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This study attempted to generate a long-term (1961–2010) daily gridded precipitation dataset for the Upper Indus Basin (UIB) with orographic adjustments so as to generate realistic precipitation estimates, enabling hydrological and water resource investigations that can close the water balance, that is difficult, if not impossible to achieve with the currently available precipitation data products for the basin. The procedure includes temporal reconstruction of precipitation series at points where data were not recorded prior to the mid-nineties, followed by a regionalization of the precipitation series to a smaller scale across the basin (0.125 ° × 0.125 °), while introducing adjustments for the orographic effect and changes in glacier storage. The reconstruction process involves interpolation of the precipitation at virtual locations of the current (1995-) dense observational network, followed by corrections for frequency and intensity and adjustments for temporal trends at these virtual locations. The data generated in this way were further validated for temporal and spatial representativeness through evaluation of SWAT-modelled streamflow responses against observed flows across the UIB. The results show that the calibrated SWAT-simulated daily discharge at the basin outlet as well as at different sub-basin outlets, when forcing the model with the reconstructed precipitation of years 1973–1996, is almost identical to that when forcing it with the reference precipitation data (1997–2008). Finally, the spatial distribution pattern of the reconstructed (1961–1996) and reference (1997–2008) precipitation were also found consistent across the UIB, reflecting well the large-scale atmospheric-circulation pattern in the region.
Asim Jahangir Khan; Manfred Koch. Generation of a long-term daily gridded precipitation dataset for the Upper Indus Basin (UIB) through temporal Reconstruction, Correction & Informed Regionalization-“ReCIR”. International Soil and Water Conservation Research 2021, 9, 445 -460.
AMA StyleAsim Jahangir Khan, Manfred Koch. Generation of a long-term daily gridded precipitation dataset for the Upper Indus Basin (UIB) through temporal Reconstruction, Correction & Informed Regionalization-“ReCIR”. International Soil and Water Conservation Research. 2021; 9 (3):445-460.
Chicago/Turabian StyleAsim Jahangir Khan; Manfred Koch. 2021. "Generation of a long-term daily gridded precipitation dataset for the Upper Indus Basin (UIB) through temporal Reconstruction, Correction & Informed Regionalization-“ReCIR”." International Soil and Water Conservation Research 9, no. 3: 445-460.
Projection of potential climate change impacts on gaining and losing streams, particularly in ephemeral river basins representing a sporadic and intricate flux exchange, has remained largely unexplored. Therefore, the present study aims to introduce a promising scheme to characterize and quantify the complex interactions of surface‐groundwater, reflected in gaining and losing streams, under a combination of climatic and groundwater pumping scenarios. To that end, a recently developed fully integrated hydrological model was forced by the daily downscaled minimum and maximum temperature and precipitation under three Representative Concentration Pathways (RCPs), namely RCP 2.6, RCP 4.5, and RCP 8.5 and under two pumping and non‐pumping scenarios. Due to forcing of the coupled model under the climatic and pumping scenarios, the net impacts of the climate change could be distinguished from that of the groundwater overutilization in Gharehsoo River Basin (GRB), in northwestern Iran. Results demonstrated that the gaining streams (effluent condition) will be more influenced by the climate change scenarios and pumping conditions, compared with the losing steams (influent condition). Overall, under the climate scenarios and the pumping condition, the baseflow, yielded by the gaining streams, will decrease, whereas the focused recharge, generated from the losing streams, will increase. Conversely, the focused recharge will be dropped under the climate scenarios and the non‐pumping condition, whereas the baseflow will be raised under the non‐pumping scenario, irrespective of the climatic scenarios. Moreover, finding revealed that, compared with climate change impacts, groundwater overutilization is the compelling reason for the groundwater storage drawdown in this aquifer.
M. Taie Semiromi; M. Koch. How Do Gaining and Losing Streams React to the Combined Effects of Climate Change and Pumping in the Gharehsoo River Basin, Iran? Water Resources Research 2020, 56, 1 .
AMA StyleM. Taie Semiromi, M. Koch. How Do Gaining and Losing Streams React to the Combined Effects of Climate Change and Pumping in the Gharehsoo River Basin, Iran? Water Resources Research. 2020; 56 (7):1.
Chicago/Turabian StyleM. Taie Semiromi; M. Koch. 2020. "How Do Gaining and Losing Streams React to the Combined Effects of Climate Change and Pumping in the Gharehsoo River Basin, Iran?" Water Resources Research 56, no. 7: 1.
Two 3D hydrodynamic models, AEM3D and MIKE3, are compared in simulating hydrodynamics of the Maroon Reservoir in southwest Iran. The reservoir has a complex bathymetry with steep walls, which makes it a good case for studying the performance of hydrodynamic models. The models were compared together and with measured water temperatures from different locations of the reservoir in a five-month period between December 2011 and April 2012. The results indicated that the AEM3D model, which uses a finite difference scheme with a purely z-level vertical discretization, showed better consistency with observations so that the AME and RMSE of the model remain below 1 °C. The MIKE3 model showed overall higher errors from 56% to 130% larger than AEM3D and the level of error strongly depends on its vertical discretization method and the turbulence model. The lowest errors by MIKE3 were seen by the k-ε turbulence model with a hybrid z-sigma discretization, while the highest errors were generated by using the sigma vertical discretization. The vertical mixing model in AEM3D model, used instead of the constant eddy viscosity or k-ε formulation, showed a better performance in modeling vertical mixing and wind mixed layer, which is another reason of observing better results by this model than MIKE3. Overall, this study shows AEM3D as a more appropriate model for simulating deep and complex reservoirs with steep slopes and walls.
Behnam Zamani; Manfred Koch. Comparison Between Two Hydrodynamic Models in Simulating Physical Processes of a Reservoir with Complex Morphology: Maroon Reservoir. Water 2020, 12, 814 .
AMA StyleBehnam Zamani, Manfred Koch. Comparison Between Two Hydrodynamic Models in Simulating Physical Processes of a Reservoir with Complex Morphology: Maroon Reservoir. Water. 2020; 12 (3):814.
Chicago/Turabian StyleBehnam Zamani; Manfred Koch. 2020. "Comparison Between Two Hydrodynamic Models in Simulating Physical Processes of a Reservoir with Complex Morphology: Maroon Reservoir." Water 12, no. 3: 814.
Projecting future hydrology for the mountainous, highly glaciated upper Indus basin (UIB) is a challenging task because of uncertainties in future climate projections and issues with the coverage and quality of available reference climatic data and hydrological modelling approaches. This study attempts to address these issues by utilizing the semi-distributed hydrological model “Soil and water assessment tool” (SWAT) with new climate datasets and better spatial and altitudinal representation as well as a wider range of future climate forcing models (general circulation model/regional climate model combinations (GCMs_RCMs) from the “Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) project to assess different aspects of future hydrology (mean flows, extremes and seasonal changes). Contour maps for the mean annual flow and actual evapotranspiration as a function of the downscaled projected mean annual precipitation and temperatures are produced and can serve as a “hands-on” forecast tool of future hydrology. The overall results of these future SWAT hydrological projections indicate similar trends of changes in magnitudes, seasonal patterns and extremes of the UIB—stream flows for almost all climate scenarios/models/periods—combinations analyzed. In particular, all but one GCM_RCM model—the one predicting a very high future temperature rise—indicated mean annual flow increases throughout the 21st century, wherefore, interestingly, these are stronger for the middle years (2041–2070) than at its end (2071–2100). The seasonal shifts as well as the extremes follow also similar trends for all climate scenario/model/period combinations, e.g., an earlier future arrival (in May–June instead of July–August) of high flows and increased spring and winter flows, with upper flow extremes (peaks) projected to drastically increase by 50 to >100%, and with significantly decreased annual recurrence intervals, i.e., a tremendously increased future flood hazard for the UIB. The future low flows projections also show more extreme values, with lower-than-nowadays-experienced minimal flows occurring more frequently and with much longer annual total duration.
Asim Khan; Manfred Koch; Adnan Tahir. Impacts of Climate Change on the Water Availability, Seasonality and Extremes in the Upper Indus Basin (UIB). Sustainability 2020, 12, 1283 .
AMA StyleAsim Khan, Manfred Koch, Adnan Tahir. Impacts of Climate Change on the Water Availability, Seasonality and Extremes in the Upper Indus Basin (UIB). Sustainability. 2020; 12 (4):1283.
Chicago/Turabian StyleAsim Khan; Manfred Koch; Adnan Tahir. 2020. "Impacts of Climate Change on the Water Availability, Seasonality and Extremes in the Upper Indus Basin (UIB)." Sustainability 12, no. 4: 1283.
The impacts of climate change on the water availability of Zarrine River Basin (ZRB), the headwater of Lake Urmia, in western Iran, with the Boukan Dam, are simulated under various climate scenarios up to year 2029, using the SWAT hydrological model. The latter is driven by meteorological variables predicted from MPI-ESM-LR-GCM (precipitation) and CanESM2-GCM (temperature) GCM models with RCP 2.6, RCP 4.5 and RCP 8.5 climate scenarios, and downscaled with Quantile Mapping (QM) bias-correction and SDSM, respectively. From two variants of QM employed, the Empirical-CDF-QM model decreased the biases of raw GCM- precipitation predictors particularly strongly. SWAT was then calibrated and validated with historical (1981–2011) ZR-streamflow, using the SWAT-CUP model. The subsequent SWAT-simulations for the future period 2012–2029 indicate that the predicted climate change for all RCPs will lead to a reduction of the inflow to Boukan Dam as well as of the overall water yield of ZRB, mainly due to a 23–35% future precipitation reduction, with a concomitant reduction of the groundwater baseflow to the main channel. Nevertheless, the future runoff-coefficient shows a 3%, 2% and 1% increase, as the −2% to −26% decrease of the surface runoff is overcompensated by the named precipitation decrease. In summary, based on these predictions, together with the expecting increase of demands due to the agricultural and other developments, the ZRB is likely to face a water shortage in the near future as the water yield will decrease by −17% to −39%, unless some adaptation plans are implemented for a better management of water resources.
Farzad Emami; Manfred Koch. Modeling the Impact of Climate Change on Water Availability in the Zarrine River Basin and Inflow to the Boukan Dam, Iran. Climate 2019, 7, 51 .
AMA StyleFarzad Emami, Manfred Koch. Modeling the Impact of Climate Change on Water Availability in the Zarrine River Basin and Inflow to the Boukan Dam, Iran. Climate. 2019; 7 (4):51.
Chicago/Turabian StyleFarzad Emami; Manfred Koch. 2019. "Modeling the Impact of Climate Change on Water Availability in the Zarrine River Basin and Inflow to the Boukan Dam, Iran." Climate 7, no. 4: 51.
Hydrological models are widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are currently available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, first, soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall (SM2R-AMSRE) at different sites in the Karkheh river basin (KRB), southwest Iran. Second, the SWAT (Soil and Water Assessment Tool) hydrological model was applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall due to soil moisture saturation not accounted for in the SM2RAIN equation. The subsequent SWAT-simulated monthly runoff from SM2R-AMSRE rainfall data (SWAT-SM2R-AMSRE) reproduces the observations at the six gauging stations (with coefficient of determination, R² > 0.71 and NSE > 0.56), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation compared to the SWAT model with ground-based rainfall input. Additionally, rainfall estimates of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model after bias correction. The monthly runoff predictions obtained with 3B42- rainfall have 0.42 < R2 < 0.72 and−0.06 < NSE < 0.74 which are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SWAT-SM2R-AMSRE. Therefore, despite the aforementioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT appears to be a viable approach in basins with limited ground-based rainfall data.
Majid Fereidoon; Manfred Koch; Luca Brocca. Predicting Rainfall and Runoff Through Satellite Soil Moisture Data and SWAT Modelling for a Poorly Gauged Basin in Iran. Water 2019, 11, 594 .
AMA StyleMajid Fereidoon, Manfred Koch, Luca Brocca. Predicting Rainfall and Runoff Through Satellite Soil Moisture Data and SWAT Modelling for a Poorly Gauged Basin in Iran. Water. 2019; 11 (3):594.
Chicago/Turabian StyleMajid Fereidoon; Manfred Koch; Luca Brocca. 2019. "Predicting Rainfall and Runoff Through Satellite Soil Moisture Data and SWAT Modelling for a Poorly Gauged Basin in Iran." Water 11, no. 3: 594.
The present study aimed to quantify the future sustainability of a water supply system using dynamically-downscaled regional climate models (RCMs), produced in the South Asia Coordinated Regional Downscaling Experiment (CORDEX) framework. The case study is the Boukan dam, located on the Zarrine River (ZR) of Urmia’s drying lake basin, Iran. Different CORDEX- models were evaluated for model performance in predicting the temperatures and precipitation in the ZR basin (ZRB). The climate output of the most suitable climate model under the RCP45 and RCP85 scenarios was then bias-corrected for three 19-year-long future periods (2030, 2050, and 2080), and employed as input to the Soil and Water Assessment Tool (SWAT) river basin hydrologic model to simulate future Boukan reservoir inflows. Subsequently, the reservoir operation/water demands in the ZRB were modeled using the MODSIM water management tool for two water demand scenarios, i.e., WDcurrent and WDrecom, which represent the current and the more sustainable water demand scenarios, respectively. The reliability of the dam’s water supply for different water uses in the study area was then investigated by computing the supply/demand ratio (SDR). The results showed that, although the SDRs for the WDrecom were generally higher than that of the WDcurrent, the SDRs were all
Farzad Emami; Manfred Koch. Sustainability Assessment of the Water Management System for the Boukan Dam, Iran, Using CORDEX- South Asia Climate Projections. Water 2018, 10, 1723 .
AMA StyleFarzad Emami, Manfred Koch. Sustainability Assessment of the Water Management System for the Boukan Dam, Iran, Using CORDEX- South Asia Climate Projections. Water. 2018; 10 (12):1723.
Chicago/Turabian StyleFarzad Emami; Manfred Koch. 2018. "Sustainability Assessment of the Water Management System for the Boukan Dam, Iran, Using CORDEX- South Asia Climate Projections." Water 10, no. 12: 1723.
This study focusses on identifying a set of representative climate model projections for the Upper Indus Basin (UIB). Although a large number of General Circulation Models (GCM) predictor sets are available nowadays in the CMIP5 archive, the issue of their reliability for specific regions must still be confronted. This situation makes it imperative to sort out the most appropriate single or small-ensemble set of GCMs for the assessment of climate change impacts in a region. Here a set of different approaches is adopted and applied for the step-wise shortlisting and selection of appropriate climate models for the UIB under two RCPs: RCP 4.5 and RCP 8.5, based on: (a) range of projected mean changes, (b) range of projected extreme changes, and (c) skill in reproducing the past climate. Furthermore, because of higher uncertainties in climate projection for high mountainous regions like the UIB, a wider range of future GCM climate projections is considered by using all possible extreme future scenarios (wet-warm, wet-cold, dry-warm, dry-cold). Based on this two-fold procedure, a limited number of climate models is pre-selected, from of which the final selection is done by assigning ranks to the weighted score for each of the mentioned selection criteria. The dynamically downscaled climate projections from the Coordinated Regional Downscaling Experiment (CORDEX) available for the top-ranked GCMs are further statistically downscaled (bias-corrected) over the UIB. The downscaled projections up to the year 2100 indicate temperature increases ranging between 2.3 °C and 9.0 °C and precipitation changes that range from a slight annual increase of 2.2% under the drier scenarios to as high as 15.9% in the wet scenarios. Moreover, for all scenarios, future precipitation will be more extreme, as the probability of wet days will decrease, while, at the same time, precipitation intensities will increase. The spatial distribution of the downscaled predictors across the UIB also shows similar patterns for all scenarios, with a distinct precipitation decrease over the south-eastern parts of the basin, but an increase in the northeastern parts. These two features are particularly intense for the “Dry-Warm” and the “Median” scenarios over the late 21st century.
Asim Jahangir Khan; Manfred Koch. Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB). Climate 2018, 6, 89 .
AMA StyleAsim Jahangir Khan, Manfred Koch. Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB). Climate. 2018; 6 (4):89.
Chicago/Turabian StyleAsim Jahangir Khan; Manfred Koch. 2018. "Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB)." Climate 6, no. 4: 89.
The current study applied a new approach for the interpolation and regionalization of observed precipitation series to a smaller spatial scale (0.125° by 0.125° grid) across the Upper Indus Basin (UIB), with appropriate adjustments for the orographic effect and changes in glacier storage. The approach is evaluated and validated through reverse hydrology, and is guided by observed flows and the available knowledge base. More specifically, the generated corrected precipitation data is validated by means of SWAT-modelled responses of the observed flows to the different input precipitation series (original and corrected ones). The results show that the SWAT-simulated flows using the corrected, regionalized precipitation series as input are much more in line with the observed flows than those using the uncorrected observed precipitation input for which significant underestimations are obtained.
Asim Khan; Manfred Koch. Correction and Informed Regionalization of Precipitation Data in a High Mountainous Region (Upper Indus Basin) and Its Effect on SWAT-Modelled Discharge. Water 2018, 10, 1557 .
AMA StyleAsim Khan, Manfred Koch. Correction and Informed Regionalization of Precipitation Data in a High Mountainous Region (Upper Indus Basin) and Its Effect on SWAT-Modelled Discharge. Water. 2018; 10 (11):1557.
Chicago/Turabian StyleAsim Khan; Manfred Koch. 2018. "Correction and Informed Regionalization of Precipitation Data in a High Mountainous Region (Upper Indus Basin) and Its Effect on SWAT-Modelled Discharge." Water 10, no. 11: 1557.
For water-stressed regions/countries, like Iran, improving the management of agricultural water-use in the wake of climate change and increasingly unsustainable demands is of utmost importance. One step further is then the maximization of the agricultural economic benefits, by properly adjusting the irrigated crop area pattern to optimally use the limited amount of water available. To that avail, a sequential hydro-economic model has been developed and applied to the agriculturally intensively used Zarrine River Basin (ZRB), Iran. In the first step, the surface and groundwater resources, especially, the inflow to the Boukan Dam, as well as the potential crop yields are simulated using the Soil Water Assessment Tool (SWAT) hydrological model, driven by GCM/QM-downscaled climate predictions for three future 21th-century periods under three climate RCPs. While in all nine combinations consistently higher temperatures are predicted, the precipitation pattern are much more versatile, leading to corresponding changes in the future water yields. Using the basin-wide water management tool MODSIM, the SWAT-simulated water available is then optimally distributed across the different irrigation plots in the ZRB, while adhering to various environmental/demand priority constraints. MODSIM is subsequently coupled with CSPSO to optimize (maximize) the agro-economic water productivity (AEWP) of the various crops and, subsequently, the net economic benefit (NEB), using crop areas as decision variables, while respecting various crop cultivation constraints. Adhering to political food security recommendations for the country, three variants of cereal cultivation area constraints are investigated. The results indicate considerably-augmented AEWPs, resulting in a future increase of the annual NEB of ~16% to 37.4 Million USD for the 65%-cereal acreage variant, while, at the same time, the irrigation water required is reduced by ~38%. This NEB-rise is achieved by augmenting the total future crop area in the ZRB by about 47%—indicating some deficit irrigation—wherefore most of this extension will be cultivated by the high AEWP-yielding crops wheat and barley, at the expense of a tremendous reduction of alfalfa acreage. Though presently making up only small base acreages, depending on the future period/RCP, tomato- and, less so, potato- and sugar beet-cultivation areas will also be increased significantly.
Farzad Emami; Manfred Koch. Agricultural Water Productivity-Based Hydro-Economic Modeling for Optimal Crop Pattern and Water Resources Planning in the Zarrine River Basin, Iran, in the Wake of Climate Change. Sustainability 2018, 10, 3953 .
AMA StyleFarzad Emami, Manfred Koch. Agricultural Water Productivity-Based Hydro-Economic Modeling for Optimal Crop Pattern and Water Resources Planning in the Zarrine River Basin, Iran, in the Wake of Climate Change. Sustainability. 2018; 10 (11):3953.
Chicago/Turabian StyleFarzad Emami; Manfred Koch. 2018. "Agricultural Water Productivity-Based Hydro-Economic Modeling for Optimal Crop Pattern and Water Resources Planning in the Zarrine River Basin, Iran, in the Wake of Climate Change." Sustainability 10, no. 11: 3953.
This study focusses on identifying a set of representative future climate projections for the Upper Indus Basin (UIB). Although a large number of GCM’s predictor sets are nowadays available in the CMIP5 archive, the issue of their reliability for specific regions must still be confronted. This situation makes it imperative to sort out the most appropriate, single or small-ensemble set of GCMs for the assessment of climate change impacts in a region. Here a set of different approaches is adopted and applied for a step-wise shortlist and selection of appropriate climate models for the UIB under two RCPs: RCP 4.5 and RCP 8.5, based on, a) range of projected mean changes, b) range of projected extreme changes, and c) skill in reproducing the past climate. Furthermore, because of higher uncertainties in climate projection for high mountainous regions like the UIB, a wider range of future GCM climate projections is considered by using all possible future extreme scenarios (wet-warm, wet-cold, dry-warm, dry-cold). Based on this two-fold procedure, a limited number of climate models is pre-selected, out of which the final selection is done by assigning ranks to the weighted score for each of the mentioned selection criteria. The dynamically downscaled climate projections from the Coordinated Regional Downscaling Experiment (CORDEX) available for the top-ranked GCMs are further statistically downscaled (bias-corrected) over the UIB. The downscaled projections up to year 2100 indicate temperature increases ranging between 2.3 °C and 9.0 °C and precipitation changes that range, from a slight annual increase of 2.2% under the drier scenarios, to as high as 15.9% for the wet scenarios. Moreover, for all scenarios, the future precipitation will be more extreme, as the probability of wet days will decrease, while, at the same time, the precipitation intensities will increase. The spatial distribution of the downscaled predictors across the UIB also shows similar patterns for all scenarios, with a distinct precipitation decrease over the south-eastern parts of the basin, but an increase in the northeastern parts. These two features are particularly intense for the “Dry-Warm” and the “Median” scenarios over the late 21st century.
Asim Jahangir Khan; Manfred Koch. Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB). 2018, 1 .
AMA StyleAsim Jahangir Khan, Manfred Koch. Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB). . 2018; ():1.
Chicago/Turabian StyleAsim Jahangir Khan; Manfred Koch. 2018. "Selecting and Downscaling a Set of Climate Models for Projecting Climatic Change for Impact Assessment in the Upper Indus Basin (UIB)." , no. : 1.
The current study applied a new approach for the interpolation and regionalization of observed precipitation series to a smaller spatial scale (0.125° by 0.125° grid) across the Upper Indus Basin (UIB), with appropriate adjustments for the orographic effect and changes in glacier storage. The approach is evaluated and validated through reverse hydrology, guided by observed flows and available knowledge base. More specifically, the generated corrected precipitation data is validated by means of SWAT-modelled responses of the observed flows to the different input precipitation series (original and corrected ones). The results show that the SWAT- simulated flows using the corrected, regionalized precipitation series as input are much more in line with the observed flows than those using the uncorrected observed precipitation input for which significant underestimations are obtained.
Asim Jahangir Khan; Manfred Koch. Correction and Informed Regionalization of Precipitation Data in a High Mountainous Region (Upper Indus Basin) and Its Effect on SWAT-Modelled Discharge. 2018, 1 .
AMA StyleAsim Jahangir Khan, Manfred Koch. Correction and Informed Regionalization of Precipitation Data in a High Mountainous Region (Upper Indus Basin) and Its Effect on SWAT-Modelled Discharge. . 2018; ():1.
Chicago/Turabian StyleAsim Jahangir Khan; Manfred Koch. 2018. "Correction and Informed Regionalization of Precipitation Data in a High Mountainous Region (Upper Indus Basin) and Its Effect on SWAT-Modelled Discharge." , no. : 1.
The present study aims to evaluate the capability of the Tropical Rainfall Measurement Mission (TRMM), Multi-satellite Precipitation Analysis (TMPA), version 7 (TRMM-3B42-V7) precipitation product to estimate appropriate precipitation rates in the Upper Indus Basin (UIB) by analyzing the dependency of the estimates’ accuracies on the time scale. To that avail, various statistical analyses and comparison of Multisatellite Precipitation Analysis (TMPA) products with gauge measurements in the UIB are carried out. The dependency of the TMPA estimates’ quality on the aggregation time scale is analyzed by comparisons of daily, monthly, seasonal and annual sums for the UIB. The results show considerable biases in the TMPA Tropical Rainfall Measurement Mission (TRMM) precipitation estimates for the UIB, as well as high numbers of false alarms and miss ratios. The correlation of the TMPA estimates with ground-based gauge data increases considerably and almost in a linear fashion with increasing temporal aggregation, i.e., time scale. There is a predominant trend of underestimation of the TRMM product across the UIB at most of the gauge stations, i.e., TRMM-estimated rainfall is generally lower than the gauge-measured rainfall. For the seasonal aggregates, the bias is mostly positive for the summer but predominantly negative for the winter season, thereby showing a slight overestimation of the precipitation in summer and underestimation in winter. The results of the study suggest that, in spite of these discrepancies between TMPA estimates and gauge data, the use of the former in hydrological watershed modeling undertaken by the authors may be a valuable alternative in data-scarce regions like the UIB, but still must be taken with a grain of salt.
Asim Jahangir Khan; Manfred Koch; Karen Milena Chinchilla. Evaluation of Gridded Multi-Satellite Precipitation Estimation (TRMM-3B42-V7) Performance in the Upper Indus Basin (UIB). Climate 2018, 6, 76 .
AMA StyleAsim Jahangir Khan, Manfred Koch, Karen Milena Chinchilla. Evaluation of Gridded Multi-Satellite Precipitation Estimation (TRMM-3B42-V7) Performance in the Upper Indus Basin (UIB). Climate. 2018; 6 (3):76.
Chicago/Turabian StyleAsim Jahangir Khan; Manfred Koch; Karen Milena Chinchilla. 2018. "Evaluation of Gridded Multi-Satellite Precipitation Estimation (TRMM-3B42-V7) Performance in the Upper Indus Basin (UIB)." Climate 6, no. 3: 76.
The present study aims to evaluate the capability of the TRMM-3B42-(V7) precipitation product to estimate appropriate precipitation rates in the Upper Indus basin (UIB) and the analysis of the dependency of the estimates’ accuracies on the time scale. To that avail statistical analyses and comparison of the TMPA- products with gauge measurements in the UIB are carried out. The dependency of the TMPA estimates’ quality on the time scale is analysed by comparisons of daily, monthly, seasonal and annual sums for the UIB. The results show considerable biases in the TMPA- (TRMM) precipitation estimates for the UIB, as well as high false alarms and miss ratios. The correlation of the TMPA- estimates with ground-based gauge data increases considerably and almost in a linear fashion with increasing temporal aggregation, i.e. time scale. The BIAS is mostly positive for the summer season, while for the winter season it is predominantly negative, thereby showing a slight over-estimation of the precipitation in summer and under-estimation in winter. The results of the study suggest that, in spite of these discrepancies between TMPA- estimates and gauge data, the use of the former in hydrological watershed modelling, endeavoured presently by the authors, may be a valuable alternative in data- scarce regions, like the UIB, but still must be taken with a grain of salt.
Asim Jahangir Khan; Manfred Koch; Karen Milena Chinchilla. Evaluation of Gridded Multi-Satellite Precipitation (TRMM-3B42-V7) Estimation Performance in the Upper Indus Basin (UIB). 2018, 1 .
AMA StyleAsim Jahangir Khan, Manfred Koch, Karen Milena Chinchilla. Evaluation of Gridded Multi-Satellite Precipitation (TRMM-3B42-V7) Estimation Performance in the Upper Indus Basin (UIB). . 2018; ():1.
Chicago/Turabian StyleAsim Jahangir Khan; Manfred Koch; Karen Milena Chinchilla. 2018. "Evaluation of Gridded Multi-Satellite Precipitation (TRMM-3B42-V7) Estimation Performance in the Upper Indus Basin (UIB)." , no. : 1.
Accurate estimates of daily rainfall are essential for understanding and modeling the physical processes involved in the interaction between the land surface and the atmosphere. In this study, daily satellite soil moisture observations from the Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR–E) generated by implementing the standard National Aeronautics and Space Administration (NASA) algorithm are employed for estimating rainfall, firstly, through the use of recently developed approach, SM2RAIN and, secondly, the nonlinear autoregressive network with exogenous inputs (NARX) neural modelling at five climate stations in the Karkheh river basin (KRB), located in south-west Iran. In the SM2RAIN method, the period 1 January 2003 to 31 December 2005 is used for the calibration of algorithm and the remaining 9 months from 1 January 2006 to 30 September 2006 is used for the validation of the rainfall estimates. In the NARX model, the full study period is split into training (1 January 2003 to 31 September 2005) and testing (1 September 2005 to 30 September 2006) stages. For the prediction of the rainfall as the desired target (output), relative soil moisture changes from AMSR–E and measured air temperature time series are chosen as exogenous (external) inputs in NARX. The quality of the estimated rainfall data is evaluated by comparing it with observed rainfall data at the five rain gauges in terms of the coefficient of determination R2, the RMSE and the statistical bias. For the SM2RAIN method, R2 ranges between 0.32 and 0.79 for all stations, whereas for the NARX- model the values are generally slightly lower. Moreover, the values of the bias for each station indicate that although SM2RAIN is likely to underestimate large rainfall intensities, due to the known effect of soil moisture saturation, its biases are somewhat lower than those of NARX. Moreover, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN–CDR) is employed to evaluate its potential for predicting the ground-based observed station rainfall, but it is found to work poorly. In conclusion, the results of the present study show that with the use of AMSR–E soil moisture products in the physically based SM2RAIN algorithm as well as in the NARX neural network, rainfall for poorly gauged regions can be predicted satisfactorily.
Majid Fereidoon; Manfred Koch. Rainfall Prediction with AMSR–E Soil Moisture Products Using SM2RAIN and Nonlinear Autoregressive Networks with Exogenous Input (NARX) for Poorly Gauged Basins: Application to the Karkheh River Basin, Iran. Water 2018, 10, 964 .
AMA StyleMajid Fereidoon, Manfred Koch. Rainfall Prediction with AMSR–E Soil Moisture Products Using SM2RAIN and Nonlinear Autoregressive Networks with Exogenous Input (NARX) for Poorly Gauged Basins: Application to the Karkheh River Basin, Iran. Water. 2018; 10 (7):964.
Chicago/Turabian StyleMajid Fereidoon; Manfred Koch. 2018. "Rainfall Prediction with AMSR–E Soil Moisture Products Using SM2RAIN and Nonlinear Autoregressive Networks with Exogenous Input (NARX) for Poorly Gauged Basins: Application to the Karkheh River Basin, Iran." Water 10, no. 7: 964.
Modeling the hydrologic responses to future changes of climate is important for improving adaptive water management. In the present application to the Zarrine River Basin (ZRB), with the major reach being the main inflow source of Lake Urmia (LU), firstly future daily temperatures and precipitation are predicted using two statistical downscaling methods: the classical statistical downscaling model (SDSM), augmented by a trend-preserving bias correction, and a two-step updated quantile mapping (QM) method. The general circulation models (GCM) input to SDSM are climate predictors of the Canadian Earth System Model (CanESM2) GCM under the representative concentration pathway (RCP) emission scenarios, RCP45 and RCP85, whereas that to the QM is provided by the most suitable of several Climate Model Intercomparison Project Phase 5 (CMIP5) GCMs under RCP60, in addition. The performances of the two downscaling methods are compared to each other for a past “future” period (2006–2016) and the QM is found to be better and so is selected in the subsequent ZR streamflow simulations by means of the Soil and Water Assessment Tool (SWAT) hydrological model, calibrated and validated for the reference period (1991–2012). The impacts of climate change on the hydrologic response of the river basin, specifically the inflow to the Boukan Reservoir, the reservoir-dependable water release (DWR), are then compared for the three RCPs in the near- (2020–2038), middle- (2050–2068) and far- (2080–2098) future periods assuming (1) the “current” consumptive demand to be continued in the future, and (2) a more conservative “recommended” demand. A systematic future shortage of the available water is obtained for case (1) which can be mitigated somewhat for (2). Finally, the SWAT-predicted ZRB outflow is compared with the Montana-based estimated environmental flow of the ZR. The latter can successfully be sustained at good and fair levels for the near- and middle-future periods, but not so for the summer months of the far-future period, particularly, for RCP85.
Farzad Emami; Manfred Koch. Evaluation of Statistical-Downscaling/Bias-Correction Methods to Predict Hydrologic Responses to Climate Change in the Zarrine River Basin, Iran. Climate 2018, 6, 30 .
AMA StyleFarzad Emami, Manfred Koch. Evaluation of Statistical-Downscaling/Bias-Correction Methods to Predict Hydrologic Responses to Climate Change in the Zarrine River Basin, Iran. Climate. 2018; 6 (2):30.
Chicago/Turabian StyleFarzad Emami; Manfred Koch. 2018. "Evaluation of Statistical-Downscaling/Bias-Correction Methods to Predict Hydrologic Responses to Climate Change in the Zarrine River Basin, Iran." Climate 6, no. 2: 30.
Samui island in southern Thailand has become an increasingly attractive tourist spot over the last decades. However, the enormous numbers of tourists has led to deficits of the available water resources, mainly surface water stored in a few reservoirs across the island during the dry season of the year, which is also the main tourist season. The Department of Groundwater Resources (DGR) has been aware of this problem and initialized a project of underground dam construction which is supposed to impede the natural groundwater outflow toward the sea and, hence, to increase the usable groundwater storage on Samui island during the dry season. The dam will be initially designed as two impermeable underground-walls amid the two rock-gorges that cut through the three layers of the aquifer system, reaching down to a maximum depth of about 50 m. A top of the 2 m wide dam which ends below the upper unconfined aquifer layer, a vertical layer of high permeability will be specified, so that a “spillway-like” over-flow of the groundwater with only minor impacts on the subsurface ecology downstream toward the sea will be generated. Based on this conceptual model, a 3D-variable density groundwater flow and transport model has been set up and calibrated in both steady and transient modes. In the subsequent modeling analysis the underground dam with the above spillway characteristics has been embedded into the model by specifying the corresponding vertical curtains of low and high conductivity, respectively. Finally, groundwater pumps upstream of the underground dams have been included into the model. Simulations without and with the hydraulic structures have been performed to ascertain the differences with respect to groundwater levels and storage and to evaluate the overall functionality of the underground dam. The results show that the underground dam is able to raise groundwater levels, that is, groundwater storage. The budget analysis of the simulation sets indicates that the underground dams serve well their purpose, particularly, for long dry spells, as more groundwater can be pumped out than would be possible without such a hydraulic structure. Finally, analyses of the seawater intrusion problem based on (1) the Ghyben-Herzberg formula, (2) analytical solutions of the sharp interface problem under Dupuit’s assumption, and (3) using the density-dependent SEAWAT – flow and solute transport modeling of the transition zone have been carried out. Differences in the landward extensions of the seawater intrusion fronts for the analytical and numerical solutions are found; however, the general predictions of the analytical theory are supported by the SEAWAT model in general, that is, a landward progression of the seawater intrusion front for pumping conditions and a partly retreat again in the presence of the two underground dams. In any case, seawater intrusion in the coastal zone of the study region does not extend deep enough inland to adversely...
Phatcharasak Arlai; Manfred Koch. Density-dependent numerical simulations of the impact of underground dams on groundwater storage on Samui island, Thailand. Journal of Applied Water Engineering and Research 2016, 5, 1 -15.
AMA StylePhatcharasak Arlai, Manfred Koch. Density-dependent numerical simulations of the impact of underground dams on groundwater storage on Samui island, Thailand. Journal of Applied Water Engineering and Research. 2016; 5 (2):1-15.
Chicago/Turabian StylePhatcharasak Arlai; Manfred Koch. 2016. "Density-dependent numerical simulations of the impact of underground dams on groundwater storage on Samui island, Thailand." Journal of Applied Water Engineering and Research 5, no. 2: 1-15.
A vital key to the development of a reservoir eutrophication management strategy is to link the watershed-nutrient model to the model of reservoir water quality. To develop a cost-effective optimization model, a coupled watershed-reservoir model with an optimization model has been developed to design control strategies in the watershed in a planning time horizon. This methodology can help reduce the phosphorus concentration of a reservoir to the standard level. In this study, the weather data for the next 10 years was generated using downscaled GCM data to simulate the watershed phosphorus load using the SWAT model. Then an optimal model for selection and placement of best management practices (BMP) at watershed scale is developed by linking the coupled watershed and reservoir models with a genetic algorithm. This model is able to identify the minimum present cost design (type and location) of BMP structural alternatives. The objective of water quality is obtained using a system dynamic model for reservoir phosphorus concentration to determine a permissible phosphorus load as the main agent of eutrophication in a reservoir. Structural BMPs in this study include, filter strips, parallel terraces, grade stabilization structures, and detention ponds. The optimum solution was obtained through a trade-off curve between cost and exceedance magnitude from the standard of reservoir phosphorus concentration. The case study is the Aharchai River Watershed upstream of the Satarkhan Reservoir in the northwestern part of Iran.
Mohammad Karamouz; Masoud Taheriyoun; Akbar Baghvand; Hamed Tavakolifar; Farzad Emami. Optimization of Watershed Control Strategies for Reservoir Eutrophication Management. Journal of Irrigation and Drainage Engineering 2010, 136, 847 -861.
AMA StyleMohammad Karamouz, Masoud Taheriyoun, Akbar Baghvand, Hamed Tavakolifar, Farzad Emami. Optimization of Watershed Control Strategies for Reservoir Eutrophication Management. Journal of Irrigation and Drainage Engineering. 2010; 136 (12):847-861.
Chicago/Turabian StyleMohammad Karamouz; Masoud Taheriyoun; Akbar Baghvand; Hamed Tavakolifar; Farzad Emami. 2010. "Optimization of Watershed Control Strategies for Reservoir Eutrophication Management." Journal of Irrigation and Drainage Engineering 136, no. 12: 847-861.