Search Results (36)

The water regime in Pakistan’s northern region has experienced significant changes regarding hydrological extremes like floods because of climate change. Coupling hydrological models with remote sensing data can be valuable for flow simulation in data-scarce regions. This study focused on simulating the snow- and glacier-melt runoff using the snowmelt runoff model (SRM) in the Gilgit and Kachura River Basins of the upper Indus basin (UIB). The SRM was applied by coupling it with in situ and improved cloud-free MODIS snow and glacier composite satellite data (MOYDGL06) to simulate the flow under current and future climate scenarios. The SRM showed significant results: the Nash–Sutcliffe coefficient (NSE) for the calibration and validation period was between 0.93 and 0.97, and the difference in volume (between the simulated and observed flow) was in the range of −1.5 to 2.8% for both catchments. The flow tends to increase by 0.3–10.8% for both regions (with a higher increase in Gilgit) under mid- and late-21st-century climate scenarios. The Gilgit Basin’s higher hydrological sensitivity to climate change, compared to the Kachura Basin, stems from its lower mean elevation, seasonal snow dominance, and greater temperature-induced melt exposure. This study concludes that the simple temperature-based models, such as the SRM, coupled with improved satellite snow cover data, are reliable in simulating the current and future flows from the data-scarce mountainous catchments of Pakistan. The outcomes are valuable and can be used to anticipate and lessen any threat of flooding to the local community and the environment under the changing climate. This study may support flood assessment and mapping models in future flood risk reduction plans. Full article

Being an agricultural country, Pakistan requires lots of water for irrigation. A major portion of its water resources is located in the upper indus basin (UIB). The snowmelt runoff generated from high-altitude areas of the UIB provides inflow into the Indus river system that boosts the water supply. Snow accumulation during the winter period in the highlands in the watershed(s) becomes a source of water inflow during the snow-melting period, which is described according to characteristics like snow depth, snow density, and snow water equivalent. Snowmelt water release (SWE) and snowmelt water depth (SD) maps are generated by tracing snow occurrence from MODIS-based images of the snow-cover area, evaluating the heating degree days (HDDs) from MODIS-derived images of the land surface temperature, computing the solar radiation, and then assimilating all the previous data in the form of the snowmelt model and ground measurements of the snowmelt water release (SWE). The results show that the average snow-cover area in the Astore river basin, in the upper indus basin, ranges from 94% in winter to 20% in summer. The maps reveal that the annual average values of the SWE range from 150 mm to 535 mm, and the SD values range from 600 mm to 2135 mm, for the snowmelt period (April–September) over the years 2010–2020. The areas linked with vegetation experience low SWE accumulation because of the low slopes in the elevated regions. The meteorological parameters and basin characteristics affect the SWE and can determine the SD values. Full article

During the third millennium cal BC, the Indus communities exploited great quantities of chert from the Rohri Hills mines in Upper Sindh for making different types of artifacts. This paper discusses the way chert was transported to the Indus Civilization centers and the problems related to the type, quantity, and quality of raw material and artifacts that were transported, including when, why, and where. This paper raises the question of land and water transport. Both these methods were probably used according to the landscape location of the Indus sites. Another problem concerns the landscape characteristics of the Indus Valley during the Bronze Age before the climate changes that took place around the end of the third millennium cal BC and the disappearance of the Hakra River, which was an important watercourse during the Indus phase. What do we know of the way the Indus communities exploited, transported, and circulated knappable chert? Why have the Indus settlements excavated around the Rohri Hills, the largest chert mines of the Indian Subcontinent, yielded little evidence of chert artifacts and nodules? What do we know of this important problem, which is strictly related to the everyday life of the Indus communities and their economy? Why this problem has been systematically neglected by most archaeologists despite its importance? Full article

Snow and ice melting in the Upper Indus Basin (UIB) is crucial for regional water availability for mountainous communities. We analyzed glacier changes in the Astak catchment, UIB, from 2000 to 2020 using remote sensing techniques based on optical satellite images from Landsat and ASTER digital elevation models. We used a surface feature-tracking technique to estimate glacier velocity. To assess the impact of climate variations, we examined temperature and precipitation anomalies using ERA5 Land climate data. Over the past two decades, the Astak catchment experienced a slight decrease in glacier area (−1.8 km²) and the overall specific mass balance was −0.02 ± 0.1 m w.e. a⁻¹. The most negative mass balance of −0.09 ± 0.06 m w.e. a⁻¹ occurred at elevations between 2810 to 3220 m a.s.l., with a lesser rate of −0.015 ± 0.12 m w.e. a⁻¹ above 5500 m a.s.l. This variation in glacier mass balance can be attributed to temperature and precipitation gradients, as well as debris cover. Recent glacier mass loss can be linked to seasonal temperature anomalies at higher elevations during winter and autumn. Given the reliance of mountain populations on glacier melt, seasonal temperature trends can disturb water security and the well-being of dependent communities. Full article

Headwater in the Indus River in Pakistan is largely dependent on the glaciers located in the northern part of the country, along with other sources such as direct precipitation. Glaciers are a major source of freshwater that provides agriculture and livelihood to millions of people. The hydro-climatic variations in the Gilgit watershed of the Upper Indus basin are poorly investigated scientifically due to high topographical differences, geography, remoteness of the region, and larger variations in climatic conditions. These glaciers are continuously changing due to melting as a consequence of global warming or accumulation due to snowfall/precipitation at higher altitude regions. The study is carried out using remote sensing data to quantify glacier changes in spatiotemporal variability in the past three decades. Five glaciers in the Gilgit region (near the junction of the Hindukush and Karakoram Mountains) with an area of more than 5 square kilometers were selected, namely Phakor, Karamber, East Gammu, Bhort, and Bad-e-Swat glaciers. These glaciers were monitored for changes in their sizes through a cloud-free continuous series of Landsat satellite imagery. The annual climatic trends were studied through spatially interpolated gridded climate data WοrldClim version-1 climate database for 1970–2000, utilized for assessment of meteorological condition by analyzing the variations of minimum and maximum temperature, solar radiation, and precipitation. The temporal variations in five glaciers in the Gilgit watershed are found to be minimal and, thus, are rather stable and show no sign of rapid melting or diminishing. The little variability of glaciers’ extent may be attributed to their geographic condition, altitude, topography, and orientation. The mapped glacier classes have been validated to check the accuracy assessment through an error matrix method. The kappa coefficient from the error matrix has been calculated as 84%, which shows a good agreement. The study makes a critical input towards understanding the dynamics of the glacier in the upper Indus catchment’s Gilgit watershed. Full article

The potential impacts of climate change on water resources in the Upper Indus Basin of Pakistan, a region heavily reliant on these resources for irrigated agriculture. We employ state-of-the-art global climate models from the CMIP6 project under the SSP245 scenario to evaluate changes in river runoff using the Soil and Water Assessment Tool (SWAT). Our findings indicate that temperature fluctuations play a crucial role in streamflow dynamics, given that the primary sources of river runoff in the Upper Indus Basin are snow and glacier melting. We project a substantial increase of approximately 18% in both minimum and maximum temperatures, precipitation pattern increases of 13–17%, and a significant rise in streamflow by 19–30% in the future, driven by warmer temperatures. Importantly, our analysis reveals season-specific impacts of temperature, precipitation, and streamflow, with increasing variability in projected annual changes as we progress into the mid and late 21st century. To address these changes, our findings suggest the need for integrated strategies and action plans encompassing hydroelectricity generation, irrigation, flood prevention, and reservoir storage to ensure effective water resource management in the region. Full article

Alpine glaciers are a fundamental component of the cryosphere and are significantly sensitive to climate change. One such region is the Hindukush Karakoram Himalaya (HKH) and Tibetan Plateau (TP) region, which contains more than 40,000 glaciers. There are more than 12 glacier inventories available covering parts of (or the entire) HKH region, but these show significant uncertainties regarding the extent of glaciers. Researchers have used different glacier inventories without assessing their accuracy. This study, therefore, assessed the implications of the accuracy of global glacier inventories in hydrological modeling and future water resource planning. The accuracy assessment of most commonly used two global glacier inventories (Global Land Ice Monitoring from Space-GLIMS v 2.0 and Randolph Glacier Inventory-RGI v 6.0) has been carried out for three sub-basins of the Upper Indus Basin—the Swat, the Chitral, and the Kabul River basins (combined, this is referred to as the Great Kabul River Basin)—with a total basin area of 94,552.86 km². Glacier outlines have been compared with various Landsat 7 ETM+, Landsat 8, high-resolution Google Earth images, and manually digitized debris-covered glacier outlines during different years. The total glacier area for the Great Kabul River Basin derived from RGI and GLIMS is estimated to be 2120.35 km² and 1789.94 km², respectively, which was a difference of 16.9%. Despite being sub-basins of the Great Kabul River Basin, the Swat, and the Chitral River basins were different by 54.74% and 19.71%, respectively, between the two inventories, with a greater glacierized area provided by RGI, whereas the Kabul River basin was different by 54.72%, with greater glacierized area provided by GLIMS. The results and analysis show that GLIMS underestimates glacier outlines in the Swat and the Chitral basins and overestimates glacier extents in the Kabul River basin. The underestimation is mainly due to the non-representation of debris-covered glaciers. The overestimation in GLIMS data is due to the digitization of seasonal snow as part of the glaciers. The use of underestimated GLIMS outlines may result in 5–10% underestimation of glacier-melt contribution to flows in the Swat River basin, while an underestimation of 7% to 15% is expected in the Chitral River Basin, all compared to RGI v 6.0 outlines. The overestimation of glacier-melt contribution to flows in the Kabul River basin is insignificant (1% to 2%) using GLIMS data. In summary, the use of the GLIMS inventory will lead to underestimated flows and show that the Great Kabul River Basin (particularly the Chitral River Basin) is less sensitive to climate change effects. Thus, the current study recommends the use of RGI v 6.0 (best glacier inventory) to revisit the existing biased hydro-climate studies and to improve future hydro-climate studies with the concomitant rectification of the MODIS snow coverage data. The use of the best glacier inventory will provide the best estimates of flow sensitivity to climate change and will result in well-informed decision-making, precise and accurate policies, and sustainable water resource management in the study area. The methodology adopted in the current study may also be used in nearby areas with similar hydro-climate conditions, as well as for the most recently released RGI v 7.0 data. Full article

The use of hydro-climatological time series to identify patterns is essential for comprehending climate change and extreme events such as drought. Hence, in this study, hydrological drought variability based on the standard drought index (SDI) using DrinC was investigated at ten (10) hydrological stations in the Upper Indus River Basin (UIRB) of Pakistan on a monthly timescale for a period of 1961–2018. Moreover, the applicability of the improved innovative trend analysis by Sen Slope method (referred hereafter as the IITA) method was evaluated in comparison with innovative trend analysis (ITA) and Mann–Kendall (MK). The findings demonstrated a significant decreasing trend in the hydrological drought from October to March; on the other hand, from April through September, a significant increasing trend was observed. In addition to that, the consistency of the outcomes across the three trend analysis methods was also observed in most of the cases, with some discrepancies in trend direction, such as at Kharmong station. Conclusively, consistency of results in all three trend analysis methods showed that the IITA method is reliable and effective due to its capability to investigate the trends in low, median, and high values of hydrometeorological timeseries with graphical representation. A degree-day or energy-based model can be used to extend the temporal range and link the effects of hydrological droughts to temperature, precipitation, and snow cover on a sub-basin scale. Full article

Reliable estimations of sediment yields are very important for investigations of river morphology and water resources management. Nowadays, soft computing methods are very helpful and famous regarding the accurate estimation of sediment loads. The present study checked the applicability of the radial M5 tree (RM5Tree) model to accurately estimate sediment yields using daily inputs of the snow cover fraction, air temperature, evapotranspiration and effective rainfall, in addition to the flow, in the Gilgit River, Upper Indus Basin (UIB) tributary, Pakistan. The results of the RM5Tree model were compared with support vector regression (SVR), artificial neural network (ANN), multivariate adaptive regression spline (MARS), M5Tree, sediment rating curve (SRC) and response surface method (RSM) models. The resulting accuracy of the models was assessed using Pearson’s correlation coefficient (R²), the root-mean-square error (RMSE) and the mean absolute percentage error (MAPE). The prediction accuracy of the RM5Tree model during the testing period was superior to the ANN, MARS, SVR, M5Tree, RSM and SRC models with the R², RMSE and MAPE being 0.72, 0.51 tons/day and 11.99%, respectively. The RM5Tree model predicted suspended sediment peaks better, with 84.10% relative accuracy, in comparison to the MARS, ANN, SVR, M5Tree, RSM and SRC models, with 80.62, 77.86, 81.90, 80.20, 74.58 and 62.49% relative accuracies, respectively. Full article

Intensive groundwater abstraction has augmented socio-economic development worldwide but threatens the sustainability of groundwater resources. Spatiotemporal analysis of groundwater storage changes is a prerequisite to sustainable water resource management over river basins. To estimate the groundwater storage changes/anomalies (GWCs) in the Indus River Basin (IRB), where observation wells are sparse, Gravity Recovery and Climate Experiment, the Global Land Data Assimilation System, and the WaterGAP Hydrological Model data were employed. The groundwater storage changes and controlling factors were investigated at three tier levels (TTLs), i.e., the basin, river reach, and region, to explore their implications on regional water resource management and provide management options at each level. Overall, the IRB groundwater declined from January 2003 to December 2016, with a relatively higher rate during 2003–2009 than during 2010–2016. Spatially, according to a reach-specific analysis, 24%, 14%, and 2% of the upper, middle, and lower reaches of the IRB, respectively, were indicated by a ‘severe groundwater decline’ over the entire period (i.e., 2003–2016). The GRACE-based GWCs were validated with in situ data of two heterogeneous regions, i.e., Kabul River Basin (KRB) and Lower Bari Doab Canal (LBDC). The analysis showed a correlation (R²) of 0.77 for LBDC and 0.29 for KRB. This study’s results reveal that climatic variations (increase in evapotranspiration); anthropogenic activities, i.e., pumping for irrigation; and water allocations in these regions mainly drive the groundwater storage changes across the Indus Basin. Full article

Riparian zones along rivers and streams provide ecosystem services that may change over time as disturbances increase and deteriorate these buffer zones globally. The effect of stressors on ecosystem services along the rivers in underdeveloped countries is unclear, which impacts the environment directly in the form of riparian health indicators (RHIs). This study fills this gap and measures the impact of stressors on RHIs (parameters of habitat, plant cover, regeneration, exotics, and erosion) in the Indus River basin (IRB) in Pakistan. Data on 11 stressors and 27 RHIs were collected using a field-based approach in 269 transects in the upper and lower Indus basins (UIB and LIB) in 2020 and analyzed using multivariate statistical methods. The Kruskal–Wallis tests (p < 0.05) indicated that RHIs varied significantly under the influence of stressors in the UIB and LIB. However, their highest mean values were found in the UIB. Principal component analysis revealed the key RHIs and stressors, which explained 62.50% and 77.10% of the variance, respectively. The Pearson correlation showed that stressors had greater impacts on RHIs in LIB (with r ranging from −0.42 to 0.56). Our results also showed that stressors affected RHI indices with r ranging from −0.39 to 0.50 (on habitat), −0.36 to 0.46 (on plant cover), −0.34 to 0.35 (on regeneration), −0.34 to 0.56 (on erosion), and −0.42 to 0.23 (on exotics). Furthermore, it was confirmed by the agglomerative hierarchical cluster that indices and sub-indices of RHIs and stressors differ across the UIB and LIB. These findings may serve as guidance for managers of large rivers and ecosystem service providers to minimize the environmental impact of stressors in terms of RHIs. Full article

Millions of people rely on river water originating from snow- and ice-melt from basins in the Hindukush-Karakoram-Himalayas (HKH). One such basin is the Upper Indus Basin (UIB), where the snow- and ice-melt contribution can be more than 80%. Being the origin of some of the world’s largest alpine glaciers, this basin could be highly susceptible to global warming and climate change. Field observations and geodetic measurements suggest that in the Karakoram Mountains, glaciers are either stable or have expanded since 1990, in sharp contrast to glacier retreats that are prevalently observed in the Himalayas and adjoining high-altitude terrains of Central Asia. Decreased summer temperature and discharge in the rivers originating from this region are cited as supporting evidence for this somewhat anomalous phenomenon. This study used remote sensing data during the summer months (July–September) for the period 2000 to 2017. Equilibrium line altitudes (ELAs) for July, August and September have been estimated. ELA trends for July and September were found statistically insignificant. The August ELA declined by 128 m during 2000–2017 at a rate of 7.1 m/year, testifying to the Karakoram Anomaly concomitant with stable to mass gaining glaciers in the Hunza Basin (western Karakoram). Stable glaciers may store fresh water for longer and provide sustainable river water flows in the near to far future. However, these glaciers are also causing low flows of the river during summer months. The Tarbela reservoir reached three times its lowest storage level during June 2019, and it was argued this was due to the low melt of glaciers in the Karakoram region. Therefore, using remote sensing data to monitor the glaciers’ health concomitant with sustainable water resources development and management in the HKH region is urgently needed. Full article

Glaciers in the Upper Indus Basin (UIB) in Pakistan are the major source of water, irrigation, and power production for downstream regions. Global warming has induced a substantial impact on these glaciers. In the present study, Landsat images were utilized to evaluate the glaciers for the period from 1990–2020 in the Central Karakoram National Park (CKNP) region to further correlate with climate parameters. The results reveal that glaciers are retreating and the highest (2.33 km²) and lowest (0.18 km²) recession rates were observed for Biafo and Khurdopin glaciers, respectively. However, a minor advancement has also been observed for the period from 1990–2001. More than 80% of glacier recession was recorded between 2009–2020 because mean summer temperature increased at both Skardu and Gilgit meteorological stations, while precipitation decreased at both stations from 2005–2020. The increase in mean summer temperature and decrease in winter precipitation resulted in glacial retreat, which will lead to water scarcity in the future as well as affect the agriculture sector and hydropower production in downstream areas of the Indus River basin. Full article

Groundwater is the main source of water for drinking, household use, and irrigation in Kabul; however, the water table is dropping due to the excessive extraction over the past two decades. The groundwater restoration criteria selection mainly depends on the techniques used to recharge the aquifer. The design of infiltration basins, for example, requires different technical criteria than the installation of infiltration wells. The different set of parameters is relevant to water being infiltrated at the surface in comparison with water being injected into the aquifers. Restoration of the groundwater resources are complicated and expensive tasks. An inexpensive preliminary investigation of the potential recharge areas, especially in developing countries such as Afghanistan with its complex Upper Indus River Basin, can be reasonably explored. The present research aims to identify the potential recharge sites through employing GIS and Analytical Hierarchy Process (AHP) and combining remote sensing information with in situ and geospatial data obtained from related organizations in Afghanistan. These data sets were employed to document nine thematic layers which include slope, drainage density, rainfall, distance to fault, distance to river channel, lithology, and ground water table, land cover, and soil texture. All of the thematic layers were allocated and ranked, based on previous studies, and field surveys and extensive questionnaire surveys carried out with Afghan experts. Based on the collected and processed data output, the groundwater recharge values were determined. These recharge values were grouped into four classes assessing the suitability for recharge as very high (100%), high (63%), moderate (26%), and low (10%). The relative importance of the various geospatial layers was identified and shows that slope (19.2%) is the most important, and faults (3.8%) the least important. The selection of climatic characteristics and geological characteristics as the most important criteria in the artificial recharge of the aquifer are investigated in many regions with good access to data and opportunities for validation and verifications. However, in regions with limited data due to the complexities in collecting data in Afghanistan, proper researching with sufficient data is a challenge. The novelty of this research is the cross-disciplinary approach with incorporation of a compiled set of input data with the set of various criteria (nine criteria based on which layers are formed, including slope, drainage density, rainfall, distance to fault, distance to river channel, lithology, ground water table, land cover, and soil texture) and experts’ questionnaires. The AHP methodology expanded with the cross-disciplinary approach by adding the local experts´ questionnaires survey can be very handy in areas with limited access to data, to provide the preliminary investigations, and reduce expenses on the localized expensive and often dangerous field works. Full article

Flooding is frequent in the province of Punjab, Pakistan, because the Indus River is a confluence point of five rivers. Researchers have primarily focused on the northern parts of the Indus basin and they have reported on simulation models that can be applied to the evaluation of flood risk. However, the inundation risks in the southern parts of the basin, including the impact of urbanization in this region, require a further assessment. The severity of flood disasters in the upper and lower reaches of the Indus basin are equally important because flash floods and riverine flooding pose a threat to densely populated areas. In this work, we aim to simulate flooding and the effects of landcover changes on inundation in the upper and lower Indus basin. Inundation was determined using the Rainfall–Runoff–Inundation (RRI) model with rainfall data from the monsoon season (00:00 UTC 1 July 2015–00:00 UTC 1 September 2015) as the input. After validating the model, sensitivity experiments were conducted to analyze the effect of landcover changes on the inundation of the Indus basin. The RRI model results showed that planting in the bare and vegetated areas led to minimum inundation in the Indus basin. Based on these results, planting between the Indus River and Chenab River could prevent flood disasters downstream of the confluence point as the discharge values reduced from 15,695.2 m³/s to 12,078.3 m³/s and 4373.7 m³/s to 2934.6 m³/s in the Indus River and Chenab River, respectively, before the confluence point. In contrast, urbanization in Punjab increased the risk of inundation after the confluence point caused by an increased discharge from 12,078.3 m³/s to 14,190.4 m³/s and 2934.6 m³/s to 4229.5 m³/s in the Indus River and Chenab River, respectively, before the confluence point. Full article