ITOM: an interval-parameter two-stage optimization model for stochastic planning of water resources systems

Planning of water resources systems is often associated with many uncertain parameters and their interrelationships are complicated. Stochastic planning of water resources systems is vital under changing climate and increasing water scarcity. This study proposes an interval-parameter two-stage optimization model (ITOM) for water resources planning in an agricultural system under uncertainty. Compared with other optimization techniques, the proposed modeling approach offers two advantages: first, it provides a linkage to pre-defined water policies, and; second, it reflects uncertainties expressed as probability distributions and discrete intervals. The ITOM is applied to a case study of irrigation planning. Reasonable solutions are obtained, and a variety of decision alternatives are generated under different combinations of water shortages. It provides desired water-allocation patterns with respect to maximum system benefits and highest feasibility. Moreover, the modeling results indicate that an optimistic water policy corresponding to higher agricultural income may be subject to a higher risk of system-failure penalties; while, a too conservative policy may lead to wastage of irrigation supplies.     

Lung function in subjects exposed to crude oil spill into sea water

A Greek oil-tanker ran aground, resulting in a huge oil spill along the costal areas of Karachi, Pakistan. The purpose of this study was to assess the lung function and follow up change after one year in subjects exposed to crude oil spill in sea water. It was a cross sectional study with follow up in 20 apparently healthy, non-smoking, male workers, who were exposed to a crude oil spill environment during oil cleaning operation. The exposed group was matched with 31 apparently healthy male control subjects. Pulmonary function test was performed using an electronic Spirometer. Subjects exposed to polluted air have significant reduction in forced vital capacity (FVC), forced expiratory volume in first second (FEV(1)), forced expiratory flow (FEF(25-75%)) and maximum voluntary ventilation (MVV) compared to their matched controls. This impairment was reversible and lung functions parameters were improved when the subjects were withdrawn from the polluted air environment.     

Stream flow variability and drought severity in the Songhua River Basin,Northeast China

A slight variation in the magnitude of stream flow can have a substantial influence on the development of water resources. The Songhua River Basin (SRB) serves as a major grain commodity basin and is located in the northeastern region of China. Recent studies have identified a gradual decrease in stream flows, which presents a serious risk to water resources of the region. It is therefore necessary to assess the variation in stream flow and to predict the future of stream flows and droughts to make a comprehensive plan for agricultural irrigation. The simulation of monthly stream flows and the investigation of the influence of climate on the stream flow in the SRB were performed by utilizing the Integrated Water Evaluation and Planning (WEAP) tool coupled with observed precipitation data, as well as the Asian Precipitation-Highly-Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE’s Water Resources) precipitation product. The Nash–Sutcliffe coefficient (NSC) was used to assess the WEAP efficiency. During the time of calibration, NSC was obtained as 0.90 and 0.67 using observed and APHRODITE precipitation data, respectively. The results indicate that WEAP can be used effectively in the SRB. The application of the model suggested a maximum decline in stream flow, reaching 24% until the end of 21st century under future climate change scenarios. The drought indices (standardized drought index and percent of normal index) demonstrated that chances of severe to extreme drought events are highest in 2059, 2060 and 2085, while in the remaining time period mild to moderate drought events may occur in the entire study area. The drought duration, severity and intensity for the period of 2011–2099 under all scenarios, [(A1B: 12, ? 1.55, ? 0.12), (A2: 12, ? 1.41, ? 0.09), (max. wetting and warming conditions: 12, ? 1.37, ? 0.11) and (min. wetting and warming conditions: 12, ? 1.69, ? 0.19)], respectively.     

Biodegradation by Co‐inoculated Bacteria and Fungi Alleviates Adverse Effects of Red‐S3B on Growth and Nitrogen Uptake of Wheat

Textile wastewater contains huge quantities of nitrogen (N)‐containing azo‐dyes. Irrigation of crops with such wastewater adds toxic dyes into our healthy soils. One of the ways to prevent their entry to soils could be these waters after the dyes' biodegradation. Therefore, the present study was conducted to evaluate the impact of textile dyes on wheat growth, dye degradation efficiency of bacteria‐fungi consortium, and alleviation of dye toxicity in wheat by treatment with microbial consortium. Among dyes, Red‐S3B (3.19% N) was found to be the most toxic to germination and growth of seven‐day‐old wheat seedlings. Shewanella sp. NIAB‐BM15 and Aspergillus terreus NIAB‐FM10 were found to be efficient degraders of Red‐S3B. Their consortium completely decolorized 500 mg L^?1 Red‐S3B within 4 h. Irrigation with Red‐S3B‐contaminated water after treatment with developed consortium increased root length, shoot length, root biomass, and shoot biomass of 30‐day‐old wheat seedlings by 47, 18, 6, and 25%, respectively, than untreated water. Moreover, irrigation after microbial treatment of dye‐contaminated water resulted in 20 and 51% increase in shoot N content and N uptake, respectively, than untreated water. Thus, co‐inoculation of bacteria and fungi could be a useful bioremediation strategy for the treatment of azo‐dye‐polluted water.     

Mixed Layer Depth and its Variability in the Eastern Equatorial Indian Ocean as Revealed by Observations and Model Simulations

Mixed layer depth (MLD) variability in the Eastern Equatorial Indian Ocean (EEIO) from a hindcast run of an Ocean General Circulation Model (OGCM) forced by daily winds and radiative fluxes from NCEP-NCAR reanalysis from 2004 to 2006 is investigated. Model MLD compares well with the ～20,000 observations from Argo floats and a TRITON buoy (1.5°S and 90°E) in the Indian Ocean. Tests with a one-dimensional upper ocean model were conducted to assess the impact on the MLD simulations that would result from the lack of the diurnal cycle in the forcing applied to the OGCM. The error was of the order of ～12 m. MLD at the TRITON buoy location shows a bimodal pattern with deep MLD during May–June and December–January. MLD pattern during fall 2006 was significantly different from the climatology and was rather shallow during December–January both in the model and observation. An examination of mixed layer heat and salt budget suggested salinity freshening caused by the advective and vertical diffusive mixing to be the cause of shallow MLD.     

Using geographical information systems to assess groundwater contamination from arsenic and related diseases based on survey data in Lahore,Pakistan

The present study was aimed at assessing the groundwater contamination from arsenic (As) and its impact on health from survey data in Lahore, Pakistan. OK (ordinary kriging) technique was used to create As and pH surfaces for samples from 380 groundwater wells at different locations and depths in the study area. Geographic information systems (GIS) was applied to delineate areas for safe, risk, and dangerous zones of As in drinking water from groundwater wells at 640 to 850 ft depths. To analyze effects of high As on public health, GIS-based field surveys were conducted to link health data along location of respondents to As contamination levels in the delineated safe, risk, and dangerous zones. Moreover, various pH levels and their effectiveness were studied to suggest cost-effective As treatment in the study area. Our results show that As contaminated strata varies with depth of groundwater wells, i.e., 44.50% areas comprising safe zone of drinking water from deep wells at 850 ft depth compared to 26% areas of shallow water at 640 ft depth. About 35% area with pH range (7 to 7.5) is marked in the risk and danger zones of As that can be initially targeted for treatment. Surveys confirm that people living in the risk and danger zones have some kind of As-related diseases.     

Mapping soil electric conductivity using Bayesian kriging: A case study from Qasur,Pakistan

Quality of soil data is vital to formulate agricultural policies at different scales. Current agricultural applications in Pakistan depend however, on average values of soil estimates over larger areas. In this work, model-based ordinary kriging (OK) and Bayesian kriging (BK) to interpolate soil data is used. The aim is to compare the two different methods for the accuracy of soil data prediction. For this soils were sampled for Electrical Conductivity (EC, dS m ^–1) at 759 different locations in the rural agricultural areas of Qasur Tehsil, Pakistan. Cross validation was used to compare the performance of OK and BK. Our results show strong skewness and spatial dependency of soil EC values in heterogeneous regions. Box-Cox transformation successfully reduced the level of skewness in the soil EC data (from 14.1 to 0.11). Contrary to OK, under-estimation of soil EC values was not evident in the BK interpolation. Mean square prediction error for BK (1.45) was significantly reduced as compared to that for OK (6.1). Considering these findings, BK is a better model to explain the sub-regional soil EC variability and estimating strategies for sustainable agricultural planning in Pakistan.     

Assessment of characteristics and distinguished hydrological periods of a river regime

This study was carried out to analyze the hydrological characteristics and assess the distinguished hydrological periods of Upper Indus Basin (UIB) Rivers of Pakistan. For this purpose, statistical analysis (variation coefficient, the auto-correlation coefficient, sequential Mann–Kendall’s test) and a proposed method for distinguishing hydrological periods (described in methodology section) were applied. The results revealed that all rivers reflect moderate variability. The results of auto-correlation displayed that the river flow observed at Astore gauging station only indicated independency, while for Gilgit, Hunza and Kachura guaging at Indus River exhibited 2, 2, 4-year lag. The mutation analysis indicated that after 1980, the change point occurred at all UIB rivers. During analysis, it was also observed that river regimes have the same hydrological periods (i.e., 4), but with different dates of occurrence. The Gilgit River showed a low high-flow hydrological period compared to Astore, Hunza and Kachora (Indus). This difference may be due to the river’s own area natural conditions. The current analysis may be helpful for planning and management of water resources, designing of hydraulic structures and to make better policies in response to agricultural water requirement downstream of UIB River.