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The aim of study to explore the potential of groundwater aquifers in northern area of Quetta valley due to rapidly shifting huge population from whole province of Balochistan and thousands of refugees from Afghanistan border. The depletion of groundwater resources In Quetta valley has become a severe issue, mainly due to prolonged droughts, unregulated extraction, urbanization, and inadequate understanding of the Complex geological conditions. To gain a more in-depth understanding of the hydrogeological conditions in the northern areas of Quetta valley, Geophysical resistivity survey was conducted to explore the subsurface groundwater aquifer and their potential. Total 12 VES were conducted along three different profile lines at the depth of 450m VES interval of 2Km from Pishin bypass to Bostan area. The collected data was processed and analysed using IPI2win software to create geoelectrical section and pseudo-sections displaying the layers and thicknesses of each survey point. It is interpreted that two aquifers are present at various depths, first shallow low potential aquifer lie in silty clay and silty sand lithology in profile 01. In profile 2 and 3 aquifer bearing limestone lithology were encountered. The aquifers in the area are characterized as low pressure and low potential due to the accumulation of silt. It is not advisable to solely rely on groundwater as a source of water for the increasing population. Alternative water sources should be explored, and measures such as installing artificial wells should be taken to recharge the aquifers. Additionally, it is essential that the relevant departments formulate monitoring strategies to keep track of the groundwater levels in the area.

This study aims to illustrate and present various techniques for evaluating the performance of check-dams and proposes some suitable approaches for impact assessment of dams built in the Balochistan province of Pakistan. These dams were built during the last decade to overcome the challenges of water scarcity and depleting aquifers due to excessive Groundwater (GW) extraction. It was expected that these dams would recharge the GW resources and save the aquifer system from collapsing. Check-dams have traditionally been the permanent source of water within the province. A check-dam is used to delay the floodwater runoff to make it available for domestic and agriculture purposes or to recharge GW. The water along these dams permeates into the ground to keep the aquifer genuinely stable throughout the year. The data were collected based on studies of published research papers and reports of international organizations containing key characteristics of performance evaluation techniques. This review will help to evaluate procedures, policy, and governance interventions in Balochistan by comparing them with the adopted practices in other regions of the world and its impact on the well-being of the society. In this paper, the performance evaluation of check-dams for specific cases is presented. The knowledge acquired will be utilized to highlight state-of-the-art practices and to identify the need for further research in this field.

This case study of rainfed Potohar region of Punjab, Pakistan, illustrates the impact of water sector interventions on the ‘three Es’ of integrated water resource management: economics, equity, and environment. Small and mini dams constructed with the support of the Agency for Barani Area Development have been selected for this study. For impacts assessment, interviews and field surveys were conducted and data from the Pakistan Bureau of Statistics and Agriculture Marketing Information Services were acquired. Moreover, precipitation data and imagery in Google Earth were also used in this study to further validate the impact of dams on agriculture. Remote sensing imagery was used to estimate vegetative cover through the normalized difference vegetation index. Overall, the study results show a significant increase in the vegetation cover between 2008 and 2016. Therefore, small and mini dams happened to be significant and effective interventions in improving the quality of livelihood and sustained agriculture in the Potohar region of Punjab. Thus, for efficient and sustainable rainwater management, small and mini dams can be considered as a feasible option not only in the unserved areas of the Potohar region but other rainfed areas as well.

This study explores the impact of runoff curve number (CN) on the hydrological model outputs for the Morai watershed, Sindh-Pakistan, using the Soil Conservation Service Curve Number (SCS-CN) method. The SCS-CN method is an empirical technique used to estimate rainfall-runoff volume from precipitation in small watersheds, and CN is an empirically derived parameter used to calculate direct runoff from a rainfall event. CN depends on soil type, its condition, and the land use and land cover (LULC) of an area. Precise knowledge of these factors was not available for the study area, and therefore, a range of values was selected to analyze the sensitivity of the model to the changing CN values. Sensitivity analysis involves a methodological manipulation of model parameters to understand their impacts on model outputs. A range of CN values from 40-90 was selected to determine their effects on model results at the sub-catchment level during the historic flood year of 2010. The model simulated 362 cumecs of peak discharge for CN=90; however, for CN=40, the discharge reduced substantially to 78 cumecs (a 78.46% reduction). Event-based comparison of water volumes for different groups of CN values—90-75, 80-75, 75-70, and 90-40 —showed reductions in water availability of 8.88%, 3.39%, 3.82%, and 41.81%, respectively. Although it is known that the higher the CN, the greater the discharge from direct runoff and the less initial losses, the sensitivity analysis quantifies that impact and determines the amount of associated discharges with changing CN values. The results of the case study suggest that CN is one of the most influential parameters in the simulation of direct runoff. Knowledge of accurate runoff is important in both wet (flood management) and dry periods (water availability). A wide range in the resulting water discharges highlights the importance of precise CN selection. Sensitivity analysis is an essential facet of establishing hydrological models in limited data watersheds. The range of CNs demonstrates an enormous quantitative consequence on direct runoff, the exactness of which is necessary for effective water resource planning and management. The method itself is not novel, but the way it is proposed here can justify investments in determining the accurate CN before initiating mega projects involving rainfall-runoff simulations. Even a small error in CN value may lead to serious consequences. In the current study, the sensitivity analysis challenges the strength of the results of a model in the presence of ambiguity regarding CN value.

The growing population and low crop water productivity (CWP) in Pakistan is putting immense pressure on its water resources. The aim of this study was to assess water productivity of one of the country's largest growing crops. The wheat crop in the Rohri canal command area during 2014–2015 and 2016–2017 was selected for this purpose. Wheat is the major crop of the Rabi (winter) season in the Sindh province of Pakistan. Rohri is one of the major canals of the Indus Basin Irrigation System (IBIS) serving Sindh's central and lower parts. METRIC EEFLUX (Mapping Evapotranspiration at high Resolution with Internalized Calibration) processed imageries were used to calculate CWP along with the crop yield statistics collected by the Sindh government. Crop masks were used to delineate the cropping area. The wheat crop's total consumptive water uses during 2014–2015 was 340.08 mm and 202.19 mm in 2016–2017. The associated CWP values in these two years were 1.03 kg/m3 and 1.02 kg/m3.

Karachi, the biggest city of Pakistan, has undergone various urban sprawls due to its continuously growing population that has severely affected its natural drainage pattern. The city had an extensive natural drainage system which has now lost its original form. This study investigated the blockages and their causes during the last two decades in one of the city’s riverbeds—Malir. Moreover, the extent of floods identifying the vulnerability of the watershed’s urban area after major rainfall events was modeled. The geospatial techniques and satellite images of Landsat 5, 7, and 8 were used to analyze the changes in land use and land cover (LULC) of the Malir Basin. The Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model and topographic sheets of 1975 were utilized to delineate the natural drainage network and streambeds of the basin using geographical information system (GIS) tools. Historical rainfall data from 1985 to 2014 were acquired from the Pakistan Meteorological Department (PMD) to simulate runoff using the US Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS and HEC-GeoHMS). The flood modeling was done using the River Analysis System (HEC-RAS and GeoRAS). Rainfall-runoff simulations and flood extent and depth of five major rainfall events—1992, 2003, 2007, 2009, and 2013—were modeled in this study. GIS overlay analysis combined the LULC, riverbed, and drainage line layers to identify the blocked area and to quantify the specific LULCs that were causing blockages in the riverbed. Several maps, which are prepared in this study, show the parts of the river with altered drainage patterns in 2013 from what existed back in 1975.

Satellite altimetry-based monitoring of water bodies is an advanced and cost-effective approach, mainly for regions where gauge density is low, as is the case of the Indus River in Pakistan. In this study, the potential of modern radar altimetry for inland waters was studied for measuring the Indus River water levels. For this purpose, two locations were selected near the Guddu and Sukkur Barrages on the lower Indus River, where Sentinel 3A tracks are available along with gauge data. Time series gauge data were used to validate altimetry derived water heights. An excellent fit of the two datasets (with correlations higher than 0.9) is found for both locations except a few points where altimetry heights deviate from ground observed heights. One of the possible reasons for this deviation may be the difference between the data acquiring time of the two datasets. Any barrage operation between this lag time may lead to changes in the gauge data. To overcome this problem, three-day moving averages of the gauge data were used that substantially improved the results (RMSD and ubRMSE lowered to less than 45 cm). The validation of satellite-derived water heights will lead to the possibility of observing river level changes on different segments of the river system. Other than the two at the Guddu and Sukkur barrages, 16 more Sentinel 3A and 3B tracks along the lower Indus River are available. These locations are the altimetry river monitoring virtual stations supplementing the low-frequency gauging network of the River.

This study aims to assess the impact of 2010-2011 flash floods on the crop production of Sanghar—an eastern district of Sindh. The population of almost two million is mainly dependent on agriculture. Cotton, sugarcane, and wheat are the main cash crops of the district. In 2010-2011 Sanghar was hit by flash floods after heavy rainfall. These floods adversely affected the crops standing at that time. However, on the other hand, they increased the fertility of agriculture lands. Satellite images, precipitation data, and Geographical Information System (GIS) tools were used to quantify the effects of floods by mapping pre- and post-floods vegetation cover. Supervised classification was manipulated on Landsat images from 2009 to 2013 to extract vegetation area. The temporal analysis unveils a significant increase in the vegetation cover in the post-flood years. Furthermore, the comparison between pre- and post-flood crop production data collected from the Pakistan Bureau of Statistics, also validated the study results by revealing an increase in crop production.

The rising water demand, coupled with mismanagement and misallocation of water, has caused water scarcity in the Sindh Province of Pakistan. The Sindh province almost entirely relies on the Indus River supply to meet its agricultural demand. The rising population will demand more food, but at the same time, agriculture water share will be under pressure due to the increasing demand of other competing users. Many studies have predicted a shortfall of water in the coming years, which will cause food security issues in the country. Since agriculture is the largest water user among all sectors, effective water management in this sector will have the most significant impact. A water balance study is presented in this paper to evaluate the current and future water supply and demands and develop sustainable agriculture water budgeting. Actual evapotranspiration (ET) or consumptive water in the entire irrigated region of Sindh comprising 14 canal command areas (CCAs) during the Rabi and Kharif seasons of 2017-2019 was studied. The study utilized Landsat satellite data product from the Earth Engine Evapotranspiration Flux (EEflux). Study results identified shortages during the Rabi seasons when flows are usually low, but consumptive water use is more than the available quantum from canal flows and rainwater. However, the Kharif season presented an opposite trend. Within CCAs, the supplies and demands showed variable trends that can be balanced by adjusting surplus and deficit supplies by recalculating canal allocations. Suggestions for balancing water in these CCAs were also presented in this study.

This case study of rainfed areas of the Potohar region of Punjab, Pakistan illustrates the impact of water sector interventions, with a focus on how small and mini dams affect agricultural development. These dams were constructed with the support of the Punjab Government. Normalized difference vegetation index (NDVI) was employed using ENVI classic image processing software for estimating vegetation cover. Buffers of 500-m and 1000-m were created around the dams using ArcGIS to identify the changes in vegetation. The study results showed an increase in the vegetation cover by 15.7 % in the entire Potohar region. These results were validated from field collected data that further informed increase in the cropping intensity and introduction of non-traditional crops after the construction of dams. This study verifies the feasibility of small dams in the rainfed areas of Punjab. This information is shared with the planning and development department of Punjab supporting such interventions in other unserved areas of the Potohar region.

Indus River is one of the largest rivers of Asia that runs through four countries (China, India, Afghanistan, Pakistan) and supports multiple economic activities in the region. Sindh Province of Pakistan is at the tail-end of the River. River monitoring, though essential to manage it well, is a necessity for the tail-enders to ascertain the availability of water and to distribute it among its users. The Sindh province depends mostly on the Indus River supply to meet its demand. The River irrigates Sindh 2540 hectares culturable area. Besides agriculture, industrial and domestic water users also greatly rely on the river water supply. The optimum management of the River necessitates an extensive network of gauge stations. Whereas, the Indus River has minimal gauging network. This paper presents the potential of satellite radar altimetry by using Sentinel 3A data to monitor river water levels. This paper validates the satellite data by comparing them with the in-situ data near the Guddu and Sukkur Barrages. The results showed an excellent agreement between the two datasets with correlations higher than 0.9, and the root mean square difference (RMSD) less than 45 cm for both locations.

Water is a limited natural resource; therefore, continuous monitoring is required to develop methods and policies to support its sustain ability. An approach like satellite radar altimetry is a powerful technique for monitoring water level variations. It was designed and developed for smooth surfaces such as the open ocean, but to some extent, it is now used to study the inland waters as well. The satellite radar altimetry coupled with passive remote sensing enabled the monitoring of continental surface water, such as inland seas, lakes, rivers, and reservoirs, by providing information about its water level, river discharge, lake extent, and its volume. This study estimated the monthly water balance of an ungauged lake, located in Pakistan, using satellite radar altimetry and passive remote sensing. The Manchar Lake is significant for its ecological, social, and economic value but is not monitored regularly and hence cannot be managed well. Due to the unavailability of gauge data, it is challenging to calculate Lake's water balance directly. The water levels from sentinel 3A combined with Landsat 8 derived lake surface areas were used to estimate changes in the lake's volume, which were used in the water balance equation. The primary inflows to the Lake are from Main Nara Valley Drain (MNVD), Indus River, and runoff from hills. Whereas, the outflows are evaporation, groundwater recharge, and domestic and agricultural water use. This study provides Manchar Lake's monthly water balance from July 2016 to July 2019. An inconsistent and random water balance values are observed during the study period, with outflows exceeding inflows 40% of the time. The Lake's ecosystem depends on the availability of sufficient water, and the negative water balance may cause a threatening situation. The approach and results may provide valuable information for water resource management of the Manchar Lake using satellite data, which has still existential issues of ground observations.

The most popular and beautiful spot of Urak valley— Hanna Lake, situated in the capital city Quetta (Balochistan, Pakistan), is shrinking affecting the surrounding environment and lake’s ecosystem. Lake completely dried thrice since 2001. One of the most stated reasons is a shortage of rainfalls due to climate change. Pakistan is ranked on 7th position in the list of most vulnerable countries to climate change with 141 extreme weather events. Linking lake drying to climate change seems to be an obvious connection in the absence of required historical records regarding temporal changes in the lake’s surface area and volume. Researching precise reasons is crucial to find appropriate solutions. This study took advantage of satellite-derived data to overcome the gap between recorded information. Changing lake surface areas from satellite images were compared with National Oceanic and Atmospheric Administration (NOAA) rainfall records since 1984 to study any interconnection between them. It was found that since 2002, rainfall trend increases, whereas, lake area decreases. This gives rise to the impression that climate change has not caused any drop in lakes and other water bodies.

This study aims to assess the correlation between the satellite radar altimetry derived water level heights and in-situ gauges on the Indus River. The in-situ gauge data at Guddu Barrage was acquired from the Sindh Irrigation Department and its outliers were removed using the interquartile method. Altimetry derived water levels near the Guddu Barrage in Sindh, Pakistan were taken from various databases such as Database for Hydrological Time Series of Inland Waters (DAHITI), Hydroweb from 17 July 2008 to 20 Nov 2018, and SARvatore (SAR Versatile Altimetric Toolkit for Ocean Research & Exploitation) for Sentinel-3. The altimetry datasets were plotted against the in-situ gauge data and analysed visually as well as statistically. The regression analyses run yielded an R2 value of around 0.6 for DAHITI and Hydroweb whereas for SARvatore it was 0.1. RMSE values produced were 0.5m, 0.6m and 0.9m respectively for Hydroweb, DAHITI and SARvatore.

Seaweed is a valuable coastal resource for its use in food, cosmetics, and other items. This study proposed new remote sensing based seaweed enhancing index (SEI) using spectral bands of near-infrared (NIR) and shortwave-infrared (SWIR) of Landsat 8 satellite data. Nine Landsat 8 satellite images of years 2014, 2016, and 2018 for the January, February, and March months were utilized to test the performance of SEI. The seaweed patches in the coastal waters of Karachi, Pakistan were mapped using the SEI, normalized difference vegetation index (NDVI), and floating algae index (FAI). Seaweed locations recorded during a field survey on February 26, 2014, were used to determine threshold values for all three indices. The accuracy of SEI was compared with NDVI while placing FAI as the reference index. The accuracy of NDVI and SEI were assessed by matching their spatial extent of seaweed cover with FAI enhanced seaweed area. SEI images of January 2016, February 2018, and March 2018 enhanced less than 50 percent of the corresponding FAI total seaweed areas. However, on these dates the NDVI performed very well, matching more than 95 percent of FAI seaweed coverage. Except for these three times, the performance of SEI in the remaining six images was either similar to NDVI or even better than NDVI. SEI enhanced 99 percent of FAI seaweed cover on January 2018 image. Overall, seaweed area not covered by FAI was greater in SEI than NDVI in almost all images, which needs to be further explored in future studies by collecting extensive field information to validate SEI mapped additional area beyond the extent of FAI seaweed cover. Based on these results, in the majority of the satellite temporal images selected for this study, the performance of the newly proposed index—SEI, was found either better than or similar to NDVI.

Dengue outbreak has become a significant mosquito-borne disease in Pakistan with the worst outbreak in the Lahore district in 2011. This situation has emerged as a serious concern for disaster management authorities, and managing risks of dengue outbreaks has become their top priority. This study investigated the relationship of the reported dengue cases in the Lahore district in 2011 with the spatial and temporal changes in climatic and environmental factors. The quantitative co-relational research method was employed to ascertain the association between dengue incidences and weather parameters, land use/cover, and demographic characteristics of the study area. Ordinary least-square and geographically weighted regression analyses were conducted to identify the influence of study variables on the dengue outbreak. Satellite and ground data were used to derive study parameters. A geostatistical dengue risk model was developed to identify the risk-prone areas in Lahore. The geographically weighted multivariate regression model indicated a statistically significant relationship between dengue cases and the built-up area and population density. These two explanatory variables explained 77.4% variance in dengue incidences. This study supported the association between the demographic parameters and distribution pattern of dengue outbreaks in the Lahore district. The dengue risk model identified the vulnerable areas that need particular attention to mitigate future outbreaks.

In the industrial sector, the financial gain is generally considered at the cost of environmental degradation. The environmental protection and economic benefit are common conflicting objectives in many optimization problems. In any multi-criteria problem, the most challenging part is to optimize the conflicting goals. But if these objectives become non-conflicting, then the problem can be solved with ease. This paper is all about minimizing the environmental impact of industrial processes while maximizing the net economic benefit. There is a general misconception of linking the environmental protection with a financial loss. This is not always true; the Eco-Efficiency or Cleaner Production Technology (CPT) is a perfect example to disprove this notion. Economics of CPT regarding water savings for the textile-processing sector in Pakistan has been analyzed in this paper. Changes in water use before and after the implementation of water conserving technologies in the textile sector of Pakistan from a study conducted by the Cleaner Production Institute (CPI) are utilized to perform a cost-benefit analysis. Direct financial benefits that could be achieved through the application of these technologies are presented only. Other environmental benefits, though not described here, are of no less importance. The study results reveal that very high potential of water savings exists for most of the investments on CPT.

Seaweeds are regarded as one of the valuable coastal resources because of their usage in human food, cosmetics, and other industrial items. They also play a significant role in providing nourishment, shelter, and breeding grounds for fish and many other sea species. This study introduces a newly developed seaweed enhancing index (SEI) using spectral bands of near-infrared (NIR) and shortwave infrared (SWIR) of Landsat 8 satellite data. The seaweed patches in the coastal waters of Karachi, Pakistan were mapped using SEI, and its performance was compared with other commonly used indices - Normalized Difference Vegetation Index (NDVI) and Floating Algae Index (FAI). The accuracy of the mapping results obtained from SEI, NDVI, and FAI was checked with field verified seaweed locations. The purpose of the field surveys was to validate the results of this study and to evaluate the performance of SEI with NDVI and FAI. The performance of SEI was found better than NDVI and FAI in enhancing submerged patches of the seaweed pixels what other indices failed to do.

The primary school system in Pakistan needs improvement in order to provide the basic right of education to all. Government schools are not enough to cater the needs of increasing population of the country. The main goal of this study was to present a methodology for the development of government schools based on geographical information system (GIS) through a case study of Orangi Town in Karachi. In this study, first the adequacy of government schools in the study area was evaluated and then the need for additional schools with their suitable locations were identified. Data regarding school locations and students enrollments were collected from Sindh Basic Education Program of a non-profit NGO iMMAP. School building footprints were digitized from 2001 and 2013 Google Earth archived images. Population in 2013 was estimated by projecting 1998 census data downloaded from the website of the Census Bureau of Pakistan. An educated assumption of 20 % of the total population of Orangi Town was used to calculate number of primary school-aged children. Study results showed that schools existed in 2013 were not sufficient to serve all these children. This study also revealed that new schools were built during this time period, but the population growth rate was much higher than the growth rate of schools that created a big supply-demand gap. The most progressive Union Council (UC) of Orangi Town was Haryana Colony where 17 new schools were constructed between 2001 and 2013 though the required number of schools still fall short. New sites for schools were also proposed to optimally serve Orangi Town’s residents using GIS proximity analysis.

The idea of including economic analysis in pollution control studies is not new. There is a long tradition of research modeling least cost load allocation for water pollution control that has led to a substantial awareness that failure to take costs into account in load allocations can greatly increase the costs of water pollution control. Despite this understanding, the current load allocation approach adopted under United States Environmental Protection Agency total maximum daily load (TMDL) program allocates pollutant loads among different polluters in the absence of economic criteria. Many water quality professionals question the appropriateness of including economic criteria into an already complex and cumbersome TMDL allocation process. The question is not why we do not include economics into waste load allocations, rather the question is why we should? This paper attempts to identify and present the benefits associated with the incorporation of economic criteria into the traditional TMDL allocation process. The TMDL process is considered to be a holistic watershed approach and as such should not overlook the economic consequences of pollutant allocation alternatives. This paper attempts to focus less on the mechanism of optimizing the costs and more on the benefits derived as a by-product of doing so. The advantages of incorporating economic criteria for a bacteria load allocation in the Roses Creek watershed in the Commonwealth of Virginia are presented in this paper.

Water quality trading (WQT) is supported by the US Environmental Protection Agency (USEPA) under the framework of its total maximum daily load (TMDL) program. An innovative approach is presented in this paper that proposes post-TMDL trade by calculating pollutant rights for each pollutant source within a watershed. Several water quality trading programs are currently operating in the USA with an objective to achieve overall pollutant reduction impacts that are equivalent or better than TMDL scenarios. These programs use trading ratios for establishing water quality equivalence among pollutant reductions. The inbuilt uncertainty in modeling the effects of pollutants in a watershed from both the point and nonpoint sources on receiving waterbodies makes WQT very difficult. A higher trading ratio carries with it increased mitigation costs, but cannot ensure the attainment of the required water quality with certainty. The selection of an applicable trading ratio, therefore, is not a simple process. The proposed approach uses an Economic TMDL optimization model that determines an economic pollutant reduction scenario that can be compared with actual TMDL allocations to calculate selling/purchasing rights for each contributing source. The methodology is presented using the established TMDLs for the bacteria (fecal coliform) impaired Muddy Creek subwatershed WAR1 in Rockingham County, Virginia, USA. Case study results show that an environmentally and economically superior trading scenario can be realized by using Economic TMDL model or any similar model that considers the cost of TMDL allocations.

Seaweed is a marine plant or algae which has economic value in many parts of the world. The purpose of this study is to evaluate different satellite sensors such as high-resolution WorldView-2 (WV2) satellite data and Landsat 8 30-meter resolution satellite data for mapping seaweed resources along the coastalwaters of Karachi. The continuous monitoring and mapping of this precious marine plant and their breeding sites may not be very efficient and cost effective using traditional survey techniques. Remote Sensing (RS) and Geographical Information System (GIS) can provide economical and more efficient solutions for mapping and monitoring coastal resources quantitatively as well as qualitatively at both temporal and spatial scales. Normalized Difference Vegetation Indices (NDVI) along with the image enhancement techniques were used to delineate seaweed patches in the study area. The coverage area of seaweed estimated with WV-2 and Landsat 8 are presented as GIS maps. A more precise area estimation wasachieved with WV-2 data that shows 15.5Ha (0.155 Km2)of seaweed cover along Karachi coast that is more representative of the field observed data. A much larger area wasestimated with Landsat 8 image (71.28Ha or 0.7128 Km2) that was mainly due to the mixing of seaweed pixels with water pixels. The WV-2 data, due to its better spatial resolution than Landsat 8, have proven to be more useful than Landsat8 in mapping seaweed patches

Karachi is a strategic city of Pakistan since it serves as the gateway for international trade through the country's oldest port. This city has faced rapid population increase and industrial growth which are now causing environmental issues, social problems and economic stresses and challenges. Urban development and industrialization have extensively changed the landuse/landcover (LULC) and drainage pattern of the city. Majority of the old streams have been blocked that caused localized flash flooding in the city after heavy rainfall events. The natural drainage network of Karachi consists of two (2) major river systems - Malir River on the eastern side of the city and Lyari River which passes through the center of the city draining majority of its storm water. These rivers and their tributaries have been affected very badly due to the urbanization and bad urban management. This paper discusses the changes in LULCs over the past 16 years selecting Malir basin as a case study. Hydraulic flood modeling of Malir River is also presented here for 50 and 100 years floods. SRTM (Shuttle Radar Topographic Mission) Digital Elevation Model (1 Arc Second) and topographic sheets of 1975 and 2001 (1:50000) are used to demarcate natural drainage or Karachi District on digital maps and to delineate stream network using Geographical Information System (GIS) software tool Arc Hydro. Historical rainfall data are used to simulate runoff using hydrologic models HEC-HMS and GeoHMS. The flood extent is modeled using hydraulic models HEC-RAS and GeoRAS. GIS overlay analysis combines LULCs and river drainage layers to identify the blocked area and to quantify the specific LULCs that caused the river blockades. Maps of blockages and flood extent can be used for revival of natural drainage network and flood mitigation and preparedness. The beneficiaries of this study may include local disaster risk management, planning and development authorities.

The total maximum daily load approach currently used by the USEPA to restore an impaired stream by allocating allowable loads to the polluters does not mandate any economic consideration. The need for a cost-effective allocation process has long been identified but no single best way to accomplish this has yet been developed. This paper describes how the most economical load allocation scenario may be determined through an optimal placement of control measures within an agricultural watershed. The proposed optimization approach is applied to the bacterially impaired Roses Creek watershed located in the Commonwealth of Virginia. The cost-effectiveness relationships were established for vegetative buffer strips, streamside fencing, pet waste management, and septic system repair and installation to illustrate the methodology. Similar relationships may be established for other control measures provided their load reduction efficiencies are known.

Many states are actively involved with the load allocation phase of the Total Maximum DailyLoad (TMDL) Program. The Environmental Protection Agency (EPA) directs that TMDLs mustinclude establishment of reasonable and equitable load allocations among point sources thatwill, alone or in conjunction with other management and restoration activities, provide for theattainment of designated water uses (water quality standards) and the restoration of impairedwaters(FDEP, 2002). Allocation of load reductions must include an evaluation of the most costeffectiveapproach, however, specific guidelines do not address how this should beaccomplished. The TMDL process is technically complex enough without the inclusion of costoptimization. What are the benefits to be derived from including cost into the allocation?Preliminary EPA reports project a median savings of 75% (with a range of 21% to 92%) inimplementation cost for BOD and Nutrients reduction when a Cost-effective TMDL Programapproach is followed (EPA, 2001). The EPA evaluation involved a simple linear comparison ofallocation alternatives. Unfortunately, the highly non-linear nature of the implementation costswas not taken into consideration. With the potential for savings, it is imperative to develop asystematic optimization approach that seeks to minimize costs of implementation whileincorporating the non-linear nature of the cost functions. The objective of this paper is to present a mathematical model that that uses a mixed integer nonlinearoptimization approach to reduce the potential costs associated with alternative allocationstrategies. The mathematical model was developed for the fecal coliform TMDL allocation forthe Muddy Creek sub-watershed (Muddy 3) located in Rockingham County, Virginia. TheVirginia TMDL Program has historically allocated the fecal reductions as follows (ASAE, 2002): 90-100% direct deposits of cattle manure in streams 100% of all unpermitted point sources 0-95% in nonpoint sources 35-85% in wildlife fecal materials in streams The mathematical model has the potential for considerable cost savings when a flexible (non-rulebased) allocation strategy is adopted that focuses on maximum environmental contribution for agiven expenditure.

In Hindu Kush Himalayas (HKH) region, observations on glacial fluctuations indicate substantial retreat of glaciers, especially in Pakistan, Nepal, India and China. Recent global temperature rise has allegedly been responsible for the depletion of these glaciers and consequently creation of lakes on their terminus. Several of these lakes have burst and caused flooding or Glacial Lake Outburst Floods (GLOFs) in the recent past. GLOFs have a potential of releasing millions of cubic meters of water in a few hours causing catastrophic flooding downstream and damaging whatever comes into their way. Hazard mapping of elements at risk may enhance the capacity of the vulnerable communities to face these disasters in order to reduce their devastating impacts. Study of GLOFs hazard in Hunza River basin of Pakistan using geospatial techniques consisting of satellite remote sensing, Geographical Information System (GIS), hydraulic and hydrology tools is proposed in this paper. Geospatial techniques have a capacity to acquire information regarding the status of glaciers and glacier lakes at spatial and temporal resolutions beyond the capability of infrequent and point scale in-situ monitoring. Remotely sensed satellite data along with ground based data are used in this study for risk mapping of Passu Lake in Hunza River basin, Pakistan. The outcomes of the proposed study will be helpful for GLOFs risk management and an overall strategy to address possible risks from future GLOFs events in the country.

Recent advances in remote sensing (RS) approaches have provided the capacity to acquire water quality information at spatial and temporal resolutions beyond the capability of infrequent and point scale in-situ measurement. Through integrating remote sensing data with Geographic Information Systems (GIS), an advanced approach to study water quality issues is possible. Traditional water quality assessment and monitoring techniques are time, data and consequently capital intensive - often beyond the means of developing countries. Utilizing the geospatial capacity of RS and GIS approaches provides a cost-effective and research quality solution to these issues. The purpose of this paper is to present an integrated approach utilizing geospatial techniques to address water quality issues under the framework of US Environmental Protection Agency’s (USEPA) Total Maximum Daily Load (TMDL) program. A TMDL is the calculated maximum amount of a pollutant that a waterbody can receive without violating the water quality standard appropriate for its intended use. This paper will demonstrate the usefulness of these technologies by proposing a RS and GIS based water quality predictive model. The future goal of this study is to apply the proposed strategy for developing countries where project budgets are usually very limited to show the usefulness of geospatial technologies in optimizing limited resources of a project without compromising the reliability of outputs - rather more realistic outcomes are expected to be achieved.

The growing demand for water coupled with surface water quality concerns, has initiated a drive towards the restoration of impaired waters. Improvement programs require that contributing pollutant sources reduce loads to levels that ensure that the water body is fit for its intended use. An effective pollution reduction program must not only consider the level of pollutant reduction required but also economic and technological limitations. Optimizing the cost of environmental remediation actions during planning will greatly improve the ability to successfully implement a restoration program. The objective of this paper is to illustrate an approach that can be used to minimize the costs of pollutant reductions necessary to accomplish water quality initiatives. A case study is presented to demonstrate the proposed concepts based on the framework of Section 303(d) of the Clean Water Act, better known as the Total Maximum Daily Load (TMDL) Program. The approach involves the systematic application of a mathematical model to minimize the costs for a load allocation that accomplishes the desired water quality goal.

The restoration of impaired waters through the Total Maximum Daily Load (TMDL) program requires contributing pollutant sources to reduce their loads to a level that will result in the attainment of the water quality standard. In-stream numeric endpoints represent the water quality goals that are to be achieved by implementing the load reductions specified in the TMDL. To date, the TMDL allocation scenario is considered as the starting point for development of an implementation strategy. Modifications may be required if the necessary load reductions are not achieved or if the water quality goals are not met. The likelihood of a successful TMDL implementation depends on a feasible load a llocation among the polluters. A load allocation scenario developed for a given water quality criteria may not be feasible due to limitations on the effectiveness of the available control measures. The practicality of the load reduction levels when translated into the relevant control strategies should be investigated to better ascertain the attainability of a given water quality standard. If one considers the technical limitations of accomplishing the high level of reduction required by many sate TMDL programs, the question arises: “Are the state standards for the designated water uses attainable?”