Proper Management Of Water Resources Research Articles

The Stem Sap Flow and Water Sources for Tamarix ramosissima in an Artificial Shelterbelt With a Deep Groundwater Table in Northwest China.

The shelterbelt forest between oases and the desert plays a vital role in preventing aeolian disasters and desertification in arid regions of northwest China. Tamarix ramosissima (T. ramosissima), a typical perennial and native xerophyte shrub in Northwest China, grows naturally and is widely used in building artificial shelterbelt forests. The balance between water consumption and the availability of water determines the survival and growth of T. ramosissima. How T. ramosissima copes with extremely low rainfall and a deep groundwater table remains unknown. To answer this, the transpiration and the water sources of T. ramosissima were investigated by the heat balance and oxygen isotopic analysis method, respectively. Our results show that the daily T. ramosissima stem sap flow (SSF) was positively correlated with air temperature (Ta), photosynthetically active radiation (PAR), and the vapor pressure deficit (VPD). We found no significant relationship between the daily SSF and soil moisture in shallow (0–40 cm) and middle (40–160 cm) soil layers. Oxygen isotope results showed that T. ramosissima mainly sources (>90%) water from deep soil moisture (160–400 cm) and groundwater (910 cm). Diurnally, T. ramosissima SSF showed a hysteresis response to variations in PAR, Ta, and VPD, which suggests that transpiration suffers increasingly from water stress with increasing PAR, Ta, and VPD. Our results indicate that PAR, Ta, and VPD are the dominant factors that control T. ramosissima SSF, not precipitation and shallow soil moisture. Deep soil water and groundwater are the primary sources for T. ramosissima in this extremely water-limited environment. These results provide information that is essential for proper water resource management during vegetation restoration and ecological reafforestation in water-limited regions.

Impact of future climate change on river discharge and groundwater recharge: a case study of Ho Chi Minh City, Vietnam

Abstract Climate change (CC) is likely to have a long-term influence on regional water resources, including surface water and groundwater. Therefore, quantifying the CC influence is indispensable for proper management of water resources. This study scrutinized the influence of CC on river discharge and groundwater recharge (GWR) in Ho Chi Minh City (HCMC), Vietnam, utilizing the Soil and Water Assessment Tool (SWAT). The calibrated SWAT was utilized to simulate the discharge and GWR under projected climate scenarios in reliance on an ensemble of seven General Circulation Models (GCMs) derived from Coupled Model Intercomparison Project Phase 6 (CMIP6) under three Shared Socioeconomic Pathways (SSPs), including SSP1-2.6, SSP2-4.5, and SSP5-8.5. Results pointed out that the climate of HCMC is warmer and wetter in the 21st century. Under the CC influence, the future discharge is envisaged to rise from 0.1 to 4.5% during the near-future period of 2030s (2021–2045), 8.1 to 11.6% during the mid-future period of 2055s (2046–2070), and 7.7 to 19.6% during the far-future period of 2080s (2071–2095) under the three SSP scenarios. In addition, the GWR is prognosticated to have rising trends of 0.9–4.9%, 5.3–7.9%, and 5.7– 13.5% during the near-future, mid-future, and far-future periods, respectively. Furthermore, uncertainties in the discharge and GWR projections connected with SSP scenarios and CMIP6 GCMs are considerable.

Investigating the changes in agricultural land use and actual evapotranspiration of the Urmia Lake basin based on FAO’s WaPOR database

The Urmia Lake Basin (ULB) is a critical region in terms of water and environment in Iran. The purpose of this study was to investigate the relationship between agricultural land-use changes and the decrease of the Lake Urmia water level, calculating the actual evapotranspiration and interception (ETIa) in agricultural and non-agricultural lands, investigating the trend of temperature changes and its relationship with ETIa, determining the water balance, and estimating net and gross biomass water productivity in the ULB. So, Land Cover Classification (LCC) maps, ETIa and water productivity were prepared from FAO’s WaPOR product (FWP) from 2009 to 2020. Daily precipitation and temperature were collected from 24 meteorological stations in the ULB. To validate FWP land cover classification, 354 control points were collected and the error matrix and Kappa coefficient were used. Then, based on the ETIa and LCC estimated by FWP, the volume of water consumed in irrigated, rainfed, fallow and non-agricultural lands, as well as the water balance of the basin, was calculated. The overall accuracy (OA) and Kappa coefficient for LCC were 86% and 0.81, respectively. The results showed that until 2013, the area of irrigated and rainfed agricultural lands had been increased by 48%, which could be regarded as an influential factor in reducing the water level of Lake Urmia. The average annual precipitation and ETIa of the basin were 15.24 × 109 and 15.91 × 109 m3, respectively. Also, the average annual ETIa of agricultural lands, grasslands and evaporation from the surface of Lake Urmia were 4.88 × 109, 8.18 × 109 and 2.85 × 109 m3, respectively. Therefore, a negative balance of 0.67 × 109 m3 was observed. The results also showed that the average annual temperature had been increased by 1.1 °C from 2009 to 2020. Finally, the rise of the temperature and area of irrigated croplands, the decrease of precipitation and the negative water balance should be considered as warning signals calling for the proper management of water resources.

Implementing Early Warning Systems in WWTP. An investigation with cost-effective LED-VIS spectroscopy-based genetic algorithms

Measuring how the pollution load evolves in real time along sewer networks is key for proper management of water resources and protecting the environment. The technique of molecular spectroscopy for water characterization has increasingly widespread use, as it is a non-invasive technique that leads to the correlation of the physical-chemical conditions of wastewater with spectroscopic surrogates by a series of mathematical estimation models. In the present research work, different symbolic regression models obtained with evolutive genetic algorithms are evaluated for the estimation of chemical oxygen demand (COD); five-day biochemical oxygen demand (BOD5); total suspended solids (TSS); total phosphorus (TP); and total nitrogen (TN), from the spectral response of samples measured between 380 and 700 nm and without the use of chemicals or pre-treatment. Around 650 wastewater samples were used in the campaign, from 43 different wastewater treatment plants (WWTP) in which both, raw/influent and treated/effluent, were examined through 18 models composed of Classical Genetic Algorithm (CGA), the Age-Layered Population Structure (ALPS), and Offspring Selection (OS) by mean of HeuristicLab software, to make a comparison among them and to determine which models and wavelengths are most suitable for the correlation. Models are proposed considering both raw and treated samples together (15) and only with tertiary treated wastewater reclaimed for agriculture irrigation effluent (3). The Pearson correlation coefficients were in the range of 67–91% for the test data in the case of the combined models. The results conform the first steps for a real-time monitoring of WWTP.

Evaluation of food processing with the management of food, water, and energy nexus in Baghdad, Iraq

Efficient use of water and energy is crucial in food processing. One of the major problems in the food processing is the creation of food waste. Reducing food waste is essential to fill the global food gap and help reduce water and energy gaps around the world. Also, efficient use of water and energy in food processing is crucial. Examining scientific sources, it seems that Nexus thinking can be considered as the key to reducing food waste. Proper planning and management of limited water, energy, and food resources to meet society's economic and social needs for sustainable development is always a challenging issue. In this paper, considering the two thermal power plants with coal fuel and natural gas fuel in Baghdad, the relationship between food production, water consumption, energy production, and CO2 emissions has been investigated. Considering three periods (5 years) and estimating demand and forecasting energy and food production, Nexus has been studied between water, food, and energy parameters. During these three periods, the amount of natural gas consumption has increased by 13.13%, 25.7%, and 28.79% compared to the total energy. Also, in the optimal case, the cost of the system is $ 5.65 billion.

Quality assessment of surface water and groundwater giving emphasis on water quality index and irrigational indicators in the southeastern part of Manipur Valley, north‐east India

Water quality index (WQI) and irrigational indices for surface water and groundwater in the southeastern part of Manipur Valley in north‐east India has been examined. The water samples were collected during the pre‐monsoon season in the year 2016. Geologically, the Manipur Valley occurs as an intermontane piedmont‐alluvial plain filled with Quaternary alluvium of fluvio‐lacustrine origin. The basic chemical parameters of pH, total dissolved solids, electrical conductivity, total hardness, Cl−, HCO3−, Na+, Ca2+, Mg2+, Fe, Mn, and Zn were considered for computing water quality index for drinking water. Irrigational indices such as sodium absorption ratio, sodium percentage, Kelly's index, magnesium hazard, and residual sodium carbonate were calculated for determining the suitability for irrigational use. WQI, SAR, %Na+, KI, MH, RSC suggest that majority of the water samples are suitable for drinking and irrigational uses. They exhibit positive relations among them suggesting that these parameters are dependent over one another. About 20% of the piedmont zone groundwater are unsuitable for both drinking and agricultural purposes. The encrustation of gypsum, halite, and evaporite into the Disang shales enhances the dissolution process of ions such as Cl−, Na+, Ca2+, Mg2+ in the piedmont water leading to quality deterioration. Gibb's plots suggest that the chemical origin of water dominates with rock‐weathering process, while hydrochemical facies evolved from the initial stage to intermediate stage. Therefore, proper integrated management and development of water resources is necessary for the effective utilization water resources particularly around the piedmont zone.

Physical\u2013chemical evaluation of groundwater quality in semi-arid areas: case study\u2014Sabzevar plain, Iran

Groundwater is one of the most important water sources in arid and semi-arid areas. With the increasing world population and the water demand for agriculture and urban use, the need for water resources has increased, especially in arid and semi-arid regions, where groundwater resources play a significant role. To prevent the pollution of groundwater resources, various studies for their preservation and maintenance should be carried out, including a detailed plan for proper management of water resources and establishing a balance between water quality and how to use them. It becomes important to understand the spatial change of the quality of groundwater resources. In this study, Sabzevar plain, a typical region of semi-arid climate in Iran, was selected as a case study to assess the groundwater quality of the region, using data from 24 observation wells between 2015 and 2019. Using Arc GIS software, a map of groundwater quality parameters in the study area was prepared for quality assessment and comparison with existing international standards. The results showed that (except pH and HCO3−) the concentration of Sodium, Magnesium, and other anions and cations is higher than the corresponding WHO standard limit, suggesting that the study area is unsuitable for drinking and agricultural use. According to the Wilcox chart, 87.5% of the samples are in the C4S4 class while 8.33% are in the C4S3 class, showing the groundwater unsuitable for agricultural use due to its high salinity and alkalinity. Piper diagrams show that more than 50% of the samples are non-carbonate alkalis, indicating a very high salinity in the area. According to the pie chart, chlorine ion and sodium ion are the dominant anions and cations in the Sabzevar plain, respectively. The Schuler diagram shows that none of the samples examined were in a good class for drinking. Therefore, considering the importance of water for agricultural activities in the study area, it is recommended to have agricultural management solutions to prevent groundwater mixing with freshwater resources.

Is the deep-learning technique a completely alternative for the hydrological model?: A case study on Hyeongsan River Basin, Korea

It is no doubt that the reliable runoff simulation for proper water resources management is essential. In the past, the runoff was generally modeled from hydrologic models that analyze the rainfall-runoff relationship of the basin. However, since techniques have developed rapidly, it has been attempted to apply especially deep-learning technique for hydrological studies as an alternative to the hydrologic model. The objective of the study is to examine whether the deep-learning technique can completely replace the hydrologic model and show how to improve the performance of runoff simulation using deep-learning technique. The runoff in the Hyeongsan River basin, South Korea from 2013 to 2020 were simulated using two models, (1) long short-term memory model that is a deep learning technique widely used in the hydrological study and (2) TANK model, and then we compared the runoff modeling results from both models. The results suggested that it is hard to completely replace the hydrological model with the deep-learning technique due to its simulating behavior and discussed how to improve the reliability of runoff simulation results. Also, a method to improve the efficiency of runoff simulation through a hybrid model which is a combination of two approaches, deep-learning technique and hydrologic model was presented.

Crop pattern optimization in a multi-reservoir system by combining many-objective and social choice methods

Crop pattern determination is an essential step toward proper water resources management in irrigated agricultural development, especially in arid and in semi-arid regions. In this paper, we propose a method for determining short-term optimal crop pattern by developing a suitable model for a four-reservoir system in the Karun basin including Karun 1, 3, and 4, and Gotvand reservoirs in Iran. The model satisfies multiple objectives including hydropower, municipal, industrial, agricultural, and environmental purposes. To achieve this goal, we examined two heuristic many-objective algorithms including SPEA2 and NSGA-III. Many-objective algorithms provide a Pareto front of optimal solutions. However in practice we need to know an exact solution of crop pattern. To overcome this problem, a novel application of social choice (SC) is accomplished. The results indicate the superiority of NSGA-III over SPEA2. Comparison of the results for the minimization objective functions shows that the average values of municipal, agricultural, environmental and hydropower obtained with the NSGA-III algorithm are 0.22, 6.73, 0.49 and 1.72, respectively, whereas in SPEA2 they are 0.72, 9.47, 2.05 and 4.72. This finding also emphasizes the importance of improvements necessary in solution algorithms for complicated water resources problems.

The low hydrologic resilience of Asian Water Tower basins to adverse climatic changes

Climate change has a significant impact on the runoff of basins in cold, dry areas. The quantification of regional ecohydrological responses to climate change such as warming and drought is essential for establishing proper water resource management schemes. We propose a simple and novel method based on the Budyko framework to evaluate the hydrologic resilience of 16 basins that conform the Asian Water Tower in the Tibetan Plateau (TP). Our method defines two metrics within the Budyko domain – tolerance (ψ) and plasticity (φ) – that characterize the hydrologic resilience of a basin. Based on an ecohydrological point of view, a basin is considered hydrologically resilient if ψ and φ are both greater than 1 or its φ is negative and ψ is greater than 1. Our results show that ψ varies between 0.27 and 0.74, with an average value of 0.45 and φ varies between 2 and 16.33, with an average value of 6.90, for 14 out of the 16 basins. Only two basins – Taohe and Datonghe – had negative φ (-11.67 and -8.11, respectively) and ψ greater than 1 (2.26 and 19.58, respectively), suggesting that these two are the only basins with a hydrologic resilience to climatic warming/drying in the TP. Within the non-resilient basins, we found vegetation to play a key role in the level of tolerance and plasticity indicating that basins with a larger vegetation cover display a lower capability to adapt to adverse climatic changes. Following these results, we call for afforestation efforts to be carefully considered in cold, dry areas. The proposed method and conclusions drawn by this study may help predict the hydrologic responses to future adverse climatic conditions.

GOOGLE EARTH ENGINE BASED AGRICULTURAL DROUGHT MONITORING IN KODAVANAR WATERSHED, PART OF AMARAVATHI BASIN, TAMIL NADU, INDIA

Abstract. The agricultural drought assessment and monitoring has become a prime concern in recent times as it impedes land capability and causes food scarcity. Therefore, the present study constructed a methodological framework through the Google Earth Engine (GEE) platform, which offers advanced and effective monitoring in a timely concern of the drought occurrences. The study has been carried out in the Kodavanar watershed, a part of the Amaravathi basin is noted with signs of drought such as insufficient rainfall and vegetation stress in the current situation. The remote sensing indices are utilised for the agriculture drought assessment including Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Temperature Condition Index (TCI), Vegetation Condition Index (VCI) and Vegetation Health Index (VHI). In particular, the VHI results show that the area of healthy vegetation and no drought category is rapidly decreased from 934.29 to 107.83 sq.km across the years and have been reached threatening condition as extreme drought category with extremely low vegetation cover has been increasing in a exponential proportion of over 5% in the year 2019 and 2020. However, the agriculture drought results compared through the meteorological drought indicator of Standardized Precipitation Index (SPI) reflects that the SPI and VHI are reflecting similar signs and indicating the dry condition of precipitation with moderate vegetation over the highlighted regions of northern tip and central eastern portions. This present work illustrates the effective use of the GEE platform in monitoring the agriculture drought and the highlighted portions of the study should be implemented with proper water resource management by the researchers, planners and policymakers in the Kodavanar watershed for reducing the vegetation stress.

Potential Climate Change Impacts on Water Resources in Egypt

This paper presents a comprehensive study to assess the impact of climate change on Egypt’s water resources, focusing on irrigation water for agricultural crops, considering that the agriculture sector is the largest consumer of water in Egypt. The study aims to estimate future climate conditions using general circulation models (GCMs), to assess the impact of climate change and temperature increase on water demands for irrigation using the CROPWAT 8 model, and to determine the suitable irrigation type to adapt with future climate change. A case study was selected in the Middle part of Egypt. The study area includes Giza, Bani-Sweif, Al-Fayoum, and Minya governorates. The irrigation water requirements for major crops under current weather conditions and future climatic changes were estimated. Under the conditions of the four selected models CCSM-30, GFDLCM20, GFDLCM21, and GISS-EH, as well as the chosen scenario of A1BAIM, climate model (MAGICC/ScenGen) was applied in 2050 and 2100 to estimate the potential rise in the annual mean temperature in Middle Egypt. The results of the MAGICC/SceGen model indicated that the potential rise in temperature in the study area will be 2.12 °C in 2050, and 3.96 °C in 2100. The percentage of increase in irrigation water demands for winter crops under study ranged from 6.1 to 7.3% in 2050, and from 11.7 to 13.2% in 2100. At the same time, the increase in irrigation water demands for summer crops ranged from 4.9 to 5.8% in 2050, and from 9.3 to 10.9% in 2100. For Nili crops, the increase ranged from 5.0 to 5.1% in 2050, and from 9.6 to 9.9% in 2100. The increase in water demands due to climate change will affect the water security in Egypt, as the available water resources are limited, and population growth is another challenge which requires a proper management of water resources.

Evaluating the groundwater quality of Damodar Fan Delta (India) using fuzzy-AHP MCDM technique

In recent years, groundwater pollution has become increasingly a serious environmental problem throughout the world due to increasing dependency on it for various purposes. The Damodar Fan Delta is one of the agriculture-dominated areas in West Bengal especially for rice cultivation and it has a serious constraint regarding groundwater quantity and quality. The present study aims to evaluate the groundwater quality parameters and spatial variation of groundwater quality index (GWQI) for 2019 using the fuzzy analytic hierarchy process (FAHP) method. The 12 water quality parameters such as pH, TDS, iron (Fe−) and fluoride (F−), major anions (SO42−, Cl−, NO3−, and HCO3−), and cations (Na+, Ca2+, Mg2+, and K+) for the 29 sample wells of the study area were used for constructing the GWQI. This study used the FAHP method to define the weights of the different parameters for the GWQI. The results reveal that the bicarbonate content of 51% of sample wells exceeds the acceptable limit of drinking water, which is maximum in the study area. Furthermore, higher concentrations of TDS, pH, fluoride, chloride, calcium, magnesium, and sodium are found in few locations while nitrate and sulfate contents of all sample wells fall under the acceptable limits. The result shows that 13.79% of the samples are excellent, 68.97% of the samples are very good, 13.79% of the samples are poor, and 3.45% of the samples are very poor for drinking purposes. Moreover, it is observed that very poor quality water samples are located in the eastern part and the poor water wells are located in the northwestern and eastern part while excellent water quality wells are located in the western and central part of the study area. The understanding of the groundwater quality can help the policymakers for the proper management of water resources in the study area.

Groundwater vulnerability assessment using water quality index (WQI) under geographic information system (GIS) framework in parts of Uttar Pradesh, India

Groundwater resources are affected in principle by three major activities. First is excessive use of fertilizers and pesticides in agricultural areas. The second is untreated/partially treated wastewater to the soil/water and the third one is excessive pumping and improper management of aquifers. Due to large-scale urban growth which has triggered domestic effluents and on the other hand industrial development activities has resulted in the generation of a copious volume of industrial effluents directly and indirectly contaminate the groundwater. In a drinking water quality assessment, the decision-making based on water quality data is a crucial issue because several parameters compromise its quality. There has been considerable advancement in the field of water quality assessment particularly based on the principle of the water quality index (WQI) using modified concepts. The study area which includes part of Varanasi and Sant Ravidas Nagar districts are centers for urban growth along with industrial setup in Uttar Pradesh, India. Water quality index (WQI) is an index reflecting the composite influence of different water quality parameters which is considered for calculation. 50 numbers of groundwater samples were collected from various locations in the study area as per the standard protocol prescribed by the American Public Health Association (APHA). Twenty-two water quality parameters have been considered for the calculation of water quality index viz. pH, electrical conductivity (EC), total hardness (TH), total dissolved solids (TDS), alkalinity, sodium (Na+), potassium (K+), calcium (Ca2+), magnesium (Mg2+), nitrates (NO3−), bicarbonate (HCO3−), chlorides (Cl−), sulphates (SO4−), fluorides (F−), chromium (Cr), zinc (Zn), copper (Cu), manganese (Mn), iron (Fe), nickel (Ni), lead (Pb) and cadmium (Cd). The Bureau of Indian Standard has been considered to assess the suitability of groundwater for drinking purposes and the calculation of the water quality index (WQI). Correlation study among various physicochemical properties also reflects certain significant negative relationships. The current study shows that 50% of the collected water samples are non-suitable for the drinking water category and the rest is falling under the good, moderate, poor, very poor as per the Water Quality Index (WQI) classification. The present study is quite helpful for the proper planning and management of available water resources for drinking purposes.

Land-Use and Land-Cover (LULC) Change Detection and the Implications for Coastal Water Resource Management in the Wami–Ruvu Basin, Tanzania

Evaluation of river basins requires land-use and land-cover (LULC) change detection to determine hydrological and ecological conditions for sustainable use of their resources. This study assessed LULC changes over 28 years (1990–2018) in the Wami–Ruvu Basin, located in Tanzania, Africa. Six pairs of images acquired using Landsat 5 TM and 8 OLI sensors in 1990 and 2018, respectively, were mosaicked into a single composite image of the basin. A supervised classification using the Neural Network classifier and training data was used to create LULC maps for 1990 and 2018, and targeted the following eight classes of agriculture, forest, grassland, bushland, built-up, bare soil, water, and wetland. The results show that over the past three decades, water and wetland areas have decreased by 0.3%, forest areas by 15.4%, and grassland by 6.7%, while agricultural, bushland, bare soil, and the built-up areas have increased by 11.6%, 8.2%, 1.6%, and 0.8%, respectively. LULC transformations were assessed with water discharge, precipitation, and temperature, and the population from 1990 to 2018. The results revealed decreases in precipitation, water discharge by 4130 m3, temperature rise by 1 °C, and an increase in population from 5.4 to 10 million. For proper management of water-resources, we propose three strategies for water-use efficiency-techniques, a review legal frameworks, and time-based LULC monitoring. This study provides a reference for water resources sustainability for other countries with basins threatened by LULC changes.

Mapping Fluctuations of Hispar Glacier, Karakoram, using Normalized Difference Snow Index (NDSI) and Normalized Difference Principal Component Snow Index (NDSPCSI)

Investigation of the fluctuations in the snow-covered area of the major glaciers of the Karakoram range is essential for proper water resource management in Pakistan, since its glaciers are responding differently to the rising temperatures. The objective of this paper is to map snow covered area of Hispar glacier in Hunza river basin for the years 1990, 2010 and 2018. Two techniques, (NDPCSI) Normalized Difference Principal Component Snow Index and (NDSI) Normalized Difference Snow Index were used. Hispar glacier of the Hunza basin has lost 114 km2 of its ice cover area, during the last 28 years, with an alarming annual retreat rate of 1.67 km2 of glacier ice from 1990 to 2018. Hunza basin experienced a +1°C rise in both mean minimum and mean maximum temperature during 2007 to 2018.as a result, Karakorum ice reserves have been affected by rising temperature of the region. Due to temperature rise, retreat of snowcovered area of Hispar, Karakoram mountain range shows a shift in the cryospheric hazard zone.

Groundwater vulnerability assessment using GIS-based DRASTIC model in Nangasai River Basin, India with special emphasis on agricultural contamination

Nangasai basin is a semi-arid watershed where agriculture is the main source of economy. In present day, increasing population demands increase in food productivity which leads to increase use of fertilizers and chemical pesticides in agriculture. These fertilizers on the other hand mix up with the groundwater and increase the pollution, which affects human health adversely. So, for controlling the groundwater contamination risk proper water resource management and assessment of groundwater vulnerability is extremely important. Total 7 hydrogeological parameters have been considered for this study, and the final groundwater vulnerability map has been prepared by overlay weighted method with the help of DRASTIC index, which is classified into 5 vulnerable classes (very high, high, moderate, low, and very low). In the south and south-eastern regions of the basin namely Deghi, Bankada, Baram, Macha, Katin, Tilabani high groundwater contamination is been observed. For validating the model, the water quality parameters-nitrate and TDS have been used with the accuracy of 89% and 86% respectively. Using effective as well as scientifically approved methods, the anthropogenic and agricultural contamination can be controlled and managed which will lower the risk of contamination. This map can be further utilized as a base map for management of groundwater pollution and its planning.

Estimation of Crop Water Requirement using CROPWAT Model for Maize, A Case Study of Raya Azebo District, Ethiopia

Water is the major limiting factor for crop production. A lot of water resources have been exploited for irrigation purpose. Irrigation systems essential to enhance crop productivity in order to meet future food demand and ensure food security. Unscientific and injudicious application of groundwater in this district resulted in depletion of the groundwater table. To achieve effective utilization of the groundwater resources, there is a need to estimate the crop water requirement for different crops at different management levels to accomplish effective irrigation management. Crop water requirements of maize crop in Raya Azebo districts was calculated using FAO Cropwat 8.0 a computer simulation model. The simulation study was conducted with the objectives of determining irrigation water requirement maize. The study was carried out to estimate the crop water requirement of maize by using the climatic data, crop evapotranspiration (ETc) and reference crop evapotranspiration (ETo) for each crop were determined using CROPWAT 8.0. The study shows that crop water requirement of maize with a growing period of 125 days to maturity requires 504.0 mm depth of water on off season and 457.8 mm on main season respectively. The result shows that in off season the crop water requirement of maize was needed more water than the main season, due to the climatic condition and in the main season the effective rainfall is more available than the off season. This study proved that the CROPWAT model is useful for calculating the crop irrigation needs for the proper management of water resources. Keywords: CROPWAT, Model, Crop water requirement, Maize, Eto DOI: 10.7176/JRDM/74-03 Publication date: March 31 st 2021

A detailed assessment of meteorological drought characteristics using simplified rainfall index over Narmada River Basin, India

Drought is amongst the most precarious phenomena that cause serious repercussions, especially over the agriculture-dominated regions. A detailed assessment of droughts is necessary to develop robust frameworks for combating its ill effects. This study presents an analysis of meteorological drought characteristics (frequency, severity and persistence) using precipitation data of twenty-four districts for 1954–2013 over the Narmada River Basin, which is located in the core of the Indian Monsoon region and has great agricultural importance. Further, the entire duration is divided into two epochs, i.e. 1954–83 and 1984–2013, for comparative analysis. A simplified rainfall index (RIS) is proposed, which is based on the concept of percentage deviation from normal monsoon rainfall along with the uniform transition from moderate to severe and severe to extreme droughts. The basin is found to be prone to droughts and the drought frequency varied from once in three to 8 years over different districts. The droughts are more frequent and severe in the western portions of the basin as compared to the eastern portions. The majority of the districts have undergone droughts persisting for 3 years at least once. The epoch-wise analysis reveals a significantly higher frequency, severity and persistence of droughts in the recent epoch. The results of trend analysis using the Modified Mann–Kendall test indicate an increasing trend of droughts over twenty-one districts and significantly increasing over eleven districts. The information reported in this study will be helpful for proper planning and management of water resources over the basin and hence, reduce the pernicious effects of droughts.

Temporal Analysis for Detection of Anomalies in Precipitation Patterns over a Selected Area in the Indus Basin of Pakistan

For efficient adaptation strategies, investigation of the variability in climatic data and its impact on meteorological drought is critical, particularly in semi-arid and arid regions. Innovative trend analysis (ITA), Mann–Kendall (MK) and Sen’s slope estimator (SSE) tests were employed to analyze the variations in precipitation (1981–2018) on annual, seasonal and monthly scale across 12 meteorological stations over the selected areas of the lower Indus basin (LIB) of Pakistan. The reliability of the ITA method was also compared and analyzed with both MK and SSE methods for 48 seasonal precipitation times series. Annual precipitation results indicated a significant increasing trend, i.e., 2.09 mm/year, at only one station (Rahim Yar Khan (RYK)-Khanpur), with MK test statistic Zmk = 2.09 and Sen’s slope estimator β = 2.56. On a monthly scale, the maximum number of positive significant trends were noted during June, with Zmk values of 2.01 to 3.24 and β values of 1.06–3.06, while the maximum number of negative trends was found during January, February, November and December. On a seasonal scale, ITA methods showed significant increasing trends during the summer at 12 selected meteorological stations, with trend indicator (B) values ranging from 0.22 to 2.46. Moreover, performance of the ITA method was found to be consistent with both MK and SSE test results at a verified significance level. The results of the study can help to increase our understanding of the annual, seasonal and monthly precipitation variability in the LIB that may be helpful in developing strategies for the proper management of water resources over the area.