the calibrated model's sole parameters to interpret the watershed processes or perform further modeling analyses could produce misleading results. Furthermore, the lack of pristine watersheds makes the task of watershed-scale calibration increasingly challenging. Subjective thresholds of acceptable performance criteria suggested by some researchers, based on comparing the measured and the best solution signals, are often not achievable. Hence, to obtain a satisfactory fit, researchers and practitioners are often forced to compromise the science behind their work. This article discusses the fallacy in using the best-fit solution in hydrologic modeling. A two-factor statistic to assess the goodness of calibration/validation is discussed, considering model output uncertainty.
K.C. Abbaspour. The fallacy in the use of the “best-fit” solution in hydrologic modeling. Science of The Total Environment 2021, 802, 149713 .
AMA StyleK.C. Abbaspour. The fallacy in the use of the “best-fit” solution in hydrologic modeling. Science of The Total Environment. 2021; 802 ():149713.
Chicago/Turabian StyleK.C. Abbaspour. 2021. "The fallacy in the use of the “best-fit” solution in hydrologic modeling." Science of The Total Environment 802, no. : 149713.
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Saeid Ashraf Vaghefi; Malihe Keykhai; Farshid Jahanbakhshi; Jaleh Sheikholeslami; Azadeh Ahmadi; Hong Yang; Karim C. Abbaspour. Author Correction: The future of extreme climate in Iran. Scientific Reports 2019, 9, 1 -1.
AMA StyleSaeid Ashraf Vaghefi, Malihe Keykhai, Farshid Jahanbakhshi, Jaleh Sheikholeslami, Azadeh Ahmadi, Hong Yang, Karim C. Abbaspour. Author Correction: The future of extreme climate in Iran. Scientific Reports. 2019; 9 (1):1-1.
Chicago/Turabian StyleSaeid Ashraf Vaghefi; Malihe Keykhai; Farshid Jahanbakhshi; Jaleh Sheikholeslami; Azadeh Ahmadi; Hong Yang; Karim C. Abbaspour. 2019. "Author Correction: The future of extreme climate in Iran." Scientific Reports 9, no. 1: 1-1.
Iran is experiencing unprecedented climate-related problems such as drying of lakes and rivers, dust storms, record-breaking temperatures, droughts, and floods. Here, we use the ensemble of five high-resolution climate models to project maximum and minimum temperatures and rainfall distribution, calculate occurrences of extreme temperatures (temperatures above and below the historical 95th and 5th percentiles, respectively), analyze compound of precipitation and temperature extremes, and determine flooding frequencies across the country. We found that compared to the period of 1980–2004, in the period of 2025–2049, Iran is likely to experience more extended periods of extreme maximum temperatures in the southern part of the country, more extended periods of dry (for ≥120 days: precipitation <2 mm, Tmax ≥30 °C) as well as wet (for ≤3 days: total precipitation ≥110 mm) conditions, and higher frequency of floods. Overall, the combination of these results projects a climate of extended dry periods interrupted by intermittent heavy rainfalls, which is a recipe for increasing the chances of floods. Without thoughtful adaptability measures, some parts of the country may face limited habitability in the future.
Saeid Ashraf Vaghefi; Malihe Keykhai; Farshid Jahanbakhshi; Jaleh Sheikholeslami; Azadeh Ahmadi; Hong Yang; Karim C. Abbaspour. The future of extreme climate in Iran. Scientific Reports 2019, 9, 1 -11.
AMA StyleSaeid Ashraf Vaghefi, Malihe Keykhai, Farshid Jahanbakhshi, Jaleh Sheikholeslami, Azadeh Ahmadi, Hong Yang, Karim C. Abbaspour. The future of extreme climate in Iran. Scientific Reports. 2019; 9 (1):1-11.
Chicago/Turabian StyleSaeid Ashraf Vaghefi; Malihe Keykhai; Farshid Jahanbakhshi; Jaleh Sheikholeslami; Azadeh Ahmadi; Hong Yang; Karim C. Abbaspour. 2019. "The future of extreme climate in Iran." Scientific Reports 9, no. 1: 1-11.
Increasing demand for food is driving a worldwide trend of agricultural input intensification. However, there is no comprehensive knowledge about the interrelations between potential yield gains and environmental trade-offs that would enable the identification of regions where input-driven intensification could achieve higher yields, yet with minimal environmental impacts. We explore ways of enhancing global yields, while avoiding significant nitrogen (N) emissions (Ne) by exploring a range of N and irrigation management scenarios. The simulated responses of yields and Ne to increased N inputs (Nin) and irrigation show high spatial variations due to differences in current agricultural inputs and agro-climatic conditions. Nitrogen use efficiency (NUE) of yield gains is negatively correlated with incremental Ne due to Nin additions. Avoiding further intensification in regions where high fractions of climatic yield potentials, ≥80%, are already achieved is key to maintain good NUE. Depending on the intensification scenarios, relative increases in Ne could be reduced by 0.3–29.6% of the baseline Ne with this intensification strategy as compared to indiscriminate further intensification, at the cost of a loss of yield increases by 0.2–16.7% of the baseline yields. In addition, irrigation water requirements and Nin would dramatically decrease by considering this intensification strategy.
Wenfeng Liu; Hong Yang; Christian Folberth; Christoph Müller; Philippe Ciais; Karim C. Abbaspour; Rainer Schulin. Achieving High Crop Yields with Low Nitrogen Emissions in Global Agricultural Input Intensification. Environmental Science & Technology 2018, 52, 13782 -13791.
AMA StyleWenfeng Liu, Hong Yang, Christian Folberth, Christoph Müller, Philippe Ciais, Karim C. Abbaspour, Rainer Schulin. Achieving High Crop Yields with Low Nitrogen Emissions in Global Agricultural Input Intensification. Environmental Science & Technology. 2018; 52 (23):13782-13791.
Chicago/Turabian StyleWenfeng Liu; Hong Yang; Christian Folberth; Christoph Müller; Philippe Ciais; Karim C. Abbaspour; Rainer Schulin. 2018. "Achieving High Crop Yields with Low Nitrogen Emissions in Global Agricultural Input Intensification." Environmental Science & Technology 52, no. 23: 13782-13791.
Fertilization, crop uptake followed by plant harvest, runoff and erosion, and transformations of phosphorus (P) in soil are the major factors influencing the P balance of croplands. It is important to integrate plant–soil–management interactions into consistent modelling systems to determine the effect of P fertilization conditions on yields and to quantify P losses. Previous assessment of P losses on large scales did not consider the interactions among these factors. Here, we applied a grid‐based crop model to estimate global P losses from three most produced crops maize, rice, and wheat. The model was forced by detailed P input datasets over the period 1998–2002. According to our simulations, global P losses from the three crops reached 1.2 Tg P yr−1, and about 44% of it was due to soil erosion. The global total P losses were dominated by contributions from a few hot‐spot regions. Reducing P fertilizer in regions experiencing excessive P uses and hence losses, especially in China and India, could achieve the same yields as today and save about two‐thirds of global total P inputs, with the co‐benefits of declining global total P losses by 41% and downstream water quality improvement. Reducing soil erosion and retaining more crop residues on croplands could further save P inputs and alleviate P losses. This study is of significance to determine the major factors influencing P balance across regions of the world and help policy makers to propose efficient strategies for tackling P‐driven environmental problems.
Wenfeng Liu; Hong Yang; Philippe Ciais; Christian Stamm; Xu Zhao; Jimmy R. Williams; Karim C. Abbaspour; Rainer Schulin. Integrative Crop-Soil-Management Modeling to Assess Global Phosphorus Losses from Major Crop Cultivations. Global Biogeochemical Cycles 2018, 32, 1074 -1086.
AMA StyleWenfeng Liu, Hong Yang, Philippe Ciais, Christian Stamm, Xu Zhao, Jimmy R. Williams, Karim C. Abbaspour, Rainer Schulin. Integrative Crop-Soil-Management Modeling to Assess Global Phosphorus Losses from Major Crop Cultivations. Global Biogeochemical Cycles. 2018; 32 (7):1074-1086.
Chicago/Turabian StyleWenfeng Liu; Hong Yang; Philippe Ciais; Christian Stamm; Xu Zhao; Jimmy R. Williams; Karim C. Abbaspour; Rainer Schulin. 2018. "Integrative Crop-Soil-Management Modeling to Assess Global Phosphorus Losses from Major Crop Cultivations." Global Biogeochemical Cycles 32, no. 7: 1074-1086.
Crop yields exhibit known responses to droughts. However, quantifying crop drought vulnerability is often not straightforward, because components of vulnerability are not defined in a standardized and spatially comparable quantity in most cases and it must be defined on a fine spatial resolution. This study aims to develop a physical crop drought vulnerability index through linking the Drought Exposure Index (DEI) with the Crop Sensitivity Index (CSI) in Sub-Saharan Africa. Two different DEIs were compared. One was derived from the cumulative distribution functions fitted to precipitation and the other from the difference between precipitation and potential evapotranspiration. DEIs were calculated for one, three, six, nine, and twelve-month time scales. Similarly, CSI was calculated by fitting a cumulative distribution function to maize yield simulated using the Environmental Policy Integrated Climate (EPIC) model. Using a power function, curves were fitted to CSI and DEI relations resulting in different shapes explaining the severity of vulnerability. The results indicated that the highest correlation was found between CSI and DEI obtained from the difference between precipitation and potential evapotranspiration in one, three, and six-month time scales. Our findings show that Southern African countries and some regions of Sahelian strip are highly vulnerable to drought due to experiencing more water stress, whereas vulnerability in Central African countries pertains to temperature stresses. The proposed methodology provides complementary information on quantifying different degrees of vulnerabilities and the underlying reasons. The methodology can be applied to different regions and spatial scales.
Bahareh Kamali; Karim C. Abbaspour; Anthony Lehmann; Bernhard Wehrli; Hong Yang. Spatial assessment of maize physical drought vulnerability in sub-Saharan Africa: Linking drought exposure with crop failure. Environmental Research Letters 2018, 13, 074010 .
AMA StyleBahareh Kamali, Karim C. Abbaspour, Anthony Lehmann, Bernhard Wehrli, Hong Yang. Spatial assessment of maize physical drought vulnerability in sub-Saharan Africa: Linking drought exposure with crop failure. Environmental Research Letters. 2018; 13 (7):074010.
Chicago/Turabian StyleBahareh Kamali; Karim C. Abbaspour; Anthony Lehmann; Bernhard Wehrli; Hong Yang. 2018. "Spatial assessment of maize physical drought vulnerability in sub-Saharan Africa: Linking drought exposure with crop failure." Environmental Research Letters 13, no. 7: 074010.
Bahareh Kamali; Karim C. Abbaspour; Anthony Lehmann; Bernhard Wehrli; Hong Yang. Uncertainty-based auto-calibration for crop yield – the EPIC+ procedure for a case study in Sub-Saharan Africa. European Journal of Agronomy 2018, 93, 57 -72.
AMA StyleBahareh Kamali, Karim C. Abbaspour, Anthony Lehmann, Bernhard Wehrli, Hong Yang. Uncertainty-based auto-calibration for crop yield – the EPIC+ procedure for a case study in Sub-Saharan Africa. European Journal of Agronomy. 2018; 93 ():57-72.
Chicago/Turabian StyleBahareh Kamali; Karim C. Abbaspour; Anthony Lehmann; Bernhard Wehrli; Hong Yang. 2018. "Uncertainty-based auto-calibration for crop yield – the EPIC+ procedure for a case study in Sub-Saharan Africa." European Journal of Agronomy 93, no. : 57-72.
Study region: Alberta, Canada. Study focus: The security of freshwater supplies is a growing concern worldwide. Understanding dynamics of water supply and demand is the key for sustainable planning and management of watersheds. Here we analyzed the uncertainties in water supply of Alberta by building an agro-hydrological model, which accounts for major hydrological features, geo-spatial heterogeneity, and conflicts over water-food-energy resources. We examined the cumulative effects of natural features (e.g., potholes, glaciers, climate, soil, vegetation), anthropogenic factors (e.g., dams, irrigation, industrial development), environmental flow requirements (EFR), and calibration schemes on water scarcity in the dynamics of blue and green water resources, and groundwater recharge. New hydrological insights for the region: Natural hydrologic features of the region create a unique hydrological system, which must be accurately represented in the model for reliable estimates of water supply at high spatial and temporal resolution. Accounting for EFR, increases the number of months of water scarcity and the population exposed. Severe blue water scarcity in spring and summer months was found to be due to irrigated agriculture, while in winter months it was mostly due to the demands of petroleum or other industries. We found over exploitation of the groundwater in southern subbasins and concluded that more detailed analysis on groundwater flow and connectivity is required. Our study provides a general and unified approach for similar analyses in other jurisdictions around the world
Monireh Faramarzi; Karim C. Abbaspour; Wiktor Adamowicz; Wei Lu; Jon Fennell; Alexander J.B. Zehnder; Greg G. Goss. Uncertainty based assessment of dynamic freshwater scarcity in semi-arid watersheds of Alberta, Canada. Journal of Hydrology: Regional Studies 2017, 9, 48 -68.
AMA StyleMonireh Faramarzi, Karim C. Abbaspour, Wiktor Adamowicz, Wei Lu, Jon Fennell, Alexander J.B. Zehnder, Greg G. Goss. Uncertainty based assessment of dynamic freshwater scarcity in semi-arid watersheds of Alberta, Canada. Journal of Hydrology: Regional Studies. 2017; 9 ():48-68.
Chicago/Turabian StyleMonireh Faramarzi; Karim C. Abbaspour; Wiktor Adamowicz; Wei Lu; Jon Fennell; Alexander J.B. Zehnder; Greg G. Goss. 2017. "Uncertainty based assessment of dynamic freshwater scarcity in semi-arid watersheds of Alberta, Canada." Journal of Hydrology: Regional Studies 9, no. : 48-68.
Failure to setup a large-scale hydrological model correctly may not allow proper calibration and uncertainty analyses, leading to inaccurate model prediction. To build a model with accurate accounting of hydrological processes, a data discrimination procedure was applied in this study. The framework uses a hydrological model of Alberta built with the Soil and Water Assessment Tool (SWAT) program. The model was used to quantify the causes and extents of biases in predictions due to different types of input data. Data types represented different sources of errors, including input data (e.g., climate), conceptual model (e.g., potholes, glaciers), and control structure (e.g., reservoirs, dams). The results showed that accounting for these measures leads to a better physical accounting of hydrological processes, significantly improving the overall model performance. The procedure used in this study helps to avoid unnecessary and arbitrary adjustment of parameters to compensate for the errors in the model structure.
Monireh Faramarzi; Raghavan Srinivasan; Majid Iravani; Kevin Bladon; Karim C. Abbaspour; Alexander J.B. Zehnder; Greg Goss. Setting up a hydrological model of Alberta: Data discrimination analyses prior to calibration. Environmental Modelling & Software 2015, 74, 48 -65.
AMA StyleMonireh Faramarzi, Raghavan Srinivasan, Majid Iravani, Kevin Bladon, Karim C. Abbaspour, Alexander J.B. Zehnder, Greg Goss. Setting up a hydrological model of Alberta: Data discrimination analyses prior to calibration. Environmental Modelling & Software. 2015; 74 ():48-65.
Chicago/Turabian StyleMonireh Faramarzi; Raghavan Srinivasan; Majid Iravani; Kevin Bladon; Karim C. Abbaspour; Alexander J.B. Zehnder; Greg Goss. 2015. "Setting up a hydrological model of Alberta: Data discrimination analyses prior to calibration." Environmental Modelling & Software 74, no. : 48-65.
Due to rapid socioeconomic development, continuous population growth and urbanization, the world is facing a severe shortage of fresh water, particularly in arid and semi‐arid regions. A lack of water will put pressure on agricultural production, water pollution, as well as eco‐environmental degradation. Traditional water resources assessment mainly focused on blue water, ignoring green water. Therefore, analysis of spatiotemporal distribution of blue and green water resources in arid and semi‐arid regions is of great significance for water resources planning and management, especially for harmonizing agricultural water use and eco‐environmental water requirements. This study applied the Soil and Water Assessment Tool (SWAT) model and the Sequential Uncertainty Fitting algorithm (SUFI‐2) to calibrate and validate the SWAT model based on river discharges in the Wei River, the largest tributary of the Yellow River in China. Uncertainty analysis was also performed to quantify the blue and green water resources availability at different spatial scales. The results showed that most parts of the Wei River basin (WRB) experienced a decrease in blue water resources during the recent 50 years with a minimum value in the 1990s. The decrease is particularly significant in the most southern part of the WRB (the Guanzhong Plain), one of the most important grain production bases in China. Variations of green water flow and green water storage were relatively small both on spatial and temporal dimensions. This study provides strategic information for optimal utilization of water resources in arid and semi‐arid river basin. Copyright © 2014 John Wiley & Sons, Ltd.
Depeng Zuo; Zongxue Xu; Dingzhi Peng; Jinxi Song; Lei Cheng; Shouke Wei; Karim C. Abbaspour; Hong Yang. Simulating spatiotemporal variability of blue and green water resources availability with uncertainty analysis. Hydrological Processes 2014, 29, 1942 -1955.
AMA StyleDepeng Zuo, Zongxue Xu, Dingzhi Peng, Jinxi Song, Lei Cheng, Shouke Wei, Karim C. Abbaspour, Hong Yang. Simulating spatiotemporal variability of blue and green water resources availability with uncertainty analysis. Hydrological Processes. 2014; 29 (8):1942-1955.
Chicago/Turabian StyleDepeng Zuo; Zongxue Xu; Dingzhi Peng; Jinxi Song; Lei Cheng; Shouke Wei; Karim C. Abbaspour; Hong Yang. 2014. "Simulating spatiotemporal variability of blue and green water resources availability with uncertainty analysis." Hydrological Processes 29, no. 8: 1942-1955.
Water resources availability in the semiarid regions of Iran has experienced severe reduction because of increasing water use and lengthening of dry periods. To better manage this resource, we investigated the impact of climate change on water resources and wheat yield in the Karkheh River Basin (KRB) in the semiarid region of Iran. Future climate scenarios for 2020–2040 were generated from the Canadian Global Coupled Model for scenarios A1B, B1 and A2. We constructed a hydrological model of KRB using the Soil and Water Assessment Tool to project water resources availability. Blue and green water components were modeled with uncertainty ranges for both historic and future data. The Sequential Uncertainty Fitting Version 2 was used with parallel processing option to calibrate the model based on river discharge and wheat yield. Furthermore, a newly developed program called critical continuous day calculator was used to determine the frequency and length of critical periods for precipitation, maximum temperature and soil moisture. We found that in the northern part of KRB, freshwater availability will increase from 1716 to 2670 m3/capita/year despite an increase of 28% in the population in 2025 in the B1 scenario. In the southern part, where much of the agricultural lands are located, the freshwater availability will on the average decrease by 44%. The long‐term average irrigated wheat yield, however, will increase in the south by 1.2%–21% in different subbasins; but for rain‐fed wheat, this variation is from −4% to 38%. The results of critical continuous day calculator showed an increase of up to 25% in both frequency and length of dry periods in south Karkheh, whereas increasing flood events could be expected in the northern and western parts of the region. In general, there is variability in the impact of climate change in the region where some areas will experience net negative whereas other areas will experience a net positive impact. Copyright © 2013 John Wiley & Sons, Ltd.
Seyed Saeid Ashraf Vaghefi; S. Jamshid Mousavi; Karim C Abbaspour; Raghavan Srinivasan; Hong Yang. Analyses of the impact of climate change on water resources components, drought and wheat yield in semiarid regions: Karkheh River Basin in Iran. Hydrological Processes 2013, 28, 2018 -2032.
AMA StyleSeyed Saeid Ashraf Vaghefi, S. Jamshid Mousavi, Karim C Abbaspour, Raghavan Srinivasan, Hong Yang. Analyses of the impact of climate change on water resources components, drought and wheat yield in semiarid regions: Karkheh River Basin in Iran. Hydrological Processes. 2013; 28 (4):2018-2032.
Chicago/Turabian StyleSeyed Saeid Ashraf Vaghefi; S. Jamshid Mousavi; Karim C Abbaspour; Raghavan Srinivasan; Hong Yang. 2013. "Analyses of the impact of climate change on water resources components, drought and wheat yield in semiarid regions: Karkheh River Basin in Iran." Hydrological Processes 28, no. 4: 2018-2032.
Monireh Faramarzi; Karim C. Abbaspour; Saeid Ashraf Vaghefi; Mohammad Reza Farzaneh; Alexander J.B. Zehnder; Raghavan Srinivasan; Hong Yang. Modeling impacts of climate change on freshwater availability in Africa. Journal of Hydrology 2013, 480, 85 -101.
AMA StyleMonireh Faramarzi, Karim C. Abbaspour, Saeid Ashraf Vaghefi, Mohammad Reza Farzaneh, Alexander J.B. Zehnder, Raghavan Srinivasan, Hong Yang. Modeling impacts of climate change on freshwater availability in Africa. Journal of Hydrology. 2013; 480 ():85-101.
Chicago/Turabian StyleMonireh Faramarzi; Karim C. Abbaspour; Saeid Ashraf Vaghefi; Mohammad Reza Farzaneh; Alexander J.B. Zehnder; Raghavan Srinivasan; Hong Yang. 2013. "Modeling impacts of climate change on freshwater availability in Africa." Journal of Hydrology 480, no. : 85-101.
Streamflow simulation is often challenging in mountainous watersheds because of irregular topography and complex hydrological processes. Rates of change in precipitation and temperature with respect to elevation often limit the ability to reproduce stream runoff by hydrological models. Anthropogenic influence, such as water transfers in high altitude hydropower reservoirs increases the difficulty in modeling since the natural flow regime is altered by long term storage of water in the reservoirs. The Soil and Water Assessment Tool (SWAT) was used for simulating streamflow in the upper Rhone watershed located in the south western part of Switzerland. The catchment area covers 5220 km2, where most of the land cover is dominated by forest and 14 % is glacier. Streamflow calibration was done at daily time steps for the period of 2001–2005, and validated for 2006–2010. Two different approaches were used for simulating snow and glacier melt process, namely the temperature index approach with and without elevation bands. The hydropower network was implemented based on the intake points that form part of the inter-reservoir network. Subbasins were grouped into two major categories with glaciers and without glaciers for simulating snow and glacier melt processes. Model performance was evaluated both visually and statistically where a good relation between observed and simulated discharge was found. Our study suggests that a proper configuration of the network leads to better model performance despite the complexity that arises for water transaction. Implementing elevation bands generates better results than without elevation bands. Results show that considering all the complexity arising from natural variability and anthropogenic influences, SWAT performs well in simulating runoff in the upper Rhone watershed. Findings from this study can be applicable for high elevation snow and glacier dominated catchments with similar hydro-physiographic constraints.
Kazi Rahman; Chetan Maringanti; Martin Beniston; Florian Widmer; Karim Abbaspour; Anthony Lehmann. Streamflow Modeling in a Highly Managed Mountainous Glacier Watershed Using SWAT: The Upper Rhone River Watershed Case in Switzerland. Water Resources Management 2012, 27, 323 -339.
AMA StyleKazi Rahman, Chetan Maringanti, Martin Beniston, Florian Widmer, Karim Abbaspour, Anthony Lehmann. Streamflow Modeling in a Highly Managed Mountainous Glacier Watershed Using SWAT: The Upper Rhone River Watershed Case in Switzerland. Water Resources Management. 2012; 27 (2):323-339.
Chicago/Turabian StyleKazi Rahman; Chetan Maringanti; Martin Beniston; Florian Widmer; Karim Abbaspour; Anthony Lehmann. 2012. "Streamflow Modeling in a Highly Managed Mountainous Glacier Watershed Using SWAT: The Upper Rhone River Watershed Case in Switzerland." Water Resources Management 27, no. 2: 323-339.
Spatially explicit large-scale crop growth models are often applied at the global scale with no or little adjustments to regional conditions, which may produce unreliable model results. To tackle this issue, we have regionalized a large-scale crop model for simulating maize cultivation in sub-Saharan Africa (SSA). Planting dates were estimated using reported planting seasons, plant growth parameters were adopted from literature to reflect a low-yielding cultivar, and agricultural practice was mimicked by simulating continuous cultivation of maize with removal of plant residues. The analysis of different estimates of planting date showed that a monthly time step was too coarse in (semi-)arid regions and a weekly step should be used. Limiting planting date estimates by reported seasons is especially important in regions with bimodal rain seasons. The parameterization of a low-yielding cultivar by decreasing the maximum and minimum harvest index (HI) in the model resulted in HI estimates within the range of values reported in the literature. The most important step in the model adjustment was found to be the removal of plant residue. This leads together with little fertilizer inputs to soil nutrient and organic carbon depletion, which has been taking place in most parts of SSA during the past decades. If residue removal is not taken into account, the simulation results in organic carbon sequestration and only minor nutrient depletion. With the adjustments of cultivar, planting dates, and agricultural practice in the model setup, crop growth is in most areas of SSA mainly constrained by nutrient stress as compared to water and temperature. The estimated national and regional average yields compared well with reported yields for the major maize producing countries, suggesting that the regionalized model is suitable for supporting policies on water and soil management in SSA.
Christian Folberth; Thomas Gaiser; Karim C. Abbaspour; Rainer Schulin; Hong Yang. Regionalization of a large-scale crop growth model for sub-Saharan Africa: Model setup, evaluation, and estimation of maize yields. Agriculture, Ecosystems & Environment 2012, 151, 21 -33.
AMA StyleChristian Folberth, Thomas Gaiser, Karim C. Abbaspour, Rainer Schulin, Hong Yang. Regionalization of a large-scale crop growth model for sub-Saharan Africa: Model setup, evaluation, and estimation of maize yields. Agriculture, Ecosystems & Environment. 2012; 151 ():21-33.
Chicago/Turabian StyleChristian Folberth; Thomas Gaiser; Karim C. Abbaspour; Rainer Schulin; Hong Yang. 2012. "Regionalization of a large-scale crop growth model for sub-Saharan Africa: Model setup, evaluation, and estimation of maize yields." Agriculture, Ecosystems & Environment 151, no. : 21-33.
There is an increasing interest in modeling groundwater contamination, particularly geogenic contaminant, on a large scale both from the researcher’s as well as policy maker’s point of view. However, modeling large scale groundwater contamination is very challenging due to the incomplete understanding of geochemical and hydrological processes in the aquifer. Despite the incomplete understanding, existing knowledge provides sufficient hints to develop predictive models of geogenic contamination. In this study we used a global database of fluoride measurements (>60,000 entities), as well as global-scale information relevant to soil, geology, elevation, climate, and hydrology to evaluate several hybrid methods. The hybrid methods were developed by combining two classification techniques including classification and regression tree (CART) and “knowledge based clustering” (KBC) and three predictive techniques including multiple linear regression (MLR), adoptive neuro-fuzzy inference system (ANFIS) and logistic regression (LR). The results indicated that combination of classification techniques and nonlinear predictive method (ANFIS and LR) were more reliable than others and provided a better prediction capability. Among the different hybrid procedures, combination of KBC-ANFIS and also CART-ANFIS resulted in larger true positive rates and smaller false negative rates for both training and test data sets. However, as the CART classifier is very unstable and very sensitive to resampling, the combination of KBC and ANFIS is preferred as it not only is more robust but also is flexible enough to account for geohydrological conditions.
Manouchehr Amini; Karim C. Abbaspour; C. Annette Johnson. A comparison of different rule-based statistical models for modeling geogenic groundwater contamination. Environmental Modelling & Software 2010, 25, 1650 -1657.
AMA StyleManouchehr Amini, Karim C. Abbaspour, C. Annette Johnson. A comparison of different rule-based statistical models for modeling geogenic groundwater contamination. Environmental Modelling & Software. 2010; 25 (12):1650-1657.
Chicago/Turabian StyleManouchehr Amini; Karim C. Abbaspour; C. Annette Johnson. 2010. "A comparison of different rule-based statistical models for modeling geogenic groundwater contamination." Environmental Modelling & Software 25, no. 12: 1650-1657.
Samira Akhavan; Jahangir Abedi-Koupai; Sayed-Farhad Mousavi; Majid Afyuni; Sayed-Saeid Eslamian; Karim C. Abbaspour. Application of SWAT model to investigate nitrate leaching in Hamadan–Bahar Watershed, Iran. Agriculture, Ecosystems & Environment 2010, 139, 675 -688.
AMA StyleSamira Akhavan, Jahangir Abedi-Koupai, Sayed-Farhad Mousavi, Majid Afyuni, Sayed-Saeid Eslamian, Karim C. Abbaspour. Application of SWAT model to investigate nitrate leaching in Hamadan–Bahar Watershed, Iran. Agriculture, Ecosystems & Environment. 2010; 139 (4):675-688.
Chicago/Turabian StyleSamira Akhavan; Jahangir Abedi-Koupai; Sayed-Farhad Mousavi; Majid Afyuni; Sayed-Saeid Eslamian; Karim C. Abbaspour. 2010. "Application of SWAT model to investigate nitrate leaching in Hamadan–Bahar Watershed, Iran." Agriculture, Ecosystems & Environment 139, no. 4: 675-688.
One of the major causes of groundwater pollution in Hamadan–Bahar aquifer in western Iran is a non-point source pollution resulting from agricultural activities. Withdrawal of over 88% of drinking water from groundwater resources, adds urgency to the studies leading to a better management of water supplies in this region. In this study, the DRASTIC model was used to construct groundwater vulnerability maps based on the “intrinsic” (natural conditions) and “specific” (including management) concepts. As DRASTIC has drawbacks to simulate specific contaminants, we conditioned the rates on measured nitrate data and optimized the weights of the specific model to obtain a nitrate vulnerability map for the region. The performance of the conditioned DRASTIC model improved significantly (R 2 = 0.52) over the intrinsic (R 2 = 0.12) and specific (R 2 = 0.19) models in predicting the groundwater nitrate concentration. Our study suggests that a locally conditioned DRASTIC model is an effective tool for predicting the region’s vulnerability to nitrate pollution. In addition, comparison of groundwater tables between two periods 30 years apart indicated a drawdown of around 50 m in the central plain of the Hamadan–Bahar region. Our interpretation of the vulnerability maps for the two periods showed a polluted zone developing in the central valley requiring careful evaluation and monitoring.
Samira Akhavan; Sayed-Farhad Mousavi; Jahangir Abedi-Koupai; Karim C. Abbaspour. Conditioning DRASTIC model to simulate nitrate pollution case study: Hamadan–Bahar plain. Environmental Earth Sciences 2010, 63, 1155 -1167.
AMA StyleSamira Akhavan, Sayed-Farhad Mousavi, Jahangir Abedi-Koupai, Karim C. Abbaspour. Conditioning DRASTIC model to simulate nitrate pollution case study: Hamadan–Bahar plain. Environmental Earth Sciences. 2010; 63 (6):1155-1167.
Chicago/Turabian StyleSamira Akhavan; Sayed-Farhad Mousavi; Jahangir Abedi-Koupai; Karim C. Abbaspour. 2010. "Conditioning DRASTIC model to simulate nitrate pollution case study: Hamadan–Bahar plain." Environmental Earth Sciences 63, no. 6: 1155-1167.
Increasing water scarcity has posed a major constraint to sustain food production in many parts of the world. To study the situation at the regional level, we took Iran as an example and analyzed how an intra-country "virtual water trade strategy" (VWTS) may help improve cereal production as well as alleviate the water scarcity problem. This strategy calls, in part, for the adjustment of the structure of cropping pattern (ASCP) and interregional food trade where crop yield and crop water productivity as well as local economic and social conditions are taken into account. We constructed a systematic framework to assess ASCP at the provincial level under various driving forces and constraints. A mixed-integer, multi-objective, linear optimization model was developed and solved by linear programming. Data from 1990–2004 were used to account for yearly fluctuations of water availability and food production. Five scenarios were designed aimed at maximizing the national cereal production while meeting certain levels of wheat self-sufficiency under various water and land constraints in individual provinces. The results show that under the baseline scenario, which assumes a continuation of the existing water use and food policy at the national level, some ASCP scenarios could produce more wheat with less water. Based on different scenarios in ASCP, we calculated that 31% to 100% of the total wheat shortage in the deficit provinces could be supplied by the wheat surplus provinces. As a result, wheat deficit provinces would receive 3.5 billion m3 to 5.5 billion m3 of virtual water by importing wheat from surplus provinces.
M. Faramarzi; H. Yang; J. Mousavi; R. Schulin; C. R. Binder; K. C. Abbaspour. Analysis of intra-country virtual water trade strategy to alleviate water scarcity in Iran. Hydrology and Earth System Sciences 2010, 14, 1417 -1433.
AMA StyleM. Faramarzi, H. Yang, J. Mousavi, R. Schulin, C. R. Binder, K. C. Abbaspour. Analysis of intra-country virtual water trade strategy to alleviate water scarcity in Iran. Hydrology and Earth System Sciences. 2010; 14 (8):1417-1433.
Chicago/Turabian StyleM. Faramarzi; H. Yang; J. Mousavi; R. Schulin; C. R. Binder; K. C. Abbaspour. 2010. "Analysis of intra-country virtual water trade strategy to alleviate water scarcity in Iran." Hydrology and Earth System Sciences 14, no. 8: 1417-1433.
[1] As water resources become further stressed due to increasing levels of societal demand, understanding the effect of climate change on various components of the water cycle is of strategic importance in management of this essential resource. In this study, we used a hydrologic model of Iran to study the impact of future climate on the country's water resources. The hydrologic model was created using the Soil and Water Assessment Tool (SWAT) model and calibrated for the period from 1980 to 2002 using daily river discharges and annual wheat yield data at a subbasin level. Future climate scenarios for periods of 2010–2040 and 2070–2100 were generated from the Canadian Global Coupled Model (CGCM 3.1) for scenarios A1B, B1, and A2, which were downscaled for 37 climate stations across the country. The hydrologic model was then applied to these periods to analyze the effect of future climate on precipitation, blue water, green water, and yield of wheat across the country. For future scenarios we found that in general, wet regions of the country will receive more rainfall while dry regions will receive less. Analysis of daily rainfall intensities indicated more frequent and larger‐intensity floods in the wet regions and more prolonged droughts in the dry regions. When aggregated to provincial levels, the differences in the predictions due to the three future scenarios were smaller than the uncertainty in the hydrologic model. However, at the subbasin level the three climate scenarios produced quite different results in the dry regions of the country, although the results in the wet regions were more or less similar.
Karim C. Abbaspour; Monireh Faramarzi; Samaneh Seyed Ghasemi; Hong Yang. Assessing the impact of climate change on water resources in Iran. Water Resources Research 2009, 45, 1 .
AMA StyleKarim C. Abbaspour, Monireh Faramarzi, Samaneh Seyed Ghasemi, Hong Yang. Assessing the impact of climate change on water resources in Iran. Water Resources Research. 2009; 45 (10):1.
Chicago/Turabian StyleKarim C. Abbaspour; Monireh Faramarzi; Samaneh Seyed Ghasemi; Hong Yang. 2009. "Assessing the impact of climate change on water resources in Iran." Water Resources Research 45, no. 10: 1.
[1] Despite the general awareness that in Africa many people and large areas are suffering from insufficient water supply, spatially and temporally detailed information on freshwater availability and water scarcity is so far rather limited. By applying a semidistributed hydrological model SWAT (Soil and Water Assessment Tool), the freshwater components blue water flow (i.e., water yield plus deep aquifer recharge), green water flow (i.e., actual evapotranspiration), and green water storage (i.e., soil water) were estimated at a subbasin level with monthly resolution for the whole of Africa. Using the program SUFI‐2 (Sequential Uncertainty Fitting Algorithm), the model was calibrated and validated at 207 discharge stations, and prediction uncertainties were quantified. The presented model and its results could be used in various advanced studies on climate change, water and food security, and virtual water trade, among others. The model results are generally good albeit with large prediction uncertainties in some cases. These uncertainties, however, disclose the actual knowledge about the modeled processes. The effect of considering these model‐based uncertainties in advanced studies is shown for the computation of water scarcity indicators.
Jürgen Schuol; Karim C. Abbaspour; Hong Yang; Raghavan Srinivasan; Alexander J. B. Zehnder. Modeling blue and green water availability in Africa. Water Resources Research 2008, 44, 1 .
AMA StyleJürgen Schuol, Karim C. Abbaspour, Hong Yang, Raghavan Srinivasan, Alexander J. B. Zehnder. Modeling blue and green water availability in Africa. Water Resources Research. 2008; 44 (7):1.
Chicago/Turabian StyleJürgen Schuol; Karim C. Abbaspour; Hong Yang; Raghavan Srinivasan; Alexander J. B. Zehnder. 2008. "Modeling blue and green water availability in Africa." Water Resources Research 44, no. 7: 1.