Water availability and demand analysis in the Kabul River Basin, Afghanistan

Kabul River Basin (KRB), the most populated and highly heterogenic river basin of Afghanistan is the lifeline of millions of people in terms of supplying them with water for agricultural, municipal, and industrial as well as hydropower production purposes. Unfortunately, KRB is facing a multiplicity of governance, management and development relevant challenges for the last couple of decades. Detailed and reliable assessments of land use and land cover, water demand (for different sectors) as well as the available water resources are prerequisites for Integrated Water Resources Management across the basin. To achieve increased accuracy for water availability and demand analysis across the KRB, the study area was segregated into different hydrological and administrative units (provincial level, subbasin level etc.) in order to capture the heterogeneity driven by complex physiographic conditions (mainly due to huge elevation differences) and resulting in diverse cropping pattern at different reaches of the river basin. The innovative part of this study has been the concept of introducing spatial segregation of the large heterogenic river basin and using crop phenological information for evapotranspiration and land cover analysis respectively; it gave a distinct value to the output of this study. Phenologically tuned normalized difference vegetation indices (NDVI) of Aqua and Terra platforms with moderate resolution (250 m) proved to be very effective in the estimation of the land cover across the KRB with high accuracy. The phenology based segregated spatial analyses of the LULC of KRB with reference to 2003 (the base year of the study) highlighted the change in the ground coverage of main crops across the KRB e.g. wheat, barley, maize and rice. Based on the evaluation of the above results referring to the period 2003 to 2013, the rise in wheat ground coverage has been compensated by the decline in barley cultivation; maize and rice share has been almost consistent among the dominant cereals production in KRB. Upon spatial segregation, across the sub-basins (Alingar, Chak aw Logar, Ghorband aw Panjshir, Gomal, Kabul, Kunar and Shamal) Shamal, Kunar and Kabul showed highest actual evapotranspiration (ETa) throughout the study period of 2003 to 2013. The later three sub-basin host relatively large irrigated areas and production of two crops per year due to relatively favorable climatic and geographic conditions. Besides the agricultural water demand (ETa), water availability estimation through rainfall-runoff modelling by the use of the Soil and Water Assessment Tool (SWAT) has been very useful in data scarce regions like KRB. The application of the hydrological model using remote sensing products as input is the only effective choice in data scarce regions and exhibited results which are required by policy makers and investors for the strategic and sustainable planning and management of land and water resources

Coupling Remote Sensing and Hydrological Model for Evaluating the Impacts of Climate Change on Streamflow in Data-Scarce Environment

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

Analysis of spatiotemporal variation in the snow cover in Western Hindukush-Himalaya region

Moderate Resolution Imaging Spectroradiometer (MODIS) products were used in this study which covers a period of 2000–2014. Comparison of the SCA derived from MODIS and Landsat NDSI showed a significant correlation, the resultant coefficient of determination (R2) was 0.85. For analyzing the trend in the SCA, the Mann-Kendall test was applied; the results show an increasing non-significant trend in the mean annual SCA with a Sen’s slope value of +16.99 (km2/year), and a significant increasing trend in the winter SCA was identified. The annual mean SCA was 8.92 km2 and 564 km2 for elevation ranges of 5001–5694 m and 4001–4500 m respectively. The spatial extent of snow cover was maximum in 70°–78.3° slope class and minimum in 30°–40° slope class. The results highlight the MODIS snow cover products’ capability to assess the spatiotemporal dynamics of snow cover in complex mountainous watersheds

Assessment of Irrigation Performance in Large River Basins under Data Scarce Environment—A Case of Kabul River Basin, Afghanistan

The Kabul River basin (KRB) of Afghanistan, a lifeline of around 10 million people, has multiplicity of governance, management, and development-related challenges leading to inequity, inadequacy, and unreliability of irrigation water distribution. Prior to any uplifting intervention, there is a need to evaluate the performance of irrigation system on a long term basis to identify the existing bottlenecks. Although there are several indicators available for the performance evaluation of the irrigation schemes, we used the coefficient of variation (CV) of actual evapotranspiration (ETa) in space (basin, sub-basin, and provincial level), relative evapotranspiration (RET), and temporal CV of RET, to assess the equity, adequacy, and reliability of water distribution, respectively, from 2003 to 2013. The ETa was estimated through a surface energy balance system (SEBS) algorithm and the ETa estimates were validated using the advection aridity (AA) method with a R2 value of 0.81 and 0.77 at Nawabad and Sultanpur stations, respectively. The global land data assimilation system (GLDAS) and moderate-resolution imaging spectroradiometer (MODIS) products were used as main inputs to the SEBS. Results show that the mean seasonal sub-based RET values during summer (May–September) (0.37 ± 0.06) and winter (October–April) (0.40 ± 0.08) are below the target values (RET ≥ 0.75) during 2003–2013. The CV of the mean ETa, within sub-basins and provinces for the entire study period, has an equitable distribution of water from October–January (0.09 ± 0.04), whereas the highest inequity (0.24 ± 0.08) in water distribution is during early summer. The range of the CV of the mean ETa (0.04–0.06) on a monthly and seasonal basis shows the unreliability of water supplies in several provinces or sub-basins. The analysis of the temporal CV of mean RET highlights the unreliable water supplies across the entire basin. The maximum ETa during the study period was estimated for the Shamal sub-basin (552 ± 43 mm) while among the provinces, Kunar experienced the highest ETa (544 ± 39 mm). This study highlights the dire need for interventions to improve the irrigation performance in time and space. The proposed methodology can be used as a framework for monitoring and implementing water distribution plans in future

Phytoremediation of Cu and Mn from Industrially Polluted Soil: An Eco-Friendly and Sustainable Approach

Water and soil polluted by heavy metals (HMs) are the primary problem due to rapidly increasing urbanization and industrialization. For the treatment of polluted soil, phytoremediation turns into a cost-effective and eco-friendly technique. The current research aimed to examine the load of pollution, specifically HMs, in sediment and wastewater (WW) of the GadoonAmazai Industrial Estate (GAIE), Pakistan and compare the ability of native grass species Cynodon dactylon and Digiteria sanguinalis for the phytoaccumulation of HMs. The industrially polluted soil was analysed for HMs using atomic absorption spectrophotometry (AAS) and compared with healthy soil (irrigated by freshwater), which served as a control. The HM accumulation was considerably higher in the soil irrigated with WW than in control soil samples. The most substantial metal pollutant was manganese (Mn), which accumulated up to 2491.7 mg/kg in the WW irrigated soil. For assessing the bioremoval efficiency of grass species, pot experimentation was performed for 90 days. Soil samples and grasses were collected from the pots to examine the HM removal efficiency. A significant reduction was noted in physicochemical characteristics of the soil, such as electrical conductivity, total organic matter, phosphorus, potassium, and saturation. The grasses removed up to 59.0% of the Cu and 59.9% of Mn from the soil. The highest bioconcentration factor (BCF) and translocation factor (TF) of Cu were observed for D. sanguinalis. While the highest BCF and TF of Mn were obtained for C. dactylon. The research showed that the grass significantly (p ≤ 0.05) reduced HM in soil samples. Moreover, the selected grasses found a higher capability to accumulate HM in the roots than in the shoot. The maximum Cu removal was obtained by D. sanguinalis and Mn by C. dactylon. The research study concluded that phytoremediation using D. sanguinalis and C. dactylon is an eco-friendly and cost-effective method that can be utilized for soil remediation