Your search found 11 records
1 Akhtar, F.; Tischbein, B.; Awan, Usman Khalid. 2013. Optimizing deficit irrigation scheduling under shallow groundwater conditions in lower reaches of Amu Darya River Basin. Water Resources Management, 27(8):3165-3178. [doi: https://doi.org/10.1007/s11269-013-0341-0]
Irrigation scheduling ; Water scarcity ; River basins ; Irrigated farming ; Irrigation water ; Groundwater table ; Water supply ; Crop yield ; Cotton ; Models ; Evapotranspiration / Central Asia / Uzbekistan / Khorezm Region / Amu Darya River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H045846)
(0.23 MB)
Water demand for irrigated agriculture is increasing against limited availability of fresh water resources in the lower reaches of the Amu Darya River e.g., Khorezm region of Uzbekistan. Future scenarios predict that Khorezm region will receive fewer water supplies due to climate change, transboundary conflicts and hence farmers have to achieve their yield targets with less water. We conducted a study and used AquaCrop model to develop the optimum and deficit irrigation schedule under shallow groundwater conditions (1.0–1.2 m) in the study region. Cotton being a strategic crop in the region was used for simulations. Capillary rise substantially contributes to crop-water requirements and is the key characteristic of the regional soils. However, AquaCrop does not simulate capillary rise contribution, thereby HYDRUS-1D model was used in this study for the quantification of capillary rise contribution. Alongside optimal irrigation schedule for cotton, deficit strategies were also derived in two ways: proportional reduction from each irrigation event (scenario-A) throughout the growth period as well as reduced water supply at specific crop growth stages (scenario-B). For scenario-A, 20, 40, 50 and 60 % of optimal water was deducted from each irrigation quota whereas for scenario-B irrigation events were knocked out at different crop growth stages (stage 1(emergence), stage 2 (vegetative), stage 3 (flowering) and stage 4 (yield formation and ripening)). For scenario-A, 0, 14, 30 and 48 % of yield reduction was observed respectively. During stress at the late crop development stage, a reduced water supply of 12 % resulted in a yield increase of 8 %. Conversely, during stress at the earlier crop development stage, yield loss was 17–18 %. During water stress at the late ripening stage, no yield loss was observed. Results of this study provide guidelines for policy makers to adopt irrigation schedule depending upon availability of irrigation water.
2 Awan, Usman Khalid; Tischbein, B.; Martius, C. 2013. Combining hydrological modeling and GIS approaches to determine the spatial distribution of groundwater recharge in an arid irrigation scheme. Irrigation Science, 31(4):793-806. [doi: https://doi.org/10.1007/s00271-012-0362-0]
Groundwater recharge ; Water balance ; Models ; GIS ; Remote sensing ; Irrigation schemes ; Irrigation efficiency ; Water user associations ; Cropping patterns ; Evapotranspiration / Uzbekistan
(Location: IWMI HQ Call no: PER Record No: H045847)
(0.48 MB)
Accurate quantification of the rate of groundwater (GW) recharge, a pre-requisite for the sustainable management of GW resources, needs to capture complex processes, such as the upward flow of water under shallow GW conditions, which are often disregarded when estimating recharge at a larger scale. This paper provides (1) a method to determine GW recharge at the field level, (2) a consequent procedure for up-scaling these findings from field to irrigation scheme level and (3) an assessment of the impacts of improved irrigation efficiency on the rate of GW recharge. The study is based on field data from the 2007 growing season in a Water Users Association (WUA Shomakhulum) in Khorezm district of Uzbekistan, Central Asia, an arid region that is characterized by a predominance of cotton, wheat and rice under irrigation. Previous qualitative studies in the region reported irrigation water supplies far above the crop water requirements, which cause GW recharge. A field water balance model was adapted to the local irrigation scheme; recharge was considered to be a fraction of the irrigation water losses, determined as the difference between net and gross irrigation requirements. Capillary rise contribution from shallow GW levels was determined with the HYDRUS-1D model. Six hydrological response units (HRUs) were created based on GW levels and soil texture using GIS and remote sensing techniques. Recharge calculated at the field level was up-scaled first to these HRUs and then to the whole WUA. To quantify the impact of improved irrigation efficiency on recharge rates, four improved irrigation efficiency scenarios were developed. The area under cotton had the second highest recharge (895 mm) in the peak irrigation period, after rice with 2,514 mm. But with a low area share of rice in the WUA of <1 %, rice impacted the total recharge only marginally. Due to the higher recharge rates of cotton, which is grown on about 40 % of the cropped area, HRUs with a higher share of cotton showed higher recharge (9.6 mm day-1 during August) than those with a lower share of cotton (4.4 mm day-1). The high recharge rates in the cotton fields were caused by its water requirements and the special treatment given to this crop by water management planners due to its strategic importance in the country. The scenario simulations showed that seasonal recharge under improved irrigation efficiency could potentially be reduced from 4 mm day-1 (business-as-usual scenario) to 1.4 mm day-1 (scenario with maximum achievable efficiency). The combination of field-level modeling/monitoring and GIS approaches improved recharge estimates because spatial variability was accounted for, which can assist water managers to assess the impact of improved irrigation efficiencies on groundwater recharge. This impact assessment enables managers to identify options for a recharge policy, which is an important component of integrated management of surface and groundwater resources.
3 Tischbein, B.; Manschadi, A. M.; Conrad, C.; Hornidge, A.-K.; Bhaduri, A.; Ul Hassan, M.; Lamers, J. P. A.; Awan, Usman Khalid; Vlek, P. L. G. 2013. Adapting to water scarcity: constraints and opportunities for improving irrigation management in Khorezm, Uzbekistan. Water Science and Technology: Water Supply, 13(2):337-348. [doi: https://doi.org/10.2166/ws.2013.028]
Water management ; Water scarcity ; Surface water ; Groundwater resources ; Irrigation management ; Irrigation scheduling ; River basins ; Rice ; Salinity control ; Soil water ; Soil moisture ; Vegetation ; Institutions / Uzbekistan / Khorezm
(Location: IWMI HQ Call no: e-copy only Record No: H045861)
(0.36 MB)
Like many irrigation schemes in Central Asia, the one in Khorezm faces a two-fold challenge: on the one side, the severe problems inherited from the past need to be remedied and on the other side, the rising supply–demand gap driven by sharpening competition for water and climate change must be dealt with. Located in the lower part of the Amu Darya basin, Khorezm irrigation and drainage scheme is particularly vulnerable to supply–demand gaps. Promising solutions towards adaptation comprise modified strategies of land and water use towards higher efficiency and flexibility in combination with measures to lessen the constraints of the system itself, which was initially designed for the management of a few, large and uniform production units and not for many diverse and small units. Solutions consist of flexible, modeling-based approaches, re-arranging institutional settings and establishing economic incentive systems. Flexible modeling allows an integrated use of surface and groundwater resources avoiding or minimizing the impact of water stress on yield. Institutional settings strengthen the position of water users via improved participation and transparency of processes in Water Consumers Associations (WCAs). Economic measures support sustainable resource use strategies and improve the functioning of WCAs. The findings could be extrapolated to other regions of Central Asia with similar conditions and challenges.
4 Ali, S.; Cheema, M. J. M.; Waqas, M. M.; Waseem, M.; Awan, Usman Khalid; Khaliq, T. 2020. Changes in snow cover dynamics over the Indus Basin: evidences from 2008 to 2018 MODIS NDSI trends analysis. Remote Sensing, 12(17):2782. (Special issue: Interactive Deep Learning for Hyperspectral Images) [doi: https://doi.org/10.3390/rs12172782]
Snow cover ; Estimation ; Mapping ; Trends ; River basins ; Catchment areas ; Temperature ; Clouds ; Landsat ; Satellite imagery ; Moderate resolution imaging spectroradiometer ; Uncertainty / Pakistan / Indus Basin / Himalayas / Chenab River Catchment / Jhelum River Catchment / Indus River Catchment / Eastern Rivers Catchment
(Location: IWMI HQ Call no: e-copy only Record No: H050209)
(4.20 MB) (4.20 MB)
The frozen water reserves on the Earth are not only very dynamic in their nature, but also have significant effects on hydrological response of complex and dynamic river basins. The Indus basin is one of the most complex river basins in the world and receives most of its share from the Asian Water Tower (Himalayas). In such a huge river basin with high-altitude mountains, the regular quantification of snow cover is a great challenge to researchers for the management of downstream ecosystems. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) daily (MOD09GA) and 8-day (MOD09A1) products were used for the spatiotemporal quantification of snow cover over the Indus basin and the western rivers’ catchments from 2008 to 2018. The high-resolution Landsat Enhanced Thematic Mapper Plus (ETM+) was used as a standard product with a minimum Normalized Difference Snow Index (NDSI) threshold (0.4) to delineate the snow cover for 120 scenes over the Indus basin on different days. All types of errors of commission/omission were masked out using water, sand, cloud, and forest masks at different spatiotemporal resolutions. The snow cover comparison of MODIS products with Landsat ETM+, in situ snow data and Google Earth imagery indicated that the minimum NDSI threshold of 0.34 fits well compared to the globally accepted threshold of 0.4 due to the coarser resolution of MODIS products. The intercomparison of the time series snow cover area of MODIS products indicated R2 values of 0.96, 0.95, 0.97, 0.96 and 0.98, for the Chenab, Jhelum, Indus and eastern rivers’ catchments and Indus basin, respectively. A linear least squares regression analysis of the snow cover area of the Indus basin indicated a declining trend of about 3358 and 2459 km2 per year for MOD09A1 and MOD09GA products, respectively. The results also revealed a decrease in snow cover area over all the parts of the Indus basin and its sub-catchments. Our results suggest that MODIS time series NDSI analysis is a useful technique to estimate snow cover over the mountainous areas of complex river basins.
5 Waqas, M. M.; Shah, S. H. H.; Awan, Usman Khalid; Waseem, M.; Ahmad, I.; Fahad, M.; Niaz, Y.; Ali, S. 2020. Evaluating the impact of climate change on water productivity of maize in the semi-arid environment of Punjab, Pakistan. Sustainability, 12(9):3905. (Special issue: Climate Resilient Sustainable Agricultural Production Systems) [doi: https://doi.org/10.3390/su12093905]
Climate change ; Impact assessment ; Water productivity ; Crop production ; Maize ; Semiarid zones ; Soil hydraulic properties ; Groundwater recharge ; Irrigation systems ; Precipitation ; Temperature ; Rain ; Models / Pakistan / Punjab / Lower Chenab Canal system
(Location: IWMI HQ Call no: e-copy only Record No: H050210)
(1.37 MB) (1.37 MB)
Impact assessments on climate change are essential for the evaluation and management of irrigation water in farming practices in semi-arid environments. This study was conducted to evaluate climate change impacts on water productivity of maize in farming practices in the Lower Chenab Canal (LCC) system. Two fields of maize were selected and monitored to calibrate and validate the model. A water productivity analysis was performed using the Soil–Water–Atmosphere–Plant (SWAP) model. Baseline climate data (1980–2010) for the study site were acquired from the weather observatory of the Pakistan Meteorological Department (PMD). Future climate change data were acquired from the Hadley Climate model version 3 (HadCM3). Statistical downscaling was performed using the Statistical Downscaling Model (SDSM) for the A2 and B2 scenarios of HadCM3. The water productivity assessment was performed for the midcentury (2040–2069) scenario. The maximum increase in the average maximum temperature (Tmax) and minimum temperature (Tmin) was found in the month of July under the A2 and B2 scenarios. The scenarios show a projected increase of 2.8 C for Tmax and 3.2 C for Tmin under A2 as well as 2.7 C for Tmax and 3.2 C for Tmin under B2 for the midcentury. Similarly, climate change scenarios showed that temperature is projected to decrease, with the average minimum and maximum temperatures of 7.4 and 6.4 C under the A2 scenario and 7.7 and 6.8 C under the B2 scenario in the middle of the century, respectively. However, the highest precipitation will decrease by 56 mm under the A2 and B2 scenarios in the middle of the century for the month of September. The input and output data of the SWAP model were processed in R programming for the easy working of the model. The negative impact of climate change was found under the A2 and B2 scenarios during the midcentury. The maximum decreases in Potential Water Productivity (WPET) and Actual Water Productivity (WPAI) from the baseline period to the midcentury scenario of 1.1 to 0.85 kgm-3 and 0.7 to 0.56 kgm-3 were found under the B2 scenario. Evaluation of irrigation practices directs the water managers in making suitable water management decisions for the improvement of water productivity in the changing climate.
6 Ali Nawaz, Rana; Awan, Usman Khalid; Anjum, L.; Liaqat, Umar Waqas. 2021. A novel approach to analyze uncertainties and complexities while mapping groundwater abstractions in large irrigation schemes. Journal of Hydrology, 596:126131. [doi: https://doi.org/10.1016/j.jhydrol.2021.126131]
Groundwater extraction ; Mapping ; Estimation ; Irrigation schemes ; Large scale systems ; Water supply ; Water use ; Canals ; Tube wells ; Evapotranspiration ; Rain ; Energy balance ; Remote sensing ; Uncertainty / Pakistan / Indus Basin / Punjab / Lower Bari Doab Canal
(Location: IWMI HQ Call no: e-copy only Record No: H050314)
(3.56 MB)
While determining the water balance for large irrigation schemes, coping with complexities and uncertainties in estimation of groundwater (GW) abstraction is still a challenge. On other hand, estimating GW abstraction is of paramount importance to ensure the proper management of surface and GW resources. Although, there are number of well-known methods exist to map GW abstraction, utilization-factor (Uf) is considered as a reliable method. However, at large scales, tubewells utilization time required for Uf method is difficult to retrieve as large and small tubewells are governed under different rules. Geo-informatics is another emerging approach being used to estimate GW abstraction, however, there are several complexities and uncertainties involved in characterizing GW abstraction using satellite remote sensing imagery that leads to inaccurate end results. In current study, in-situ GW measurements were performed to calibrate and validate the GW abstraction estimated from geo-informatics approach at Lower Bari Doab Canal (LBDC) command area of the Indus basin of Pakistan. For in-situ measurements, an intensive tubewell survey was conducted at a grid size of 1 km at 30 locations situated at head, middle and tail end reaches of the LBDC. For the geo-informatics approach used in this study, GW abstraction is considered as a difference of actual evapotranspiration (ETa) from net canal water use and effective rainfall after satisfying soil moisture storage changes. Results of calibration of geo-informatics approach compared with the in-situ measurements showed R2 of 0.89, 0.81 and 0.79 at head, middle and tail end reaches, respectively. Intra-grid annual comparison of in-situ measurements showed that tubewells were being governed by different rules and thus yielded different abstraction within a grid ranging from 854 mm (±105) at head, 742 mm (±220) at middle and 649 mm (±244) at tail grids. Statistical analysis showed that annual GW abstraction by in-situ measurements at head 814 mm (±52), middle 769 mm (±44) and tail 688 mm (±56) end reaches varied significantly at a confidence interval of 95%. The spatial mapping by geo-informatics showed that farmers’ fields situated at proximity of head end reaches utilize 4% and 9% extra water than from those placed at middle and tail end reaches, respectively. The inequity of GW abstraction in LBDC command area highlighted in this study requires immediate intervention of policy makers for sustainable GW management.
7 Akhtar, F.; Nawaz, R. A.; Hafeez, Mohsin; Awan, Usman Khalid; Borgemeister, C.; Tischbein, B. 2022. Evaluation of GRACE derived groundwater storage changes in different agro-ecological zones of the Indus Basin. Journal of Hydrology, 605:127369. [doi: https://doi.org/10.1016/j.jhydrol.2021.127369]
Groundwater depletion ; Water storage ; Agroecological zones ; River basins ; Water extraction ; Aquifers ; Precipitation ; Trends ; Satellite observation / Pakistan / Afghanistan / Indus Basin / Kabul River Basin / Lower Bari Doab Canal
(Location: IWMI HQ Call no: e-copy only Record No: H050895)
(4.45 MB)
The Gravity Recovery and Climate Experiment (GRACE) has recently been identified as a useful tool for monitoring changes in groundwater storage (GWS), especially in areas with sparse groundwater monitoring networks. However, GRACE’s performance has not been evaluated in the highly heterogeneous Indus Basin (IB) to date. The objective of this study was thus (i) to evaluate GRACE’s performance in two distinctively different agroecological zones of the IB, and (ii) to quantify the trend of groundwater abstraction over 15 years (i.e., from 2002 to 2017). To capture this heterogeneity at the IB, the two different agro-ecological zones were selected: i) the Kabul River Basin (KRB), Afghanistan, and ii) the Lower Bari Doab Canal (LBDC) command area in Pakistan. The groundwater storage anomalies (GWSA) for both regions were extracted from random pixels. The results show a correlation (R2 ) of 0.46 for LBDC and 0.32 for the KRB, between the GWSA and in-situ measurements. The results further reveal a mean annual depletion in GWSA of - 304.2 ± 749 and - 301 ± 527 mm at the LBDC and the KRB, respectively. Overall, a net GWS depletion during 2002–2017 at the LBDC and KRB was 4.87 and 4.82 m, respectively. The GWSA’s response to precipitation analyzed through cross-correlation shows a lag of 4 and 3 months at the KRB and the LBDC, respectively. The GWSA’s poor correlation with the in-situ measurements particularly in the mountainous region of the KRB is driven by the 4 months lag time unlike in the LBDC (i.e. 3 months); besides, the observations wells are sparse and limited. The complex geomorphology and slope of the landscape also cause discrepancies in the correlation of the in-situ measurements and the GRACE-derived changes in GWS at the two different agroecological zones of the IB. The spatially averaged GWSA in monthly time steps is another reason for the lower correlation between GRACE-based GWSA estimates and point-based in-situ measurements. Therefore, care must be taken while using GRACE’s output in regions with heterogeneous geomorphologic features.
8 Akhtar, F.; Awan, Usman Khalid; Borgemeister, C.; Tischbein, B. 2021. Coupling remote sensing and hydrological model for evaluating the impacts of climate change on streamflow in data-scarce environment. Sustainability, 13(24):14025. [doi: https://doi.org/10.3390/su132414025]
Climate change ; Remote sensing ; Hydrological modelling ; Forecasting ; River basins ; Stream flow ; Water resources ; Precipitation ; Land use ; Land cover ; Soil types ; Calibration / Afghanistan / Kabul River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H050783)
(6.38 MB) (6.38 MB)
The Kabul River Basin (KRB) in Afghanistan is densely inhabited and heterogenic. The basin’s water resources are limited, and climate change is anticipated to worsen this problem. Unfortunately, there is a scarcity of data to measure the impacts of climate change on the KRB’s current water resources. The objective of the current study is to introduce a methodology that couples remote sensing and the Soil and Water Assessment Tool (SWAT) for simulating the impact of climate change on the existing water resources of the KRB. Most of the biophysical parameters required for the SWAT model were derived from remote sensing-based algorithms. The SUFI-2 technique was used for calibrating and validating the SWAT model with streamflow data. The stream-gauge stations for monitoring the streamflow are not only sparse, but the streamflow data are also scarce and limited. Therefore, we selected only the stations that are properly being monitored. During the calibration period, the coefficient of determination (R2) and Nash–Sutcliffe Efficiency (NSE) were 0.75–0.86 and 0.62–0.81, respectively. During the validation period (2011–2013), the NSE and R2 values were 0.52–0.73 and 0.65–0.86, respectively. The validated SWAT model was then used to evaluate the potential impacts of climate change on streamflow. Regional Climate Model (RegCM4-4) was used to extract the data for the climate change scenarios (RCP 4.5 and 8.5) from the CORDEX domain. The results show that streamflow in most tributaries of the KRB would decrease by a maximum of 5% and 8.5% under the RCP 4.5 and 8.5 scenarios, respectively. However, streamflow for the Nawabad tributary would increase by 2.4% and 3.3% under the RCP 4.5 and 8.5 scenarios, respectively. To mitigate the impact of climate change on reduced/increased surface water availability, the SWAT model, when combined with remote sensing data, can be an effective tool to support the sustainable management and strategic planning of water resources. Furthermore, the methodological approach used in this study can be applied in any of the data-scarce regions around the world.
9 Hafeez, Mohsin; Awan, Usman Khalid. 2022. Viewpoint: irrigation water management in a space age. Irrigation and Drainage, 71(S1):39-50. (Special issue: Achieving Climate Resilience through Improved Irrigation Water Management from Farm to Basin Scale) [doi: https://doi.org/10.1002/ird.2705]
Irrigation water ; Water management ; Water resources ; Climate change ; Irrigation efficiency ; Groundwater ; River basins ; Irrigation schemes ; Evapotranspiration ; Precipitation ; Soil moisture ; Remote sensing / Australia / Pakistan / Uzbekistan / Amu Darya River Basin / Indus Basin / Murray Darling Basin
(Location: IWMI HQ Call no: e-copy only Record No: H051022)
(3.16 MB) (3.16 MB)
Climate change and rapid population growth are already putting increasing demand and pressure on the world's freshwater resources. Irrigated agriculture is responsible for about 70% of global freshwater withdrawals, consuming the most amount of water. However, the diverted water in irrigation systems is often not utilized efficiently because of poor water management at different spatial scales, resulting in a system efficiency of only 30–50% in most Asian countries. Typically, improving water management in irrigated areas requires accurate information on various water balance parameters while also considering a changing climate across different spatial scales. There have been technical limitations in getting accurate and reliable information on various key water balance parameters with the conventional approaches used in the recent past. In the twenty-first century, considerable advances have been made in using satellite imagery, including processing and geospatial algorithms, to estimate hydro-meteorological fluxes and relevant components at different spatial scales. This paper provides a perspective on the application of innovative and non-conventional approaches to water resources management in the Murray Darling basin, Australia, the Indus basin, Pakistan and the Amu Darya basin, Uzbekistan. Examples of the state-of-the-art tools described in this paper include: (i) using geoinformatics to monitor the diagnostic and operational performance of large irrigation schemes; (ii) quantifying groundwater and surface water to better manage these two resources using geoinformatics; (iii) forecasting irrigation supply and demand at high spatial and temporal scales using hydrological modelling based on the nodal network; (iv) forecasting crop yield production by satellite remote sensing. The approaches in this study clearly demonstrate that new monitoring and planning tools and methods are highly effective in improving irrigation water management in the ‘space age’ (for the purposes of this paper, space age refers to a period in which earth observation satellites are available to accurately monitor agricultural practices and water balance parameters such as soil moisture and evapotranspiration). The application of these innovative tools can assist in strategizing, diagnosing, monitoring and improving the performance of irrigation systems to grow more crop per drop of water while minimizing environmental impacts and dealing with climate change impacts.
10 Waqas, M. M.; Waseem, M.; Ali, S.; Hopman, J. W.; Awan, Usman Khalid; Shah, S. H. H.; Shah, A. N. 2022. Capturing spatial variability of factors affecting the water allocation plans—a geo-informatics approach for large irrigation schemes. Environmental Science and Pollution Research, 29(54):81418-81429. [doi: https://doi.org/10.1007/s11356-022-20912-9]
Irrigation schemes ; Water allocation ; Plans ; Spatial variation ; Geostatistics ; Geographical information systems ; Remote sensing ; Irrigation water ; Cropping patterns ; Soil texture ; Soil salinity ; Groundwater level ; Water quality ; Irrigation systems ; Canals / Pakistan / Indus Basin Irrigation System / Lower Chenab Canal Irrigation Scheme
(Location: IWMI HQ Call no: e-copy only Record No: H051314)
(1.81 MB)
The livelihoods of poor people living in rural areas of Indus Basin Irrigation System (IBIS) of Pakistan depend largely on irrigated agriculture. Water duties in IBIS are mainly calculated based on crop-specific evapotranspiration. Recent studies show that ignoring the spatial variability of factors affecting the crop water requirements can affect the crop production. The objective of the current study is thus to identify the factors which can affect the water duties in IBIS, map these factors by GIS, and then develop the irrigation response units (IRUs), an area representing the unique combinations of factors affecting the gross irrigation requirements (GIR). The Lower Chenab Canal (LCC) irrigation scheme, the largest irrigation scheme of the IBIS, is selected as a case. Groundwater quality, groundwater levels, soil salinity, soil texture, and crop types are identified as the main factors for IRUs. GIS along with gamma design software GS + was used to delineate the IRUs in the large irrigation scheme. This resulted in a total of 84 IRUs in the large irrigation scheme based on similar biophysical factors. This study provided the empathy of suitable tactics to increase water management and productivity in LCC. It will be conceivable to investigate a whole irrigation canal command in parts (considering the field-level variations) and to give definite tactics for management.
11 Akhtar, F.; Borgemeister, C.; Tischbein, B.; Awan, Usman Khalid. 2022. Metrics assessment and streamflow modeling under changing climate in a data-scarce heterogeneous region: a case study of the Kabul River Basin. Water, 14(11):1697. [doi: https://doi.org/10.3390/w14111697]
Stream flow ; Modelling ; Climate change ; River basins ; Case studies ; Watersheds ; Soil water content ; Land use ; Land cover ; Temperature ; Parameters / Afghanistan / Kabul River Basin / Alingar Watershed
(Location: IWMI HQ Call no: e-copy only Record No: H051380)
https://www.mdpi.com/2073-4441/14/11/1697/pdf?version=1653561387
https://vlibrary.iwmi.org/pdf/H051380.pdf
https://vlibrary.iwmi.org/pdf/H051380.pdf
(2.75 MB) (2.75 MB)
Due to many uncertainties in hydrological data and modeling, the findings are frequently regarded as unreliable, especially in heterogeneous catchments such as the Kabul River Basin (KRB). Besides, statistical methods to assess the performance of the models have also been called into doubt in several studies. We evaluated the performance of the Soil and Water Assessment Tool (SWAT) model by statistical indicators including the Kling-Gupta efficiency (KGE), Nash–Sutcliffe efficiency (NSE), and the coefficient of determination (R2 ) at single and multi-outlets in the KRB and assessed the streamflow under changing climate scenarios i.e., Representative Concentration Pathways (RCP) 4.5 and 8.5 (2020–2045). Because of the heterogeneous nature of the KRB, NSE and R 2 performed poorly at multi-outlets. However, the KGE, as the basic objective function, fared much better at singleoutlet. We conclude that KGE is the most crucial metric for streamflow evaluation in heterogeneous basins. Similarly, the mean and maximum annual streamflow is projected to decrease by 15.2–15.6% and 17.2–41.8% under the RCP 4.5 and 8.5, respectively.
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