No abstract

Land use and land cover (LULC) change is one of the key driving elements responsible for altering the hydrology of a watershed. In this study, we investigated the spatio-temporal LULC changes between 2001 and 2018 and their impacts on the water balance of the Jhelum River Basin. The Soil and Water Assessment Tool (SWAT) was used to analyze the impacts on water yield (WY) and evapotranspiration (ET). The model was calibrated and validated with discharge data between 1995 and 2005 and then simulated with different land use. The increase was observed in forest, settlement and water areas during the study period. At the catchment scale, we found that afforestation has reduced the WY and surface runoff, while enhanced the ET. Moreover, this change was more pronounced at the sub-basin scale. Some sub-basins, especially in the northern part of the study area, exhibited an increase in WY due to an increase in the snow cover area. Similarly, extremes land use scenarios also showed significant impact on water balance components. The basin WY has decreased by 38 mm/year and ET has increased about 36 mm/year. The findings of this study could guide the watershed manager in the development of sustainable LULC planning and water resources management.

Drought is a continuous process in Thar Desert, Pakistan. The extent of this drought needs to be assessed for future land use and adaptation. The effect of previous drought on vegetation cover of the Thar region was studied, through combined use of drought indices and geographic information (GIS) techniques. Five years (2002, 2005, 2008, 2011 and 2014) were selected to analyze the drought conditions and land use pattern of the Thar region. The drought indices used in this study included the Normalized Difference Vegetation Index (NDVI) and the Standard Precipitation Index (SPI). Images of past drought were compared with post-drought images of our targeted area and land use maps were developed for spatio-temporal analysis. The results of the study revealed that vegetation in Thar showed an improving trend from 2002 to 2011 and then declined from 2011 to 2014. The rainfall occurred at a below average rate and SPI values for each year were calculated to be negative, indicating below average rainfall. This actual precipitation data was then compared with the data obtained from the Tropical Rainfall Measuring Mission (TRMM) satellite and R 2 ; Pearson correlation coefficients were also calculated. The R 2 values for the years 2002 and 2014 were 0.519 and 0.670 respectively. In the same manner, the Pearson correlation coefficient values for the years 2002 and 2014 were 0.721 and 0.867 respectively. The results showed the TRMM satellite's over-estimation in calculating rainfall data. Further, the average temperature for the five years under study was analyzed by graphical representation and it was revealed that the temperature of Thar has increased by almost 1 °C during the last decade.

A high resolution seasonal and annual precipitation climatology of the Upper Indus Basin was developed, based on 1995-2017 precipitation normals obtained from four different gridded datasets (Aphrodite, CHIRPS, PERSIANN-CDR and ERA5) and quality-controlled high and mid elevation ground observations. Monthly precipitation values were estimated through the anomaly method at the catchment scale and compared with runoff data (1975-2017) for verification and detection of changes in the hydrological cycle. The gridded dataset is then analysed using running trends and spectral analysis and the Mann–Kendall test was employed to detect significant trends. The nonparametric Pettitt test was also used to identify the change point in precipitation and runoff time series. The results indicated that bias corrected CHIRPS precipitation dataset, followed by ERA5, performed better in terms of RMSE, MAE, MAPE and BIAS in simulating rain gauge-observed precipitation. The running trend analysis of annual precipitation exhibited a very slight increase whereas a more significant increase was found in the winter season (DJF). A runoff coefficient value greater than one, especially in glacierized catchments (Shigar, Shyok and Gilgit) indicate that precipitation was likely underestimated and glacial melt in a warming climate provides excess runoff volumes. As far as the streamflow is concerned, variabilities are more pronounced at the seasonal rather than at the annual scale. At the annual scale, trend analysis of discharge shows slightly significant increasing trend for the Indus River at the downstream Kachura, Shyok and Gilgit stations. Seasonal flow analysis reveals more complex regimes and its comparison with the variability of precipitation favours a deeper understanding of precipitation, snow- and ice-melt runoff dynamics, addressing the hydroclimatic behaviour of the Karakoram region.

<p>Textile products made with cotton produced in Pakistan, Turkey, and Uzbekistan are largely imported to European markets. This is responsible for high virtual water imports from these countries and thus puts immense pressure on their water resources, which is further extravagated due to climate change and population growth. The solution to combat the issue, on one hand, is to cut water usage for cotton irrigation, and on the other hand, to increase water productivity. The biggest challenge in this regard is the correct quantification of consumptive water use, cotton yield estimation and crop water productivities at a finer spatial resolution on regional levels, which is now possible by utilizing remote sensing (RS) data and approaches. It can also facilitate comparing regions of interest, like in this study, Pakistan, Turkey, and Uzbekistan by utilizing similar data and techniques. For the current study, MODIS data along with various climatic variables were utilized for the estimation of consumptive water use and cotton yield estimation by employing SEBAL and Light Use Efficiency (LUE) models, respectively. These estimations were then used for working out water productivities of different regions of selected countries as case studies. The results show that the study area in Turkey achieved maximum cotton water productivity (i.e. 0.75 - 1.2 kg.m<sup>-3</sup>) followed by those in Uzbekistan (0.05 – 0.85 kg.m<sup>-3</sup>) and Pakistan (0.04 – 0.23 kg.m<sup>-3</sup>).  The variability is higher for Uzbekistan possibly due to agricultural transition post-soviet-union era. In the case of Pakistan, the lower cotton water productivities are mainly attributed to lower crop yields (400 – 1200 kg.ha<sup>-1</sup>) in comparison to Turkey (3850 – 5800 kg.ha<sup>-1</sup>) and Uzbekistan (450 – 2500 kg.ha<sup>-1</sup>). Although the highest crop water productivity is achieved for the study region in Turkey, there is still potential for further improvement by introducing on-farm water management. In the case of the other two countries, especially for Pakistan, major improvements are possible through maximizing crop yields. The next steps include comparisons of the results in economic out-turns.</p>