Your search found 22 records
1 Patten, G. P.; Hussain, A.; Ali, S.. 1963. Analysis of seepage losses from unlined canals in the Punjab region of West Pakistan. Report prepared by the West Pakistan Water and Power Development Authority. 29p. (West Pakistan Water and Power Development Authority technical paper no.4)
(Location: IWMI-HQ Call no: 631.7.5 G730 PAT Record No: H0586)
2 Bennett, G. D.; Ata-Ur-Rehman; Sheik, A,; Ali, S.. 1967. Analysis of aquifer test in the Punjab region of West Pakistan. Washington, DC, USA: US. Government Printing Office. iv, 56p. (Geological Survey Water-Supply paper 1608-G)
(Location: IWMI-HQ Call no: 631.7.6.3 G730 BEN Record No: H0625)
3 Rehman, G.; Aslam, M.; Jehangir, W. A.; Ahmad, Mobin-ud -Din; Munawwar, H. Z.; Hussain, A.; Ali, N.; Ali, F.; Ali, S.. 1997. Salinity management alternatives for the Rechna Doab, Punjab, Pakistan. Volume 4 - Field data collection and processing. Lahore, Pakistan: International Irrigation Management Institute (IIMI). Pakistan National Program. xii, 59p. + appendices. (IWMI Pakistan Report R-021.4 / IIMI Pakistan Report R-021.4)
Irrigation management ; Soil salinity ; Agricultural development ; Water quality ; Data processing ; Groundwater ; Crop production ; Intensive cropping ; Models ; Farm surveys / Pakistan / Punjab / Rechna Doab
(Location: IWMI-HQ Call no: IIMI 631.7.5 G730 REH Record No: H009237)
(8.12 MB)
4 Asif, S.; Chemin, Y.; Ali, S.. 1997. Using GIS and RS to monitor and evaluate irrigation and drainage projects: example from IIMI Pakistan National Program. ITIS (Information Techniques for Irrigation Systems), 4(1):19-20.
Irrigation programs ; Drainage ; Monitoring ; Performance evaluation ; GIS ; Remote sensing / Pakistan
(Location: IWMI-HQ Call no: PER Record No: H021969)
(0.16 MB)
5 Alexandridis, T.; Asif, S.; Ali, S.. 1999. Water performance indicators using satellite imagery for the Fordwah Eastern Sadiqia (South) Irrigation and Drainage Project. Lahore, Pakistan: International Water Management Institute (IWMI). Pakistan National Program. vi, 16p. (IWMI Pakistan Report R-087) [doi: https://doi.org/10.3910/2009.518]
Irrigation programs ; Performance indexes ; Satellite surveys ; Water use ; Equity ; Evapotranspiration ; Indicators / Pakistan / Fordwah Eastern Sadiqia
(Location: IWMI-HQ Call no: IIMI 631.7.1 G730 ALE Record No: H024895)
(1.03MB)
6 Ali, S.; Singh, K. D.; Prasad, S. N. 2000. Watershed management: A strategy for conservation of natural resources and sustained bio-mass production. Indian Farming, 50(7):30-32, 53.
Watershed management ; Natural resources ; Rural development ; Villages ; Land development ; Development plans ; Constraints / India
(Location: IWMI-HQ Call no: P 5807 Record No: H028624)
7 Opadeyi, J.; Ali, S.. 2001. Towards a GIS-based Caribbean Land and Water Resources Information System (CLAWRIS) In Paul, C. L.; Opadeyi, J. (Eds.), Land and water resources management in the Caribbean - Proceedings of a conference held 2-4 October 2000 at Accra Beach Hotel, Barbados. St. Augustine, Trinidad and Tobago: Caribbean Agricultural Research and Development Institute. Land and Water Resources Network (CLAWRENET) of PROCICARIBE. pp.109-131.
GIS ; Information systems ; Databases ; Design ; Land management ; Water resource management ; Environmental effects ; Monitoring / Caribbean
(Location: IWMI-HQ Call no: 333.91 G310 PAU Record No: H030479)
8 Bastiaanssen, W. G. M.; Ali, S.. 2003. A new crop yield forecasting model based on satellite measurements applied across the Indus Basin, Pakistan. Agriculture, Ecosystems and Environment, 94:321-340.
(Location: IWMI-HQ Call no: IWMI 631.7.1 G730 BAS Record No: H031274)
(0.90 MB)
9 Ali, S.; Singh, K. D. 2003. Drought plannings for its mitigation. Indian Farming, 53(6):20-22.
(Location: IWMI-HQ Call no: P 6888 Record No: H034925)
10 Ahmad, M.; Ali, B.; Ali, S.; Aslam, M.; Babar, Q. R.; Haider, M. S.; Hussein, K.; Iftikhar, S.; Iqbal, A.; Khan, M. A.; Kuper, M.; Mehmood, K.; Pasha, M. A.; Ramzan, M.; Raza, R. A.; Razaq, A.; Riaz, A.; Samad, A.; Shah, Q. A.; Shauq, G. R.; Skogerboe, G. 1995. Training course: Field Calibration of Irrigation Structures, Fordwah Canal, Fordwah Eastern Sadiqia Irrigation and Drainage Project, Bahawalnagar, 28 May to 6 June, 1995 - Technical report. Lahore, Pakistan: International Irrigation Management Institute (IIMI). 92p. + annex.
Irrigation canals ; Open channels ; Flow control ; Calibrations ; Discharges ; Measurement ; Measuring instruments ; Velocity ; Training courses / Pakistan / Sutlej River / Fordwah Canal
(Location: IWMI HQ Call no: IIMI 631.7.1 G730 AHM Record No: H019737)
11 Ahmad, Mobin-ud -Din; Chemin, Y.; Asif, S.; Ali, S.. 1998. GIS metadata for an irrigation system, volume I: Chishtian Sub-Division. Lahore, Pakistan: International Irrigation Management Institute (IIMI). Pakistan National Program. 74p. (IWMI Pakistan Report R-065.1 / IIMI Pakistan Report R-065.1) [doi: https://doi.org/10.3910/2009.500]
GIS ; Satellite surveys ; Irrigation canals ; Distributary canals ; Watercourses ; Soil salinity ; Water table ; Tube wells ; Water quality / Pakistan / Chishtian Sub-Division
(Location: IWMI-HQ Call no: IIMI 631.7.1 G730 MOB Record No: H023382)
12 Ali, S.; Chemin, Y.; Asif, S.; Ahmad, Mobin-ud -Din. 1998. GIS metadata for an irrigation system, volume 2: selected watercourses within Chishtian Sub-Division. Lahore, Pakistan: International Irrigation Management Institute (IIMI). Pakistan National Program. 56p. (IWMI Pakistan Report R-065.2 / IIMI Pakistan Report R-065.2) [doi: https://doi.org/10.3910/2009.501]
GIS ; Satellite surveys ; Irrigation canals ; Distributary canals ; Watercourses ; Water allocation ; Cropping systems ; Tube wells / Pakistan / Chishtian Sub-Division
(Location: IWMI-HQ Call no: IIMI 631.7.1 G730 MOB Record No: H023383)
13 Amin, R.; Zaidi, M. B.; Bashir, S.; Khanani, R.; Nawaz, R.; Ali, S.; Khan, S. 2019. Microbial contamination levels in the drinking water and associated health risks in Karachi, Pakistan. Journal of Water, Sanitation and Hygiene for Development, 9(2):319-328. [doi: https://doi.org/10.2166/washdev.2019.147]
Drinking water ; Biological contamination ; Health hazards ; Public health ; Water quality ; Groundwater ; Water supply ; Water use ; Waterborne diseases ; Microbiological analysis ; Bacteriological analysis ; Coliform bacteria ; Faecal coliforms / Pakistan / Karachi
(Location: IWMI HQ Call no: e-copy only Record No: H049302)
(0.40 MB)
The current study aimed to assess the microbial quality of municipal (tap) and ground (borehole) water in Karachi, Pakistan. A health survey was also conducted to assess possible health risks of the drinking water. Fifty water samples (n = 25 each of tap and ground water) were collected from various locations of five administrative districts of Karachi for bacteriological analysis. In addition, a survey was conducted to assess the impact of drinking water on the health of city residents. Microbiological analysis results showed the presence of total coliform in 48 out of 50 (96%) tested samples. The total viable plate count at 37 °C was >200 CFU/ml in the majority of the collected samples which exceeded the permissible limit set by the World Health Organization (WHO) and the Pakistan Environmental Protection Agency. To evaluate the health risk of contaminated water, a total of 744 residents were interviewed. The information acquired from this field work revealed a high prevalence of waterborne diseases in the order of diarrhea and vomiting > skin problems > malaria > prolonged fever > eye problems and jaundice. To solve water and environmental problems, awareness and regular monitoring programs of water management and safe disposal of waste have been suggested.
14 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.
15 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.
16 Nazeer, A.; Waqas, M. M.; Ali, S.; Awan, U. K.; Cheema, M. J. M.; Baksh, A. 2020. Land use land cover classification and wheat yield prediction in the Lower Chenab Canal System using remote sensing and GIS. Big Data In Agriculture, 2(2):47-51. [doi: https://doi.org/10.26480/bda.02.2020.47.51]
Crop yield ; Forecasting ; Wheat ; Land use ; Land cover ; Normalized difference vegetation index ; Remote sensing ; Geographical information systems ; Landsat ; Satellite imagery ; Canals / Pakistan / Lower Chenab Canal System / Khurrian Wala Distributary / Killian Wala Distributary / Mungi Distributary
(Location: IWMI HQ Call no: e-copy only Record No: H050212)
https://bigdatainagriculture.com/paper/issue2%202020/2bda2020-47-51.pdf
https://vlibrary.iwmi.org/pdf/H050212.pdf
https://vlibrary.iwmi.org/pdf/H050212.pdf
(1.40 MB) (1.40 MB)
Reliable and timely information regarding area under wheat and its yield prediction can help in better management of the commodity. The remotely sensed data especially in combination with Geographic Information System (GIS) can provide an important and powerful tool for both, land use land cover (LULC) classification and crop yield prediction. The study objectives include LULC classification and wheat yield prediction. The study was conducted for Rabi Season from Nov. 2011 to April 2012, in the command area of three distributaries i.e. Khurrian Wala, Killian Wala and Mungi of Lower Chennai Canal (LCC) system. The Landsat-7 imagery data with spatial resolution of 30 m was used for this study. Physical features were monitored and assessed using Normalized Difference Vegetative Index (NDVI). LULC classification was done for wheat and non-wheat area which shows wheat proportion and area 87.22% and 28867.95 Ha in Khurrian wala, 71.07% and 22423.20 Ha in Killian Wala and 79.18% and 17974.34 Ha in Mungi distributary, respectively. The correlation values between maximum NDVI value and yield data were 0.45, 0.36 and 0.39 for Khurrian Wala, Killian Wala and Mungi distributary, respectively. On the basis of this correlation, average wheat yield was estimated as 3.48 T/Ha, 3.83 T/Ha and 3.80 T/Ha for Khurrian Wala, Killian Wala and Mungi distributary, respectively.
17 Waqas, M. M.; Niaz, Y.; Ali, S.; Ahmad, I.; Fahad, M.; Rashid, H.; Awan, U. K. 2020. Soil salinity mapping using satellite remote sensing: a case study of Lower Chenab Canal System, Punjab. Earth Sciences Pakistan, 4(1):07-09. [doi: https://doi.org/10.26480/esp.01.2020.07.09]
Soil salinity ; Mapping ; Canals ; Irrigation schemes ; Satellite imagery ; Remote sensing ; Groundwater ; Landsat ; Normalized difference vegetation index ; Case studies / Pakistan / Punjab / Indus Basin / Lower Chenab Canal System
(Location: IWMI HQ Call no: e-copy only Record No: H050213)
https://earthsciencespakistan.com/archives/1esp2020/1esp2020-07-09.pdf
https://vlibrary.iwmi.org/pdf/H050213.pdf
https://vlibrary.iwmi.org/pdf/H050213.pdf
(0.31 MB) (318 KB)
Salinity is the most important factor of consideration for the water management policies. The water availability from the rootzone reduced with the increase in the soil salinity due to the increase in the osmatic pressure. In Pakistan, salinity is the major threat to the agriculture land due to the tradition practices of irrigation and extensive utilization of the groundwater to meet the cope the irrigation water requirement of high intensity cropping system. The salinity impact is spatially variable on the canal commands area of the irrigation system. There is dire need to map the spatially distributed soil salinity with the high resolution. Landsat satellite imagery provides an opportunity to have 30m pixel information in seven spectral wavelength ranges. In this study, the soil salinity mapping was performed using pixel information on visible and infrared bands for 2015. These bands were also used to infer Normalized Difference Vegetation Index (NDVI). The raw digital numbers were converted into soil salinity information. The accuracy assessment was carried out using ground trothing information obtained using the error matrix method. Four major classes of non-saline, marginal saline, moderate saline and strongly, saline area was mapped. The overall accuracy of the classified map was found 83%. These maps can be helpful to delineate hot spots with severe problem of soil salinity in order to prepare reciprocate measures for improvement.
18 Ali, S.; Liu, D.; Fu, Q.; Cheema, M. J. M.; Pham, Q. B.; Rahaman, Md. M.; Dang, T. D.; Anh, D. T. 2021. Improving the resolution of GRACE data for spatio-temporal groundwater storage assessment. Remote Sensing, 13(17):3513. (Special Issue: Remote Sensing and Modelling of Water Storage Dynamics from Bedrock to Atmosphere) [doi: https://doi.org/10.3390/rs13173513]
Groundwater assessment ; Water storage ; Irrigation systems ; Aquifers ; Groundwater table ; Soil moisture ; Evapotranspiration ; Runoff ; Models ; Satellites ; Neural networks / Pakistan / Sindh / Punjab / Indus Basin Irrigation System
(Location: IWMI HQ Call no: e-copy only Record No: H050649)
(9.12 MB) (9.12 MB)
Groundwater has a significant contribution to water storage and is considered to be one of the sources for agricultural irrigation; industrial; and domestic water use. The Gravity Recovery and Climate Experiment (GRACE) satellite provides a unique opportunity to evaluate terrestrial water storage (TWS) and groundwater storage (GWS) at a large spatial scale. However; the coarse resolution of GRACE limits its ability to investigate the water storage change at a small scale. It is; therefore; needed to improve the resolution of GRACE data at a spatial scale applicable for regional-level studies. In this study; a machine-learning-based downscaling random forest model (RFM) and artificial neural network (ANN) model were developed to downscale GRACE data (TWS and GWS) from 1° to a higher resolution (0.25°). The spatial maps of downscaled TWS and GWS were generated over the Indus basin irrigation system (IBIS). Variations in TWS of GRACE in combination with geospatial variables; including digital elevation model (DEM), slope; aspect; and hydrological variables; including soil moisture; evapotranspiration; rainfall; surface runoff; canopy water; and temperature; were used. The geospatial and hydrological variables could potentially contribute to; or correlate with; GRACE TWS. The RFM outperformed the ANN model and results show Pearson correlation coefficient (R) (0.97), root mean square error (RMSE) (11.83 mm), mean absolute error (MAE) (7.71 mm), and Nash–Sutcliffe efficiency (NSE) (0.94) while comparing with the training dataset from 2003 to 2016. These results indicate the suitability of RFM to downscale GRACE data at a regional scale. The downscaled GWS data were analyzed; and we observed that the region has lost GWS of about -9.54 ± 1.27 km3 at the rate of -0.68 ± 0.09 km3/year from 2003 to 2016. The validation results showed that R between downscaled GWS and observational wells GWS are 0.67 and 0.77 at seasonal and annual scales with a confidence level of 95%, respectively. It can; therefore; be concluded that the RFM has the potential to downscale GRACE data at a spatial scale suitable to predict GWS at regional scales.
19 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.
20 Ahmed, N.; Zhu, L.; Wang, G.; Adeyeri, O. E.; Shah, S.; Ali, S.; Marhaento, H.; Munir, Sarfraz. 2023. Occurrence and distribution of long-term variability in precipitation classes in the source region of the Yangtze River. Sustainability, 15(7):5834. (Special issue: Hydro-Meteorology and its Application in Hydrological Modeling) [doi: https://doi.org/10.3390/su15075834]
Climate change ; Precipitation ; Trends ; Rivers ; Rainfall ; Drought ; Time series analysis ; Hydrological factors ; Dry spells ; Vegetation / China / Yangtze River
(Location: IWMI HQ Call no: e-copy only Record No: H051888)
https://www.mdpi.com/2071-1050/15/7/5834/pdf?version=1679974417
https://vlibrary.iwmi.org/pdf/H051888.pdf
https://vlibrary.iwmi.org/pdf/H051888.pdf
(6.22 MB) (6.22 MB)
Various precipitation-related studies have been conducted on the Yangtze River. However, the topography and atmospheric circulation regime of the Source Region of the Yangtze River (SRYZ) differ from other basin parts. Along with natural uniqueness, precipitation constitutes over 60% of the direct discharge in the SRYZ, which depicts the decisive role of precipitation and a necessary study on the verge of climate change. The study evaluates the event distribution of long-term variability in precipitation classes in the SRYZ. The precipitation was classified into three precipitation classes: light precipitation (0–5 mm, 5–10 mm), moderate precipitation (10–15 mm, 15–20 mm, 20–25 mm), and heavy precipitation (>25 mm). The year 1998 was detected as a changing year using the Pettitt test in the precipitation time series; therefore, the time series was divided into three scenarios: Scenario-R (1961–2016), the pre-change point (Scenario-I; 1961–1998), and the post-change point (Scenario-II; 1999–2016). Observed annual precipitation amounts in the SRYZ during Scenario-R and Scenario-I significantly increased by 13.63 mm/decade and 48.8 mm/decade, respectively. The same increasing trend was evident in seasonal periods. On a daily scale, light precipitation (0–5 mm) covered most of the days during the entire period, with rainy days accounting for 83.50%, 84.5%, and 81.30%. These rainy days received up to 40%, 41%, and 38% of the annual precipitation during Scenario-R, Scenario-I, and Scenario-II, respectively. Consequently, these key findings of the study will be helpful in basin-scale water resources management.
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